BACKGROUND/OBJECTIVES:Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluation. However, current automated approaches for lesion detection and segmentation are typically designed for specific MRI contrasts or acquisition sites, limiting their generalizability in real-world clinical settings where imaging protocols vary widely. This work proposes a robust multi-site, multi-contrast segmentation framework for spinal cord lesions. METHODS:The segmentation model was trained and evaluated on a large-scale dataset comprising 4428 annotated images from 1849 persons with MS across 23 imaging centers, encompassing six MRI contrasts (T1w, T2w, T2*w, PSIR, STIR, and UNIT1) acquired at 1.5 tesla (T), 3 T, and 7 T. RESULTS:Likert-type assessment performed by neuroradiologist ratings demonstrated superior generalization of the model compared to existing contrast-specific pipelines (p < 0.01). Additional experiments evaluated robustness across spinal levels, acquisition resolutions, binarization thresholds, and quantitative evaluation on external labeled datasets. CONCLUSIONS:The proposed model can achieve accurate and reliable spinal cord MS lesion segmentation across heterogeneous MRI data, addressing a key barrier to clinical translation. The model is available in the Spinal Cord Toolbox v7.2 and higher.Code repository: https://github.com/ivadomed/seg-sc-ms-lesion-multicontrast.

Magnetic resonance neuroimaging is undergoing a major paradigm shift from traditional qualitative anatomical mapping toward integrated, quantitative measurement systems with biological interpretability. This review systematically synthesizes nine methodological pillars driving this transformation, encompassing advances ranging from hardware innovation to artificial intelligence algorithms. We first explore the pivotal role of deep learning in image reconstruction and acceleration, followed by detailed analyses of quantitative brain oxygen metabolism assessment, standardized spinal cord imaging frameworks, and the non-invasive monitoring of the glymphatic system using diffusion MRI. Furthermore, the review delves into tractometry, susceptibility-based myelin mapping, the clinical standardization of arterial spin labeling, and the application of radiomics in extracting high-dimensional phenotypes. Finally, the importance of open science and workflow coordination in enhancing research reproducibility is highlighted. Through the deep integration of hardware, sequences, and artificial intelligence, these technologies form a synergistic ecosystem that provides unprecedented precision tools and translational potential for both basic neuroscience research and clinical precision medicine. Across these domains, AI contributes not only to acceleration and reconstruction but also to segmentation, quality control, quantitative parameter extraction, and multiparametric pattern recognition that can support diagnostic interpretation. The quantitative emphasis of this review therefore lies in measurable outputs such as image-quality metrics, metabolic and perfusion parameters, tract-specific diffusion indices, susceptibility-based components, and radiomic features.

BACKGROUND AND PURPOSE:Accurate in vivo quantification of myelin remains challenging despite advances in MRI. We evaluated three-dimensional synthetic MRI-derived myelin volume fraction from three-dimensional quantification using an interleaved Look-Locker acquisition sequence with T2 preparation pulse (3D-QALAS) by comparing it with inhomogeneous magnetization transfer ratio, myelin water fraction, and the T1-weighted/T2-weighted ratio in healthy volunteers and patients with multiple sclerosis. MATERIALS AND METHODS:Thirty-one healthy volunteers and 33 consecutive patients with multiple sclerosis underwent 3T MRI including 3D-QALAS, 3D inhomogeneous magnetization transfer imaging, and 2D multi-echo spin-echo imaging for myelin water fraction. Synthetic T1-weighted/T2-weighted ratio maps were generated from quantitative R1, R2, and proton density data. Lesions were segmented using a deep learning-based method, and periplaque regions were defined by 2-voxel isotropic dilation. Atlas-based ROI analyses in normal-appearing brain tissue were performed using repeated-measures correlation. WM lesion-centered analyses were performed to compare metric differences relative to normal-appearing white matter using linear mixed-effects models. RESULTS:In normal-appearing brain tissue pooled across patients and volunteers, myelin volume fraction demonstrated strong overall repeated-measures correlations with the inhomogeneous magnetization transfer ratio (r = 0.86; 95% CI, 0.85-0.87) and the T1-weighted/T2-weighted ratio (r = 0.89; 95% CI, 0.88-0.89), and more modest correlations with myelin water fraction (r = 0.63; 95% CI, 0.61-0.64). The inhomogeneous magnetization transfer ratio-myelin water fraction correlation was r = 0.60 (95% CI, 0.58-0.62). This overall ranking was preserved in volunteers and patients analyzed separately, and Spearman analyses showed a similar pattern. In WM lesion-centered analyses, values relative to normal-appearing WM were lowest for myelin volume fraction (44.2% in plaque, 75.4% in periplaque), followed by the T1-weighted/T2-weighted ratio (56.5%, 77.3%), the inhomogeneous magnetization transfer ratio (74.7%, 87.8%), and myelin water fraction (93.4%, 98.3%). CONCLUSIONS:3D-QALAS-derived myelin volume fraction demonstrated strong overall concordance with the inhomogeneous magnetization transfer ratio in normal-appearing brain tissue and greater lesion-associated deviation from normal-appearing white matter than the other myelin-sensitive metrics. These findings support 3D-QALAS-derived myelin volume fraction as a promising volumetric biomarker of myelin integrity with whole-brain coverage suitable for routine clinical application.

