Correlation Between Respiratory Accessory Muscles and Diaphragm Pillars MRI and Pulmonary Function Test in Late-Onset Pompe Disease Patients.

Objectives: Pompe disease is a rare genetic disease produced by mutations in the GAA gene leading to progressive skeletal and respiratory muscle weakness. T1-weighted magnetic resonance imaging is useful to identify fatty replacement in skeletal muscles of late-onset Pompe disease (LOPD) patients. Previous studies have shown that replacement by fat correlates with worse results of muscle function tests. Our aim was to investigate if fat replacement of muscles involved in the ventilation process correlated with results of the spirometry and predicted respiratory muscle impairment in LOPD patients over time. Materials and
Methods: We studied a cohort of 36 LOPD patients followed up annually in our center for a period of 4 years. We quantified muscle fat replacement using Mercuri score of the thoracic paraspinal and abdominal muscles and the pillars of the diaphragm. We correlated the combined Mercuri scores of these areas with spirometry results and the need of respiratory support.
Results: We found a statistically significant correlation (Spearman test, p < 0.05; coefficient of correlation > 0.6) between forced vital capacity seated and lying and fat fraction score of all muscle groups studied. The group of patients who needed respiratory support had higher fat fraction scores than patients not requiring ventilatory support. Higher fat replacement in these areas correlated with worse progression in spirometry values over time. Conclusions: Fat replacement of paraspinal, abdominal, and trunk muscles correlates with results of spirometry and is able to predict worsening in respiratory muscle function tests that could lead to an emerging ventilatory dysfunction. Therefore, the identification of fat replacement in these muscle groups should lead to a closer monitorization of patients. Radiologic evaluation of diaphragm pillars in T1-weighted imaging axial sequences could also be helpful to predict respiratory insufficiency.