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Three-dimensional multi-parameter brain mapping using MR fingerprinting

The purpose of this study was to develop and test a 3D multi-parameter MR fingerprinting (MRF) method for brain imaging applications. The subject cohort included 5 healthy volunteers, repeatability tests done on 2 healthy volunteers and tested on two multiple sclerosis (MS) patients. A 3D-MRF imagin...

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Detalles Bibliográficos
Autores principales: Menon, Rajiv G., Sharafi, Azadeh, Muccio, Marco, Smith, Tyler, Kister, Ilya, Ge, Yulin, Regatte, Ravinder R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055680/
https://www.ncbi.nlm.nih.gov/pubmed/36993561
http://dx.doi.org/10.21203/rs.3.rs-2675278/v1
Descripción
Sumario:The purpose of this study was to develop and test a 3D multi-parameter MR fingerprinting (MRF) method for brain imaging applications. The subject cohort included 5 healthy volunteers, repeatability tests done on 2 healthy volunteers and tested on two multiple sclerosis (MS) patients. A 3D-MRF imaging technique capable of quantifying T(1), T(2) and T(1ρ) was used. The imaging sequence was tested in standardized phantoms and 3D-MRF brain imaging with multiple shots (1, 2 and 4) in healthy human volunteers and MS patients. Quantitative parametric maps for T(1), T(2), T(1ρ), were generated. Mean gray matter (GM) and white matter (WM) ROIs were compared for each mapping technique, Bland-Altman plots and intra-class correlation coefficient (ICC) were used to assess repeatability and Student T-tests were used to compare results in MS patients. Standardized phantom studies demonstrated excellent agreement with reference T(1)/T(2/)T(1ρ) mapping techniques. This study demonstrates that the 3D-MRF technique is able to simultaneously quantify T(1), T(2) and T(1ρ) for tissue property characterization in a clinically feasible scan time. This multi-parametric approach offers increased potential to detect and differentiate brain lesions and to better test imaging biomarker hypotheses for several neurological diseases, including MS.