![Emiliano Spezi FInstP CSci PhD FIPEM CPhys](https://profiles-cardiff.imgix.net/attachments/4441?w=200&h=200&auto=format&crop=faces&fit=crop&q=90")
Professor Emiliano Spezi
(he/him)
FInstP CSci PhD FIPEM CPhys
Professor in Medical Engineering
- Available for postgraduate supervision
Overview
Founding Member, Medical Engineering Research Group
Team Leader, Life Imaging and Data Analytics Research Team
Chair, School of Engineering Research Ethics Committe
Associate Editor, European Journal of Medical Physics
Founding Member and Past Chair, Task Group No. 363 - Guidelines for harmonizing the validation of tumor PET auto-segmentation algorithms
Emiliano Spezi PhD, is Professor in Medical Engineering at Cardiff University School of Engineering. He is Chair of the School Research Ethics Committee and Leader of the Life Imaging and Data Analytics team. He is the past Director of Research of the School and past Academic Group Leader of the Medical Engineering Research Group. He is a state registered Clinical Scientist with 15 years working experience in Research and Development in the National Health Service (NHS), where he now holds honorary position with Velindre University NHS Trust and Velindre Cancer Centre. His current research interests centre on three main areas: (1) Quantitative Imaging Biomarkers and Radiomics, (2) Image Guidance for Precision Medicine, (3) Modelling in Radiation Oncology.
Examples of application of the research generated in Professor Spezi’s laboratory include: (1) use of advanced image segmentation methods in the PEARL radiotherapy trial as featured in BBC News, (2) innovative use of AI with Intel Corporation to improve accuracy and efficiency of radiotherapy treatments (MedWales Lifestories Magazine, pp. 26), (3) development of federated learning methods to aid cancer research.
Featured activity
Image Biomarker Standardisation Initiative (IBSI)
A second landmark paper from the IBSI https://theibsi.github.io on standardizing convolutional filters for reproducible radiomics is now published in the Radiological Society of North America (RSNA) Radiolgy journal https://pubs.rsna.org/doi/10.1148/radiol.231319.
This is another milestone in the standardisation, reproducibility and usability of quantitative imaging biomarkers and I am particularly proud of the contribution of my SPAARC team (https://spaarc-radiomics.io) at Cardiff University School of Engineering to this particular work.
Also note the accompanying Radiology editorial from Merel Huisman & Tugba Akinci D’Antonoli explaining why this work matters and Cardiff University newsletter describing this work to a lay audience.
Interdisciplinary Precision Oncology Cardiff Hub (IPOCH)
We run the IPOCH Interdisciplinary Hub in Precision Oncology funded by the Engineering and Physical Sciences Research Council (EPSRC). The projects, covering Biomedical Imaging, Pathology and Genomics, are delivered by our fantastic students across the Schools of Engineering, Computer Science and Medicine.
Find out more on the IPOCH research website.
Publication
2024
- Duman, A., Sun, X., Thomas, S., Powell, J. R. and Spezi, E. 2024. Reproducible and interpretable machine learning-based radiomic analysis for overall survival prediction in glioblastoma multiforme. Cancers 16(19), article number: 3351. (10.3390/cancers16193351)
- Smith, R. L. et al. 2024. From radiomics to deep learning: Leveraging gramian matrix features in CNNs for NSCLC survival analysis. Presented at: 2024 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detector Conference, Tampa, FL, USA, 26 October - 2 November 20242024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD). IEEE pp. 1-2., (10.1109/nss/mic/rtsd57108.2024.10657697)
- Grassi, E. et al. 2024. Patient-specific dosimetry evaluations in Theranostics software for internal radiotherapy. Applied Sciences 14(16), article number: 7345. (10.3390/app14167345)
- Della Corte, A. et al. 2024. Preoperative MRI radiomic analysis for predicting local tumor progression in colorectal liver metastases before microwave ablation. International Journal of Hyperthermia 41(1), article number: 2349059. (10.1080/02656736.2024.2349059)
- Spezi, E. and Bray, M. eds. 2024. Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press. (10.18573/conf1)
- Spezi, E. and Bray, M. 2024. Foreword. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press, (10.18573/conf1.a)
- Duman, A., Powell, J., Thomas, S., Sun, X. and Spezi, E. 2024. Generalizability of deep learning models on brain tumour segmentation. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 3-5., (10.18573/conf1.b)
- Cagni, E., Trojani, V., Botti, A., Lewis, A. and Spezi, E. 2024. A tool for radiotherapy plan evaluation analysis: generalise Uniform Ideal Dose (gUIDE). Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 6-10., (10.18573/conf1.c)
- Doherty, C., Duman, A., Chuter, R., Hutton, M. and Spezi, E. 2024. Investigating the feasibility of MRI auto-segmentation for Image Guided Brachytherapy. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 11-14., (10.18573/conf1.d)
- Duman, A., Powell, J., Thomas, S. and Spezi, E. 2024. Evaluation of radiomic analysis over the comparison of machine learning approach and radiomic risk score on glioblastoma. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 19-22., (10.18573/conf1.f)
- Foster, I., Spezi, E. and Wheeler, P. 2024. Inter-planner variability in expert driven Pareto-guided automated planning solutions. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 23-26., (10.18573/conf1.g)
- Wheeler, P. A. et al. 2024. Multi-institutional evaluation of a Pareto navigation guided automated radiotherapy planning solution for prostate cancer. Radiation Oncology 19, article number: 45. (10.1186/s13014-024-02404-x)
- Whybra, P. et al. 2024. The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights. Radiology 310(2) (10.1148/radiol.231319)
- Lou, J. et al. 2024. Predicting radiologists' gaze with computational saliency models in mammogram reading. IEEE Transactions on Multimedia 26, pp. 256-269. (10.1109/TMM.2023.3263553)
2023
- Duman, A., Karakuş, O., Sun, X., Thomas, S., Powell, J. and Spezi, E. 2023. RFS+: A clinically adaptable and computationally efficient strategy for enhanced brain tumor segmentation. Cancers 15(23), article number: 5620. (10.3390/cancers15235620)
- Welgemoed, C., Spezi, E., Riddle, P., Gooding, M. J., Gujral, D., McLauchlan, R. and Aboagye, E. O. 2023. Clinical evaluation of atlas-based auto-segmentation in breast and nodal radiotherapy. British Journal of Radiology 96(1149), article number: 20230040. (10.1259/bjr.20230040)
- Whybra, P. and Spezi, E. 2023. Sensitivity of standardised radiomics algorithms to mask generation across different software platforms. Scientific Reports 13, article number: 14419. (10.1038/s41598-023-41475-w)
- Mukherjee, S. et al. 2023. Efficacy of early PET-CT directed switch to carboplatin and paclitaxel based definitive chemoradiotherapy in patients with oesophageal cancer who have a poor early response to induction cisplatin and capecitabine in the UK: a multi-centre randomised controlled phase II trial. EClinicalMedicine 61, article number: 102059. (10.1016/j.eclinm.2023.102059)
- Loi, S. et al. 2023. Limited impact of discretization/interpolation parameters on the predictive power of CT radiomic features in a surgical cohort of pancreatic cancer patients. La Radiologia Medica 128(7), pp. 799–807. (10.1007/s11547-023-01649-y)
- Mori, M. et al. 2023. External validation of an 18F-FDG-PET radiomic model predicting survival after radiotherapy for oropharyngeal cancer. European Journal of Nuclear Medicine and Molecular Imaging 50, pp. 1329-1336. (10.1007/s00259-022-06098-9)
- Lacan, F., Johnston, R., Carrington, R., Spezi, E. and Theobald, P. 2023. Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms. Journal of Medical Engineering & Technology 47, pp. 189-196. (10.1080/03091902.2023.2193267)
- Foster, I., Spezi, E. and Wheeler, P. 2023. Evaluating the use of machine learning to predict expert-driven pareto-navigated calibrations for personalised automated radiotherapy planning. Applied Sciences 13(7), article number: 4548. (10.3390/app13074548)
- Alsyed, E., Smith, R., Bartley, L., Marshall, C. and Spezi, E. 2023. A heterogeneous phantom study for investigating the stability of PET images radiomic features with varying reconstruction settings. Frontiers in Nuclear Medicine 3 (10.3389/fnume.2023.1078536)
2022
- Cagni, E. et al. 2022. Evaluating the quality of patient-specific deformable image registration in adaptive radiotherapy using a digitally enhanced head and neck phantom. Applied Sciences 12(19), article number: 9493. (10.3390/app12199493)
- Theophanous, S. et al. 2022. Development and validation of prognostic models for anal cancer outcomes using distributed learning: protocol for the international multi-centre atomCAT2 study. Diagnostic and Prognostic Research 6(1), article number: 14. (10.1186/s41512-022-00128-8)
2021
- Parkinson, C., Matthams, C., Foley, K. and Spezi, E. 2021. Artificial intelligence in radiation oncology: A review of its current status and potential application for the radiotherapy workforce. Radiography 27, pp. S63-S68. (10.1016/j.radi.2021.07.012)
- Palumbo, D. et al. 2021. Prediction of early distant recurrence in upfront resectable pancreatic adenocarcinoma: A multidisciplinary, machine learning-based approach. Cancers 13(19), article number: 4938. (10.3390/cancers13194938)
- Alsyed, E., Smith, R., Paisey, S., Marshall, C. and Spezi, E. 2021. A self organizing map for exploratory analysis of PET radiomic features. Presented at: 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Boston, MA, USA, 31 October -7 November 20202020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, (10.1109/NSS/MIC42677.2020.9507846)
- Piazzese, C., Evans, E., Thomas, B., Staffurth, J., Gwynne, S. and Spezi, E. 2021. FIELDRT: an open-source platform for the assessment of target volume delineation in radiation therapy. British Journal of Radiology 94(1126), article number: 20210356. (10.1259/bjr.20210356)
- Cagni, E., Botti, A., Chendi, A., Iori, M. and Spezi, E. 2021. Use of knowledge based DVH predictions to enhance automated re-planning strategies in head and neck adaptive radiotherapy. Physics in Medicine and Biology 66(13), article number: 135004. (10.1088/1361-6560/ac08b0)
- Shi, Z. et al. 2021. Prediction of lymph node metastases using pre-treatment PET radiomics of the primary tumour in esophageal adenocarcinoma: an external validation study. British Journal of Radiology 94(1118), article number: 20201042. (10.1259/bjr.20201042)
- Cagni, E. et al. 2021. Variations in head and neck treatment plan quality assessment among radiation oncologists and medical physicists in a single radiotherapy department. Frontiers in Oncology - Radiation Oncology 11, article number: 706034. (10.3389/fonc.2021.706034)
2020
- Mori, M. et al. 2020. Training and validation of a robust PET radiomic-based index to predict distant-relapse-free-survival after radio-chemotherapy for locally advanced pancreatic cancer. Radiotherapy and Oncology 153, pp. 258-264. (10.1016/j.radonc.2020.07.003)
- Kazmierska, J. et al. 2020. From multisource data to clinical decision aids in radiation oncology: the need for a clinical data science community. Radiotherapy and Oncology 153, pp. 43-54. (10.1016/j.radonc.2020.09.054)
- Spezi, E. et al. 2020. Metabolic tumour volume segmentation for oesophageal cancer on hybrid PET/CT using convolutional network architecture. Presented at: 33rd Annual European Association of Nuclear Medicine Congress (EANM 2020), Virtual, 22-30 October 2020European Journal of Nuclear Medicine and Molecular Imaging, Vol. 47. Vol. S1. Springer Verlag (Germany) pp. 5481-5482., (10.1007/s00259-020-04988-4)
- Zwanenburg, A. et al. 2020. The Image Biomarker Standardization Initiative: standardized quantitative radiomics for high throughput image-based phenotyping. Radiology 295(2), pp. 328-338. (10.1148/radiol.2020191145)
- Deist, T. M. et al. 2020. Distributed learning on 20 000+ lung cancer patients - The Personal Health Train. Radiotherapy and Oncology 144, pp. 189-200. (10.1016/j.radonc.2019.11.019)
- Finocchiaro, D. et al. 2020. Comparison of different calculation techniques for absorbed dose assessment in patient specific peptide receptor radionuclide therapy. PLoS ONE 15(8), article number: e0236466. (10.1371/journal.pone.0236466)
- Parkinson, C. et al. 2020. Qualitative assessment of oesophageal cancer metabolic tumour volumes delineated by an artificial intelligence algorithm. Presented at: NCRI Virtual Showcase 2020, Virtual, 2-3 November 2020.
2019
- Wheeler, P. A. et al. 2019. Evaluating the application of Pareto navigation guided automated radiotherapy treatment planning to prostate cancer. Radiotherapy and Oncology 141, pp. 220-226. (10.1016/j.radonc.2019.08.001)
- Shi, Z. et al. 2019. External validation of radiation-induced dyspnea models on esophageal cancer radiotherapy patients. Frontiers in Oncology 9, article number: 1411. (10.3389/fonc.2019.01411)
- Piazzese, C., Foley, K., Whybra, P., Hurt, C., Crosby, T. and Spezi, E. 2019. Discovery of stable and prognostic CT-based radiomic features independent of contrast administration and dimensionality in oesophageal cancer. PLoS ONE 14(11), article number: e0225550. (10.1371/journal.pone.0225550)
- Alsyed, E., Smith, R., Marshall, C., Paisey, S. and Spezi, E. 2019. The statistical influence of imaging time and segmentation volume on PET radiomic features: A preclinical study. Presented at: 2019 IEEE NSS-MIC, 26 October - 2 November 20192019 IEEE NSS-MIC. IEEE
- Alsyed, E., Smith, R., Marshall, C., Paisey, S. and Spezi, E. 2019. Stability of PET radiomic features: A preclinical study [Abstract]. Presented at: Annual Congress of the European Association of Nuclear Medicine, Barcelona, Spain, 12-16 Oct 2019.
