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Despite advancements, the prevalence of HIV-associated neurocognitive impairment remains at approximately 40%, attributed to factors like pre-cART (combination antiretroviral therapy) irreversible brain injury. People with HIV (PWH) treated with cART do not show significant neurocognitive changes over relatively short follow-up periods. However, quantitative neuroimaging may be able to detect ongoing subtle microstructural changes. In this study, we hypothesized that tensor-valued diffusion encoding metrics would provide greater sensitivity than conventional diffusion tensor imaging (DTI) metrics in detecting HIV-associated brain microstructural injury. We further hypothesized that tensor-valued metrics would exhibit stronger associations with blood markers of neuronal and glial injury, such as neurofilament light chain (NFL) and glial fibrillary acidic protein (GFAP), as well as with cognitive performance. Using MRI at 3T, 24 PWH and 31 healthy controls underwent cross-sectional examination. The results revealed significant variations in tensor-valued diffusion encoding metrics across white matter regions, with associations observed between these metrics, cognitive performance, NFL and GFAP. Moreover, a significant interaction between HIV status and imaging metrics in gray and white matter was observed, particularly impacting total cognitive scores. Of interest, DTI metrics were less likely to be associated with HIV status than tensor-valued diffusion metrics. These findings suggest that tensor-valued diffusion encoding metrics offer heightened sensitivity in detecting subtle changes associated with axonal injury in HIV infection. Longitudinal studies are needed to further evaluate responsiveness of tensor-valued diffusion b-tensor encoding metrics in the contest HIV-associate mild chronic neuroinflammation., Competing Interests: Competing interests: FS and MN are inventors on patents related to b-tensor encoding and declares financial conflicts of interest. None of the other authors have any competing financial or non-financial interests in relation to the work described in this manuscript. Approval for human experiments: All protocols were reviewed and approved by the Research Subjects Review Board (RSRB) at the University of Rochester Medical Center. All participants signed a written consent form. Consent to participate: All participants signed a written consent form., (© 2024. The Author(s).)

To determine diagnostic value of diffusion tensor imaging (DTI) in amyotrophic lateral sclerosis (ALS) patients and investigate the association between DTI and neurofilaments (NFs), including serum and cerebrospinal fluid (CSF) levels of neurofilament light chain (NFL) and phosphorylated neurofilament heavy chain (pNFH). Forty-three clinically diagnosed ALS patients and 32 control subjects without neurological disorders underwent routine MRI (magnetic resonance imaging) and DTI scans. DTI parameters (mean diffusivity [MD] and fractional anisotropy [FA]) at axial levels of internal capsules and cerebral peduncles along the corticospinal tract (CST) were measured. The study compared the differences of DTI parameters between ALS patients and controls using the Mann-Whitney U test. Diagnostic efficacy of each DTI metric was evaluated using the receiver operating characteristic (ROC) curve. NFs (NFL and pNFH levels in serum and CSF) were measured by enzyme-linked immunosorbent assay. Correlation analyses were conducted between DTI parameters and NFs. Capsule-MD and Peduncle-MD in ALS patients were higher than those in controls; whereas Capsule-FA and Peduncle-FA in ALS patients were lower than those in controls (all, p < 0.05). The area under curve (AUC) was 0.730 for Capsule-FA, 0.828 for Capsule-MD, 0.890 for Peduncle-FA, and 0.896 for Peduncle-MD. Capsule-FA was negatively correlated with CSF-NFL (r = - 0.813, p < 0.001), Serum-NFL (r = - 0.493, p = 0.001), CSF-pNFH (r = - 0.637, p < 0.001), and Serum-pNFH (r = - 0.672, p < 0.001); Peduncle-FA negatively with CSF-NFL (r = - 0.562, p < 0.001), CSF-pNFH (r = - 0.506, p = 0.001), and Serum-pNFH (r = - 0.488, p = 0.001); Peduncle-MD positively with CSF-NFL (r = 0.516, p < 0.001), CSF-pNFH (r = 0.494, p = 0.001). DTI had superior performance in identifying ALS patients and could serve as a reliable predictor. DTI parameters related to neurofilament markers, and Capsule-FA may become a robust surrogate biomarker indicating disease severity and progression rate for ALS patients., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Autism spectrum disorder (ASD) is characterized by social interaction deficits and repetitive behaviors. Recent research has linked that gut dysbiosis may contribute to ASD-like behaviors. However, the exact developmental time point at which gut microbiota alterations affect brain function and behavior in patients with ASD remains unclear. We hypothesized that ASD-related brain microstructural changes and gut dysbiosis induce metabolic dysregulation and proinflammatory responses, which collectively contribute to the social behavioral deficits observed in early childhood. We used an autistic-like rat model that was generated via prenatal valproic acid exposure. We analyzed brain microstructural changes using diffusion tensor imaging (DTI) and examined microbiota, blood, and fecal samples for inflammation biomarkers. The ASD model rats exhibited significant brain microstructural changes in the anterior cingulate cortex, hippocampus, striatum, and thalamus; reduced microbiota diversity (Prevotellaceae and Peptostreptococcaceae); and altered metabolic signatures. The shift in microbiota diversity and density observed at postnatal day (PND) 35, which is a critical developmental period, underscored the importance of early ASD interventions. We identified a unique metabolic signature in the ASD model, with elevated formate and reduced acetate and butyrate levels, indicating a dysregulation in short-chain fatty acid (SCFA) metabolism. Furthermore, increased astrocytic and microglial activation and elevated proinflammatory cytokines-interleukin-1 beta (IL-1β), interleukin-6 (IL-6), interferon-gamma (IFN-γ), and tumor necrosis factor-alpha (TNF-α)-were observed, indicating immune dysregulation. This study provided insights into the complex interplay between the brain and the gut, and indicated DTI metrics as potential imaging-based biomarkers in ASD, thus emphasizing the need for early childhood interventions., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Dynamic spasticity (DS) is a common complication post-spinal cord injury (SCI), marked by intermittent increases in muscle tone during postural transitions or movement. Despite its prevalence, high-quality research on DS incidence, risk factors, and underlying mechanisms in SCI patients remains limited. With the growing application of spinal cord stimulation (SCS) for spasticity control, the role of proprioception in DS development has garnered attention. Additionally, advances in diffusion tensor imaging (DTI) allow for the analysis of the reticulospinal tract's (RST) role in postural control among SCI patients. However, the impact of microstructural changes in RST and proprioception on DS following SCI remains unclear., Objective: To investigate the relationship between microstructural changes in the RST and proprioceptive circuits in SCI patients, exploring their association with DS and potential predictive factors that influence recovery., Methods: This is a 12-month prospective cohort study. The neurophysiological and global functional status of the participants will be assessed. Primary outcomes include DTI indices of RST and proprioception, and spasticity assessment. Secondary outcomes include auditory startle reflex (ASR), H-reflex, shear wave velocity (SWV), overall functional status including spinal cord independence measure, gait analysis, modified Barthel Index, and the 36-item short form health survey. Data will be collected at 1, 3, 6, and 12 months after enrolment. Matched healthy controls will be measured during the same period after recruitment., Discussion: This study is the first to explore the role of microstructural changes in the RST and proprioception in the assessment and prediction of DS following SCI. The findings aim to enhance theoretical understanding of SCS in spasticity management and to establish pre-treatment criteria for SCS interventions targeting motor function recovery in SCI., Trial Registration Number: ChiCTR2400090724., Competing Interests: Declarations Ethics approval and consent to participate This study will follow the ethical criteria for medical research involving human subjects of the Declaration of Helsinki and the ethical criteria for medical research of Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center) in the development of the study. This study was approved by the Ethics Review Committee of Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center) (No. YZ2024-073) and is registered in the Clinical Trial Registry (No. ChiCTR2400090724). All subjects will be required to agree to participate in the study and provide informed consent. Consent for publication All the detection personnel and subjects in the figures of this study fully understood the purpose of this research, agreed to appear in the figures of this study, and signed the Consent to Publish Declaration. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

The glymphatic system theory postulates that brain waste is removed through the cerebrospinal fluid (CSF) flow. According to this theory, CSF in the subarachnoid space (SAS) moves to the perivascular space around the penetrating arteries, flows into parenchyma to mix with interstitial fluid and brain waste, and then moves to the perivenous space to be flushed out of the brain. Despite the controversies about the glymphatic theory, it is clear that SAS plays a key role in waste clearance. For instance, the SAS around the middle cerebral artery is known to be highly involved in glymphatic influx. While diffusion tensor imaging has been used for studying the glymphatic system, there has been limited exploration of age-related changes in diffusion anisotropy within SAS and their regional variations. Given the narrow and heterogeneous morphology of SAS, the fractional anisotropy (FA) in diverse brain regions may be more relevant to glymphatic transport than mean diffusivity (MD). The goal of this study was to investigate FA in SAS to observe age-related changes across different brain regions and to interpret the results based on the glymphatic transport. We segmented SAS in the whole brain of 83 young adults and divided SAS into four cortical lobes. We demonstrated regional variations in FA and MD within SAS and an age-related decline in FA among young adults, indicating that diffusion within SAS becomes more isotropic with aging. These findings raise new questions about the factors influencing diffusion anisotropy within SAS, which are relevant to glymphatic transport., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 International Brain Research Organization (IBRO). Published by Elsevier Inc. All rights reserved.)

