Partial volume effect as a hidden covariate in DTI analyses

Free water-corrected fractional anisotropy of the fornix and parahippocampal cingulum predicts longitudinal memory change in cognitively healthy older adults

Prior studies have reported inconsistent results regarding the relationships between the integrity of the fornix and parahippocampal cingulum and both memory performance and longitudinal change in performance. In the present study, we examined associations in a sample of cognitively healthy older adults between free water-corrected fractional anisotropy (FA) metrics derived from the fornix and cingulum, baseline memory performance, and 3-year memory change. Neither fornix nor cingulum FA correlated with memory performance at baseline. By contrast, FA of each tract was predictive of memory change, such that greater FA was associated with less longitudinal decline. These associations remained significant after controlling for FA of other white matter tracts and for performance in other cognitive domains. Furthermore, fornix and cingulum FA explained unique variance in memory change. These results suggest that free water-corrected measures of fornix and parahippocampal cingulum integrity are reliable predictors of future memory change in cognitively healthy older adults. The findings for the fornix in particular highlight the utility of correcting for free water when estimating diffusion tensor imaging metrics of white matter integrity.

Quantitative metrics commonly derived from diffusion tractography covary with streamline length: a characterization and method of adjustment

Tractography algorithms are used extensively to delineate white matter structures, by operating on the voxel-wise information generated through the application of diffusion tensor imaging (DTI) or other models to diffusion weighted (DW) magnetic resonance imaging (MRI) data. Through statistical modelling, we demonstrate that these methods commonly yield substantial and systematic associations between streamline length and several tractography derived quantitative metrics, such as fractional anisotropy (FA). These associations may be described as piecewise linear. For streamlines shorter than an inflection point (determined for a group of tracts delineated for each individual brain), estimates of FA exhibit a positive linear relation with streamline length. For streamlines longer than the point of inflection, the association is weaker, with the slope of the relationship between streamline length and FA differing only marginally from zero. As the association is most pronounced for a range of streamline lengths encountered typically in DW imaging of the human brain (less than ~ 100 mm), our results suggest that some quantitative metrics derived from diffusion tractography have the potential to mislead, if variations in streamline length are not considered. A method is described, whereby an Akaike information weighted average of linear, Blackman and piecewise linear model predictions, may be used to compensate effectively for the association of FA (and other quantitative metrics) with streamline length, across the entire range of streamline lengths present in each specimen.

Unveiling the axonal connectivity between the precuneus and temporal pole: Structural evidence from the cingulum pathways

Neuroimaging studies have consistently demonstrated concurrent activation of the human precuneus and temporal pole (TP), both during resting-state conditions and various higher-order cognitive functions. However, the precise underlying structural connectivity between these brain regions remains uncertain despite significant advancements in neuroscience research. In this study, we investigated the connectivity of the precuneus and TP by employing parcellation-based fiber micro-dissections in human brains and fiber tractography techniques in a sample of 1065 human subjects and a sample of 41 rhesus macaques. Our results demonstrate the connectivity between the posterior precuneus area POS2 and the areas 35, 36, and TG of the TP via the fifth subcomponent of the cingulum (CB-V) also known as parahippocampal cingulum. This finding contributes to our understanding of the connections within the posteromedial cortices, facilitating a more comprehensive integration of anatomy and function in both normal and pathological brain processes. PRACTITIONER POINTS: Our investigation delves into the intricate architecture and connectivity patterns of subregions within the precuneus and temporal pole, filling a crucial gap in our knowledge. We revealed a direct axonal connection between the posterior precuneus (POS2) and specific areas (35, 35, and TG) of the temporal pole. The direct connections are part of the CB-V pathway and exhibit a significant association with the cingulum, SRF, forceps major, and ILF. Population-based human tractography and rhesus macaque fiber tractography showed consistent results that support micro-dissection outcomes.

Tensor-valued diffusion MRI detects brain microstructure changes in HIV infected individuals with cognitive impairment

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. This study aimed to investigate the sensitivity of tensor-valued diffusion encoding in detecting such changes in brain microstructural integrity in cART-treated PWH. Additionally, it explored relationships between these metrics, neurocognitive scores, and plasma levels of neurofilament light (NFL) chain and glial fibrillary acidic protein (GFAP). Using MRI at 3T, 24 PWH and 31 healthy controls underwent cross-sectional examination. The results revealed significant variations in b-tensor encoding metrics across white matter regions, with associations observed between these metrics, cognitive performance, and blood markers of neuronal and glial injury (NFL and GFAP). Moreover, a significant interaction between HIV status and imaging metrics was observed, particularly impacting total cognitive scores in both gray and white matter. These findings suggest that b-tensor encoding metrics offer heightened sensitivity in detecting subtle changes associated with axonal injury in HIV infection, underscoring their potential clinical relevance in understanding neurocognitive impairment in PWH.

Advancements in Diffusion MRI Tractography for Neurosurgery

ABSTRACT

Diffusion magnetic resonance imaging tractography is a noninvasive technique that enables the visualization and quantification of white matter tracts within the brain. It is extensively used in preoperative planning for brain tumors, epilepsy, and functional neurosurgical procedures such as deep brain stimulation. Over the past 25 years, significant advancements have been made in imaging acquisition, fiber direction estimation, and tracking methods, resulting in considerable improvements in tractography accuracy. The technique enables the mapping of functionally critical pathways around surgical sites to avoid permanent functional disability. When the limitations are adequately acknowledged and considered, tractography can serve as a valuable tool to safeguard critical white matter tracts and provides insight regarding changes in normal white matter and structural connectivity of the whole brain beyond local lesions. In functional neurosurgical procedures such as deep brain stimulation, it plays a significant role in optimizing stimulation sites and parameters to maximize therapeutic efficacy and can be used as a direct target for therapy. These insights can aid in patient risk stratification and prognosis. This article aims to discuss state-of-the-art tractography methodologies and their applications in preoperative planning and highlight the challenges and new prospects for the use of tractography in daily clinical practice.

Probing brain tissue microstructure with MRI: principles, challenges, and the role of multidimensional diffusion-relaxation encoding

Diffusion MRI uses the random displacement of water molecules to sensitize the signal to brain microstructure and to properties such as the density and shape of cells. Microstructure modeling techniques aim to estimate these properties from acquired data by separating the signal between virtual tissue 'compartments' such as the intra-neurite and the extra-cellular space. A key challenge is that the diffusion MRI signal is relatively featureless compared with the complexity of brain tissue. Another challenge is that the tissue microstructure is wildly different within the gray and white matter of the brain. In this review, we use results from multidimensional diffusion encoding techniques to discuss these challenges and their tentative solutions. Multidimensional encoding increases the information content of the data by varying not only the b-value and the encoding direction but also additional experimental parameters such as the shape of the b-tensor and the echo time. Three main insights have emerged from such encoding. First, multidimensional data contradict common model assumptions on diffusion and T2 relaxation, and illustrates how the use of these assumptions cause erroneous interpretations in both healthy brain and pathology. Second, many model assumptions can be dispensed with if data are acquired with multidimensional encoding. The necessary data can be easily acquired in vivo using protocols optimized to minimize Cramér-Rao lower bounds. Third, microscopic diffusion anisotropy reflects the presence of axons but not dendrites. This insight stands in contrast to current 'neurite models' of brain tissue, which assume that axons in white matter and dendrites in gray matter feature highly similar diffusion. Nevertheless, as an axon-based contrast, microscopic anisotropy can differentiate gray and white matter when myelin alterations confound conventional MRI contrasts.

