Beyond the grey scale: A focus review of microstructural, metabolic, and AI-driven advances in TBI neuroimaging

Traumatic Brain Injury (TBI) presents a significant diagnostic challenge due to the frequent dissociation between severe clinical symptoms and absence of abnormal findings on conventional neuroimaging. This focus review synthesizes pivotal peer-reviewed literature to characterize the shift from anatomical to microstructural, physiological, and computational diagnostics. We examine the implementation of the 2024 NINDS CBI-M (Clinical, Biomarker, Imaging, Modifiers) framework, which recommends a multimodal approach. Key advances reviewed include Neurite Orientation Dispersion and Density Imaging (NODDI) for detecting microstructural reorganization; Quantitative Susceptibility Mapping (QSM) for quantifying chronic iron and indirectly inflammation; Arterial Spin Labeling (ASL) for assessing cerebral perfusion and neurovascular health; systematic evidence of functional connectivity disruption via fMRI; and the emergence of Artificial Intelligence (AI) for accurate prognosis. These technologies collectively support a move toward precision medicine, characterizing TBI by specific biotypes rather than broad severity scores.