Introduction: Hypertensive intracerebral hemorrhage (HICH) is a condition associated with significant morbidity, mortality, and disability, particularly among the elderly population. The management of moderate thalamic-basal ganglia cerebral hemorrhage primarily relies on conservative approaches. Nevertheless, the rate of long-term disability remains high. In recent years, there has been significant advancement in minimally invasive surgery and diffusion tensor imaging techniques. Consequently, the utilization of Diffusion Tensor Imaging (DTI) technology in patients with cerebral haemorrhage allows for the identification of the haematoma's location in relation to the Corticospinal Tract (CST). This enables the development of precise puncture pathways that can be visualized, thereby avoiding any potential damage to the CST., Methods and Analysis: Diffusion Tensor Imaging (DTI) is a method used to assess the structural and physiological characteristics of biological tissue by examining the diffusion behavior of water molecules.In the central nervous system, limb paralysis will be inevitable if the corticospinal tract is damaged. By employing DTI imaging techniques on individuals, it becomes possible to visualize the spatial relationship between the hematoma and the CST. This approach allows avoidance of the CST during preoperative planning of the puncture path, thus reducing secondary injuries caused by the procedure. The primary objective of this study was to assess the ability of patients in the minimally invasive surgery group and the conservative group to perform activities of daily living after 6 months of treatment. In addition, secondary outcomes included assessment of hematoma resorption/clearance ratios, cytokine levels, complication rates, and therapeutic indexes at different treatment durations, as well as long-term safety and efficacy at 2-3 years of follow-up. Furthermore, subgroup analysis, and sensitivity analysis were conducted to further analyze the data. Logistic single-variate and multivariate regression analyses were applied to understand the adverse factors affecting prognosis., Ethics and Dissemination: The clinical study was reviewed and approved by the Ethics Committee of the First People's Hospital of Yibin. The ethical number is: 2023 Review (64)., Registration Number: This protocol is registered in the Prospective Registry of Chinese Clinical Trial Registries (PROCCTR). The full date of first registration is 28/12/2023. The registration number for PROCCTR is ChiCTR2300079252., (© 2024. The Author(s).)

Background and Purpose: Preoperative assessment of meningioma consistency is beneficial for optimizing surgical strategy and prognosis of patients. We aim to develop a noninvasive prediction model for meningioma consistency utilizing MR elastography and DTI., Materials and Methods: Ninety-four patients (52 ± 22 years old, 69 women, 25 men) diagnosed with meningioma were recruited in the study. Each patient underwent preoperative T1WI, T2WI, DTI, and MR elastography. Combined MR elastography-DTI model was developed based on multiple logistic regression. Intraoperative tumor descriptions served as clinical criteria for evaluating meningioma consistency. The diagnostic efficacy in determining meningioma consistency was evaluated by using a receiver operating characteristic curve. Further validation was conducted in 27 stereotactic biopsies by using indentation tests and underlying mechanism was investigated by histologic analysis., Results: Among all the imaging modalities, MR elastography demonstrated the highest efficacy with the shear modulus magnitude (|G*|) achieving an area under the curve (AUC) of 0.81 (95% CI: 0.699-0.929). When combined with DTI, the diagnostic accuracy further increased (AUC: 0.88, 95% CI: 0.784-0.971), surpassing any technique alone. Indentation measurement based on stereotactic biopsies further demonstrated that the MR elastography-DTI model was suitable for predicting intratumor consistency. Histologic analysis suggested that meningioma consistency may be correlated with tumor cell density and fibrous content., Conclusions: The MR elastography-DTI combined model is effective in noninvasive prediction of meningioma consistency., (© 2024 by American Journal of Neuroradiology.)

Background: New daily persistent headache (NDPH) is a rare primary headache disorder characterized by daily and persistent sudden onset headaches. Specific abnormalities in gray matter and white matter structure are associated with pain, but have not been well studied in NDPH. The objective of this work is to explore the fiber tracts and structural connectivity, which can help reveal unique gray and white matter structural abnormalities in NDPH., Methods: The regional radiomics similarity networks were calculated from T1 weighted (T1w) MRI to depict the gray matter structure. The fiber connectivity matrices weighted by diffusion metrics like fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) were built, meanwhile the fiber tracts were segmented by anatomically-guided superficial fiber segmentation (Anat-SFSeg) method to explore the white matter structure from diffusion MRI. The considerable different neuroimaging features between NDPH and healthy controls (HC) were extracted from the connectivity and tract-based analyses. Finally, decision tree regression was used to predict the clinical scores (i.e. pain intensity) from the above neuroimaging features., Results: T1w and diffusion MRI data were available in 51 participants after quality control: 22 patients with NDPH and 29 HCs. Significantly decreased morphological similarity was found between the right superior frontal gyrus and right hippocampus. The superficial white matter (SWM) showed significantly decreased FA in fiber tracts including the right superficial-frontal, left superficial-occipital, bilateral superficial-occipital-temporal (Sup-OT) and right superficial-temporal, meanwhile significant increased RD was found in the left Sup-OT. For the fiber connectivity, NDPH showed significantly decreased FA in the bilateral basal ganglion and temporal lobe, increased MD in the right frontal lobe, and increased RD in the right frontal lobe and left temporal-occipital lobe. Clinical scores could be predicted dominantly by the above significantly different neuroimaging features through decision tree regression., Conclusions: Our research indicates the structural abnormalities of SWM and the neural pathways projected between regions like right hippocampus and left caudate nucleus, along with morphological similarity changes between the right superior frontal gyrus and right hippocampus, constitute the pathological features of NDPH. The decision tree regression demonstrates correlations between these structural changes and clinical scores., (© 2024. The Author(s).)

Background and Purpose: Trigeminal neuralgia (TN) is a severe chronic pain condition, typically affecting patients over 50-year-old, caused by the compression of the nerve at the root entry zone (REZ) by blood vessels. While the diagnosis is clinical, advanced imaging like diffusion tensor imaging (DTI) is crucial to identify underlying causes and assessing nerve damage. DTI may help develop neuroimaging markers to improve understanding of TN and predict surgical outcomes. The goal of the present systematic review is to evaluate the effectiveness of DTI and tractography in order to better assess treatment planning and outcome prediction through the analysis of trigeminal nerve alterations., Methods: The authors conducted a systematic review and meta-analysis of the literature to compare radiological parameters identified in pre- and post-operative MRI with DTI sequences, including fractional anisotropy (FA), quantity of anisotropy (QA), radial diffusivity (RD), and to correlate these findings with post-operative clinical outcomes. A comprehensive search of the PubMed and Scopus databases was carried out for studies published between April 2010 and January 2024., Results: This review included 11 studies and 603 patients. Of the 363 patients with trigeminal neuralgia (TN), 193 underwent microvascular decompression (MVD), with 72.5% showing clinical improvement and 27.5% not improving, possibly due to chronic nerve damage. Four studies assessed radiological parameters before and after MVD, while two focused only on post-MVD data. The mean fractional anisotropy (FA) in affected nerves increased from 0.328 before MVD to 0.382 afterward. Five studies did not report postoperative outcomes, just comparing radiological parameters in TN patients versus healthy controls., Conclusions: Recent studies show that MRI-DTI parameters, including FA, RD, and QA, are useful for diagnosing trigeminal neuralgia and predicting treatment outcomes. Lower FA and higher RD values indicate better results after surgery. More research is mandatory to guide treatment decisions and enhance patients' care., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In recent years, the glymphatic system has received increasing attention due to its possible implications in biological mechanisms associated with neurodegeneration. In the field of human brain mapping, this led to the development of diffusion tensor image analysis along the perivascular space (DTI-ALPS) index. While this index has been repeatedly used to investigate possible differences between neurodegenerative disorders and healthy controls, a comprehensive evaluation of its stability across multiple measurements and different disorders is still missing. In this study, we perform a Bayesian meta-analysis aiming to assess the consistency of the DTI-ALPS results previously reported for 12 studies on Parkinson's disease and 11 studies on Alzheimer's disease. We also evaluated if the measured value of the DTI-ALPS index can quantitatively inform the diagnostic process, allowing disambiguation between these two disorders. Our results, expressed in terms of Bayes' Factor values, confirmed that the DTI-ALPS index is consistent in measuring the different functioning of the glymphatic system between healthy subjects and patients for both Parkinson's disease (Log10(BF10) = 30) and Alzheimer's disease (Log10(BF10) = 10). Moreover, we showed that the DTI-ALPS can be used to compare these two disorders directly, therefore providing a first proof of concept supporting the reliability of taking into consideration this neuroimaging measurement in the diagnostic process. Our study underscores the potential of the DTI-ALPS index in advancing our understanding of neurodegenerative pathologies and enhancing clinical diagnostics., (© 2024. The Author(s).)

The Adolescent Brain and Cognitive Development (ABCD) project is the largest study of adolescent brain development. ABCD longitudinally tracks 11,868 participants aged 9-10 years from 21 sites using standardized protocols for multi-site MRI data collection and analysis. While the multi-site and multi-scanner study design enhances the robustness and generalizability of analysis results, it may also introduce nonbiological variances including scanner-related variations, subject motion, and deviations from protocols. ABCD imaging data were collected biennially within a period of ongoing maturation in cortical thickness and integrity of cerebral white matter. These changes can bias the classical test-retest methodologies, such as intraclass correlation coefficients (ICC). We developed a site-wise adaptive ICC (AICC) to evaluate the reliability of imaging-derived phenotypes while accounting for ongoing brain development. AICC iteratively estimates the population-level age-related brain development trajectory using a weighted mixed model and updates age-corrected site-wise reliability until convergence. We evaluated the test-retest reliability of regional fractional anisotropy (FA) measures from diffusion tensor imaging and cortical thickness (CT) from structural MRI data for each site. The mean AICC for 20 FA tracts across sites was 0.61 ± 0.19, lower than the mean AICC for CT in 34 regions across sites, 0.76 ± 0.12. Remarkably, sites using Siemens scanners consistently showed significantly higher AICC values compared with those using GE/Philips scanners for both FA (AICC = 0.71 ± 0.12 vs. 0.46 ± 0.17, p < 0.001) and CT (AICC = 0.80 ± 0.10 vs. 0.69 ± 0.11, p < 0.001). These findings demonstrate site-and-scanner related variations in data quality and underscore the necessity for meticulous data curation in subsequent association analyses., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Purpose: To evaluate the diagnostic accuracy of diffusion tensor imaging (DTI)-derived metrics mean diffusivity (MD) and fractional anisotropy (FA) in differentiating glioma recurrence from pseudoprogression., Methods: The Cochrane Library, Scopus, PubMed, and the Web of Science were systematically searched. Study selection and data extraction were done by two investigators independently. The quality assessment of diagnostic accuracy studies was applied to evaluate the quality of the included studies. Combined sensitivity (SEN) and specificity (SPE) and the area under the summary receiver operating characteristic curve (SROC) with the 95% confidence interval (CI) were calculated., Results: Seven high-quality studies involving 246 patients were included. Quantitative synthesis of studies showed that the pooled SEN and SPE for MD were 0.81 (95% CI 0.70-0.88) and 0.82 (95% CI 0.70-0.90), respectively, and the value of the area under the SROC curve was 0.88 (95% CI 0.85-0.91). The pooled SEN and SPE for FA were 0.74 (95% CI 0.65-0.82) and 0.79 (95% CI 0.66-0.88), respectively, and the value of the area under the SROC curve was 0.84 (95% CI 0.80-0.87)., Conclusions: This meta-analysis showed that both MD and FA have a high diagnostic accuracy in differentiating glioma recurrence from pseudoprogression., Registration: PROSPERO protocol: CRD42024501146.

