Cross-vendor multiparametric mapping of the human brain using 3D-QALAS: A multicenter and multivendor study.

PURPOSE: To evaluate a vendor-agnostic multiparametric mapping scheme based on 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) for whole-brain T1, T2, and proton density (PD) mapping. METHODS: This prospective, multi-institutional study was conducted between September 2021 and February 2022 using five different 3T systems from four prominent MRI vendors. The accuracy of this technique was evaluated using a standardized MRI system phantom. Intra-scanner repeatability and inter-vendor reproducibility of T1, T2, and PD values were evaluated in 10 healthy volunteers (6 men; mean age ± SD, 28.0 ± 5.6 y) who underwent scan-rescan sessions on each scanner (total scans = 100). To evaluate the feasibility of 3D-QALAS, nine patients with multiple sclerosis (nine women; mean age ± SD, 48.2 ± 11.5 y) underwent imaging examination on two 3T MRI systems from different manufacturers. RESULTS: Quantitative maps obtained with 3D-QALAS showed high linearity (R2 = 0.998 and 0.998 for T1 and T2, respectively) with respect to reference measurements. The mean intra-scanner coefficients of variation for each scanner and structure ranged from 0.4% to 2.6%. The mean structure-wise test-retest repeatabilities were 1.6%, 1.1%, and 0.7% for T1, T2, and PD, respectively. Overall, high inter-vendor reproducibility was observed for all parameter maps and all structure measurements, including white matter lesions in patients with multiple sclerosis. CONCLUSION: The vendor-agnostic multiparametric mapping technique 3D-QALAS provided reproducible measurements of T1, T2, and PD for human tissues within a typical physiological range using 3T scanners from four different MRI manufacturers.

Noninvasive Magnetic Resonance Imaging Measures of Glymphatic System Activity.

The comprehension of the glymphatic system, a postulated mechanism responsible for the removal of interstitial solutes within the central nervous system (CNS), has witnessed substantial progress recently. While direct measurement techniques involving fluorescence and contrast agent tracers have demonstrated success in animal studies, their application in humans is invasive and presents challenges. Hence, exploring alternative noninvasive approaches that enable glymphatic research in humans is imperative. This review primarily focuses on several noninvasive magnetic resonance imaging (MRI) techniques, encompassing perivascular space (PVS) imaging, diffusion tensor image analysis along the PVS, arterial spin labeling, chemical exchange saturation transfer, and intravoxel incoherent motion. These methodologies provide valuable insights into the dynamics of interstitial fluid, water permeability across the blood-brain barrier, and cerebrospinal fluid flow within the cerebral parenchyma. Furthermore, the review elucidates the underlying concept and clinical applications of these noninvasive MRI techniques, highlighting their strengths and limitations. It addresses concerns about the relationship between glymphatic system activity and pathological alterations, emphasizing the necessity for further studies to establish correlations between noninvasive MRI measurements and pathological findings. Additionally, the challenges associated with conducting multisite studies, such as variability in MRI systems and acquisition parameters, are addressed, with a suggestion for the use of harmonization methods, such as the combined association test (COMBAT), to enhance standardization and statistical power. Current research gaps and future directions in noninvasive MRI techniques for assessing the glymphatic system are discussed, emphasizing the need for larger sample sizes, harmonization studies, and combined approaches. In conclusion, this review provides invaluable insights into the application of noninvasive MRI methods for monitoring glymphatic system activity in the CNS. It highlights their potential in advancing our understanding of the glymphatic system, facilitating clinical applications, and paving the way for future research endeavors in this field. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

Neuroimaging findings related to glymphatic system alterations in older adults with metabolic syndrome.