Tumor stiffness strongly influences exposure, extent of resection, operative time, and approach in meningioma surgery, but magnetic resonance imaging-based prediction still relies mainly on qualitative assessment. We evaluated whether a diffusion-derived stiffness surrogate calculated from diffusion-weighted magnetic resonance imaging-based virtual elastography correlates with intraoperative quantitative tumor stiffness in meningiomas and assessed its usefulness for preoperative stiffness prediction. Of 33 patients who underwent meningioma surgery between May 2022 and January 2025, 22 with both preoperative virtual elastography and intraoperative stiffness measurements were analyzed. Preoperative 3-Tesla diffusion-weighted magnetic resonance imaging with 2 b values was used to generate shifted apparent diffusion coefficient maps, and a single-slice volume of interest with a 5.51 mm slice thickness was manually delineated on the axial slice showing the largest tumor cross-sectional area. Intraoperative tumor stiffness of approximately 1-cm3 fresh specimens was measured with a rheometer and expressed as Young's modulus. The relationship between the diffusion-derived stiffness surrogate and stiffness was examined using Pearson correlation and multivariate linear regression. The diffusion-derived stiffness surrogate showed a significant negative correlation with tumor stiffness (r = -0.655, p = 0.00094), and this association remained significant after exclusion of embolized cases. Lower diffusion-derived stiffness surrogate values were associated with firmer tumors, whereas higher values were associated with softer tumors. These findings indicate that diffusion-weighted magnetic resonance imaging-based virtual elastography may provide a noninvasive, quantitative preoperative surrogate marker for estimating the stiffness of selected solid components of meningiomas and may offer adjunctive information for surgical planning.

