0591

Brain and cervical spinal cord myelination and age-related changes in adulthood: a preliminary study based on ihMTsat and T₁ relaxometry mapping

Arash Forodighasemabadi^1,2,3,4, Lucas Soustelle^1,2, Olivier M. Girard^1,2, Thomas Troalen⁵, Jean-Philippe Ranjeva^1,2, Guillaume Duhamel^1,2, and Virginie Callot^1,2,4
¹Aix-Marseille Univ, CNRS, CRMBM, Marseille, France, ²APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France, ³Aix-Marseille Univ, Université Gustave Eiffel, LBA, Marseille, France, ⁴iLab-Spine International Associated Laboratory, Montreal, Canada, Marseille, France, ⁵Siemens Healthcare SAS, Saint-Denis, France

Synopsis

Keywords: Neurodegeneration, Aging

Inhomogeneous Magnetization Transfer (ihMT) has shown to be a biomarker of myelin with enhanced specificity as compared to conventional MT. To compensate for B₁⁺ and T₁ effects, a 3D ihMT-RAGE sequence with an ihMTsat framework has recently been proposed.

In this study, ihMTsat was used in combination with an optimized MP2RAGE sequence to study both brain and spinal cord adulthood aging process.

The ihMTsat and R₁=1/T₁ metrics followed an inverse U-shaped evolution with age in different ROIs, from which a maturation age was extracted. A multiparametric (R₁,ihMTsat) voxel-wise analysis revealed significant age effect in the microstructure of different cord tracts.

Introduction

A wide range of MR techniques has been developed in the past decades to provide sensitive and/or specific biomarkers of myelin and subsequently investigate myelin impairments occurring in various neurodegenerative diseases¹ and normal aging^2,3.
Among them, the recently developed inhomogeneous Magnetization Transfer (ihMT)⁴ technique has attracted attention thanks to increased specificity to myelinated tissue^5,6.
Nevertheless, the standard ihMT Ratio (ihMTR) derived from ihMT sequences can be biased by B₁⁺ inhomogeneity and T₁ relaxation effects^7–9. To compensate from these effects, a strategy inspired by Helms et al¹⁰ was recently developed to derive a T₁- and B₁⁺- unbiased ihMTsat parameter^11,12, and applied to study the cortical myeloarchitecture⁷.
In this study and for the first time, an ihMTsat approach, optimized for both brain and cervical spinal cord (cSC) imaging, was combined with an optimized MP2RAGE T₁ mapping^13,14 to study age-related changes in different regions of the human brain and cSC.

Materials & Methods

Thirty-six adult healthy subjects of different age ranges (younger (Y), middle-aged (M), and older (O), cf. Table 1) were scanned with a 3T MR system (MAGNETOM Vida, Siemens Healthcare, Germany) and a 20-channel head and neck coil.
The protocol included: a prototype 3D ihMT-RAGE sequence with a 2-mm isotropic / 0.9×0.9×10-mm3 resolution for brain/cSC, respectively (cf. Fig1.a), a 0.9-mm isotropic resolution T₁ Magnetization Prepared 2 Rapid Acquisition Gradient Echo (MP2RAGE) sequence¹⁴ optimized for simultaneous brain and cSC¹³, and a B₁⁺ mapping based on a pre-saturated turbo flash sequence¹⁶.

Post-processing & Statistical analysis

The main post-processing steps are depicted in Figure 1.b-d. Briefly, T₁ data were corrected for B₁⁺ inhomogeneity as in¹⁷. The corrected T₁ map, B₁⁺ map and the motion-corrected MT volumes, were then used to calculate the ihMTsat map, based on the strategy described in ^7,15,18 and using a freely available post-processing pipeline (https://github.com/lsoustelle/ihmt_proc).
Quantification of T₁ and ihMTsat metrics in the subject space were performed using the ROI masks from PAM50¹⁹ on SC and JHU WM tracts^20,21 and MNI parcellation maps^22,23 on brain. To investigate the evolution of metrics with age, a quadratic regression was used separately to fit T₁ and ihMTsat values as a function of the subjects’ age, as performed in previous studies with R₁ and DTI metrics^24,25. A “maturation” age was derived from the fitted curve as the age at maximal ihMTsat (respectively minimal T₁).
To further analyze the maturation of different tissues in the middle-aged group, R₁ (=1/T₁) and ihMTsat maps were used in voxel-wise multi-variate analyses using Non-Parametric Combination (NPC) tool²⁶ from PALM (version alpha119) using 5000 permutations (p-value<0.05 for significance).

