Multimodal magnetic resonance imaging assessment of white matter aging trajectories over the lifespan of healthy individuals.

BACKGROUND: Postmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in middle age. We examined whether known regional differences in axon size and age at myelination influence the timing and rates of development and degeneration/repair trajectories of white matter (WM) microstructure biomarkers. METHODS: Healthy subjects (n = 171) 14-93 years of age were examined with transverse relaxation rate (R(2)) and four diffusion tensor imaging measures (fractional anisotropy [FA] and radial, axial, and mean diffusivity [RD, AxD, MD, respectively]) of frontal lobe, genu, and splenium of the corpus callosum WM (FWM, GWM, and SWM, respectively). RESULTS: Only R(2) reflected known levels of myelin content with high values in late-myelinating FWM and GWM regions and low ones in early-myelinating SWM. In FWM and GWM, all metrics except FA had significant quadratic components that peaked at different ages (R(2) < RD < MD < AxD), with FWM peaking later than GWM. Factor analysis revealed that, although they defined different factors, R(2) and RD were the metrics most closely associated with each other and differed from AxD, which entered into a third factor. CONCLUSIONS: The R(2) and RD trajectories were most dynamic in late-myelinating regions and reflect age-related differences in myelination, whereas AxD reflects axonal size and extra-axonal space. The FA and MD had limited specificity. The data suggest that the healthy adult brain undergoes continual change driven by development and repair processes devoted to creating and maintaining synchronous function among neural networks on which optimal cognition and behavior depend.

Patient-tailored connectomics visualization for the assessment of white matter atrophy in traumatic brain injury.

Available approaches to the investigation of traumatic brain injury (TBI) are frequently hampered, to some extent, by the unsatisfactory abilities of existing methodologies to efficiently define and represent affected structural connectivity and functional mechanisms underlying TBI-related pathology. In this paper, we describe a patient-tailored framework which allows mapping and characterization of TBI-related structural damage to the brain via multimodal neuroimaging and personalized connectomics. Specifically, we introduce a graphically driven approach for the assessment of trauma-related atrophy of white matter connections between cortical structures, with relevance to the quantification of TBI chronic case evolution. This approach allows one to inform the formulation of graphical neurophysiological and neuropsychological TBI profiles based on the particular structural deficits of the affected patient. In addition, it allows one to relate the findings supplied by our workflow to the existing body of research that focuses on the functional roles of the cortical structures being targeted. A graphical means for representing patient TBI status is relevant to the emerging field of personalized medicine and to the investigation of neural atrophy.

Characteristics of patients with target magnetic resonance mismatch profile: data from two geographically and racially distinct populations.

BACKGROUND: Recently, the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution (DEFUSE) and the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET) trialists suggested that diffusion-perfusion magnetic resonance imaging (MRI) can classify patients into 4 subgroups likely to differentially experience benefit or harm from reperfusion therapies. However, there is a lack of data comparing MR mismatch profiles between different race-ethnic groups. In addition, clinical factors affecting MR mismatch profiles are not well described. METHODS: We analyzed clinical and pretreatment MRI data of patients from 2 geographically and ethnically distinct study populations (Seoul, South Korea, and Los Angeles, Calif., USA) who are eligible for recanalization therapy. Diffusion-perfusion mismatch regions were classified among the 4 DEFUSE MR profiles: target mismatch, no mismatch, small lesion and malignant. RESULTS: A total of 147 South Korean and 162 Southern Californian subjects (64.2% Whites) were included. Pretreatment MRIs revealed that the MR mismatch profiles were different in the 2 study populations (p < 0.001). Target mismatch was more prevalent in Southern Californian subjects (67.9%) compared with South Korean subjects (58.5%), whereas the small lesion pattern was more prevalent in the latter (9.9 vs. 23.1%). After adjusting for covariables, 3 features independently decreased the likelihood of presence of target mismatch: history of diabetes (OR 0.369, 95% CI 0.196-0.694), small versus large arterial occlusion (OR 0.052, 95% CI 0.01-0.255) and largest size (highest tertile) of diffusion-weighted imaging (DWI) lesion volume (OR 0.516, 95% CI 0.266-0.999). The one feature independently increasing target mismatch likelihood was intermediate size (middle tertile) DWI volume (OR 2.977, 95% CI 1.431-6.195). CONCLUSIONS: Target mismatch profiles are present in 55-70% of patients. Target mismatch is less common in patients with diabetes, small vessel occlusion, Asian ethnicity and extensive DWI lesions, and more common in patients with DWI lesions of intermediate size.