Tongue volume in spinal and bulbar muscular atrophy (SBMA): an AI-assisted automatic MRI analysis

Atrophy of the tongue muscle without severe dysarthria is one of the clinical hallmarks of spinal and bulbar muscular atrophy (SBMA), a motor neuron disease caused by an androgene receptor defect. An operator-independent AI-based automatic segmentation of the tongue was applied to 3-D MRI data of the head in SBMA in order to quantify the tongue atrophy. Thirty-nine patients with SBMA and 51 age-matched healthy controls underwent MRI which were used for tongue volume quantification. A single triplanar convolutional neural network of U-Net architecture trained on axial, coronal, and sagittal planes was used for the segmentation of the tongue in MRI scans of the head, the resulting volumes were processed slice-wise across the three orientations and corrected for age. At the group level, a significant atrophy of the tongue was observed in SBMA when compared to controls (p < 0.05). Atrophy correlated well with total SBMA-functional rating scale and even more with bulbar subscores. In summary, the study employed an AI-assisted advanced imaging analysis to quantify the tongue morphology in individuals with SBMA in correlation to clinical bulbar function, suggesting this approach as a potential biomarker for disease assessment.