Background Perfusion imaging of the brain has important clinical applications in detecting neurological abnormalities in neonates. However, such tools have not been available to date. Although arterial‐spin‐labeling (ASL) MRI is a powerful noninvasive tool to measure perfusion, its application in neonates has encountered obstacles related to low signal‐to‐noise ratio (SNR), large‐vessel contaminations, and lack of technical development studies. Purpose To systematically develop and optimize ASL perfusion MRI in healthy neonates under 1 week of age. Study Type Prospective. Subjects Thirty‐two healthy term neonates (19 female; postnatal age 1.9 ± 0.7 days). Field Strength/Sequence 3. 0 T ; T 2 ‐weighted half‐Fourier single‐shot turbo‐spin‐echo ( HASTE ) imaging, single‐delay and multi‐delay 3D gradient‐and‐spin‐echo ( GRASE ) large‐vessel‐suppression pseudo‐continuous ASL ( LVS ‐ pCASL ). Assessment Three studies were conducted. First, an LVS‐pCASL MRI sequence was developed to suppress large‐vessel spurious signals in neonatal pCASL. Second, multiple post‐labeling delays (PLDs) LVS‐pCASL were employed to simultaneously estimate normative cerebral blood flow (CBF) and arterial transit time (ATT) in neonates. Third, an enhanced background‐suppression (BS) scheme was developed to increase the SNR of neonatal pCASL. Statistical Tests Repeated measure analysis‐of‐variance, paired t ‐test, spatial intraclass‐correlation‐coefficient (ICC), and voxel‐wise coefficient‐of‐variation (CoV). P ‐value <0.05 was considered significant. Results LVS‐pCASL reduced spurious ASL signals, making the CBF images more homogenous and significantly reducing the temporal variation of CBF measurements by 58.0% when compared to the standard pCASL. Multi‐PLD ASL yielded ATT and CBF maps showing a longer ATT and lower CBF in the white matter relative to the gray matter. The highest CBF was observed in basal ganglia and thalamus (10.4 ± 1.9 mL/100 g/min). Enhanced BS resulted in significantly higher test–retest reproducibility (ICC = 0.90 ± 0.04, CoV = 8.4 ± 1.2%) when compared to regular BS (ICC = 0.59 ± 0.12, CoV = 23.6 ± 3.8%). Data Conclusion We devised an ASL method that can generate whole‐brain CBF images in 4 minutes with a test–retest image ICC of 0.9. This technique holds potential for studying neonatal brain diseases involving perfusion abnormalities. Plain Language Summary MR imaging of cerebral blood flow in neonates remains a challenge due to low blood flow rates and confounding factors from large blood vessels. This study systematically developed an advanced MRI technique to enhance the reliability of perfusion measurements in neonates. The proposed method reduced signal artifacts from large blood vessels and improved the signal‐to‐noise ratio of brain perfusion images. With this approach, whole‐brain neonatal perfusion can be measured in 4 minutes with excellent reproducibility. This technique may provide a useful tool for studying neonatal brain maturation and detecting perfusion abnormalities in diseases. Evidence Level 2 Technical Efficacy Stage 1

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e., height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1 ± 6.6 years old, 125 females). We show that body height correlates with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44 ≤ r ≤ 0.62). Intracranial volume (ICV) correlates with body height (r = 0.46) and the brain volumes and CSA-WM (0.37 ≤ r ≤ 0.77). In comparison, age correlates with cortical GM volume, precentral GM volume, and cortical thickness (-0.21 ≥ r ≥ -0.27). Body weight correlates with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20 ≥ r ≥ -0.23). Body weight further correlates with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r = -0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlates with brain volumes (0.39 ≤ r ≤ 0.64), and with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22 ≥ r ≥ -0.25). Linear mixture of age, sex, or sex and age, explained 2 ± 2%, 24 ± 10%, or 26 ± 10%, of data variance in brain volumetry and SC CSA. The amount of explained variance increased to 33 ± 11%, 41 ± 17%, or 46 ± 17%, when body height, ICV, or body height and ICV were added into the mixture model. In females, the explained variances halved suggesting another unidentified biological factor(s) determining females' central nervous system (CNS) morphology. In conclusion, body size and ICV are significant biological variables. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure; and body size and ICV should be considered as covariates in statistical analyses. Normalization of different brain regions with ICV diminishes their correlations with body size, but simultaneously amplifies ICV-related variance (r = 0.72 ± 0.07) and suppresses volume variance of the different brain regions (r = 0.12 ± 0.19) in the normalized measurements.

Prosopagnosia is a cognitive disorder in which facial recognition is severely impaired despite normal vision and intelligence. Prosopagnosia was first reported in the 1800s, but its cause remains unclear. Although other neurological symptoms are often present, some patients have pure prosopagnosia. The bilateral occipital lobes are believed to be associated with symptoms. Recent brain imaging techniques have identified the right fusiform gyrus (rFG), located at the junction of the right occipital temporal lobe, as the affected region. In this report, we present a case of associative prosopagnosia with no concomitant symptoms in a 76-year-old man. Brain magnetic resonance imaging detected a subcortical hemorrhage in the right temporal lobe. Using tractography based on diffusion tensor imaging, we visualized atrophy of the right inferior longitudinal fasciculus (ILF). This is the first time tractography has been used to show a clear association between associative prosopagnosia and ILF damage projecting from the rFG.

