Physics in Medicine & Biology最新文献

{"title":"First clinical implementation of a highly efficient daily online adapted proton therapy (DAPT) workflow.","authors":"Francesca Albertini,Katarzyna Czerska,Miriam Vazquez,Ilija Andaca,Barbara Bachtiary,Rico Besson,Alessandra Bolsi,Anne Sophie Bogaert,Evangelia Choulilitsa,Jan Hrbacek,Sisse Jakobsen,Dominic Leiser,Michael Matter,Alexandre Mayor,Gabriel Meier,Andre Nanz,Lena Nenoff,David Oxley,Dorota Siewert,Benno Andreas Rohrer Schnidrig,Andreas Johan Smolders,Hubert Szweda,Michelle Van Heerden,Carla Winterhalter,Antony John Lomax,Damien Charles Weber","doi":"10.1088/1361-6560/ad7cbd","DOIUrl":"https://doi.org/10.1088/1361-6560/ad7cbd","url":null,"abstract":"This study presents the first clinical implementation of an efficient online daily adaptive proton therapy workflow (DAPT).
Approach: The DAPT workflow includes a pre-treatment phase, where a template and a fallback plan are optimized on the planning CT. In the online phase, the adapted plan is re-optimized on daily images from an in-room CT. Daily structures are rigidly propagated from the planning CT. Automated quality assurance (QA) involves geometric, sanity checks and an independent dose calculation from the machine files. 
Differences from the template plan are analyzed field-by-field, and clinical plan is assessed by reviewing the achieved clinical goals using a traffic light protocol. If the daily adapted plan fails any QA or clinical goals, the fallback plan is used. In the offline phase the delivered dose is recalculated from log-files onto the daily CT, and a gamma analysis is performed (3%/3mm). The DAPT workflow has been applied to selected adult patients treated in rigid anatomy for the last serie of the treatment between October 2023 and April 2024.

Main Results: DAPT treatment sessions averaged around 23 minutes [range: 15-30 min] and did not exceed the typical 30-minute time slot. Treatment adaptation, including QA and clinical plan assessment, averaged just under 7 minutes [range: 3:30-16 min] per fraction. All plans passed the online QAs steps. In the offline phase a good agreement with the log-files reconstructed dose was achieved (minimum gamma pass rate of 97.5 %). The online adapted plan was delivered for > 85% of the fractions. In 92% of total fractions, adapted plans exhibited improved individual dose metrics to the targets and/or organs at risk.
Significance: This study demonstrates the successful implementation of an online daily DAPT workflow. Notably, the duration of a DAPT session did not exceed the time slot typically allocated for non-DAPT treatment. As far as we are aware, this is a first clinical implementation of daily online adaptive proton therapy.&#xD.","PeriodicalId":519254,"journal":{"name":"Physics in Medicine & Biology","volume":"150 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dose-rate effects and tumor control probability in177Lu-based targeted radionuclide therapy: a theoretical analysis.","authors":"Markus Galler,Christoph Chibolela,Felix Thiele,Julian Manuel Michael Rogasch,Holger Amthauer","doi":"10.1088/1361-6560/ad7cbe","DOIUrl":"https://doi.org/10.1088/1361-6560/ad7cbe","url":null,"abstract":"OBJECTIVE177Lu-based targeted radionuclide therapy (TRT) has become an important cancer treatment option in recent years, in particular in the treatment of advanced prostate cancer and metastasized neuroendocrine tumors. Although it is known from conventional radiotherapy that the temporal dynamics of the dose-rate can be of relevance for tumor cell survival, the analysis of TRT efficacy usually considers only the absorbed dose. Thus, the aim of this theoretical analysis is to shed light on the possible effects of the pattern of dose-rate in TRT on tumor control probability (TCP).APPROACHFor this purpose, TCP is studied numerically in a typical four-cycle treatment regime based on the mechanistic lethal-potentially lethal model and the Zaider-Minerbo model for TCP including repopulation of tumor cells.MAIN RESULTSIt is shown that the dose-rate pattern in TRT can have a substantial effect on TCP even though the absorbed dose in the tumor lesion is unchanged. These dose-rate effects are particularly evident when repair of potentially lethal lesions is slow.SIGNIFICANCEThe results indicate that in some situations in the analysis of the efficacy of TRT it is necessary to consider the full dose-rate pattern instead of the absorbed dose alone. This can be highly relevant for optimization and further development of TRTs. In particular, it could be of relevancy in studying the efficacy of newly emerging treatment concepts that combine the use of TRT and drugs that inhibit DNA damage repair.","PeriodicalId":519254,"journal":{"name":"Physics in Medicine & Biology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prior-image-based low-dose CT reconstruction for adaptive radiation therapy.","authors":"Yao Xu,Jiazhou Wang,Weigang Hu","doi":"10.1088/1361-6560/ad7b9b","DOIUrl":"https://doi.org/10.1088/1361-6560/ad7b9b","url":null,"abstract":"OBJECTIVEThe study aims to reduce the imaging