- Hargreaves, S., Johnstone, E., Parkinson, C., Rackley, T., Spezi, E., Staffurth, J. and Evans, M. 2019. Interim 18F-FDG positron emission tomography/computed tomography during chemoradiotherapy in the management of cancer patients: a response [Letter]. Clinical Oncology 31(9), pp. 669-670. (10.1016/j.clon.2019.05.005)
- Whybra, P., Parkinson, C., Foley, K., Staffurth, J. and Spezi, E. 2019. Assessing radiomic feature robustness to interpolation in 18F-FDG PET imaging. Scientific Reports 9(1), article number: 9649. (10.1038/s41598-019-46030-0)
- Tsang, Y., Hoskin, P., Spezi, E., Landau, D., Lester, J., Miles, E. and Conibear, J. 2019. Assessment of contour variability in target volumes and organs at risk in lung cancer radiotherapy. Technical Innovations and Patient Support in Radiation Oncology 10, pp. 8-12. (10.1016/j.tipsro.2019.05.001)
- Foley, K., Christian, A., Peaker, J., Marshall, C., Spezi, E., Kynaston, H. and Roberts, S. A. 2019. Cyclo-oxygenase-2 expression is associated with mean standardised uptake value on 18F-fluorodeoxyglucose positron emission tomography in oesophageal adenocarcinoma. British Journal of Radiology 92(1099), article number: 20180668. (10.1259/bjr.20180668)
- Parkinson, C. et al. 2019. Machine-learned target volume delineation of 18F-FDG PET images after one cycle of induction chemotherapy. Physica Medica, European Journal of Medical Physics 61, pp. 85-93. (10.1016/j.ejmp.2019.04.020)
- Foley, K. G. et al. 2019. External validation of a prognostic model incorporating quantitative PET image features in esophageal cancer. Radiotherapy and Oncology 133, pp. 205-212. (10.1016/j.radonc.2018.10.033)
- Wheeler, P. A. et al. 2019. Utilisation of Pareto navigation techniques to calibrate a fully automated radiotherapy treatment planning solution. Physics and Imaging in Radiation Oncology 10, pp. 41-48. (10.1016/j.phro.2019.04.005)
- Evans, E., Piazzese, C., Spezi, E., Staffurth, J. and Gwynne, S. 2019. EP-1666 ARENA: Improving training in target volume delineation for radiotherapy. Radiotherapy and Oncology 133(S1), pp. S896-S897. (10.1016/S0167-8140(19)32086-9)
- Md Radzi, Y., Windle, R., Lewis, D. and Spezi, E. 2019. EP-1744 Enhancing the accuracy in VMAT dose verification by the use of EPID-based commercial software. Radiotherapy and Oncology 133(S1), pp. S940-S491. (10.1016/S0167-8140(19)32164-4)
- Cagni, E. et al. 2019. EP-2010 A QA method for evaluation of deformable image registration in head and neck adaptive radiotherapy. Radiotherapy and Oncology 133, pp. S1101. (10.1016/S0167-8140(19)32430-2)
- Md Radzi, Y., Windle, R., Lewis, D. and Spezi, E. 2019. EP-1748 Adaptive solution for an improved treatment verification using Dosimetry Check system. Radiotherapy and Oncology 133(S1), pp. S942-S943. (10.1016/S0167-8140(19)32168-1)
- Wheeler, P. et al. 2019. OC-0183 Multi-institutional evaluation of a Pareto navigation guided automated planning solution. Radiotherapy and Oncology 133(S1), pp. S92. (10.1016/S0167-8140(19)30603-6)
- Deist, T. et al. 2019. OC-0544 Distributed learning on 20 000+ lung cancer patients. Radiotherapy and Oncology 133(S1), pp. S287-S288. (10.1016/S0167-8140(19)30964-8)
- Piazzese, C., Whybra, P., Qasem, E., Harris, D., Gtaes, R., Foley, K. and Spezi, E. 2019. EP-1926 Radiomics in rectal cancer: prognostic significance of 3D features extracted from diagnostic MRI. Radiotherapy and Oncology 133(S1), pp. S1048. (10.1016/S0167-8140(19)32346-1)
- Piazzese, C., Whybra, P., Carrington, R., Crosby, T., Staffurth, J., Foley, K. and Spezi, E. 2019. PO-0964 Stability and prognostic significance of CT radiomic features from oesophageal cancer patients. Radiotherapy and Oncology 133(S1), pp. S524-S525. (10.1016/S0167-8140(19)31384-2)
- Whybra, P., Parkinson, C., Foley, K., Staffurth, J. and Spezi, E. 2019. PO-0963 A novel normalisation technique for voxel size dependent radiomic features in oesophageal cancer. Radiotherapy and Oncology 133(S1), pp. S523-S524. (10.1016/S0167-8140(19)31383-0)
- Cagni, E., Botti, A., Orlandi, M., Sghedoni, R., Spezi, E. and Iori, M. 2019. PO-0996 A knowledge-based tool to estimate the gain of re-planning strategy for Head and Neck (HN) ART. Radiotherapy and Oncology 133(S1), pp. S548-S549. (10.1016/S0167-8140(19)31416-1)
- Piazzese, C., Whybra, P., Qasem, E., Harris, D., Gtaes, R., Foley, K. and Spezi, E. 2019. Radiomics in rectal cancer: prognostic significance of 3D features extracted from diagnostic MRI [Abstract]. Radiotherapy and Oncology 133, pp. S1048-S1048. (10.1016/S0167-8140(19)32346-1)
- Whybra, P., Parkinson, C., Foley, K., Staffurth, J. and Spezi, E. 2019. A novel normalisation technique for voxel size dependent radiomic features in oesophageal cancer [Abstract]. Radiotherapy and Oncology 133, pp. S523-S524. (10.1016/S0167-8140(19)31383-0)
- Ackerley, I. et al. 2019. Using deep learning to detect esophageal lesions in PET-CT scans. Presented at: SPIE Medical Imaging 2019, San Diego, California, USA, 16-21 February 2019 Presented at Gimi, B. and Krol, A. eds.Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging. SPIE, (10.1117/12.2511738)
- Finocchiaro, D. et al. 2019. Partial volume effect of SPECT images in PRRT with 177Lu labelled somatostatin analogues: A practical solution. Physica Medica 57, pp. 153-159. (10.1016/j.ejmp.2018.12.029)
2018
- Parkinson, C. et al. 2018. Dependency of patient risk stratification on PET target volume definition in oesophageal cancer. Presented at: ESTRO, Barcelona, Spain, 20-24 April 2018.
- Apte, A. P. et al. 2018. Technical note: Extension of CERR for computational radiomics: a comprehensive MATLAB platform for reproducible radiomics research. Medical Physics 45(8), pp. 3713-3720. (10.1002/mp.13046)
- Parkinson, C., Whybra, P., Staffurth, J., Marshall, C. and Spezi, E. 2018. ATLAAS - Investigation into the incorporation of morphological data on automated segmentation. Presented at: EANM Congress 2018: European Association of Nuclear Medicine., Dusseldorf, Germany, 12-18 October 2018.
- Portakal, Z., Shermer, S., Jenkins, C., Spezi, E., Perrett, T., Tuncel, N. and Phillips, J. 2018. Design and characterization of tissue-mimicking gel phantoms for diffusion kurtosis imaging. Medical Physics 45(6), pp. 2476-2485. (10.1002/mp.12907)
- Parkinson, C. et al. 2018. Target volume delineation of FDG PET images post one cycle of induction chemotherapy in oropharyngeal cancer using advanced automated segmentation methods. Presented at: ESTRO 37, Barcelona, 20-24 April 2018.
- Parkinson, C. et al. 2018. Evaluation of prognostic models developed using standardised image features from different PET automated segmentation methods. EJNMMI Research 8, article number: 29. (10.1186/s13550-018-0379-3)
- Whybra, P., Foley, K., Parkinson, C., Staffurth, J. and Spezi, E. 2018. Effect of interpolation on 3D texture analysis of PET imaging in oesophageal cancer. Radiotherapy and Oncology 127(S1), pp. S1164-S1165. (10.1016/S0167-8140(18)32426-5)
- Parkinson, C. et al. 2018. Target volume delineation of PET post one cycle of induction chemotherapy in oropharyngeal cancer. Radiotherapy and Oncology 127(S1), pp. S634-S635., article number: EP-1126. (10.1016/S0167-8140(18)31436-1)
- Parkinson, C. et al. 2018. Dependency of patient risk stratification on PET target volume definition in Oesophageal cancer. Radiotherapy and Oncology 127(S1), pp. S503-S504. (10.1016/S0167-8140(18)31241-6)
- Piazzese, C., Whybra, P., Carrington, R., Crosby, T., Staffurth, J., Foley, K. and Spezi, E. 2018. Evaluation of 2D and 3D radiomics features extracted from CT images of oesophageal cancer patients. Radiotherapy and Oncology 127, pp. S1180-S1181. (10.1016/S0167-8140(18)32450-2)
- Shi, Z. et al. 2018. External validation of radiation-induced dyspnea models on esophageal cancer radiotherapy patients. Radiotherapy and Oncology 127, pp. S168-S168. (10.1016/S0167-8140(18)30628-5)
- Foley, K. G. et al. 2018. Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer. European Radiology 28, pp. 428-436. (10.1007/s00330-017-4973-y)
- Grassi, E. et al. 2018. Effect of image registration on 3D absorbed dose calculations in 177 Lu-DOTATOC Peptide Receptor Radionuclide Therapy. Physica Medica: European Journal of Medical Physics 45, pp. 177-185. (10.1016/j.ejmp.2017.11.021)
2017
- Gleisner, K. S. et al. 2017. Variations in the practice of molecular radiotherapy and implementation of dosimetry: results from a European survey. EJNMMI Physics 4, article number: 28. (10.1186/s40658-017-0193-4)
- D'Arienzo, M. et al. 2017. Phantom validation of quantitative Y-90 PET/CT based dosimetry in liver radioembolisation. EJNMMI Research 7, article number: 94. (10.1186/s13550-017-0341-9)
- Stokke, C. et al. 2017. Dosimetry-based treatment planning for molecular radiotherapy; a summary of the 2017 report from the Internal Dosimetry Task Force. EJNMMI Physics 4, article number: 27. (10.1186/s40658-017-0194-3)
- Sykes, J., Alaei, P. and Spezi, E. 2017. Imaging dose in radiation therapy. In: Mijnheer, B. ed. Clinical 3D Dosimetry in Modern Radiation Therapy. CRC Press, pp. 561-588.
- Berthon, B. et al. 2017. Toward a standard for the evaluation of PET-Auto-Segmentation methods following the recommendations of AAPM task group No. 211: Requirements and implementation. Medical Physics 44(8), pp. 4098-4111. (10.1002/mp.12312)
- Supanich, M., Schmidtlein, C., El Naqa, I., Kirov, A. and Spezi, E. 2017. How to select and evaluate a PET auto-segmentation tool-insights from AAPM TG211. Medical Physics 44(6), pp. 3285-3286. (10.1002/mp.12304)
- Hatt, M. et al. 2017. Classification and evaluation strategies of auto-segmentation approaches for PET: report of AAPM task group No. 211. Medical Physics 44(6), pp. e1-e42. (10.1002/mp.12124)
- Dabkowski, A., Paisey, S. J., Spezi, E., Chester, J. and Marshall, C. 2017. Optimization of Zirconium-89 production in IBA cyclone 18/9 cyclotron with COSTIS solid target system. Presented at: WTTC16: Proceedings of the 16th International Workshop on Targetry and Target Chemistry, Santa Fe, NM, USA, 29 August–1 September 2016 Presented at Engle, J. W. et al. eds.AIP Conference Proceedings, Vol. 1845. Melville, NY: AIP pp. 20005., (10.1063/1.4983536)
- Parkinson, C., Chan, J., Syndikus, I., Marshall, C., Staffurth, J. and Spezi, E. 2017. Impact of 18F-Choline PET scan acquisition time on delineation of GTV in prostate cancer [Poster Abstract]. Radiotherapy and Oncology 123(S1), pp. S714-S715. (10.1016/S0167-8140(17)31768-1)
- Berthon, B. et al. 2017. Head and neck target delineation using a novel PET automatic segmentation algorithm. Radiotherapy and Oncology 122(2), pp. 242-247. (10.1016/j.radonc.2016.12.008)
- Gleisner, K. S. et al. 2017. Treatment planning for molecular radiotherapy: potential and prospects. European Association of Nuclear Medicine. Available at: http://www.eanm.org/publications/idtf-report
2016
- Ward, G. et al. 2016. Superiority of deformable image co-registration in the integration of diagnostic positron emission tomography-computed tomography to the radiotherapy treatment planning pathway for oesophageal carcinoma. Clinical Oncology 28(10), pp. 655-662. (10.1016/j.clon.2016.05.009)
- D'Arienzo, M. et al. 2016. Calculation and measurement of absorbed doses for non uniform activity distributions in liver radioembolization using 90Y-PET imaging. European Journal of Nuclear Medicine and Molecular Imaging 43(S1), pp. S409-S410. (10.1007/s00259-016-3484-4)
- Fokas, E. et al. 2016. Comparison of investigator-delineated gross tumour volumes and quality assurance in pancreatic cancer: analysis of the on-trial cases for the SCALOP trial. Radiotherapy and Oncology 120(2), pp. 212-216. (10.1016/j.radonc.2016.07.002)
- Berthon, B., Marshall, C., Evans, M. and Spezi, E. 2016. ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography. Physics in Medicine and Biology 61(13), pp. 4855-4869. (10.1088/0031-9155/61/13/4855)
- Gwynne, S. et al. 2016. Prospective review of radiotherapy trials through implementation of standardised multi-centre workflow and IT infrastructure. British Journal of Radiology 89, article number: 20160020. (10.1259/bjr.20160020)
- Fokas, E. et al. 2016. P-222 Analysis of tumour contours and radiotherapy planning of 'on-trial' patients undergoing chemoradiotherapy (CRT) in SCALOP trial: does pre-trial Radiotherapy Quality Assurance (RTQA) improve the quality of 'on-trial' radiotherapy?. Annals of Oncology 27(sup. 2), pp. ii64.3-ii65. (10.1093/annonc/mdw199.214)
- Carrington, R., Spezi, E., Gwynne, S., Dutton, P., Hurt, C. N., Staffurth, J. N. and Crosby, T. 2016. The influence of dose distribution on treatment outcome in the SCOPE 1 oesophageal cancer trial. Radiation Oncology 11, article number: 19. (10.1186/s13014-016-0594-x)
- Carrington, R., Spezi, E., Gwynne, S., Dutton, P., Hurt, C. N., Staffurth, J. N. and Crosby, T. 2016. The influence of radiotherapy treatment method on dose distribution and its relation to patient outcome in the SCOPE 1 oesophageal cancer trial using Type B algorithms. Radiation Oncology (London, England) 11, article number: 19. (10.1186/s13014-016-0594-x)
2015
- Berthon, B. et al. 2015. PETSTEP: Generation of synthetic PET lesions for fast evaluation of segmentation methods. Physica Medica 31(8), pp. 969-980. (10.1016/j.ejmp.2015.07.139)
- Fokas, E. et al. 2015. Comparison of investigator-delineated gross tumor volumes and quality assurance in pancreatic cancer: Analysis of the pretrial benchmark case for the SCALOP trial. Radiotherapy and Oncology 117(3), pp. 432-437. (10.1016/j.radonc.2015.08.026)
- Carrington, R. et al. 2015. The effect of dose escalation on gastric toxicity when treating lower oesophageal tumours: a radiobiological investigation. Radiation Oncology 10, article number: 236. (10.1186/s13014-015-0537-y)
- Alaei, P. and Spezi, E. 2015. Imaging dose from cone beam computed tomography in radiation therapy. Physica Medica 31(7), pp. 647-658. (10.1016/j.ejmp.2015.06.003)
- Fenwick, A. J., Johansson, L., Spezi, E., Evans, W. and Marshall, C. 2015. Metrology for Zr-89 in the clinic [Abstract]. European Journal of Nuclear Medicine and Molecular Imaging 42, pp. S342-S343.
- Fenwick, A., Marshall, C., Spezi, E., Evans, W. and Johansson, L. 2015. Quantitative Imaging of Zr-89 on a pre-clinical PET/CT system [Abstract]. European Journal of Nuclear Medicine and Molecular Imaging 42(S1), pp. S415-S415.
- Carrington, R. et al. 2015. A radiobiological investigation of dose escalation in lower oesophageal tumours with a focus on gastric toxicity. Medical Physics 42(6), pp. 3346-3347. (10.1118/1.4924430)
- Berthon, B., Marshall, C., Holmes, R. and Spezi, E. 2015. A novel phantom technique for evaluating the performance of PET auto-segmentation methods in delineating heterogeneous and irregular lesions. EJNMMI Physics 2(1), article number: 13. (10.1186/s40658-015-0116-1)
2014
- Skripcak, T. et al. 2014. Creating a data exchange strategy for radiotherapy research: Towards federated databases and anonymised public datasets. Radiotherapy and Oncology 113(3), pp. 303-309. (10.1016/j.radonc.2014.10.001)
- Berthon, B. et al. 2014. Intensity modulated radiotherapy treatment of head and neck cancer patients using PET auto-segmentation to delineate primary tumour. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S196-S197.
- D'Arienzo, M. et al. 2014. 90Y-PET imaging after liver radioembolization: from PET calibration to absorbed dose determination using a Monte Carlo approach. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S331-S331.
- Berthon, B., Marshall, C. and Spezi, E. 2014. A predictive model for optimal segmentation of PET images. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S172-S172.
- Bagni, O., Spezi, E., Patterson, N., Filippi, L., D'Arienzo, M., Chiaramida, P. and Scopinaro, F. 2014. A workflow for treatment evaluation of 90Y microspheres SIRT therapy of hepatic lesions based on FDG-PET and Y90-PET. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S255-S255.
- Berthon, B. et al. 2014. A fast positron emission tomography simulator for synthetic lesion smulation.. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S367-S367.
- Gwynne, S. et al. 2014. Progress towards prospective real-time review of outlining in GI trials at a UK radiation therapy quality assurance center. International Journal of Radiation Oncology*Biology*Physics 90(S1), pp. S734-S735. (10.1016/j.ijrobp.2014.05.2138)
- Rackley, T. et al. 2014. Esophageal delineation - lessons learned from pre-accrual benchmark cases in the UK NeoSCOPE esophageal trial. International Journal of Radiation Oncology - Biology - Physics 90(1), pp. S10-S10. (10.1016/j.ijrobp.2014.05.088)
- Gwynne, S. et al. 2014. Prospective review of outlining in the UK NeoSCOPE esophageal trial. International Journal of Radiation Oncology - Biology - Physics 90(1), pp. S733-S733. (10.1016/j.ijrobp.2014.05.2135)
- Pettinato, C. et al. 2014. Pretherapeutic dosimetry in patients affected by metastatic thyroid cancer using I-124 PET/CT sequential scans for I-131 treatment planning. Clinical Nuclear Medicine 39(8), pp. E367-E374. (10.1097/RLU.0000000000000490)
- Alaei, P., Spezi, E. and Reynolds, M. 2014. Dose calculation and treatment plan optimization including imaging dose from kilovoltage cone beam computed tomography. Acta Oncologica 53(6), pp. 839-844. (10.3109/0284186X.2013.875626)
- Berthon, B., Marshall, C., Evans, M. and Spezi, E. 2014. Evaluation of advanced automatic PET segmentation methods using nonspherical thin-wall inserts. Medical Physics 41, article number: 22502. (10.1118/1.4863480)
2013
- Berthon, B., Marshall, C., Evans, M. and Spezi, E. 2013. Implementation and optimization of automatic 18F-FDG PET segmentation methods. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S299-S299.
- Berthon, B., Marshall, C., Evans, M., Edwards, A. and Spezi, E. 2013. Performance of 18F-FDG PET automated segmentation methods for non-spherical objects. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S236-S237.
- Berthon, B., Holmes, R. B., Marshall, C., Jayaprakasam, V. S., Evans, M. and Spezi, E. 2013. Evaluation of several automatic PET-segmentation algorithms for radiotherapy treatment planning in H&N using a printed sub-resolution sandwich phantom. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S236-S236.
- Pettinato, C. et al. 2013. Negative predictive value of 124I-PET/CT imaging in patients affected by metastatic thyroid cancer and treated with 131I. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S276-S276.
- Pettinato, C. et al. 2013. Salivary gland dosimetry using 124I-PET/CT imaging and MIRD method. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S125-S126.
- Berthon, B., Marshall, C., Edwards, A., Evans, M. and Spezi, E. 2013. Influence of cold walls on PET image quantification and volume segmentation: A phantom study. Medical Physics 40(8), article number: 82505. (10.1118/1.4813302)
- Azimi, R. et al. 2013. Dosimetric and biological benchmarking of a murine total marrow irradiation platform. Medical Physics 40(6)
- Gwynne, S. et al. 2013. Oesophageal chemoradiotherapy in the UK-current practice and future directions. Clinical Oncology 25(6), pp. 368-377. (10.1016/j.clon.2013.01.006)
- Alaei, P., Spezi, E., Ehler, E. and Dusenbery, K. 2013. Assessing and minimizing the dose From KV cone beam CT to pediatric patients undergoing radiation therapy. Medical Physics 40(6), article number: 151. (10.1118/1.4814220)
- Marcatili, S., Pettinato, C., Daniels, S., Lewis, G., Edwards, P., Fanti, S. and Spezi, E. 2013. Development and validation of RAYDOSE: a Geant4-based application for molecular radiotherapy. Physics in Medicine and Biology 58(8), pp. 2491-2508. (10.1088/0031-9155/58/8/2491)
- Gwynne, S., Spezi, E., Sebag-Montefiore, D., Mukherjee, S., Miles, E., Conibear, J. and Staffurth, J. 2013. Improving radiotherapy quality assurance in clinical trials: assessment of target volume delineation of the pre-accrual benchmark case. British Journal of Radiology 86(1024), article number: 20120398. (10.1259/bjr.20120398)
- Spezi, E. and Leal, A. 2013. Special section: Selected papers from the third European workshop on Monte Carlo treatment planning (MCTP2012) PREFACE. Physics in Medicine and Biology 58(8) (10.1088/0031-9155/58/8/E01)
- Mukherjee, S. et al. 2013. Comparison of investigator-delineated GTV in chemoradiotherapy (CRT) for locally advanced nonmetastatic pancreatic cancer (LANPC): Analysis of the pretrial test case for the SCALOP trial. Journal of Clinical Oncology 31(4), article number: 230.
2012
- Pettinato, C. et al. 2012. Usefulness of I-124 PET/CT imaging to predict absorbed doses in patients affected by metastatic thyroid cancer and treated with I-131. Quarterly journal of nuclear medicine and molecular imaging 56(6), pp. 509-514.
- Gwynne, S. H. et al. 2012. Toward semi-automated assessment of target volume delineation in radiotherapy trials: the SCOPE 1 pretrial test case. International Journal of Radiation Oncology*Biology*Physics 84(4), pp. 1037-1042. (10.1016/j.ijrobp.2012.01.094)
- Berthon, B., Spezi, E., Edwards, A. and Marshall, C. 2012. Quantitative effect of cold plastic walls on 18F-FDG PET images. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S385-S385.
- Berthon, B., Holmes, R. B., Marshall, C. and Spezi, E. 2012. Use of a printed subresolution sandwich phantom for simulation of FDG PET images. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S498-S498.
- Berthon, B., Spezi, E., Marshall, C. and Evans, M. 2012. Comparison of automatic segmentation methods of 18F-FDG PET images for radiation therapy planning in H&N: a phantom study. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S265-S265.
- Shepherd, T. et al. 2012. Design of a benchmark platform for evaluating PET-based contouring accuracy in oncology applications. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S264-S264.
- Marcatili, S. et al. 2012. Monte Carlo based 3D absorbed dose distributions for organs at risk in molecular radiotherapy. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S350-S350.
- Pettinato, C. et al. 2012. Usefulness of 124I PET/CT imaging to predict absorbed doses in patients affected by metastatic thyroid cancer and treated with 131I. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S202-S203.
- Alaei, P., Spezi, E. and Reynolds, M. 2012. Calculating the dose from KV cone beam CT within and outside the treatment volume using a treatment planning system. Medical Physics 39(6), pp. 3655-3655.
- Spezi, E., Downes, P., Jarvis, R., Radu, E. and Staffurth, J. N. 2012. Patient-specific three-dimensional concomitant dose from cone beam computed tomography exposure in image-guided radiotherapy. International Journal of Radiation Oncology*Biology*Physics 83(1), pp. 419-426. (10.1016/j.ijrobp.2011.06.1972)
- Gwynne, S., Mukherjee, S., Webster, R., Spezi, E., Staffurth, J., Coles, B. and Adams, R. 2012. Imaging for target volume delineation in rectal cancer radiotherapy - A systematic review. Clinical Oncology 24(1), pp. 52-63. (10.1016/j.clon.2011.10.001)
- Alaei, P. and Spezi, E. 2012. Commissioning kilovoltage cone-beam CT beams in a radiation therapy treatment planning system. Journal of Applied Clinical Medical Physics 13(6), pp. 19-33., article number: 3971.
2011
- Gwynne, S. et al. 2011. Inter-observer variation in outlining of pre-trial test case in the SCOPE1 trial: A United Kingdom definitive chemoradiotherapy trial for esophageal cancer. International Journal of Radiation Oncology - Biology - Physics 81(2), pp. S67-S68. (10.1016/j.ijrobp.2011.06.135)
- Marcatili, S. et al. 2011. RAYDOSE: a Geant4 application for 3D Targeted Radionuclide Therapy (TRT) dosimetry. European Journal of Nuclear Medicine and Molecular Imaging 38, pp. S201-S202.
- Spezi, E., Volken, W., Frei, D. and Fix, M. K. 2011. A virtual source model for Kilo-voltage cone beam CT: Source characteristics and model validation. Medical Physics 38(9), pp. 5254-5263. (10.1118/1.3626574)
- Gwynne, S., Webster, R., Adams, R., Mukherjee, S., Spezi, E. and Staffurth, J. 2011. Image guided radiotherapy for rectal cancer - a review. Clinical Oncology 23(3), pp. S37-S37.
- Gwynne, S., Webster, R., Mukherjee, S., Staffurth, J. N., Spezi, E. and Adams, R. 2011. Imaging for rectal cancer radiotherapy - a systematic review. Clinical Oncology 23(3), pp. S37-S37.
2010
- Cufflin, R. S., Spezi, E., Millin, A. E. and Lewis, D. G. 2010. An investigation of the accuracy of Monte Carlo portal dosimetry for verification of IMRT with extended fields. Physics in Medicine and Biology 55(16), pp. 4589-4600. (10.1088/0031-9155/55/16/S12)
2009
- Downes, P., Jarvis, R., Radu, E., Kawrakow, I. and Spezi, E. 2009. Monte Carlo simulation and patient dosimetry for a kilovoltage cone-beam CT unit. Medical Physics 36(9), pp. 4156-4167.
- Downes, P., Yaikhom, G., Giddy, J. P., Walker, D. W., Spezi, E. and Lewis, D. G. 2009. High-performance computing for Monte Carlo radiotherapy calculations. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367(1897), pp. 2607-2617. (10.1098/rsta.2009.0028)
- Downes, P. and Spezi, E. 2009. Simulating oblique incident irradiation using the BEAMnrc Monte Carlo code. Physics in Medicine and Biology 54(7), pp. N93-N100. (10.1088/0031-9155/54/7/N02)
- Cufflin, R. S., Spezi, E. and Lewis, D. G. 2009. IMRT verification using portal dosimetry and a 3D planning system. Clinical Oncology 21(3), pp. 264-265.
- Jarvis, R., Downes, P., Radu, E. and Spezi, E. 2009. Patient dose from the elekta XVI cone-beam CT: Phantom and Monte Carlo study. Clinical Oncology 21(3), pp. 270-270.
- Guido, A. et al. 2009. Combined F-18-FDG-PET/CT imaging in radiotherapy target delineation for head-and-neck cancer. International Journal of Radiation Oncology - Biology - Physics 73(3), pp. 759-763.
- Spezi, E., Downes, P., Radu, E. and Jarvis, R. 2009. Reply to "comment on 'Monte Carlo simulation of an x-ray volume imaging cone beam CT unit'". Medical Physics 36(3), pp. 1040-1040.
