Reliability and validity of an artificial intelligence-assisted system for the detection of abnormalities in chest and bone radiographs in an emergency department.
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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Silva Afonso Raissa de Fátima, Gallardo-Rodríguez Pilar, Espinosa Begoña, Bautista Alejandro, Serrano Javier, Veguillas Mónica, Corell María, Garrido Chamorro Raúl, Arenas Jiménez Juan, Astor Rodríguez Celia, Abellón Fernández Álvaro, Palazón Ruíz de Tremiño Álvaro, Garfias Baladrón María Javiera, Marquina Arribas Víctor, Chico-Sánchez Pablo, Gras Valenti Paula, Cabrer González Miguel, Martínez Riera Carlos, Moliner Mateu David, Salinas Serrano José María, Vivancos Rubio Emilio, Valdivieso Martínez Bernardo, Concepción-Aramendia Luis, Sanchez-Payá José, Llorens Pere
Аннотация
METHODS: We conducted a diagnostic test evaluation study on a random selection of 346 CXRs and 261 BXRs requested in the ED. Examinations were independently analysed by the AI systems and the various observers. The reference diagnosis (gold standard) was established by consensus among 3 radiologists, resorting to additional imaging tests or clinical information when necessary. Sensitivity, specificity, and positive and negative (NPV) predictive values were then calculated and compared.
RESULTS: For CXRs, AI (ChestView) showed overall sensitivity (64.4%) significantly higher than that of emergency physicians (49.2%; P = .018), although lower than that of the expert radiologist (83.9%; P .001). Performance was notable for the detection of nodules/masses (sensitivity 80.0%) and pneumothorax (NPV, 99.7%), but lower for consolidations (sensitivity, 40.4%). For BXRs, AI (BoneView) achieved sensitivity for fracture detection (87.5%) higher than that of the expert radiologist (77.1%), with an NPV of 96.9%. However, its performance was lower for detecting dislocations (sensitivity 60.0%) and joint effusions (25.0%).
CONCLUSIONS: The evaluated AI systems demonstrate clinically relevant performance in the emergency setting, significantly enhancing the diagnostic capacity of emergency physicians. Their high sensitivity for fracture detection and high NPV for pulmonary nodules, pneumothorax, and fractures establish them as a high-impact safety tool.