Deep Learning Nomogram for the Identification of Deep Stromal Invasion in Patients With Early‐Stage Cervical Adenocarcinoma and Adenosquamous Carcinoma: A Multicenter Study

Author:

Xiao Mei Ling1,Qian Ting2,Fu Le3,Wei Yan4,Ma Feng Hua5,Gu Wei Yong6,Li Hai Ming7ORCID,Li Yong Ai1,Qian Zhao Xia2,Cheng Jie Jun3,Zhang Guo Fu5ORCID,Qiang Jin Wei1ORCID

Affiliation:

1. Department of Radiology Jinshan Hospital, Fudan University Shanghai China

2. Department of Radiology International Peace Maternity and Child Health Hospital, Shanghai Jiaotong University School of Medicine Shanghai China

3. Department of Radiology Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine Shanghai China

4. Department of Automation Zhejiang University of Technology Hangzhou China

5. Department of Radiology Obstetrics & Gynecology Hospital, Fudan University Shanghai China

6. Department of Pathology Obstetrics & Gynecology Hospital, Fudan University Shanghai China

7. Department of Radiology Fudan University Shanghai Cancer Center Shanghai China

Abstract

BackgroundDeep stromal invasion (DSI) is one of the predominant risk factors that determined the types of radical hysterectomy (RH). Thus, the accurate assessment of DSI in cervical adenocarcinoma (AC)/adenosquamous carcinoma (ASC) can facilitate optimal therapy decision.PurposeTo develop a nomogram to identify DSI in cervical AC/ASC.Study TypeRetrospective.PopulationSix hundred and fifty patients (mean age of 48.2 years) were collected from center 1 (primary cohort, 536), centers 2 and 3 (external validation cohorts 1 and 2, 62 and 52).Field Strength/Sequence5‐T, T2‐weighted imaging (T2WI, SE/FSE), diffusion‐weighted imaging (DWI, EPI), and contrast‐enhanced T1‐weighted imaging (CE‐T1WI, VIBE/LAVA).AssessmentThe DSI was defined as the outer 1/3 stromal invasion on pathology. The region of interest (ROI) contained the tumor and 3 mm peritumoral area. The ROIs of T2WI, DWI, and CE‐T1WI were separately imported into Resnet18 to calculate the DL scores (TDS, DDS, and CDS). The clinical characteristics were retrieved from medical records or MRI data assessment. The clinical model and nomogram were constructed by integrating clinical independent risk factors only and further combining DL scores based on primary cohort and were validated in two external validation cohorts.Statistical TestsStudent's t‐test, Mann–Whitney U test, or Chi‐squared test were used to compare differences in continuous or categorical variables between DSI‐positive and DSI‐negative groups. DeLong test was used to compare AU‐ROC values of DL scores, clinical model, and nomogram.ResultsThe nomogram integrating menopause, disruption of cervical stromal ring (DCSRMR), DDS, and TDS achieved AU‐ROCs of 0.933, 0.807, and 0.817 in evaluating DSI in primary and external validation cohorts. The nomogram had superior diagnostic ability to clinical model and DL scores in primary cohort (all P < 0.0125 [0.05/4]) and CDS (P = 0.009) in external validation cohort 2.Data ConclusionThe nomogram achieved good performance for evaluating DSI in cervical AC/ASC.Level of Evidence3Technical EfficacyStage 2

Funder

National Natural Science Foundation of China

Shanghai Municipal Health Commission

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

全球学者库

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

"全球学者库"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,当前全球学者库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 © 2019-2023 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