- A Review of Intracranial Aneurysm Imaging Modalities, from CT to State-of-the-Art MR
This review article covers the established imaging modalities (eg, CT, CTA, DSA, FLAIR, 3D TOF-MRA, contrast-enhanced MRA) and novel MR techniques (MR vessel wall imaging, dynamic contrast-enhanced MRI, computational fluid dynamics) of intracranial aneurysm evaluation. Artificial intelligence software and its integration into diagnostic and risk-stratification pipelines for intracranial aneurysms are also discussed.
- Enhancing Lesion Detection in Inflammatory Myelopathies: A Deep Learning–Reconstructed Double Inversion Recovery MRI Approach
This observational study compared the acquisition time, image quality, diagnostic confidence, and lesion detection rates among sagittal T2WI, standard DIR, and DL-reconstructed DIR in patients with inflammatory myelopathies. It was found that DL-reconstructed DIR significantly reduced acquisition time and improved image quality. DL-reconstructed DIR also improved lesion detection, showing superior diagnostic performance in inflammatory myelopathies without compromising diagnostic confidence.
- Development and Evaluation of Automated Artificial Intelligence–Based Brain Tumor Response Assessment in Patients with Glioblastoma
The goal of this study was to compare AI-based volumetric GBM MRI response assessment with standardized radiologist response assessments. The AI-based volumetric response assessment yielded overall moderate performance for recapitulating most human response assessment categories (BT-RADS 1, 2, and 4) but demonstrated the lowest performance for predicting BT-RADS 3, which is likely related to the high variability of this assessment. In comparison to radiologist assessment, the AI-based volumetric GBM MRI response assessment showed comparable performance for overall survival.
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