Development and Validation of an MRI‐Based Nomogram for Preoperative Detection of Muscle Invasion in VI‐RADS 3

Author:

Yu Ruixi1,Cai Lingkai12,Cao Qiang1,Liu Peikun1,Gong Yuxi3,Li Kai1,Wu Qikai1,Zhang Yudong4,Li Pengchao1,Yang Xiao1,Lu Qiang1ORCID

Affiliation:

1. Department of Urology The First Affiliated Hospital of Nanjing Medical University Nanjing China

2. Department of Urology Wuxi Medical Center, Nanjing Medical University Wuxi China

3. Department of Pathology The First Affiliated Hospital of Nanjing Medical University Nanjing China

4. Department of Radiology The First Affiliated Hospital of Nanjing Medical University Nanjing China

Abstract

BackgroundThe relationship between tumor and muscle layer in the vesical imaging‐reporting and data system (VI–RADS) 3 is ambiguous, and there is a lack of preoperative and non‐invasive procedures to detect muscle invasion in VI‐RADS 3.PurposeTo develop a nomogram based on MRI features for detecting muscle invasion in VI–RADS 3.Study TypeRetrospective.Population235 cases (Age: 67.5 ± 11.5 years) with 11.9% females were randomly divided into a training cohort (n = 164) and a validation cohort (n = 71).Field Strength/Sequence3T, T2‐weighted imaging (turbo spin‐echo), diffusion‐weighted imaging (breathing‐free spin echo), and dynamic contrast‐enhanced imaging (gradient echo).Assessment3 features were selected from the training cohort, including tumor contact length greater than maximum tumor diameter (TCL > Dmax), flat tumor morphology, and lower standard deviation of apparent diffusion coefficient (ADCSD). Three readers assessed VI‐RADS scores and the tumor morphology.Statistical TestsInterobserver agreement was assessed by Kappa analysis. Features for final analysis were selected by logistic regression. The performance of the nomogram was evaluated by the receiver operating characteristic curve, decision curve analysis, and calibration curve.ResultsTCL > Dmax, flat morphology, and lower ADCSD were the independent risk factors for muscle invasive in VI‐RADS 3. The AUCs, accuracy, sensitivity, and specificity of the nomogram 1 composed of three features for detecting muscle invasion were 0.852 (95% CI: 0.793–0.912), 0.756, 0.917, and 0.663 in the training cohort, and 0.885 (95% CI: 0.801–0.969), 0.817, 0.900, and 0.784 in the validation cohort. The nomogram 2 without ADCSD has nearly the same performance as the nomogram 1.Data ConclusionNomogram can be an efficient tool for preoperative detection of muscle invasion in VI–RADS 3.Level of Evidence3Technical EfficacyStage 2

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3