Transcutaneous spinal stimulation has been applied to gait rehabilitation for persons with neurological diseases. The authors developed electromyography-triggered transcutaneous spinal cord and hip stimulation for gait rehabilitation and called this system FAST walk. This study aimed to assess the effect of FAST walk in a randomized, controlled trial. All participants were randomly allocated to three groups: FAST walk combined with treadmill gait training (FAST walk); spinal stimulation combined with treadmill gait training (spinal stim); and treadmill gait training (treadmill). Participants performed two sets of 15-min treadmill gait training with 5-min intervals in the FAST walk, spinal stim, and treadmill groups. Gait training was performed twice weekly for a total of 10 sessions. The primary outcome was 10-m walking time. The secondary outcomes were the time symmetry index (TSI) with gait analysis and spinal reciprocal inhibition on the conditioned-test H reflex study. Twenty persons with chronic stroke participated in this study, and 17 persons completed this study. For the primary outcome, there was no significant interaction between time and intervention in 10-m walking time on two-way analysis of covariance (ANCOVA) (P = 0.382, η2 = 0.064). For the FAST walk group, 10-m walking time improved significantly at post and post-4w (P = 0.024 and 0.022, respectively). In the other groups, no significant improvements in 10-m walking time were seen at post and post-4w compared with before. There was also no significant between-group difference in the 10-m walking time. The newly developed electromyography-triggered transcutaneous spinal cord and hip stimulation, FAST walk, is safe and may improve the gait speed of persons with chronic stroke. We did not, however, find a significant between-group difference among the FAST walk, spinal stim, and treadmill gait groups. Trial registration: Japan Registry of Clinical Trial (JRCT registration ID: jRCTs032180289).

To characterize utility of atrioventricular block (AVB) dogs as atrial fibrillation (AF) model, we studied remodeling processes occurring in their atria in acute (<2 weeks) and chronic (>4 weeks) phases. Fifty beagle dogs were used. Holter electrocardiogram demonstrated that paroxysmal AF occurred immediately after the production of AVB, of which duration tended to be prolonged in chronic phase. Electrophysiological analysis showed that inter-atrial conduction time and duration of burst pacing-induced AF increased in the chronic phase compared with those in the acute phase, but that atrial effective refractory period was hardly altered. Echocardiographic study revealed that diameters of left atrium, right pulmonary vein and inferior vena cava increased similarly in the acute and chronic phases. Histological evaluation indicated that hypertrophy and fibrosis in atrial tissue increased in the chronic phase. Electropharmacological characterization showed that i.v. pilsicainide effectively suppressed burst pacing-induced AF with increasing atrial conduction time and refractoriness of AVB dogs in chronic phase, but that i.v. amiodarone did not exert such electrophysiological effects. Taken together, AVB dogs in chronic phase appear to possess such pathophysiology as developed in the atria of early-stage AF patients, and therefore they can be used to evaluate drug candidates against early-stage AF.

Frontal-striatal-thalamic circuit impairment is presumed to underlie schizophrenia. Individuals with attenuated psychosis syndrome (APS) show longitudinal volume reduction of the putamen in the striatum, which has a neural connection with the premotor cortex through the frontal-striatal-thalamic subcircuit. However, comprehensive investigations into the biological changes in the frontal-striatal-thalamic subcircuit originating from the premotor cortex in APS are lacking. We investigated differences in fractional anisotropy (FA) values between the striatum and premotor cortex (ST-PREM) and between the thalamus and premotor cortex (T-PREM) in individuals with APS and healthy controls, using a novel method TractSeg. Our study comprised 36 individuals with APS and 38 healthy controls. There was a significant difference between the control and APS groups in the right T-PREM (odds ratio = 1.76, p = 0.02). Other factors, such as age, sex, other values of FA, and antipsychotic medication, were not associated with differences between groups. However, while FA value reduction of ST-PREM and T-PREM in schizophrenia has been previously reported, in the present study on APS, the alteration of the FA value was limited to T-PREM in APS. This finding suggests that ST-PREM impairment is not predominant in APS but emerges in schizophrenia. Impairment of the neural network originating from the premotor cortex can lead to catatonia and aberrant mirror neuron networks that are presumed to provoke various psychotic symptoms of schizophrenia. Our findings highlight the potential role of changes in a segment of the frontal-thalamic pathway derived from the premotor cortex as a biological basis of APS.