Background: Quantitative magnetic resonance imaging (MRI) metrics could be used in personalized medicine to assess individuals against normative distributions. Conventional Zscore analysis is inadequate in the presence of non-Gaussian distributions. Therefore, if quantitative MRI metrics deviate from normality, an alternative is needed., Purpose: To confirm non-Gaussianity of diffusion MRI (dMRI) metrics on a publicly available dataset, and to propose a novel percentile-based method, "Pscore" to address this issue., Study Type: Retrospective cohort., Population: Nine hundred and sixty-one healthy young adults (age: 22-35 years, females: 53%) from the Human Connectome Project., Field Strength/sequence: 3-T, spin-echo diffusion echo-planar imaging, T1-weighted: MPRAGE., Assessment: The dMRI data were preprocessed using the TORTOISE pipeline. Forty-eight regions of interest (ROIs) from the JHU atlas were redrawn on a study-specific diffusion tensor (DT) template and average values were computed from various DT and mean apparent propagator (MAP) metrics. For each ROI, percentile ranks across participants were computed to generate "Pscores"-which normalized the difference between the median and a participant's value with the corresponding difference between the median and the 5th/95th percentile values., Statistical Tests: ROI-wise distributions were assessed using log transformations, Zscore, and the "Pscore" methods. The percentages of extreme values above-95th and below-5th percentile boundaries (PEV >95 (%), PEV <5 (%)) were also assessed in the overall white matter. Bootstrapping was performed to test the reliability of Pscores in small samples (N = 100) using 100 iterations., Results: The dMRI metric distributions were systematically non-Gaussian, including positively skewed (eg, mean and radial diffusivity) and negatively skewed (eg, fractional and propagator anisotropy) metrics. This resulted in unbalanced tails in Zscore distributions (PEV >95  ≠ 5%, PEV <5  ≠ 5%) whereas "Pscore" distributions were symmetric and balanced (PEV >95  = PEV <5  = 5%); even for small bootstrapped samples (average PEV > 95 ¯ = PEV < 5 ¯ = 5 ± 0 % [SD])., Data Conclusion: The inherent skewness observed for dMRI metrics may preclude the use of conventional Zscore analysis. The proposed "Pscore" method may help estimating individual deviations more accurately in skewed normative data, even from small datasets., Level of Evidence: 1 TECHNICAL EFFICACY: Stage 1., (Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

White matter (WM) development has been studied extensively, but most studies used cross-sectional data, and to the best of our knowledge, none of them considered the possible effects of biological (vs. chronological) age. Therefore, we conducted a longitudinal multimodal study of WM development and studied changes in fractional anisotropy (FA) in the different WM tracts and their relationship with cortical thickness-based measures of brain aging in young adulthood. A total of 105 participants from the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) prenatal birth cohort underwent magnetic resonance imaging (MRI) at the age of 23-24, and the age of 28-30 years. At both time points, FA in the different WM tracts was extracted using the JHU atlas, and brain age gap estimate (BrainAGE) was calculated using the Neuroanatomical Age Prediction using R (NAPR) model based on cortical thickness maps. Changes in FA and the speed of cortical brain aging were calculated as the difference between the respective variables in the late vs. early 20s. We demonstrated tract-specific increases as well as decreases in FA, which indicate that the WM microstructure continues to develop in the third decade of life. Moreover, the significant interaction between the speed of cortical brain aging, tract, and sex on mean FA revealed that a greater speed of cortical brain aging in young adulthood predicted greater decreases in FA in the bilateral cingulum and left superior longitudinal fasciculus in young adult men. Overall, these changes in FA in the WM tracts in young adulthood point out the protracted development of WM microstructure, particularly in men., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Alpha-synuclein deposits in the brain have been suspected to cause Parkinson's disease and dementia with Lewy bodies (DLB). It was recently revealed that the glymphatic system is largely responsible for the removal of alpha-synuclein. We investigated changes in the glymphatic system's activity by determining the DTI‑ALPS (diffusion tensor image analysis along the perivascular space) index in DLB patients. Twenty-six patients with DLB and 43 healthy subjects underwent diffusion tensor imaging (DTI) scanning at our hospital during the period April 2013 to March 2023. We retrospectively computed each subject's DTI‑ALPS index to evaluate his/her glymphatic-system activity and then analyzed the relationships between the subjects' DTI‑ALPS index data and their DLB neuroimaging biomarker values. A significant reduction of the DTI‑ALPS index was observed in the patients with DLB compared to the healthy subjects. Significant positive correlations were also detected in the DLB group between the DTI‑ALPS index and the regional gray matter volume in the left insula and between the index and the specific binding ratio of 123 I-N-ω-fluoropropyl-2β-carboxymethoxy-3β-(4-iodophenyl)nortropane ([ 123 I]-FP-CIT). These results indicate that (i) the DTI‑ALPS index is a good biomarker of the progression of DLB, and (ii) this index might be effective to distinguish DLB from other neurocognitive disorders., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In the entorhinal cortex (EC), attempts have been made to identify the human homologue regions of the medial (MEC) and lateral (LEC) subregions using either functional magnetic resonance imaging (fMRI) or diffusion tensor imaging (DTI). However, there are still discrepancies between entorhinal subdivisions depending on the choice of connectivity seed regions and the imaging modality used. While DTI can be used to follow the white matter tracts of the brain, fMRI can identify functionally connected brain regions. In this study, we used both DTI and resting-state fMRI in 103 healthy adults to investigate both structural and functional connectivity between the EC and associated cortical brain regions. Differential connectivity with these regions was then used to predict the locations of the human homologues of MEC and LEC. Our results from combining DTI and fMRI support a subdivision into posteromedial (pmEC) and anterolateral (alEC) EC and reveal a confined border between the pmEC and alEC. Furthermore, the EC subregions obtained by either imaging modality showed similar distinct whole-brain connectivity profiles. Optimizing the delineation of the human homologues of MEC and LEC with a combined, cross-validated DTI-fMRI approach allows to define a likely border between the two subdivisions and has implications for both cognitive and translational neuroscience research., (© 2024 The Author(s). Hippocampus published by Wiley Periodicals LLC.)

Objectives: Based on the literature, tensor-based morphometry (TBM) parameters were related to neurocognitive functions such as memory, learning, language ability, and executive functions. The present study aims to evaluate the associations between TBM indices with executive functions, memory, language, and visuospatial abilities and the value of TBM in the clinical diagnosis of Alzheimer's disease (AD) among individuals with Alzheimer's disease continuum and mild cognitive impairment (MCI) from Alzheimer's Disease Neuroimaging Initiative (ADNI)., Methods: The authors used ADNI-memory (ADNI-MEM), ADNI-executive functions (ADNI-EF), ADNI-language (ADNI-LAN), and ADNI-visuospatial (ADNI-VS) composite scores. TBM parameters, including measure 1, which represents average within a statistically defined region-of-interest inside the temporal lobes and measure 2 which indicates average within an anatomically defined region-of-interest including bilateral temporal lobes were utilized in the current study. Statistical analysis was performed using IBM SPSS Statistics version 26, and Pearson's correlation, Bonferroni's correction, and multiple linear regression were utilized for data analysis. P <0.05 was considered statistically significant., Results: After screening 800 participants, 270 (151 men, 119 women) were selected for a study with TBM scores and cognition-related assessments at 6, 12, and 24 months. Groups included healthy controls (n=53), MCI (n=158), and Alzheimer's Disease (AD) (n=59). TBM indices correlated with cognitive scores in MCI and AD groups but not healthy controls. Changes in TBM indices and cognitive scores were significantly correlated in MCI and AD groups over 24 months. TBM indices were weak predictors of cognitive decline at all time points., Conclusions: TBM can help physicians diagnose MCI and AD early. However, TBM could not strongly predict cognitive functions decline at all time points., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neurons' degeneration of the substantia nigra, presenting with motor and non-motor symptoms. We hypothesized that altered diffusion metrics are associated with clinical symptoms in de novo PD patients., Methods: Fractional Anisotropy (FA) and Mean (MD), Axial (AD), and Radial Diffusivity (RD) were assessed in 55 de novo PD patients (58.62 ± 9.85 years, 37 men) and 55 age-matched healthy controls (59.92 ± 11.25 years, 34 men). Diffusion-weighted images and clinical variables were collected from the Parkinson's Progression Markers Initiative study. Tract-based spatial statistics were used to identify white matter (WM) changes, and fiber tracts were localized using the JHU-WM tractography atlas. Motor and non-motor symptoms were evaluated in patients., Results: We observed higher FA values and lower RD values in patients than controls in various fiber tracts (p-TFCE < 0.05). No significant MD or AD difference was observed between groups. Diffusion metrics of several regions significantly correlated with non-motor (state and trait anxiety and daytime sleepiness) and axial motor symptoms in the de novo PD group. No correlations were observed between diffusion metrics and other clinical symptoms evaluated., Conclusion: Our findings suggest microstructural changes in de novo PD fiber tracts; however, limited associations with clinical symptoms reveal the complexity of PD pathology. They may contribute to understanding the neurobiological changes underlying PD and have implications for developing targeted interventions. However, further longitudinal research with larger cohorts and consideration of confounding factors are necessary to elucidate the underlying mechanisms of these diffusion alterations in de novo PD., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Non-human primates are extensively used in neuroscience research as models of the human brain, with the rhesus macaque being a prominent example. We have previously introduced a set of tractography protocols (XTRACT) for reconstructing 42 corresponding white matter (WM) bundles in the human and the macaque brain and have shown cross-species comparisons using such bundles as WM landmarks. Our original XTRACT protocols were developed using the F99 macaque brain template. However, additional macaque template brains are becoming increasingly common. Here, we generalise the XTRACT tractography protocol definitions across five macaque brain templates, including the F99, D99, INIA, Yerkes and NMT. We demonstrate equivalence of such protocols in two ways: (a) Firstly by comparing the bodies of the tracts derived using protocols defined across the different templates considered, (b) Secondly by comparing the projection patterns of the reconstructed tracts across the different templates in two cross-species (human-macaque) comparison tasks. The results confirm similarity of all predictions regardless of the macaque brain template used, providing direct evidence for the generalisability of these tractography protocols across the five considered templates., (© 2024. The Author(s).)