- Spezi, E., Downes, P., Radu, E. and Jarvis, R. 2009. Monte Carlo simulation of an x-ray volume imaging cone beam CT unit. Medical Physics 36(1), pp. 127-136. (10.1118/1.3031113)
2008
- Palleri, F., Baruffald, F., Angelini, A. L., Ferri, A. and Spezi, E. 2008. Monte Carlo characterization of materials for prosthetic implants and dosimetric validation of Pinnacle(3) TPS. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 266(23), pp. 5001-5006. (10.1016/j.nimb.2008.08.013)
- Spezi, E., Angelini, A. L., Romani, F., Guido, A., Bunkheila, F., Ntreta, M. and Ferri, A. 2008. Evaluating the influence of the Siemens IGRT carbon fibre tabletop in head and neck IMRT. Radiotherapy and Oncology 89(1), pp. 114-122. (10.1016/j.radonc.2008.06.011)
- Spezi, E. and Lewis, G. 2008. An overview of Monte Carlo treatment planning for radiotherapy. Radiation Protection Dosimetry 131(1), pp. 123-129. (10.1093/rpd/ncn277)
- Yaikhom, G., Giddy, J. P., Walker, D. W., Downes, P., Spezi, E. and Lewis, D. G. 2008. A distributed simulation framework for conformal radiotherapy. Presented at: 22nd IEEE International Symposium on Parallel & Distributed Processing, Miami, FL, USA, 14-18 April 2008Proceedings of the IEEE International Symposium on Parallel and Distributed Processing, 2008 (IPDPS 2008), Miami, FL, 14-18 April 2008. Piscataway, NJ: IEEE, (10.1109/IPDPS.2008.4536471)
2007
- Spezi, E. 2007. Status of MCTP in Europe. Radiotherapy and Oncology 84, pp. S6-S7.
- Buettner, F., Spezi, E., Paganetti, H. and Seco, J. 2007. Dosimetric uncertainties in IMRT QA in plastic phantoms due to CT calibration. Medical Physics 34(6), pp. 2442-2442.
- Vanderstraeten, B. et al. 2007. Conversion of CT numbers into tissue parameters for Monte Carlo dose calculations: a multi-centre study. Physics in Medicine and Biology 52(3), pp. 539-562. (10.1088/0031-9155/52/3/001)
- Spezi, E. and Ferri, A. 2007. Dosimetric characteristics of the siemens IGRT carbon fiber tabletop. Medical Dosimetry 32(4), pp. 295-298.
- Spezi, E., Angelini, A. L. and Ferri, A. 2007. Monte Carlo simulation of the SIEMENS IGRT carbon fibre tabletop. Journal of Physics: Conference Series 74, pp. U145-U150. (10.1088/1742-6596/74/1/021017)
- Spezi, E., Palleri, F., Angelini, A. L., Ferri, A. and Baruffaldi, F. 2007. Characterization of materials for prosthetic implants using the BEAMnrc Monte Carlo code. Journal of Physics: Conference Series 74, pp. U141-U144. (10.1088/1742-6596/74/1/021016)
2006
- Deasy, J. et al. 2006. The computational environment for radiotherapy research: New tools for multi-modality imaging, treatment plan comparisons, and plan evaluations. Medical Physics 33(6), pp. 2140-2140.
- Spezi, E. and Lewis, D. G. 2006. Gamma histograms for radiotherapy plan evaluation. Radiotherapy and Oncology 79(2), pp. 224-230. (10.1016/j.radonc.2006.03.020)
- Spezi, E., Angelini, A. L. and Ferri, A. 2006. A multiple acquisition sequence for IMRT verification with a 2D ion chamber array. Medical Dosimetry 31(4), pp. 269-272.
2005
- Spezi, E., Angelini, A. L., Romani, F. and Ferri, A. 2005. IMRT plan verification using a 2D ion chamber array. Radiotherapy and Oncology 76, pp. S176-S177.
- Cora, S. et al. 2005. Evaluation of the treatment planning system of the Cyberknife by means of a comparison to Monte Carlo calculation. Radiotherapy and Oncology 76, pp. S96-S96. (10.1016/S0167-8140(05)81172-7)
- Spezi, E., Angelini, A. L., Romani, F. and Ferri, A. 2005. Characterization of a 2D ion chamber array for the verification of radiotherapy treatments. Physics in Medicine and Biology 50(14), pp. 3361-3373. (10.1088/0031-9155/50/14/012)
- Alaly, J., Zakarian, K., Lindsay, P., El Naqa, I., Hope, A., Spezi, E. and Deasy, I. 2005. Software tools for 4-D and adaptive treatment planning data visualization and manipulation (CERR version 3). Medical Physics 32(6), pp. 2033-2033.
2004
- Alaly, J., Deasy, J., Zakarian, C., Hope, A., Spezi, E., Bosch, W. and Purdy, J. 2004. Modeling radiotherapy treatment outcomes: Open-source data collection, database, and plan review tools. Medical Physics 31(6), pp. 1901-1902.
- Chin, P. W., Lewis, D. G. and Spezi, E. 2004. Correction for dose-response variations in a scanning liquid ion chamber EPID as a function of linac gantry angle. Physics in Medicine and Biology 49(8), pp. N93-N103. (10.1088/0031-9155/49/8/N01)
- Spezi, E. and Lewis, D. G. 2004. Full forward Monte Carlo calculation of portal dose from MLC collimated treatment beams (vol 47, pg 377, 2002). Physics in Medicine and Biology 49(2), pp. 355-355.
2003
- Spezi, E. and Deasy, J. 2003. An open source DICOM-RT/MATLAB based computational platform for radiotherapy research. Radiotherapy and Oncology 68(s1), pp. S106.
- Spezi, E., Lewis, D. G., Millin, A. and Cuffin, R. 2003. MC based QA of IMRT. Radiotherapy and Oncolocy 68(S1), pp. S46-S46. (10.1016/S0167-8140(03)80135-4)
- Chin, P. W., Spezi, E. and Lewis, D. G. 2003. Monte Carlo simulation of portal dosimetry on a rectilinear voxel geometry: a variable gantry angle solution. Physics in Medicine and Biology 48(16), pp. N231-N238. (10.1088/0031-9155/48/16/401)
Articles
- Duman, A., Sun, X., Thomas, S., Powell, J. R. and Spezi, E. 2024. Reproducible and interpretable machine learning-based radiomic analysis for overall survival prediction in glioblastoma multiforme. Cancers 16(19), article number: 3351. (10.3390/cancers16193351)
- Grassi, E. et al. 2024. Patient-specific dosimetry evaluations in Theranostics software for internal radiotherapy. Applied Sciences 14(16), article number: 7345. (10.3390/app14167345)
- Della Corte, A. et al. 2024. Preoperative MRI radiomic analysis for predicting local tumor progression in colorectal liver metastases before microwave ablation. International Journal of Hyperthermia 41(1), article number: 2349059. (10.1080/02656736.2024.2349059)
- Wheeler, P. A. et al. 2024. Multi-institutional evaluation of a Pareto navigation guided automated radiotherapy planning solution for prostate cancer. Radiation Oncology 19, article number: 45. (10.1186/s13014-024-02404-x)
- Whybra, P. et al. 2024. The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights. Radiology 310(2) (10.1148/radiol.231319)
- Lou, J. et al. 2024. Predicting radiologists' gaze with computational saliency models in mammogram reading. IEEE Transactions on Multimedia 26, pp. 256-269. (10.1109/TMM.2023.3263553)
- Duman, A., Karakuş, O., Sun, X., Thomas, S., Powell, J. and Spezi, E. 2023. RFS+: A clinically adaptable and computationally efficient strategy for enhanced brain tumor segmentation. Cancers 15(23), article number: 5620. (10.3390/cancers15235620)
- Welgemoed, C., Spezi, E., Riddle, P., Gooding, M. J., Gujral, D., McLauchlan, R. and Aboagye, E. O. 2023. Clinical evaluation of atlas-based auto-segmentation in breast and nodal radiotherapy. British Journal of Radiology 96(1149), article number: 20230040. (10.1259/bjr.20230040)
- Whybra, P. and Spezi, E. 2023. Sensitivity of standardised radiomics algorithms to mask generation across different software platforms. Scientific Reports 13, article number: 14419. (10.1038/s41598-023-41475-w)
- Mukherjee, S. et al. 2023. Efficacy of early PET-CT directed switch to carboplatin and paclitaxel based definitive chemoradiotherapy in patients with oesophageal cancer who have a poor early response to induction cisplatin and capecitabine in the UK: a multi-centre randomised controlled phase II trial. EClinicalMedicine 61, article number: 102059. (10.1016/j.eclinm.2023.102059)
- Loi, S. et al. 2023. Limited impact of discretization/interpolation parameters on the predictive power of CT radiomic features in a surgical cohort of pancreatic cancer patients. La Radiologia Medica 128(7), pp. 799–807. (10.1007/s11547-023-01649-y)
- Mori, M. et al. 2023. External validation of an 18F-FDG-PET radiomic model predicting survival after radiotherapy for oropharyngeal cancer. European Journal of Nuclear Medicine and Molecular Imaging 50, pp. 1329-1336. (10.1007/s00259-022-06098-9)
- Lacan, F., Johnston, R., Carrington, R., Spezi, E. and Theobald, P. 2023. Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms. Journal of Medical Engineering & Technology 47, pp. 189-196. (10.1080/03091902.2023.2193267)
- Foster, I., Spezi, E. and Wheeler, P. 2023. Evaluating the use of machine learning to predict expert-driven pareto-navigated calibrations for personalised automated radiotherapy planning. Applied Sciences 13(7), article number: 4548. (10.3390/app13074548)
- Alsyed, E., Smith, R., Bartley, L., Marshall, C. and Spezi, E. 2023. A heterogeneous phantom study for investigating the stability of PET images radiomic features with varying reconstruction settings. Frontiers in Nuclear Medicine 3 (10.3389/fnume.2023.1078536)
- Cagni, E. et al. 2022. Evaluating the quality of patient-specific deformable image registration in adaptive radiotherapy using a digitally enhanced head and neck phantom. Applied Sciences 12(19), article number: 9493. (10.3390/app12199493)
- Theophanous, S. et al. 2022. Development and validation of prognostic models for anal cancer outcomes using distributed learning: protocol for the international multi-centre atomCAT2 study. Diagnostic and Prognostic Research 6(1), article number: 14. (10.1186/s41512-022-00128-8)
- Parkinson, C., Matthams, C., Foley, K. and Spezi, E. 2021. Artificial intelligence in radiation oncology: A review of its current status and potential application for the radiotherapy workforce. Radiography 27, pp. S63-S68. (10.1016/j.radi.2021.07.012)
- Palumbo, D. et al. 2021. Prediction of early distant recurrence in upfront resectable pancreatic adenocarcinoma: A multidisciplinary, machine learning-based approach. Cancers 13(19), article number: 4938. (10.3390/cancers13194938)
- Piazzese, C., Evans, E., Thomas, B., Staffurth, J., Gwynne, S. and Spezi, E. 2021. FIELDRT: an open-source platform for the assessment of target volume delineation in radiation therapy. British Journal of Radiology 94(1126), article number: 20210356. (10.1259/bjr.20210356)
- Cagni, E., Botti, A., Chendi, A., Iori, M. and Spezi, E. 2021. Use of knowledge based DVH predictions to enhance automated re-planning strategies in head and neck adaptive radiotherapy. Physics in Medicine and Biology 66(13), article number: 135004. (10.1088/1361-6560/ac08b0)
- Shi, Z. et al. 2021. Prediction of lymph node metastases using pre-treatment PET radiomics of the primary tumour in esophageal adenocarcinoma: an external validation study. British Journal of Radiology 94(1118), article number: 20201042. (10.1259/bjr.20201042)
- Cagni, E. et al. 2021. Variations in head and neck treatment plan quality assessment among radiation oncologists and medical physicists in a single radiotherapy department. Frontiers in Oncology - Radiation Oncology 11, article number: 706034. (10.3389/fonc.2021.706034)
- Mori, M. et al. 2020. Training and validation of a robust PET radiomic-based index to predict distant-relapse-free-survival after radio-chemotherapy for locally advanced pancreatic cancer. Radiotherapy and Oncology 153, pp. 258-264. (10.1016/j.radonc.2020.07.003)
- Kazmierska, J. et al. 2020. From multisource data to clinical decision aids in radiation oncology: the need for a clinical data science community. Radiotherapy and Oncology 153, pp. 43-54. (10.1016/j.radonc.2020.09.054)
- Zwanenburg, A. et al. 2020. The Image Biomarker Standardization Initiative: standardized quantitative radiomics for high throughput image-based phenotyping. Radiology 295(2), pp. 328-338. (10.1148/radiol.2020191145)
- Deist, T. M. et al. 2020. Distributed learning on 20 000+ lung cancer patients - The Personal Health Train. Radiotherapy and Oncology 144, pp. 189-200. (10.1016/j.radonc.2019.11.019)
- Finocchiaro, D. et al. 2020. Comparison of different calculation techniques for absorbed dose assessment in patient specific peptide receptor radionuclide therapy. PLoS ONE 15(8), article number: e0236466. (10.1371/journal.pone.0236466)
- Wheeler, P. A. et al. 2019. Evaluating the application of Pareto navigation guided automated radiotherapy treatment planning to prostate cancer. Radiotherapy and Oncology 141, pp. 220-226. (10.1016/j.radonc.2019.08.001)
- Shi, Z. et al. 2019. External validation of radiation-induced dyspnea models on esophageal cancer radiotherapy patients. Frontiers in Oncology 9, article number: 1411. (10.3389/fonc.2019.01411)
- Piazzese, C., Foley, K., Whybra, P., Hurt, C., Crosby, T. and Spezi, E. 2019. Discovery of stable and prognostic CT-based radiomic features independent of contrast administration and dimensionality in oesophageal cancer. PLoS ONE 14(11), article number: e0225550. (10.1371/journal.pone.0225550)
- Hargreaves, S., Johnstone, E., Parkinson, C., Rackley, T., Spezi, E., Staffurth, J. and Evans, M. 2019. Interim 18F-FDG positron emission tomography/computed tomography during chemoradiotherapy in the management of cancer patients: a response [Letter]. Clinical Oncology 31(9), pp. 669-670. (10.1016/j.clon.2019.05.005)
