CTLESS:基于散射窗投影和深度学习的心肌灌注 SPECT 无传输衰减补偿方法

Zitong Yu;Md Ashequr Rahman;Craig K. Abbey;Richard Laforest;Nancy A. Obuchowski;Barry A. Siegel;Abhinav K. Jha
{"title":"CTLESS:基于散射窗投影和深度学习的心肌灌注 SPECT 无传输衰减补偿方法","authors":"Zitong Yu;Md Ashequr Rahman;Craig K. Abbey;Richard Laforest;Nancy A. Obuchowski;Barry A. Siegel;Abhinav K. Jha","doi":"10.1109/TMI.2024.3496870","DOIUrl":null,"url":null,"abstract":"Attenuation compensation (AC), while being beneficial for visual-interpretation tasks in myocardial perfusion imaging (MPI) by single-photon emission computed tomography (SPECT), typically requires the availability of a separate X-ray CT component, leading to additional radiation dose, higher costs, and potentially inaccurate diagnosis in case of misalignment between SPECT and CT images. To address these issues, we developed a method for <underline>c</u>ardiac SPEC<underline>T</u> AC using deep <underline>l</u>earning and <underline>e</u>mission <underline>s</u>catter-window photon<underline>s</u> without a separate transmission scan (CTLESS). In this method, an estimated attenuation map reconstructed from scatter-energy window projections is segmented into different regions using a multi-channel input multi-decoder network trained on CT scans. Pre-defined attenuation coefficients are assigned to these regions, yielding the attenuation map used for AC. We objectively evaluated this method in a retrospective study with anonymized clinical SPECT/CT stress MPI images on the clinical task of detecting perfusion defects with an anthropomorphic model observer. CTLESS yielded statistically non-inferior performance compared to a CT-based AC (CTAC) method and significantly outperformed a non-AC (NAC) method on this clinical task. Similar results were observed in stratified analyses with different sexes, defect extents, and defect severities. The method was observed to generalize across two SPECT scanners, each with a different camera. In addition, CTLESS yielded similar performance as CTAC and outperformed NAC method on the fidelity-based figures of merit, namely, root mean squared error (RMSE) and structural similarity index measure (SSIM). Moreover, as we reduced the training dataset size, CTLESS yielded relatively stable AUC values and generally outperformed another DL-based AC method that directly estimated the attenuation coefficient within each voxel. These results demonstrate the capability of the CTLESS method for transmission-less AC in SPECT and motivate further clinical evaluation.","PeriodicalId":94033,"journal":{"name":"IEEE transactions on medical imaging","volume":"44 3","pages":"1308-1320"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10767308","citationCount":"0","resultStr":"{\"title\":\"CTLESS: A Scatter-Window Projection and Deep Learning-Based Transmission-Less Attenuation Compensation Method for Myocardial Perfusion SPECT\",\"authors\":\"Zitong Yu;Md Ashequr Rahman;Craig K. Abbey;Richard Laforest;Nancy A. Obuchowski;Barry A. Siegel;Abhinav K. Jha\",\"doi\":\"10.1109/TMI.2024.3496870\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Attenuation compensation (AC), while being beneficial for visual-interpretation tasks in myocardial perfusion imaging (MPI) by single-photon emission computed tomography (SPECT), typically requires the availability of a separate X-ray CT component, leading to additional radiation dose, higher costs, and potentially inaccurate diagnosis in case of misalignment between SPECT and CT images. To address these issues, we developed a method for <underline>c</u>ardiac SPEC<underline>T</u> AC using deep <underline>l</u>earning and <underline>e</u>mission <underline>s</u>catter-window photon<underline>s</u> without a separate transmission scan (CTLESS). In this method, an estimated attenuation map reconstructed from scatter-energy window projections is segmented into different regions using a multi-channel input multi-decoder network trained on CT scans. Pre-defined attenuation coefficients are assigned to these regions, yielding the attenuation map used for AC. We objectively evaluated this method in a retrospective study with anonymized clinical SPECT/CT stress MPI images on the clinical task of detecting perfusion defects with an anthropomorphic model observer. CTLESS yielded statistically non-inferior performance compared to a CT-based AC (CTAC) method