subspace models

Abnormal mitochondrial metabolism is a hallmark of many prevalent diseases such as diabetes and cardiovascular disease; however, current understanding of mitochondrial function is mostly gained from studies on isolated mitochondria under nonphysiological conditions. This work presents a novel high-resolution dynamic 31P magnetic resonance spectroscopic imaging method that synergistically integrates physics-based models of spectral structures, biochemical modeling of molecular dynamics, and subspace learning, for metabolic mapping at high-spatiotemporal resolution. It enables in vivo imaging of phosphocreatine resynthesis rates, a well-established index of mitochondrial oxidative capacity, thus providing a powerful tool for longitudinal assessment of mitochondrial function in disease progression. read more