OBJECTIVE: The glymphatic system is a glial-based perivascular network that promotes brain metabolic waste clearance. Reduced glymphatic flow has been observed in rat models of type 2 diabetes and hypertension, indicating the role of vascular risk factors in the glymphatic system. However, little is known about how vascular risk factors affect the human glymphatic system. The present study aims to assess the relationships between metabolic syndrome (MetS), a cluster of vascular risk factors, and the glymphatic system function using diffusion magnetic resonance imaging (MRI)-based measures of water diffusivity in the glymphatic compartments, including the brain interstitial space and perivascular spaces around the deep medullary vein. We hypothesized that vascular risk factors are associated with glymphatic dysfunction, leading to cognitive impairment in older adults. METHODS: This cross-sectional study assessed 61 older adults (age range, 65-82 years) who had participated in the Bunkyo Health Study, including 15 healthy controls (mean age, 70.87 ± 4.90 years) and 46 individuals with MetS (mean age, 71.76 ± 4.61 years). Fractional volume of extracellular-free water (FW) and an index of diffusion tensor imaging along the perivascular space (DTI-ALPS) were used as indirect indicators of water diffusivity in the interstitial extracellular and perivenous spaces of white matter, respectively. RESULTS: After adjusting for age, sex, years of education, total Fazekas scale, Pittsburgh sleep quality index (PSQI) score, and intracranial volume (ICV), a significantly (P = 0.030; Cohen's d = 1.01) higher FW was observed in individuals with MetS than in the healthy controls. Furthermore, individuals with MetS had a significantly (P = 0.031; Cohen's d = 0.86) lower ALPS index than the healthy controls, with age, sex, years of education, total Fazekas scale, PSQI score, ICV, fractional anisotropy, and mean diffusivity included as confounding factors. Higher FW was significantly associated with lower ALPS index (r = -0.37; P = 0.004). Multiple linear regression (MLR) with backward elimination analyses showed that higher diastolic blood pressure (BP; standardized ß = 0.33, P = 0.005) was independently associated with higher FW, whereas higher fasting plasma glucose levels (standardized ß = -0.63, P = 0.002) or higher Brinkman index of cigarette consumption cumulative amount (standardized ß = -0.27, P = 0.022) were associated with lower ALPS index. The lower ALPS index (standardized ß, 0.28; P = 0.040) was associated with poorer global cognitive performance, which was determined using the Japanese version of the Montreal Cognitive Assessment (MOCA-J) scores. Finally, partial correlation analyses showed a significant correlation between higher FW and lower MOCA-J scores (r = -0.35; P = 0.025) and between higher FW and higher diastolic BP (r = 0.32, P = 0.044). CONCLUSION: The present study shows the changes in diffusion MRI-based measures reflected by the higher FW and lower ALPS index in older adults with MetS, possibly due to the adverse effect of vascular risk factors on the glymphatic system. Our findings also indicate the associations between the diffusion MRI-based measures and elevated diastolic BP, hyperglycemia, smoking habit, and poorer cognitive performance. However, owing to the limitations of this study, the results should be cautiously interpreted.

Fiber-Specific White Matter Alterations in Parkinson's Disease Patients with GBA Gene Mutations.

BACKGROUND: Patients with Parkinson's disease (PD) carrying GBA gene mutations (GBA-PD) have a more aggressive disease course than those with idiopathic PD (iPD). OBJECTIVE: The objective of this study was to investigate fiber-specific white matter (WM) differences in nonmedicated patients with early-stage GBA-PD and iPD using fixel-based analysis, a novel technique to assess tract-specific WM microstructural and macrostructural features comprehensively. METHODS: Fixel-based metrics, including microstructural fiber density (FD), macrostructural fiber-bundle cross section (FC), and a combination of FD and FC (FDC), were compared among 30 healthy control subjects, 16 patients with GBA-PD, and 35 patients with iPD. Associations between FDC and clinical evaluations were also explored using multiple linear regression analyses. RESULTS: Patients with GBA-PD showed significantly lower FD in the fornix and superior longitudinal fasciculus than healthy control subjects, and lower FC in the corticospinal tract (CST) and lower FDC in the CST, middle cerebellar peduncle, and striatal-thalamo-cortical pathways than patients with iPD. Contrarily, patients with iPD showed significantly higher FC and FDC in the CST and striatal-thalamo-cortical pathways than healthy control subjects. In addition, lower FDC in patients with GBA-PD was associated with reduced glucocerebrosidase enzyme activity, lower cerebrospinal fluid total α-synuclein levels, lower Montreal Cognitive Assessment scores, lower striatal binding ratio, and higher Unified Parkinson's Disease Rating Scale Part III scores. CONCLUSIONS: We report reduced fiber-specific WM density and bundle cross-sectional size in patients with GBA-PD, suggesting neurodegeneration linked to glucocerebrosidase deficiency, α-synuclein accumulation, and poorer cognition and motor functions. Conversely, patients with iPD showed increased fiber bundle size, likely because of WM reorganization. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Multimodal magnetic resonance imaging quantification of gray matter alterations in relapsing-remitting multiple sclerosis and neuromyelitis optica spectrum disorder.

