Submillimeter T₁ atlas for subject‐specific abnormality detection at 7T

Abstract

Purpose: Studies at 3T have shown that T 1 relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T 1 values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T. Methods: T 1 maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T 1 values was established by modeling the T 1 inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept. Results: The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results. Conclusion:A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.

Normative trajectories of R1, R2* and magnetic susceptibility in basal ganglia on healthy ageing

“…Alternatively, normative modelling of qMRI can be conducted at the voxel level, as exemplified in the work of Piredda et al (Piredda et al, 2023. These quantitative atlases serve as valuable resources for facilitating automated pathology detection at the voxel level.…”

Pushing MP2RAGE boundaries: Ultimate time‐efficient parameterization combined with exhaustive T1 synthetic contrasts

“…2 Moreover, from the UNI image, a quantitative T 1 map 11 can be derived that can be useful in clinical research. [12][13][14] In addition to this main UNI contrast, the original contrasts obtained with each inversion of the MP2RAGE (GRE TI1 and GRE TI2 ) could also provide new and specific information. Thus, it turns out that the contrast obtained during the first inversion (GRE TI1 ) of the MP2RAGE nullifies the voxels at the boundary between gray and white matter, a characteristic that has shown its relevance in focal cortical dysplasia detection at 3 T 15 and 7 T 16 (resulting in the renaming of this contrast as "EDGE" for edge-enhancing gradient echo).…”

“…This so‐called “UNI” contrast, free from $$$ {\mathrm{B}}_1^{-} $$$ reception bias, showed high potential for segmentation purposes 1,3 and major interest in pathological contexts such as epilepsy or multiple sclerosis (MS) imaging at 7 T 4–8 and 3 T, 9,10 progressively turning into a surrogate to the MPRAGE sequence for T 1 ‐weighted brain imaging 2 . Moreover, from the UNI image, a quantitative T 1 map 11 can be derived that can be useful in clinical research 12–14 …”