Reproducibility of diffusion tensor imaging-derived parameters: implications for the streptozotocin-induced type 1 diabetic rats

OBJECTIVE

Diffusion tensor imaging (DTI) is a useful approach for studying neuronal integrity in animals. However, the test-retest reproducibility of DTI techniques in animals has not been discussed. Therefore, the first part of this work was to systematically elucidate the reliability of DTI-derived parameters in an animal study. Subsequently, we applied the DTI approach to an animal model of diabetes in a longitudinal manner.

MATERIALS AND METHODS

In Study 1, nine rats underwent two DTI sessions using the same scanner and protocols, with a gap of 4 weeks. The reliability of the DTI-derived parameters was evaluated in terms of sessions and raters. In Study 2, nine rats received a single intraperitoneal injection of 70 mg/kg streptozotocin (STZ) to develop diabetes. Longitudinal DTI scans were used to assess brain alterations before and 4 weeks after STZ administration.

RESULTS

In the test-retest evaluation, the inter-scan coefficient of variation (CoV) ranged from 3.04 to 3.73% and 2.12-2.59% for fractional anisotropy (FA) and mean diffusivity (MD), respectively, in different brain regions, suggesting excellent reproducibility. Moreover, rater-dependence had minimal effects on FA and MD quantification, with all inter-rater CoV values less than 4%. Following the onset of diabetes, FA in striatum and cortex were noted to be significantly lower relative to the period where they had not developed diabetes (both P < 0.05). However, when compared to the control group, a significant change in FA caused by diabetes was detected only in the striatum (P < 0.05), but not in the cortex.

CONCLUSION

These results demonstrate good inter-rater and inter-scan reliability of DTI in animal studies, and the longitudinal setting has a beneficial effect on detecting small changes in the brain due to diseases.

Long-term associations between early-life family functioning and preadolescent white matter microstructure

BACKGROUND

Causes of childhood behavior problems remain poorly understood. Enriched family environments and corresponding brain development may reduce the risk of their onset, but research investigating white matter neurodevelopmental pathways explaining associations between the family environment and behavior remains limited. We hypothesized that more positive prenatal and mid-childhood family functioning - a measure of a family's problem solving and supportive capacity - would be associated with two markers of preadolescent white matter neurodevelopment related to reduced behavior problems: higher global fractional anisotropy (FA) and lower global mean diffusivity (MD).

METHODS

Data are from 2727 families in the Generation R Study, the Netherlands. Mothers reported family functioning (McMaster Family Assessment Device, range 1-4, higher scores indicate healthier functioning) prenatally and in mid-childhood (mean age 6.1 years). In preadolescence (mean age 10.1), the study collected diffusion-weighted scans. We computed standardized global MD and FA values by averaging metrics from 27 white matter tracts, and we fit linear models adjusting for possible confounders to examine global and tract-specific outcomes.

RESULTS

Prenatal and mid-childhood family functioning scores were moderately correlated, r = 0.38. However, only prenatal family functioning - and not mid-childhood functioning - was associated with higher global FA and lower global MD in preadolescence in fully adjusted models: βglobal FA = 0.11 (95% CI 0.00, 0.21) and βglobal MD = -0.15 (95% CI -0.28, -0.03) per one-unit increase in functioning score. Sensitivity and tract-specific analyses supported these global findings.

CONCLUSIONS

These results suggest high-functioning prenatal or perinatal family environments may confer lasting white matter neurodevelopmental benefits into preadolescence.

White matter microstructural metrics are sensitively associated with clinical staging in Alzheimer's disease

Introduction

White matter microstructure may be abnormal along the Alzheimer's disease (AD) continuum.

Methods

Diffusion magnetic resonance imaging (dMRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 627), Baltimore Longitudinal Study of Aging (BLSA, n = 684), and Vanderbilt Memory & Aging Project (VMAP, n = 296) cohorts were free-water (FW) corrected and conventional, and FW-corrected microstructural metrics were quantified within 48 white matter tracts. Microstructural values were subsequently harmonized using the Longitudinal ComBat technique and inputted as independent variables to predict diagnosis (cognitively unimpaired [CU], mild cognitive impairment [MCI], AD). Models were adjusted for age, sex, race/ethnicity, education, apolipoprotein E (APOE) ε4 carrier status, and APOE ε2 carrier status.

Results

Conventional dMRI metrics were associated globally with diagnostic status; following FW correction, the FW metric itself exhibited global associations with diagnostic status, but intracellular metric associations were diminished.

Discussion

White matter microstructure is altered along the AD continuum. FW correction may provide further understanding of the white matter neurodegenerative process in AD.

Highlights

Longitudinal ComBat successfully harmonized large-scale diffusion magnetic resonance imaging (dMRI) metrics.Conventional dMRI metrics were globally sensitive to diagnostic status.Free-water (FW) correction mitigated intracellular associations with diagnostic status.The FW metric itself was globally sensitive to diagnostic status. Multivariate conventional and FW-corrected models may provide complementary information.

Alcohol use disorder: Neuroimaging evidence for accelerated aging of brain morphology and hypothesized contribution to age-related dementia

Excessive alcohol use curtails longevity by rendering intoxicated individuals vulnerable to heightened risk from accidents, violence, and alcohol poisoning, and makes chronically heavy drinkers vulnerable to acceleration of age-related medical and psychiatric conditions that can be life threatening (Yoon, Chen, Slater, Jung, & White, 2020). Thus, studies of factors influencing age-alcohol interactions must consider the potential that the alcohol use disorder (AUD) population may not represent the oldest ages of the unaffected population and may well have accrued comorbidities associated with both AUD and aging itself. Herein, we focus on the aging of the brains of men and women with AUD, keeping AUD contextual factors in mind. Knowledge of the potential influence of the AUD-associated co-factors on the condition of brain structure may lead to identifying modifiable risk factors to avert physical declines and may reverse or arrest further AUD-related degradation of the brain. In this narrative review, we 1) describe quantitative, controlled studies of brain macrostructure and microstructure of adults with AUD, 2) consider the possibility of recovery of brain integrity through harm reduction with sustained abstinence or reduced drinking, and 3) speculate on the ramifications of accelerated aging in AUD as contributing to age-related dementia.

Diffusion tensor imaging of superficial prefrontal white matter in healthy aging

The prefrontal cortex (PFC) is a heterogenous structure that is highly susceptible to the effects of aging. Few studies have investigated age effects on the superficial white matter (WM) contained within the PFC using in-vivo magnetic resonance imaging (MRI). This study used diffusion tensor imaging (DTI) tractography to examine the effects of age, sex, and intracranial volume (ICV) on superficial WM within specific PFC subregions, and to model the relationships with age using higher order polynomial regression modelling. PFC WM of 140 healthy individuals, aged 18-85, was segmented into medial and lateral orbitofrontal, medial prefrontal, and dorsolateral prefrontal subregions. Differences due to age in microstructural parameters such as fractional anisotropy (FA), axial and radial diffusivities, and macrostructural measures of tract volumes, fiber counts, average fiber lengths, and average number of fibers per voxel were examined. We found that most prefrontal subregions demonstrated age effects, with decreases in FA, tract volume, and fiber counts, and increases in all diffusivity measures. Age relationships were mostly non-linear, with higher order regressions chosen in most cases. Declines in PFC FA began at the onset of adulthood while the greatest changes in diffusivity and volume did not occur until middle age. The effects of age were most prominent in medial tracts while the lateral orbitofrontal tracts were less affected. Significant effects of sex and ICV were also observed in certain parameters. The patterns mostly followed myelination order, with late-myelinating prefrontal subregions experiencing earlier and more pronounced age effects, further supporting the frontal theory of aging.

