INTRODUCTION: Cognitive motor interference (CMI) is performance impairment due to simultaneuous task execution and is measured using the dual task cost (DTC). No pathological feature of MS has to date been associated with CMI. AIM: To assess the relationship between brain volumes and CMI, as measured using the DTC, in a cross-sectional study. METHODS: A group of persons with MS (pwMS) and an age- and sex-matched healthy control (HC) group underwent 3D gait analysis during using the dual task paradigm. Brain volumes were measured on T1-weighted gradient echo scans using SIENAX software. The relationships between brain volumes and the DTCs of spatial temporal parameters were evaluated using Pearson correlation. A multiple regression model was used to evaluate the ability to predict the DTC of cadence based on brain volume and grey matter (GM) volume. RESULTS: Forty-four patients and 16 HCs underwent MRI and gait analysis. The mean expanded disability status scale (EDSS) was 2.4 ± 1.5. Significant relationships between brain volumes and DTC were found only in the pwMS group, with higher rho scores for the DTC of mean velocity, DTC of cadence, and DTC of stride time. A statistically significant regression equation with an R2 value of 0.684 was found using GM and Z-score on the Stroop test as predictors of the DTC of cadence (p < 0.001). CONCLUSION: Brain atrophy, especially than in the GM, is a major determinant of DTC, although other pathological markers also contribute to CMI in patients with MS.
INTRODUCTION:Cognitive motor interference (CMI) is performance impairment due to simultaneuous task execution and is measured using the dual task cost (DTC). No pathological feature of MS has to date been associated with CMI. AIM: To assess the relationship between brain volumes and CMI, as measured using the DTC, in a cross-sectional study. METHODS: A group of persons with MS (pwMS) and an age- and sex-matched healthy control (HC) group underwent 3D gait analysis during using the dual task paradigm. Brain volumes were measured on T1-weighted gradient echo scans using SIENAX software. The relationships between brain volumes and the DTCs of spatial temporal parameters were evaluated using Pearson correlation. A multiple regression model was used to evaluate the ability to predict the DTC of cadence based on brain volume and grey matter (GM) volume. RESULTS: Forty-four patients and 16 HCs underwent MRI and gait analysis. The mean expanded disability status scale (EDSS) was 2.4 ± 1.5. Significant relationships between brain volumes and DTC were found only in the pwMS group, with higher rho scores for the DTC of mean velocity, DTC of cadence, and DTC of stride time. A statistically significant regression equation with an R2 value of 0.684 was found using GM and Z-score on the Stroop test as predictors of the DTC of cadence (p < 0.001). CONCLUSION:Brain atrophy, especially than in the GM, is a major determinant of DTC, although other pathological markers also contribute to CMI in patients with MS.