White Matter Bundles Research Articles

NIMG-81. PREDICTING TUMOR PROGRESSION WITH FIBER DENSITY-WEIGHTED WHITE MATTER PATHLENGTH MAPS IN PATIENTS WITH GLIOBLASTOMA

Abstract PURPOSE Although histopathological evidence indicates that glioma cells preferentially migrate along large white-matter bundles, standard-of-care (SOC) radiation therapy (RT) planning remains an isotropic expansion of the anatomical lesion. We hypothesize that anisotropic expansion of RT target volumes along white-matter pathways using fiber density-weighted, white-matter pathlength maps (DW-WMPLMs) derived from diffusion tensor imaging (DTI) could improve the prediction of tumor cell migration beyond surgical margins by a deep learning model compared to SOC clinical target volumes (CTVs). METHODS DTI and anatomical MRI from 118 patients newly-diagnosed with glioblastoma were retrospectively analyzed with anatomical imaging from post-surgical resection and latest progression scan before intervention. Parallel-transport tractography seeded from the pre-surgery T2-lesion was used to estimate white-matter fiber propagation. Fibers that intersected with the resection cavity were weighted by their density to control the length of expansion and create a DW-WMPLM that was used together with T2-FLAIR and T1-post-contrast images as inputs to a novel 3D-Swin-UNetR network, trained to predict the recurrence region using 4-fold cross-validation and evaluated in a holdout test-set (95/23 CV/test). New weighted-overlap, coverage, and sparing indices were introduced to evaluate coverage of the progressed lesion and healthy brain excluded. RESULTS 52% of patients had progression outside the standard 2cm-isotropic CTV margin, motivating the need for anisotropic CTVs. Our novel DW-WMPLMs had 87±20% and 83±18% overlap with contrast-enhancing and T2-lesion progression, respectively. The deep-learning model trained with DW-WMPLMs and anatomical images achieved 19% and 56% higher Dice and weighted-overlap indices compared to the isotropic 2cm-CTV(p<0.02), with less normal brain included. CONCLUSION This study demonstrates the feasibility and benefit of incorporating a novel metric of white-matter track characterization into deep learning progression prediction models of glioblastoma for RT-planning. Current work is validating findings in a prospective cohort acquired immediately prior to RT and incorporating other imaging metrics.

Dissociation of White Matter Bundles in Different Recovery Measures in Poststroke Aphasia.

Poststroke aphasia (PSA) recovery shows high variability across individuals and at different time points. Although diffusion biomarkers from the ventral and dorsal streams have demonstrated strong predictive power for language outcomes, it is still unclear how these biomarkers relate to the various stages of PSA recovery. In this study, we aim to compare diffusion metrics and language measures as predictors of language recovery in a longitudinal cohort of participants with PSA. Participants were recruited at a stroke unit at the emergency room, and underwent diffusion magnetic resonance imaging scanning and language assessment within 3 days (acute phase) after stroke, with behavioral follow-ups at subacute (10±3 days) and chronic phases (>6 months). We conducted regression analyses on language performance (cross-sectional), Δscores between all time points (acute-subacute, subacute-chronic, acute-chronic), and relative Δscores between all time points (Δscore/language baseline score), with acute diffusion metrics from language-related white matter tracts, lesion size, language baseline scores, and demographic data as predictors. Thirty-nine participants presenting PSA were recruited, and 24 participants (mean age, 73 years; 8 women) completed the 3-time point assessment in total. The best prediction model of performance scores used axial diffusivity from the left arcuate fasciculus in both the subacute (R2=0.785) and chronic stages (R2=0.626). Moreover, the prediction of ∆scores depended on axial diffusivity from the left inferior frontal-occipital fasciculus in the subacute stage (R2=0.5) and depended additionally on axial diffusivity from the right inferior frontal-occipital fasciculus in the chronic stage (R2=0.68). The prediction of mediation analyses showed that the lesion load of the left arcuate fasciculus mediated the relationship between axial diffusivity from the left arcuate fasciculus and chronic language performance. Language performance at subacute and chronic time points could be predicted by the integrity of the left arcuate fasciculus, whereas Δscores in the subacute and chronic phases depended on the left inferior frontal-occipital fasciculus, showing a dissociation of the white matter pathways about language outcomes. These results suggest a functional differentiation of the dual-stream components in PSA recovery.

Dietary omega-3 polyunsaturated fatty acids reduce cytochrome c oxidase in brain white matter and sensorimotor regions while increasing functional interactions between neural systems related to escape behavior in postpartum rats.

Previously, we showed that omega-3 polyunsaturated fatty acid n-3 (PUFA) supplementation improved the performance of postpartum rats in the shuttle box escape test (SBET). The brains of these rats were used in the current study which examined brain cytochrome c oxidase (CCO) activity in white matter bundles and 39 regions spanning sensorimotor, limbic, and cognitive areas to determine the effects of n-3 PUFAs on neural metabolic capacity and network interactions. We found that n-3 PUFA supplementation decreased CCO activity in white matter bundles, deep and superficial areas within the inferior colliculus, the anterior and barrel field regions of the primary somatic sensorimotor cortex, the secondary somatic sensorimotor cortex, the lateral, anterior regions of the secondary visual cortex and the ventral posterior nucleus of the thalamus, and the medial nucleus of the amygdala. Structural equation modeling revealed that animals consuming diets without n-3 PUFAs exhibited fewer inter-regional interactions when compared to those fed diets with n-3 PUFAs. Without n-3 PUFAs, inter-regional interactions were observed between the posterior cingulate cortex and amygdala as well as among amygdala subregions. With n-3 PUFAs, more inter-regional interactions were observed, particularly between regions associated with fear memory processing and escape. Correlations between regional CCO activity and SBET behavior were observed in rats lacking dietary n-3 PUFAs but not in those supplemented with these nutrients. In conclusion, consumption of n-3 PUFAs results in reduced CCO activity in white matter bundles and sensorimotor regions, reflecting more efficient neurotransmission, and an increase in inter-regional interactions, facilitating escape from footshock.

Ex vivo magnetic resonance imaging of the human fetal brain.

The fetal brain undergoes a dynamic process of development during gestation, marked by well-orchestrated events such as neuronal proliferation, migration, axonal outgrowth, and dendritic arborization, mainly elucidated through histological studies. Ex vivo magnetic resonance imaging (MRI) has emerged as a useful tool for 3D visualization of the developing fetal brain, serving as a complementary tool to traditional histology. In this review, we summarized the commonly employed ex vivo MRI techniques and their advances in fetal brain imaging, as well as a standard protocol for postmortem fetal brain specimen collection and fixation. We then provided an overview of ex vivo MRI-based studies on the fetal brain. According to our review, ex vivo T1- or T2-weighted structural MRI has contributed to the characterization of the anatomy of transient neuronal proliferative zones, the basal ganglia, and the cortex. Diffusion MRI related techniques, such as diffusion tensor imaging and tractography, have helped to investigate the microstructural patterns of fetal brain tissue, as well as the early emergence and development of neuronal migration pathways and white matter bundles. Ex vivo MRI findings have shown strong histological correlations, supporting the potential of MRI in evaluating the developmental events in the fetal brain. Postmortem MRI examinations have also demonstrated comparable, and in certain cases, superior performance to traditional autopsy in revealing fetal brain abnormalities. In conclusion, ex vivo fetal brain MRI is an invaluable tool that provides unique insights into the early stages of brain development.

Fiber Microstructure Quantile (FMQ) Regression: A Novel Statistical Approach for Analyzing White Matter Bundles from Periphery to Core.