- Whybra, P., Parkinson, C., Foley, K., Staffurth, J. and Spezi, E. 2019. Assessing radiomic feature robustness to interpolation in 18F-FDG PET imaging. Scientific Reports 9(1), article number: 9649. (10.1038/s41598-019-46030-0)
- Tsang, Y., Hoskin, P., Spezi, E., Landau, D., Lester, J., Miles, E. and Conibear, J. 2019. Assessment of contour variability in target volumes and organs at risk in lung cancer radiotherapy. Technical Innovations and Patient Support in Radiation Oncology 10, pp. 8-12. (10.1016/j.tipsro.2019.05.001)
- Foley, K., Christian, A., Peaker, J., Marshall, C., Spezi, E., Kynaston, H. and Roberts, S. A. 2019. Cyclo-oxygenase-2 expression is associated with mean standardised uptake value on 18F-fluorodeoxyglucose positron emission tomography in oesophageal adenocarcinoma. British Journal of Radiology 92(1099), article number: 20180668. (10.1259/bjr.20180668)
- Parkinson, C. et al. 2019. Machine-learned target volume delineation of 18F-FDG PET images after one cycle of induction chemotherapy. Physica Medica, European Journal of Medical Physics 61, pp. 85-93. (10.1016/j.ejmp.2019.04.020)
- Foley, K. G. et al. 2019. External validation of a prognostic model incorporating quantitative PET image features in esophageal cancer. Radiotherapy and Oncology 133, pp. 205-212. (10.1016/j.radonc.2018.10.033)
- Wheeler, P. A. et al. 2019. Utilisation of Pareto navigation techniques to calibrate a fully automated radiotherapy treatment planning solution. Physics and Imaging in Radiation Oncology 10, pp. 41-48. (10.1016/j.phro.2019.04.005)
- Evans, E., Piazzese, C., Spezi, E., Staffurth, J. and Gwynne, S. 2019. EP-1666 ARENA: Improving training in target volume delineation for radiotherapy. Radiotherapy and Oncology 133(S1), pp. S896-S897. (10.1016/S0167-8140(19)32086-9)
- Md Radzi, Y., Windle, R., Lewis, D. and Spezi, E. 2019. EP-1744 Enhancing the accuracy in VMAT dose verification by the use of EPID-based commercial software. Radiotherapy and Oncology 133(S1), pp. S940-S491. (10.1016/S0167-8140(19)32164-4)
- Cagni, E. et al. 2019. EP-2010 A QA method for evaluation of deformable image registration in head and neck adaptive radiotherapy. Radiotherapy and Oncology 133, pp. S1101. (10.1016/S0167-8140(19)32430-2)
- Md Radzi, Y., Windle, R., Lewis, D. and Spezi, E. 2019. EP-1748 Adaptive solution for an improved treatment verification using Dosimetry Check system. Radiotherapy and Oncology 133(S1), pp. S942-S943. (10.1016/S0167-8140(19)32168-1)
- Wheeler, P. et al. 2019. OC-0183 Multi-institutional evaluation of a Pareto navigation guided automated planning solution. Radiotherapy and Oncology 133(S1), pp. S92. (10.1016/S0167-8140(19)30603-6)
- Deist, T. et al. 2019. OC-0544 Distributed learning on 20 000+ lung cancer patients. Radiotherapy and Oncology 133(S1), pp. S287-S288. (10.1016/S0167-8140(19)30964-8)
- Piazzese, C., Whybra, P., Qasem, E., Harris, D., Gtaes, R., Foley, K. and Spezi, E. 2019. EP-1926 Radiomics in rectal cancer: prognostic significance of 3D features extracted from diagnostic MRI. Radiotherapy and Oncology 133(S1), pp. S1048. (10.1016/S0167-8140(19)32346-1)
- Piazzese, C., Whybra, P., Carrington, R., Crosby, T., Staffurth, J., Foley, K. and Spezi, E. 2019. PO-0964 Stability and prognostic significance of CT radiomic features from oesophageal cancer patients. Radiotherapy and Oncology 133(S1), pp. S524-S525. (10.1016/S0167-8140(19)31384-2)
- Whybra, P., Parkinson, C., Foley, K., Staffurth, J. and Spezi, E. 2019. PO-0963 A novel normalisation technique for voxel size dependent radiomic features in oesophageal cancer. Radiotherapy and Oncology 133(S1), pp. S523-S524. (10.1016/S0167-8140(19)31383-0)
- Cagni, E., Botti, A., Orlandi, M., Sghedoni, R., Spezi, E. and Iori, M. 2019. PO-0996 A knowledge-based tool to estimate the gain of re-planning strategy for Head and Neck (HN) ART. Radiotherapy and Oncology 133(S1), pp. S548-S549. (10.1016/S0167-8140(19)31416-1)
- Piazzese, C., Whybra, P., Qasem, E., Harris, D., Gtaes, R., Foley, K. and Spezi, E. 2019. Radiomics in rectal cancer: prognostic significance of 3D features extracted from diagnostic MRI [Abstract]. Radiotherapy and Oncology 133, pp. S1048-S1048. (10.1016/S0167-8140(19)32346-1)
- Whybra, P., Parkinson, C., Foley, K., Staffurth, J. and Spezi, E. 2019. A novel normalisation technique for voxel size dependent radiomic features in oesophageal cancer [Abstract]. Radiotherapy and Oncology 133, pp. S523-S524. (10.1016/S0167-8140(19)31383-0)
- Finocchiaro, D. et al. 2019. Partial volume effect of SPECT images in PRRT with 177Lu labelled somatostatin analogues: A practical solution. Physica Medica 57, pp. 153-159. (10.1016/j.ejmp.2018.12.029)
- Apte, A. P. et al. 2018. Technical note: Extension of CERR for computational radiomics: a comprehensive MATLAB platform for reproducible radiomics research. Medical Physics 45(8), pp. 3713-3720. (10.1002/mp.13046)
- Portakal, Z., Shermer, S., Jenkins, C., Spezi, E., Perrett, T., Tuncel, N. and Phillips, J. 2018. Design and characterization of tissue-mimicking gel phantoms for diffusion kurtosis imaging. Medical Physics 45(6), pp. 2476-2485. (10.1002/mp.12907)
- Parkinson, C. et al. 2018. Evaluation of prognostic models developed using standardised image features from different PET automated segmentation methods. EJNMMI Research 8, article number: 29. (10.1186/s13550-018-0379-3)
- Whybra, P., Foley, K., Parkinson, C., Staffurth, J. and Spezi, E. 2018. Effect of interpolation on 3D texture analysis of PET imaging in oesophageal cancer. Radiotherapy and Oncology 127(S1), pp. S1164-S1165. (10.1016/S0167-8140(18)32426-5)
- Parkinson, C. et al. 2018. Target volume delineation of PET post one cycle of induction chemotherapy in oropharyngeal cancer. Radiotherapy and Oncology 127(S1), pp. S634-S635., article number: EP-1126. (10.1016/S0167-8140(18)31436-1)
- Parkinson, C. et al. 2018. Dependency of patient risk stratification on PET target volume definition in Oesophageal cancer. Radiotherapy and Oncology 127(S1), pp. S503-S504. (10.1016/S0167-8140(18)31241-6)
- Piazzese, C., Whybra, P., Carrington, R., Crosby, T., Staffurth, J., Foley, K. and Spezi, E. 2018. Evaluation of 2D and 3D radiomics features extracted from CT images of oesophageal cancer patients. Radiotherapy and Oncology 127, pp. S1180-S1181. (10.1016/S0167-8140(18)32450-2)
- Shi, Z. et al. 2018. External validation of radiation-induced dyspnea models on esophageal cancer radiotherapy patients. Radiotherapy and Oncology 127, pp. S168-S168. (10.1016/S0167-8140(18)30628-5)
- Foley, K. G. et al. 2018. Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer. European Radiology 28, pp. 428-436. (10.1007/s00330-017-4973-y)
- Grassi, E. et al. 2018. Effect of image registration on 3D absorbed dose calculations in 177 Lu-DOTATOC Peptide Receptor Radionuclide Therapy. Physica Medica: European Journal of Medical Physics 45, pp. 177-185. (10.1016/j.ejmp.2017.11.021)
- Gleisner, K. S. et al. 2017. Variations in the practice of molecular radiotherapy and implementation of dosimetry: results from a European survey. EJNMMI Physics 4, article number: 28. (10.1186/s40658-017-0193-4)
- D'Arienzo, M. et al. 2017. Phantom validation of quantitative Y-90 PET/CT based dosimetry in liver radioembolisation. EJNMMI Research 7, article number: 94. (10.1186/s13550-017-0341-9)
- Stokke, C. et al. 2017. Dosimetry-based treatment planning for molecular radiotherapy; a summary of the 2017 report from the Internal Dosimetry Task Force. EJNMMI Physics 4, article number: 27. (10.1186/s40658-017-0194-3)
- Berthon, B. et al. 2017. Toward a standard for the evaluation of PET-Auto-Segmentation methods following the recommendations of AAPM task group No. 211: Requirements and implementation. Medical Physics 44(8), pp. 4098-4111. (10.1002/mp.12312)
- Supanich, M., Schmidtlein, C., El Naqa, I., Kirov, A. and Spezi, E. 2017. How to select and evaluate a PET auto-segmentation tool-insights from AAPM TG211. Medical Physics 44(6), pp. 3285-3286. (10.1002/mp.12304)
- Hatt, M. et al. 2017. Classification and evaluation strategies of auto-segmentation approaches for PET: report of AAPM task group No. 211. Medical Physics 44(6), pp. e1-e42. (10.1002/mp.12124)
- Parkinson, C., Chan, J., Syndikus, I., Marshall, C., Staffurth, J. and Spezi, E. 2017. Impact of 18F-Choline PET scan acquisition time on delineation of GTV in prostate cancer [Poster Abstract]. Radiotherapy and Oncology 123(S1), pp. S714-S715. (10.1016/S0167-8140(17)31768-1)
- Berthon, B. et al. 2017. Head and neck target delineation using a novel PET automatic segmentation algorithm. Radiotherapy and Oncology 122(2), pp. 242-247. (10.1016/j.radonc.2016.12.008)
- Ward, G. et al. 2016. Superiority of deformable image co-registration in the integration of diagnostic positron emission tomography-computed tomography to the radiotherapy treatment planning pathway for oesophageal carcinoma. Clinical Oncology 28(10), pp. 655-662. (10.1016/j.clon.2016.05.009)
- D'Arienzo, M. et al. 2016. Calculation and measurement of absorbed doses for non uniform activity distributions in liver radioembolization using 90Y-PET imaging. European Journal of Nuclear Medicine and Molecular Imaging 43(S1), pp. S409-S410. (10.1007/s00259-016-3484-4)
- Fokas, E. et al. 2016. Comparison of investigator-delineated gross tumour volumes and quality assurance in pancreatic cancer: analysis of the on-trial cases for the SCALOP trial. Radiotherapy and Oncology 120(2), pp. 212-216. (10.1016/j.radonc.2016.07.002)
- Berthon, B., Marshall, C., Evans, M. and Spezi, E. 2016. ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography. Physics in Medicine and Biology 61(13), pp. 4855-4869. (10.1088/0031-9155/61/13/4855)
- Gwynne, S. et al. 2016. Prospective review of radiotherapy trials through implementation of standardised multi-centre workflow and IT infrastructure. British Journal of Radiology 89, article number: 20160020. (10.1259/bjr.20160020)
- Fokas, E. et al. 2016. P-222 Analysis of tumour contours and radiotherapy planning of 'on-trial' patients undergoing chemoradiotherapy (CRT) in SCALOP trial: does pre-trial Radiotherapy Quality Assurance (RTQA) improve the quality of 'on-trial' radiotherapy?. Annals of Oncology 27(sup. 2), pp. ii64.3-ii65. (10.1093/annonc/mdw199.214)
- Carrington, R., Spezi, E., Gwynne, S., Dutton, P., Hurt, C. N., Staffurth, J. N. and Crosby, T. 2016. The influence of dose distribution on treatment outcome in the SCOPE 1 oesophageal cancer trial. Radiation Oncology 11, article number: 19. (10.1186/s13014-016-0594-x)
- Carrington, R., Spezi, E., Gwynne, S., Dutton, P., Hurt, C. N., Staffurth, J. N. and Crosby, T. 2016. The influence of radiotherapy treatment method on dose distribution and its relation to patient outcome in the SCOPE 1 oesophageal cancer trial using Type B algorithms. Radiation Oncology (London, England) 11, article number: 19. (10.1186/s13014-016-0594-x)
- Berthon, B. et al. 2015. PETSTEP: Generation of synthetic PET lesions for fast evaluation of segmentation methods. Physica Medica 31(8), pp. 969-980. (10.1016/j.ejmp.2015.07.139)
- Fokas, E. et al. 2015. Comparison of investigator-delineated gross tumor volumes and quality assurance in pancreatic cancer: Analysis of the pretrial benchmark case for the SCALOP trial. Radiotherapy and Oncology 117(3), pp. 432-437. (10.1016/j.radonc.2015.08.026)
- Carrington, R. et al. 2015. The effect of dose escalation on gastric toxicity when treating lower oesophageal tumours: a radiobiological investigation. Radiation Oncology 10, article number: 236. (10.1186/s13014-015-0537-y)
- Alaei, P. and Spezi, E. 2015. Imaging dose from cone beam computed tomography in radiation therapy. Physica Medica 31(7), pp. 647-658. (10.1016/j.ejmp.2015.06.003)
- Fenwick, A. J., Johansson, L., Spezi, E., Evans, W. and Marshall, C. 2015. Metrology for Zr-89 in the clinic [Abstract]. European Journal of Nuclear Medicine and Molecular Imaging 42, pp. S342-S343.
- Fenwick, A., Marshall, C., Spezi, E., Evans, W. and Johansson, L. 2015. Quantitative Imaging of Zr-89 on a pre-clinical PET/CT system [Abstract]. European Journal of Nuclear Medicine and Molecular Imaging 42(S1), pp. S415-S415.
- Carrington, R. et al. 2015. A radiobiological investigation of dose escalation in lower oesophageal tumours with a focus on gastric toxicity. Medical Physics 42(6), pp. 3346-3347. (10.1118/1.4924430)
- Berthon, B., Marshall, C., Holmes, R. and Spezi, E. 2015. A novel phantom technique for evaluating the performance of PET auto-segmentation methods in delineating heterogeneous and irregular lesions. EJNMMI Physics 2(1), article number: 13. (10.1186/s40658-015-0116-1)
- Skripcak, T. et al. 2014. Creating a data exchange strategy for radiotherapy research: Towards federated databases and anonymised public datasets. Radiotherapy and Oncology 113(3), pp. 303-309. (10.1016/j.radonc.2014.10.001)
- Berthon, B. et al. 2014. Intensity modulated radiotherapy treatment of head and neck cancer patients using PET auto-segmentation to delineate primary tumour. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S196-S197.
