Methods of Visualizing the Results of an Artificial-Intelligence-Based Computer-Aided Detection System for Chest Radiographs: Effect on the Diagnostic Performance of Radiologists

Autor: Sungho Hong, Eui Jin Hwang, Soojin Kim, Jiyoung Song, Taehee Lee, Gyeong Deok Jo, Yelim Choi, Chang Min Park, Jin Mo Goo
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Diagnostics, Vol 13, Iss 6, p 1089 (2023)
Druh dokumentu: article
ISSN: 13061089
2075-4418
DOI: 10.3390/diagnostics13061089
Popis: It is unclear whether the visualization methods for artificial-intelligence-based computer-aided detection (AI-CAD) of chest radiographs influence the accuracy of readers’ interpretation. We aimed to evaluate the accuracy of radiologists’ interpretations of chest radiographs using different visualization methods for the same AI-CAD. Initial chest radiographs of patients with acute respiratory symptoms were retrospectively collected. A commercialized AI-CAD using three different methods of visualizing was applied: (a) closed-line method, (b) heat map method, and (c) combined method. A reader test was conducted with five trainee radiologists over three interpretation sessions. In each session, the chest radiographs were interpreted using AI-CAD with one of the three visualization methods in random order. Examination-level sensitivity and accuracy, and lesion-level detection rates for clinically significant abnormalities were evaluated for the three visualization methods. The sensitivity (p = 0.007) and accuracy (p = 0.037) of the combined method are significantly higher than that of the closed-line method. Detection rates using the heat map method (p = 0.043) and the combined method (p = 0.004) are significantly higher than those using the closed-line method. The methods for visualizing AI-CAD results for chest radiographs influenced the performance of radiologists’ interpretations. Combining the closed-line and heat map methods for visualizing AI-CAD results led to the highest sensitivity and accuracy of radiologists.
Databáze: Directory of Open Access Journals
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje