An artificial intelligence tool that may assist with interpretation of rapid plasma reagin test for syphilis: development and on-site evaluation.

Abstract

Objectives: The rapid plasma reagin (RPR) test, a traditional method for diagnosing syphilis and evaluating treatment efficacy, relies on subjective interpretation and requires high technical proficiency. This study aimed to develop and validate a user-friendly RPR-artificial intelligence (AI) interpretative tool.

Methods: A dataset comprising 600 images of photographed RPR cards from 276 negative and 223 positive RPR samples was used for model development. The reference result was based on consistent interpretations by at least two out of three experienced laboratory personnel. Then an interpretative model was developed using deep learning algorithms and loaded into smartphones for on-site interpretation at two clinical centers from October 2023 to April 2024.

Results: The model demonstrated an accuracy of 82·67% (95% CI 71·82%-90·09%) for reactive circles and 84·44% (95% CI 69·94%-93·01%) for non-reactive circles. In the field study, 669 specimens showed a sensitivity of 94·85% (95% CI 89·29%-97·73%), specificity of 91·56% (95% CI 88·78%-93·71%), and concordance of 92·23% (95% CI 89·87%-94·09%). The positive predictive value was 74·14% (95% CI 66·86%-80·33%) and negative predictive value was 98.59% (95% CI 96·98%-99·38%).

Conclusions: The tool assists in RPR interpretation standardization, enabling data traceability, and quality control for remote and underdeveloped areas.