Magnetic resonance imaging volumetry studies report inverted U-patterns with increasing white-matter (WM) volume into middle age suggesting protracted WM maturation compared with the cortical gray matter. Diffusion tensor imaging (DTI) is sensitive to degree and direction of water permeability in biological tissues, providing in vivo indices of WM microstructure. The aim of this cross-sectional study was to delineate age trajectories of WM volume and DTI indices in 430 healthy subjects ranging 8-85 years of age. We used automated regional brain volume segmentation and tract-based statistics of fractional anisotropy, mean, and radial diffusivity as markers of WM integrity. Nonparametric regressions were used to fit the age trajectories and to estimate the timing of maximum development and deterioration in aging. Although the volumetric data supported protracted growth into the sixth decade, DTI indices plateaued early in the fourth decade across all tested regions and then declined slowly into late adulthood followed by an accelerating decrease in senescence. Tractwise and voxel-based analyses yielded regional differences in development and aging but did not provide ample evidence in support of a simple last-in-first-out hypothesis of life-span changes.

There is a growing realization that early life influences have lasting impact on brain function and structure. Recent research has demonstrated that genetic relationships in adults can be used to parcellate the cortex into regions of maximal shared genetic influence, and a major hypothesis is that genetically programmed neurodevelopmental events cause a lasting impact on the organization of the cerebral cortex observable decades later. Here we tested how developmental and lifespan changes in cortical thickness fit the underlying genetic organizational principles of cortical thickness in a longitudinal sample of 974 participants between 4.1 and 88.5 y of age with a total of 1,633 scans, including 773 scans from children below 12 y. Genetic clustering of cortical thickness was based on an independent dataset of 406 adult twins. Developmental and adult age-related changes in cortical thickness followed closely the genetic organization of the cerebral cortex, with change rates varying as a function of genetic similarity between regions. Cortical regions with overlapping genetic architecture showed correlated developmental and adult age change trajectories and vice versa for regions with low genetic overlap. Thus, effects of genes on regional variations in cortical thickness in middle age can be traced to regional differences in neurodevelopmental change rates and extrapolated to further adult aging-related cortical thinning. This finding suggests that genetic factors contribute to cortical changes through life and calls for a lifespan perspective in research aimed at identifying the genetic and environmental determinants of cortical development and aging.here is a growing realization that events during development impact brain and cognition throughout the entire lifespan (1). For instance, the major portion of the relationship between cortical thickness and IQ in old age can be explained by childhood IQ (2), and genotype may explain a substantial part of the lifetime stability in intelligence (3). Effects of genes on the organization of the cortex have been shown in adults (4-6), but it is unknown whether and how regional differences in cortical development correspond to these regional genetic subdivisions.Although consensus has not been reached for the exact trajectories, cortical thickness as measured by MRI appears to decrease in childhood (7-12). The exact foundation for this thinning is not known, as MRI provides merely representations of the underlying neurobiology, and available histological data cannot with certainty be used to guide interpretations of MRI results. Although speculative, apparent thickness decrease may be grounded in factors such as synaptic pruning and intracortical myelination, although the link between established synaptic processes (13-15) and cortical thickness has not been empirically confirmed. After childhood, cortical thinning continues throughout the remainder of the lifespan, speculated to reflect neuronal shrinkage and reductions in number of spines and synapses (16), although sim...

Diffusion weighted imaging (DWI) has been at the forefront of cancer imaging since the early 2000’s. Prior to its application in clinical oncology, this powerful technique had already achieved widespread recognition due to its utility in the diagnosis of cerebral infarction. Following this initial success, the ability of DWI to detect inherent tissue contrast began to be exploited in the field of oncology. Although the initial oncologic applications for tumor detection and characterization, assessing treatment response, and predicting survival were primarily in the field of neuro-oncology, the scope of DWI has since broadened to include oncologic imaging of the prostate gland, breast, and liver. Despite its growing success and application, misconceptions as to the underlying physical basis of the DWI signal exist among researchers and clinicians alike. In this review, we provide a detailed explanation of the biophysical basis of diffusion contrast, emphasizing the difference between hindered and restricted diffusion, and elucidating how diffusion parameters in tissue are derived from the measurements via the diffusion model. We describe one advanced DWI modeling technique, called Restriction Spectrum Imaging (RSI). This technique offers a more direct in vivo measure of tumor cells, due to its ability to distinguish separable pools of water within tissue based on their intrinsic diffusion characteristics. Using RSI as an example, we then highlight the ability of advanced DWI techniques to address key clinical challenges in neuro-oncology, including improved tumor conspicuity, distinguishing actual response to therapy from pseudoresponse, and delineation of white matter tracts in regions of peritumoral edema. We also discuss how RSI, combined with new methods for correction of spatial distortions inherent diffusion MRI scans, may enable more precise spatial targeting of lesions, with implications for radiation oncology, and surgical planning.