Herein, we combined neurite orientation dispersion and density imaging (NODDI) and synthetic magnetic resonance imaging (SyMRI) to evaluate the spatial distribution and extent of gray matter (GM) microstructural alterations in patients with relapsing-remitting multiple sclerosis (RRMS) and neuromyelitis optica spectrum disorder (NMOSD). The NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) and SyMRI (myelin volume fraction [MVF]) measures were compared between age- and sex-matched groups of 30 patients with RRMS (6 males and 24 females; mean age, 51.43 ± 8.02 years), 18 patients with anti-aquaporin-4 antibody-positive NMOSD (2 males and 16 females; mean age, 52.67 ± 16.07 years), and 19 healthy controls (6 males and 13 females; mean age, 51.47 ± 9.25 years) using GM-based spatial statistical analysis. Patients with RRMS showed reduced NDI and MVF and increased ODI and ISOVF, predominantly in the limbic and paralimbic regions, when compared with healthy controls, while only increases in ODI and ISOVF were observed when compared with NMOSD. Compared to NDI and MVF, the changes in ODI and ISOVF were observed more widely, including in the cerebellar cortex. These abnormalities were associated with disease progression and disability. In contrast, patients with NMOSD only showed reduced NDI mainly in the cerebellar, limbic, and paralimbic cortices when compared with healthy controls and patients with RRMS. Taken together, our study supports the notion that GM pathologies in RRMS are distinct from those of NMOSD. However, owing to the limitations of the study, the results should be cautiously interpreted.

Multiple sclerosis plaques may undergo continuous myelin degradation: a cross-sectional study with myelin and axon-related quantitative magnetic resonance imaging metrics.

PURPOSE: We hypothesize that myelin is more susceptible to damage over time than axons. We investigated the association between the estimated duration from the onset of multiple sclerosis (MS) plaques and myelin- and axon-related quantitative synthetic magnetic resonance imaging (SyMRI) and neurite orientation dispersion and density imaging (NODDI) metrics. METHODS: We analyzed 31 patients with MS with 73 newly appeared plaques. Simple linear regression analysis was performed to assess the association between the estimated duration from the onset of plaques and quantitative MRI metrics. These metrics included the myelin volume fraction (MVF), axon volume fraction, and g-ratio in plaque and normal-appearing white matter. RESULTS: MS plaques with a longer estimated duration from onset were significantly correlated with a lower MVF (slope = - 0.0070, R2 = 0.0970), higher g-ratio (slope = 0.0078, R2 = 0.0842) (all P values < 0.05). CONCLUSION: These results suggested that myelin in plaques undergoes continuous damage, more so than axons. Myelin imaging with SyMRI and NODDI may be useful for the quantitative assessment of temporal changes in MS plaques.

Connectome analysis of male world-class gymnasts using probabilistic multishell, multitissue constrained spherical deconvolution tracking.

