Academic Journal
Assessment of elemental decomposition algorithms for particle therapy dose monitoring using positron emission tomography and prompt-gamma imaging.
| Τίτλος: | Assessment of elemental decomposition algorithms for particle therapy dose monitoring using positron emission tomography and prompt-gamma imaging. |
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| Συγγραφείς: | Li Y; School of Physics, Beihang University, Beijing 102206, People's Republic of China.; Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China., Li W; School of Physics, Beihang University, Beijing 102206, People's Republic of China.; Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China., Hu XY; School of Physics, Beihang University, Beijing 102206, People's Republic of China.; Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China., Yin YY; School of Physics, Beihang University, Beijing 102206, People's Republic of China.; Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China., Yang X; Hangzhou International Innovation Institute, Beihang University, Hangzhou, Zhejiang 311115, People's Republic of China., Yu S; Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China.; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, People's Republic of China., Yang C; Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China., Chang C; Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China., Wang M; Department of Radiation Oncology, Cancer Center, Peking University Third Hospital, 49 North Garden Rd., Haidian District, Beijing 100191, People's Republic of China., Li KW; Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China., Geng LS; School of Physics, Beihang University, Beijing 102206, People's Republic of China.; Sino-French Carbon Neutrality Research Center, École Centrale de Pékin/School of General Engineering, Beihang University, Beijing 100191, People's Republic of China.; Beijing Key Laboratory of Advanced Nuclear Materials and Physics, Beihang University, Beijing 102206, People's Republic of China.; Peng Huanwu Collaborative Center for Research and Education, Beihang University, Beijing 100191, People's Republic of China.; Southern Center for Nuclear-Science Theory (SCNT), Institute of Modern Physics, Chinese Academy of Sciences, Huizhou 516000, People's Republic of China., Zhang Y; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, People's Republic of China. |
| Πηγή: | Physics in medicine and biology [Phys Med Biol] 2026 Sep 24; Vol. 71 (18). Date of Electronic Publication: 2026 Sep 24. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: IOP Publishing Country of Publication: England NLM ID: 0401220 Publication Model: Electronic Cited Medium: Internet ISSN: 1361-6560 (Electronic) Linking ISSN: 00319155 NLM ISO Abbreviation: Phys Med Biol Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Bristol : IOP Publishing |
| Ιατρικοί όροι (MeSH): | Image Processing, Computer-Assisted*/methods , Algorithms* , Positron-Emission Tomography* , Radiation Dosage* , Gamma Rays*, Head and Neck Neoplasms/diagnostic imaging ; Head and Neck Neoplasms/radiotherapy ; Humans ; Phantoms, Imaging ; Radiotherapy Dosage ; Monte Carlo Method |
| Περίληψη: | Objective.Accurate dose verification remains a major challenge in particle therapy. Dose monitoring methods such as positron emission tomography (PET) and prompt-gamma (PG) imaging are highly sensitive to uncertainties in tissue composition derived from CT, which can be improved by dual-energy CT (DECT)-based material decomposition. This study systematically assessed the accuracy of four DECT elemental decomposition algorithms in predicting physical dose, annihilation-photon, and PG reference distributions in particle therapy, focusing on CT-based model uncertainty without detector considerations.Approach.Three parameterization-based DECT methods, a machine-learning (ML) DECT method, and a conventional single-energy CT (SECT) method were used to predict the elemental composition of the ICRP110 human phantom and 10 head-and-neck patients. The physical dose, annihilation, and PG distributions for incident proton, helium, carbon, and oxygen pencil beams were compared using Monte Carlo simulations. For the phantom, mean relative errors (MREs) were calculated relative to the reference distributions. For the patients, the distal fall-off positions of annihilation and PG profiles were compared across the methods.Main results.In the phantom study, the ML method yielded the lowest MREs across the four incident particle types. For oxygen ions, the ML method yielded an annihilation-photon MRE of 2.64%, compared with 6.50%-6.74% for the parameterization-based DECT methods. The corresponding PG MRE were 1.53%, 2.44%-2.60% for the ML and parameterization-based methods. The matched SECT analysis provided a conventional baseline under the same simulation and evaluation settings. In the patient analyses, the distal fall-off positions of annihilation and PG differed by up to 1.93 ± 0.42 mm and 1.76 ± 0.44 mm, respectively, between ML and the parameterization-based methods. Without voxel-wise patient ground truth, these results describe inter-method differences rather than an accuracy ranking.Significance.Compared with the parameterization-based methods, the ML method reduced errors in predicting source-level PET and PG reference distributions under the idealized Monte Carlo conditions used here, especially for heavier incident particles. These results quantify model-related uncertainty in complementary with detector resolution in clinical monitoring accuracy. (© 2026 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.) |
| Contributed Indexing: | Keywords: Dual-energy CT; elemental decomposition; particle-therapy dose monitoring; positron emission tomography; prompt-gamma imaging |
| Entry Date(s): | Date Created: 20260902 Date Completed: 20260924 Latest Revision: 20260924 |
| Update Code: | 20260924 |
| DOI: | 10.1088/1361-6560/aea1d4 |
| PMID: | 42685782 |
| Βάση Δεδομένων: | MEDLINE |
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