Pattern recognition analysis of dynamic susceptibility contrast (DSC)‐MRI curves automatically segments tissue areas with intact blood–brain barrier in a rat stroke model: A feasibility and comparison study

Abstract

Background: The manual segmentation of intact blood-brain barrier (BBB) regions in the stroke brain is cumbersome, due to the coexistence of infarction, large blood vessels, ventricles, and intact BBB regions, specifically in areas with weak signal enhancement following contrast agent injection. Hypothesis: That from dynamic susceptibility contrast (DSC)-MRI alone, without user intervention, regions of weak BBB damage can be segmented based on the leakage-related parameter K 2 and the extent of intact BBB regions, needed to estimate K 2 values, determined. Study Type: Feasibility. Animal Model: Ten female Sprague-Dawley rats (SD, 200-250g) underwent 1-hour middle carotid artery occlusion (MCAO) and 1-day reperfusion. Two SD rats underwent 1-hour MCAO with 3-day and 5-day reperfusion. Field Strength/Sequence: 7T; ADC and T 1 maps using diffusion-weighted echo planar imaging (EPI) and relaxation enhancement (RARE) with variable repetition time (TR), respectively. dynamic contrast-enhanced (DCE)-MRI using FLASH. DSC-MRI using gradient-echo EPI. Assessment: Constrained nonnegative matrix factorization (cNMF) was applied to the dynamic ΔR * 2 -curves of DSC-MRI (<4 min) in a BBB-disrupted rat model. Areas of voxels with intact BBB, classified by automated cNMF analyses, were then used in estimating K 1 and K 2 values, and compared with corresponding values from manually-derived areas. Statistical Tests: Mean AE standard deviation of ΔT 1 -differences between ischemic and healthy areas were displayed with unpaired Student's t-tests. Scatterplots were displayed with slopes and intercepts and Pearson's r values were evaluated between K 2 maps obtained with automatic (cNMF)-and manually-derived regions of interest (ROIs) of the intact BBB region. Results: Mildly BBB-damaged areas (indistinguishable from DCE-MRI (10 min) parameters) were automatically segmented. Areas of voxels with intact BBB, classified by automated cNMF, matched closely the corresponding, manually-derived areas when respective areas were used in estimating K 2 maps (Pearson's r = 0.97, 12 slices). Data Conclusion: Automatic segmentation of short DSC-MRI data alone successfully identified areas with intact and compromised BBB in the stroke brain and compared favorably with manual segmentation.

Model‐free leakage index estimation of the blood‐brain barrier using dual dynamic susceptibility contrast MRI acquisition

“…Although DCE-MRI is widely used for evaluating vascular permeability, previous studies have shown that DCE-MRI has limited sensitivity for evaluating subtle ischemic vascular permeability. 11,[28][29][30] A long DCE-MRI acquisition time ($20 min) would enhance the contrast as a result of the increased amount of extravasated CA. [31][32][33] However, extravascular extracellular space volume (v e ) and CA diffusion begin to affect the amount of extravasated CA over time and may not directly represent spatial vascular permeability.…”

“…As it requires a certain amount of CA accumulation for T 1 values to change, its sensitivity may be limited in detecting subtle BBB damage, as in the early stage of ischemic stroke, within short DCE-MRI acquisition time (<10 min). 11 Dynamic susceptibility contrast (DSC)-MRI is a T 2 * -based or T 2 -based technique that is typically used for evaluating cerebral blood volume, cerebral blood flow (CBF), and mean transit time in capillaries. 12 DSC-MRI has a basic assumption that the CA is not extravasated from blood vessels, [13][14][15] but numerous studies have used the K 1 , K 2 model to study the effects of CA extravasation on the DSC-MRI signal in brains with BBB damage, especially for tumors and strokes.…”