Spinal muscular atrophy (SMA) is an autosomal recessive lower motor neuron disorder caused by biallelic loss-of-function variants in SMN1. SMA type 3 is a milder phenotype in which patients remain ambulant, subdivided into type 3a (onset <3 years) and 3b (onset >3 years). While natural history is well established for types 1 and 2, the clinical course of late-onset patients remains insufficiently characterized, representing a limitation in their management—especially in the current context of effective disease-modifying therapies.
This study included adult SMA type 3 patients confirmed by genetic testing who were able to undergo MRI, along with an equal number of age-matched healthy controls. All subjects were scanned on a 3T Phillips Achieva system using a 16-channel neurovascular coil in two visits one year apart. Axial-oblique images were acquired at the C2–C3 level, and cross-sectional area (CSA) and gray matter (GM) area were automatically segmented with a deep-learning algorithm. MRI processing was performed using Spinal Cord Toolbox v4.0.1.
Seventeen adults with SMA type 3 (12 men, 5 women; mean age 32.1 years) were evaluated. CSA at C3 showed no significant difference between visits in patients (p=0.89) nor between patients and controls (p=0.20). GM area similarly showed no significant longitudinal change, but the comparison between patients and controls demonstrated a marked difference (p<0.0001). When combined with clinical measures, GM area strongly correlated with MFM scores (r=0.79, p=0.0002). These findings reinforce that SMA-related pathology is concentrated in spinal gray matter and, for the first time, demonstrate that GM area measured non-invasively by MRI correlates almost linearly with motor function. GM quantification thus emerges as a promising biomarker in adult SMA patients.