The structural connections of the brain's white matter are critical for brain function. Diffusion MRI tractography enables the in-vivo reconstruction of white matter fiber bundles and the study of their relationship to covariates of interest, such as neurobehavioral or clinical factors. In this work, we introduce Fiber Microstructure Quantile (FMQ) Regression, a new statistical approach for studying the association between white matter fiber bundles and scalar factors (e.g., cognitive scores). Our approach analyzes tissue microstructure measures based on quantile-specific bundle regions . These regions are defined according to the quantiles of fractional anisotropy (FA) from the periphery to the core of a population fiber bundle, which pools all individuals' bundles. To investigate how fiber bundle tissue microstructure relates to covariates of interest, we employ the statistical technique of quantile regression. Unlike ordinary regression, which only models a conditional mean, quantile regression models the conditional quantiles of a response variable. This enables the proposed analysis, where a quantile regression is fitted for each quantile-specific bundle region. To demonstrate FMQ Regression, we perform an illustrative study in a large healthy young adult tractography dataset derived from the Human Connectome Project-Young Adult (HCP-YA), focusing on particular bundles expected to relate to particular aspects of cognition and motor function. Importantly, our analysis considers sex-specific effects in brain-behavior associations. In comparison with a traditional method, Automated Fiber Quantification (AFQ), which enables FA analysis in regions defined along the trajectory of a bundle, our results suggest that FMQ Regression is much more powerful for detecting brain-behavior associations. Importantly, FMQ Regression finds significant brain-behavior associations in multiple bundles, including findings unique to males or to females. In both males and females, language performance is significantly associated with FA in the left arcuate fasciculus, with stronger associations in the bundle's periphery. In males only, memory performance is significantly associated with FA in the left uncinate fasciculus, particularly in intermediate regions of the bundle. In females only, motor performance is significantly associated with FA in the left and right corticospinal tracts, with a slightly lower relationship at the bundle periphery and a slightly higher relationship toward the bundle core. No significant relationships are found between executive function and cingulum bundle FA. Our study demonstrates that FMQ Regression is a powerful statistical approach that can provide insight into associations from bundle periphery to bundle core. Our results also identify several brain-behavior relationships unique to males or to females, highlighting the importance of considering sex differences in future research.

Breakdown of TMS evoked EEG signal propagation within the default mode network in Alzheimer’s disease

BackgroundThe neural activity of the Default Mode Network (DMN) is disrupted in patients with In Alzheimer’s disease (AD). ObjectivesWe used a novel multimodal approach to track neural signal propagation within the DMN in AD patients. MethodsTwenty mild to moderate AD patients were recruited. We used transcranial magnetic stimulation (TMS) pulses to probe with a millisecond time resolution the propagation of evoked electroencephalography (EEG) signal following the neural activation of the Precuneus (PC), which is a key hub area of the DMN. Moreover, functional and structural magnetic resonance imaging (MRI) data were collected to reconstruct individual features of the DMN. ResultsIn AD patients a probe TMS pulse applied over the PC evokes an increased local activity unmasking underlying hyperexcitability. In contrast, the EEG evoked neural signal did not propagate efficiently within the DMN showing a remarkable breakdown of signal propagation. fMRI and structural tractography showed that impaired signal propagation was related to the same connectivity matrices derived from DMN BOLD signal and transferred by specific white matter bundles forming the cingulum. These features were not detectable stimulating other areas (left dorsolateral prefrontal cortex) or for different networks (fronto-parietal network). Finally, connectivity breakdown was associated with cognitive impairment, as measured with the Clinical Dementia Rating Scale sum of boxes (CDR-SB). ConclusionsTMS-EEG in AD shows both local hyperexcitability and a lack of signal propagation within the DMN. These neurophysiological features also correlate with structural and cognitive attributes of the patients. SignificanceNeuronavigated TMS-EEG may be used as a novel neurophysiological biomarker of DMN connectivity in AD patients.

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.

Exploration of the white matter bundles connected to the pineal gland: A DTI study.

Pineal gland (PG) is a structure located in the midline of the brain, and is considered as a main part of the epithalamus. There are reports on the role of this area for brain function by hormone secretion, as well as few reports on its role in brain cognition. However, little knowledge is available on the PG, and in particular on the structural connectivity of this region with the other brain structures. Using diffusion-weighted images collected by a 3T MRI scanner, and using a sample of 61 (29F) mentally and physically healthy young individuals in the age range of 20-30 years old, we tried to extract the white matter bundles connected to the PG. Based on prior knowledge, seven target bundles were suggested to be between the PG body and the PG roots, Pons, Periventricular region, thalamus, caudate, lentiform, suprachiasmatic nuclei, and the supercervical ganglia. Nearly all the target bundles were successfully extracted, with the exception of the lentiform. Rate of identification of the tracts was different, with the bundle between the PG body and roots having the highest identification rate (97%); then it was with the Pons (70%), Periventricular region (57%), SCN (55%), left thalamus (52%), right thalamus (47%), left caudate (27%) and right caudate (22%). This study is an attempt to expand our knowledge on the neuroanatomy of the PG, which might help for identifying further roles for it in brain functionality, and also be a help for the treatment of some disorders in the future.

