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Sensitivity of Quantitative Susceptibility Mapping in Clinical Brain Research
Arxiv
|February 20, 2025
Summary
Algorithmic choices in Quantitative Susceptibility Mapping (QSM) significantly impact brain imaging results. Optimizing QSM pipelines is crucial for reliable detection of neurodegenerative diseases and aging effects.
Area of Science:
- Neuroimaging
- Biomarkers
- Medical Physics
Background:
- Quantitative Susceptibility Mapping (QSM) is an advanced MRI technique measuring brain tissue composition (iron, calcium, myelin).
- QSM's clinical application in neurodegenerative diseases is growing, but the impact of processing choices on outcomes is unclear.
Purpose of the Study:
- To evaluate how background field removal (BFR), dipole inversion, and anatomical referencing affect QSM sensitivity and reproducibility.
- To assess QSM's ability to detect group and longitudinal changes in deep gray matter susceptibility in a clinical context.
Main Methods:
- Compared 378 QSM pipelines on a 10-year longitudinal dataset of healthy adults.
- Analyzed pipeline sensitivity to detect age-related susceptibility changes in deep gray matter (DGM).
Main Results:
- High variability in QSM pipeline sensitivity was observed.
- BFR algorithm and referencing strategy significantly influenced reproducibility error and sensitivity.
- REப்பையும் with AMP-PE, HEIDI, or LSQR inversion demonstrated the highest sensitivity.
Conclusions:
- Algorithmic choices in QSM processing critically affect the accuracy and reliability of detecting brain physiological changes.
- Careful QSM pipeline configuration is essential for optimizing clinical research and trials using QSM as a biomarker.