Background: Lumbosacral radicular pain diagnosis remains challenging. Diffusion tensor imaging (DTI) and diffusion weighted imaging (DWI) have potential to quantitatively evaluate symptomatic nerve root, which may facilitate diagnosis., Purpose: To determine the ability of DTI and DWI metrics, namely fractional anisotropy (FA) and apparent diffusion coefficient (ADC), to discriminate between healthy and symptomatic lumbosacral nerve roots, to evaluate the association between FA and ADC values and patient symptoms, and to determine FA and ADC reliability., Study Type: Systematic review., Subjects: Eight hundred twelve patients with radicular pain with or without radiculopathy caused by musculoskeletal-related compression or inflammation of a single, unilateral lumbosacral nerve root and 244 healthy controls from 29 studies., Field Strength/sequence: Diffusion weighted echo planar imaging sequence at 1.5 T or 3 T., Assessment: An extensive systematic review of the literature was conducted in Embase, Scopus, and Medline databases. FA and ADC values in symptomatic and contralateral lumbosacral nerve roots were extracted and summarized, together with intra- and inter-rater agreements. Where available, associations between DWI or DTI parameters and patient symptoms or symptom duration were extracted., Statistical Tests: The main results of the included studies are summarized. No additional statistical analyses were performed., Results: The DTI studies systematically found significant differences in FA values between the symptomatic and contralateral lumbosacral nerve root of patients suffering from radicular pain with or without radiculopathy. In contrast, identification of the symptomatic nerve root with ADC values was inconsistent for both DTI and DWI studies. FA values were moderately to strongly correlated with several symptoms (eg, disability, nerve dysfunction, and symptom duration). The inter- and intra-rater reliability of DTI parameters were moderate to excellent. The methodological quality of included studies was very heterogeneous., Data Conclusion: This systematic review showed that DTI was a reliable and discriminative imaging technique for the assessment of symptomatic lumbosacral nerve root, which more consistently identified the symptomatic nerve root than DWI. Further studies of high quality are needed to confirm these results., Evidence Level: N/A TECHNICAL EFFICACY: Stage 2., (© 2024 International Society for Magnetic Resonance in Medicine.)

Diffusion tensor imaging (DTI) has emerged as a promising neuroimaging tool for detecting blast-induced mild traumatic brain injury (bmTBI). However, lack of refined acute-phase monitoring and reliable imaging biomarkers hindered its clinical application in early diagnosis of bmTBI, leading to potential long-term disability of patients. In this study, we used DTI in a rat model of bmTBI generated by exposing to single lateral blast waves (151.16 and 349.75 kPa, lasting 47.48 ms) released in a confined bioshock tube, to investigate whole-brain DTI changes at 1, 3, and 7 days after injury. Combined assessment of immunohistochemical analysis, transmission electron microscopy, and behavioral readouts allowed for linking DTI changes to synchronous cellular damages and identifying stable imaging biomarkers. The corpus callosum (CC) and brainstem were identified as predominantly affected regions, in which reduced fractional anisotropy (FA) was detected as early as the first day after injury, with a maximum decline occurring at 3 days post-injury before returning to near normal levels by 7 days. Axial diffusivity (AD) values within the CC and brainstem also significantly reduced at 3 days post-injury. In contrast, the radial diffusivity (RD) in the CC showed acute elevation, peaking at 3 days after injury before normalizing by the 7-day time point. Damages to nerve fibers, including demyelination and axonal degeneration, progressed in lines with changes in DTI parameters, supporting a real-time macroscopic reflection of microscopic neuronal fiber injury by DTI. The most sensitive biomarker was identified as a decrease in FA, AD, and an increase in RD within the CC on the third day after injury, supporting the diagnostic utility of DTI in cases of bmTBI in the acute phase.

Quantitative muscle magnetic resonance imaging (qMRI) is a valuable methodology for assessing muscular injuries and neuromuscular disorders. Notably, muscle diffusion tensor imaging (DTI) gives insights into muscle microstructural and macrostructural characteristics. However, the long-term reproducibility and robustness of these measurements remain relatively unexplored. The purpose of this prospective longitudinal cohort study was to assess the long-term robustness and range of variation of qMRI parameters, especially DTI metrics, in the lower extremity muscles of healthy controls under real-life conditions. Twelve volunteers (seven females, age 44.1 ± 12.1 years, body mass index 23.3 ± 2.0 kg/m 2 ) underwent five leg muscle MRI sessions every 20 ± 4 weeks over a total period of 1.5 years. A multiecho gradient-echo Dixon-based sequence, a multiecho spin-echo T2-mapping sequence, and a spin-echo echo planar imaging diffusion-weighted sequence were acquired bilaterally with a Philips 3-T Achieva MR System using a 16-channel torso coil. Fifteen leg muscles were segmented in both lower extremities. qMRI parameters, including fat fraction (FF), water T2 relaxation time, and the diffusion metrics fractional anisotropy (FA) and mean diffusivity (MD), were evaluated. Coefficients of variance (wsCV) and intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of qMRI parameters. The standard error of measurement (SEM) and the minimal detectable change (MDC) were calculated to determine the range of variation. All tests were applied to all muscles and, subsequently, to each muscle separately. wsCV showed good reproducibility (≤ 10%) for all qMRI parameters in all muscles. The ICCs revealed excellent agreement between time points (FF = 0.980, water T2 = 0.941, FA = 0.952, MD = 0.948). Random measurement errors assessed by SEM and the MDC were low (< 12%). In conclusion, in this study, we showed that qMRI parameters in healthy volunteers living normal lives are stable over 18 months, thereby defining a benchmark for the expected range of variation over time., (© 2024 The Author(s). NMR in Biomedicine published by John Wiley & Sons Ltd.)

Purpose: To fully characterize the orientation dependence of magnetization transfer (MT) and inhomogeneous MT (ihMT) measures in the whole white matter (WM), for both single-fiber and crossing-fiber voxels., Methods: A characterization method was developed using the fiber orientation obtained from diffusion MRI (dMRI) with diffusion tensor imaging (DTI) and constrained spherical deconvolution. This allowed for characterization of the orientation dependence of measures in all of WM, regardless of the number of fiber orientation in a voxel. Furthermore, the orientation dependence inside 31 different WM bundles was characterized to evaluate the homogeneity of the effect. Variation of the results within and between-subject was assessed from a 12-subject dataset., Results: Previous results for single-fiber voxels were reproduced and a novel characterization was produced in voxels of crossing fibers, which seems to follow trends consistent with single-fiber results. Heterogeneity of the orientation dependence across bundles was observed, but homogeneity within similar bundles was also highlighted. Differences in behavior between MT and ihMT measures, as well as the ratio and saturation versions of these, were noted., Conclusion: Orientation dependence characterization was proven possible over the entirety of WM. The vast range of effects and subtleties of the orientation dependence on MT measures showed the need for, but also the challenges of, a correction method., (© 2024 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background Context: Extreme lateral interbody fusion (XLIF) has been established as an effective treatment for degenerative disorders of the lumbar spine. Nevertheless, there is a potential risk of lumbar plexus damage associated with XLIF, especially during surgeries at the L4-5 segment. Diffusion tensor imaging (DTI) evaluates the directional diffusion of water molecules in tissue, providing a more intricate depiction of internal tissue microstructure compared to conventional MRI techniques. The capability of DTI sequences to elucidate the 3-dimensional interplay between lumbar nerve pathways and adjacent musculoskeletal structures, potentially reducing the incidence of nerve injury complications related to XLIF, remains to be established., Purpose: This study evaluates the effectiveness of preoperative DTI in reducing neurological complications after XLIF surgeries at the L4-5 level, focusing on the interaction between lumbar nerves and the psoas major muscle., Study Design: Retrospective case-control study., Patient Sample: The study included 128 patients undergoing XLIF surgery for degenerative disorders at the L4-5 segment: 68 in the traditional group and 62 in the DTI group., Outcome Measures: The study assessed Visual Analogue Scale (VAS) and Oswestry Disability Index (ODI) scores, along with complication rates. It also documented psoas major muscle morphology and its correlation with nerve pathways., Methods: A retrospective analysis of 128 patients undergoing XLIF surgery for degenerative disorders at the L4-5 segment between February 2020 and August 2022 was conducted. The cohort was divided into a traditional group (68 patients) receiving presurgery MRI scans to identify surgical entry points at the intervertebral space midpoint (Zones II-III junction) and a DTI group (62 patients) who additionally underwent preoperative DTI to customize entry points. The study evaluated VAS and ODI scores, complication rates, psoas major muscle morphology, and its interaction with nerve pathways., Results: The traditional group uniformly chose the Zone II-III junction for entry. In contrast, the DTI group's entry points varied. Postoperative follow-up revealed significant improvements in VAS and ODI scores in both groups. However, the DTI group experienced fewer immediate postoperative complications such as thigh pain, numbness, and motor disturbances. The study also noted a ventral shift in nerve positioning in patients with elevated psoas muscles., Conclusions: Preoperative DTI effectively maps the relationship between the psoas major muscle and lumbar nerves. Tailoring surgical entry points based on DTI results significantly reduces the risk of nerve damage in XLIF surgeries. The study underscores the importance of recognizing variability in lumbar nerve pathways due to differing psoas muscle morphologies, highlighting a higher risk of nerve injury in patients with elevated psoas muscles during XLIF procedures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: The alternation of brain white matter (WM) network has been studied in adult spinal cord injury (SCI) patients. However, the WM network alterations in pediatric SCI patients remain unclear., Purpose: To evaluate WM network changes and their functional impact in children with thoracolumbar SCI (TSCI)., Study Type: Prospective., Subjects: Thirty-five pediatric patients with TSCI (8.94 ± 1.86 years, 8/27 males/females) and 34 age- and gender-matched healthy controls (HCs) participated in this study., Field Strength/sequence: 3.0 T/DTI imaging using spin-echo echo-planar and T1-weighted imaging using 3D T1-weighted magnetization-prepared rapid gradient-echo sequence., Assessment: Pediatric SCI patients were evaluated for motor and sensory scores, injury level, time since injury, and age at injury. The WM network was constructed using a continuous tracing method, resulting in a 90 × 90 matrix. The global and regional metrics were obtained to investigate the alterations of the WM structural network. topology., Statistical Tests: Two-sample independent t-tests, chi-squared test, Mann-Whitney U-test, and Spearman correlation. Statistical significance was set at P < 0.05., Results: Compared with HCs, pediatric TSCI patients displayed decreased shortest path length (L p  = 1.080 ± 0.130) and normalized L p (λ = 5.020 ± 0.363), and increased global efficiency (E g  = 0.200 ± 0.015). Notably, these patients also demonstrated heightened regional properties in the orbitofrontal cortex, limbic system, default mode network, and several audio-visual-related regions. Moreover, the λ and L p values negatively correlated with sensory scores. Conversely, nodal efficiency values in the right calcarine fissure and surrounding cortex positively correlated with sensory scores. The age at injury positively correlated with node degree in the left parahippocampal gyrus and nodal efficiency in the right posterior cingulate gyrus., Data Conclusion: Reorganization of the WM networks in pediatric SCI patients is indicated by increased global and nodal efficiency, which may provide promising neuroimaging biomarkers for functional assessment of pediatric SCI., Evidence Level: 2 TECHNICAL EFFICACY: Stage 5., (© 2024 International Society for Magnetic Resonance in Medicine.)

Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia. Genetic risk loci for white matter hyperintensities (WMH), the most common MRI-marker of cSVD in older age, were recently shown to be significantly associated with white matter (WM) microstructure on diffusion tensor imaging (signal-based) in young adults. To provide new insights into these early changes in WM microstructure and their relation with cSVD, we sought to explore the genetic underpinnings of cutting-edge tissue-based diffusion imaging markers across the adult lifespan. We conducted a genome-wide association study of neurite orientation dispersion and density imaging (NODDI) markers in young adults (i-Share study: N = 1 758, (mean[range]) 22.1[18-35] years), with follow-up in young middle-aged (Rhineland Study: N = 714, 35.2[30-40] years) and late middle-aged to older individuals (UK Biobank: N = 33 224, 64.3[45-82] years). We identified 21 loci associated with NODDI markers across brain regions in young adults. The most robust association, replicated in both follow-up cohorts, was with Neurite Density Index (NDI) at chr5q14.3, a known WMH locus in VCAN. Two additional loci were replicated in UK Biobank, at chr17q21.2 with NDI, and chr19q13.12 with Orientation Dispersion Index (ODI). Transcriptome-wide association studies showed associations of STAT3 expression in arterial and adipose tissue (chr17q21.2) with NDI, and of several genes at chr19q13.12 with ODI. Genetic susceptibility to larger WMH volume, but not to vascular risk factors, was significantly associated with decreased NDI in young adults, especially in regions known to harbor WMH in older age. Individually, seven of 25 known WMH risk loci were associated with NDI in young adults. In conclusion, we identified multiple novel genetic risk loci associated with NODDI markers, particularly NDI, in early adulthood. These point to possible early-life mechanisms underlying cSVD and to processes involving remyelination, neurodevelopment and neurodegeneration, with a potential for novel approaches to prevention., (© 2024. The Author(s).)

Background: Tractography based on diffusion MRI (dMRI) is a useful tool to study white matter of the developing brain. However, its application in fetal brains is limited due to motion artifacts and low resolution of in utero dMRI, leading to reduced reliability, which was scarcely investigated in previous studies., Purpose: To identify reliably traceable fibers in fetal brains and assess whether reproducibility varies with gestational age (GA) and varies between brain regions., Study Type: Prospective cohort study., Subjects: A total of 44 healthy fetuses with GAs between 25 and 37 (31 ± 6)., Field Strength/sequence: 3-T, diffusion-weighted echo-planar imaging sequence (2-5 repeated dMRI scans within the same session per subject)., Assessment: We fitted dMRI with constrained spherical deconvolution model and conducted tractography on eight fibers. We extracted volume, fractional anisotropy, and fiber count for each fiber and assessed the reproducibility of these metrics between repeated scans within each subject. Data were divided into two age-based subgroups (≤30 weeks, N = 28, and >30 weeks, N = 16) for further tests., Statistical Tests: The reproducibility were compared between fibers by analysis of variance and two-sample t tests. Multiple comparisons were corrected by the false discovery rate (5% was accepted)., Results: The reproducibility of the anterior thalamic radiation, inferior longitudinal fasciculus (ILF), genu of the corpus callosum (GCC), and body of the corpus callosum (BCC) significantly decreased with advancing GA (correlation coefficient = 0.525-0.823), as confirmed by group comparisons between fetuses in early GA (≤30 weeks) and late GA (>30 weeks) groups. Corticospinal tract, inferior fronto-occipital fasciculus, and GCC showed high reproducibility for fiber count (weighted dice average = 0.846 vs. 0.814), while BCC and ILF exhibited the lowest reproducibility in both age groups., Data Conclusion: The study indicates that the reliability of fetal brain tractography depends on GA and varies among different fibers., Level of Evidence: 2 TECHNICAL EFFICACY: Stage 2., (© 2024 International Society for Magnetic Resonance in Medicine.)

Objectives: To explore whether differences in diffusional kurtosis imaging (DKI) between therapy-naïve high-grade gliomas (HGGs) and low-grade gliomas (LGGs) are related to the cellularity and/or the nuclear-to-cytoplasmic (N/C) ratio., Methods: We analyzed 44 and 40 diffuse glioma samples that were pathologically confirmed as HGGs and IDH1-mutant LGGs, respectively. The DKI parameters included kurtosis metrics (mean kurtosis [MK], axial kurtosis [K // ], and radial kurtosis [K ⊥ ]), and the diffusional metrics (fractional anisotropy [FA], mean diffusion [MD], axial diffusion [λ // ], and radial diffusion [λ ⊥ ]). The cellularity and the N/C ratio were compared within LGGs and HGGs using the Mann-Whitney U test (significant level, p < 0.007 [0.05/7]); Bonferroni correction). Spearman's correlation analysis was used to calculate the correlation coefficients among DKI metrics, cellularity, and the N/C ratio at a significant level of p = 0.05., Results: Excluding FA, all DKI metrics showed significant differences between HGGs and LGGs (all p ≤ 0.001). The N/C ratio of HGGs was significantly higher than that of LGGs; however, differences in cellularity were not significant between the two glioma groups (p = 0.525). Similarly, excluding FA, all DKI metrics were significantly correlated with the N/C ratio in LGGs, with correlation coefficients of - 0.365 (MD), - 0.313 (λ // ), - 0.376 (λ ⊥ ), 0.859 (MK), 0.772 (K // ), and 0.842 (K // ). There was a non-significant correlation between any DKI parameters and the cellularity in LGGs. Additionally, the cellularity and N/C ratios in HGGs did not correlate with any DKI metrics., Conclusions: DKI differentiate LGGs from HGGs associated with their different N/C ratios., Clinical Relevance Statement: This study shows that DKI differentiates LGGs from HGGs may correlated with their different N/C ratios, this could provide a possible histopathological mechanism about why DKI can DKI differentiate LGGs from HGGs., Key Points: • Excluding FA, all DKI metrics showed a significant difference between high-grade gliomas and IDH1-mutant low-grade gliomas. • The nuclear-to-cytoplasm ratios in high-grade gliomas were significantly more extensive than that in IDH1-mutant low-grade gliomas, but not the cellularity. • Significant associations were seen between DKI measures and the N/C ratio; a non-significant correlation was noted between any DKI metric and cellularity in glioma specimens., (© 2023. The Author(s), under exclusive licence to European Society of Radiology.)

Purpose: The aim of this study was to develop a model-based deep learning architecture to accurately reconstruct fiber orientation distributions (FODs) from a reduced number of diffusion-weighted images (DWIs), facilitating accurate analysis with reduced acquisition times., Methods: Our proposed architecture, Spherical Deconvolution Network (SDNet), performed FOD reconstruction by mapping 30 DWIs to fully sampled FODs, which have been fit to 288 DWIs. SDNet included DWI-consistency blocks within the network architecture, and a fixel-classification penalty within the loss function. SDNet was trained on a subset of the Human Connectome Project, and its performance compared with FOD-Net, and multishell multitissue constrained spherical deconvolution., Results: SDNet achieved the strongest results with respect to angular correlation coefficient and sum of squared errors. When the impact of the fixel-classification penalty was increased, we observed an improvement in performance metrics reliant on segmenting the FODs into the correct number of fixels., Conclusion: Inclusion of DWI-consistency blocks improved reconstruction performance, and the fixel-classification penalty term offered increased control over the angular separation of fixels in the reconstructed FODs., (© 2024 The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background: Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) can provide quantitative parameters that show promise for evaluation of diabetic kidney disease (DKD). The combination of radiomics with DTI and DKI may hold potential clinical value in detecting DKD., Purpose: To investigate radiomics models of DKI and DTI for predicting DKD in type 2 diabetes mellitus (T2DM) and evaluate their performance in automated renal parenchyma segmentation., Study Type: Prospective., Population: One hundred and sixty-three T2DM patients (87 DKD; 63 females; 27-80 years), randomly divided into training cohort (N = 114) and validation cohort (N = 49)., Field Strength/sequence: 1.5-T, diffusion spectrum imaging (DSI) with 9 different b-values., Assessment: The images of DSI were processed to generate DKI and DTI parameter maps, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). The Swin UNETR model was trained with 5-fold cross-validation using 100 samples for renal parenchyma segmentation. Subsequently, radiomics features were automatically extracted from each parameter map. The performance of the radiomics models on the validation cohort was evaluated by utilizing the receiver operating characteristic (ROC) curve., Statistical Tests: Mann-Whitney U test, Chi-squared test, Pearson correlation coefficient, least absolute shrinkage and selection operator (LASSO), dice similarity coefficient (DSC), decision curve analysis (DCA), area under the curve (AUC), and DeLong's test. The threshold for statistical significance was set at P < 0.05., Results: The DKI&#95;MD achieved the best segmentation performance (DSC, 0.925 ± 0.011). A combined radiomics model (DTI&#95;FA, DTI&#95;MD, DKI&#95;FA, DKI&#95;MD, and DKI&#95;RD) showed the best performance (AUC, 0.918; 95% confidence interval [CI]: 0.820-0.991). When the threshold probability was greater than 20%, the combined model provided the greatest net benefit. Among the single parameter maps, the DTI&#95;FA exhibited superior diagnostic performance (AUC, 887; 95% CI: 0.779-0.972)., Data Conclusion: The radiomics signature constructed based on DKI and DTI may be used as an accurate and non-invasive tool to identify T2DM and DKD., Level of Evidence: 2 TECHNICAL EFFICACY: Stage 2., (© 2024 International Society for Magnetic Resonance in Medicine.)