Sub-bundle based analysis reveals the role of human optic radiation in visual working memory.

White matter (WM) functional activity has been reliably detected through functional magnetic resonance imaging (fMRI). Previous studies have primarily examined WM bundles as unified entities, thereby obscuring the functional heterogeneity inherent within these bundles. Here, for the first time, we investigate the function of sub-bundles of a prototypical visual WM tract-the optic radiation (OR). We use the 7T retinotopy dataset from the Human Connectome Project (HCP) to reconstruct OR and further subdivide the OR into sub-bundles based on the fiber's termination in the primary visual cortex (V1). The population receptive field (pRF) model is then applied to evaluate the retinotopic properties of these sub-bundles, and the consistency of the pRF properties of sub-bundles with those of V1 subfields is evaluated. Furthermore, we utilize the HCP working memory dataset to evaluate the activations of the foveal and peripheral OR sub-bundles, along with LGN and V1 subfields, during 0-back and 2-back tasks. We then evaluate differences in 2bk-0bk contrast between foveal and peripheral sub-bundles (or subfields), and further examine potential relationships between 2bk-0bk contrast and 2-back task d-prime. The results show that the pRF properties of OR sub-bundles exhibit standard retinotopic properties and are typically similar to the properties of V1 subfields. Notably, activations during the 2-back task consistently surpass those under the 0-back task across foveal and peripheral OR sub-bundles, as well as LGN and V1 subfields. The foveal V1 displays significantly higher 2bk-0bk contrast than peripheral V1. The 2-back task d-prime shows strong correlations with 2bk-0bk contrast for foveal and peripheral OR fibers. These findings demonstrate that the blood oxygen level-dependent (BOLD) signals of OR sub-bundles encode high-fidelity visual information, underscoring the feasibility of assessing WM functional activity at the sub-bundle level. Additionally, the study highlights the role of OR in the top-down processes of visual working memory beyond the bottom-up processes for visual information transmission. Conclusively, this study innovatively proposes a novel paradigm for analyzing WM fiber tracts at the individual sub-bundle level and expands understanding of OR function.

Comparative analysis of the chimpanzee and human brain superficial structural connectivities

Diffusion MRI tractography (dMRI) has fundamentally transformed our ability to investigate white matter pathways in the human brain. While long-range connections have extensively been studied, superficial white matter bundles (SWMBs) have remained a relatively underexplored aspect of brain connectivity. This study undertakes a comprehensive examination of SWMB connectivity in both the human and chimpanzee brains, employing a novel combination of empirical and geometric methodologies to classify SWMB morphology in an objective manner. Leveraging two anatomical atlases, the Ginkgo Chauvel chimpanzee atlas and the Ginkgo Chauvel human atlas, comprising respectively 844 and 1375 superficial bundles, this research focuses on sparse representations of the morphology of SWMBs to explore the little-understood superficial connectivity of the chimpanzee brain and facilitate a deeper understanding of the variability in shape of these bundles. While similar, already well-known in human U-shape fibers were observed in both species, other shapes with more complex geometry such as 6 and J shapes were encountered. The localisation of the different bundle morphologies, putatively reflecting the brain gyrification process, was different between humans and chimpanzees using an isomap-based shape analysis approach. Ultimately, the analysis aims to uncover both commonalities and disparities in SWMBs between chimpanzees and humans, shedding light on the evolution and organization of these crucial neural structures.

Treatment of vascular dementia in female rats with AV-001, an Angiopoietin-1 mimetic peptide, improves cognitive function.

