Diffusion Tensor Imaging Research Articles

Diffusion Magnetic Resonance Imaging and Human Reward System Research: A Bibliometric Analysis and Visualisation of Current Research Trends.

The human reward system has been extensively studied using neuroimaging. This bibliometric analysis aimed to determine the global trend in diffusion magnetic resonance imaging (dMRI) and human reward research in terms of the number of documents, the most active countries and their collaborating countries, the top journals and institutions, the most prominent authors and most cited articles, and research hotspots. The research datasets were acquired from the Scopus database. The search terms used were 'reward' AND 'human' AND 'diffusion imaging' OR 'diffusion tensor imaging' OR 'diffusion MRI' OR 'diffusion-weighted imaging' OR 'tractography' in the abstract, article title and keywords. A total of 336 publications were analysed using Harzing's Publish or Perish and VOSviewer software. The results revealed an upward trend in the number of publications with the highest number of articles in 2020 and 2022. Most publications were limited to countries, authors, and institutions in the USA, China and Europe. Bracht, Coenen, Wiest, Federspiel and Feng were among the top authors from Switzerland, Germany and the UK. Neuroimage, Neuroimage Clinical, Frontiers in Human Neuroscience, Human Brain Mapping, and the Journal of Neuroscience were the top journals. Among the top articles, six were reviews and four were original articles, while the top keywords in human reward research were 'diffusion MRI', 'adolescence', 'depression' and 'reward-related brain areas'. These findings may serve as researchers' references to find collaborative authors, relevant journals, cooperative countries/institutions, and hot topics related to dMRI and reward research.

Radiomics based on diffusion tensor imaging and 3D T1-weighted MRI for essential tremor diagnosis.

Due to the absence of biomarkers, the misdiagnosis of essential tremor (ET) with other tremor diseases and enhanced physiologic tremor is very common in practice. Combined radiomics based on diffusion tensor imaging (DTI) and three-dimensional T1-weighted imaging (3D-T1) with machine learning (ML) give a most promising way to identify essential tremor (ET) at the individual level and further reveal the potential imaging biomarkers. Radiomics features were extracted from 3D-T1 and DTI in 103 ET patients and 103 age-and sex-matched healthy controls (HCs). After data dimensionality reduction and feature selection, five classifiers, including the support vector machine (SVM), random forest (RF), logistic regression (LR), extreme gradient boosting (XGBoost) and multi-layer perceptron (MLP), were adopted to discriminate ET from HCs. The mean values of the area under the curve (mAUC) and accuracy were used to assess the model's performance. Furthermore, a correlation analysis was conducted between the most discriminative features and clinical tremor characteristics. All classifiers achieved good classification performance (with mAUC at 0.987, 0.984, 0.984, 0.988 and 0.981 in the test set, respectively). The most powerful discriminative features mainly located in the cerebella-thalamo-cortical (CTC) and visual pathway. Furthermore, correlation analysis revealed that some radiomics features were significantly related to the clinical tremor characteristics in ET patients. These results demonstrated that combining radiomics with ML algorithms could not only achieve high classification accuracy for identifying ET but also help us to reveal the potential brain microstructure pathogenesis in ET patients.

Advanced MRI-based evaluation of gray and white matter changes in Parkinson’s disease

BackgroundParkinson’s disease (PD) is the most common movement disorder and the second most common neurodegenerative disease. The aim of our study was to compare gray–white matter changes (GWC) between Parkinson's disease (PD) patients and age-matched healthy control group as well as comparing GWC between different stages of PD (early and complicated). Our study was prospective cross-sectional case–control observational study with analytic component conducted on twenty patients and ten controls without any signs or symptoms of PD or any history of PD in first-degree relatives. All patients and controls were tested for history taking with stress on resting tremors, rigidity, gait abnormalities, postural instability and any symptoms of cognitive impairment, clinical examination including general examination and neurological examination. Also diffusion tensor imaging (DTI) with fiber tracking (tractography) and susceptibility-weighted MR imaging were performed for all cases.ResultsAs regards DTI and evaluation of fractional anisotropy (FA) and mean diffusivity (MD) values between PD cases and healthy controls, the cases group showed significant decrease in FA values at substantia nigra on both sides and left cingulum as well as significant increase in MD values at substantia nigra on both sides and corpus callosum. Also, there are significant decrease in FA values at substantia nigra on both sides and significant increase in MD values at substantia nigra on both sides and right cingulum in late parkinsonism when compared to early parkinsonism. A cutoff FA value of 0.945 at right substantia nigra and cutoff FA value of 0.585 at left substantia nigra showed significant AUC that could differentiate between cases and controls. Also cutoff MD value of 0.791 at right substantia nigra and cutoff MD value of 0.813 at left substantia nigra showed significant AUC that could differentiate between cases and controls.ConclusionsDiffusion tensor imaging showed valuable role in evaluation of gray–white matter changes in Parkinson's disease. Also, it helps to assess degree of gray–white matter changes when comparing late parkinsonism to early parkinsonism through evaluation of FA and MD values at corpus callosum, substania nigra, and cingulum.

Diffusion tensor imaging in Behcet's disease with and without neurological involvement patients: evaluation of microstructural white matter abnormality with a tract-based spatial statistical analysis.

This study aims to assess the microstructural abnormalities in white matter (WM) among Behcet's disease (BD) patients, both with and without neurological involvement, utilising tract-based spatial statistics (TBSS) to elucidate the underlying causes of WM microstructural changes. This prospective study comprised 43 BD patients without neurological involvement, 15 neuro-Behcet's disease (NBD) patients with normal conventional MRI, and 54 healthy controls matched for age and sex. TBSS was applied in this diffusion tensor imaging study to conduct a whole-brain voxel-wise analysis of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of WM. Compared to the control group, BD patients exhibited decreased FA and increased MD and RD in nearly all WM tracts, along with increased AD in the left corticospinal tract (CST), left inferior longitudinal fasciculus (ILF), and left superior longitudinal fasciculus (SLF). NBD patients also showed a widespread decrease in FA and increased MD and RD, similar to BD patients without neurological involvement. Additionally, NBD patients had increased AD in the left CST, left ILF, left SLF, left inferior fronto-occipital fasciculus (IFOF), and right CST. Compared to BD patients without neurological involvement, NBD patients exhibited a greater reduction in FA and an increase in MD and RD in WM tracts, with no significant differences in AD. These results suggest that the main mechanism of microstructural changes in the WM of BD patients may be related to impaired fibre integrity, demyelination, and decreased myelin sheath integrity. This study demonstrated BD patients without neurological involvement and NBD patients a decrease in FA and an increase in MD and RD were observed in larger areas of major WM tracts, while an increase in AD values was observed in fewer tracts. Our findings may be useful in understanding the pathophysiology underlying subclinical parenchymal involvement and neurological dysfunction in BD patients and the management of BD patients.

Assessment of Tumor Cell Invasion and Radiotherapy Response in Experimental Glioma by Magnetic Resonance Elastography.

Gliomas are highly invasive brain neoplasms. MRI is the most important tool to diagnose and monitor glioma but has shortcomings. In particular, the assessment of tumor cell invasion is insufficient. This is a clinical dilemma, as recurrence can arise from MRI-occult glioma cell invasion. Tumor cell invasion, tumor growth and radiotherapy alter the brain parenchymal microstructure and thus are assessable by diffusion tensor imaging (DTI) and MR elastography (MRE). Experimental, animal model. Twenty-three male NMRI nude mice orthotopically implanted with S24 patient-derived glioma cells (experimental mice) and 9 NMRI nude mice stereotactically injected with 1 μL PBS (sham-injected mice). 2D and 3D T2-weighted rapid acquisition with refocused echoes (RARE), 2D echo planar imaging (EPI) DTI, 2D multi-slice multi-echo (MSME) T2 relaxometry, 3D MSME MRE at 900 Hz acquired at 9.4 T (675 mT/m gradient strength). Longitudinal 4-weekly imaging was performed for up to 4 months. Tumor volume was assessed in experimental mice (n = 10 treatment-control, n = 13 radiotherapy). The radiotherapy subgroup and 5 sham-injected mice underwent irradiation (3 × 6 Gy) 9 weeks post-implantation/sham injection. MRI-/MRE-parameters were assessed in the corpus callosum and tumor core/injection tract. Imaging data were correlated to light sheet microscopy (LSM) and histology. Paired and unpaired t-tests, a P-value ≤0.05 was considered significant. From week 4 to 8, a significant callosal stiffening (4.44 ± 0.22 vs. 5.31 ± 0.29 kPa) was detected correlating with LSM-proven tumor cell invasion. This was occult to all other imaging metrics. Histologically proven tissue destruction in the tumor core led to an increased T2 relaxation time (41.65 ± 0.34 vs. 44.83 ± 0.66 msec) and ADC (610.2 ± 12.27 vs. 711.2 ± 13.42 × 10-6 mm2/s) and a softening (5.51 ± 0.30 vs. 4.24 ± 0.29 kPa) from week 8 to 12. Radiotherapy slowed tumor progression. MRE is promising for the assessment of key glioma characteristics. NA TECHNICAL EFFICACY: Stage 2.

Residential ambient air pollution exposure and the development of white matter microstructure throughout adolescence

BackgroundRecent evidence suggests an association of air pollution exposure with brain development, but evidence on white matter microstructure in children is scarce. We investigated how air pollution exposure during pregnancy and childhood impacts longitudinal development of white matter microstructure throughout adolescence. MethodsOur study population consisted of 4108 participants of Generation R, a large population-based birth cohort from Rotterdam, the Netherlands. Residential air pollution exposure to 14 air pollutants during pregnancy and childhood was estimated with land-use regression models. Diffusion tensor images were obtained around age 10 and 14, resulting in a total of 5422 useable scans (n = 3082 for wave 1 and n = 2340 for wave 2; n = 1314 for participants with data on both waves). We calculated whole-brain fractional anisotropy (FA) and mean diffusivity (MD) and performed single- and multi-pollutant analyses using mixed effects models adjusted for life-style and socioeconomic status variables. ResultsHigher exposure to PM2.5 during pregnancy, and PM10, PM2.5, PM2.5-10, and NOX during childhood was associated with a consistently lower whole-brain FA throughout adolescence (e.g. – 0.07 × 10−2 FA [95%CI -0.12; −0.02] per 1 standard deviation higher PM2.5 exposure during pregnancy). Higher exposure to silicon (Si) in PM2.5 and oxidative potential of PM2.5 during pregnancy, and PM2.5 during childhood was associated with an initial higher MD followed by a faster decrease in MD throughout adolescence (e.g. – 0.02 × 10−5 mm2/s MD [95%CI -0.03; −0.00] per year of age per 1 standard deviation higher Si exposure during pregnancy). Results were comparable when performing the analysis in children with complete data on the outcome for both neuroimaging assessments. ConclusionsExposure to several pollutants was associated with a consistently lower whole-brain FA throughout adolescence. The association of few pollutants with whole-brain MD at baseline attenuated throughout adolescence. These findings suggest both persistent and age-limited associations of air pollution exposure with white matter microstructure.

Embedded finite element modeling of the mechanics of brain axonal fiber tracts under head impact conditions

Investigating and understanding the biomechanical kinematics and kinetics of human brain axonal fibers during head impact process is crucial to study the mechanisms of Traumatic Axonal Injury (TAI). Such a study may require the explicit incorporation of brain fiber tracts into the host brain in order to distinguish the mechanical states of axonal fibers and brain tissue. Herein we extend our previously developed human head model by using an embedded element method to include fiber tracts reconstructed from diffusion tensor images in a host brain with the purpose of numerically tracking the deformation state of axonal fiber tracts during a head impact simulation. The updated model is validated by comparing its prediction of intracranial pressures with experimental data, followed by a thorough study of the effects of element types used for fiber tracts and the stiffness ratios of fiber to host brain. The validated model is also used to predict and visualize the damaged region of fiber tracts during the head impact process based on different injury criteria. The model is promising in tracking the state of fiber tracts and can add more objective functions such as axonal fiber deformation if used in the future design optimization of head protective equipment such as a football helmet.

Alternation of psychological resilience may moderate mentalization toward mental health conditions from macro- and microstructure aspects

ObjectiveWe aim to investigate the interplay between mentalization, brain microstructure, and psychological resilience as potential protective factors against mental illness. MethodFour hundred and twenty-six participants (mean age 40.12±16.95; 202 males, 224 females), without psychiatric or neurological history, completed assessments: Dissociative Process Scale (DPS), Peace of Mind (PoM), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Resilience Scale for Adults (RSA), and Magnetic Resonance Imaging (MRI) structures with selected regions of interest, and Diffusion Tensor Imaging (DTI) maps from various tracts in the right hemisphere and connection to the frontal areas, including anterior thalamic radiation (ATR), Cingulum (hippocampus) (CH), Corticospinal tract (CST), Superior longitudinal fasciculus (SLF), Inferior fronto-occipital fasciculus (IFOF), and Uncinate fasciculus (UF) were analyzed. ResultsTwo clusters, representing hypomentalization (HypoM) and hypermentalization (HyperM), were identified based on DPS, CPSS, and RFQ responses. One-way ANOVA showed no significant age or gender differences between clusters. The HypoM group exhibited lower PoM scores, higher BDI and BAI scores, and lower RSA scores (ps< 0.05). Structural brain metric comparison showed significant differences in GMV in the right caudal middle frontal gyrus (rcMFG), right superior frontal gyrus (rsFG), and right frontal pole (rFP) between groups. In addition, the HyperM individuals with a higher risk of depression and a higher ratio of intrapersonal to interpersonal factors of resilience were found with reduced GMV on the rcMFG. Additionally, analyses of DTI metrics revealed significant differences between two groups in rATR and rSLF in terms of fractional anisotropy (FA) values; rATR, rCST, rUF, rSLF, rCH and rIFOF in terms of mean diffusivity (MD) values, and radial diffusivity (RD) (corrected p = 0.05). Moreover, the positive correlation between different domains of resilience and white matter (WM) integrity implied further enhancement of intrapersonal or interpersonal resilience factors that are different for people with different mentalization. ConclusionsThe findings underscore the importance of considering both intrapersonal and interpersonal factors in understanding the interactions between psychological resilience and mental health conditions relevant to brain mechanisms.

Advancing Neuroimaging Frontiers: A Comprehensive Review of Novel Diagnostic Techniques in Neuroradiology and Their Clinical Applications

The review article provides a comprehensive overview of the latest advancements in neuroradiological techniques and their clinical applications. It explores various advanced magnetic resonance imaging (MRI) methods, including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), functional MRI (fMRI), and magnetic resonance spectroscopy (MRS), as well as developments in computed tomography (CT) technology, such as multidetector CT (MDCT) and dual-energy CT (DECT). The article discusses the principles, applications, and limitations of these techniques, highlighting their impact on patient care, particularly in diagnosing and managing neurological conditions, including cerebrovascular diseases, brain tumors, neurodegenerative disorders, and traumatic brain injuries. The review also addresses the challenges and potential future directions in neuroradiology.

Unveiling the link between glymphatic function and cortical microstructures in post-traumatic stress disorder

PurposeThe discovery of the glymphatic system, crucial for cerebrospinal and interstitial fluid exchange, has enhanced our grasp of brain protein balance and its potential role in neurodegenerative disease prevention and therapy. Detecting early neurodegenerative shifts via noninvasive biomarkers could be key in identifying at-risk individuals for Alzheimer's disease (AD). Our research explores a diffusion tensor imaging (DTI) method that measures cortical mean diffusivity (cMD), potentially a more sensitive indicator of neurodegeneration than traditional macrostructural methods. Materials and methodsWe analyzed 67 post-traumatic stress disorder (PTSD)-diagnosed veterans from the Alzheimer's Disease Neuroimaging Initiative database. Participants underwent structural MRI, DTI, Aβ PET imaging, and cognitive testing. We focused on the DTI-ALPS technique to assess glymphatic function and its relation to cMD, cortical Aβ accumulation, and thickness, accounting for age and APOE ε4 allele variations. ResultsThe cohort, all male with an average age of 68.1 (SD 3.4), showed a strong inverse correlation between DTI-ALPS and cMD in AD-affected regions, especially in the entorhinal, parahippocampal, and fusiform areas. Higher DTI-ALPS readings were consistently linked with greater cortical thickness, independent of Aβ deposits and genetic risk factors. Age and cMD emerged as inversely proportional predictors of DTI-ALPS, indicating a complex interaction with age. ConclusionThe study confirms a meaningful association between glymphatic efficiency and cMD in AD-sensitive zones, accentuating cortical microstructural alterations in PTSD. It positions DTI-ALPS as a viable biomarker for assessing glymphatic function in PTSD, implicating changes in DTI-ALPS as indicative of glymphatic impairment.