To retrospectively explore the role of magnetic resonance imaging (MRI) diffusion tensor imaging (DTI) in analyzing the corticospinal tract injury in acute cerebral anterior circulation infarction in the basal ganglia region and the correlation between DTI parameters and neurological function scores, patients with acute cerebral infarction and stroke had undergone plain MRI and DTI sequence scanning were enrolled. Diffusion tensor tractography was used to perform 3-dimensional reconstruction of bilateral corticospinal tracts (CST). The image data were processed to obtain fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values, and the correlation between the DTI parameters and neurological function scores of National Institutes of Health Stroke Scale (NIHSS) was evaluated. A total of thirty-two patients with acute ischemic cerebral infarction were retrospectively enrolled, including 19 males and 13 females with a mean age 63.22 ± 7.78 years. The CST score was 0 in 2 (6.25%) patients, 1 in 9 (28.13%), 2 in 9 (28.13%), 3 in 7 (21.88%), and 4 in 5 (15.63%). The FA value significantly (P = .01) decreased (0.52 ± 0.03 vs 0.62 ± 0.04) on the ischemic side compared with that on the normal side. A significant (P < .05) difference was detected in the number of nerve fibers (223.3 ± 110.0 vs 246.7 ± 104.4) rather than in the ADC values (0.86 ± 0.06 vs 0.84 ± 0.06) between the ischemic and healthy sides. The FA and ADC values were not significantly (P > .05) different according to the CST scores 0, 1, 2, 3, or 4 between the ischemic and healthy sides. There was a significant (P < .05) negative correlation between the FA value on the infarcted side and the NIHSS score. In conclusion, with the DTI technology, varying degrees of damage to the corticospinal tract at the infarcted side can be detected and important clinical information can be provided for the diagnosis and prognosis of acute cerebral infarction by evaluating the degree of corticospinal tract injury., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Objective. Decades ago, neurosurgeons used electrical impedance measurements in the brain for coarse intraoperative tissue differentiation. Over time, these techniques were largely replaced by more refined imaging and electrophysiological localization. Today, advanced methods of diffusion tensor imaging (DTI) and finite element method (FEM) modeling may permit non-invasive, high-resolution intracerebral impedance prediction. However, expectations for tissue-impedance relationships and experimentally verified parameters for impedance modeling in human brains are lacking. This study seeks to address this need. Approach. We used FEM to simulate high-resolution single- and dual-electrode impedance measurements along linear electrode trajectories through (1) canonical gray and white matter tissue models, and (2) selected anatomic structures within whole-brain patient DTI-based models. We then compared intraoperative impedance measurements taken at known locations along deep brain stimulation (DBS) surgical trajectories with model predictions to evaluate model accuracy and refine model parameters. Main results. In DTI-FEM models, single- and dual-electrode configurations performed similarly. While only dual-electrode configurations were sensitive to white matter fiber orientation, other influences on impedance, such as white matter density, enabled single-electrode impedance measurements to display significant spatial variation even within purely white matter structures. We compared 308 intraoperative single-electrode impedance measurements in five DBS patients to DTI-FEM predictions at one-to-one corresponding locations. After calibration of model coefficients to these data, predicted impedances reliably estimated intraoperative measurements in all patients (R=0.784±0.116,n=5). Through this study, we derived an updated value for the slope coefficient of the DTI conductance model published by Tuch et al ,k=0.0649 S⋅smm-3 (originalk=0.844), for use specifically in humans at physiological frequencies. Significance. This is the first study to compare impedance estimates from imaging-based models of human brain tissue to experimental measurements at the same locations in vivo . Accurate, non-invasive, imaging-based impedance prediction has numerous applications in functional neurosurgery, including tissue mapping, intraoperative electrode localization, and DBS., (Creative Commons Attribution license.)

Background: Our intent was to explore the mediating role of interstitial free water (FW) linking deep medullary vein (DMV) score to white matter hyperintensity (WMH) volume., Methods: Our research team conducted a forward-looking analysis of initial clinical and imaging information gathered from 125 patients with cerebral small vessel disease. We identified six anatomic DMV regions on susceptibility weighted imaging (SWI) studies. Each region earned a score of 0-3, determined by the visual conditions of vessels, summing all six to generate a DMV score. We utilized fluid-attenuated inversion recovery (FLAIR) sequences to measure the volume of WMH. Additionally, we employed diffusion tensor imaging (DTI) to assess FW value., Results: DMV score significantly positively correlated with FW value and with WMH volume (p < 0.05), and value of FW positively correlated with WMH volume (p < 0.05). The indirect effect of DMV score on WMH volume was mediated by FW (β = 0.281, 95% confidence interval [CI]: 0.178-0.388), whether adjusted for age and gender (β = 0.142, 95% CI: 0.058-0.240) or for age, gender and vascular risk factors (β = 0.141, 95% CI: 0.054-0.249)., Conclusion: DMV score correlate with WMH volume by virtue of FW increases in white matter., (© 2024. The Author(s).)

Background: Disorders of consciousness (DoC) are a group of conditions that affect the level of awareness and communication in patients. While neuroimaging techniques can provide useful information about the brain structure and function in these patients, most existing methods rely on a single modality for analysis and rarely account for brain injury. To address these limitations, we propose a novel method that integrates two neuroimaging modalities, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), to enhance the classification of subjects into different states of consciousness., Method and Results: The main contributions of our work are threefold: first, after constructing a dual-model individual graph using functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), we introduce a brain injury mask mechanism that consolidates damaged brain regions into a single graph node, enhancing the modeling of brain injuries and reducing deformation effects. Second, to address over-smoothing, we construct a dual-level graph that dynamically construct a population-level graph with node features from individual graphs, to promote the clustering of similar subjects while distinguishing dissimilar ones. Finally, we employ a subgraph exploration model with task-fMRI data to validate the interpretability of our model, confirming that the selected brain regions are task-relevant in cognition. Our experimental results on data from 89 healthy participants and 204 patients with DoC from Huashan Hospital, Fudan University, demonstrate that our method achieves high accuracy in classifying patients into unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), or normal conscious state, outperforming current state-of-the-art methods. The explainability results of our method identified a subset of brain regions that are important for consciousness, such as the default mode network, the salience network, the dorsal attention network, and the visual network. Our method also revealed the relationship between brain networks and language processing in consciousness, and showed that language-related subgraphs can distinguish MCS from UWS patients., Conclusion: We proposed a novel graph learning method for classifying DoC based on fMRI and DTI data, introducing a brain injury mask mechanism to effectively handle damaged brains. The classification results demonstrate the effectiveness of our method in distinguishing subjects across different states of consciousness, while the explainability results identify key brain regions relevant to this classification. Our study provides new evidence for the role of brain networks and language processing in consciousness, with potential implications for improving the diagnosis and prognosis of patients with DoC., (© 2024. The Author(s).)

Background: Synaptic degeneration, axonal injury, and white matter disintegration are among the pathological events in Alzheimer's disease (AD), for which growth-associated protein 43 (GAP-43) and diffusion tensor imaging (DTI) could be an indicator. In this study, the cerebrospinal fluid (CSF) GAP-43 clinical trajectories and their association with progression and AD hallmarks with white matter microstructural changes were evaluated., Methods: A total number of 133 participants were enrolled in GAP-43 and DTI values were compared between groups, both cross-sectionally and longitudinally with two and four-year follow-ups. Subsequently, the correlation between GAP-43 levels in the CSF and DTI values was investigated using Spearman's correlation., Results: The CSF level of GAP-43 is negatively correlated with the mean diffusivity measures in Fornix (Cres)/Stria terminals in early and late MCI (r s =-0.478 p = 0.021 and r s =-0.425 p = 0.038). Additionally, the CSF level of GAP-43 is negatively correlated with fractional anisotropy in the cingulum in late MCI (r s =-0.437 p = 0.033). Moreover, the axial diffusivity in superior corona radiate (r s =-0.562 p = 0.005 and r s =-0.484 p = 0.036) and radial diffusivity in superior fronto-occipital fasciculus was negatively correlated with GAP-43 level in the early and mid-MCI participants (r s =-0.520 p = 0.011 and r s =-0.498 p = 0.030)., Conclusions: Presynaptic marker GAP-43 in combination with DTI can be used as a novel biomarker to identify microstructural synaptic degeneration in the early MCI. In addition, it can be used as a biomarker for tracking the progression of AD and monitoring treatment efficacy., (© 2024. The Author(s).)

