Abstract
INTRODUCTION: Combination antiretroviral therapy (cART) has been shown to reduce inflammation in persons with HIV (PWH), leading to overall improvements in cognition. However, these improvements are patient-dependent and not always observable over short treatment periods. METHODS: We applied a multimodal integrative model to associate various baseline MR neuroimaging metrics with baseline neurocognitive performance and their longitudinal changes over 12 weeks of cART treatment. Features in our model included volumetric data, cerebral blood flow metrics, cerebrovascular reactivity, and diffusion MRI data from cortical, subcortical, and white matter regions of the brain. Our integrative model, which includes multilayered principal component analysis, penalized regression, and feature weight back-propagation, is designed for "large p, small n" data and offers better interpretability than deep-learning methods. RESULTS: There is a modest association between imaging metrics and baseline neurocognitive scores for both PWH and age-matched healthy controls, driven primarily by subcortical regions. In contrast, baseline imaging features exhibited stronger associations with longitudinal changes in cognitive performance over 12 weeks of cART in PWH than with baseline cognitive scores. The multimodal integrative model outperformed all comparable unimodal models in explaining longitudinal cognitive change. Among unimodal analyses, models based on cerebral blood flow and free-water-corrected fractional anisotropy demonstrated the strongest associations. Frequently selected predictors included the frontal pole (cortical gray matter); the amygdala, putamen, and hippocampus (subcortical gray matter); and the posterior limb of the internal capsule (white matter). DISCUSSION: Our approach provides an interpretable statistical framework that integrates complementary information across various imaging modalities into a robust and interpretable model for short-term cognitive trajectories in PWH undergoing cART.