---
title: "Physics-informed decomposition networks for dose monitoring in carbon ion radiotherapy"
id: "pubmed-42628571"
canonical_url: "https://medichelpline.com/clinical-feed/pubmed-42628571"
content_type: "clinical_feed_article"
specialty: "Critical Care"
source_name: "PubMed / NCBI"
source_url: "https://pubmed.ncbi.nlm.nih.gov/42628571/"
doi: "10.1088/1361-6560/ae9d0f"
published_at: "2026-09-03T00:00:00.000Z"
evidence_level: "Journal Article"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Physics-informed decomposition networks for dose monitoring in carbon ion radiotherapy
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/pubmed-42628571
- **Specialty:** [Critical Care](https://medichelpline.com/clinical-feed/critical-care.md)
- **Primary Source:** PubMed / NCBI
- **Source URL:** [Original Journal Publication](https://pubmed.ncbi.nlm.nih.gov/42628571/)
- **DOI:** [10.1088/1361-6560/ae9d0f](https://doi.org/10.1088%2F1361-6560%2Fae9d0f)
- **Published At:** 2026-09-03T00:00:00.000Z
- **Evidence Rating:** Journal Article
## Executive GIST (TL;DR)
- The study addresses mapping between **positron-emitter activity** measured by in-beam PET and physical dose deposition in **carbon ion radiotherapy (CIRT)**, a relationship that is complex and nonlinear. - Researchers developed decomposition-based deep learning frameworks with auxiliary physical supervision to improve activity-to-dose mapping. - Idealized Monte Carlo (MC) simulations were run on CT phantoms from 18 non-small cell lung cancer patients to generate training and ground-truth data. - Models predicted laterally integrated one-dimensional depth-dose distributions for individual pencil-beam spots using 5-minute cumulative activity and CT Hounsfield unit profiles as inputs. - Three neural network approaches were evaluated: baseline DirectNet and two decomposition-based models, **TemcoNet** and **NucoNet**, which use Transformer-based decomposition modules. - TemcoNet used supervision from cumulative post-irradiation activity at 10, 15, and 20 minutes; NucoNet used supervision from **nuclide-specific yields** of 11C, 15O, and 10C; DirectNet served as the baseline with no decomposition supervision. - All models achieved similar median range accuracy compared with MC ground truth, but TemcoNet and NucoNet markedly improved dose-prediction accuracy. - The mean relative error decreased from 2.36% with DirectNet to below 0.4% for both decomposition-based models; the mean gamma passing rate at 2 mm/2% rose from 45.31% to approximately 96%. - Ablation experiments indicated the decomposition pathway learned physically meaningful intermediate representations and that nuclide-yield supervision provided additional benefit for dose prediction. - The study concludes that **physics-informed decomposition-based modeling** can substantially enhance MC-derived activity-to-dose mapping for in-beam PET monitoring in CIRT. Details on clinical translation, experimental conditions beyond the MC study, and full implementation specifics were not reported in the source.
## Clinical Analysis & Structured Key Points
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more resources Phys Med Biol Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Phys+Med+Biol%22%5Bjour%5D&sort=date&sort_order=desc) * [ Search in NLM Catalog ](https://www.ncbi.nlm.nih.gov/nlmcatalog?term=%22Phys+Med+Biol%22%5BTitle+Abbreviation%5D) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42628571/) . 2026 Sep 3;71(17). doi: 10.1088/1361-6560/ae9d0f. # A physics-informed decomposition network for carbon ion radiotherapy dose monitoring: a proof-of-concept study [Xin-Yu Hu](https://pubmed.ncbi.nlm.nih.gov/?term=Hu+XY&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Yan Li](https://pubmed.ncbi.nlm.nih.gov/?term=Li+Y&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Wei-Guang Li](https://pubmed.ncbi.nlm.nih.gov/?term=Li+WG&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Yu-Ying Yin](https://pubmed.ncbi.nlm.nih.gov/?term=Yin+YY&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Chao Yang](https://pubmed.ncbi.nlm.nih.gov/?term=Yang+C&cauthor_id=42628571)[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Cheng Chang](https://pubmed.ncbi.nlm.nih.gov/?term=Chang+C&cauthor_id=42628571)[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Ming-Qing Wang](https://pubmed.ncbi.nlm.nih.gov/?term=Wang+MQ&cauthor_id=42628571)[ 3 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-3 "Department of Radiation Oncology, Cancer Center, Peking University Third Hospital, 49 North Garden Rd., Haidian District, Beijing 100191, People's Republic of China."), [Kai-Wen Li](https://pubmed.ncbi.nlm.nih.gov/?term=Li+KW&cauthor_id=42628571)[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Xueying Yang](https://pubmed.ncbi.nlm.nih.gov/?term=Yang+X&cauthor_id=42628571)[ 4 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-4 "Hangzhou International Innovation Institute, Beihang University, Hangzhou, Zhejiang 311115, People's Republic of China."), [Li-Sheng Geng](https://pubmed.ncbi.nlm.nih.gov/?term=Geng+LS&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 5 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-5 "Sino-French Carbon Neutrality Research Center, École Centrale de Pékin/School of General Engineering, Beihang University, Beijing 100191, People's Republic of China.")[ 6 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-6 "Beijing Key Laboratory of Advanced Nuclear Materials and Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 7 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-7 "Peng Huanwu Collaborative Center for Research and Education, Beihang University, Beijing 100191, People's Republic of China.")[ 8 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#full-view-affiliation-8 "Southern Center for Nuclear-Science Theory \(SCNT\), Institute of Modern Physics, Chinese Academy of Sciences, Huizhou 516000, People's Republic of China.") Affiliations Expand ### Affiliations * 1 School of Physics, Beihang University, Beijing 102206, People's Republic of China. * 2 Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China. * 3 Department of Radiation Oncology, Cancer Center, Peking University Third Hospital, 49 North Garden Rd., Haidian District, Beijing 100191, People's Republic of China. * 4 Hangzhou International Innovation Institute, Beihang University, Hangzhou, Zhejiang 311115, People's Republic of China. * 5 Sino-French Carbon Neutrality Research Center, École Centrale de Pékin/School of General Engineering, Beihang University, Beijing 100191, People's Republic of China. * 6 Beijing Key Laboratory of Advanced Nuclear Materials and Physics, Beihang University, Beijing 102206, People's Republic of China. * 7 Peng Huanwu Collaborative Center for Research and Education, Beihang University, Beijing 100191, People's Republic of China. * 8 Southern Center for Nuclear-Science Theory (SCNT), Institute of Modern Physics, Chinese Academy of Sciences, Huizhou 516000, People's Republic of China. * PMID: **42628571** * DOI: [ 10.1088/1361-6560/ae9d0f ](https://doi.org/10.1088/1361-6560/ae9d0f) Item in Clipboard # A physics-informed decomposition network for carbon ion radiotherapy dose monitoring: a proof-of-concept study Xin-Yu Hu et al. Phys Med Biol. 2026. Show details Display options Display options Format Abstract PubMed PMID Phys Med Biol Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Phys+Med+Biol%22%5Bjour%5D&sort=date&sort_order=desc) * [ Search in NLM Catalog ](https://www.ncbi.nlm.nih.gov/nlmcatalog?term=%22Phys+Med+Biol%22%5BTitle+Abbreviation%5D) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42628571/) . 2026 Sep 3;71(17). doi: 10.1088/1361-6560/ae9d0f. ### Authors [Xin-Yu Hu](https://pubmed.ncbi.nlm.nih.gov/?term=Hu+XY&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Yan Li](https://pubmed.ncbi.nlm.nih.gov/?term=Li+Y&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Wei-Guang Li](https://pubmed.ncbi.nlm.nih.gov/?term=Li+WG&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Yu-Ying Yin](https://pubmed.ncbi.nlm.nih.gov/?term=Yin+YY&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Chao Yang](https://pubmed.ncbi.nlm.nih.gov/?term=Yang+C&cauthor_id=42628571)[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Cheng Chang](https://pubmed.ncbi.nlm.nih.gov/?term=Chang+C&cauthor_id=42628571)[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Ming-Qing Wang](https://pubmed.ncbi.nlm.nih.gov/?term=Wang+MQ&cauthor_id=42628571)[ 3 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-3 "Department of Radiation Oncology, Cancer Center, Peking University Third Hospital, 49 North Garden Rd., Haidian District, Beijing 100191, People's Republic of China."), [Kai-Wen Li](https://pubmed.ncbi.nlm.nih.gov/?term=Li+KW&cauthor_id=42628571)[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-2 "Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China."), [Xueying