Background: The pathophysiology of protracted symptoms after COVID-19 is unclear. This study aimed to determine if long-COVID is associated with differences in baseline characteristics, markers of white matter diffusivity in the brain, and lower scores on objective cognitive testing., Methods: Individuals who experienced COVID-19 symptoms for more than 60 days post-infection (long-COVID) (n = 56) were compared to individuals who recovered from COVID-19 within 60 days of infection (normal recovery) (n = 35). Information regarding physical and mental health, and COVID-19 illness was collected. The National Institute of Health Toolbox Cognition Battery was administered. Participants underwent magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI). Tract-based spatial statistics were used to perform a whole-brain voxel-wise analysis on standard DTI metrics (fractional anisotropy, axial diffusivity, mean diffusivity, radial diffusivity), controlling for age and sex. NIH Toolbox Age-Adjusted Fluid Cognition Scores were used to compare long-COVID and normal recovery groups, covarying for Age-Adjusted Crystallized Cognition Scores and years of education. False discovery rate correction was applied for multiple comparisons., Results: There were no significant differences in age, sex, or history of neurovascular risk factors between the groups. The long-COVID group had significantly (p < 0.05) lower mean diffusivity than the normal recovery group across multiple white matter regions, including the internal capsule, anterior and superior corona radiata, corpus callosum, superior fronto-occiptal fasciculus, and posterior thalamic radiation. However, the effect sizes of these differences were small (all β<|0.3|) and no significant differences were found for the other DTI metrics. Fluid cognition composite scores did not differ significantly between the long-COVID and normal recovery groups (p > 0.05)., Conclusions: Differences in diffusivity between long-COVID and normal recovery groups were found on only one DTI metric. This could represent subtle areas of pathology such as gliosis or edema, but the small effect sizes and non-specific nature of the diffusion indices make pathological inference difficult. Although long-COVID patients reported many neuropsychiatric symptoms, significant differences in objective cognitive performance were not found., Competing Interests: Declaration of competing interest WGH is a Consultant to Newron, AbbVie and Boehringer Ingelheim. Other authors have no conflicts of interest to declare., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Introduction: Atrophy of the nucleus basalis of Meynert (NBM) is an early indicator of Alzheimer's disease (AD). However, reduced integrity of the NBM white matter tracts may be more relevant for cognitive impairment and progression to dementia than NBM volume. Research is needed to compare differences in NBM volume and integrity of the lateral and medial NBM tracts across early and later stages of AD progression., Methods: 187 participants were included in this study who were either healthy controls (HC; n = 50) or had early mild cognitive impairment (EMCI; n = 50), late MCI (LMCI; n = 37), or AD (n = 50). NBM volume was calculated using voxel-based morphometry and mean diffusivity (MD) of the lateral and medial NBM tracts were extracted using probabilistic tractography. Between group differences in NBM volume and tract MD were compared using linear mixed models controlling for age, sex, and either total intracranial volume or MD of a control mask, respectively. Associations between NBM volume and tract MD with executive function, memory, language, and visuospatial function were also analysed., Results: NBM volume was smallest in AD followed by LMCI (p < 0.0001), with no difference between EMCI and HC. AD had highest MD for both tracts compared to all other groups (p < 0.01). Both MCI groups had higher lateral tract MD compared to HC (p < 0.05). Medial tract MD was higher in LMCI (p = 0.008), but not EMCI (p = 0.09) compared to HC. Higher lateral tract MD was associated with executive function (p = 0.001) and language (p = 0.02)., Discussion: Integrity of the lateral NBM tract is most sensitive to the earliest stages of AD and should be considered an important therapeutic target for early detection and intervention., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: White matter (WM) fiber tracts in the brainstem communicate with various regions in the cerebrum, cerebellum, and spinal cord. Clinically, small lesions, malformations, or histopathological changes in the brainstem can cause severe neurological disorders. A direct and non-invasive assessment approach could bring valuable information about the intricate anatomical variations of the white matter fiber tracts and nuclei. Although tractography from diffusion tensor imaging has been commonly used to map the WM fiber tracts connectivity, it is difficult to differentiate the complex WM tracts anatomically. Both high field MRI methods and ultrahigh-field MRI methods at 7T and 11.7 T have been used to enhance the contrast of WM fiber tracts. Despite their promising results, it is still challenging to achieve wide clinical adoption at 3T. In this study, we explored a clinically feasible method using a proton density weighted (PDW) 3D gradient echo (GRE) sequence to directly image the WM fiber tracts in the brainstem at 3T in vivo., Methods: We optimized a 3D high resolution, double echo, short TR, PDW GRE sequence on 5 healthy volunteers using a clinical 3T scanner to visualize the complicated anatomy of WM fiber tracts in the brain stem. Tissue properties including T1, proton density and T2* from in vivo quantitative MRI data were used for simulations to determine the optimal flip angle for the sequence. The visualization of multiple WM fiber tracts in the brainstem was assessed qualitatively and quantitatively using relative contrast and contrast-to-noise ratio (CNR). To improve the CNR, the final images were created by averaging over all echoes from two consecutive scans at the optimal flip angle. The results were compared to anatomical atlases and histology sections to identify the major fiber tracts. All the identified major fiber tracts were labeled on axial, sagittal and coronal slices., Results: The WM fiber tracts were found to have distinct hypointense signal throughout the brainstem and most of the major WM fiber tracts, such as the corticospinal tract, medial lemniscus, medial longitudinal fasciculus, and central tegmental tract, in the brainstem up to and including the thalamus were identified in all subjects. Both qualitative and quantitative evaluations showed that the 3° scan offered the best contrast for WM fiber tracts for a TR of 20 ms. The average over the first two echo times and two consecutive 3° scans gave a CNR of 47.8 ± 6.2 for the pyramidal tracts in particular and CNRs values greater than 6.5 ± 2.4 for the rest of the fiber tracts., Conclusions: All the major fiber tracts in the brainstem could be visualized. Given the reasonably short scan time of 10 min at 3T, double echo PDW GRE sequence is a very practical approach for clinical adoption., Competing Interests: Declaration of competing interest All authors declare that they have no conflicts of interest., (Copyright © 2024. Published by Elsevier Inc.)

The common marmoset is an essential model for understanding social cognition and neurodegenerative diseases. This study explored the structural and functional brain connectivity in a marmoset under isoflurane anesthesia, aiming to statistically overcome the effects of high inter-individual variability and noise-related confounds such as physiological noise, ensuring robust and reliable data. Similarities and differences in individual subject data, including assessments of functional and structural brain connectivities derived from resting-state functional MRI and diffusion tensor imaging were meticulously captured. The findings highlighted the high consistency of structural neural connections within the species, indicating a stable neural architecture, while functional connectivity under anesthesia displayed considerable variability. Through independent component and dual regression analyses, several distinct brain connectivities were identified, elucidating their characteristics under anesthesia. Insights into the structural and functional features of the marmoset brain from this study affirm its value as a neuroscience research model, promising advancements in the field through fundamental and translational studies., Competing Interests: Declaration of competing interest None, (Copyright © 2024. Published by Elsevier Inc.)

Objectives: Previous studies have shown that microstructural alterations in white matter (WM) could contribute to the symptom manifestation and support the dysconnectivity hypothesis in schizophrenia patients. These alterations were pervasive, non-specific, and reported inconsistently across the literature. This study aimed to specifically investigate the microstructure alterations of the posterior limb of the internal capsule (PLIC) in first-episode, drug-naive schizophrenia patients. Utilizing a multicompartmental biophysical model, we further explored the correlation between these alterations and syndrome scale scores., Methods: Thirty-two individuals with first-episode, drug-naive schizophrenia (FES) and thirty demographically matched healthy controls were enrolled. High-resolution multi-shell diffusion MRI data were collected, followed by the application of a three-compartment Neurite Orientation Dispersion and Density Imaging (NODDI) model to scrutinize the alterations in white matter microstructure. Changes in sensory and motor fibers within the PLIC were specifically focused on. Additionally, the correlation between these pathological changes and scores on the Positive and Negative Syndrome Scale (PANSS) was investigated., Results: The Neurite density index (NDI) in the left PLIC was significantly lower in FES patients compared to healthy individuals, and positively correlated with PANSS positive syndrome scores (r = 0.0379, p = 0.046). In the sensory component (left superior thalamic radiation within PLIC, STR&#95;P), the NDI was significantly elevated (p < 0.0001). Conversely, the NDI in the motor component (left corticospinal tract within PLIC, CST&#95;P) was reduced (p = 0.007) in FES patients compared to healthy individuals, and strongly correlated with PANSS positive syndrome scores (p < 0.020) and PANSS total scores (p < 0.045). Moreover, the NDI deviation of STR from total PLIC (f STR&#95;P ) and NDI deviation in STR&#95;P and CST&#95;P compared to PLIC region (f PLIC ) were significantly higher in FES patients than in healthy controls (p < 0.00001), with an area under the curve (AUC) of f PLIC reaching 0.872., Conclusion: The study's findings provided new insights into the discrepancy of white matter microstructure changes associated with the sensory and motor fibers in the PLIC region in FES patients. These results contribute to the growing body of evidence suggesting that WM microstructural alterations play a critical role in schizophrenia pathophysiology., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Neurovascular compression (NVC) is a primary etiology of trigeminal neuralgia (TN) and hemifacial spasm (HFS). Despite Magnetic Resonance Tomographic Angiography (MRTA) being a useful tool for 3D multimodal fusion imaging (MFI) in microvascular decompression (MVD) surgery planning, it may not visualize smaller arterial vessels and veins effectively. We validate a novel computed tomography angiography and venography (CTA/V) - diffusion tensor tractography (DTT) -3D-MFI to enhance the MVD surgical guidance., Methods: In this prospective study, 80 patients with unilateral primary TN or HFS who underwent MVD surgery were included. Imaging was conducted using CTA/V-DTT-3D-MFI compared with CT-MRTA-3D-MFI in predicting the responsible vessel and assessing the severity of NVC. Surgical outcomes were subsequently analyzed. Neurosurgery residents were provided with questionnaires to evaluate and compare the two approaches., Results: CTA/V-DTT-3D-MFI significantly improved accuracy in identifying the responsible vessel (kappa = 0.954) and NVC (kappa = 0.969) compared to CT-MRTA-3D-MFI, aligning well with surgical findings. CTA/V-DTT-3D-MFI also exhibited higher sensitivity in identifying responsible vessels (98.0%) and NVC (98.7%) than CT-MRTA-3D-MFI. Additionally, CTA/V-DTT-3D-MFI showed fewer complications, shorter operation times, and lower recurrence after one year (all p < 0.05). Resident neurosurgeons emphasized that CTA/V-DTT-3D-MFI greatly assisted in formulating precise surgical strategies for more accurate identification and protection of responsible vessels and nerves (all p < 0.001)., Conclusion: CTA/V-DTT-3D-MFI enhances MVD surgery guidance, improving accuracy in identifying responsible vessels and NVC for better outcomes. This advanced imaging plays a crucial role in safer and more effective MVD surgery, as well as in training neurosurgeons., (© 2024. The Author(s).)

