Measuring subtle Blood‐Brain Barrier permeability changes with reduced scan time in DCE‐MRI

Abstract

AbstractBackgroundIncreasing evidence suggests the subtle changes of Blood‐Brain Barrier (BBB) permeability in normal aging and in Alzheimer’s disease using Dynamic Contrast‐Enhanced MRI (DCE‐MRI). However, measuring this subtle change poses great challenge for accurate measurement, resulting in inconsistent results among previous studies. Two major challenges are long scan times, as suggested by previous studies and selection of the arterial input function (AIF). In this study, we aim to estimate the capillary level input function (CIF) using a deep learning network to overcome these two challenges.MethodsHealthy volunteers (n= 8, ages: 21‐76) were recruited for DCE‐MRI scan for 28min. Golden‐angle RAdial Sampling Parallel (GRASP) sequence was used to obtain the dynamic images at ∼5s/frame. Individual AIF was sampled from the superior sagittal sinus of the brain (Fig.1a). FSL was used to segment the gray and white matters (Fig.1b). Each voxel was fitted using the graphical Patlak model (Fig.2a) to assess the vascular permeability‐surface area product (PS) for both 28‐min data and 10‐min truncated data. We used a 3x3 kernel sliding through the images (Fig.3) and feed each voxel’s dynamic as the input to our vision‐transformer. Training data were generated using individual AIFs with a mathematical model, consisting of two Gaussian and one exponential function, and used to simulate dynamic patches using the Extended Patlak model (Fig.2b).ResultWhen the 10‐min data are used, the conventional approach with AIF results in overestimation of PS when the scan‐time is reduced, while the network‐predicted CIF allows more accurate estimation, with refence to the results using the 28‐min data, as illustrated by an example in Figure 4. Figure 5 shows the regional permeability differences between young and old subjects, where the conventional approach with AIF does not show the difference, while the approach with CIF shows subtle increases in PS with aging.ConclusionOur proposed CIF‐based approach provides an appropriate input‐function for DCE analysis, allowing assessment of subtle permeability changes in the BBB.