AI-driven online adaptive radiotherapy in prostate cancer treatment: considerations on activity time and dosimetric benefits.

IF 3.3 2区医学 Q2 ONCOLOGY

Radiation Oncology Pub Date : 2025-07-25 DOI:10.1186/s13014-025-02697-6

Francesco Preziosi, Althea Boschetti, Francesco Catucci, Claudio Votta, Luca Vellini, Sebastiano Menna, Flaviovincenzo Quaranta, Elisa Pilloni, Andrea D'Aviero, Michele Aquilano, Carmela Di Dio, Martina Iezzi, Alessia Re, Antonio Piras, Marco Marras, Francesca Gruosso, Domenico Piro, Danila Piccari, Luca Tagliaferri, Maria Antonietta Gambacorta, Luca Indovina, Gian Carlo Mattiucci, Davide Cusumano

{"title":"AI-driven online adaptive radiotherapy in prostate cancer treatment: considerations on activity time and dosimetric benefits.","authors":"Francesco Preziosi, Althea Boschetti, Francesco Catucci, Claudio Votta, Luca Vellini, Sebastiano Menna, Flaviovincenzo Quaranta, Elisa Pilloni, Andrea D'Aviero, Michele Aquilano, Carmela Di Dio, Martina Iezzi, Alessia Re, Antonio Piras, Marco Marras, Francesca Gruosso, Domenico Piro, Danila Piccari, Luca Tagliaferri, Maria Antonietta Gambacorta, Luca Indovina, Gian Carlo Mattiucci, Davide Cusumano","doi":"10.1186/s13014-025-02697-6","DOIUrl":null,"url":null,"abstract":"Aims: Recent advances in Radiotherapy have led to the development of online adaptive RT (oART), a procedure addressing inter-fraction anatomical variations. Integrating artificial intelligence (AI) into the oART procedure speeds up the process and reduces user dependency. This study investigates the dosimetric advantage of implementing AI-driven oART in prostate cancer.Methods: A total of 31 prostate cancer patients treated with oART on an AI-integrated Linac were analyzed. Patients were categorized by nodal involvement. For prostate-only cases, the Clinical Target Volume (CTV) included the prostate and seminal vesicles (CTV1), with a 5 mm margin (8 mm caudally) for Planning Target Volume (PTV), named PTV1. For nodal cases, pelvic lymph nodes were added (and categorized as CTV2) with a 5 mm isotropic margin (PTV2). Daily CBCTs were acquired, with OARs (rectum, bladder, bowels) automatically segmented by the AI system, while targets were manually delineated. Two plans were generated: a predicted one, calculating the original plan's fluence on daily anatomy, and an adapted one, with complete fluence re-optimization. Daily DVH indicators for PTV(V95%), CTV(D98%), bladder (V65Gy), bowel (V45Gy), and rectum (V50Gy) were compared between predicted and adapted plans using the Wilcoxon-Mann-Whitney test. Total session time, from CBCT acquisition to treatment completion, was also recorded.Results: oART treatment improved prostate coverage in both patient groups (+10.4% and +11.8% in PTV V95% for patients with and without lymph nodes) and CTV D98% (+2.6% with lymph nodes, +2.9% without). Improvements for arm 2 were smaller (+3.1% in PTV2 V95%, +2.2% in CTV2 D98%). Statistical differences were insignificant in OAR DVH indicators (p > 0.1). Median treatment time was 25 min and 32 min for prostate-only and lymph node cases, respectively.Conclusion: This study demonstrates that oART in prostate cancer results in a significant improvement in target coverage with no significant difference in OARs.","PeriodicalId":49639,"journal":{"name":"Radiation Oncology","volume":"20 1","pages":"116"},"PeriodicalIF":3.3000,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12296583/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiation Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13014-025-02697-6","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Aims: Recent advances in Radiotherapy have led to the development of online adaptive RT (oART), a procedure addressing inter-fraction anatomical variations. Integrating artificial intelligence (AI) into the oART procedure speeds up the process and reduces user dependency. This study investigates the dosimetric advantage of implementing AI-driven oART in prostate cancer.

