AI-Accelerated Brain MRI: 30% Faster Scans with Uncompromised Diagnostic Accuracy for Aging Populations
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.
Authors
- Wenquan Gu
- Yongming Dai (ORCID: https://orcid.org/0000-0002-6084-9685)
- Qi Zhang (ORCID: https://orcid.org/0000-0002-5377-577X)
- Dongmei Wu (ORCID: https://orcid.org/0009-0002-8483-5883)
- Chunhong Yang (ORCID: https://orcid.org/0000-0003-1087-8135)
- Shanshan Cai (ORCID: https://orcid.org/0000-0002-0594-0953)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/3847
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00