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Multiparametric MRI dataset for susceptibility-based radiomic feature extraction and analysis
Cristiana Fiscone1, Giovanni Sighinolfi2, David Neil Manners3,4
1Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
Scientific Data
|June 4, 2024
Summary
Quantitative Susceptibility Mapping (QSM) radiomics can identify specific signs of pre-clinical inflammation in multiple sclerosis (MS) by analyzing normal-appearing white matter. This approach offers a more precise method for detecting early disease changes in the central nervous system.
Area of Science:
- Neuroimaging
- Radiology
- Biomarker Discovery
Background:
- Multiple sclerosis (MS) is a central nervous system demyelinating disease.
- Conventional MRI may show non-specific lesions.
- Quantitative MRI offers potential for early inflammation detection.
Purpose of the Study:
- To explore Quantitative Susceptibility Mapping (QSM) radiomics for analyzing normal-appearing white matter (NAWM) in MS.
- To quantify imaging biomarkers for pre-clinical inflammation.
- To assess the reliability of QSM-based radiomic features.
Main Methods:
- Utilized Quantitative Susceptibility Mapping (QSM) and radiomics.
- Analyzed normal-appearing white matter (NAWM) and its tracts.
- Included T1w, T2w, QSM, and DWI MRI sequences.
- Assessed feature reliability.
Main Results:
- QSM-based radiomic features were extracted from NAWM.
- The study outlines a workflow for QSM radiomics analysis.
- Feature reliability was assessed in a cohort of MS patients and healthy controls.
Conclusions:
- QSM radiomics shows promise for identifying specific imaging biomarkers in MS.
- This technique can potentially detect pre-clinical inflammatory changes.
- The presented workflow and dataset facilitate further research in MS neuroimaging.
