Clinical Impact of Radiologist’s Alert System on Patient Care for High-risk Incidental CT Findings: A Machine Learning-Based Risk Factor Analysis

Abstract

Rationale and ObjectivesEfficient communication between radiologists and clinicians ordering computed tomography (CT) examinations is crucial for managing high-risk incidental CT findings (ICTFs). Herein, we introduced a Radiologist’s Alert and Patient Care Follow-up System (APCFS) for high-risk ICTFs. This study aimed to analyze the ICTFs detected by this system and the factors associated with them. Materials and MethodsThis retrospective study was approved by the institutional review board. We analyzed 52,331 CT examinations conducted between 2019 and 2021. In cases where high-risk ICTFs were identified, radiologists utilized APCFS to prompt ordering clinicians for further patient care. We assessed the frequency, affected body organs, presence or absence of therapeutic interventions, and diagnoses of high-risk ICTFs. An automated machine learning platform was employed to analyze the factors associated with high-risk ICTFs. ResultsAmong the 52,331 CT examinations, 507 (0.96%) revealed high-risk ICTFs, primarily affecting the lung (18.0%). Of these 507 high-risk ICTFs, 117 (23.1%) underwent therapeutic interventions, while 362 (71.4%) required only follow-up. Of the 117 cases undergoing interventions, 61 (52.1%) required surgery. Of the 219 high-risk ICTFs leading to a confirmed diagnosis, 146 (66.7%) were neoplastic lesions, including 88 (60.3%) malignancies, and 73 (33.3%) were non-neoplastic lesions. The top three risk factors associated with high-risk ICTFs in the regularized logistic regression model were the imaging protocol (especially aortic valve implantation planning protocol), imaging area (especially whole-body imaging), and clinical department (especially cardiology). ConclusionUtilizing APCFS, high-risk ICTFs were detected in approximately 1% of all CT examinations, likely associated with specific imaging protocols, areas, and clinical departments.