Artificial Intelligence Methods for the Argenta Classification of Deformational Plagiocephaly to Predict Severity and Treatment Recommendation

Abstract

Introduction Deformational plagiocephaly (DP) can be classified into 5 severity types using the Argenta scale (AS). Patients with type III or higher require referral to craniofacial surgery for management. Primary care pediatricians (PCPs) are often the first to encounter patients with DP, but current screening methods are subjective, increasing the risk of bias, especially for clinicians with little exposure to this population. The authors propose the use of artificial intelligence (AI) to classify patients with DP using the AS and to make recommendations for referral to craniofacial surgery. Methods Vertex photographs were obtained for patients diagnosed with unilateral DP from 2019 to 2020. Using the photographs, an AI program was created to characterize the head contour of these infants into 3 groups based on the AS. The program was trained using photographs from patients whose DP severity was confirmed clinically by craniofacial surgeons. To assess the accuracy of the software, the AS predicted by the program was compared with the clinical diagnosis. Results Nineteen patients were assessed by the AI software. All 3 patients with type I DP were correctly classified by the program (100%). In addition, 4 patients with type II were correctly identified (67%), and 7 were correctly classified as type III or greater (70%). Conclusions Using vertex photographs and AI, the authors were able to objectively classify patients with DP based on the AS. If converted into a smartphone application, the program could be helpful to PCPs in remote or low-resource settings, allowing them to objectively determine which patients require referral to craniofacial surgery.