Estimation of free water-corrected microscopic fractional anisotropy

Water diffusion anisotropy MRI is sensitive to microstructural changes in the brain that are hallmarks of various neurological conditions. However, conventional metrics like fractional anisotropy are confounded by neuron fiber orientation dispersion, and the relatively low resolution of diffusion-weighted MRI gives rise to significant free water partial volume effects in many brain regions that are adjacent to cerebrospinal fluid. Microscopic fractional anisotropy is a recent metric that can report water diffusion anisotropy independent of neuron fiber orientation dispersion but is still susceptible to free water contamination. In this paper, we present a free water elimination (FWE) technique to estimate microscopic fractional anisotropy and other related diffusion indices by implementing a signal representation in which the MRI signal within a voxel is assumed to come from two distinct sources: a tissue compartment and a free water compartment. A two-part algorithm is proposed to rapidly fit a set of diffusion-weighted MRI volumes containing both linear- and spherical-tensor encoding acquisitions to the representation. Simulations and in vivo acquisitions with four healthy volunteers indicated that the FWE method may be a feasible technique for measuring microscopic fractional anisotropy and other indices with greater specificity to neural tissue characteristics than conventional methods.

Fiber-specific structural properties relate to reading skills in children and adolescents

Recent studies suggest that the cross-sectional relationship between reading skills and white matter microstructure, as indexed by fractional anisotropy, is not as robust as previously thought. Fixel-based analyses yield fiber-specific micro- and macrostructural measures, overcoming several shortcomings of the traditional diffusion tensor model. We ran a whole-brain analysis investigating whether the product of fiber density and cross-section (FDC) related to single-word reading skills in a large, open, quality-controlled dataset of 983 children and adolescents ages 6-18. We also compared FDC between participants with (n = 102) and without (n = 570) reading disabilities. We found that FDC positively related to reading skills throughout the brain, especially in left temporoparietal and cerebellar white matter, but did not differ between reading proficiency groups. Exploratory analyses revealed that among metrics from other diffusion models - diffusion tensor imaging, diffusion kurtosis imaging, and neurite orientation dispersion and density imaging - only the orientation dispersion and neurite density indexes from NODDI were associated (inversely) with reading skills. The present findings further support the importance of left-hemisphere dorsal temporoparietal white matter tracts in reading. Additionally, these results suggest that future DWI studies of reading and dyslexia should be designed to benefit from advanced diffusion models, include cerebellar coverage, and consider continuous analyses that account for individual differences in reading skill.

Investigating Tissue-Specific Abnormalities in Alzheimer's Disease with Multi-Shell Diffusion MRI

BACKGROUND

Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer's disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM.

OBJECTIVE

In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and controls.

METHODS

By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons.

RESULTS

Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus.

CONCLUSION

This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset.

Sensory processing sensitivity and axonal microarchitecture: identifying brain structural characteristics for behavior

Previous research using functional MRI identified brain regions associated with sensory processing sensitivity (SPS), a proposed normal phenotype trait. To further validate SPS, to characterize it anatomically, and to test the usefulness in psychology of methodologies that assess axonal properties, the present study correlated SPS proxy questionnaire scores (adjusted for neuroticism) with diffusion tensor imaging (DTI) measures. Participants (n = 408) from the Human Connectome Project were studied. Voxelwise analysis showed that mean- and radial diffusivity correlated positively with SPS scores in the right and left subcallosal and anterior-ventral cingulum bundle, and the right forceps minor of the corpus callosum, all frontal cortex areas generally underlying emotion, motivation, and cognition. Further analyses showed correlations throughout medial frontal cortical regions in the right and left ventromedial prefrontal cortex, including the superior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate, and arcuate fasciculus. Fractional anisotropy was negatively correlated with SPS scores in white matter (WM) of the right premotor/motor/somatosensory/supramarginal gyrus regions. Region of interest (ROI) analysis showed small effect sizes (- 0.165 to 0.148) in WM of the precuneus and inferior frontal gyrus. Other ROI effects were found in the dorsal-, ventral visual pathways and primary auditory cortex. The results reveal that in a large group of participants, axonal microarchitectural differences can be identified with SPS traits that are subtle and in the range of typical behavior. The results suggest that the heightened sensory processing in people who show that SPS may be influenced by the microstructure of WM in specific cortical regions. Although previous fMRI studies had identified most of these areas, the DTI results put a new focus on brain areas related to attention and cognitive flexibility, empathy, emotion, and first levels of sensory processing, as in primary auditory cortex. Psychological trait characterization may benefit from DTI methodology by identifying influential brain systems for traits.

Rapid Diffusion Magnetic Resonance Imaging Using Slice-Interleaved Encoding

In this paper, we present a robust reconstruction scheme for diffusion MRI (dMRI) data acquired using slice-interleaved diffusion encoding (SIDE). When combined with SIDE undersampling and simultaneous multi-slice (SMS) imaging, our reconstruction strategy is capable of significantly reducing the amount of data that needs to be acquired, enabling high-speed diffusion imaging for pediatric, elderly, and claustrophobic individuals. In contrast to the conventional approach of acquiring a full diffusion-weighted (DW) volume per diffusion wavevector, SIDE acquires in each repetition time (TR) a volume that consists of interleaved slice groups, each group corresponding to a different diffusion wavevector. This strategy allows SIDE to rapidly acquire data covering a large number of wavevectors within a short period of time. The proposed reconstruction method uses a diffusion spectrum model and multi-dimensional total variation to recover full DW images from DW volumes that are slice-undersampled due to unacquired SIDE volumes. We formulate an inverse problem that can be solved efficiently using the alternating direction method of multipliers (ADMM). Experiment results demonstrate that DW images can be reconstructed with high fidelity even when the acquisition is accelerated by 25 folds.

Sex interaction of white matter microstructure and verbal IQ in corpus callosum in typically developing children and adolescents

BACKGROUND

Childhood is an extremely important time for neural development that has a critical role in human intelligence. Efficient information processing is crucial for higher intelligence, so the intra- or inter-hemispheric interaction is vital. However, the relationship between neuroanatomical connections and intelligence in typically developing children, as well as sex differences in this relationship, remains unknown.

METHODS

Participants were 253 typically developing children (121 boys and 132 girls) aged 5-18. We acquired diffusion tensor imaging data and intelligence using an age-appropriate version of the IQ test; Wechsler Intelligence Scale for Children (WISC) or Wechsler Adult Intelligence Scale (WAIS). We conducted whole-brain multiple regression analysis to investigate the association between fractional anisotropy (FA), which reflects white matter microstructural properties, and each composite score of IQ test (full-scale IQ, performance IQ, and verbal IQ).

RESULTS

FA was positively correlated with full-scale IQ in bilateral inferior occipitofrontal fasciculus, genu, and splenium of corpus callosum (CC). FA in the right superior longitudinal fasciculus, bilateral inferior longitudinal fasciculus, and splenium of CC were also positively correlated with performance IQ. Furthermore, we found significant sex interaction between FA in the CC and verbal IQ. FA was positively correlated in boys, and negatively correlated in girls.

CONCLUSION

Results suggest that efficient anatomical connectivity between parietal and frontal regions is crucial for children's intelligence. Moreover, inter-hemispheric connections play a critical role in verbal abilities in boys.

