Differences in the variability of cerebral proton magnetic resonance spectroscopy (1H-MRS) measurements within three HIV-infected cohorts.

INTRODUCTION Cerebral functional impairment remains prevalent in effectively treated HIV-infected subjects. As the results of formal cognitive testing are highly variable, surrogate markers to accurately measure cerebral function parameters are needed. Such markers include measurement of cerebral metabolite ratios (CMR) using proton magnetic resonance spectroscopy (1H-MRS). However, data on the inter-subject variability of CMR are sparse. Our aim was to assess inter-subject variability in CMRs within three different HIV-infected cohorts. METHODS Cerebral 1H-MRS was performed using a Phillips Achieva™ 1.5 Tesla magnetic resonance scanner in HIV-infected subjects as follows: 12 subjects before (group 1) and after intensification of antiretroviral therapy with maraviroc (group 2) and 13 subjects with acute viral hepatitis C (HCV) co-infection (group 3). The coefficients of variation (CV) for CMRs in each group were determined and compared using non-parametric tests to determine whether the inter-subject variability differed significantly. All baseline characteristics between the groups were similar. RESULTS Overall CVs for all CMRs in groups 1, 2 and 3 were 32.3%, 33.2% and 23.4%, respectively (group 1 vs. 2, p=0.863; group 1 vs. 3, p=0.076). On testing for differences in variability between individual CMRs, two metabolites in the right basal ganglia (RBG) had statistically significantly different CVs when comparing group 1 with group 3: N-acetyl aspartate/creatine (NAA/Cr), p=0.029 and myo-Inositol/creatine (mI/Cr), p=0.016. CONCLUSION The variability of 1H MRS-measurable CMRs in HIV-infected individuals was lower in those with acute HCV co-infection (group 3).We can conclude that the use of these CMRs in 1H MRS imaging in patients with HIV/acute HCV co-infection is more reliable to assess cerebral function than in patients with HIV infection alone. This has implications for future sample size estimations.