Diagnostic value of dual-layer spectral detector CT parameters for differentiating high- from low-grade bladder cancer.

IF 4.1 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Li Chen, Lili Xu, Xiaoxiao Zhang, Jiahui Zhang, Xin Bai, Qianyu Peng, Erjia Guo, Xiaomei Lu, Shenghui Yu, Zhengyu Jin, Gumuyang Zhang, Yi Xie, Huadan Xue, Hao Sun
{"title":"Diagnostic value of dual-layer spectral detector CT parameters for differentiating high- from low-grade bladder cancer.","authors":"Li Chen, Lili Xu, Xiaoxiao Zhang, Jiahui Zhang, Xin Bai, Qianyu Peng, Erjia Guo, Xiaomei Lu, Shenghui Yu, Zhengyu Jin, Gumuyang Zhang, Yi Xie, Huadan Xue, Hao Sun","doi":"10.1186/s13244-024-01881-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>This study aimed to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in distinguishing between low- and high-grade bladder cancer (BCa).</p><p><strong>Methods: </strong>This single-center retrospective study included pathologically confirmed BCa patients who underwent preoperative contrast-enhanced DLCT. Patients were divided into low- and high-grade groups based on pathology. We measured and calculated the following spectral CT parameters: iodine density (ID), normalized ID (NID), arterial enhancement fraction (AEF), extracellular volume (ECV) fraction, virtual non-contrast (VNC), slope of the attenuation curve, and Z effective (Z<sub>eff</sub>). Univariate and multivariable logistic regression analyses were used to determine the best predictive factors in differentiating between low- and high-grade BCa. We used receiver operating characteristic curve analysis to assess diagnostic performance and decision curve analysis to determine the net benefit.</p><p><strong>Results: </strong>The study included 64 patients (mean age, 64 ± 11.0 years; 46 men), of whom 42 had high-grade BCa and 22 had low-grade BCa. Univariate analysis revealed that differences in ID and NID in the corticomedullary phase, AEF, ECV, VNC, and Z<sub>eff</sub> images were statistically significant (p = 0.001-0.048). Multivariable analysis found that AEF was the best predictor of high-grade tumors (p = 0.006). With AEF higher in high-grade BCa, AEF results were as follows: area under the curve (AUC), 0.924 (95% confidence interval, 0.861-0.988); sensitivity, 95.5%; specificity, 81.0%; and accuracy, 85.9%. The cutoff valve of AEF for predicting high-grade BCa was 67.7%.</p><p><strong>Conclusion: </strong>Using DLCT AEF could help distinguish high-grade from low-grade BCa.</p><p><strong>Critical relevance statement: </strong>This research demonstrates that the arterial enhancement fraction (AEF), a parameter derived from dual-layer spectral detector CT (DLCT), effectively distinguishes between high- and low-grade bladder cancer, thereby aiding in the selection of appropriate clinical treatment strategies.</p><p><strong>Key points: </strong>This study investigated the value of dual-layer spectral detector CT in the assessment of bladder cancer (BCa) histological grade. The spectral parameter arterial enhancement fraction could help determine BCa grade. Our results can help clinicians formulate initial treatment strategies and improve prognostications.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"6"},"PeriodicalIF":4.1000,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11695557/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Insights into Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13244-024-01881-8","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

Abstract

Objectives: This study aimed to investigate the diagnostic value of spectral parameters of dual-layer spectral detector computed tomography (DLCT) in distinguishing between low- and high-grade bladder cancer (BCa).

Methods: This single-center retrospective study included pathologically confirmed BCa patients who underwent preoperative contrast-enhanced DLCT. Patients were divided into low- and high-grade groups based on pathology. We measured and calculated the following spectral CT parameters: iodine density (ID), normalized ID (NID), arterial enhancement fraction (AEF), extracellular volume (ECV) fraction, virtual non-contrast (VNC), slope of the attenuation curve, and Z effective (Zeff). Univariate and multivariable logistic regression analyses were used to determine the best predictive factors in differentiating between low- and high-grade BCa. We used receiver operating characteristic curve analysis to assess diagnostic performance and decision curve analysis to determine the net benefit.