This study develops explainable artificial intelligence for predicting safe balance using hospital data, including clinical, neurophysiological, and diffusion tensor imaging properties. Retrospective data from 92 first-time stroke patients from January 2016 to June 2023 was analysed. The dependent variables were independent mobility scores, i.e., Berg Balance Scales with 0 (45 or below) vs. 1 (above 45) measured after three and six months, respectively. Twenty-nine predictors were included. Random forest variable importance was employed for identifying significant predictors of the Berg Balance Scale and testing its associations with the predictors, including Berg Balance Scale after one month and corticospinal tract diffusion tensor imaging properties. Shapley Additive Explanation values were calculated to analyse the directions of these associations. The random forest registered a higher or similar area under the curve compared to logistic regression, i.e., 91% vs. 87% (Berg Balance Scale after three months), 92% vs. 92% (Berg Balance Scale after six months). Based on random forest variable importance values and rankings: (1) Berg Balance Scale after three months has strong associations with Berg Balance Scale after one month, Fugl-Meyer assessment scale, ipsilesional corticospinal tract fractional anisotropy, fractional anisotropy laterality index and age; (2) Berg Balance Scale after six months has strong relationships with Fugl-Meyer assessment scale, Berg Balance Scale after one month, ankle plantar flexion muscle strength, knee extension muscle strength and hip flexion muscle strength. These associations were positive in the SHAP summary plots. Including Berg Balance Scale after one month, Fugl-Meyer assessment scale or ipsilesional corticospinal tract fractional anisotropy in the random forest will increase the probability of Berg Balance Scale after three months being above 45 by 0.11, 0.08, or 0.08. In conclusion, safe balance after stroke strongly correlates with its initial motor function, Fugl-Meyer assessment scale, and ipsilesional corticospinal tract fractional anisotropy. Diffusion tensor imaging information aids in developing explainable artificial intelligence for predicting safe balance after stroke., (© 2024. The Author(s).)

Background: Recurrence of lower grade glioma (LrGG) appeared to be unavoidable despite considerable research performed in last decades. Thus, we evaluated the postoperative recurrence within two years after the surgery in patients with LrGG by preoperative advanced diffusion magnetic resonance imaging (dMRI)., Materials and Methods: 48 patients with lower-grade gliomas (23 recurrence, 25 nonrecurrence) were recruited into this study. Different models of dMRI were reconstructed, including apparent fiber density (AFD), white matter tract integrity (WMTI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), Bingham NODDI and standard model imaging (SMI). Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) was used to construct a multiparametric prediction model for the diagnosis of postoperative recurrence., Results: The parameters derived from each dMRI model, including AFD, axon water fraction (AWF), mean diffusivity (MD), mean kurtosis (MK), fractional anisotropy (FA), intracellular volume fraction (ICVF), extra-axonal perpendicular diffusivity (De ⊥ ), extra-axonal parallel diffusivity (De ∥ ) and free water fraction (fw), showed significant differences between nonrecurrence group and recurrence group. The extra-axonal perpendicular diffusivity (De ⊥ ) had the highest area under curve (AUC = 0.885), which was significantly higher than others. The variable importance for the projection (VIP) value of De ⊥ was also the highest. The AUC value of the multiparametric prediction model merging AFD, WMTI, DTI, DKI, NODDI, Bingham NODDI and SMI was up to 0.96., Conclusion: Preoperative advanced dMRI showed great efficacy in evaluating postoperative recurrence of LrGG and De ⊥ of SMI might be a valuable marker., (© 2024. The Author(s).)

Emerging research in nonhuman animals implicates cerebellar projections to the ventral tegmental area (VTA) in appetitive behaviors, but these circuits have not been characterized in humans. Here, we mapped cerebello-VTA white matter connectivity in a cohort of men and women using probabilistic tractography on diffusion imaging data from the Human Connectome Project. We uncovered the topographical organization of these connections by separately tracking from parcels of cerebellar lobule VI, crus I/II, vermis, paravermis, and cerebrocerebellum. Results revealed that connections between the cerebellum and VTA predominantly originate in the right cerebellar hemisphere, interposed nucleus, and paravermal cortex and terminate mostly ipsilaterally. Paravermal crus I sends the most connections to the VTA compared with other lobules. We discovered a mediolateral gradient of connectivity, such that the medial cerebellum has the highest connectivity with the VTA. Individual differences in microstructure were associated with measures of negative affect and social functioning. By splitting the tracts into quarters, we found that the socioaffective effects were driven by the third quarter of the tract, corresponding to the point at which the fibers leave the deep nuclei. Taken together, we produced detailed maps of cerebello-VTA structural connectivity for the first time in humans and established their relevance for trait differences in socioaffective regulation., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 the authors.)

Epileptic seizures recorded with stereo-EEG can take a fraction of a second or several seconds to propagate from one region to another. What explains such propagation patterns? We combine tractography and stereo-EEG to determine the relationship between seizure propagation and the white matter architecture and to describe seizure propagation mechanisms. Patient-specific spatiotemporal seizure propagation maps were combined with tractography from diffusion imaging of matched subjects from the Human Connectome Project. The onset of seizure activity was marked on a channel-by-channel basis by two board-certified neurologists for all channels involved in the seizure. We measured the tract connectivity (number of tracts) between regions-of-interest pairs among the seizure onset zone, regions of seizure spread and non-involved regions. We also investigated how tract-connected the seizure onset zone is to regions of early seizure spread compared with regions of late spread. Comparisons were made after correcting for differences in distance. Sixty-nine seizures were marked across 26 patients with drug-resistant epilepsy; 11 were seizure free after surgery (Engel IA) and 15 were not (Engel IB-Engel IV). The seizure onset zone was more tract-connected to regions of seizure spread than to non-involved regions (P < 0.0001); however, regions of seizure spread were not differentially tract-connected to other regions of seizure spread compared with non-involved regions. In seizure-free patients only, regions of seizure spread were more tract-connected to the seizure onset zone than to other regions of spread (P < 0.0001). Over the temporal evolution of a seizure, the seizure onset zone was significantly more tract-connected to regions of early spread compared with regions of late spread in seizure-free patients only (P < 0.0001). By integrating information on structure, we demonstrate that seizure propagation is likely to be mediated by white matter tracts. The pattern of connectivity between seizure onset zone, regions of spread and non-involved regions demonstrates that the onset zone might be largely responsible for seizures propagating throughout the brain, rather than seizures propagating to intermediate points, from which further propagation takes place. Our findings also suggest that seizure propagation over seconds might be the result of a continuous bombardment of action potentials from the seizure onset zone to regions of spread. In non-seizure-free patients, the paucity of tracts from the presumed seizure onset zone to regions of spread suggests that the onset zone was missed. Fully understanding the structure-propagation relationship might eventually provide insight into selecting the correct targets for epilepsy surgery., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

We investigated differences in subcortical white matter according to the presence disorders of consciousness (DOC) in patients with hypoxic-ischemic brain injury (HI-BI), using tract-based spatial statistics (TBSS). Thirty-two consecutive patients with HI-BI were recruited. The patients were assigned in group A [preserved consciousness (Glasgow Coma Scale: 15 and Coma Recovery Scale-revised (CRS-R): 23, 9 patients)] or group B [DOC present (Glasgow Coma Scale <15 and CRS-R < 23, 20 patients)]. Voxel-wise statistical analysis of fractional anisotropy data was performed by using TBSS as implemented in the FMRIB Software Library. We calculated mean fractional anisotropy values across the white matter skeleton and within 48 regions of interest (ROIs) based on intersections between the skeleton and the probabilistic Johns Hopkins University white matter atlases. Among the 48 ROIs examined, the fractional anisotropy values of two ROIs (the left superior corona radiata, and left tapetum) were significantly lower in group B than in group A ( P  < 0.05). No significant differences were observed, however, in the other 46 ROIs ( P  > 0.05). Our results suggest that abnormalities of the superior corona radiata and tapetum may be critical for DOC presence in patients with HI-BI., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Molecular alteration events are common in glioblastomas, the isocitrate dehydrogenase (IDH)-wild of which have had poor survival results so far. The progress of radiomics-based model provides novel sights for its preoperatively noninvasive prediction., Purpose: To develop a radiomics-based model for predicting epidermal growth factor receptor (EGFR) amplification status in IDH1-wild glioblastomas of adults by pretreatment diffusion tensor imaging (DTI)., Material and Methods: A total of 124 patients with diagnosed glioblastomas were retrospectively collected. Six conventional magnetic resonance imaging (MRI) features of all the tumors were evaluated visually. Patients were divided into the training (n = 87) and the test set (n = 37) with a ratio of 7:3. Radiomics features were extracted from two regions of the glioblastomas, which were the total tumor (ROI&#95;1) and the solid portion of tumor (ROI&#95;2). The radiomics features extracted from the DTI and T1-contrast-enhanced (T1C) images were selected using the least absolute shrinkage and selection operator (LASSO) regression algorithm. Logistic regression analysis was conducted to develop models for EGFR amplification prediction in the training set., Results: The radiomics model based on ROI&#95;1 demonstrated favorable discrimination in both the training (area under the curve [AUC] = 0.86) and the test set (AUC = 0.82) ( P  < 0.05). Combining the radiomics features and the conventional feature tumor location, no significant improvement of AUCs was achieved (AUC = 0.86 and 0.81)., Conclusion: The radiomics model derived from pretreatment DTI may have potential in differentiating the EGFR mutation status in glioblastomas., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Despite substantial neuroscience research in the last decade revealing the claustrum's prominent role in mammalian forebrain organization, as evidenced by its extraordinarily widespread connectivity pattern, claustrum studies in humans are rare. This is particularly true for studies focusing on claustrum connections. Two primary reasons may account for this situation: First, the intricate anatomy of the human claustrum located between the external and extreme capsule hinders straightforward and reliable structural delineation. In addition, the few studies that used diffusion-weighted-imaging (DWI)-based tractography could not clarify whether in vivo tractography consistently and reliably identifies claustrum connections in humans across different subjects, cohorts, imaging methods, and connectivity metrics. To address these issues, we combined a recently developed deep-learning-based claustrum segmentation tool with DWI-based tractography in two large adult cohorts: 81 healthy young adults from the human connectome project and 81 further healthy young participants from the Bavarian longitudinal study. Tracts between the claustrum and 13 cortical and 9 subcortical regions were reconstructed in each subject using probabilistic tractography. Probabilistic group average maps and different connectivity metrics were generated to assess the claustrum's connectivity profile as well as consistency and replicability of tractography. We found, across individuals, cohorts, DWI-protocols, and measures, consistent and replicable cortical and subcortical ipsi- and contralateral claustrum connections. This result demonstrates robust in vivo tractography of claustrum connections in humans, providing a base for further examinations of claustrum connectivity in health and disease., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)