Limitations of multiexponential T1 mapping of cortical myeloarchitecture

Jakub Jamárik, Jiří Vitouš, Radovan Jiřík, Daniel Schwarz and Eva Koriťáková

PLOS ONE, 2025, vol. 20, issue 12, 1-15

Abstract: Neuropsychiatric malignancies frequently manifest at the level of individual cortical layers. The resolutions currently available for medical magnetic resonance imaging (MRI) prevent the study of these pathologies at clinically available field strengths of 3 T. Previous studies have claimed to have overcome these issues by extensions of quantitative MRI. Following this, the feasibility of multiexponential T1 relaxometry was assessed as a basis for in vivo delineation of cortical lamination. Three methods of non-linear least-squares-based multiexponential analysis were examined across key degrees of freedom identified in the literature. The methods employ a wide variety of ways to overcome the common pitfalls of multiexponential analysis, such as regularization, bound constraints, and repeated optimization from multiple starting points. A custom MRI phantom was 3D-printed and filled with various MnCL2 mixtures that represent the spin-lattice relaxation times that commonly occur in neocortical gray and white matter at 3 T. A 96 × 96-voxel image consisting of a single slice was acquired using a FLASH sequence and used to create 10 composite datasets with known distributions of T1 decay constants. The results showed that lowest relative error achieved across multiexponential models was approximately 20%. As achieving even this level of estimation accuracy requires either T1 ratios that rarely occur in the cerebral cortex or knowledge of the number of relaxation components and their expected values to a degree that is seldom feasible, the visualization of cortical layers based on these estimates is unlikely to represent their true distribution. In conclusion, the current methodological approaches do not allow for sufficiently precise estimation of T1 decay constants spanning the range of cortical gray and white matter.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0338035

DOI: 10.1371/journal.pone.0338035

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