Christopher Thompson
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Christopher Thompson has a total of 26 co-authors. Here are the top co-authors by number of shared publications:
A. Choudhury
Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, UK; Division of Cancer Sciences, University of Manchester, Manchester, UK
1 shared publication- Andrew Frederick Scarsbrook
Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
1 shared publication - Ane Lindegaard Appelt
Department of Oncology, Centre for Cancer and Organ Diseases, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark; Department of Health Technology, Technical University of Denmark, Copenhagen, Denmark
1 shared publication - Ann Henry
Leeds Institute of Medical Research, University of Leeds, Leeds, UK
1 shared publication - Catharine Mary Louise West
The University of Manchester, Manchester, United Kingdom
1 shared publication - Christopher J H Pagett
Medical Physics, Leeds Teaching Hospitals NHS Trust, Leeds Cancer Centre, Leeds, England, LS7 9TF, United Kingdom of Great Britain and Northern Ireland
1 shared publication
Latest Publications
- Open Access
- 26 February 2026
- Published by IOP Publishing in Physics in Medicine & Biology
- Vol. 71 (6)
Robust organ mapped dose: using multiple image registrations to identify deformation uncertainty in radiation dose mapping
Objective To assist with reirradiation (reRT) treatment planning, we propose a robust organ-mapped dose (ROAD) method for cumulative dose estimation within critical organs-at-risk (OARs), incorporating deformable image registration (DIR) uncertainty via a dose resampling kernel derived from organ-specific independent DIRs. Approach The discordance among three distinct DIRs, each of unknown accuracy, was used to estimate spatial uncertainty. For each voxel within an OAR, the discordance generated a per-voxel dose-resampling kernel. Two additional kernel expansions incorporated uncertainties not captured by inter-DIR discordance: the first ensured all returned dose originated within the OAR, while the second ensured all OAR dose voxels were sampled. The maximum dose within the kernel–OAR intersection was assigned to each voxel to yield a robust dose map. The approach was demonstrated for pelvic, head-and-neck, and thoracic reRT cases using DIR-mapped background doses. Kernel generation was analysed by tracking kernel magnitude (KM) and its correlation with mean distance to agreement (MDA) and Hausdorff distance (HD). Resulting dose distributions were compared with baseline mapped doses and a fixed-kernel robustness method. Main Results Analysis confirmed generally well-chosen DIRs but revealed residual errors beyond DIR discordance, detected by the additional kernel expansions. ROAD produced dose distributions comparable to fixed-kernel methods under low deformation uncertainty but demonstrated greater robustness in regions with large anatomical variation, particularly in the pelvis. ROAD reduced instances where mapped near-maximum doses underestimated original values, without increasing overall dose, by capturing uncertainty from organ filling and positional changes missed by fixed-kernel accumulation. Significance Accurate cumulative dose estimation is critical for safe and effective reirradiation planning. The proposed ROAD framework explicitly incorporates voxel-level DIR uncertainty, providing a more reliable OAR dose estimate in regions with substantial anatomical change. This enhances confidence in reirradiation dose assessment and offers a practical, robust tool for clinical evaluation of cumulative organ doses.
- 26 February 2026
- Published by IOP Publishing in Physics in Medicine & Biology
- Vol. 71 (6)
Open AccessRobust organ mapped dose: using multiple image registrations to identify deformation uncertainty in radiation dose mapping
Objective To assist with reirradiation (reRT) treatment planning, we propose a robust organ-mapped dose (ROAD) method for cumulative dose estimation within critical organs-at-risk (OARs), incorporating deformable image registration (DIR) uncertainty via a dose resampling kernel derived from organ-specific independent DIRs. Approach The discordance among three distinct DIRs, each of unknown accuracy, was used to estimate spatial uncertainty. For each voxel within an OAR, the discordance generated a per-voxel dose-resampling kernel. Two additional kernel expansions incorporated uncertainties not captured by inter-DIR discordance: the first ensured all returned dose originated within the OAR, while the second ensured all OAR dose voxels were sampled. The maximum dose within the kernel–OAR intersection was assigned to each voxel to yield a robust dose map. The approach was demonstrated for pelvic, head-and-neck, and thoracic reRT cases using DIR-mapped background doses. Kernel generation was analysed by tracking kernel magnitude (KM) and its correlation with mean distance to agreement (MDA) and Hausdorff distance (HD). Resulting dose distributions were compared with baseline mapped doses and a fixed-kernel robustness method. Main Results Analysis confirmed generally well-chosen DIRs but revealed residual errors beyond DIR discordance, detected by the additional kernel expansions. ROAD produced dose distributions comparable to fixed-kernel methods under low deformation uncertainty but demonstrated greater robustness in regions with large anatomical variation, particularly in the pelvis. ROAD reduced instances where mapped near-maximum doses underestimated original values, without increasing overall dose, by capturing uncertainty from organ filling and positional changes missed by fixed-kernel accumulation. Significance Accurate cumulative dose estimation is critical for safe and effective reirradiation planning. The proposed ROAD framework explicitly incorporates voxel-level DIR uncertainty, providing a more reliable OAR dose estimate in regions with substantial anatomical change. This enhances confidence in reirradiation dose assessment and offers a practical, robust tool for clinical evaluation of cumulative organ doses.
- Open Access
- 19 February 2026
- Published by Elsevier in Clinical Oncology
- Vol. 52, 104085
Reirradiation Options for Previously Irradiated Prostate Cancer: Is It Feasible to Randomise Between Treatment With Stereotactic Body Radiotherapy (SBRT) Versus High-Dose-Rate Brachytherapy?
- 19 February 2026
- Published by Elsevier in Clinical Oncology
- Vol. 52, 104085
Open AccessReirradiation Options for Previously Irradiated Prostate Cancer: Is It Feasible to Randomise Between Treatment With Stereotactic Body Radiotherapy (SBRT) Versus High-Dose-Rate Brachytherapy?