前列腺癌放疗后 T2 加权磁共振成像定量分析综合框架

Evangelia I. Zacharaki , Adrian L. Breto , Ahmad Algohary , Veronica Wallaengen , Sandra M. Gaston , Sanoj Punnen , Patricia Castillo , Pradip M. Pattany , Oleksandr N. Kryvenko , Benjamin Spieler , John C. Ford , Matthew C. Abramowitz , Alan Dal Pra , Alan Pollack , Radka Stoyanova
{"title":"前列腺癌放疗后 T2 加权磁共振成像定量分析综合框架","authors":"Evangelia I. Zacharaki ,&nbsp;Adrian L. Breto ,&nbsp;Ahmad Algohary ,&nbsp;Veronica Wallaengen ,&nbsp;Sandra M. Gaston ,&nbsp;Sanoj Punnen ,&nbsp;Patricia Castillo ,&nbsp;Pradip M. Pattany ,&nbsp;Oleksandr N. Kryvenko ,&nbsp;Benjamin Spieler ,&nbsp;John C. Ford ,&nbsp;Matthew C. Abramowitz ,&nbsp;Alan Dal Pra ,&nbsp;Alan Pollack ,&nbsp;Radka Stoyanova","doi":"10.1016/j.phro.2024.100660","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>The aim of this study is to develop a framework for quantitative analysis of longitudinal T2-weighted MRIs (T2w) following radiotherapy (RT) for prostate cancer.</div></div><div><h3>Materials and methods</h3><div>The developed methodology includes: <em>(i)</em> deformable image registration of longitudinal series to pre-RT T2w for automated detection of prostate, peripheral zone (PZ), and gross tumor volume (GTV); and <em>(ii)</em> T2w signal-intensity harmonization based on three reference tissues. The <em>RE</em>gistration and <em>HARM</em>onization (<em>REHARM</em>) framework was applied on T2w acquired in a clinical trial consisting of two pre-RT and three post-RT MRI exams. Image registration was assessed by the DICE coefficient between automatic and manual contours, and intensity normalization via inter-patient histogram intersection. Longitudinal consistency was evaluated by the repeatability coefficient and Pearson correlation (<em>r</em>) between the two T2w exams before RT.</div></div><div><h3>Results</h3><div>T2w from 107 MRI exams (23 patients) were utilized. Following <em>REHARM</em>, the histogram intersections for prostate, PZ and GTV increased from median = 0.43/0.16/0.13 to 0.66/0.44/0.46. The repeatability in T2w intensity estimation was better for the automatic than the manual contours for all three regions of interest (<em>r</em> = 0.9, <em>p</em> &lt; 0.0001, for GTV). The changes in the tissues’ T2w values pre- and post-RT became significant, indicating the measurable quantitative signal related to radiation.</div></div><div><h3>Conclusions</h3><div>The developed methodology allows to automate longitudinal analysis reducing data acquisition-related variation and improving consistency. The quantitative characterization of RT-induced changes in T2w will lead to new understanding of radiation effects enabling prediction modeling of RT response.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100660"},"PeriodicalIF":3.4000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated framework for quantitative T2-weighted MRI analysis following prostate cancer radiotherapy\",\"authors\":\"Evangelia I. Zacharaki ,&nbsp;Adrian L. Breto ,&nbsp;Ahmad Algohary ,&nbsp;Veronica Wallaengen ,&nbsp;Sandra M. Gaston ,&nbsp;Sanoj Punnen ,&nbsp;Patricia Castillo ,&nbsp;Pradip M. Pattany ,&nbsp;Oleksandr N. Kryvenko ,&nbsp;Benjamin Spieler ,&nbsp;John C. Ford ,&nbsp;Matthew C. Abramowitz ,&nbsp;Alan Dal Pra ,&nbsp;Alan Pollack ,&nbsp;Radka Stoyanova\",\"doi\":\"10.1016/j.phro.2024.100660\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><div>The aim of this study is to develop a framework for quantitative analysis of longitudinal T2-weighted MRIs (T2w) following radiotherapy (RT) for prostate cancer.</div></div><div><h3>Materials and methods</h3><div>The developed methodology includes: <em>(i)</em> deformable image registration of longitudinal series to pre-RT T2w for automated detection of prostate, peripheral zone (PZ), and gross tumor volume (GTV); and <em>(ii)</em> T2w signal-intensity harmonization based on three reference tissues. The <em>RE</em>gistration and <em>HARM</em>onization (<em>REHARM</em>) framework was applied on T2w acquired in a clinical trial consisting of two pre-RT and three post-RT MRI exams. Image registration was assessed by the DICE coefficient between automatic and manual contours, and intensity normalization via inter-patient histogram intersection. Longitudinal consistency was evaluated by the repeatability coefficient and Pearson correlation (<em>r</em>) between the two T2w exams before RT.</div></div><div><h3>Results</h3><div>T2w from 107 MRI exams (23 patients) were utilized. Following <em>REHARM</em>, the histogram intersections for prostate, PZ and GTV increased from median = 0.43/0.16/0.13 to 0.66/0.44/0.46. The repeatability in T2w intensity estimation was better for the automatic than the manual contours for all three regions of interest (<em>r</em> = 0.9, <em>p</em> &lt; 0.0001, for GTV). The changes in the tissues’ T2w values pre- and post-RT became significant, indicating the measurable quantitative signal related to radiation.</div></div><div><h3>Conclusions</h3><div>The developed methodology allows to automate longitudinal analysis reducing data acquisition-related variation and improving consistency. The quantitative characterization of RT-induced changes in T2w will lead to new understanding of radiation effects enabling prediction modeling of RT response.</div></div>\",\"PeriodicalId\":36850,\"journal\":{\"name\":\"Physics and Imaging in Radiation Oncology\",\"volume\":\"32 \",\"pages\":\"Article 100660\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physics and Imaging in Radiation Oncology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2405631624001301\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics and Imaging in Radiation Oncology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405631624001301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