In athletes, long-term intensive training has been shown to increase unparalleled athletic ability and might induce brain plasticity. We evaluated the structural connectome of world-class gymnasts (WCGs), as mapped by diffusion-weighted magnetic resonance imaging probabilistic tractography and a multishell, multitissue constrained spherical deconvolution method to increase the precision of tractography at the tissue interfaces. The connectome was mapped in 10 Japanese male WCGs and in 10 age-matched male controls. Network-based statistic identified subnetworks with increased connectivity density in WCGs, involving the sensorimotor, default mode, attentional, visual, and limbic areas. It also revealed a significant association between the structural connectivity of some brain structures with functions closely related to the gymnastic skills and the D-score, which is used as an index of the gymnasts' specific physical abilities for each apparatus. Furthermore, graph theory analysis demonstrated the characteristics of brain anatomical topology in the WCGs. They displayed significantly increased global connectivity strength with decreased characteristic path length at the global level and higher nodal strength and degree in the sensorimotor, default mode, attention, and limbic/subcortical areas at the local level as compared with controls. Together, these findings extend the current understanding of neural mechanisms that distinguish WCGs from controls and suggest brain anatomical network plasticity in WCGs resulting from long-term intensive training. Future studies should assess the contribution of genetic or early-life environmental factors in the brain network organization of WCGs. Furthermore, the indices of brain topology (i.e., connection density and graph theory indices) could become markers for the objective evaluation of gymnastic performance.

Parkinson's disease: deep learning with a parameter-weighted structural connectome matrix for diagnosis and neural circuit disorder investigation.

PURPOSE: To investigate whether Parkinson's disease (PD) can be differentiated from healthy controls and to identify neural circuit disorders in PD by applying a deep learning technique to parameter-weighted and number of streamlines (NOS)-based structural connectome matrices calculated from diffusion-weighted MRI. METHODS: In this prospective study, 115 PD patients and 115 healthy controls were enrolled. NOS-based and parameter-weighted connectome matrices were calculated from MRI images obtained with a 3-T MRI unit. With 5-fold cross-validation, diagnostic performance of convolutional neural network (CNN) models using those connectome matrices in differentiating patients with PD from healthy controls was evaluated. To identify the important brain connections for diagnosing PD, gradient-weighted class activation mapping (Grad-CAM) was applied to the trained CNN models. RESULTS: CNN models based on some parameter-weighted structural matrices (diffusion kurtosis imaging (DKI)-weighted, neurite orientation dispersion and density imaging (NODDI)-weighted, and g-ratio-weighted connectome matrices) showed moderate performance (areas under the receiver operating characteristic curve (AUCs) = 0.895, 0.801, and 0.836, respectively) in discriminating PD patients from healthy controls. The DKI-weighted connectome matrix performed significantly better than the conventional NOS-based matrix (AUC = 0.761) (DeLong's test, p < 0.0001). Alterations of neural connections between the basal ganglia and cerebellum were indicated by applying Grad-CAM to the NODDI- and g-ratio-weighted matrices. CONCLUSION: Patients with PD can be differentiated from healthy controls by applying the deep learning technique to the parameter-weighted connectome matrices, and neural circuit disorders including those between the basal ganglia on one side and the cerebellum on the contralateral side were visualized.

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases.

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.

Neurocognitive and psychiatric disorders-related axonal degeneration in Parkinson's disease.

Neurocognitive and psychiatric disorders have significant consequences for quality of life in patients with Parkinson's disease (PD). In the current study, we evaluated microstructural white matter (WM) alterations associated with neurocognitive and psychiatric disorders in PD using neurite orientation dispersion and density imaging (NODDI) and linked independent component analysis (LICA). The indices of NODDI were compared between 20 and 19 patients with PD with and without neurocognitive and psychiatric disorders, respectively, and 25 healthy controls using tract-based spatial statistics and tract-of-interest analyses. LICA was applied to model inter-subject variability across measures. A widespread reduction in axonal density (indexed by intracellular volume fraction [ICVF]) was demonstrated in PD patients with and without neurocognitive and psychiatric disorders, as compared with healthy controls. Compared with patients without neurocognitive and psychiatric disorders, patients with neurocognitive and psychiatric disorders exhibited more extensive (posterior predominant) decreases in axonal density. Using LICA, ICVF demonstrated the highest contribution (59% weight) to the main effects of diagnosis that reflected widespread decreases in axonal density. These findings suggest that axonal loss is a major factor underlying WM pathology related to neurocognitive and psychiatric disorders in PD, whereas patients with neurocognitive and psychiatric disorders had broader axonal pathology, as compared with those without. LICA suggested that the ICVF can be used as a useful biomarker of microstructural changes in the WM related to neurocognitive and psychiatric disorders in PD.

