Synopsis

In this work, we evaluated if structural characteristics of cortical regions and the U-fibers connected to these regions allows predicting multiple sclerosis patients’ score in FAS, SDMT and PASAT tests. For this purpose, we represented structural characteristics as the proportion of the regions and fibers covered by lesion and the U-fiber’s mean fractional anisotropy. In our sample, FAS test score results significantly correlated with structural damage in U-fibers from Frontal and Temporal lobes. PASAT test score significantly correlated with structural damage in U-fibers in the bilateral Frontal and Parietal lobes. No significant correlations were found for the SDMT.

Introduction

Multiple sclerosis (MS) patients develop measurable cognitive declines since the earliest stages of the disease, with significant changes in cortical recruitment related to cognitive tasks (1,2). Different tests have been developed to assess these disabilities. The FAS test measures word fluency; the symbol digit modalities test (SDMT) assess attention and visual and motor speed; and the Paced Auditory Serial Addition Test (PASAT) evaluates information processing and attention capacity (3). Magnetic resonance imaging (MRI) is also useful for the diagnosis of the disease and follow up (4). However, traditional imaging findings do not correlate strongly with patients' clinical symptoms. (5-7). Furthermore, the relation between clinical tests and structural changes found in the MRI along the disease progression is not well understood.

We evaluated if the structural characteristics of cortical regions that have been reported to relate to the corresponding test and U-fibers that connected to these regions allow predicting the score in the clinical tests. To test this hypothesis, we represented structural characteristics as: (i) proportion of the regions and U-fibers covered by lesion and (ii) the average of its fractional anisotropy (FA).

Material and Methods

Forty-five relapsing-remitting multiple sclerosis patients (20 males with mean age 35 years old, range, 21-50 years old; 25 females with mean age 38 years, range 22-63 years old) were diagnosed according to McDonald’s Criteria (4) and scanned on a 3T MRI scanner (Philips Ingenia, Best, Netherlands). Diffusion weighted images were acquired to calculate FA maps through Diffusion Tensor Imaging (DTI). T1 and T2 weighted images were acquired as anatomical reference and to measure lesions, respectively. MRI acquisition parameters are summarized in Table 1. All subjects had at least 13 years of education and did not have any MR-incompatible implants. Patients were evaluated using FAS, SDMT and PASAT. The study was approved by the local ethics committee.

FA maps were calculated using DSI Studio (http://dsi-studio.labsolver.org). The resulting maps were then coregistered with the T1 weighted images and normalized to the MNI space using SPM12 (http://www.fil.ion.ucl.ac.uk/spm/software/spm12/).

Results

Discussion and Conclusion

The results presented in this study show that there is a correlation between structural indicators of U-fibers and cognitive performance of MS patients. The U-fibers that correlated the most with verbal fluency performance connect the right Pars opercularis with the Precentral gyrus and the right Pars opercularis with the Superior frontal gyrus. Whereas the fibers connecting the left Postcentral with the Supramarginal gyrus and left lateral Orbitofrontal cortex with the rostral middle frontal gyrus were found to strongly correlate with information processing speed and attention capacities.

The statistically significant coefficients found are potential biomarkers that might help to predict cognitive performance in early stages of MS. Therefore contributing to a better understanding of how this disease is affecting the brain and indicating that there is a direct effect on function caused by structural damage. Future work should include a deeper analysis on the effects of structural indicators on cognitive performance, for instance, incorporating the fractional anisotropy variability within the U-fibers.

Acknowledgements

References

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