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Abstract #3847

AI-Accelerated Brain MRI: 30% Faster Scans with Uncompromised Diagnostic Accuracy for Aging Populations

Wenquan Gu1, Chunhong Yang2, Qi zhang2, Sunmei Cai2, Dongmei Wu3, and Yongming Dai4
1Department of Radiology, Shanghai Punan Hospital of Pudong New Area, Shanghai, China, 2Shanghai Punan Hospital of Pudong New Area, Shanghai, China, 3Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China, 4School of Biomedical Engineering, ShanghaiTech University, Shanghai, China

Synopsis

Keywords: Diagnosis/Prediction, AI/ML Software

Motivation: Conventional brain MRI protocols require longer scan times, leading to patient discomfort and motion artifacts, which is especially problematic for aging populations with neurodegenerative or cerebrovascular diseases.

Goal(s): This study aimed to reduce scan time using AI-assisted compressed sensing (ACS) while maintaining diagnostic accuracy and image quality equivalent to conventional parallel imaging.

Approach: Seventy patients underwent both ACS and conventional brain MRI. Radiologists evaluated image quality (artifacts, boundary sharpness, lesion visibility) and diagnostic performance for conditions like white matter hyperintensities and infarcts.

Results: ACS reduced scan time by 29.2%, improved image quality, and maintained diagnostic accuracy with strong inter-observer agreement.

Impact: ACS dramatically reduces brain MRI scan time while maintaining diagnostic accuracy. This offers a practical, time-efficient alternative for routine neuroimaging, particularly in elderly populations and resource-limited settings, enhancing patient comfort and clinical workflow without sacrificing diagnostic quality.

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Keywords