Examining the relative contribution of slow-burning inflammation and chronic demyelination to axonal damage in chronic multiple sclerosis lesions

Background and ObjectivesSlow-burning inflammation at the edge, and chronic demyelination at the core, of established multiple sclerosis (MS) lesions are potential mediators of disease progression. However, their relative contribution to progressive axonal damage has not been explored. Therefore, in this study, we investigated the comparative contribution of slow-burning inflammation and chronic demyelination to axonal attrition within MS lesions by measuring progressive tissue rarefaction. In addition, we use the visual system as a model to investigate the effect of chronic demyelination on the acceleration of axonal death in a sub-group of patients with unilateral optic neuritis. MethodsPre- and post-gadolinium 3D-T1, 3D FLAIR, diffusion tensor images, Optical Coherence tomography and multifocal visual evoked potentials were acquired from 52 relapsing-remitting MS patients who completed at least 5 years follow-up.Lesion expansion was measured using custom software, and the rate of tissue rarefication inside lesion core was assessed by measuring increase of normalized mean diffusivity (nMD). Axonal loss was also examined in eyes with severe optic nerve demyelination. ResultsAmong the 361 lesions analyzed, 104 were expanding (a minimum of 4 % expansion per year) and 257 were stable. Expanding lesions showed a significantly higher rate of progressive tissue rarefication inside lesion (1.12 % per year) core compared to stable lesions (0.21 % per year, p = 0.01). The magnitude of nMD change was significantly correlated with the rate of lesion expansion (r = 0.4, p < 0.001). Analysis of retinal ganglion cells in eyes with severe optic nerve demyelination (Inter-eye latency delay of >10 ms) revealed a similar rate of axonal loss (0.19 %) to the degree of tissue rarefaction observed in stable lesions (0.21 %). DiscussionThe results of the study suggest that the slow-burning inflammation at the lesion's edge (as measured by lesion expansion), is likely to have a greater impact on tissue damage (as measured by nMD change), when compared to stable chronically demyelinated lesions. The similar modest degree of tissue damage was also observed in chronically demyelinated fibers of the optic nerve.

Subclinical brain manifestations of repeated mild traumatic brain injury are changed by chronic exposure to sleep loss, caffeine, and sleep aids

IntroductionAfter mild traumatic brain injury (mTBI), the brain is labile for weeks and months and vulnerable to repeated concussions. During this time, patients are exposed to everyday circumstances that, in themselves, affect brain metabolism and blood flow and neural processing. How commonplace activities interact with the injured brain is unknown. The present study in an animal model investigated the extent to which three commonly experienced exposures—daily caffeine usage, chronic sleep loss, and chronic sleep aid medication—affect the injured brain in the chronic phase. MethodsSubclinical trauma by repeated mTBIs was produced by our head rotational acceleration injury model, which causes brain injury consistent with the mechanism of concussion in humans. Forty-eight hours after a third mTBI, chronic administrations of caffeine, sleep restriction, or zolpidem (sedative hypnotic) began and were continued for 70 days. On Days 30 and 60 post injury, resting state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were performed. ResultsChronic caffeine, sleep restriction, and zolpidem each changed the subclinical brain characteristics of mTBI at both 30 and 60 days post injury, detected by different MRI modalities. Each treatment caused microstructural alterations in DTI metrics in the insular cortex and retrosplenial cortex compared with mTBI, but also uniquely affected other gray and white matter regions. Zolpidem administration affected the largest number of individual structures in mTBI at both 30 and 60 days, and not necessarily toward normalization (sham treatment). Chronic sleep restriction changed local functional connectivity at 30 days in diametrical opposition to chronic caffeine ingestion, and both treatment outcomes were different from sham, mTBI-only and zolpidem comparisons. The results indicate that commonly encountered exposures modify subclinical brain activity and structure long after healing is expected to be complete. ConclusionsChanges in activity and structure detected by fMRI are widely understood to reflect changes in the functions of the affected region which conceivably underlie mTBI neuropathology and symptomatology in the chronic phase after injury.

Timing of diffusion tensor imaging in the management of a ruptured pediatric arteriovenous malformation: illustrative case.