Reduced asymmetry of the hand knob area and decreased sensorimotor u-fiber connectivity in middle-aged adults with autism

Individuals with autism spectrum disorder (ASD) frequently present with impairments in motor skills (e.g., limb coordination, handwriting and balance), which are observed across the lifespan but remain largely untreated. Many adults with ASD may thus experience adverse motor outcomes in aging, when physical decline naturally occurs. The 'hand knob' of the sensorimotor cortex is an area that is critical for motor control of the fingers and hands. However, this region has received little attention in ASD research, especially in adults after midlife. The hand knob area of the precentral (PrC_hand) and postcentral (PoC_hand) gyri was semi-manually delineated in 49 right-handed adults (25 ASD, 24 typical comparison [TC] participants, aged 41-70 years). Using multimodal (T1-weighted, diffusion-weighted, and resting-state functional) MRI, we examined the morphology, ipsilateral connectivity and laterality of these regions. We also explored correlations between hand knob measures with motor skills and autism symptoms, and between structural and functional connectivity measures. Bayesian analyses indicated moderate evidence of group effects with greater right PrC_hand volume and reduced leftward laterality of PrC_hand and PoC_hand volume in the ASD relative to TC group. Furthermore, the right PoC-PrC_hand u-fibers showed increased mean diffusivity in the ASD group. In the ASD group, right u-fiber volume positively correlated with corresponding functional connectivity but did not survive multiple comparisons correction. Correlations of hand knob measures and behavior were observed in the ASD group but did not survive multiple comparisons correction. Our findings suggest that morphological laterality and u-fiber connectivity of the sensorimotor network, putatively involved in hand motor/premotor function, may be diminished in middle-aged adults with ASD, perhaps rendering them more vulnerable to motor decline in old age. The altered morphology may relate to atypical functional motor asymmetries found in ASD earlier in life, possibly reflecting altered functional asymmetries over time.

Structural and Functional Brain Connectivity Uniquely Contribute to Episodic Memory Performance in Older Adults

In this study, we examined the independent contributions of structural and functional connectivity markers to individual differences in episodic memory performance in 107 cognitively normal older adults from the BIOCARD study. Structural connectivity, defined by the diffusion tensor imaging (DTI) measure of radial diffusivity (RD), was obtained from two medial temporal lobe white matter tracts: the fornix and hippocampal cingulum, while functional connectivity markers were derived from network-based resting state functional magnetic resonance imaging (rsfMRI) of five large-scale brain networks: the control, default, limbic, dorsal attention, and salience/ventral attention networks. Hierarchical and stepwise linear regression methods were utilized to directly compare the relative contributions of the connectivity modalities to individual variability in a composite delayed episodic memory score, while also accounting for age, sex, cerebrospinal fluid (CSF) biomarkers of amyloid and tau pathology (i.e., Aβ₄₂/Aβ₄₀ and p-tau₁₈₁), and gray matter volumes of the entorhinal cortex and hippocampus. Results revealed that fornix RD, hippocampal cingulum RD, and salience network functional connectivity were each significant independent predictors of memory performance, while CSF markers and gray matter volumes were not. Moreover, in the stepwise model, the addition of sex, fornix RD, hippocampal cingulum RD, and salience network functional connectivity each significantly improved the overall predictive value of the model. These findings demonstrate that both DTI and rsfMRI connectivity measures uniquely contributed to the model and that the combination of structural and functional connectivity markers best accounted for individual variability in episodic memory function in cognitively normal older adults.

White matter abnormalities characterize the acute stage of sports-related mild traumatic brain injury

Sports-related concussion, a form of mild traumatic brain injury, is characterized by transient disturbances of brain function. There is increasing evidence that functional brain changes may be driven by subtle abnormalities in white matter microstructure, and diffusion MRI has been instrumental in demonstrating these white matter abnormalities in vivo. However, the reported location and direction of the observed white matter changes in mild traumatic brain injury are variable, likely attributable to the inherent limitations of the white matter models used. This cross-sectional study applies an advanced and robust technique known as fixel-based analysis to investigate fibre tract-specific abnormalities in professional Australian Football League players with a recent mild traumatic brain injury. We used the fixel-based analysis framework to identify common abnormalities found in specific fibre tracts in participants with an acute injury (≤12 days after injury; n = 14). We then assessed whether similar changes exist in subacute injury (&gt;12 days and &lt;3 months after injury; n = 15). The control group was 29 neurologically healthy control participants. We assessed microstructural differences in fibre density and fibre bundle morphology and performed whole-brain fixel-based analysis to compare groups. Subsequent tract-of-interest analyses were performed within five selected white matter tracts to investigate the relationship between the observed tract-specific abnormalities and days since injury and the relationship between these tract-specific changes with cognitive abnormalities. Our whole-brain analyses revealed significant increases in fibre density and bundle cross-section in the acute mild traumatic brain injury group when compared with controls. The acute mild traumatic brain injury group showed even more extensive differences when compared with the subacute injury group than with controls. The fibre structures affected in acute concussion included the corpus callosum, left prefrontal and left parahippocampal white matter. The fibre density and cross-sectional increases were independent of time since injury in the acute injury group, and were not associated with cognitive deficits. Overall, this study demonstrates that acute mild traumatic brain injury is characterized by specific white matter abnormalities, which are compatible with tract-specific cytotoxic oedema. These potential oedematous changes were absent in our subacute mild traumatic brain injury participants, suggesting that they may normalize within 12 days after injury, although subtle abnormalities may persist in the subacute stage. Future longitudinal studies are needed to elucidate individualized recovery after brain injury.

ADC textural features in patients with single brain metastases improve clinical risk models

AIMS

In this retrospective study we performed a quantitative textural analysis of apparant diffusion coefficient (ADC) images derived from diffusion weighted MRI (DW-MRI) of single brain metastases (BM) patients from different primary tumors and tested whether these imaging parameters may improve established clinical risk models.

METHODS

We identified 87 patients with single BM who had a DW-MRI at initial diagnosis. Applying image segmentation, volumes of contrast-enhanced lesions in T1 sequences, hyperintense T2 lesions (peritumoral border zone (T2PZ)) and tumor-free gray and white matter compartment (GMWMC) were generated and registered to corresponding ADC maps. ADC textural parameters were generated and a linear backward regression model was applied selecting imaging features in association with survival. A cox proportional hazard model with backward regression was fitted for the clinical prognostic models (diagnosis-specific graded prognostic assessment score (DS-GPA) and the recursive partitioning analysis (RPA)) including these imaging features.

RESULTS

Thirty ADC textural parameters were generated and linear backward regression identified eight independent imaging parameters which in combination predicted survival. Five ADC texture features derived from T2PZ, the volume of the T2PZ, the normalized mean ADC of the GMWMC as well as the mean ADC slope of T2PZ. A cox backward regression including the DS-GPA, RPA and these eight parameters identified two MRI features which improved the two risk scores (HR = 1.14 [1.05;1.24] for normalized mean ADC GMWMC and HR = 0.87 [0.77;0.97]) for ADC 3D kurtosis of the T2PZ.) CONCLUSIONS: Textural analysis of ADC maps in patients with single brain metastases improved established clinical risk models. These findings may aid to better understand the pathogenesis of BM and may allow selection of patients for new treatment options.

Diffusion tensor imaging in glioblastoma patients treated with volumetric modulated arc radiotherapy: a longitudinal study

BACKGROUND

Chemo- and radiotherapy (RT) is standard treatment for patients with high-grade glioma, but may cause side-effects on the patient's cognitive function.

AIM

Use of diffusion tensor imaging (DTI) to investigate the longitudinal changes in normal-appearing brain tissue in glioblastoma patients undergoing modern arc-based RT with volumetric modulated arc therapy (VMAT) or helical tomotherapy.