Yang](https://pubmed.ncbi.nlm.nih.gov/?term=Yang+X&cauthor_id=42628571)[ 4 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-4 "Hangzhou International Innovation Institute, Beihang University, Hangzhou, Zhejiang 311115, People's Republic of China."), [Li-Sheng Geng](https://pubmed.ncbi.nlm.nih.gov/?term=Geng+LS&cauthor_id=42628571)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-1 "School of Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 5 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-5 "Sino-French Carbon Neutrality Research Center, École Centrale de Pékin/School of General Engineering, Beihang University, Beijing 100191, People's Republic of China.")[ 6 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-6 "Beijing Key Laboratory of Advanced Nuclear Materials and Physics, Beihang University, Beijing 102206, People's Republic of China.")[ 7 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-7 "Peng Huanwu Collaborative Center for Research and Education, Beihang University, Beijing 100191, People's Republic of China.")[ 8 ](https://pubmed.ncbi.nlm.nih.gov/42628571/#short-view-affiliation-8 "Southern Center for Nuclear-Science Theory \(SCNT\), Institute of Modern Physics, Chinese Academy of Sciences, Huizhou 516000, People's Republic of China.") ### Affiliations * 1 School of Physics, Beihang University, Beijing 102206, People's Republic of China. * 2 Research and Development Department, CAS Ion Medical Technology Co., Ltd, Beijing 100190, People's Republic of China. * 3 Department of Radiation Oncology, Cancer Center, Peking University Third Hospital, 49 North Garden Rd., Haidian District, Beijing 100191, People's Republic of China. * 4 Hangzhou International Innovation Institute, Beihang University, Hangzhou, Zhejiang 311115, People's Republic of China. * 5 Sino-French Carbon Neutrality Research Center, École Centrale de Pékin/School of General Engineering, Beihang University, Beijing 100191, People's Republic of China. * 6 Beijing Key Laboratory of Advanced Nuclear Materials and Physics, Beihang University, Beijing 102206, People's Republic of China. * 7 Peng Huanwu Collaborative Center for Research and Education, Beihang University, Beijing 100191, People's Republic of China. * 8 Southern Center for Nuclear-Science Theory (SCNT), Institute of Modern Physics, Chinese Academy of Sciences, Huizhou 516000, People's Republic of China. * PMID: **42628571** * DOI: [ 10.1088/1361-6560/ae9d0f ](https://doi.org/10.1088/1361-6560/ae9d0f) Item in Clipboard Full text links Cite Display options Display options Format Abstract PubMed PMID ## Abstract _Objective._ In-beam positron emission tomography (PET) provides a promising strategy for dose monitoring in carbon ion radiotherapy (CIRT), but accurate dose prediction remains difficult due to the complex, nonlinear relationship between positron-emitter activity and physical dose deposition. This proof-of-concept study aimed to improve activity-to-dose mapping by developing decomposition-based deep learning frameworks with auxiliary physical supervision._Approach._ Idealized Monte Carlo (MC) simulations were conducted on computed tomography (CT) phantoms from 18 non-small cell lung cancer patients. The models were designed to predict laterally integrated one-dimensional depth-dose distributions for individual pencil-beam spots from corresponding 5 min cumulative activity and CT Hounsfield unit profiles. Two decomposition-based models, TemcoNet and NucoNet, incorporated Transformer-based decomposition modules supervised by cumulative post-irradiation activity at 10, 15, and 20 min and nuclide-specific yields of11C,15O, and10C, respectively, while DirectNet served as a baseline._Main results._ Compared with MC ground truth, all models achieved similar median range accuracy, but TemcoNet and NucoNet substantially improved dose prediction, reducing the mean relative error from 2.36% for DirectNet to below 0.4%. The mean gamma passing rate at 2 mm/2% increased from 45.31% to approximately 96% for both decomposition-based models. Ablation experiments showed that the decomposition pathway learned physically meaningful intermediate representations, and that nuclide-yield supervision provided an additional dose-prediction benefit._Significance._ Physics-informed decomposition-based modeling improves MC-derived positron-emitter activity-to-dose mapping by combining effective repre
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