Vascular dementia (VaD) is a complex neurodegenerative disorder. We previously found that treatment of VaD in middle-aged male rats subjected to multiple microinfarction (MMI) with AV-001, a Tie2 receptor agonist, significantly improves cognitive function. Age and sex affect the development and response of VaD to therapeutic intervention. Thus, the present study investigated the therapeutic effect of AV-001 on VaD in aged female rats subjected to MMI. Female 18-month-old Wistar rats were subjected to MMI by injecting either 1,000 (low dose, LD-MMI) or 6,000 (high dose, HD-MMI) cholesterol crystals of size 70-100 μm into the right internal carotid artery. AV-001 (1 μg/Kg, i.p.) was administered once daily after MMI for 1 month, with treatment initiated 1 day after MMI. A battery of behavioral tests to examine sensorimotor and cognitive functions was performed at 21-28 days after MMI. All rats were sacrificed at 1 month after MMI. Aged female rats subjected to LD-MMI exhibit severe neurological deficits, memory impairment, and significant white matter (WM) and oligodendrogenesis injury in the corpus callosum compared with control rats. HD-MMI in aged female rats induces significant anxiety- and depression-like behaviors, which were not detected in LD-MMI aged female rats. Also, HD-MMI induces significantly increased WM injury compared to LD-MMI. AV-001 treatment of LD-MMI and HD-MMI increases oligodendrogenesis, myelin and axon density in the corpus callosum and striatal WM bundles, promotes WM integrity and attenuates neurological and cognitive deficits. Additionally, both LD-MMI and HD-MMI rats exhibit a significant increase, while AV-001 significantly decreases the levels of inflammatory factors in the cerebrospinal fluid (CSF). MMI reduces oligodendrogenesis, and induces demyelination, axonal injury and WM injury, and causes memory impairment, while HD-MMI induces increased WM injury and further depression-like behaviors compared to LD-MMI rats. AV-001 has a therapeutic effect on aged female rats with MMI by reducing WM damage and improving neuro-cognitive outcomes.

Increased mean diffusivity of the caudal motor SNc identifies patients with REM sleep behaviour disorder and Parkinson’s disease

Idiopathic rapid eye movement sleep behaviour disorder (iRBD)—a Parkinson’s disease (PD) prodrome—might exhibit neural changes similar to those in PD. Substantia nigra pars compacta (SNc) degeneration underlies motor symptoms of PD. In iRBD and early PD (ePD), we measured diffusion MRI (dMRI) in the caudal motor SNc, which overlaps the nigrosome-1—the earliest-degenerating dopaminergic neurons in PD—and in the striatum. Nineteen iRBD, 26 ePD (1.7 ± 0.03 years), and 46 age-matched healthy controls (HCs) were scanned at Western University, and 47 iRBD, 115 ePD (0.9 ± 0.01 years), and 56 HCs were scanned through the Parkinson’s Progression Markers Initiative, using 3T MRI. We segmented the SNc and striatum into subregions using automated probabilistic tractography to the cortex. We measured mean diffusivity (MD) and fractional anisotropy (FA) along white-matter bundles and subregional surfaces. We performed group-level and classification analyses. Increased caudal motor SNc surface MD was the only iRBD-HCs and ePD-HCs difference replicating across datasets (padj < 0.05). No iRBD-ePD differences emerged. Caudal motor SNc surface MD classified patient groups from HCs at the single-subject level with good-to-excellent balanced accuracy in an independent sample (0.91 iRBD and 0.86 iRBD and ePD combined), compared to fair performance for total SNc surface MD (0.72 iRBD and ePD). Caudal motor SNc surface MD correlated significantly with MDS-UPDRS-III scores in ePD patients. Using dMRI and automated segmentation, we detected changes suggesting altered microstructural integrity in iRBD and ePD in the nigrostriatal subregion known to degenerate first in PD. Surface MD of the caudal motor SNc presents a potential measure for inclusion in neuroimaging biomarkers of iRBD and PD.

Topological alterations in white matter anatomical networks in cervical dystonia

BackgroundAccumulating neuroimaging evidence indicates that patients with cervical dystonia (CD) have changes in the cortico-subcortical white matter (WM) bundle. However, whether these patients’ WM structural networks undergo reorganization remains largely unclear. We aimed to investigate topological changes in large-scale WM structural networks in patients with CD compared to healthy controls (HCs), and explore the network changes associated with clinical manifestations.MethodsDiffusion tensor imaging (DTI) was conducted in 30 patients with CD and 30 HCs, and WM network construction was based on the BNA-246 atlas and deterministic tractography. Based on the graph theoretical analysis, global and local topological properties were calculated and compared between patients with CD and HCs. Then, the AAL-90 atlas was used for the reproducibility analyses. In addition, the relationship between abnormal topological properties and clinical characteristics was analyzed.ResultsCompared with HCs, patients with CD showed changes in network segregation and resilience, characterized by increased local efficiency and assortativity, respectively. In addition, a significant decrease of network strength was also found in patients with CD relative to HCs. Validation analyses using the AAL-90 atlas similarly showed increased assortativity and network strength in patients with CD. No significant correlations were found between altered network properties and clinical characteristics in patients with CD.ConclusionOur findings show that reorganization of the large-scale WM structural network exists in patients with CD. However, this reorganization is attributed to dystonia-specific abnormalities or hyperkinetic movements that need further identification.

