Extending longitudinal field-of-view for cone-beam CT based on a novel surface-aware diffusion model.
Authors
Affiliations (14)
Affiliations (14)
- School of Physics, Peking University, Beijing, Beijing, 100190, China.
- Beihang University, Xueyuan Road, Beijing, Beijing, 100091, China.
- Medical Technology College, Hebei Medical University, Shijiazhuang 050031, China, Shijiazhuang 050031, China, Shijiazhuang, 050031, China.
- Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China, Beijing, 100191, China.
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142 China, Haidian District, Beijing, 100142, China.
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Beijing Cancer Hospital, Beijing 100142, China, Beijing, Beijing, 100142, China.
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China, Beijing, 100142, China.
- Research and Development Department, CAS Ion Medical Technology Co., Ltd., beijing, Beijing, 100391, China.
- Medical Management Department, CAS Ion Medical Technology Co., Ltd, Yingu Masion, Beijing, 100190, China.
- State Key Laboratory of Nuclear Physics and Technology, Beijing 100871, China, Beijing, Beijing, 100871, China.
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, 999077, China, Kowloon, 999077, Hong Kong.
- State Key Laboratory of Nuclear Physics and Technology, and Key Laboratory of HEDP of the Ministry of Education, CAPT, Peking University, Beijing, 100871, China, Beijing 100871, China, Beijing, 100871, China.
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing,100021, China, Beijing, 100021, China.
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing Cancer Hospital & Institute, Beijing, China, Beijing 100142, China, Beijing, 100142, China.
Abstract
The limited longitudinal field-of-view (FOV) of cone-beam CT (CBCT) impedes accurate patient setup and adaptive radiotherapy (ART). A surface-aware DDIM-based RePaint diffusion framework was proposed to extend the longitudinal CBCT anatomies with inter-fractional changes, by leveraging prior planning CT (pCT) and updated optical surface image (OSI) as prior knowledge. Three CBCTs on different days and one pCT of 41 patients from two centers were retrospectively selected (Center A: 34 training, 4 testing, Trilogy; Center B: 3 testing, Ethos), yielding 102 training pairs and 21 test pairs. A surface-aware DDIM-RePaint model was developed to restore truncated CBCT volumes of the treatment day conditioned on prior pCT and updated OSI inputs. The masked (restored) volumes were quantitatively evaluated using mean absolute error (MAE, HU), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). Ablation studies were performed to assess the contribution of OSI. On testing cases, DDIM-RePaint achieved MAE = 25.28 ± 2.45 HU, SSIM = 94.89 ± 0.73, PSNR = 23.05 ± 0.83 for Center A, and MAE = 35.20 ± 4.30 HU, SSIM = 91.27 ± 2.50, PSNR = 21.12 ± 0.89 for Center B, both were significantly better than that of fusing pCT and CBCT as the current clinical approach (all P < 0.001). Based on various metrics and extension proportions, ablation results consistently demonstrated the significant contribution of OSI to the accuracy of longitudinal image restoration, which decreased monotonically with the extending volume. The inference time on 12 samples was reduced from 45 minutes to 2.2 minutes by sampler optimization. The proposed surface-aware DDIM-RePaint framework provided an accurate and efficient approach for longitudinal CBCT FOV extension, potentially facilitating patient setup and ART planning without extra imaging dose and hardware upgrade.