radiation dose in Adaptive Radiotherapy (ART) while maintaining high-quality CT images, critical for effective treatment planning and monitoring.APPROACHWe developed the Prior-aware Learned Primal-Dual Network (pLPD-UNet), which uses prior CT images to enhance reconstructions from low-dose scans. The network was separately trained on thorax and abdomen datasets to accommodate the unique imaging requirements of each anatomical region.MAIN RESULTSThe pLPD-UNet demonstrated improved reconstruction accuracy and robustness in handling sparse data compared to traditional methods. It effectively maintained image quality essential for precise organ delineation and dose calculation, while achieving a significant reduction in radiation exposure.SIGNIFICANCEThis method offers a significant advancement in the practice of ART by integrating prior imaging data, potentially setting a new standard for balancing radiation safety with the need for high-resolution imaging in cancer treatment planning.","PeriodicalId":519254,"journal":{"name":"Physics in Medicine & Biology","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dosimetry at cellular level for the alpha-emitting radionuclides actinium-225, astatine-211 and radium-223 for bone metastasis cells from castration resistant prostate cancer.","authors":"Catherine Costa Oliveira-Silva,Mateus S Maillard,Raoni Silva,Lidia Vasconcelos de Sá","doi":"10.1088/1361-6560/ad7b9a","DOIUrl":"https://doi.org/10.1088/1361-6560/ad7b9a","url":null,"abstract":"Objectives
The aim is to evaluate energy deposition in the nucleus and cytoplasm in targeted alpha therapy of metastatic castration-resistant prostate cancer by modeling two cell lines, PC3 (osteolytic) and LNCaP C4-2 (osteoblastic), for actinium-225, astatine-211, and radium-223 and their progeny, using Monte Carlo simulations with the GATE/Geant4 code.
Approach
We developed single cell and cell clusters models and couple them to Monte Carlo simulations performed on the GATE platform version 9.3, setting the GEANT4-DNA physics list emstandard_opt3_mixed_dna for At-211, Ac-225 and Ra-223 progenies. We considered three radionuclide distributions as a sources: the nucleus, the cytoplasm and the whole cell.
Main Results
When the nucleus was considered as a target, the S-values (N←N) calculated for At-211, Ac-225 and Ra-223 progenies were significantly higher, within 60-90%, than S-values (N←Cy), demonstrating less influence of cytoplasm internalization. When the cytoplasm was considering as a target, the S-values (Cy←Cy) calculated for At-211, Ac-225 and Ra-223 progeny were significantly higher, within 30-90%, than the S-values (Cy←N). When no progeny migration occurs and the nucleus was considered as the target, the cumulative S-values (N←N) calculated for At-211, Ac-225 and Ra-223 were significantly higher, within 50- 70%, than the S-values (N←N) computed for At-211, Ac-225, and Ra-223. Comparing the cumulative S-values, Ac-225 and 
Ra-223 therapies is more effective, in terms of deposited energy in a target, than that with At-211.
Significance
The data presented in this research indicates that Ac-225 therapy may be theoptimum choice due to the energy deposited in the nucleus, as long as the recoil effects and redistribution of progeny are understood. In contrast, At-211 is an alternative to avoid progeny migration. However, to completely analyze the efficacy of radionuclide therapy, other parameters must be considered, such as biological half-life, stability of the transport molecule, progeny migration, excretion pathways, and uptake in different organs.&#xD.","PeriodicalId":519254,"journal":{"name":"Physics in Medicine & Biology","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning-based segmentation for high-dose-rate brachytherapy in cervical cancer using 3D Prompt-ResUNet.","authors":"Xian Xue,Lining Sun,Dazhu Liang,Jingyang Zhu,Lele Liu,Quanfu Sun,Hefeng Liu,Jianwei Gao,Xiaosha Fu,Jingjing Ding,Xiangkun Dai,Laiyuan Tao,Jinsheng Cheng,Tengxiang Li,Fugen Zhou","doi":"10.1088/1361-6560/ad7ad1","DOIUrl":"https://doi.org/10.1088/1361-6560/ad7ad1","url":null,"abstract":"To develop and evaluate a 3D Prompt-ResUNet module that utilized the prompt-based model combined with 3D nnUNet for rapid and consistent autosegmentation of high-risk clinical target volume and organ at risk in high-dose-rate brachytherapy for cervical cancer patients. 
Approach. We used 73 computed tomography (CT) and 62 magnetic resonance imaging (MRI) scans from 135 (103 for training, 16 for validation, and 16 for testing) cervical cancer patients across two hospitals for HRCTV and OAR segmentation. A novel comparison of the deep learning neural networks 3D Prompt-ResUNet, nnUNet, and SAM-Med3D was applied for the segmentation. Evaluation was conducted in two parts: geometric and clinical assessments. Quantitative metrics included the Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95%), Jaccard index (JI), and Matthews correlation coefficient (MCC). Clinical evaluation involved interobserver comparison, 4-grade expert scoring, and a double-blinded Turing test.