Results & Discussion

Examples of the quadratic fit for T₁ and ihMTsat on different ROIs are illustrated in figure 2. The T₁ values (blue curve) follow a U-shape trend with age (decreasing to a minimum and then increasing), in agreement with previous literature²⁴ on brain. The ihMTsat values (orange curve) follow an inverse U-shape, as similarly observed for Fractional Anisotropy in DTI measurements^25,27 on brain. Although similar trends for T₁ and ihMTsat were observed for SC, none of the SC ROI regressions reached the significance level. To our knowledge, the quadratic evolution for quantitative metrics on SC has never been reported.
The heterogeneity of the aging process and maturation across different regions is illustrated on Figure 3. The ihMTsat (resp T₁) “maturation” ages were found in average as 38.6 (resp 42.1) years for brain whole WM, and 46.1 (resp 52.2) for brain whole GM (see fig. 3). In all GM ROIs, maturation age obtained from T₁ was higher than ihMTsat, presumably due to concomitant sensitivity of T₁ to other factors such as iron deposition that further reduces the metric value. This observation is consistent with the contrast fraction (~36% vs. 10%) that comes from iron in GM vs. WM²⁸.
Finally, PALM analysis results combining R₁ and ihMTsat values and comparing the middle-aged group to the younger and older ones using the WM mask are shown in Figure 4. Significant differences were observed in various regions such as PCR, SLF, PTR, and SS in brain WM, as well as PST and LST (especially left tracts) in cSC, whereas univariate analyses (with either modality) led to no significant clusters (data not shown). Interestingly, significant clusters in cSC WM, especially in sensory pathways, were demonstrated, which could indicate the presence of a maturation process in the cord, as observed in the brain. To the best of our knowledge, this has never been reported in the literature before.
No significant clusters were found in GM.

Conclusion

The ihMTsat metric was used for the first time to investigate aging in healthy adults’ brain and cSC. Parametric microstructural characterization of brain and SC using T₁ and ihMT showed a lifespan quadratic evolution of brain WM and GM but not of SC. However, voxel-wise multiparametric approach combining the two parameters showed significant differences in WM bundle microstructure for middle-aged subjects compared to younger and older subjects both in brain and SC, suggesting a similar maturation and aging process in SC as in brain. This database is intended to be completed over time and made available for future studies investigating neurodegenerative pathologies.

Acknowledgements

This work was performed within a laboratory member of France Life Imaging network (grant ANR-11-INBS-0006) and was supported by the Institut Carnot Star, the ARSEP Foundation (Fondation pour l’Aide à la Recherche sur la Sclérose en Plaques) and the CNRS (Centre National de la Recherche Scientifique). The project also received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No713750, with the financial support of the Regional Council of Provence-Alpes-Côte d’Azur. This work received support from the French government under the France 2030 investment plan, as part of the Initiative d'Excellence d'Aix-Marseille Université - A*MIDEX.

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Figures

Table 1: No. of subjects and mean±SD of age in Younger, Middle-aged, and Older age groups. Indications in brackets refer to [min, median, max].

Figure 1: a) Illustration of the different images acquired in this study: B₁⁺ map, MP2RAGE-UNI from which a T₁ map can be derived, and MT-weighted images (here MT± or MT-dual) from which ihMT maps will be derived. The orange boxes indicate the slab location for the brain and SC ihMT acquisitions. The green boxes indicate the shim areas. (b-d) Post-processing pipeline: b) Unbiased ihMTsat and T₁ map derivation. These steps are common for both brain and SC data; c) post-processing steps (segmentation and ROI extraction) for brain images; d) similar steps for SC.

Figure 2: Quadratic fit of T₁ (in blue) and ihMTsat (in orange) in some ROIs of brain WM tracts, brain GM, and SC (SLF: Superior Longitudinal Fasciculus, SFOF: Superior Fronto-Occipital Fasciculus, SCR: Superior Corona Radiata, Fr: Frontal, Pu: Putamen, Th: Thalamus, ant-int: Anterior-Intermediate, PST: Posterior Sensory Tracts, CST: CorticoSpinal Tracts; L: Left, R: Right). The ANOVA test of significance for quadratic regression for brain WM and brain GM regions were significant (p<0.05) and non-significant for SC ROIs.

Figure 3: Illustration of the maturation age for T₁ (blue color) and ihMTsat (orange color) in some brain WM and GM selected ROIs (GCC: Genu of Corpus Callosum, BCC: Body of Corpus Callosum, PCR: Posterior Corona Radiata, PTR: Posterior Thalamic Radiation, SS: Sagittal Stratum, SLF: Superior Longitudinal Fasciculus, wWM: whole White Matter; Fr: Frontal, Th: Thalamus, wGM: whole Gray Matter; R: Right, L: Left) determined from the quadratic model fit (minimum T₁/peak ihMTsat). Maturation age was calculated for the ROIs with a significant quadratic metric=f(age) regression.

Figure 4: Significant clusters from the multivariate PALM analyses (combining both R₁ and ihMTsat) for M vs. Y & O in: a) SC with a WM mask from C1-C5 and b) brain obtained with whole brain WM mask thresholded at p<0.05 (1-p>0.95). No significant clusters were found on SC or brain with GM mask. The results are shown on PAM50 template¹⁹ for SC and MNI-152 atlas^22,23 for brain. The clusters with highest significance levels on brain WM are mainly found in tracts such as PCR, SLF, PTR, and SS. On SC, they mainly correspond to PST and LST regions.

Proc. Intl. Soc. Mag. Reson. Med. 31 (2023)

0591

DOI: https://doi.org/10.58530/2023/0591