Diffusion tensor imaging (DTI) can characterize eloquent white matter tracts affected by brain arteriovenous malformations (AVMs). However, DTI interpretation can be difficult in ruptured cases due to the presence of blood products. The authors present the case of a ruptured pediatric AVM in the corticospinal tract (CST) and discuss how DTI at different time points informed the treatment. A 9-year-old female presented with a sudden headache and left hemiparesis. She was found to have a Spetzler-Martin grade III, Supplementary grade I AVM in the right caudate and centrum semiovale, with obliteration and corresponding reduced fractional anisotropy (FA), fiber density (FD), and tract count (TC) of the adjacent CST on DTI. The patient remained stable and was scheduled for elective resection following a 6-week period to facilitate hematoma resorption. After 6 weeks, repeat DTI showed part of the nidus within intact CST fibers with concordant improvement in FA, FD, and TC. Considering the nidus location, CST integrity, and motor function recovery, surgery was deferred in favor of stereotactic radiosurgery. In ruptured AVMs, DTI may initially create an incomplete picture and false assumptions about white matter tract integrity. DTI should be repeated if delayed treatment is appropriate to ensure informed decision-making and prevent avoidable permanent neurological deficits. https://thejns.org/doi/10.3171/CASE24225.

The developing hippocampus: Microstructural evolution through childhood and adolescence.

The hippocampus is a structure in the medial temporal lobe which serves multiple cognitive functions. While important, the development of the hippocampus in the formative period of childhood and adolescence has not been extensively investigated, with most contemporary research focusing on macrostructural measures of volume. Thus, there has been little research on the development of the micron-scale structures (i.e., microstructure) of the hippocampus, which engender its cognitive functions. The current study examined age-related changes of hippocampal microstructure using diffusion MRI data acquired with an ultra-strong gradient (300 mT/m) MRI scanner in a sample of children and adolescents (N=88; 8-19 years). Surface-based hippocampal modelling was combined with established microstructural approaches, such as Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion Density Imaging (NODDI), and a more advanced gray matter diffusion model Soma And Neurite Density Imaging (SANDI). No significant changes in macrostructural measures (volume, gyrification, and thickness) were found between 8-19 years, while significant changes in microstructure measures related to neurites (from NODDI and SANDI), soma (from SANDI), and mean diffusivity (from DTI) were found. In particular, there was a significant increase across age in neurite MR signal fraction and a significant decrease in extracellular MR signal fraction and mean diffusivity across the hippocampal subfields and long-axis. A significant negative correlation between age and MR apparent soma radius was found in the subiculum and CA1 throughout the anterior and body of the hippocampus. Further surface-based analyses uncovered variability in age-related microstructural changes between the subfields and long-axis, which may reflect ostensible developmental differences along these two axes. Finally, correlation of hippocampal surfaces representing age-related changes of microstructure with maps derived from histology allowed for postulation of the potential underlying microstructure that diffusion changes across age may be capturing. Overall, distinct neurite and soma developmental profiles in the human hippocampus during late childhood and adolescence are reported for the first time.

White matter structure and derived network properties are used to predict the progression from mild cognitive impairment of older adults to Alzheimer’s disease

ObjectiveTo identify white matter fiber injury and network changes that may lead to mild cognitive impairment (MCI) progression, then a joint model was constructed based on neuropsychological scales to predict high-risk individuals for Alzheimer's disease (AD) progression among older adults with MCI.MethodsA total of 173 MCI patients were included from the Alzheimer's Disease Neuroimaging Initiative(ADNI) database and randomly divided into training and testing cohorts. Forty-five progressed to AD during a 4-year follow-up period. Diffusion tensor imaging (DTI) techniques extracted relevant DTI quantitative features for each patient. In addition, brain networks were constructed based on white matter fiber bundles to extract network property features. Ensemble dimensionality reduction was applied to reduce both DTI quantitative features and network features from the training cohort, and machine learning algorithms were added to construct white matter signature. In addition, 52 patients from the National Alzheimer's Coordinating Center (NACC) database were used for external validation of white matter signature. A joint model was subsequently generated by combining with scale scores, and its performance was evaluated using data from the testing cohort.ResultsBased on multivariate logistic regression, clinical dementia rating and Alzheimer’s disease assessment scales (CDRS and ADAS, respectively) were selected as independent predictive factors. A joint model was constructed in combination with the white matter signature. The AUC, sensitivity, and specificity in the training cohort were 0.938, 0.937, and 0.91, respectively, and the AUC, sensitivity, and specificity in the test cohort were 0.905, 0.923, and 0.872, respectively. The Delong test showed a statistically significant difference between the joint model and CDRS or ADAS scores (P < 0.05), yet no significant difference between the joint model and the white matter signature (P = 0.341).ConclusionThe present results demonstrate that a joint model combining neuropsychological scales can be constructed by using machine learning and DTI technology to identify MCI patients who are at high-risk of progressing to AD.