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.

IntroductionAberrant fixation and scan paths in visual searches have been repeatedly reported in schizophrenia. The frontal eye fields (FEF) and thalamus may be responsible for fixation and scan paths. These two regions are connected by superior thalamic radiation (STR) in humans. Studies have reported reduced fixation numbers and shortened scan path lengths in individuals with attenuated psychosis syndrome (APS) and schizophrenia. In this study, we hypothesized that STRs in the white matter fiber bundles of impairments underlie abnormalities in fixation and scan path length in individuals with APS.MethodsTwenty-one individuals with APS and 30 healthy controls participated in this study. All participants underwent diffusion tensor imaging, and fractional anisotropy (FA) values of the left and right STR were analyzed using the novel method TractSeg. The number of eye fixations (NEF), total eye scanning length (TESL), and mean eye scanning length (MESL), derived using the exploratory eye movement (EEM) test, were adopted to evaluate the fixation and scan path length. We compared the FA values of the bilateral STR and EEM parameters between the APS and healthy control groups. We investigated the correlation between bilateral STR and EEM parameters in the APS and healthy control groups.ResultsNEF, TESL, MESL, and the FA values of the left STR were significantly reduced in individuals with APS compared to healthy controls. The left STR FA value in the APS group was significantly positively correlated with the MESL (r = 0.567, p = 0.007). In addition, the right STR FA value of the APS group was significantly correlated with the TESL (r = 0.587, p = 0.005) and MESL (r = 0.756, p = 0.7×10-4).DiscussionThese results demonstrate that biological changes in the STR, which connects the thalamus and FEF, underlie abnormalities in fixation and scanning. Recently, aberrations in the thalamus–frontal connection have been shown to underlie the emergence of psychotic symptoms. STR impairment may be a part of the biological basis of APS in individuals with subthreshold psychotic symptoms.

Moyamoya disease (MMD) causes cerebral arterial stenosis and hemodynamic disturbance, the latter of which may disrupt glymphatic system activity, the waste clearance system. We evaluated 46 adult patients with MMD and 33 age- and sex-matched controls using diffusivity along the perivascular space (ALPS) measured with diffusion tensor imaging (ALPS index), which may partly reflect glymphatic system activity, and multishell diffusion MRI to generate freewater maps. Twenty-three patients were also evaluated via 15O-gas positron emission tomography (PET), and all patients underwent cognitive tests. Compared to controls, patients (38.4 (13.2) years old, 35 females) had lower ALPS indices in the left and right hemispheres (1.94 (0.27) vs. 1.65 (0.25) and 1.94 (0.22) vs. 1.65 (0.19), P < 0.001). While the right ALPS index showed no correlation, the left ALPS index was correlated with parenchymal freewater ( ρ = −0.47, P < 0.001); perfusion measured with PET (cerebral blood flow, ρ = 0.70, P < 0.001; mean transit time, ρ = −0.60, P = 0.003; and oxygen extraction fraction, ρ = −0.52, P = 0.003); and cognitive tests (trail making test part B for executive function; ρ = −0.37, P = 0.01). Adult patients with MMD may exhibit decreased glymphatic system activity, which is correlated with the degree of hemodynamic disturbance, increased interstitial freewater, and cognitive dysfunction, but further investigation is needed.

