Alteration of skeletal muscle energy metabolism assessed by 31P MRS in clinical routine: Part 2. Clinical application

Abstract

AbstractIn this second part of a two‐part paper, we intend to demonstrate the impact of the previously proposed advanced quality control pipeline. To understand its benefit and challenge the proposed methodology in a real scenario, we chose to compare the outcome when applying it to the analysis of two patient populations with significant but highly different types of fatigue: COVID‐19 and multiple sclerosis (MS). 31P‐MRS was performed on a 3 T clinical MRI, in 19 COVID‐19 patients, 38 MS patients, and 40 matched healthy controls. Dynamic acquisitions using an MR‐compatible ergometer ran over a rest (40 s), exercise (2 min), and a recovery phase (6 min). Long and short TR acquisitions were also made at rest for T1 correction. The advanced data quality control pipeline presented in Part 1 is applied to the selected patient cohorts to investigate its impact on clinical outcomes. We first used power and sample size analysis to estimate objectively the impact of adding the quality control score (QCS). Then, comparisons between patients and healthy control groups using the validated QCS were performed using unpaired t tests or Mann–Whitney tests (p < 0.05). The application of the QCS resulted in increased statistical power, changed the values of several outcome measures, and reduced variability (standard deviation). A significant difference was found between the T1PCr and T1Pi values of MS patients and healthy controls. Furthermore, the use of a fixed correction factor led to systematically higher estimated concentrations of PCr and Pi than when using individually corrected factors. We observed significant differences between the two patient populations and healthy controls for resting [PCr]—MS only, [Pi], [ADP], [H2PO4−], and pH—COVID‐19 only, and post‐exercise [PCr], [Pi], and [H2PO4−]—MS only. The dynamic indicators τPCr, τPi, ViPCr, and Vmax were reduced for COVID‐19 and MS patients compared with controls. Our results show that QCS in dynamic 31P‐MRS studies results in smaller data variability and therefore impacts study sample size and power. Although QCS resulted in discarded data and therefore reduced the acceptable data and subject numbers, this rigorous and unbiased approach allowed for proper assessment of muscle metabolites and metabolism in patient populations. The outcomes include an increased metabolite T1, which directly affects the T1 correction factor applied to the amplitudes of the metabolite, and a prolonged τPCr, indicating reduced muscle oxidative capacity for patients with MS and COVID‐19.