Comparison of Integrated Versus Sequential Artificial Intelligence-Based Computer-Aided Diagnosis Systems in Breast Ultrasound: A Prospective Pilot Study on Examination Time, Reproducibility, and Diagnostic Performance.

RATIONALE AND OBJECTIVES: To compare integrated and sequential artificial intelligence-based computer-aided diagnosis (AI-CAD) systems in terms of examination time, reproducibility, and diagnostic performance in breast ultrasound (US). MATERIALS AND METHODS: This prospective single-center study included women who underwent breast US at a breast imaging center between February and March 2025. Two real-time AI-CAD systems were evaluated: an integrated system providing simultaneous lesion detection and diagnosis during scanning, and a sequential system in which lesion detection and diagnostic assessment were performed separately. Examination time was assessed in patients who underwent paired breast US examinations with both AI-CAD systems during the same visit, with randomized examination order. Reproducibility was assessed by applying both systems twice to the same breast lesions. Diagnostic performance was evaluated using sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). RESULTS: Examination time analysis included 97 patients and showed longer examination time with sequential AI-CAD than with integrated AI-CAD (P < .001), regardless of examination order. Reproducibility analysis included 145 patients with 215 lesions and showed almost perfect agreement between the first and second acquisitions for both systems (integrated vs. sequential: κ = 0.81 vs. 0.83). For the comparison between the first and second acquisitions, κ values for the integrated versus sequential systems were 0.92 versus 0.76 for malignant lesions, 0.79 versus 0.84 for mass lesions, and 1.00 versus 0.75 for nonmass lesions. However, agreement patterns varied across other scan-plane comparisons. Diagnostic performance analysis included 242 patients. Integrated AI-CAD showed higher sensitivity (integrated vs. sequential: 87.6% vs. 76.9%; P < .001), whereas sequential AI-CAD showed higher specificity (integrated vs. sequential: 74.2% vs. 90.0%; P < .001). AUC did not differ between the two systems. CONCLUSION: Integrated and sequential AI-CAD systems showed complementary strengths in breast US. Integrated AI-CAD favored shorter examination time and higher sensitivity, whereas sequential AI-CAD favored higher specificity, with reproducibility differing according to lesion type.