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

Verbal fluency is one of the most severely impaired components of cognitive function in schizophrenia and is also impaired in at-risk mental states (ARMSs) for psychosis. The aim of this study was to explore the markers of disease progression in subjects with ARMSs by comparing the association between the white matter integrity of the superior longitudinal fasciculus (SLF) and verbal fluency in subjects with ARMSs and healthy control (HC) subjects. The correlations of the fractional anisotropy (FA) values on diffusion tensor imaging (DTI) and the laterality index (LI) values of SLF branches I, II, and III with the verbal fluency performance were analyzed in right-handed subjects with ARMSs (ARMS group; n = 18) and HC subjects (HC group; n = 34) aged 18 to 40 years old. In the HC group compared with the ARMS group, the LI values suggested right lateralization of the SLF II and III. Letter fluency was significantly correlated with the LI of the SLF III in both the ARMS and HC groups. The regression coefficient (β) of this correlation was calculated using the least squares method and yielded a positive number (73.857) in the ARMS group and a negative number (−125.304) in the HC group. The association of the rightward asymmetry of the SLF III with the verbal fluency performance observed in the HC group appeared to be lost in the ARMS group, and this could serve as one of the markers of the pathological progression to psychosis in patients with schizophrenia.

PURPOSE:Here, we aimed to characterize the cortical and subcortical microstructural alterations in the brains of patients with amyotrophic lateral sclerosis (ALS). In particular, we compared these features between bulbar-onset ALS (b-ALS) and limb-onset ALS (l-ALS). METHODS:Diffusion MRI data (b = 0, 700, 2000 ms/mm2, 1.7-mm isotropic voxel) from 28 patients with ALS (9 b-ALS and 19 l-ALS) and 17 healthy control subjects (HCs) were analyzed. Diffusional kurtosis imaging (DKI) metrics were sampled at the mid-cortical and subcortical surfaces. We used permutation testing with a nonparametric combination of mean diffusivity (MD), fractional anisotropy (FA), and mean kurtosis (MK) to assess intergroup differences over the cerebrum. We also carried out an atlas-based analysis focusing on Brodmann Area 4 and 6 (primary motor and premotor areas) and investigated the correlation between MRI metrics and clinical parameters. RESULTS:At both the mid-cortical and subcortical surfaces, b-ALS was associated with significantly greater MD, smaller FA, and smaller MK in the motor and premotor areas than HC. In contrast, the patients with l-ALS showed relatively moderate differences relative to HCs. The ALS Functional Rating Scale-Revised bulbar subscore was significantly correlated with the diffusion metrics in Brodmann Area 4. CONCLUSION:The distribution of abnormalities over the cerebral hemispheres and the more severe microstructural alteration in b-ALS compared to l-ALS were in good agreement with findings from postmortem histology. Our results suggest the feasibility of surface-based DKI analyses for exploring brain microstructural pathologies in ALS. The observed differences between b-ALS and l-ALS and their correlations with functional bulbar impairment support the clinical relevance of DKI measurement in the cortical and juxtacortical regions of patients with ALS.

Introduction: Monoamine oxidase type B inhibitors, including selegiline, are established as anti-Parkinsonian Drugs. Inhibition of monoamine oxidase type B enzymes might suppress the inflammation because of inhibition to generate reactive oxygen species. However, its effect on brain microstructure remains unclear. The aim of this study is to elucidate white matter and substantia nigra (SN) microstructural differences between Patients with Parkinson's disease with and without selegiline treatment by two independently recruited cohorts. Methods: Diffusion tensor imaging and free water imaging indices of WM and SN were compared among 22/15 Patients with Parkinson's disease with selegiline (PDselegiline(+)), 33/23 Patients with Parkinson's disease without selegiline (PDselegiline(-)), and 25/20 controls, in the first/second cohorts. Two cohorts were analyzed with different MRI protocols. Results: Diffusion tensor imaging and free-water indices of major white matter tracts were significantly differed between the PDselegiline(-) and controls in both cohorts, although not between the PDselegiline(+) and controls except for restricted areas. Compared with the PDselegiline(+), free-water was significantly higher in the PDselegiline(-) in the inferior fronto-occipital fasciculus, superior longitudinal fasciculus, and superior and posterior corona radiata (first cohort) and the forceps major and splenium of the corpus callosum (second cohort). There were no significant differences in free -water of anterior or posterior substantia nigra between PDselegiline(+) and PDselegiline(-). Conclusions: Selegiline treatment might reduce the white matter microstructural abnormalities detected by freewater imaging in Parkinson's disease.