1. Role of DTI-MRI parameters in diagnosis of ALS: useful biomarkers for daily practice? Tertiary centre experience and literature review
- Author
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Edyta Maj, Miłosz Jamroży, Maksymilian Bielecki, Marta Bartoszek, Marek Gołębiowski, Mikołaj Wojtaszek, and Magdalena Kuźma-Kozakiewicz
- Subjects
Surgery ,Neurology (clinical) - Abstract
Despite the rapid development of neuroimaging techniques, the diagnosis of amyotrophic lateral sclerosis (ALS) remains a significant challenge. Magnetic resonance imaging (MRI) is important for ruling out ALS mimickers, while Diffusion Tensor Imaging (DTI) is a useful tool for the identification of cortical tract damage. The aim of this study was to identify the optimal set of DTI parameters to support the diagnosis of ALS that could be applied to everyday MRI and be used as a disease biomarker in daily practice.Forty-seven ALS patients and 55 age- and gender-matched healthy individuals underwent MRI using a 1.5-Tesla scanner including a DTI sequence with 30 spatial directions and a b-value 0/1,000 s/mm2. Two independent researchers measured the DTI parameters: fractional anisotropy (FA), TRACE and apparent diffusion coefficient (ADC) using freehand regions of interest (ROIs) placed along both corticospinal tracts (CSTs), starting at the level of the internal capsule and ending at the medulla.Statistical significance was only achieved for fractional anisotropy (FA) (ALS vs controls, p0.001). The highest sensitivity was found in the brainstem (cerebral peduncles, pons and pyramids) where it ranged from 72.3% to 80.9%, whereas the highest specificity was observed at the level of the internal capsule (94.6%). The combined highest sensitivity and specificity was obtained in the pons (72.3% and 72.7%, respectively). Classifier based positive predictive values for Youden index cut-off scores varied between 60.7% and 69.4%.Fractional anisotropy (FA) measured at the level of the brainstem was shown to be the single most relevant parameter in differentiating patients with ALS from healthy subjects. This has the potential to become an ALS-specific biomarker for patient identification in daily practice.
- Published
- 2022