- D'Arienzo, M. et al. 2014. 90Y-PET imaging after liver radioembolization: from PET calibration to absorbed dose determination using a Monte Carlo approach. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S331-S331.
- Berthon, B., Marshall, C. and Spezi, E. 2014. A predictive model for optimal segmentation of PET images. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S172-S172.
- Bagni, O., Spezi, E., Patterson, N., Filippi, L., D'Arienzo, M., Chiaramida, P. and Scopinaro, F. 2014. A workflow for treatment evaluation of 90Y microspheres SIRT therapy of hepatic lesions based on FDG-PET and Y90-PET. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S255-S255.
- Berthon, B. et al. 2014. A fast positron emission tomography simulator for synthetic lesion smulation.. European Journal of Nuclear Medicine and Molecular Imaging 41, pp. S367-S367.
- Gwynne, S. et al. 2014. Progress towards prospective real-time review of outlining in GI trials at a UK radiation therapy quality assurance center. International Journal of Radiation Oncology*Biology*Physics 90(S1), pp. S734-S735. (10.1016/j.ijrobp.2014.05.2138)
- Rackley, T. et al. 2014. Esophageal delineation - lessons learned from pre-accrual benchmark cases in the UK NeoSCOPE esophageal trial. International Journal of Radiation Oncology - Biology - Physics 90(1), pp. S10-S10. (10.1016/j.ijrobp.2014.05.088)
- Gwynne, S. et al. 2014. Prospective review of outlining in the UK NeoSCOPE esophageal trial. International Journal of Radiation Oncology - Biology - Physics 90(1), pp. S733-S733. (10.1016/j.ijrobp.2014.05.2135)
- Pettinato, C. et al. 2014. Pretherapeutic dosimetry in patients affected by metastatic thyroid cancer using I-124 PET/CT sequential scans for I-131 treatment planning. Clinical Nuclear Medicine 39(8), pp. E367-E374. (10.1097/RLU.0000000000000490)
- Alaei, P., Spezi, E. and Reynolds, M. 2014. Dose calculation and treatment plan optimization including imaging dose from kilovoltage cone beam computed tomography. Acta Oncologica 53(6), pp. 839-844. (10.3109/0284186X.2013.875626)
- Berthon, B., Marshall, C., Evans, M. and Spezi, E. 2014. Evaluation of advanced automatic PET segmentation methods using nonspherical thin-wall inserts. Medical Physics 41, article number: 22502. (10.1118/1.4863480)
- Berthon, B., Marshall, C., Evans, M. and Spezi, E. 2013. Implementation and optimization of automatic 18F-FDG PET segmentation methods. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S299-S299.
- Berthon, B., Marshall, C., Evans, M., Edwards, A. and Spezi, E. 2013. Performance of 18F-FDG PET automated segmentation methods for non-spherical objects. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S236-S237.
- Berthon, B., Holmes, R. B., Marshall, C., Jayaprakasam, V. S., Evans, M. and Spezi, E. 2013. Evaluation of several automatic PET-segmentation algorithms for radiotherapy treatment planning in H&N using a printed sub-resolution sandwich phantom. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S236-S236.
- Pettinato, C. et al. 2013. Negative predictive value of 124I-PET/CT imaging in patients affected by metastatic thyroid cancer and treated with 131I. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S276-S276.
- Pettinato, C. et al. 2013. Salivary gland dosimetry using 124I-PET/CT imaging and MIRD method. European Journal of Nuclear Medicine and Molecular Imaging 40, pp. S125-S126.
- Berthon, B., Marshall, C., Edwards, A., Evans, M. and Spezi, E. 2013. Influence of cold walls on PET image quantification and volume segmentation: A phantom study. Medical Physics 40(8), article number: 82505. (10.1118/1.4813302)
- Azimi, R. et al. 2013. Dosimetric and biological benchmarking of a murine total marrow irradiation platform. Medical Physics 40(6)
- Gwynne, S. et al. 2013. Oesophageal chemoradiotherapy in the UK-current practice and future directions. Clinical Oncology 25(6), pp. 368-377. (10.1016/j.clon.2013.01.006)
- Alaei, P., Spezi, E., Ehler, E. and Dusenbery, K. 2013. Assessing and minimizing the dose From KV cone beam CT to pediatric patients undergoing radiation therapy. Medical Physics 40(6), article number: 151. (10.1118/1.4814220)
- Marcatili, S., Pettinato, C., Daniels, S., Lewis, G., Edwards, P., Fanti, S. and Spezi, E. 2013. Development and validation of RAYDOSE: a Geant4-based application for molecular radiotherapy. Physics in Medicine and Biology 58(8), pp. 2491-2508. (10.1088/0031-9155/58/8/2491)
- Gwynne, S., Spezi, E., Sebag-Montefiore, D., Mukherjee, S., Miles, E., Conibear, J. and Staffurth, J. 2013. Improving radiotherapy quality assurance in clinical trials: assessment of target volume delineation of the pre-accrual benchmark case. British Journal of Radiology 86(1024), article number: 20120398. (10.1259/bjr.20120398)
- Spezi, E. and Leal, A. 2013. Special section: Selected papers from the third European workshop on Monte Carlo treatment planning (MCTP2012) PREFACE. Physics in Medicine and Biology 58(8) (10.1088/0031-9155/58/8/E01)
- Mukherjee, S. et al. 2013. Comparison of investigator-delineated GTV in chemoradiotherapy (CRT) for locally advanced nonmetastatic pancreatic cancer (LANPC): Analysis of the pretrial test case for the SCALOP trial. Journal of Clinical Oncology 31(4), article number: 230.
- Pettinato, C. et al. 2012. Usefulness of I-124 PET/CT imaging to predict absorbed doses in patients affected by metastatic thyroid cancer and treated with I-131. Quarterly journal of nuclear medicine and molecular imaging 56(6), pp. 509-514.
- Gwynne, S. H. et al. 2012. Toward semi-automated assessment of target volume delineation in radiotherapy trials: the SCOPE 1 pretrial test case. International Journal of Radiation Oncology*Biology*Physics 84(4), pp. 1037-1042. (10.1016/j.ijrobp.2012.01.094)
- Berthon, B., Spezi, E., Edwards, A. and Marshall, C. 2012. Quantitative effect of cold plastic walls on 18F-FDG PET images. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S385-S385.
- Berthon, B., Holmes, R. B., Marshall, C. and Spezi, E. 2012. Use of a printed subresolution sandwich phantom for simulation of FDG PET images. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S498-S498.
- Berthon, B., Spezi, E., Marshall, C. and Evans, M. 2012. Comparison of automatic segmentation methods of 18F-FDG PET images for radiation therapy planning in H&N: a phantom study. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S265-S265.
- Shepherd, T. et al. 2012. Design of a benchmark platform for evaluating PET-based contouring accuracy in oncology applications. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S264-S264.
- Marcatili, S. et al. 2012. Monte Carlo based 3D absorbed dose distributions for organs at risk in molecular radiotherapy. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S350-S350.
- Pettinato, C. et al. 2012. Usefulness of 124I PET/CT imaging to predict absorbed doses in patients affected by metastatic thyroid cancer and treated with 131I. European Journal of Nuclear Medicine and Molecular Imaging 39, pp. S202-S203.
- Alaei, P., Spezi, E. and Reynolds, M. 2012. Calculating the dose from KV cone beam CT within and outside the treatment volume using a treatment planning system. Medical Physics 39(6), pp. 3655-3655.
- Spezi, E., Downes, P., Jarvis, R., Radu, E. and Staffurth, J. N. 2012. Patient-specific three-dimensional concomitant dose from cone beam computed tomography exposure in image-guided radiotherapy. International Journal of Radiation Oncology*Biology*Physics 83(1), pp. 419-426. (10.1016/j.ijrobp.2011.06.1972)
- Gwynne, S., Mukherjee, S., Webster, R., Spezi, E., Staffurth, J., Coles, B. and Adams, R. 2012. Imaging for target volume delineation in rectal cancer radiotherapy - A systematic review. Clinical Oncology 24(1), pp. 52-63. (10.1016/j.clon.2011.10.001)
- Alaei, P. and Spezi, E. 2012. Commissioning kilovoltage cone-beam CT beams in a radiation therapy treatment planning system. Journal of Applied Clinical Medical Physics 13(6), pp. 19-33., article number: 3971.
- Gwynne, S. et al. 2011. Inter-observer variation in outlining of pre-trial test case in the SCOPE1 trial: A United Kingdom definitive chemoradiotherapy trial for esophageal cancer. International Journal of Radiation Oncology - Biology - Physics 81(2), pp. S67-S68. (10.1016/j.ijrobp.2011.06.135)
- Marcatili, S. et al. 2011. RAYDOSE: a Geant4 application for 3D Targeted Radionuclide Therapy (TRT) dosimetry. European Journal of Nuclear Medicine and Molecular Imaging 38, pp. S201-S202.
- Spezi, E., Volken, W., Frei, D. and Fix, M. K. 2011. A virtual source model for Kilo-voltage cone beam CT: Source characteristics and model validation. Medical Physics 38(9), pp. 5254-5263. (10.1118/1.3626574)
- Gwynne, S., Webster, R., Adams, R., Mukherjee, S., Spezi, E. and Staffurth, J. 2011. Image guided radiotherapy for rectal cancer - a review. Clinical Oncology 23(3), pp. S37-S37.
- Gwynne, S., Webster, R., Mukherjee, S., Staffurth, J. N., Spezi, E. and Adams, R. 2011. Imaging for rectal cancer radiotherapy - a systematic review. Clinical Oncology 23(3), pp. S37-S37.
- Cufflin, R. S., Spezi, E., Millin, A. E. and Lewis, D. G. 2010. An investigation of the accuracy of Monte Carlo portal dosimetry for verification of IMRT with extended fields. Physics in Medicine and Biology 55(16), pp. 4589-4600. (10.1088/0031-9155/55/16/S12)
- Downes, P., Jarvis, R., Radu, E., Kawrakow, I. and Spezi, E. 2009. Monte Carlo simulation and patient dosimetry for a kilovoltage cone-beam CT unit. Medical Physics 36(9), pp. 4156-4167.
- Downes, P., Yaikhom, G., Giddy, J. P., Walker, D. W., Spezi, E. and Lewis, D. G. 2009. High-performance computing for Monte Carlo radiotherapy calculations. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367(1897), pp. 2607-2617. (10.1098/rsta.2009.0028)
- Downes, P. and Spezi, E. 2009. Simulating oblique incident irradiation using the BEAMnrc Monte Carlo code. Physics in Medicine and Biology 54(7), pp. N93-N100. (10.1088/0031-9155/54/7/N02)
- Cufflin, R. S., Spezi, E. and Lewis, D. G. 2009. IMRT verification using portal dosimetry and a 3D planning system. Clinical Oncology 21(3), pp. 264-265.
- Jarvis, R., Downes, P., Radu, E. and Spezi, E. 2009. Patient dose from the elekta XVI cone-beam CT: Phantom and Monte Carlo study. Clinical Oncology 21(3), pp. 270-270.
- Guido, A. et al. 2009. Combined F-18-FDG-PET/CT imaging in radiotherapy target delineation for head-and-neck cancer. International Journal of Radiation Oncology - Biology - Physics 73(3), pp. 759-763.
- Spezi, E., Downes, P., Radu, E. and Jarvis, R. 2009. Reply to "comment on 'Monte Carlo simulation of an x-ray volume imaging cone beam CT unit'". Medical Physics 36(3), pp. 1040-1040.
- Spezi, E., Downes, P., Radu, E. and Jarvis, R. 2009. Monte Carlo simulation of an x-ray volume imaging cone beam CT unit. Medical Physics 36(1), pp. 127-136. (10.1118/1.3031113)
- Palleri, F., Baruffald, F., Angelini, A. L., Ferri, A. and Spezi, E. 2008. Monte Carlo characterization of materials for prosthetic implants and dosimetric validation of Pinnacle(3) TPS. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 266(23), pp. 5001-5006. (10.1016/j.nimb.2008.08.013)
- Spezi, E., Angelini, A. L., Romani, F., Guido, A., Bunkheila, F., Ntreta, M. and Ferri, A. 2008. Evaluating the influence of the Siemens IGRT carbon fibre tabletop in head and neck IMRT. Radiotherapy and Oncology 89(1), pp. 114-122. (10.1016/j.radonc.2008.06.011)
- Spezi, E. and Lewis, G. 2008. An overview of Monte Carlo treatment planning for radiotherapy. Radiation Protection Dosimetry 131(1), pp. 123-129. (10.1093/rpd/ncn277)
- Spezi, E. 2007. Status of MCTP in Europe. Radiotherapy and Oncology 84, pp. S6-S7.
- Buettner, F., Spezi, E., Paganetti, H. and Seco, J. 2007. Dosimetric uncertainties in IMRT QA in plastic phantoms due to CT calibration. Medical Physics 34(6), pp. 2442-2442.
- Vanderstraeten, B. et al. 2007. Conversion of CT numbers into tissue parameters for Monte Carlo dose calculations: a multi-centre study. Physics in Medicine and Biology 52(3), pp. 539-562. (10.1088/0031-9155/52/3/001)
- Spezi, E. and Ferri, A. 2007. Dosimetric characteristics of the siemens IGRT carbon fiber tabletop. Medical Dosimetry 32(4), pp. 295-298.
- Spezi, E., Angelini, A. L. and Ferri, A. 2007. Monte Carlo simulation of the SIEMENS IGRT carbon fibre tabletop. Journal of Physics: Conference Series 74, pp. U145-U150. (10.1088/1742-6596/74/1/021017)
- Spezi, E., Palleri, F., Angelini, A. L., Ferri, A. and Baruffaldi, F. 2007. Characterization of materials for prosthetic implants using the BEAMnrc Monte Carlo code. Journal of Physics: Conference Series 74, pp. U141-U144. (10.1088/1742-6596/74/1/021016)
- Deasy, J. et al. 2006. The computational environment for radiotherapy research: New tools for multi-modality imaging, treatment plan comparisons, and plan evaluations. Medical Physics 33(6), pp. 2140-2140.