and significantly outperformed a non-AC (NAC) method on this clinical task. Similar results were observed in stratified analyses with different sexes, defect extents, and defect severities. The method was observed to generalize across two SPECT scanners, each with a different camera. In addition, CTLESS yielded similar performance as CTAC and outperformed NAC method on the fidelity-based figures of merit, namely, root mean squared error (RMSE) and structural similarity index measure (SSIM). Moreover, as we reduced the training dataset size, CTLESS yielded relatively stable AUC values and generally outperformed another DL-based AC method that directly estimated the attenuation coefficient within each voxel. These results demonstrate the capability of the CTLESS method for transmission-less AC in SPECT and motivate further clinical evaluation.\",\"PeriodicalId\":94033,\"journal\":{\"name\":\"IEEE transactions on medical imaging\",\"volume\":\"44 3\",\"pages\":\"1308-1320\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10767308\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE transactions on medical imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10767308/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE transactions on medical imaging","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10767308/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

衰减补偿(AC)虽然有利于通过单光子发射计算机断层扫描(SPECT)进行心肌灌注成像(MPI)的视觉解释任务,但通常需要单独的x射线CT组件,导致额外的辐射剂量,更高的成本,并且在SPECT和CT图像不一致的情况下可能不准确的诊断。为了解决这些问题,我们开发了一种使用深度学习和发射散射窗光子的心脏SPECT交流方法,而无需单独的透射扫描(CTLESS)。该方法利用基于CT扫描训练的多通道输入多解码器网络,将散射-能量窗投影重建的估计衰减图分割成不同的区域。预先定义的衰减系数被分配到这些区域,从而产生用于AC的衰减图。我们在一项回顾性研究中客观地评估了这种方法,该研究使用匿名临床SPECT/CT应力MPI图像,使用拟人化模型观察者检测灌注缺陷的临床任务。与基于ct的AC (CTAC)方法相比,CTLESS在统计上的表现不差,并且在该临床任务中显著优于非AC (NAC)方法。在不同性别、缺陷程度和缺陷严重程度的分层分析中也观察到类似的结果。该方法被观察到跨越两个SPECT扫描仪,每一个不同的相机。此外,CTLESS的表现与CTAC相似,并且在基于保真度的优点指标,即均方根误差(RMSE)和结构相似指数测量(SSIM)上优于NAC方法。此外,当我们减少训练数据集的大小时,CTLESS产生了相对稳定的AUC值,并且通常优于另一种基于dl的AC方法,该方法直接估计每个体素内的衰减系数。这些结果证明了CTLESS方法在SPECT中无传输交流的能力,并激发了进一步的临床评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CTLESS: A Scatter-Window Projection and Deep Learning-Based Transmission-Less Attenuation Compensation Method for Myocardial Perfusion SPECT
Attenuation compensation (AC), while being beneficial for visual-interpretation tasks in myocardial perfusion imaging (MPI) by single-photon emission computed tomography (SPECT), typically requires the availability of a separate X-ray CT component, leading to additional radiation dose, higher costs, and potentially inaccurate diagnosis in case of misalignment between SPECT and CT images. To address these issues, we developed a method for cardiac SPECT AC using deep learning and emission scatter-window photons without a separate transmission scan (CTLESS). In this method, an estimated attenuation map reconstructed from scatter-energy window projections is segmented into different regions using a multi-channel input multi-decoder network trained on CT scans. Pre-defined attenuation coefficients are assigned to these regions, yielding the attenuation map used for AC. We objectively evaluated this method in a retrospective study with anonymized clinical SPECT/CT stress MPI images on the clinical task of detecting perfusion defects with an anthropomorphic model observer. CTLESS yielded statistically non-inferior performance compared to a CT-based AC (CTAC) method and significantly outperformed a non-AC (NAC) method on this clinical task. Similar results were observed in stratified analyses with different sexes, defect extents, and defect severities. The method was observed to generalize across two SPECT scanners, each with a different camera. In addition, CTLESS yielded similar performance as CTAC and outperformed NAC method on the fidelity-based figures of merit, namely, root mean squared error (RMSE) and structural similarity index measure (SSIM). Moreover, as we reduced the training dataset size, CTLESS yielded relatively stable AUC values and generally outperformed another DL-based AC method that directly estimated the attenuation coefficient within each voxel. These results demonstrate the capability of the CTLESS method for transmission-less AC in SPECT and motivate further clinical evaluation.
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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信