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  • Title: Tractography in amyotrophic lateral sclerosis using a novel probabilistic tool: a study with tract-based reconstruction compared to voxel-based approach.
    Author: Sarica A, Cerasa A, Vasta R, Perrotta P, Valentino P, Mangone G, Guzzi PH, Rocca F, Nonnis M, Cannataro M, Quattrone A.
    Journal: J Neurosci Methods; 2014 Mar 15; 224():79-87. PubMed ID: 24406465.
    Abstract:
    BACKGROUND: Diffusion tensor imaging (DTI) is one of the most sensitive MRI tools for detecting subtle cerebral white matter abnormalities in amyotrophic lateral sclerosis (ALS). Nowadays a plethora of DTI tools have been proposed, but very few methods have been translated into clinical practice. NEW METHOD: The aim of this study is to validate the objective measurement of fiber tracts as provided by a new unbiased and automated tractography reconstruction tool named as TRActs Constrained by UnderLying Anatomy (TRACULA). The reliability of this tract-based approach was evaluated on a dataset of 14 patients with definite ALS compared with 14 age/sex-matched healthy controls. To further corroborate these measurements, we used a well-known voxelwise approach, called tract-based spatial statistics (TBSS), on the same dataset. RESULTS: TRACULA showed specific significant alterations of several DTI parameters in the corticospinal tract of the ALS group with respect to controls. COMPARISON WITH EXISTING METHOD: The same finding was detected using the well-known TBSS analysis. Similarly, both methods depicted also additional microstructural changes in the cingulum. CONCLUSIONS: DTI tractography metrics provided by TRACULA perfectly agree with those previously reported in several post-mortem and DTI studies, thus demonstrating the accuracy of this method in characterizing the microstructural changes occurring in ALS. With further validation (i.e. considering the heterogeneity of other clinical phenotypes), this method has the potential to become useful for clinical practice providing objective measurements that might aid radiologists in the interpretation of MR images and improve diagnostic accuracy of ALS.
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