Researchers have developed FORESEE-MS, a new evaluation protocol aimed at predicting future multiple sclerosis (MS) lesions from baseline FLAIR MRI scans. The study tested five deep learning models against a population-prior atlas, finding that the atlas performed best on pooled voxel-level metrics like AUROC and AUPRC. While some models showed slightly better within-patient lesion localization, the results were not statistically significant, indicating that patient-specific predictive information in baseline FLAIR MRI remains uncertain for improving lesion forecasting beyond general population patterns. AI
IMPACT This research explores the potential of AI in predicting disease progression, though current models show limited advantage over existing methods for multiple sclerosis lesion forecasting.
RANK_REASON Research paper detailing a new evaluation protocol and model performance on a specific medical imaging task. [lever_c_demoted from research: ic=1 ai=1.0]
- 3D U-Net
- Attn+ResBlock+VAE
- AUPRC
- Auroc
- Flair Mri
- FORESEE-MS
- Maryam Akhavan Aghdam
- MSSEG-2
- multiple sclerosis
- SwinUNETR
- Vít
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