Multiparametric MRI dataset for susceptibility-based radiomic feature extraction and analysis.
Sci Data
; 11(1): 575, 2024 Jun 04.
Article
em En
| MEDLINE
| ID: mdl-38834674
ABSTRACT
Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g., T2w images) help diagnose MS, although they sometimes reveal non-specific lesions. Quantitative MRI techniques are capable of quantifying imaging biomarkers in vivo, offering the potential to identify specific signs related to pre-clinical inflammation. Among those techniques, Quantitative Susceptibility Mapping (QSM) is particularly useful for studying processes that influence the magnetic properties of brain tissue, such as alterations in myelin concentration. Because of its intrinsic quantitative nature, it is particularly well-suited to be analyzed through radiomics, including techniques that extract a high number of complex and multi-dimensional features from radiological images. The dataset presented in this work provides information about normal-appearing white matter (NAWM) in a cohort of MS patients and healthy controls. It includes QSM-based radiomic features from NAWM and its tracts, and MR sequences necessary to implement the pipeline T1w, T2w, QSM, DWI. The workflow is outlined in this article, along with an application showing feature reliability assessment.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Substância Branca
/
Imageamento por Ressonância Magnética Multiparamétrica
/
Esclerose Múltipla
Limite:
Humans
Idioma:
En
Revista:
Sci Data
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Itália