BundleAGE: Predicting White Matter Age using Along-Tract Microstructural Profiles from Diffusion MRI.

Brain Age Gap Estimation (BrainAGE) is an estimate of the gap between a person's chronological age (CA) and a measure of their brain's 'biological age' (BA). This metric is often used as a marker of accelerated aging, albeit with some caveats. Age prediction models trained on brain structural and functional MRI have been employed to derive BrainAGE biomarkers, for predicting the risk of neurodegeneration. While voxel-based and along-tract microstructural maps from diffusion MRI have been used to study brain aging, no studies have evaluated along-tract microstructure for computing BrainAGE. In this study, we train machine learning models to predict a person's age using along-tract microstructural profiles from diffusion tensor imaging. We were able to demonstrate differential aging patterns across different white matter bundles and microstructural measures. The novel Bundle Age Gap Estimation (BundleAGE) biomarker shows potential in quantifying risk factors for neurodegenerative diseases and aging, while incorporating finer scale information throughout white matter bundles.

White matter brain-age in diverse forms of epilepsy and interictal psychosis

Abnormal brain aging is suggested in epilepsy. Given the brain network dysfunction in epilepsy, the white matter tracts, which primarily interconnect brain regions, could be of special importance. We focused on white matter brain aging in diverse forms of epilepsy and comorbid psychosis. We obtained brain diffusion tensor imaging (DTI) data at 3 T-MRI in 257 patients with epilepsy and 429 healthy subjects. The tract-based fractional anisotropy values of the healthy subjects were used to build a brain-age prediction model, and we calculated the brain-predicted age difference (brain-PAD: predicted age—chronological age) of all subjects. As a result, almost all epilepsy categories showed significantly increased brain-PAD (p < 0.001), including temporal lobe epilepsy (TLE) with no MRI-lesion (+ 4.2 yr), TLE with hippocampal sclerosis (+ 9.1 yr), extratemporal focal epilepsy (+ 5.1 yr), epileptic encephalopathy or progressive myoclonus epilepsy (+ 18.4 yr), except for idiopathic generalized epilepsy (IGE). Patients with psychogenic non-epileptic seizures also presented increased brain-PAD. In TLE, interictal psychosis significantly raised brain-PAD by 8.7 years. In conclusion, we observed increased brain aging in most types of epilepsy, which was generally consistent with brain morphological aging results in previous studies. Psychosis may accelerate brain aging in TLE. These findings may suggest abnormal aging mechanisms in epilepsy and comorbid psychotic symptoms.

The Association between Individual Food Groups, Limbic System White Matter Tracts, and Episodic Memory: Initial Data from the Aiginition Longitudinal Biomarker Investigation of Neurodegeneration (ALBION) Study.

(1) Background: Many studies link food intake with clinical cognitive outcomes, but evidence for brain biomarkers, such as memory-related limbic white matter (WM) tracts, is limited. We examined the association between food groups, limbic WM tracts integrity, and memory performance in community-dwelling individuals. (2) Methods: We included 117 non-demented individuals (ALBION study). Verbal and visual episodic memory tests were administered, and a composite z-score was calculated. Diffusion tensor imaging tractography was applied for limbic WM tracts (fornix-FX, cingulum bundle-CB, uncinate fasciculus-UF, hippocampal perforant pathway zone-hPPZ). Food intake was evaluated through four 24-h recalls. We applied linear regression models adjusted for demographics and energy intake. (3) Results: We found significant associations between (a) higher low-to-moderate alcohol intake and higher FX fractional anisotropy (FA), (b) higher full-fat dairy intake and lower hPPZ FA, and (c) higher red meat and cold cuts intake and lower hPPZ FA. None of the food groups was associated with memory performance. (4) Conclusions: Despite non-significant associations between food groups and memory, possibly due to participants' cognitive profile and/or compensatory mechanisms, the study documented a possible beneficial role of low-to-moderate alcohol and a harmful role of full-fat dairy and red meat and cold cuts on limbic WM tracts.