Main results. The Prompt-ResUNet model performed most similarly to experienced radiation oncologists, outperforming less experienced ones. During testing, the DSC, HD95% (mm), JI, and MCC value (mean ± SD) for HRCTV were 0.92±0.03, 2.91 ± 0.69, 0.85± 0.04, and 0.92 ± 0.02, respectively. For the bladder, these values were 0.93 ± 0.05, 3.07 ± 1.05, 0.87 ± 0.08, and 0.93 ± 0.05, respectively. For the rectum, they were 0.87 ± 0.03, 3.54 ± 1.46, 0.78 ± 0.05, and 0.87 ± 0.03, respectively. For the sigmoid, they were 0.76 ± 0.11, 7.54 ± 5.54, 0.63 ± 0.14, and 0.78 ± 0.09, respectively. The Prompt-ResUNet achieved a clinical viability score of at least 2 in all evaluation cases (100%) for both HRCTV and bladder and exceeded the 30% positive rate benchmark for all evaluated structures in the Turing test.
Significance. The Prompt-ResUNet architecture demonstrated high consistency with ground truth (GT) in autosegmentation of HRCTV and OARs, reducing interobserver variability and shortening treatment times.&#xD.","PeriodicalId":519254,"journal":{"name":"Physics in Medicine & Biology","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142257833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to comment on ‘Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation’","authors":"Yuta Shiraishi, Yusuke Matsuya and Hisanori Fukunaga","doi":"10.1088/1361-6560/ad3edc","DOIUrl":"https://doi.org/10.1088/1361-6560/ad3edc","url":null,"abstract":"Liew and Mairani commented on our paper ‘Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation’ (Shiraishi et al 2024a Phys. Med. Biol.69 015017), which proposed a biophysical model to predict the dose–response curve of surviving cell fractions after ultra-high dose rate irradiation following conventional dose rate irradiation by considering DNA damage yields. They suggested the need to consider oxygen concentration in our prediction model and possible issues related to the data selection process used for the benchmarking test in our paper. In this reply, we discuss the limitations of both the present model and the available experimental data for determining the model’s parameters. We also demonstrate that our proposed model can reproduce the experimental survival data even when using only the experimental DNA damage data measured reliably under normoxic conditions.","PeriodicalId":519254,"journal":{"name":"Physics in Medicine & Biology","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140829621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on ‘Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation’","authors":"Hans Liew and Andrea Mairani","doi":"10.1088/1361-6560/ad3edb","DOIUrl":"https://doi.org/10.1088/1361-6560/ad3edb","url":null,"abstract":"We comment on the recently published study ‘Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation’ by Shiraishi et al. While the general approach of the study may be appropriate, we wish to comment on its limitations and point out issues concerning their choice of the benchmarking and fitting data. The approach by the authors could become viable in an extended form once more comprehensive data is available.","PeriodicalId":519254,"journal":{"name":"Physics in Medicine & Biology","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140829588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual-space disentangled-multimodal network (DDM-net) for glioma diagnosis and prognosis with incomplete pathology and genomic data","authors":"Lu Qiu, Lu Zhao, Wangyuan Zhao, Jun Zhao","doi":"10.1088/1361-6560/ad37ec","DOIUrl":"https://doi.org/10.1088/1361-6560/ad37ec","url":null,"abstract":"<italic toggle=\"yes\">Objective</italic>. Effective fusion of histology slides and molecular profiles from genomic data has shown great potential in the diagnosis and prognosis of gliomas. However, it remains challenging to explicitly utilize the consistent-complementary information among different modalities and create comprehensive representations of patients. Additionally, existing researches mainly focus on complete multi-modality data and usually fail to construct robust models for incomplete samples. <italic toggle=\"yes\">Approach</italic>. In this paper, we propose a <bold>dual-space disentangled-multimodal network (DDM-net)</bold> for glioma diagnosis and prognosis. DDM-net disentangles the latent features generated by two separate variational autoencoders (VAEs) into common and specific components through a dual-space disentangled approach, facilitating the construction of comprehensive representations of patients. More importantly, DDM-net imputes the unavailable modality in the latent feature space, making it robust to incomplete samples. <italic toggle=\"yes\">Main results</italic>. We evaluated our approach on the TCGA-GBMLGG dataset for glioma grading and survival analysis tasks. Experimental results demonstrate that the proposed method achieves superior performance compared to state-of-the-art methods, with a competitive AUC of 0.952 and a C-index of 0.768. <italic toggle=\"yes\">Significance</italic>. The proposed model may help the clinical understanding of gliomas and can serve as an effective fusion model with multimodal data. Additionally, it is capable of handling incomplete samples, making it less constrained by clinical limitations.","PeriodicalId":519254,"journal":{"name":"Physics in Medicine & Biology","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140617976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}