Extreme ultra-endurance races are growing in popularity, but their effects on skeletal muscles remain mostly unexplored. This longitudinal study explores physiological changes in mountain ultramarathon athletes' quadriceps using quantitative magnetic resonance imaging (MRI) coupled with serological biomarkers. The study aimed to monitor the longitudinal effect of the race and recovery and to identify local inflammatory and metabolic muscle responses by codetection of biological markers.
An automatic image processing framework was designed to extract imaging-based biomarkers from quantitative MRI acquisitions of the upper legs of 20 finishers at three time points. The longitudinal effect of the race was demonstrated by analyzing the image markers with dedicated biostatistical analysis.
Our framework allows for a reliable calculation of statistical data not only inside the whole quadriceps volume but also within each individual muscle head. Local changes in MRI parameters extracted from quantitative maps were described and found to be significantly correlated with principal serological biomarkers of interest. A decrease in the PDFF after the race and a stable paramagnetic susceptibility value were found. Pairwise post hoc tests suggested that the recovery process differs among the muscle heads.
This longitudinal study conducted during a prolonged and extreme mechanical stress showed that quantitative MRI-based markers of inflammation and metabolic response can detect local changes related to the prolonged exercise, with differentiated involvement of each head of the quadriceps muscle as expected in such eccentric load. Consistent and efficient extraction of the local biomarkers enables to highlight the interplay/interactions between blood and MRI biomarkers. This work indeed proposes an automatized analytic framework to tackle the time-consuming and mentally exhausting segmentation task of muscle heads in large multi-time-point cohorts.