AI Article Synopsis

  • The study evaluated how effective intelligence-based CAD software is for ultrasound in helping less experienced radiologists diagnose breast lesions.
  • The research involved 385 breast lesions and showed that the use of CAD improved diagnostic metrics like sensitivity and accuracy for junior and intermediate radiologists.
  • Additionally, the agreement between less experienced and experienced radiologists regarding BI-RADS categories significantly improved when CAD was employed, indicating its value as a clinical tool.

Article Abstract

This study aimed to assess the effectiveness of intelligence-based computer-aided diagnosis (CAD) software in ultrasound (US) and its potential to improve the diagnostic performance of less experienced radiologists, as well as the agreement on Breast Imaging Reporting and Data System (BI-RADS) categories with the experienced radiologist. Images of 385 breast lesions in 351 female taken from January 2019 to December 2020 were included. Two less experienced radiologists independently reviewed US images with and without CAD assistance, recording final assessments using the BI-RADS category. The diagnostic performance of CAD and radiologists were calculated and compared. Kappa statistics were used to determine agreement between the experienced radiologist and the less experienced radiologists, based on BI-RADS category before and after using CAD software. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of CAD software were 95.5%, 71.5%, 81.3%, 69.8%, and 95.9%, respectively, and those were improved in junior radiologist and intermediate-level radiologist after the addition of CAD. Additionally, with the assistance of CAD, the area under the curve was improved for both the junior radiologist and radiologist (0.704 vs 0.847 and 0.876 vs 0.900, P = 0.009, 0.005), although it remained lower than the senior radiologist. The agreement of BI-RADS category between the less experienced and the experienced radiologists showed a significant improvement (P = 0.04, 0.000). The CAD on US could improve less experienced radiologists' diagnostic performance and agreement on BI-RADS categories, making it an effective decision-making tool in clinical practice.

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http://dx.doi.org/10.1097/RUQ.0000000000000695DOI Listing

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