目的本研究旨在开发一种框架,用于对前列腺癌放疗(RT)后的纵向 T2 加权磁共振成像(T2w)进行定量分析:开发的方法包括:(i) 将纵向系列图像与 RT 前的 T2w 进行可变形图像配准,以自动检测前列腺、外周区 (PZ) 和肿瘤总体积 (GTV);(ii) 基于三个参考组织的 T2w 信号强度协调。REgistration and HARMonization (REHARM) 框架应用于一项临床试验中获取的 T2w 图像,该试验包括两次前列腺癌术前和三次前列腺癌术后 MRI 检查。通过自动轮廓和手动轮廓之间的 DICE 系数评估图像配准,并通过患者间直方图交集评估强度归一化。通过 RT 前两次 T2w 检查之间的重复性系数和皮尔逊相关性(r)来评估纵向一致性。REHARM后,前列腺、PZ和GTV的直方图交点从中位数=0.43/0.16/0.13增加到0.66/0.44/0.46。在所有三个感兴趣区中,自动轮廓图的 T2w 强度估计重复性均优于手动轮廓图(对于 GTV,r = 0.9,p < 0.0001)。RT前后组织 T2w 值的变化显著,表明与辐射有关的定量信号是可测量的。对 RT 引起的 T2w 变化进行定量分析将有助于对辐射效应有新的认识,从而建立 RT 反应的预测模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Integrated framework for quantitative T2-weighted MRI analysis following prostate cancer radiotherapy

Purpose

The aim of this study is to develop a framework for quantitative analysis of longitudinal T2-weighted MRIs (T2w) following radiotherapy (RT) for prostate cancer.

Materials and methods

The developed methodology includes: (i) deformable image registration of longitudinal series to pre-RT T2w for automated detection of prostate, peripheral zone (PZ), and gross tumor volume (GTV); and (ii) T2w signal-intensity harmonization based on three reference tissues. The REgistration and HARMonization (REHARM) framework was applied on T2w acquired in a clinical trial consisting of two pre-RT and three post-RT MRI exams. Image registration was assessed by the DICE coefficient between automatic and manual contours, and intensity normalization via inter-patient histogram intersection. Longitudinal consistency was evaluated by the repeatability coefficient and Pearson correlation (r) between the two T2w exams before RT.

Results

T2w from 107 MRI exams (23 patients) were utilized. Following REHARM, the histogram intersections for prostate, PZ and GTV increased from median = 0.43/0.16/0.13 to 0.66/0.44/0.46. The repeatability in T2w intensity estimation was better for the automatic than the manual contours for all three regions of interest (r = 0.9, p < 0.0001, for GTV). The changes in the tissues’ T2w values pre- and post-RT became significant, indicating the measurable quantitative signal related to radiation.

Conclusions

The developed methodology allows to automate longitudinal analysis reducing data acquisition-related variation and improving consistency. The quantitative characterization of RT-induced changes in T2w will lead to new understanding of radiation effects enabling prediction modeling of RT response.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Physics and Imaging in Radiation Oncology
Physics and Imaging in Radiation Oncology Physics and Astronomy-Radiation
CiteScore
5.30
自引率
18.90%
发文量
93
审稿时长
6 weeks
期刊最新文献
Results of 2023 survey on the use of synthetic computed tomography for magnetic resonance Imaging-only radiotherapy: Current status and future steps Head and neck automatic multi-organ segmentation on Dual-Energy Computed Tomography Automatic segmentation for magnetic resonance imaging guided individual elective lymph node irradiation in head and neck cancer patients Development of a novel 3D-printed dynamic anthropomorphic thorax phantom for evaluation of four-dimensional computed tomography Technical feasibility of delivering a simultaneous integrated boost in partial breast irradiation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1