- Spezi, E. and Lewis, D. G. 2006. Gamma histograms for radiotherapy plan evaluation. Radiotherapy and Oncology 79(2), pp. 224-230. (10.1016/j.radonc.2006.03.020)
- Spezi, E., Angelini, A. L. and Ferri, A. 2006. A multiple acquisition sequence for IMRT verification with a 2D ion chamber array. Medical Dosimetry 31(4), pp. 269-272.
- Spezi, E., Angelini, A. L., Romani, F. and Ferri, A. 2005. IMRT plan verification using a 2D ion chamber array. Radiotherapy and Oncology 76, pp. S176-S177.
- Cora, S. et al. 2005. Evaluation of the treatment planning system of the Cyberknife by means of a comparison to Monte Carlo calculation. Radiotherapy and Oncology 76, pp. S96-S96. (10.1016/S0167-8140(05)81172-7)
- Spezi, E., Angelini, A. L., Romani, F. and Ferri, A. 2005. Characterization of a 2D ion chamber array for the verification of radiotherapy treatments. Physics in Medicine and Biology 50(14), pp. 3361-3373. (10.1088/0031-9155/50/14/012)
- Alaly, J., Zakarian, K., Lindsay, P., El Naqa, I., Hope, A., Spezi, E. and Deasy, I. 2005. Software tools for 4-D and adaptive treatment planning data visualization and manipulation (CERR version 3). Medical Physics 32(6), pp. 2033-2033.
- Alaly, J., Deasy, J., Zakarian, C., Hope, A., Spezi, E., Bosch, W. and Purdy, J. 2004. Modeling radiotherapy treatment outcomes: Open-source data collection, database, and plan review tools. Medical Physics 31(6), pp. 1901-1902.
- Chin, P. W., Lewis, D. G. and Spezi, E. 2004. Correction for dose-response variations in a scanning liquid ion chamber EPID as a function of linac gantry angle. Physics in Medicine and Biology 49(8), pp. N93-N103. (10.1088/0031-9155/49/8/N01)
- Spezi, E. and Lewis, D. G. 2004. Full forward Monte Carlo calculation of portal dose from MLC collimated treatment beams (vol 47, pg 377, 2002). Physics in Medicine and Biology 49(2), pp. 355-355.
- Spezi, E. and Deasy, J. 2003. An open source DICOM-RT/MATLAB based computational platform for radiotherapy research. Radiotherapy and Oncology 68(s1), pp. S106.
- Spezi, E., Lewis, D. G., Millin, A. and Cuffin, R. 2003. MC based QA of IMRT. Radiotherapy and Oncolocy 68(S1), pp. S46-S46. (10.1016/S0167-8140(03)80135-4)
- Chin, P. W., Spezi, E. and Lewis, D. G. 2003. Monte Carlo simulation of portal dosimetry on a rectilinear voxel geometry: a variable gantry angle solution. Physics in Medicine and Biology 48(16), pp. N231-N238. (10.1088/0031-9155/48/16/401)
Book sections
- Sykes, J., Alaei, P. and Spezi, E. 2017. Imaging dose in radiation therapy. In: Mijnheer, B. ed. Clinical 3D Dosimetry in Modern Radiation Therapy. CRC Press, pp. 561-588.
Books
- Spezi, E. and Bray, M. eds. 2024. Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press. (10.18573/conf1)
Conferences
- Smith, R. L. et al. 2024. From radiomics to deep learning: Leveraging gramian matrix features in CNNs for NSCLC survival analysis. Presented at: 2024 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room Temperature Semiconductor Detector Conference, Tampa, FL, USA, 26 October - 2 November 20242024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD). IEEE pp. 1-2., (10.1109/nss/mic/rtsd57108.2024.10657697)
- Spezi, E. and Bray, M. 2024. Foreword. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press, (10.18573/conf1.a)
- Duman, A., Powell, J., Thomas, S., Sun, X. and Spezi, E. 2024. Generalizability of deep learning models on brain tumour segmentation. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 3-5., (10.18573/conf1.b)
- Cagni, E., Trojani, V., Botti, A., Lewis, A. and Spezi, E. 2024. A tool for radiotherapy plan evaluation analysis: generalise Uniform Ideal Dose (gUIDE). Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 6-10., (10.18573/conf1.c)
- Doherty, C., Duman, A., Chuter, R., Hutton, M. and Spezi, E. 2024. Investigating the feasibility of MRI auto-segmentation for Image Guided Brachytherapy. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 11-14., (10.18573/conf1.d)
- Duman, A., Powell, J., Thomas, S. and Spezi, E. 2024. Evaluation of radiomic analysis over the comparison of machine learning approach and radiomic risk score on glioblastoma. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 19-22., (10.18573/conf1.f)
- Foster, I., Spezi, E. and Wheeler, P. 2024. Inter-planner variability in expert driven Pareto-guided automated planning solutions. Presented at: Cardiff University Engineering Research Conference 2023, Cardiff, UK, 12-14 July 2023 Presented at Spezi, E. and Bray, M. eds.Proceedings of the Cardiff University Engineering Research Conference 2023. Cardiff: Cardiff University Press pp. 23-26., (10.18573/conf1.g)
- Alsyed, E., Smith, R., Paisey, S., Marshall, C. and Spezi, E. 2021. A self organizing map for exploratory analysis of PET radiomic features. Presented at: 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Boston, MA, USA, 31 October -7 November 20202020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, (10.1109/NSS/MIC42677.2020.9507846)
- Spezi, E. et al. 2020. Metabolic tumour volume segmentation for oesophageal cancer on hybrid PET/CT using convolutional network architecture. Presented at: 33rd Annual European Association of Nuclear Medicine Congress (EANM 2020), Virtual, 22-30 October 2020European Journal of Nuclear Medicine and Molecular Imaging, Vol. 47. Vol. S1. Springer Verlag (Germany) pp. 5481-5482., (10.1007/s00259-020-04988-4)
- Parkinson, C. et al. 2020. Qualitative assessment of oesophageal cancer metabolic tumour volumes delineated by an artificial intelligence algorithm. Presented at: NCRI Virtual Showcase 2020, Virtual, 2-3 November 2020.
- Alsyed, E., Smith, R., Marshall, C., Paisey, S. and Spezi, E. 2019. The statistical influence of imaging time and segmentation volume on PET radiomic features: A preclinical study. Presented at: 2019 IEEE NSS-MIC, 26 October - 2 November 20192019 IEEE NSS-MIC. IEEE
- Alsyed, E., Smith, R., Marshall, C., Paisey, S. and Spezi, E. 2019. Stability of PET radiomic features: A preclinical study [Abstract]. Presented at: Annual Congress of the European Association of Nuclear Medicine, Barcelona, Spain, 12-16 Oct 2019.
- Ackerley, I. et al. 2019. Using deep learning to detect esophageal lesions in PET-CT scans. Presented at: SPIE Medical Imaging 2019, San Diego, California, USA, 16-21 February 2019 Presented at Gimi, B. and Krol, A. eds.Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging. SPIE, (10.1117/12.2511738)
- Parkinson, C. et al. 2018. Dependency of patient risk stratification on PET target volume definition in oesophageal cancer. Presented at: ESTRO, Barcelona, Spain, 20-24 April 2018.
- Parkinson, C., Whybra, P., Staffurth, J., Marshall, C. and Spezi, E. 2018. ATLAAS - Investigation into the incorporation of morphological data on automated segmentation. Presented at: EANM Congress 2018: European Association of Nuclear Medicine., Dusseldorf, Germany, 12-18 October 2018.
- Parkinson, C. et al. 2018. Target volume delineation of FDG PET images post one cycle of induction chemotherapy in oropharyngeal cancer using advanced automated segmentation methods. Presented at: ESTRO 37, Barcelona, 20-24 April 2018.
- Dabkowski, A., Paisey, S. J., Spezi, E., Chester, J. and Marshall, C. 2017. Optimization of Zirconium-89 production in IBA cyclone 18/9 cyclotron with COSTIS solid target system. Presented at: WTTC16: Proceedings of the 16th International Workshop on Targetry and Target Chemistry, Santa Fe, NM, USA, 29 August–1 September 2016 Presented at Engle, J. W. et al. eds.AIP Conference Proceedings, Vol. 1845. Melville, NY: AIP pp. 20005., (10.1063/1.4983536)
- Yaikhom, G., Giddy, J. P., Walker, D. W., Downes, P., Spezi, E. and Lewis, D. G. 2008. A distributed simulation framework for conformal radiotherapy. Presented at: 22nd IEEE International Symposium on Parallel & Distributed Processing, Miami, FL, USA, 14-18 April 2008Proceedings of the IEEE International Symposium on Parallel and Distributed Processing, 2008 (IPDPS 2008), Miami, FL, 14-18 April 2008. Piscataway, NJ: IEEE, (10.1109/IPDPS.2008.4536471)
Monographs
- Gleisner, K. S. et al. 2017. Treatment planning for molecular radiotherapy: potential and prospects. European Association of Nuclear Medicine. Available at: http://www.eanm.org/publications/idtf-report
- Zwanenburg, A. et al. 2020. The Image Biomarker Standardization Initiative: standardized quantitative radiomics for high throughput image-based phenotyping. Radiology 295(2), pp. 328-338. (10.1148/radiol.2020191145)
- Deist, T. M. et al. 2020. Distributed learning on 20 000+ lung cancer patients - The Personal Health Train. Radiotherapy and Oncology 144, pp. 189-200. (10.1016/j.radonc.2019.11.019)
- Piazzese, C., Foley, K., Whybra, P., Hurt, C., Crosby, T. and Spezi, E. 2019. Discovery of stable and prognostic CT-based radiomic features independent of contrast administration and dimensionality in oesophageal cancer. PLoS ONE 14(11), article number: e0225550. (10.1371/journal.pone.0225550)
- Whybra, P., Parkinson, C., Foley, K., Staffurth, J. and Spezi, E. 2019. Assessing radiomic feature robustness to interpolation in 18F-FDG PET imaging. Scientific Reports 9(1), article number: 9649. (10.1038/s41598-019-46030-0)
- Foley, K. G. et al. 2018. Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer. European Radiology 28, pp. 428-436. (10.1007/s00330-017-4973-y)
- Berthon, B. et al. 2017. Toward a standard for the evaluation of PET-Auto-Segmentation methods following the recommendations of AAPM task group No. 211: Requirements and implementation. Medical Physics 44(8), pp. 4098-4111. (10.1002/mp.12312)
- Hatt, M. et al. 2017. Classification and evaluation strategies of auto-segmentation approaches for PET: report of AAPM task group No. 211. Medical Physics 44(6), pp. e1-e42. (10.1002/mp.12124)
- Berthon, B., Marshall, C., Evans, M. and Spezi, E. 2016. ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography. Physics in Medicine and Biology 61(13), pp. 4855-4869. (10.1088/0031-9155/61/13/4855)
- Skripcak, T. et al. 2014. Creating a data exchange strategy for radiotherapy research: Towards federated databases and anonymised public datasets. Radiotherapy and Oncology 113(3), pp. 303-309. (10.1016/j.radonc.2014.10.001)
- Marcatili, S., Pettinato, C., Daniels, S., Lewis, G., Edwards, P., Fanti, S. and Spezi, E. 2013. Development and validation of RAYDOSE: a Geant4-based application for molecular radiotherapy. Physics in Medicine and Biology 58(8), pp. 2491-2508. (10.1088/0031-9155/58/8/2491)
Research
Life Imaging and Data Analytics
Life Imaging and Data Analytics is a team with multi-disciplinary skills established at the Cardiff University School of Engineering. LIDA is led by Dr Emiliano Spezi (Professor of Healthcare Engineering) and consists of post-doctoral research associates and PhD students. The research interest of the group spans from advanced medical image processing and radiomics to advanced computer modelling in radiation oncology. In the field of medical imaging the team has developed ATLAAS, an award-winning machine learning based tool which can be used to select the optimal Positron Emission Tomography automated segmentation method for radiotherapy treatment planning.
Furthermore, we have established a programme of image analysis techniques, including segmentation, texture, shape and intensity analysis and wavelet analysis, combining this with clinical and genomic data to produce diagnostic, prognostic and predictive models. We have a very intensive programme of development of radiomics algorithms, which are advanced imaging techniques that allow non-invasive, high-throughput, three-dimensional extraction of large numbers of descriptive features from any volume of interest. LIDA is a founding member of the Image Biomarker Standardisation Initiative (IBSI) to develop standardised radiomics algorithms and reporting guidelines that can make radiomics analyses reproducible and comparable. We developed SPAARC radiomics, a tool for multimodal quantitative image analysis incorporating 164 features all compliant and validated in accordance with the IBSI recommendations. Features include morphology, intensity-based statistics, intensity and intensity volume histograms and grey level matrixes. This is a selected list of publications featuring SPAARC radiomics:
- Palumbo, D.et al. 2021. Prediction of early distant recurrence in upfront resectable pancreatic adenocarcinoma: A multidisciplinary, machine learning-based approach. Cancers13(19), article number: 4938. (10.3390/cancers13194938)
- Mori, M.et al. 2020. Training and validation of a robust PET radiomic-based index to predict distant-relapse-free-survival after radio-chemotherapy for locally advanced pancreatic cancer. Radiotherapy and Oncology153, pp. 258-264. (10.1016/j.radonc.2020.07.003)
- Zwanenburg, A.et al. 2020. The Image Biomarker Standardization Initiative: standardized quantitative radiomics for high throughput image-based phenotyping. Radiology295(2), pp. 328-338. (10.1148/radiol.2020191145)
- Piazzese, C.et al. 2019. Discovery of stable and prognostic CT-based radiomic features independent of contrast administration and dimensionality in oesophageal cancer. PLoS ONE14(11), article number: e0225550. (10.1371/journal.pone.0225550)
- Whybra, P.et al. 2019. Assessing radiomic feature robustness to interpolation in 18F-FDG PET imaging. Scientific Reports9(1), article number: 9649. (10.1038/s41598-019-46030-0)
Watch a video on radiomics research: radiomics reseach
(credit: MAASTRO Clinic).