MR Biomarkers of Degenerative Brain Disorders Derived From Diffusion Imaging.

The incidence of neurodegenerative diseases has shown an increasing trend. These conditions typically cause progressive functional disability. Identification of robust biomarkers of neurodegenerative diseases is a key imperative to facilitate early identification of the pathological features and to foster a better understanding of the pathogenetic mechanisms of individual diseases. Diffusion tensor imaging (DTI) is the most widely used diffusion MRI technique for assessment of neurodegenerative diseases. The DTI parameters are promising biomarkers for evaluation of microstructural changes; however, some limitations of DTI restrict its wider clinical use. New diffusion MRI techniques, such as diffusion kurtosis imaging (DKI), bi-tensor DTI, and neurite orientation density and dispersion imaging (NODDI) have been demonstrated to provide value addition to DTI for evaluation of neurodegenerative diseases. In this review article, we summarize the key technical aspects and provide an overview of the current state of knowledge regarding the role of DKI, bi-tensor DTI, and NODDI as biomarkers of microstructural changes in representative neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1620-1636.

Scan-rescan and inter-vendor reproducibility of neurite orientation dispersion and density imaging metrics.

PURPOSE: The reproducibility of neurite orientation dispersion and density imaging (NODDI) metrics in the human brain has not been explored across different magnetic resonance (MR) scanners from different vendors. This study aimed to evaluate the scan-rescan and inter-vendor reproducibility of NODDI metrics in white and gray matter of healthy subjects using two 3-T MR scanners from two vendors. METHODS: Ten healthy subjects (7 males; mean age 30 ± 7 years, range 23-37 years) were included in the study. Whole-brain diffusion-weighted imaging was performed with b-values of 1000 and 2000 s/mm2 using two 3-T MR scanners from two different vendors. Automatic extraction of the region of interest was performed to obtain NODDI metrics for whole and localized areas of white and gray matter. The coefficient of variation (CoV) and intraclass correlation coefficient (ICC) were calculated to assess the scan-rescan and inter-vendor reproducibilities of NODDI metrics. RESULTS: The scan-rescan and inter-vendor reproducibility of NODDI metrics (intracellular volume fraction and orientation dispersion index) were comparable with those of diffusion tensor imaging (DTI) metrics. However, the inter-vendor reproducibilities of NODDI (CoV = 2.3-14%) were lower than the scan-rescan reproducibility (CoV: scanner A = 0.8-3.8%; scanner B = 0.8-2.6%). Compared with the finding of DTI metrics, the reproducibility of NODDI metrics was lower in white matter and higher in gray matter. CONCLUSION: The lower inter-vendor reproducibility of NODDI in some brain regions indicates that data acquired from different MRI scanners should be carefully interpreted.

Evaluation of white matter microstructure in patients with Parkinson's disease using microscopic fractional anisotropy.

