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Evaluation of the Quadri-Planes Method in Computer-Aided Diagnosis of Breast Lesions by Ultrasonography: Prospective Single-Center Study

Authors :
Yongping, Liang
Juan, Zhang
Zhou, Ping
Yongfeng, Zhao
Liu, Wengang
Shi, Yifan
Source :
JMIR Medical Informatics, Vol 8, Iss 5, p e18251 (2020)
Publication Year :
2020
Publisher :
JMIR Publications, 2020.

Abstract

BackgroundComputer-aided diagnosis (CAD) is a tool that can help radiologists diagnose breast lesions by ultrasonography. Previous studies have demonstrated that CAD can help reduce the incidence of missed diagnoses by radiologists. However, the optimal method to apply CAD to breast lesions using diagnostic planes has not been assessed. ObjectiveThe aim of this study was to compare the performance of radiologists with different levels of experience when using CAD with the quadri-planes method to detect breast tumors. MethodsFrom November 2018 to October 2019, we enrolled patients in the study who had a breast mass as their most prominent symptom. We assigned 2 ultrasound radiologists (with 1 and 5 years of experience, respectively) to read breast ultrasonography images without CAD and then to perform a second reading while applying CAD with the quadri-planes method. We then compared the diagnostic performance of the readers for the 2 readings (without and with CAD). The McNemar test for paired data was used for statistical analysis. ResultsA total of 331 patients were included in this study (mean age 43.88 years, range 17-70, SD 12.10), including 512 lesions (mean diameter 1.85 centimeters, SD 1.19; range 0.26-9.5); 200/512 (39.1%) were malignant, and 312/512 (60.9%) were benign. For CAD, the area under the receiver operating characteristic curve (AUC) improved significantly from 0.76 (95% CI 0.71-0.79) with the cross-planes method to 0.84 (95% CI 0.80-0.88; P

Details

Language :
English
ISSN :
22919694
Volume :
8
Issue :
5
Database :
Directory of Open Access Journals
Journal :
JMIR Medical Informatics
Publication Type :
Academic Journal
Accession number :
edsdoj.3397b429b682489f9810cce3be47ca48
Document Type :
article
Full Text :
https://doi.org/10.2196/18251