In addition, we are building an IT infrastructure and standardised algorithms that can be included in any machine learning training and validation process. The idea is that any developed and validated prognostic/predictive model can be included in libraries as part of a Decision Support System that can be used in real time by clinicians in the clinic. LIDA and Velindre University NHS Trust were the recipients of the NHS Innovation Award 2018 (Welsh Government, Efficiency Through Technology programme). As part of the “AI Solutions for Personalised Radiotherapy” (ASPIRE) project LIDA, Velindre and Intel Corporation are working on a project aimed at training and validating AI software for the automated delineation of tumour volumes on anatomical and functional imaging modalities. The training is designed to be performed on a large retrospective dataset of labelled clinical scans and will be validated on a prospective dataset acquired throughout the duration of the project. In addition to reducing dramatically the workload in radiotherapy planning, we expect AI auto-segmented volumes to be of equal quality and more consistent than those outlined manually, which our research group have investigated extensively. The integration of AI in the clinical radiotherapy workflow will prepare the ground for future developments related to high throughput medical image analysis (radiomics), development of a fully automated radiotherapy workflow (from AI-based automated segmentation to AI-based automated planning), and development of decision support system for clinicians to use in clinical practice. LIDA and Velindre are also partners on a project (FAST-RTP2) aimed at including AI in the process of automating the preparation of external radiotherapy plans.
Machine learning applications for personalized medicine are highly dependent on access to sufficient data. Large datasets from a broad range of different populations representing the variation in the entire cancer patient population need to be acquired and used to learn prediction models. In LIDA we use a distributed learning approach which was designed to address ethical and legal boundaries and to limit the impact of data privacy collaboration between research institutes. Cardiff University and The Christie NHS Foundation Trust are the only two UK centers participating to the European Computer Assisted Theragnostics project (EuroCAT) project and to the Community in Oncology for Rapid Learning (CORAL). CORAL includes almost 30 cancer centres worldwide (Netherlands, USA, UK, India, China, South-Africa, Australia, Italy, Germany, Belgium, Canada, Denmark). CORAL is based on a distributed approach in which data do not cross the firewall, where data is made semantically interoperable locally, and where centres allow applications to enter their firewall and use their data to answer a particular research questions, without any patient identifiable information being exposed/shared. Applications are focused on machine learning and modelling to predict for instance overall survival in a particular tumour site.
Watch a video on distributed learning in radiation oncology and on personal health trains:
distributed learning in radiation oncology
(credit: MAASTRO Clinic).
Members of the LIDA team
Dr Philip Whybra (Research associate)
Miss Iona Foster (PhD candidate)
Mr Emad Alsyed (PhD candidate)
Miss Elisabetta Cagni (PhD candidate)
Mr Kerim Duman (PhD candidate)
Associated members of the LIDA team
Prof John Staffurth (Professor Cinical Oncology, Cardiff University School of Medicine and Velindre Cancer Centre)
Dr Kieran Foley (Consultant Radiologist, Velindre Cancer Centre)
Contracts
| Title | Role | Sponsor | Value | Duration |
|---|---|---|---|---|
| ASPIRE: AI Solutions for Personalised Radiotherapy (Efficiency Through Technology programme) | Co-PI | Welsh Government and Intel Corp | 198,030 | 2018-2020 |
| DOTATER+: Advanced Personalised 3D Dosimetry for a clinical trial in peptide radionuclide therapy | PI | Cancer Research Wales | 80,341 | 2015-2018 |
| ARENA: Extension of RTTQA outlining activity into the educational arena | Co-PI | Velindre NHS Trust | 340,200 | 2018-2021 |
| PEARL: PET-based Adaptive Radiotherapy Clinical Trial | Co-I | Cancer Research Wales | 720,000 | 2017-2021 |
| FAST-RTP2: Implementing automated techniques in radiotherapy treatment planning | Co-I | Velindre NHS Trust | 76,430 | 2018-2021 |
| STORM_GLIO: Developing Radiomics as an Imaging Biomarker in High Grade Glioma | Co-PI | Velindre NHS Trust | 37,835 | 2018-2021 |
TEXRAD: Establishing image derived prognostic and predictive biomarkers of radiotherapy treatments and assessing treatment response using texture analysis | Co-PI | Velindre NHS Trust - Moondance Foundation | 81,540 | 2017-2020 |
Past grants and contracts
Title: Informatics Platform for Advanced Cancer Imaging Research
Value: £18,638
Role: Principal Investigator
Period: 2017
Funding body: Data Innovation and Research Institute
Title: Raydose GUI development
Value: £26,646
Role: Principal Investigator
Period: 2015-2016
Funding body: EURAMET - Velindre NHS Trust
Title: Advanced FDG PET-CT target volume delineation in Intensity Modulated Radiotherapy planning for Head and Neck cancers
Value: £45,000
Role: Principal Investigator
Period: 2014-2015
Funding body: Cancer Research Wales
Title: 3-D Printed sources for High-Resolution Molecular Imaging
Value: £10,000
Role: Principal Investigator
Period: 2014-2015
Funding body: Velindre NHS Trust
Title: RAYDOSEPLAN a multimodality platform for treatment planning research in molecular radiotherapy
Value: €242,000
Role: Principal Investigator
Period: 2012-2015
Funding body: European Association of National Metrology Institutes (EURAMET)
Title: Adaptive Image-Guided Radiotherapy Strategies for Bladder and Cervical Cancer to Enable Dose Escalation and Reduce Late Toxicity
Value: £60,000
Role: Co-Investigator
Period: 2014-2015
Funding body: Cancer Research Wales
Title: XVI5IEC: Evaluation of patient dose to skin and eye lens for default CBCT settings
Value: £8,000
Role: Principal Investigator
Period: 2013
Funding body: Elekta Ltd Crawley UK
Title: XVIoptimal5: Evaluation of patient dose reduction and image quality for new Cone Beam CT settings
Value: £8,100
Role: Principal Investigator
Period: 2013
Funding body: Elekta Ltd Crawley UK
Title: MOZART: Parameters affecting tumour control and toxicity in oesophageal cancer: a multi-dimensional outcome analysis
Value: £67,000
Role: Principal Investigator
Period: 2012-2015
Funding body: Cancer Research Wales
Title: POSITIVE: Optimisation of positron emission tomography based target volume delineation in Head and Neck radiotherapy
Value: £81,000
Role: Principal Investigator
Period: 2011-2014
Funding body: Cancer Research Wales
Title: RAYDOSE: Assessment of patient dose using novel radioisotopes in Molecular Targeted Radiotherapy
Value: £170,000
Role: Principal Investigator
Period: 2010-2012
Funding body: Wales Office of Research and Development for Health and Social Care (WORD)
Title: A Comparison of Convolution/Superposition and Monte Carlo methods for conformal radiotherapy
Value: £80,000
Role: Co-Investigator
Period: 2009-2014
Funding body: Cancer Research Wales
Title: XVIctdi: Cone Beam CT dosimetry using an optimised phantom
Value: £20,000
Role: Principal Investigator
Period: 2009-2014
Funding body: Elekta Ltd Crawley UK
Title: Extending the RTGrid portal to the wider user community
Value: £52,000
Role: Co-Investigator
Period: 2009
Funding body: JISC ENGAGE e-Infrastructure programme
Title: MRI in radiotherapy planning
Value: £10,000
Role: Principal Investigator
Period: 2009
Funding body: Velindre NHS Trust
Title: The application of GafChromic film in routine and non routine quality control methods in radiotherapy physics
Value: £4,000
Role: Principal Investigator
Period: 2007
Funding body: Velindre NHS Trust
Teaching
In addition to providing undergraduate project, dissertation and essay supervision, I am Module Organiser for the following modules at the School of Engineering:
Between 2016 and 2021 I was also module organiser for the following module at the School of Physics and Astronomy:
- PX3247: Radiation for Medical Therapy (BSc)
Biography
Education
2003: PhD (Medical Physics), University of Wales College of Medicine, Cardiff, UK
1998: MSc (Clinical Scientist), University of Bologna, Bologna, Italy
1996: Laurea (Physics), University of Bologna, Bologna, Italy
Honours and awards
Winner of the European Radiology ESGAR Silver Award 2018 (awarded in 2019)
- Foley et al Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer. Eur Radiol. 2018 Jan;28(1):428-436
Winner of the ESTRO-Varian Research Award 2019
- Deist et al Distributed learning on 20 000+ lung cancer patients, Radiother Oncol (2019) Vol 133 Supp. 1, S287-8 https://www.estro.org/Congresses/ESTRO-38/Awards
Winner of the journal’s Best Paper Award 2018: European Journal of Nuclear Medicine and Molecular Imaging Physics
- Sjögreen Gleisner et al Variations in the practice of molecular radiotherapy and implementation of dosimetry: results from a European survey, EJNMMI Physics (2017) 4:28 https://doi.org/10.1186/s40658-017-0193-4
Winner of the Burgen Scholarship Award 2016: Academia Europaea
- Computational Models in Funtional Imaging and Radiation Therapy
Winner of the Best Physics Poster Award 2016: ESTRO
- Berthon et al Towards standardisation of PET-autosegmentaion with the ATLAAS machine learning algorithm, Radiother. Oncol. (2016) 119 (Supp 1): S452
Winner of the Manufactures' Award for Innovation 2015: IPEM
- ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography, Phys. Med. Biol. (2016) Jul 7;61(13):4855-69
Winner of IPEM/AAPM Travel award: IPEM/AAPM
- A Monte Carlo investigation of the accuracy of intensity modulated radiotherapy, Med. Phys. (2004) https://doi.org/10.1118/1.164451
Professional memberships
Fellow Member of the Institute of Physics and Engineering in Medicine (IPEM)
Chartered Member of the Instutte of Physics (IoP)
State Registered Clinical Scientist: Health and Care Professions Council (HCPC)
Academic positions
External examiner (research degrees): University of The Free State (South Africa), University of Cape Town (South Africa), Swansea University, Swansea (United Kingdom), Universitat Politècnica de Catalunya, Barcelona (Spain), National University of Ireland, Galway (Ireland), University of London, London (United Kingdom), Niels Bohr Institute, Copenhagen (Denmark).
Committees and reviewing
Current duties
Chair of the Research Ethics Committe of Cardiff University School of Engineering
Associate Editor of the European Journal of Medical Physics (Physica Medica), Elsevier
Member of the Welsh Government - Welsh Scientific Advisory Committee
Past duties
Vice-Chair of the American Association of Physicists in Medicine (AAPM) Task Group 211 Classification, Advantages and Limitations of the Auto-Segmentation Approaches for PET
Chair of theNational Cancer Research Institute (NCRI) Radiotherapy Trials QA Database solutions and IT subgroup
Member of the NCRI Clinical and Translational Radiotherapy Research Working Group (CTRad) Workstream 4: New Technology, Physics and Quality Assurance
Supervisions
Areas of interest
I am available to supervise Post Graduate Research students in the following areas:
- MEDICAL IMAGE ANALYSIS
- RADIOMICS
- MACHINE LEARNING IN RADIATION ONCOLOGY
- MONTE CARLO MODELLING OF RADIATION TRANSPORT
- MOLECULAR RADIOTHERAPY DOSIMETRY
- ADVANCED RADIOTHERAPY TECHNIQUES
PubMed search of publications by Professor Spezi (link).
Opportunities for Post Graduate Research
If you are interested in enrolling on Postgraduate Research at the School og Engineering, contact the PGR Enquiries Team to know more about all current opportunities.
Current PhD projects
|
Title |
Student |
Status |
Degree |
Type |
Role |
|
Non-invasive radiomic classifiers of radiotherapy response in rectal cancer |
Yiwen Dong |
Current |
PhD |
Full time |
Main supervisor |
|
Improving radiotherapy plan quality through auditing with automated planning |
Megan Barrell |
Current |
PhD |
Part time |
Main supervisor |
|
Radiomics enhanced deep learning-based classifier to improve survival in glioblastoma multiforme |
Kerim Duman |
Current |
PhD |
Full time |
Main supervisor |
|
Microstructural imaging of the tumour microenvironment: towards virtual biopsy of prostate cancer. |
Solanki Mitra |
Current |
PhD |
Full time |
Main supervisor |
|
Integration of Engineered and Deep Learning Radiomics Imaging Features to Characterise Tumour heterogeneity in Non-Small Cell Lung Cancer |
Mengcheng Li |
Current |
PhD |
Full time |
Main supervisor |
|
Artificial Intelligence with Human In The Loop for Automated Medical Image Contouring. |
Faye Warren |
Current |
PhD |
Full time |
Co-supervisor |
|
Non-invasive characterisation of brain cancer tissue microstructure from MRI using Deep Learning |
Adam Threlfall |
Current |
PhD |
Full time |
Co-supervisor |
|
Artificial Intelligence assisted grading of prostate cancer progression in patient biopsies with novel tissue labelling biomarkers. |
Michail Papachristos |
Current |
PhD |
Full time |
Co-supervisor |
Current supervision
Past projects
Implementing Automated Techniques in Radiotherapy Treatment Planning, PhD, Iona Foster
PET Image Texture Analysis and Radiotherapy, PhD, Emad Alsyed
Automated Image-Guided Radiotherapy Planning, PhD, Elisabetta Cagni
Application of Texture Analysis to Identify Prognostic Biomarkers for the Optimisation of Radiotherapy Treatments, PhD, Philip Whybra
Advanced Personalised 3D Dosimetry for a Clinical Trial in Peptide Radionuclide Therapy, PhD, Salvatore Berenato
Advanced Automated Segmentation of PET in Radiotherapy, PhD, Craig Parkinson
Parameters Affecting Tumour Control and Toxicity in Oesophageal Cancer: a Multi-dimensional Outcome Analysis, PhD, Rhys Carrington
Outlining Variantion in Upper Gastrintestinal Cancer Radiotherapy Clinical Trials, MD, Sarah Swynne
Development of Techniques for Verification of Advanced Radiotherapy by Portal Dosimetry, PhD, Yasmin Radzi
Radiotherapy dose calculation in oesophageal cancer: comparison of analytical and Monte Carlo methods, PhD, Dewi Johns
Optimisation of Positron Emission Tomography Based Target Volume Delineation in Head and Neck Radiotherapy, PhD, Beatrice Berthon
Contact Details
espezi@cardiff.ac.uk
+44 29208 76521
Queen's Buildings, Room S/2.05, 5 The Parade, Newport Road, Cardiff, CF24 3AA
+44 29208 76521
Queen's Buildings, Room S/2.05, 5 The Parade, Newport Road, Cardiff, CF24 3AA
Research themes
Specialisms
- Applied computing
- Radiotherapy Physics
- radiomics
- medical image analysis
- Biomedical imaging
