Background: Cerebral intravoxel incoherent motion (IVIM) imaging assumes two components. However, more compartments are likely present in pathologic tissue. We hypothesized that spectral analysis using a nonnegative least‐squares (NNLS) approach can detect an additional, intermediate diffusion component, distinct from the parenchymal and microvascular components, in lesion‐prone regions.Purpose: To investigate the presence of this intermediate diffusion component and its relation with cerebral small vessel disease (cSVD)‐related lesions.Study Type: Prospective cross‐sectional study.Population: Patients with cSVD (n = 69, median age 69.8) and controls (n = 39, median age 68.9).Field Strength/Sequence: Whole‐brain inversion recovery IVIM acquisition at 3.0T.Assessment: Enlarged perivascular spaces (PVS) were rated by three raters. White matter hyperintensities (WMH) were identified on a fluid attenuated inversion recovery (FLAIR) image using a semiautomated algorithm.Statistical Tests: Relations between IVIM measures and cSVD‐related lesions were studied using the Spearman's rank order correlation.Results: NNLS yielded diffusion spectra from which the intermediate volume fraction f_int was apparent between parenchymal diffusion and microvasular pseudodiffusion. WMH volume and the extent of MRI‐visible enlarged PVS in the basal ganglia (BG) and centrum semiovale (CSO) were correlated with f_int in the WMHs, BG, and CSO, respectively. f_int was 4.2 ± 1.7%, 7.0 ± 4.1% and 13.6 ± 7.7% in BG and 3.9 ± 1.3%, 4.4 ± 1.4% and 4.5 ± 1.2% in CSO for the groups with low, moderate, and high number of enlarged PVS, respectively, and increased with the extent of enlarged PVS (BG: r = 0.49, P < 0.01; CSO: r = 0.23, P = 0.02). f_int in the WMHs was 27.1 ± 13.1%, and increased with the WMH volume (r = 0.57, P < 0.01).Data Conclusion: We revealed the presence of an intermediate diffusion component in lesion‐prone regions of cSVD and demonstrated its relation with enlarged PVS and WMHs. In tissue with these lesions, tissue degeneration or perivascular edema can lead to more freely diffusing interstitial fluid contributing to f_int.Level of Evidence: 2Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2020;51:1170–1180.

Myelin is a vital element of normal brain development and structure. Myelination is most prominent during the first two years of life and proceeds until the age of 30. Abnormal myelination is related to several neurological and neuropsychiatric disorders such as Alzheimer's disease and multiple sclerosis. Recently, abnormal myelin content has also been reported in children with epilepsy. Furthermore, more and more literature hints at a link between abnormal myelination and epilepsy, hence it is worthwhile to evaluate the benefits of non-invasive myelin imaging. In this literature review, we provide an overview of the current evidence of myelin abnormalities in epilepsy from imaging and histological studies. After preselection, 21 histological and 21 in vivo imaging studies were identified. Primarily, epilepsy is found to be associated with a reduced myelin content. This review shows that the currently available literature does not provide a complete view into the nature of myelin abnormalities in epilepsy. However, the reported literature is indicative of a relation between the pathophysiology of epilepsy and the myelin content. More studies that apply myelin-specific imaging techniques are needed to determine whether the myelin abnormalities are an underlying cause of epilepsy, or a consequence of the excessive activity in epilepsy.

Cognition in absence epilepsy (AE) is generally considered undisturbed. However, reports on cognitive deficits in AE in recent years have suggested otherwise. This review systematically assesses current literature on cognitive performance in children with AE. A systematic literature search was performed in Pubmed, Embase, Cochrane and Web of Science. All studies reporting on cognitive performance in children with AE were considered. In total 33 studies were eligible for inclusion. Neuropsychological tests were classified into the following domains: intelligence; executive function; attention; language; motor & sensory-perceptual examinations; visuoperceptual/visuospatial/visuoconstructional function; memory and learning; achievement. Random-effect meta-analyses were conducted by estimating the pooled mean and/or pooling the mean difference in case-control studies. Full-scale IQ in children with AE was estimated at 96.78 (95%CI:94.46–99.10) across all available studies and in case-control studies IQ was on average 8.03 (95%CI:-10.45- -5.61) lower. Verbal IQ was estimated at 97.98 (95%CI:95.80–100.16) for all studies and 9.01 (95%CI:12.11- -5.90) points lower in case-control studies. Performance IQ was estimated at 97.23 (93.24–101.22) for all available studies and 5.32 (95%CI:-8.27–2.36) points lower in case-control studies. Lower performance was most often reported in executive function (cognitive flexibility, planning, and verbal fluency) and attention (sustained, selective and divided attention). Reports on school difficulties, neurodevelopmental problems, and attentional problems were high. In conclusion, in contrast to common beliefs, lower than average neurocognitive performance was noted in multiple cognitive domains, which may influence academic and psychosocial development.