PURPOSE: Micro fractional anisotropy (µFA) is more accurate than conventional fractional anisotropy (FA) for assessing microscopic tissue properties and can overcome limitations related to crossing white matter fibres. We compared µFA and FA for evaluating white matter changes in patients with Parkinson's disease (PD). METHODS: We compared FA and µFA measures between 25 patients with PD and 25 age- and gender-matched healthy controls using tract-based spatial statistics (TBSS) analysis. We also examined potential correlations between changes, revealed by conventional FA or µFA, and disease duration or Unified Parkinson's Disease Rating Scale (UPDRS)-III scores. RESULTS: Compared with healthy controls, patients with PD had significantly reduced µFA values, mainly in the anterior corona radiata (ACR). In the PD group, µFA values (primarily those from the ACR) were significantly negatively correlated with UPDRS-III motor scores. No significant changes or correlations with disease duration or UPDRS-III scores with tissue properties were detected using conventional FA. CONCLUSION: µFA can evaluate microstructural changes that occur during white matter degeneration in patients with PD and may overcome a key limitation of FA.

Ventricular volumetry and free-water corrected diffusion tensor imaging of the anterior thalamic radiation in idiopathic normal pressure hydrocephalus.

BACKGROUND AND PURPOSE: The pathophysiology of idiopathic normal pressure hydrocephalus (iNPH) has not been completely clarified. We investigated the brain structure in iNPH using automatic ventricular volumetry, single-tensor diffusion tensor imaging (DTI) and bi-tensor free-water (FW) imaging analyses while focusing on cognitive impairments before and after lumboperitoneal shunt surgery. MATERIALS AND METHODS: This retrospective study included 12 iNPH patients with structural magnetic resonance imaging (MRI) and diffusion MRI (dMRI) on a 3T-MRI scanner who underwent neuropsychological assessments before and after shunting and 8 healthy controls. Ventricular volumetry was conducted on structural MRI datasets using FreeSurfer. Ventricular volume was compared pre- and postoperatively. Correlation analyses were performed between ventricular volume or volume change and neuropsychological scores or score change. Tract-based spatial statistics were performed using dMRI datasets for group analyses between iNPH and controls and between pre- and post-surgery iNPH patients and for correlation analyses using neuropsychological scores. Tract-specific analyses were performed in the anterior thalamic radiation (ATR), followed by comparison and correlation analyses. RESULTS: The third ventricular volume was significantly decreased after shunting; its volume reduction negatively correlated with a neuropsychological improvement. Compared with controls, iNPH patients had lower fractional anisotropy and higher axial, radial, and mean diffusivities, and FW in the periventricular white matter including ATR, resulting in no difference in FW-corrected indices. Single-tensor DTI indices partially correlated with neuropsychological improvements, while FW-corrected indices had no correlations. CONCLUSION: Third ventricle enlargement is possibly linked to cognitive impairment and FW imaging possibly provides better white matter characterization in iNPH.

3D quantitative synthetic MRI-derived cortical thickness and subcortical brain volumes: Scan-rescan repeatability and comparison with conventional T1 -weighted images.

BACKGROUND: Previous quantitative synthetic MRI of the brain has been solely performed in 2D. PURPOSE: To evaluate the feasibility of the recently developed sequence 3D-QALAS for brain cortical thickness and volumetric analysis. STUDY TYPE: Reproducibility/repeatability study. SUBJECTS: Twenty-one healthy volunteers (35.6 ± 13.8 years). FIELD STRENGTH/SEQUENCE: 3D T1 -weighted fast spoiled gradient recalled echo (FSPGR) sequence was performed once, and 3D-QALAS sequence was performed twice with a 3T scanner. ASSESSMENT: FreeSurfer and FIRST were used to measure cortical thickness and volume of subcortical structures, respectively. Agreement with FSPGR and scan-rescan repeatability were evaluated for 3D-QALAS. STATISTICAL TESTS: Percent relative difference and intraclass correlation coefficient (ICC) were used to assess reproducibility and scan-rescan repeatability of the 3D-QALAS sequence-derived measurements. RESULTS: Percent relative difference compared with FSPGR in cortical thickness of the whole cortex was 3.1%, and 89% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.65, and 74% of the structures showed substantial to almost perfect agreement. For volumes of subcortical structures, the median percent relative differences were lower than 10% across all subcortical structures, except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. For the scan-rescan test, percent relative difference in cortical thickness of the whole cortex was 2.3%, and 97% of the regional areas showed less than 10% relative difference in cortical thickness. The mean ICC across all regions was 0.73, and 80% showed substantial to almost perfect agreement. For volumes of subcortical structures, relative differences were less than 10% across all subcortical structures except for the accumbens area, and all structures showed ICCs of substantial to almost perfect agreement. DATA CONCLUSION: 3D-QALAS could be reliably used for measuring cortical thickness and subcortical volumes in most brain regions. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1834-1842.