Maternal prenatal immune activation associated with brain tissue microstructure and metabolite concentrations in newborn infants

Few human studies have assessed the association of prenatal maternal immune activation (MIA) with measures of brain development and psychiatric risk in newborn offspring. Our goal was to identify the effects of MIA during the 2nd and 3rd trimesters of pregnancy on newborn measures of brain metabolite concentrations, tissue microstructure, and motor development. This was a prospective longitudinal cohort study conducted with nulliparous pregnant women who were aged 14 to 19 years and recruited in their 2nd trimester, as well as their children who were followed through 14 months of age. MIA was indexed by maternal interleukin-6 (IL-6) and C-reactive protein (CRP) in both trimesters of pregnancy.Primary outcomes included: (1) newborn brain metabolite concentrations as ratios to creatine (N-acetylaspartate (NAA)/creatine (Cr) and choline (Cho)/Cr) measured using Magnetic Resonance Spectroscopy; (2) newborn fractional anisotropy and mean diffusivity, measured using Diffusion Tensor Imaging; and (3) indices of motor development, assessed prenatally and postnatally at ages 4- and 14-months. Maternal IL-6 and CRP levels associated significantly with both metabolites in the putamen, thalamus, insula, and the internal capsule. Maternal IL-6 associated significantly with fractional anisotropy in the putamen, caudate, thalamus, insula, and precuneus, and with mean diffusivity in the inferior parietal and middle temporal gyrus. CRP associated significantly with fractional anisotropy in the thalamus, insula, and putamen. Significant associations were found in common regions across imaging modalities, though the direction of associations differed by immune marker. In addition, both maternal IL-6 and CRP (in both trimesters) prenatally associated significantly with offspring motor development at 4- and 14-months of age. The left thalamus mediated effects of IL-6 on postnatal motor development. These findings demonstrate that levels of MIA in mid- to late pregnancy in a generally healthy sample associate with tissue characteristics in newborn brain regions that primarily support motor integration and coordination, as well as behavioral regulation. Those brain effects may contribute to differences in motor development.

Efficacy of personalized repetitive transcranial magnetic stimulation based on functional reserve to enhance ambulatory function in patients with Parkinson’s disease: study protocol for a randomized controlled trial

BackgroundRepetitive transcranial magnetic stimulation (rTMS) is one of the non-invasive brain stimulations that modulate cortical excitability through magnetic pulses. However, the effects of rTMS on Parkinson’s disease (PD) have yielded mixed results, influenced by factors including various rTMS stimulation parameters as well as the clinical characteristics of patients with PD. There is no clear evidence regarding which patients should be applied with which parameters of rTMS. The study aims to investigate the efficacy and safety of personalized rTMS in patients with PD, focusing on individual functional reserves to improve ambulatory function.MethodsThis is a prospective, exploratory, multi-center, single-blind, parallel-group, randomized controlled trial. Sixty patients with PD will be recruited for this study. This study comprises two sub-studies, each structured as a two-arm trial. Participants are classified into sub-studies based on their functional reserves for ambulatory function, into either the motor or cognitive priority group. The Timed-Up and Go (TUG) test is employed under both single and cognitive dual-task conditions (serial 3 subtraction). The motor dual-task effect, using stride length, and the cognitive dual-task effect, using the correct response rate of subtraction, are calculated. In the motor priority group, high-frequency rTMS targets the primary motor cortex of the lower limb, whereas the cognitive priority group receives rTMS over the left dorsolateral prefrontal cortex. The active comparator for each sub-study is bilateral rTMS of the primary motor cortex of the upper limb. Over 4 weeks, the participants will undergo 10 rTMS sessions, with evaluations conducted pre-intervention, mid-intervention, immediately post-intervention, and at 2-month follow-up. The primary outcome is a change in TUG time between the pre- and immediate post-intervention evaluations. The secondary outcome variables are the TUG under cognitive dual-task conditions, Movement Disorder Society-Unified Parkinson’s Disease Rating Scale Part III, New Freezing of Gait Questionnaire, Digit Span, trail-making test, transcranial magnetic stimulation-induced motor-evoked potentials, diffusion tensor imaging, and resting state functional magnetic resonance imaging.DiscussionThe study will reveal the effect of personalized rTMS based on functional reserve compared to the conventional rTMS approach in PD. Furthermore, the findings of this study may provide empirical evidence for an rTMS protocol tailored to individual functional reserves to enhance ambulatory function in patients with PD.Trial registrationClinicalTrials.gov NCT06350617. Registered on 5 April 2024.