Association between segmental alterations of white matter bundles and cognitive performance in first-episode, treatment-naïve young adults with major depressive disorder

BackgroundCumulative evidence has consistently shown that white matter (WM) disruption is associated with cognitive decline in geriatric depression. However, limited research has been conducted on the correlation between these lesions and cognitive performance in untreated young adults with major depressive disorder (MDD), particularly with the specific segmental alterations of the fibers. MethodDiffusion tensor images were performed on 60 first-episode, treatment-naïve young adult patients with MDD and 54 matched healthy controls (HCs). Automated fiber quantification was applied to calculate the tract profiles of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) to evaluate the WM microstructural organization. Correlation analysis was performed to find the associations between the diffusion properties and cognitive performance. ResultsCompared with HCs, patients with MDD exhibited predominantly different diffusion properties in bilateral uncinate fasciculus (UF), corticospinal tracts (CSTs), left superior longitudinal fasciculus and anterior thalamic radiation. The FA of the temporal cortex portion of right UF was positively correlated with working memory. The MD of the temporal component of left UF was negatively correlated with working memory and positively correlated with symptom severity. Additionally, a positive correlation between the MD of left CST and the psychomotor speed, negative correlation between the MD of left CST and the executive functions and complex attentional processes were observed. ConclusionsOur study validated the alterations in spatial localization of WM microstructure and its correlations with cognitive performance in first-episode, treatment-naïve young adults with MDD. This study added to the knowledge of the neuropathological basis of MDD.

Human intraparietal sulcal morphology relates to individual differences in language and memory performance

The sulco-gyral pattern is a qualitative feature of the cortical anatomy that is determined in utero, stable throughout lifespan and linked to brain function. The intraparietal sulcus (IPS) is a nodal associative brain area, but the relation between its morphology and cognition is largely unknown. By labelling the left and right IPS of 390 healthy participants into two patterns, according to the presence or absence of a sulcus interruption, here we demonstrate a strong association between the morphology of the right IPS and performance on memory and language tasks. We interpret the results as a morphological advantage of a sulcus interruption, probably due to the underlying white matter organization. The right-hemisphere specificity of this effect emphasizes the neurodevelopmental and plastic role of sulcus morphology in cognition prior to lateralisation processes. The results highlight a promising area of investigation on the relationship between cognitive performance, sulco-gyral pattern and white matter bundles.

Selective Alteration of the Left Arcuate Fasciculus in Two Patients Affected by Creatine Transporter Deficiency.

(1) Background: In hereditary creatine transporter deficiency (CTD), there is an absence of creatine in the brain and neurological symptoms are present, including severe language impairment. However, the pathological changes caused by creatine deficiency that generate neuropsychological symptoms have been poorly studied. (2) Aims: To investigate if the language impairment in CTD is underpinned by possible pathological changes. (3) Methods: We used MRI tractography to investigate the trophism of the left arcuate fasciculus, a white matter bundle connecting Wernicke's and Broca's language areas that is specifically relevant for language establishment and maintenance, in two patients (28 and 18 y.o.). (4) Results: The T1 and T2 MRI imaging results were unremarkable, but the left arcuate fasciculus showed a marked decrease in mean fractional anisotropy (FA) compared to healthy controls. In contrast, the FA values in the corticospinal tract were similar to those of healthy controls. Although white matter atrophy has been reported in CTD, this is the first report to show a selective abnormality of the language-relevant arcuate fasciculus, suggesting a possible region-specific impact of creatine deficiency.

Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study.