Aberrant myelination in patients with Sturge-Weber syndrome analyzed using synthetic quantitative magnetic resonance imaging.

PURPOSE: Accelerated myelination in the affected hemisphere has been demonstrated previously in patients with Sturge-Weber syndrome (SWS). This prospective study investigated myelin-related changes in patients with unilateral SWS using synthetic quantitative magnetic resonance imaging (qMRI). METHODS: Fourteen children with unilateral SWS were categorized according to age, i.e., ≤ 2 years (group A, n = 5, mean age 1.1 years, 3 males) and > 2 years (group B, n = 9, mean age 3.9 years, 4 males). All children underwent two-dimensional synthetic qMRI. The myelin volume in the cerebral hemisphere and white matter (WM) myelin volume fraction (MVF), proton density (PD), R1 and R2 relaxation rates ipsilateral to the leptomeningeal enhancement, and/or a port-wine birthmark were compared with the corresponding values in the contralateral hemisphere. RESULTS: In group A, 3 patients had a higher myelin volume in the ipsilateral hemisphere and a higher MVF, R1, and R2 and lower PD in the ipsilateral WM than on the contralateral side; the findings were the opposite in the remaining two patients. All patients in group B had a significantly lower myelin volume in the ipsilateral hemisphere (P < 0.05) and a lower MVF and R1 and higher PD in the ipsilateral WM than on the contralateral side (P < 0.0125). CONCLUSION: Higher estimated myelin was observed on the ipsilateral side in some patients aged ≤ 2 years and lower myelin on the ipsilateral side in all older patients. Synthetic qMRI might be useful for showing myelin-related abnormalities in SWS.

Brain tissue and myelin volumetric analysis in multiple sclerosis at 3T MRI with various in-plane resolutions using synthetic MRI.

PURPOSE: Synthetic MRI (SyMRI) enables automatic brain tissue and myelin volumetry based on the quantification of R1 and R2 relaxation rates and proton density. This study aimed to determine the validity of SyMRI brain tissue and myelin volumetry using various in-plane resolutions at 3T in patients with multiple sclerosis (MS). METHODS: We scanned 19 MS patients and 10 healthy age- and gender-matched controls using a 3T MR scanner with in-plane resolutions of 0.8, 1.8, and 3.6 mm. The acquisition times were 5 min 8 s, 2 min 52 s, and 2 min 1 s, respectively. White matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and myelin and non-WM/GM/CSF (NoN) volumes; brain parenchymal volume (BPV); and intracranial volume (ICV) were compared between different in-plane resolutions. These parameters were also compared between both groups, after ICV normalization. RESULTS: No significant differences in measured volumes were noted between the 0.8 and 1.8 mm in-plane resolutions, except in NoN and CSF for healthy controls and NoN for MS patients. Meanwhile, significant volumetric differences were noted in most brain tissues when compared between the 3.6 and 0.8 or 1.8 mm resolution for both healthy controls and MS patients. The normalized WM volume, myelin volume, and BPV showed significant differences between controls and MS patients at in-plane resolutions of 0.8 and 1.8 mm. CONCLUSIONS: SyMRI brain tissue and myelin volumetry with in-plane resolution as low as 1.8 mm can be useful in the evaluation of MS with a short acquisition time of < 3 min.

White matter alterations in adult with autism spectrum disorder evaluated using diffusion kurtosis imaging.