MATERIALS AND METHODS

The study included 27 patients newly diagnosed with glioblastoma and planned for VMAT or tomotherapy. All subjects underwent magnetic resonance imaging at the start of RT and at week 3, 6, 15, and 26. Fourteen subjects were additionally imaged at week 52. The DTI data were co-registered to the dose distribution maps. Longitudinal changes in fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were assessed in the corpus callosum, the centrum semiovale, the hippocampus, and the amygdala.

RESULTS

Significant longitudinal changes in FA, MD, and RD were mainly found in the corpus callosum. In the other examined brain structures, only sparse and transient changes were seen. No consistent correlations were found between biodose, age, or gender and changes in DTI parameters.

CONCLUSION

Longitudinal changes in MD, FA, and RD were observed but only in a limited number of brain structures and the changes were smaller than expected from literature. The results suggest that modern, arc-based RT may have less negative effect on normal-appearing parts of the brain tissue up to 12 months after radiotherapy.

What's new and what's next in diffusion MRI preprocessing

Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the analysis of results and their interpretability if not appropriately accounted for. This review will cover dMRI artifacts and preprocessing steps, some of which have not typically been considered in existing pipelines or reviews, or have only gained attention in recent years: brain/skull extraction, B-matrix incompatibilities w.r.t the imaging data, signal drift, Gibbs ringing, noise distribution bias, denoising, between- and within-volumes motion, eddy currents, outliers, susceptibility distortions, EPI Nyquist ghosts, gradient deviations, B1 bias fields, and spatial normalization. The focus will be on "what's new" since the notable advances prior to and brought by the Human Connectome Project (HCP), as presented in the predecessing issue on "Mapping the Connectome" in 2013. In addition to the development of novel strategies for dMRI preprocessing, exciting progress has been made in the availability of open source tools and reproducible pipelines, databases and simulation tools for the evaluation of preprocessing steps, and automated quality control frameworks, amongst others. Finally, this review will consider practical considerations and our view on "what's next" in dMRI preprocessing.

Relationship between White Matter Alterations and Pathophysiological Symptoms in Patients with Ultra-High Risk of Psychosis, First-Episode, and Chronic Schizophrenia

Some symptoms of schizophrenia might be present before full-blown psychosis, so white matter changes must be studied both in individuals with emerging psychosis and chronic schizophrenia. A total of 86 patients—12 ultra-high risk of psychosis (UHR), 20 first episode psychosis (FEP), 54 chronic schizophrenia (CS), and 33 healthy controls (HC)—underwent psychiatric examination and diffusion tensor imaging (DTI) in a 3-Tesla MRI scanner. We assessed fractional anisotropy (FA) and mean diffusivity (MD) of the superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILS). We found that CS patients had lower FA than FEP patients (p = 0.025) and HC (p = 0.088), and higher MD than HC (p = 0.037) in the right SLF. In the CS group, we found positive correlations of MD in both right ILF (rho = 0.39, p < 0.05) and SLF (rho = 0.43, p < 0.01) with disorganization symptoms, as well as negative correlation of FA in the right ILF with disorganization symptoms (rho = −0.43, p < 0.05). Among UHR individuals, we found significant negative correlations between MD in the left ILF and negative (r = −0.74, p < 0.05) and general symptoms (r = −0.77, p < 0.05). However promising, these findings should be treated as preliminary, and further research must verify whether they can be treated as potential biomarkers of psychosis.

Diffusion tensor imaging indices as biomarkers for cognitive changes following paediatric radiotherapy: a systematic review and meta-analysis

Diffusion tensor imaging (DTI) can detect subtle manifestations of white matter (WM) injury following paediatric radiotherapy, which may be a potential biomarker for cognitive changes. This study aimed to synthesise the relationships between DTI indices and cognitive changes following paediatric radiotherapy through systematic review and meta-analysis. PubMed and Scopus electronic databases were used to identify eligible studies. Quality assessment was performed using the National Institute of Health (NIH) Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Information on demographics, DTI changes, and associations to cognitive outcomes were extracted. Meta-analyses were performed on DTI changes in specific anatomical locations. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed in the preparation of this report. Eighteen studies were included (median study size: 21; range 18-146). 17/18 studies showed significant cognitive decline following irradiation. Meta-analyses found significant cognitive changes within patient's group of acute lymphoblastic leukaemia (ALL; standard mean differences [SMD] = -0.075, P = 0.01) and brain tumours (BT; SMD = -1.037, P ≤ 0.001) compared to control/baseline. Both groups also had significantly lower fractional anisotropy (FA) scores in the corpus callosum (ALL: SMD = -0.979, P = 0.002; BT: SMD = -1.025, P < 0.001). Decreased FA was consistently associated with cognitive decline. Correlation on WMFA integrity to cognitive domains was statistically significant (Z = 9.86, P < 0.001) with a large effect size (r = 0.52). White matter tract integrity of the corpus callosum measured with FA has the potential to be a biomarker for radiotherapy-related cognitive decline. Inclusion of DTI in follow-up imaging should be encouraged.

Refined Analysis of Chronic White Matter Changes after Traumatic Brain Injury and Repeated Sports-Related Concussions: Of Use in Targeted Rehabilitative Approaches?

Traumatic brain injury (TBI) or repeated sport-related concussions (rSRC) may lead to long-term memory impairment. Diffusion tensor imaging (DTI) is helpful to reveal global white matter damage but may underestimate focal abnormalities. We investigated the distribution of post-injury regional white matter changes after TBI and rSRC. Six patients with moderate/severe TBI, and 12 athletes with rSRC were included ≥6 months post-injury, and 10 (age-matched) healthy controls (HC) were analyzed. The Repeatable Battery for the Assessment of Neuropsychological Status was performed at the time of DTI. Major white matter pathways were tracked using q-space diffeomorphic reconstruction and analyzed for global and regional changes with a controlled false discovery rate. TBI patients displayed multiple classic white matter injuries compared with HC (p < 0.01). At the regional white matter analysis, the left frontal aslant tract, anterior thalamic radiation, and the genu of the corpus callosum displayed focal changes in both groups compared with HC but with different trends. Both TBI and rSRC displayed worse memory performance compared with HC (p < 0.05). While global analysis of DTI-based parameters did not reveal common abnormalities in TBI and rSRC, abnormalities to the fronto-thalamic network were observed in both groups using regional analysis of the white matter pathways. These results may be valuable to tailor individualized rehabilitative approaches for post-injury cognitive impairment in both TBI and rSRC patients.

White matter diffusivity and its correlations to state measures of psychopathology in male refugees with posttraumatic stress disorder

Post-traumatic stress disorder (PTSD) is a heterogenous condition and the underlying neurobiology is still poorly understood. In this study, we tested the hypothesis that PTSD is associated with microstructural changes in white matter (WM) fibre tracts that connect regions involved in emotional processing, memory, attention, and language. Furthermore, we examined how different response patterns to individualized trauma-provoking stimuli related to underlying WM microstructure. Sixty-nine trauma-affected male refugees with PTSD (N = 38) or without PTSD (N = 31) underwent clinical assessments and diffusion-weighted magnetic resonance imaging (DWI) of the whole brain at 3 Tesla. Diffusion tensor metrics were computed from DWI data and used to characterize regional white-matter microstructure. An automated tract segmentation method was used to extract diffusion tensor metrics from subject-based reconstructions of tract segments (ROI), including uncinate fasciculus (UF), cingulum bundle (CB), superior longitudinal fasciculus (SLF) in three subdivisions (SLF I - III), and fibre bundles connecting orbito-frontal cortex to striatum (OF-ST). Outside the scanner we obtained measures of immediate (state) arousal, avoidance and dissociation symptoms assessed in response to auditory exposure to a personal traumatic memory. Using mean FA of the middle part of each ROI, mixed ANOVA revealed a significant interaction between group, ROI and hemisphere. Post-hoc comparisons showed that, relative to refugees without PTSD, refugees with PTSD had lower FA in right CB, left SLF-I, bilateral OF-ST and bilateral SLF-II. Mean FA scaled negatively with avoidance in right CB while mean FA in bilateral UF scaled positively with individual scores reflecting dissociation symptoms. The results support a pathophysiological model of PTSD that implicates limbic structures, prefrontal cortex and striatum. The results also emphasize the need to consider PTSD's multifaceted manifestations when searching for functional-structural relationships.

Not all voxels are created equal: Reducing estimation bias in regional NODDI metrics using tissue-weighted means

Neurite orientation dispersion and density imaging (NODDI) estimates microstructural properties of brain tissue relating to the organisation and processing capacity of neurites, which are essential elements for neuronal communication. Descriptive statistics of NODDI tissue metrics are commonly analyzed in regions-of-interest (ROI) to identify brain-phenotype associations. Here, the conventional method to calculate the ROI mean weights all voxels equally. However, this produces biased estimates in the presence of CSF partial volume. This study introduces the tissue-weighted mean, which calculates the mean NODDI metric across the tissue within an ROI, utilising the tissue fraction estimate from NODDI to reduce estimation bias. We demonstrate the proposed mean in a study of white matter abnormalities in young onset Alzheimer's disease (YOAD). Results show the conventional mean induces significant bias that correlates with CSF partial volume, primarily affecting periventricular regions and more so in YOAD subjects than in healthy controls. Due to the differential extent of bias between healthy controls and YOAD subjects, the conventional mean under- or over-estimated the effect size for group differences in many ROIs. This demonstrates the importance of using the correct estimation procedure when inferring group differences in studies where the extent of CSF partial volume differs between groups. These findings are robust across different acquisition and processing conditions. Bias persists in ROIs at higher image resolution, as demonstrated using data obtained from the third phase of the Alzheimer's disease neuroimaging initiative (ADNI); and when performing ROI analysis in template space. This suggests that conventional ROI means of NODDI metrics are biased estimates under most contemporary experimental conditions, the correction of which requires the proposed tissue-weighted mean. The tissue-weighted mean produces accurate estimates of ROI means and group differences when ROIs contain voxels with CSF partial volume. In addition to NODDI, the technique can be applied to other multi-compartment models that account for CSF partial volume, such as the free water elimination method. We expect the technique to help generate new insights into normal and abnormal variation in tissue microstructure of regions typically confounded by CSF partial volume, such as those in individuals with larger ventricles due to atrophy associated with neurodegenerative disease.

Using diffusion MRI data acquired with ultra-high gradient strength to improve tractography in routine-quality data

The development of scanners with ultra-high gradient strength, spearheaded by the Human Connectome Project, has led to dramatic improvements in the spatial, angular, and diffusion resolution that is feasible for in vivo diffusion MRI acquisitions. The improved quality of the data can be exploited to achieve higher accuracy in the inference of both microstructural and macrostructural anatomy. However, such high-quality data can only be acquired on a handful of Connectom MRI scanners worldwide, while remaining prohibitive in clinical settings because of the constraints imposed by hardware and scanning time. In this study, we first update the classical protocols for tractography-based, manual annotation of major white-matter pathways, to adapt them to the much greater volume and variability of the streamlines that can be produced from today’s state-of-the-art diffusion MRI data. We then use these protocols to annotate 42 major pathways manually in data from a Connectom scanner. Finally, we show that, when we use these manually annotated pathways as training data for global probabilistic tractography with anatomical neighborhood priors, we can perform highly accurate, automated reconstruction of the same pathways in much lower-quality, more widely available diffusion MRI data. The outcomes of this work include both a new, comprehensive atlas of WM pathways from Connectom data, and an updated version of our tractography toolbox, TRActs Constrained by UnderLying Anatomy (TRACULA), which is trained on data from this atlas. Both the atlas and TRACULA are distributed publicly as part of FreeSurfer. We present the first comprehensive comparison of TRACULA to the more conventional, multi-region-of-interest approach to automated tractography, and the first demonstration of training TRACULA on high-quality, Connectom data to benefit studies that use more modest acquisition protocols.

Diffusion imaging of fornix and interconnected limbic deep grey matter is linked to cognitive impairment in multiple sclerosis

Diffusion tensor imaging (DTI) and volumetric magnetic resonance imaging (MRI) have shown white matter (WM) and deep grey matter (GM) abnormalities in the limbic system of multiple sclerosis (MS) participants. Structures like the fornix have been associated with cognitive impairment (CI) in MS, but the diffusion metrics are often biased by partial volume effects from cerebrospinal fluid (CSF) due to its small bundle size and intraventricular location. These errors in DTI parameter estimation worsen with atrophy in MS. The goal here was to evaluate DTI parameters and volumes of the fornix, as well as associated deep GM structures like the thalamus and hippocampus, with high-resolution fluid-attenuated inversion recovery (FLAIR)-DTI at 3T in 43 MS patients, with and without CI, versus 43 controls. The fornix, thalamus and hippocampus displayed atrophy and/or abnormal diffusion metrics, with the fornix showing the most extensive changes within the structures studied here, mainly in CI MS. The affected fornix volumes and diffusion metrics were associated with thalamic atrophy and atypical diffusion metrics in interconnected limbic GM, larger total lesion volume and global brain atrophy. Lower fractional anisotropy (FA) and higher mean and radial diffusivity in the fornix, lower hippocampus FA and lower thalamus volume were strongly correlated with CI in MS. Hippocampus FA and thalamus atrophy were negatively correlated with fatigue and longer time since MS symptoms onset, respectively. FLAIR-DTI and volumetric analyses provided methodologically superior evidence for microstructural abnormalities and extensive atrophy of the fornix and interconnected deep GM in MS that were associated with cognitive deficits.

Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease

OBJECTIVES

Acquisition-related differences in diffusion magnetic resonance imaging (dMRI) hamper pooling of multicentre data to achieve large sample sizes. A promising solution is to harmonize the raw diffusion signal using rotation invariant spherical harmonic (RISH) features, but this has not been tested in elderly subjects. Here we aimed to establish if RISH harmonization effectively removes acquisition-related differences in multicentre dMRI of elderly subjects with cerebral small vessel disease (SVD), while preserving sensitivity to disease effects.

METHODS

Five cohorts of patients with SVD (N = 397) and elderly controls (N = 175) with 3 Tesla MRI on different systems were included. First, to establish effectiveness of harmonization, the RISH method was trained with data of 13 to 15 age and sex-matched controls from each site. Fractional anisotropy (FA) and mean diffusivity (MD) were compared in matched controls between sites using tract-based spatial statistics (TBSS) and voxel-wise analysis, before and after harmonization. Second, to assess sensitivity to disease effects, we examined whether the contrast (effect sizes of FA, MD and peak width of skeletonized MD - PSMD) between patients and controls within each site remained unaffected by harmonization. Finally, we evaluated the association between white matter hyperintensity (WMH) burden, FA, MD and PSMD using linear regression analyses both within individual cohorts as well as with pooled scans from multiple sites, before and after harmonization.

