Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis

Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomic techniques that exploit its intrinsic quantitative nature, QSM may furnish biomarkers to facilitate early diagnosis of MS and timely assessment of progression. In this work, we explore the robustness of QSM radiomic features by varying the number of grey levels (GLs) and echo times (TEs), in a sample of healthy controls and patients with MS. We analysed the white matter in total and within six clinically relevant tracts, including the cortico-spinal tract and the optic radiation. After optimising the number of GLs (n = 64), at least 65% of features were robust for each Volume of Interest (VOI), with no difference (p > .05) between left and right hemispheres. Different outcomes in feature robustness among the VOIs depend on their characteristics, such as volume and variance of susceptibility values. This study validated the processing pipeline for robustness analysis and established the reliability of QSM-based radiomics features against GLs and TEs. Our results provide important insights for future radiomics studies using QSM in clinical applications.

Descrição

Fiscone, C., Rundo, L., Lugaresi, A., Manners, D. N., Allinson, K., Baldin, E., Vornetti, G., Lodi, R., Tonon, C., Testa, C., Castelli, M., & Zaccagna, F. (2023). Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis. Scientific Reports, 13(1), 1-16. [16239]. https://doi.org/10.1038/s41598-023-42914-4---The publication of this article was supported by the “Ricerca Corrente” funding from the Italian Ministry of Health. This work is partially funded by national funds thought the FCT – Foundation for Science and Technology, I.P., within the scope of the project UIDB/04152/2020 – Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS.