The study of plain CT combined with contrast-enhanced CT-based models for predicting malignancy of solitary solid pulmonary nodules

Author:

Zhang Wenjia1,Cui Xiaonan2,Wang Jing3,Cui Sha4,Yang Jianghua4,Meng Junjie4,Zhu Weijie2,Li Zhiqi2,Niu Jinliang1

Affiliation:

1. Shanxi Medical University

2. Tianjin Medical University Cancer Institute and Hospital

3. Hangzhou Medical College

4. Second Hospital of Shanxi Medical University

Abstract

Abstract

Background: Tocompare the diagnostic performance between only plain CT based model and plain &contrast-enhanced CT based model in the classification of malignancy for solitary solid pulmonary nodules. Methods: From January 2011 to July 2020, 527 patients with pathologically confirmed solitary solid pulmonary nodules collected at two centers with similar CT examinations and scanning parameters. Prior to surgery, all patients underwent both plain and contrast-enhanced chest CT scan. Two clinical characteristics, fifteen plain CT characteristics and four enhanced characteristics were used to develop logistic regression model with only plain CT and plain & contrast-enhanced CT. The diagnostic performance of the two models were assessed separately in the development and external validation cohorts using the AUC. Results: 392patients from A center were included in the development cohort (median size, 20.0 [IQR, 15.0-24.0] mm; mean age, 55.8 [SD, 9.9] years; male 53.3%). 153 patients from B center were included in the external validation cohort (median size, 20.0 [IQR, 16.0-24.0] mm; mean age, 56.4 [SD, 9.6] years; man 51.9%).Preoperative patients with 201 malignant (adenocarcinoma, 148 [73.6%]; squamous cell carcinoma, 35 [17.4%]; large cell carcinoma,18 [9.0%]) and 326 benign (pulmonary hamartoma, 118[36.2%]; sclerosing pneumocytoma, 35 [10.7%]; tuberculosis, 104 [31.9%]; inflammatory pseudonodule, 69 [21.2%]) solitary solid pulmonary nodules were gathered from two independent centers.. The mean sensitivity, specificity, accuracy, PPV, NPV, and AUC (95%CI) of the only plain CT based model were 0.79, 0.78, 0.79, 0.67, 0.87, and 0.88 (95%CI, 0.82-0.93), the plain & contrast enhanced CT based model were 0.88, 0.91, 0.90, 0.84, 0.93, 0.93 (95%CI, 0.88-0.98) in external validation cohort, respectively. Conclusions:A logistic regression model based on plain and contrast-enhanced CT characteristics showed exceptional performance in the evaluation of malignancy for solitary solid lung nodules. The utilization of this contrast-enhanced CT model would provide recommendations concerning follow-up or surgical intervention for preoperative patient presenting with solid lung nodules.

Publisher

Research Square Platform LLC

Reference29 articles.

1. Projections in breast and lung cancer mortality among women: A Bayesian analysis of 52 countries worldwide;Martín-Sánchez JC;Cancer Res,2018

2. Chen, W., et al. Cancer statistics in China, 2015. CA: a cancer journal for clinicians66, 115–132 (2016).

3. European position statement on lung cancer screening;Oudkerk M;The Lancet Oncology,2017

4. Liang, W., et al. Chinese multi-institutional registry (CMIR) for resected non-small cell lung cancer: survival analysis of 5,853 cases. Journal of thoracic disease5, 726–729 (2013).

5. Community-based lung cancer screening with low-dose CT in China: Results of the baseline screening;Yang WJ;Lung Cancer,2018

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