PURPOSE: Autism spectrum disorder (ASD) is related to impairment in various white matter (WM) pathways. Utility of the recently developed two-compartment model of diffusion kurtosis imaging (DKI) to analyse axial diffusivity of WM is restricted by several limitations. The present study aims to validate the utility of model-free DKI in the evaluation of WM alterations in ASD and analyse the potential relationship between DKI-evident WM alterations and personality scales. METHODS: Overall, 15 participants with ASD and 15 neurotypical (NT) controls were scanned on a 3 T magnetic resonance (MR) scanner, and scores for autism quotient (AQ), systemising quotient (SQ) and empathising quotient (EQ) were obtained for both groups. Multishell diffusion-weighted MR data were acquired using two b-values (1000 and 2000 s/mm2). Differences in mean kurtosis (MK), radial kurtosis (RK) and axial kurtosis (AK) between the groups were evaluated using tract-based spatial statistics (TBSS). Finally, the relationships between the kurtosis indices and personality quotients were examined. RESULTS: The ASD group demonstrated significantly lower AK in the body and splenium of corpus callosum than the NT group; however, no other significant differences were identified. Negative correlations were found between AK and AQ or SQ, predominantly in WM areas related to social-emotional processing such as uncinate fasciculus, inferior fronto-occipital fasciculus, and inferior and superior longitudinal fasciculi. CONCLUSIONS: Model-free DKI and its indices may represent a novel, objective method for detecting the disease severity and WM alterations in patients with ASD.

Convolutional neural network-based segmentation can help in assessing the substantia nigra in neuromelanin MRI.

PURPOSE: This study aimed to evaluate the accuracy and diagnostic test performance of the U-net-based segmentation method in neuromelanin magnetic resonance imaging (NM-MRI) compared to the established manual segmentation method for Parkinson's disease (PD) diagnosis. METHODS: NM-MRI datasets from two different 3T-scanners were used: a "principal dataset" with 122 participants and an "external validation dataset" with 24 participants, including 62 and 12 PD patients, respectively. Two radiologists performed SNpc manual segmentation. Inter-reader precision was determined using Dice coefficients. The U-net was trained with manual segmentation as ground truth and Dice coefficients used to measure accuracy. Training and validation steps were performed on the principal dataset using a 4-fold cross-validation method. We tested the U-net on the external validation dataset. SNpc hyperintense areas were estimated from U-net and manual segmentation masks, replicating a previously validated thresholding method, and their diagnostic test performances for PD determined. RESULTS: For SNpc segmentation, U-net accuracy was comparable to inter-reader precision in the principal dataset (Dice coefficient: U-net, 0.83 ± 0.04; inter-reader, 0.83 ± 0.04), but lower in external validation dataset (Dice coefficient: U-net, 079 ± 0.04; inter-reader, 0.85 ± 0.03). Diagnostic test performances for PD were comparable between U-net and manual segmentation methods in both principal (area under the receiver operating characteristic curve: U-net, 0.950; manual, 0.948) and external (U-net, 0.944; manual, 0.931) datasets. CONCLUSION: U-net segmentation provided relatively high accuracy in the evaluation of the SNpc in NM-MRI and yielded diagnostic performance comparable to that of the established manual method.

Review of synthetic MRI in pediatric brains: Basic principle of MR quantification, its features, clinical applications, and limitations.

Quantitative magnetic resonance imaging (MRI) with multislice, multi-echo, and multi-delay acquisition enables simultaneous quantification of R1 and R2 relaxation rates, proton density, and the B1 field in a single acquisition, and requires only about 6 minutes for full-head coverage. Using dedicated SyMRI software, radiologists can generate any contrast-weighted image by manipulating the acquisition parameters, including repetition time, echo time, and inversion time. Moreover, automatic brain tissue segmentation, volumetry, and myelin measurement can also be performed. Using the SyMRI approach, a shorter scan time, an objective examination, and personalized MR imaging parameters can be obtained in daily clinical pediatric imaging. Here we summarize and review the use of SyMRI in imaging of the pediatric brain, including the basic principles of MR quantification along with its features, clinical applications, and limitations.