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优化基于锥形束计算机断层扫描的在线自适应放射治疗工作流程,以减少医生的参与。

Optimizing Workflow for Cone Beam Computed Tomography-Based Online Adaptive Radiation Therapy Toward Reduced Physician Involvement.

作者信息

Kalinauskaite Goda, Künzel Luise A, Kluge Anne, Rubarth Kerstin, Dannehl Jakob, Höhne Celina, Beck Marcus, Zips Daniel, Senger Carolin

机构信息

Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology and Radiotherapy, Augustenburger Platz 1, 13353 Berlin, Germany.

Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.

出版信息

Adv Radiat Oncol. 2025 Jul 25;10(10):101874. doi: 10.1016/j.adro.2025.101874. eCollection 2025 Oct.

DOI:10.1016/j.adro.2025.101874
PMID:40927651
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12414823/
Abstract

PURPOSE

To evaluate the impact of an optimized online adaptive radiation therapy workflow on physician involvement.

METHODS AND MATERIALS

Data from a prospective phase 2 trial involving 34 prostate cancer patients treated with cone beam computed tomography (CBCT)-based online adaptive radiation therapy (62 Gy in 20 fractions) were analyzed. Manual interventions were required for 2 steps in the workflow: radiation therapy technologist review and adjustment of automatically segmented organs, guiding target segmentation, so-called "influencer," while physicians reviewed and refined the targets. Three different workflows were compared: 2-influencer (rectum and bladder), 3-influencer (+prostate), and 5-influencer (+seminal vesicles and bowel). Time for workflow steps, extent of manual corrections, and target volume changes were compared.

RESULTS

A total of 613 fractions were analyzed. The 5-influencer workflow reduced manual target corrections to 11% of fractions compared with 51% for the 3-influencer workflow and 61% for the 2-influencer workflow ( < .001). Median session duration across workflows was 24.0 minutes (IQR, 22.0-28.0). Median target review times were shortest with the 5-influencer workflow at 2.5 minutes compared with 5.0 minutes for the 3-influencer workflow ( < .001) and 5.6 minutes for the 2-influencer workflow ( = .002). Most patients (84%) found the treatment time well tolerable.

CONCLUSIONS

This study of prostate cancer patients suggests that optimized workflow reduces the need for physician involvement in online CBCT guided adaptive radiation therapy. Optimized workflows may facilitate a more radiation therapy technologist-driven approach similar to standard image guided radiation therapy. Further studies in other cancers, also focusing on clinical endpoints, are needed to further improve CBCT guided online adaptive radiation therapy.

摘要

目的

评估优化的在线自适应放射治疗工作流程对医生参与度的影响。

方法与材料

分析了一项前瞻性2期试验的数据,该试验涉及34例接受基于锥形束计算机断层扫描(CBCT)的在线自适应放射治疗(20次分割,62 Gy)的前列腺癌患者。工作流程中有两个步骤需要人工干预:放射治疗技术人员对自动分割的器官进行审查和调整,指导靶区分割,即所谓的“影响因素”,而医生则对靶区进行审查和完善。比较了三种不同的工作流程:2个影响因素(直肠和膀胱)、3个影响因素(+前列腺)和5个影响因素(+精囊和肠道)。比较了工作流程步骤的时间、人工校正的程度和靶区体积的变化。

结果

共分析了613个分割。与3个影响因素工作流程的51%和2个影响因素工作流程的61%相比,5个影响因素工作流程将人工靶区校正减少到分割数的11%(P<0.001)。各工作流程的中位治疗时间为24.0分钟(四分位间距,22.0 - 28.0)。5个影响因素工作流程的中位靶区审查时间最短,为2.5分钟,而3个影响因素工作流程为5.0分钟(P<0.001),2个影响因素工作流程为5.6分钟(P = 0.002)。大多数患者(84%)认为治疗时间耐受性良好。

结论

这项对前列腺癌患者的研究表明,优化的工作流程减少了医生在在线CBCT引导的自适应放射治疗中的参与需求。优化的工作流程可能有助于采用更由放射治疗技术人员主导的方法,类似于标准图像引导放射治疗。需要在其他癌症中进行进一步研究,也关注临床终点,以进一步改进CBCT引导的在线自适应放射治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/4d741abd26d5/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/e2268189e632/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/1a5649498e1f/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/b54444027b21/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/4f5fe0b20f4c/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/4d741abd26d5/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/e2268189e632/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/1a5649498e1f/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/b54444027b21/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/4f5fe0b20f4c/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec7/12414823/4d741abd26d5/gr5.jpg

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