Methods: A total of 31 prostate cancer patients treated with oART on an AI-integrated Linac were analyzed. Patients were categorized by nodal involvement. For prostate-only cases, the Clinical Target Volume (CTV) included the prostate and seminal vesicles (CTV1), with a 5 mm margin (8 mm caudally) for Planning Target Volume (PTV), named PTV1. For nodal cases, pelvic lymph nodes were added (and categorized as CTV2) with a 5 mm isotropic margin (PTV2). Daily CBCTs were acquired, with OARs (rectum, bladder, bowels) automatically segmented by the AI system, while targets were manually delineated. Two plans were generated: a predicted one, calculating the original plan's fluence on daily anatomy, and an adapted one, with complete fluence re-optimization. Daily DVH indicators for PTV(V95%), CTV(D98%), bladder (V65Gy), bowel (V45Gy), and rectum (V50Gy) were compared between predicted and adapted plans using the Wilcoxon-Mann-Whitney test. Total session time, from CBCT acquisition to treatment completion, was also recorded.

Results: oART treatment improved prostate coverage in both patient groups (+10.4% and +11.8% in PTV V95% for patients with and without lymph nodes) and CTV D98% (+2.6% with lymph nodes, +2.9% without). Improvements for arm 2 were smaller (+3.1% in PTV2 V95%, +2.2% in CTV2 D98%). Statistical differences were insignificant in OAR DVH indicators (p > 0.1). Median treatment time was 25 min and 32 min for prostate-only and lymph node cases, respectively.

Conclusion: This study demonstrates that oART in prostate cancer results in a significant improvement in target coverage with no significant difference in OARs.

Abstract Image

查看原文本刊更多论文

人工智能驱动的在线自适应放疗在前列腺癌治疗中的应用：对活动时间和剂量学益处的考虑。

目的：放射治疗的最新进展导致了在线自适应放射治疗（oART）的发展，这是一种解决分数间解剖变异的方法。将人工智能（AI）集成到oART程序中可以加快流程并减少用户依赖性。本研究探讨了在前列腺癌中实施人工智能驱动的oART的剂量学优势。方法：对31例前列腺癌患者在人工智能集成直线试验机上接受oART治疗的临床资料进行分析。根据淋巴结受累情况对患者进行分类。对于只有前列腺的病例，临床靶体积（CTV）包括前列腺和精囊（CTV1），规划靶体积（PTV）有5mm的边缘（尾部8mm），称为PTV1。对于淋巴结病例，加入盆腔淋巴结（并归类为CTV2），其各向同性边缘为5mm （PTV2）。获得每日cbct，人工智能系统自动分割OARs（直肠、膀胱、肠道），同时手动划定目标。生成了两个平面：一个是预测平面，计算原平面对日常解剖的影响；另一个是适应平面，对影响进行了完全的重新优化。采用Wilcoxon-Mann-Whitney试验比较预测方案和适应方案的每日DVH指标：PTV（V95%）、CTV（D98%）、膀胱（V65Gy）、肠（V45Gy）和直肠（V50Gy）。从CBCT获取到治疗完成，总疗程时间也被记录下来。结果：oART治疗提高了两组患者的前列腺覆盖率（PTV组为+10.4%，无淋巴结组为+11.8%，有淋巴结组为95%）和CTV组为98%（有淋巴结组为+2.6%，无淋巴结组为+2.9%）。第2组的改善较小（PTV2 V95% +3.1%, CTV2 D98% +2.2%）。OAR DVH指标差异无统计学意义（p < 0.01）。仅前列腺和淋巴结病例的中位治疗时间分别为25分钟和32分钟。结论：本研究表明，前列腺癌oART治疗可显著提高靶覆盖率，而OARs治疗无显著差异。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Radiation Oncology ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

CiteScore

6.50

自引率

2.80%

发文量

181

审稿时长

3-6 weeks

期刊介绍： Radiation Oncology encompasses all aspects of research that impacts on the treatment of cancer using radiation. It publishes findings in molecular and cellular radiation biology, radiation physics, radiation technology, and clinical oncology.