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ORIGINAL RESEARCH article

Front. Med.
Sec. Pulmonary Medicine
Volume 11 - 2024 | doi: 10.3389/fmed.2024.1449537
This article is part of the Research Topic Advances in the Management of Lung Cancer: From the Bench to the Bedside and Back View all articles

Impact of AI-Assisted CXR Analysis in Detecting Incidental Lung Nodules and Lung Cancers in Non-Respiratory Outpatient Clinics

Provisionally accepted
Se Hyun Kwak Se Hyun Kwak Kyeong Yeon Kim Kyeong Yeon Kim Ji Soo Choi Ji Soo Choi Min Chul Kim Min Chul Kim Chang H. Seol Chang H. Seol Sung Ryeol Kim Sung Ryeol Kim Eun Hye LEE Eun Hye LEE *
  • College of Medicine, Yonsei University, Seoul, Republic of Korea

The final, formatted version of the article will be published soon.

    Purpose: The use of artificial intelligence (AI) for chest X-ray (CXR) analysis is becoming increasingly prevalent in medical environments. This study aimed to determine whether AI in CXR can unexpectedly detect lung nodule detection and influence patient diagnosis and management in non-respiratory outpatient clinics. Methods: In this retrospective study, patients over 18 years of age, who underwent CXR at Yongin Severance Hospital outpatient clinics between March 2021 and January 2023 and were identified to have lung nodules through AI software, were included. Commercially available AI-based lesion detection software (Lunit INSIGHT CXR) was used to detect lung nodules. Results: Out Of 56,802 radiographic procedures, 40,191 were from non-respiratory departments, with AI detecting lung nodules in 1,754 cases (4.4%). Excluding 139 patients with known lung lesions, 1,615 patients were included in the final analysis. Out of these, 30.7% (495/1615) underwent respiratory consultation and 31.7% underwent chest CT scans (512/1,615). As a result of the CT scans, 71.5% (366 cases) were found to have true nodules. Among these, the final diagnoses included 36 lung cancers (7.0%, 36/512), 141 lung nodules requiring follow-up (27.5%, 141/512), 114 active pulmonary infections (22.3%, 114/512), and 75 old inflammatory sequelae (14.6%, 75/512). The mean AI nodule score for lung cancer was significantly higher than that for other nodules (56.72 vs. 33.44, p<0.001). Additionally, active pulmonary infection had a higher consolidation score, and old inflammatory sequelae had the highest fibrosis score, demonstrating differences in the AI analysis among the final diagnosis groups. Conclusions: This study indicates that AI-detected incidental nodule abnormalities on CXR in non-respiratory outpatient clinics result in a substantial number of clinically significant diagnoses, emphasizing AI’s role in detecting lung nodules and need for further evaluation and specialist consultation for proper diagnosis and management.

    Keywords: artificial intelligence, X-Rays, Lung Neoplasms, Lung nodule, detection

    Received: 15 Jun 2024; Accepted: 29 Jul 2024.

    Copyright: © 2024 Kwak, Kim, Choi, Kim, Seol, Kim and LEE. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Eun Hye LEE, College of Medicine, Yonsei University, Seoul, Republic of Korea

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