Multi-shell diffusion Magnetic Resonance Imaging (dMRI) data has been widely used to characterise white matter microstructure in several neurodegenerative diseases. The lack of standardised dMRI protocols often implies the acquisition of redundant measurements, resulting in prolonged acquisition times. In this study, we investigate the impact of the number of gradient directions on Diffusion Tensor Imaging (DTI) and on Neurite Orientation Dispersion and Density Imaging (NODDI) metrics. Data from 124 healthy controls collected in three different longitudinal studies were included. Using an in-house algorithm, we reduced the number of gradient directions in each data shell. We estimated DTI and NODDI measures on six white matter bundles clinically relevant for neurodegenerative diseases. Fractional Anisotropy (FA) measures on bundles where data were sampled at the 30% rate, showed a median L1 distance of up to 3.92% and a 95% CI of (1.74, 8.97)% when compared to those obtained at reference sampling. Mean Diffusivity (MD) reached up to 4.31% and a 95% CI of (1.60, 16.98)% on the same premises. At a sampling rate of 50%, we obtained a median of 3.90% and a 95% CI of (1.99, 16.65)% in FA, and 5.49% with a 95% CI of (2.14, 21.68)% in MD. The Intra-Cellular volume fraction (ICvf) median L1 distance was up to 2.83% with a 95% CI of (1.98, 4.82)% at a 30% sampling rate and 3.95% with a 95% CI of (2.39, 7.81)% at a 50% sampling rate. The volume difference of the reconstructed white matter at reference and 50% sampling reached a maximum of (2.09 ± 0.81)%. In conclusion, DTI and NODDI measures reported at reference sampling were comparable to those obtained when the number of dMRI volumes was reduced by up to 30%. Close to reference DTI and NODDI metrics were estimated with a significant reduction in acquisition time using three shells, respectively with: 4 directions at a b value of 700 s/mm2, 14 at 1000 s/mm2, and 32 at 2000 s/mm2. The study revealed aspects that can be important for large-scale clinical studies on bundle-specific diffusion MRI.

A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging.

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of 26 participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n = 20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.

Cortical white matter microstructural alterations underlying the impaired gamma-band auditory steady-state response in schizophrenia

The gamma-band auditory steady-state response (ASSR), primarily generated from the auditory cortex, has received substantial attention as a potential brain marker indicating the pathophysiology of schizophrenia. Previous studies have shown reduced gamma-band ASSR in patients with schizophrenia and demonstrated correlations with impaired neurocognition and psychosocial functioning. Recent studies in clinical and healthy populations have suggested that the neural substrates of reduced gamma-band ASSR may be distributed throughout the cortices surrounding the auditory cortex, especially in the right hemisphere. This study aimed to investigate associations between the gamma-band ASSR and white matter alterations in the bundles broadly connecting the right frontal, parietal and occipital cortices to clarify the networks underlying reduced gamma-band ASSR in patients with schizophrenia. We measured the 40 Hz ASSR using electroencephalography and diffusion tensor imaging in 42 patients with schizophrenia and 22 healthy comparison subjects. The results showed that the gamma-band ASSR was positively correlated with fractional anisotropy (an index of white matter integrity) in the regions connecting the right frontal, parietal and occipital cortices in healthy subjects (β = 0.41, corrected p = 0.075, uncorrected p = 0.038) but not in patients with schizophrenia (β = 0.17, corrected p = 0.46, uncorrected p = 0.23). These findings support our hypothesis that the generation of gamma-band ASSR is supported by white matter bundles that broadly connect the cortices and that these relationships may be disrupted in schizophrenia. Our study may help characterize and interpret reduced gamma-band ASSR as a useful brain marker of schizophrenia.

Selection of Appropriate Approaches to Preserve Brain Function for Deep Seated Brain Tumors:Our Experience of Two Posterior Thalamic Cases

What is the most important factor to achieve successful surgery for deep-seated brain tumors with preservation of brain functions? Definitely, it is to identify the tumor origin site at which a tumor arose and select appropriate surgical approaches that immediately lead directly to the site in the early stage of surgery, minimizing damages of cortices and important white matter bundles, and controlling main arterial supply to the tumor. For this, neurosurgeons must have thorough knowledge of brain anatomy and function, and tailor the best surgical approach for each patient, based on three-dimensional anatomical simulation. For lesions situated in the posterior and lower part of the thalamus and extending to the lateral part, two "cross-court" approaches; the occipital transtentorial/falcine and infratentorial supracerebellar transtentorial approaches, provide a wide corridor to even the lateral aspect of the thalamus and early access to the posterior choroidal arteries, usually main feeders of this territory tumors, without damaging any cerebral cortices and major white matter bundles. Here, we describe the selection of approaches for two representative cases and demonstrate surgical procedures and postoperative courses.