RESULTS

Before harmonization, significant differences in FA and MD were observed between matched controls of different sites (p < 0.05). After harmonization these site-differences were removed. Within each site, RISH harmonization did not alter the effect sizes of FA, MD and PSMD between patients and controls (relative change in Cohen's d = 4 %) nor the strength of association with WMH volume (relative change in R2 = 2.8 %). After harmonization, patient data of all sites could be aggregated in a single analysis to infer the association between WMH volume and FA (R2 = 0.62), MD (R2 = 0.64), and PSMD (R2 = 0.60).

CONCLUSIONS

We showed that RISH harmonization effectively removes acquisition-related differences in dMRI of elderly subjects while preserving sensitivity to SVD-related effects. This study provides proof of concept for future multicentre SVD studies with pooled datasets.

Meta-analysis of the normal diffusion tensor imaging values of the median nerve and how they change in carpal tunnel syndrome

Carpal tunnel syndrome (CTS) leads to distortion of axonal architecture, demyelination and fibrosis within the median nerve. Diffusion tensor imaging (DTI) characterises tissue microstructure and generates reproducible proxy measures of nerve 'health' which are sensitive to myelination, axon diameter, fiber density and organisation. This meta-analysis summarises the normal DTI values of the median nerve, and how they change in CTS. This systematic review included studies reporting DTI of the median nerve at the level of the wrist in adults. The primary outcome was to determine the normal fractional anisotropy (FA) and mean diffusivity (MD) of the median nerve. Secondarily, we show how the FA and MD differ between asymptomatic adults and patients with CTS, and how these differences are independent of the acquisition methods. We included 32 studies of 2643 wrists, belonging to 1575 asymptomatic adults and 1068 patients with CTS. The normal FA was 0.58 (95% CI 0.56, 0.59) and the normal MD was 1.138 × 10^-3 mm²/s (95% CI 1.101, 1.174). Patients with CTS had a significantly lower FA than controls (mean difference 0.12 [95% CI 0.09, 0.16]). Similarly, the median nerve of patients with CTS had a significantly higher mean diffusivity (mean difference 0.16 × 10^-3 mm²/s [95% CI 0.05, 0.27]). The differences were independent of experimental factors. We provide summary estimates of the normal FA and MD of the median nerve in asymptomatic adults. Furthermore, we show that diffusion throughout the length of the median nerve becomes more isotropic in patients with CTS.

A high temporal/spatial resolution neuro-architecture study of rodent brain by wideband echo planar imaging

Latest simultaneous multi-slice (SMS) methods greatly benefit MR efficiency for recent studies using parallel imaging technique. However, these methods are limited by the requirement of array coils. The proposed Coherent Wideband method, which employs an extended field of view to separate multiple excited slices, can be applied to any existing MRI instrument, even those without array coils. In this study, the Coherent Wideband echo-planar imaging method was implemented on 7 T animal MRI to exhibit comprehensive enhancements in neuro-architecture, including diffusion tensor imaging (DTI) and functional MR studies (fMRI). Under the same scan time, the time-saving effect can be manipulated to increase the number of averages for DTI SNR improvement, reducing fractional anisotropy difference by 56.9% (from 0.072 to 0.041) and the deviation angle by 64% (from 25.3° to 16.2°). In summary, Coherent Wideband Echo Planar Imaging (EPI) will provide faster, higher resolution, thinner slice, or higher SNR imaging for precision neuro-architecture studies.

Quantitative magnetic resonance imaging of the brachial plexus shows specific changes in nerve architecture in chronic inflammatory demyelinating polyneuropathy, multifocal motor neuropathy and motor neuron disease

BACKGROUND

The immunological pathophysiologies of chronic inflammatory demyelinating polyneuropathy (CIDP) and multifocal motor neuropathy (MMN) differ considerably, but neither has been elucidated completely. Quantitative magnetic resonance imaging (MRI) techniques such as diffusion tensor imaging, T2 mapping, and fat fraction analysis may indicate in vivo pathophysiological changes in nerve architecture. Our study aimed to systematically study nerve architecture of the brachial plexus in patients with CIDP, MMN, motor neuron disease (MND) and healthy controls using these quantitative MRI techniques.

METHODS

We enrolled patients with CIDP (n = 47), MMN (n = 29), MND (n = 40) and healthy controls (n = 10). All patients underwent MRI of the brachial plexus and we obtained diffusion parameters, T2 relaxation times and fat fraction using an automated processing pipeline. We compared these parameters between groups using a univariate general linear model.

RESULTS

Fractional anisotropy was lower in patients with CIDP compared to healthy controls (p < 0.001), patients with MND (p = 0.010) and MMN (p < 0.001). Radial diffusivity was higher in patients with CIDP compared to healthy controls (p = 0.015) and patients with MND (p = 0.001) and MMN (p < 0.001). T2 relaxation time was elevated in patients with CIDP compared to patients with MND (p = 0.023). Fat fraction was lower in patients with CIDP and MMN compared to patients with MND (both p < 0.001).

CONCLUSION

Our results show that quantitative MRI parameters differ between CIDP, MMN and MND, which may reflect differences in underlying pathophysiological mechanisms.

Diffusion tensor imaging in cubital tunnel syndrome

Cubital tunnel syndrome (CuTS) is the 2nd most common compressive neuropathy. To improve both diagnosis and the selection of patients for surgery, there is a pressing need to develop a reliable and objective test of ulnar nerve 'health'. Diffusion tensor imaging (DTI) characterises tissue microstructure and may identify differences in the normal ulnar from those affected by CuTS. The aim of this study was to compare the DTI metrics from the ulnar nerves of healthy (asymptomatic) adults and patients with CuTS awaiting surgery. DTI was acquired at 3.0 T using single-shot echo-planar imaging (55 axial slices, 3 mm thick, 1.5 mm2 in-plane) with 30 diffusion sensitising gradient directions, a b-value of 800 s/mm2 and 4 signal averages. The sequence was repeated with the phase-encoding direction reversed. Data were combined and corrected using the FMRIB Software Library (FSL) and reconstructed using generalized q-sampling imaging in DSI Studio. Throughout the length of the ulnar nerve, the fractional anisotropy (FA), quantitative anisotropy (QA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were extracted, then compared using mixed-effects linear regression. Thirteen healthy controls (8 males, 5 females) and 8 patients with CuTS (6 males, 2 females) completed the study. Throughout the length of the ulnar nerve, diffusion was more isotropic in patients with CuTS. Overall, patients with CuTS had a 6% lower FA than controls, with the largest difference observed proximal to the cubital tunnel (mean difference 0.087 [95% CI 0.035, 0.141]). Patients with CuTS also had a higher RD than controls, with the largest disparity observed within the forearm (mean difference 0.252 × 10-4 mm2/s [95% CI 0.085 × 10-4, 0.419 × 10-4]). There were no significant differences between patients and controls in QA, MD or AD. Throughout the length of the ulnar nerve, the fractional anisotropy and radial diffusivity in patients with CuTS are different to healthy controls. These findings suggest that DTI may provide an objective assessment of the ulnar nerve and potentially, improve the management of CuTS.

Diffusion MR Imaging with T2-based Water Suppression (T2wsup-dMRI)

Purpose: This study proposes and assesses a new diffusion MRI (dMRI) technique to solve problems related to the quantification of parameter maps (apparent diffusion coefficient [ADC] or mean diffusivity [MD], fractional anisotropy [FA]) and misdrawing of fiber tractography (FT) due to cerebrospinal fluid (CSF)-partial volume effects (PVEs) for brain tissues by combining with the T2-based water suppression (T2wsup) technique.

