Sarah Milla

Amir Paydar

In 2011, we began our investigation into the detection of microstructural changes that occur in both the white matter (WM) and gray matter (GM) of the developing pediatric brain using an MRI diffusion technique called diffusional kurtosis imaging (DKI). This technique is an extension of the traditional DWI/DTI model, as it acknowledges non-Gaussian diffusional properties of water motion in complex media and is more comprehensive in evaluating microstructural complexity of brain tissue. Our research interest emerged from the speculation that, owing to their potentially higher sensitivity for the detection of age-related microstructural changes, DKI metrics may provide additional information about gray and white matter maturation when compared with metrics obtained with conventional DTI techniques. Our research was presented at ASNR 2012 and subsequently published in AJNR in 2014.

Our data showed that, similar to DTI, DKI was able to reflect significant age-related WM changes as a function of myelination in the first 2 years of life. However, the DKI method was also able to resolve further WM changes that occur beyond 2 years of age. For instance, the mean kurtosis metric allowed the assessment of continued microstructural changes occurring in the WM even up to a year after fractional anisotropy had demonstrated a plateau.

The results also supported the hypothesis that DKI is sensitive to age-related microstructural changes that occur in the isotropic GM, for which DTI had previously shown limited sensitivity. Specifically, when compared with DTI, DKI can better resolve the progression of GM organization with respect to age by accounting for other isotropic microstructural barriers that form at the cellular level.

Our investigation demonstrated the potential of this innovative MRI technique to detect developmental changes within neural tissues in normal infants and children from 0–5 years of age.

Since our article was published in 2014, further investigations from collaborators and from other institutions have shown DKI can also detect changes in neuropathologies, including brain tumors, traumatic brain injury, stroke, and Parkinson disease, as well as for other body applications, such as breast, liver, and prostate cancer. These increasing applications are reflecting the ability of DKI metrics to differentiate between normal and abnormal histology, as well as detect subtle differences in tissue characterization. We look forward to the continued assessment of DKI metrics as biomarkers in healthy tissues, as well as in disease detection and the assessment of future therapies.

Read this article at AJNR.org …