Results: The study included 64 patients (mean age, 64 ± 11.0 years; 46 men), of whom 42 had high-grade BCa and 22 had low-grade BCa. Univariate analysis revealed that differences in ID and NID in the corticomedullary phase, AEF, ECV, VNC, and Zeff images were statistically significant (p = 0.001-0.048). Multivariable analysis found that AEF was the best predictor of high-grade tumors (p = 0.006). With AEF higher in high-grade BCa, AEF results were as follows: area under the curve (AUC), 0.924 (95% confidence interval, 0.861-0.988); sensitivity, 95.5%; specificity, 81.0%; and accuracy, 85.9%. The cutoff valve of AEF for predicting high-grade BCa was 67.7%.

Conclusion: Using DLCT AEF could help distinguish high-grade from low-grade BCa.

Critical relevance statement: This research demonstrates that the arterial enhancement fraction (AEF), a parameter derived from dual-layer spectral detector CT (DLCT), effectively distinguishes between high- and low-grade bladder cancer, thereby aiding in the selection of appropriate clinical treatment strategies.

Key points: This study investigated the value of dual-layer spectral detector CT in the assessment of bladder cancer (BCa) histological grade. The spectral parameter arterial enhancement fraction could help determine BCa grade. Our results can help clinicians formulate initial treatment strategies and improve prognostications.

双层光谱检测器CT参数对膀胱癌高低分级的诊断价值。
目的:探讨双层光谱检测器计算机断层扫描(dct)光谱参数在鉴别低级别和高级别膀胱癌(BCa)中的诊断价值。方法:这项单中心回顾性研究纳入了术前行对比增强dct的病理证实的BCa患者。根据病理情况将患者分为低级别组和高级别组。我们测量并计算了以下频谱CT参数:碘密度(ID)、归一化ID (NID)、动脉增强分数(AEF)、细胞外体积(ECV)分数、虚拟非对比(VNC)、衰减曲线斜率和有效Z值(Zeff)。采用单变量和多变量logistic回归分析确定区分低级别和高级别BCa的最佳预测因素。我们使用受试者工作特征曲线分析来评估诊断表现,并使用决策曲线分析来确定净效益。结果:纳入64例患者(平均年龄64±11.0岁;46例男性),其中42例为高级别BCa, 22例为低级别BCa。单因素分析显示,皮质髓质期、AEF、ECV、VNC和Zeff影像的ID和NID差异有统计学意义(p = 0.001-0.048)。多变量分析发现,AEF是高级别肿瘤的最佳预测因子(p = 0.006)。高分级BCa的AEF越高,AEF结果为:曲线下面积(AUC)为0.924(95%可信区间0.861 ~ 0.988);敏感性,95.5%;特异性,81.0%;准确率为85.9%。AEF预测高级别BCa的截止值为67.7%。结论:dct AEF可用于鉴别高、低分级BCa。关键相关性声明:本研究表明,动脉增强分数(AEF)是由双层光谱检测器CT (dct)得出的一个参数,可以有效区分高级别和低级别膀胱癌,从而有助于选择合适的临床治疗策略。本研究探讨双层光谱检测CT在膀胱癌(BCa)组织学分级评估中的价值。动脉增强分数的光谱参数可以帮助确定BCa的分级。我们的结果可以帮助临床医生制定初始治疗策略并改善预后。
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
Insights into Imaging
Insights into Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
7.30
自引率
4.30%
发文量
182
审稿时长
13 weeks
期刊介绍: Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere! I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe. Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy. A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field. I³ is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly. The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members. The journal went open access in 2012, which means that all articles published since then are freely available online.
×
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