Strain map of the tongue in normal and ALS speech patterns from tagged and diffusion MRI

Abstract

Amyotrophic Lateral Sclerosis (ALS) is a neurological disease that causes death of neurons controlling muscle movements. Loss of speech and swallowing functions is a major impact due to degeneration of the tongue muscles. In speech studies using magnetic resonance (MR) techniques, diffusion tensor imaging (DTI) is used to capture internal tongue muscle fiber structures in three-dimensions (3D) in a non-invasive manner. Tagged magnetic resonance images (tMRI) are used to record tongue motion during speech. In this work, we aim to combine information obtained with both MR imaging techniques to compare the functionality characteristics of the tongue between normal and ALS subjects. We first extracted 3D motion of the tongue using tMRI from fourteen normal subjects in speech. The estimated motion sequences were then warped using diffeomorphic registration into the b0 spaces of the DTI data of two normal subjects and an ALS patient. We then constructed motion atlases by averaging all warped motion fields in each b0 space, and computed strain in the line of action along the muscle fiber directions provided by tractography. Strain in line with the fiber directions provides a quantitative map of the potential active region of the tongue during speech. Comparison between normal and ALS subjects explores the changing volume of compressing tongue tissues in speech facing the situation of muscle degradation. The proposed framework provides for the first time a dynamic map of contracting fibers in ALS speech patterns, and has the potential to provide more insight into the detrimental effects of ALS on speech.

A Deep Joint Sparse Non-negative Matrix Factorization Framework for Identifying the Common and Subject-specific Functional Units of Tongue Motion During Speech

“…In order to accurately localize the internal muscles, structural MRI or diffusion MRI are needed as they can provide the location of the internal muscles or fiber architecture, respectively. In addition, our framework can be applied to patient populations, such as, those with amyotrophic lateral sclerosis (Xing et al, 2018;Lee et al, 2018) or tongue cancer with speech or swallowing impairments; assessing how local functional units adapt after a variety of treatments can potentially advance therapeutic, rehabilitative, and surgical procedures.…”

VoxelHop: Successive Subspace Learning for ALS Disease Classification Using Structural MRI

“…To assess volume differences between an atlas constructed using healthy subjects and a cohort of patients, voxel-based morphometry (VBM) [16] has been widely used in the brain to assess volume differences for a variety of neurological disorders, such as Alzheimer's disease [17], stroke [18], traumatic brain injury [19], depression [20], and ALS [14]. Independent of the brain, there are also a few works to characterize volume or motion differences between ALS patients and healthy controls [21], [15], [22]. Since hypoglossal neurons gradually degenerate due to ALS, previous works focused on how ALS causes muscle atrophy and weakness by measuring anatomical characteristics, such as volume and muscle fibers in the tongue using diffusion and structural MRI methods [15], [22].…”

“…Independent of the brain, there are also a few works to characterize volume or motion differences between ALS patients and healthy controls [21], [15], [22]. Since hypoglossal neurons gradually degenerate due to ALS, previous works focused on how ALS causes muscle atrophy and weakness by measuring anatomical characteristics, such as volume and muscle fibers in the tongue using diffusion and structural MRI methods [15], [22]. To our knowledge, however, there is no previous work that simultaneously assesses differences in both the brain and tongue between controls and ALS patients.…”

Atlas-Based Tongue Muscle Correlation Analysis From Tagged and High-Resolution Magnetic Resonance Imaging

“…To localize internal tongue motion, previous studies have divided the tongue into a smaller set of coordinated motion patternsthat is, functional units-to reveal parts of the tissue that are most likely to work in coordination . In terms of studying individual tongue muscles, there have been works that analyzed strain in tongue muscle fiber directions, showing active or passive contractions of individual muscles during speech (Xing et al, 2018;Xing, Ye, Woo, Stone, & Prince, 2015).…”