Non-invasive quantification of the in vivo myelin content may provide valuable information regarding healthy maturation of the brain, as well as insights into demyelination of several neurological disorders. However, these scans are often long thereby limiting acquisition of large brain parts in clinically feasible acquisition times. Therefore, fast acquisition of whole brain myelin content is important. To avoid errors related to slice-selective pulses, most of the previous whole brain studies on myelin content relied on a 3D acquisition. However, multi-slice (2D) acquisition methods are often faster, and less susceptible to motion artifacts. Therefore, multi-slice approaches can be beneficial in a clinical setting. We investigated the applicability and reproducibility of whole brain multi-slice GRASE myelin-water imaging with post-acquisition slice-profile correction in healthy volunteers (aged 25-32y). The applicability was evaluated using the agreement between the multi-slice GRASE and the reference method for myelin-water imaging, single-slice multi spin-echo (MSE) acquisition. Additionally, we assessed the effect of varying acquisition acceleration using parallel imaging on the reproducibility values. First, the multi-slice myelin-water maps showed good agreement with the single-slice reference method, with a bias of at most 1.2% in absolute MWF values. Second, we found an average within-subject coefficient of variation (CoV) of 5.9% and an average intra-class correlation coefficient (ICC) of 0.90 for myelin-water estimation using a multi-slice GRASE sequence without parallel acceleration (scan time 14:06 min), while acquisition with a parallel acceleration factor of 2 resulted in a slightly worse average within-subject CoV of 6.4% and an average ICC of 0.83 at half the scan time. Hence, a multi-slice GRASE acquisition with parallel acceleration factor 2 and a scan time of 7:30 min still provides an excellent reproducibility.

Purpose: To obtain better microstructural integrity, interstitial fluid, and microvascular images from multi‐b‐value diffusion MRI data by using a physics‐informed neural network (PINN) fitting approach.Methods: Test–retest whole‐brain inversion recovery diffusion‐weighted images with multiple b‐values (IVIM: intravoxel incoherent motion) were acquired on separate days for 16 patients with cerebrovascular disease on a 3.0T MRI system. The performance of the PINN three‐component IVIM (3C‐IVIM) model fitting approach was compared with conventional fitting approaches (i.e., non‐negative least squares and two‐step least squares) in terms of (1) parameter map quality, (2) test–retest repeatability, and (3) voxel‐wise accuracy. Using the in vivo data, the parameter map quality was assessed by the parameter contrast‐to‐noise ratio (PCNR) between normal‐appearing white matter and white matter hyperintensities, and test–retest repeatability was expressed by the coefficient of variation (CV) and intraclass correlation coefficient (ICC). The voxel‐wise accuracy of the 3C‐IVIM parameters was determined by 10,000 computer simulations mimicking our in vivo data. Differences in PCNR and CV values obtained with the PINN approach versus conventional fitting approaches were assessed using paired Wilcoxon signed‐rank tests.Results: The PINN‐derived 3C‐IVIM parameter maps were of higher quality and more repeatable than those of conventional fitting approaches, while also achieving higher voxel‐wise accuracy.Conclusion: Physics‐informed neural networks enable robust voxel‐wise estimation of three diffusion components from the diffusion‐weighted signal. The repeatable and high‐quality biological parameter maps generated with PINNs allow for visual evaluation of pathophysiological processes in cerebrovascular disease.