Methods: T2wsup–diffusion-weighted imaging (DWI) images were obtained by subtracting those images from the acquired multi-b value (b) DWI images after correcting the signal intensities of multiecho time (TE) images using long TE water signal-dominant images. Quantitative parameter maps and FT were obtained from minimum data points and were compared with those using the standard (without wsup) DWI method, and partly compared with those obtained using other alternative DWI methods of applying fluid attenuation inversion recovery (FLAIR), non-b-zero (NBZ) by theoretical or noise-added simulation and MR images.

Results: In the T2wsup-dMRI method, the hyperintense artifacts due to CSF-PVEs in MRI data were dramatically suppressed even at lower b (≲ 500 s/mm²) while keeping the tissue SNR. The quantitative parameter map values became precisely close to the pure tissue values precisely even in water (CSF) PVE voxels in healthy brain tissues (T2 ≲ 100 ms). Furthermore, the fiber tracts were correctly connected, particularly at the fornix in closest contact to the CSF.

Conclusion: Solving the problem of CSF-PVE in the current dMRI technique using our proposed T2wsup-dMRI technique is easy, with higher SNR than those obtained with FLAIR or NBZ methods when applying to healthy brain tissues. The proposed T2wsup–dMRI could be useful in clinical settings, although further optimization of the pulse sequence and processing techniques and clinical assessments are required, particularly for long T2 lesions.

Neurite density and arborization is associated with reading skill and phonological processing in children

Background:

Studies exploring neuroanatomic correlates of reading have associated white matter tissue properties with reading disability and related componential skills (e.g., phonological and single-word reading skills). Mean diffusivity (MD) and fractional anisotropy (FA) are widely used surrogate measures of tissue microstructure with high sensitivity; however, they lack specificity for individual microstructural features. Here we investigated neurite features with higher specificity in order to explore the underlying microstructural architecture.

Methods:

Diffusion weighted images (DWI) and a battery of behavioral and neuropsychological assessments were obtained from 412 children (6 – 16 years of age). Neurite indices influenced by orientation and density were attained from 23 major white matter tracts. Partial correlations were calculated between neurite indices and indicators of phonological processing and single-word reading skills using age, sex, and image quality metrics as covariates. In addition, mediation analysis was performed using structural equation modeling (SEM) to evaluate the indirect effect of phonological processing on reading skills.

Results:

We observed that orientation dispersion index (ODI) and neurite density index (NDI) were negatively correlated with single-word reading and phonological processing skills in several tracts previously shown to have structural correlates with reading efficiency. We also observed a significant and substantial effect in which phonological processing mediated the relationship between neurite indices and reading skills in most tracts.

Conclusions:

In sum, we established that better reading and phonological processing skills are associated with greater tract coherence (lower ODI) and lower neurite density (lower NDI). We interpret these findings as evidence that reading is associated with neural architecture and its efficiency.

The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students

We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1870 young healthy adults, aged 18-35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility-weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early ageing.

Temporal Dynamics of Brain White Matter Plasticity in Sighted Subjects during Tactile Braille Learning: A Longitudinal Diffusion Tensor Imaging Study

The white matter (WM) architecture of the human brain changes in response to training, though fine-grained temporal characteristics of training-induced white matter plasticity remain unexplored. We investigated white matter microstructural changes using diffusion tensor imaging at five different time points in 26 sighted female adults during 8 months of training on tactile braille reading. Our results show that training-induced white matter plasticity occurs both within and beyond the trained sensory modality, as reflected by fractional anisotropy (FA) increases in somatosensory and visual cortex, respectively. The observed changes followed distinct time courses, with gradual linear FA increase along the training in the somatosensory cortex and sudden visual cortex cross-modal plasticity occurring after braille input became linguistically meaningful. WM changes observed in these areas returned to baseline after the cessation of learning in line with the supply-demand model of plasticity. These results also indicate that the temporal dynamics of microstructural plasticity in different cortical regions might be modulated by the nature of computational demands. We provide additional evidence that observed FA training-induced changes are behaviorally relevant to tactile reading. Together, these results demonstrate that WM plasticity is a highly dynamic process modulated by the introduction of novel experiences.SIGNIFICANCE STATEMENT Throughout the lifetime the human brain is shaped by various experiences. Training-induced reorganization in white matter (WM) microstructure has been reported, but we know little about its temporal dynamics. To fill this gap, we scanned sighted subjects five times during tactile braille reading training. We observed different dynamics of WM plasticity in the somatosensory and visual cortices implicated in braille reading. The former showed a continuous increase in WM tissue anisotropy along with tactile training, while microstructural changes in the latter were observed only after the participants learned to read braille words. Our results confirm the supply-demand model of brain plasticity and provide evidence that WM reorganization depends on distinct computational demands and functional roles of regions involved in the trained skill.

Common genetic variation influencing human white matter microstructure

Brain regions communicate with each other through tracts of myelinated axons, commonly referred to as white matter. We identified common genetic variants influencing white matter microstructure using diffusion magnetic resonance imaging of 43,802 individuals. Genome-wide association analysis identified 109 associated loci, 30 of which were detected by tract-specific functional principal components analysis. A number of loci colocalized with brain diseases, such as glioma and stroke. Genetic correlations were observed between white matter microstructure and 57 complex traits and diseases. Common variants associated with white matter microstructure altered the function of regulatory elements in glial cells, particularly oligodendrocytes. This large-scale tract-specific study advances the understanding of the genetic architecture of white matter and its genetic links to a wide spectrum of clinical outcomes.

Selective Effects of Healthy Cognitive Aging and Catechol-O-Methyl Transferase Polymorphism on Limbic White Matter Tracts

Introduction: The cingulum bundle and uncinate fasciculus are major limbic white matter tracts involved in emotion, memory, and cognition. The main goal of the present study was to investigate the relationship between age and structural properties of the uncinate fasciculus and the cingulum bundle using diffusion tensor imaging (DTI) tractography in a large cohort of healthy individuals. The second goal was to determine the effects of the catechol-O-methyl transferase (COMT) gene polymorphism on the DTI measurements of these white matter tracts. Methods: We recruited 140 healthy participants (18-85 years old). DTI data sets were acquired on a 1.5T magnetic resonance imaging system. The rostral, dorsal, and parahippocampal cingulum, as well as uncinate fasciculus, were delineated using deterministic tractography. Fractional anisotropy (FA), mean (MD), radial (RD), and axial (AD) diffusivities, tract volume, linear (C_l), planar (C_p), and spherical (C_s) tensor shapes were calculated. The COMT polymorphism (methionine homozygous vs. valine carriers) was determined using single nucleotide polymorphism. Results: We found that age was negatively associated with FA, but positively associated with MD and RD for the rostral cingulum, dorsal cingulum, and the uncinate fasciculus but not for the parahippocampal cingulum. Furthermore, individuals with the COMT methionine homozygous had higher FA and lower MD, RD, AD, and C_s values in the right rostral cingulum compared with the valine carriers across the entire adult life span. Discussion: This study indicates that limbic tracts might be nonuniformly affected by healthy aging, and the methionine homozygous genotype might be associated with micro/macro white matter properties of the right rostral cingulum.

Neural substrates of neuropsychological profiles in dystrophynopathies: A pilot study of diffusion tractography imaging

Introduction

Cognitive difficulties and neuropsychological alterations in Duchenne and Becker muscular dystrophy (DMD, BMD) boys are not yet sufficiently explored, although this topic could have a relevant impact, finding novel biomarkers of disease both at genetics and neuroimaging point of view. The current study aims to: 1) analyze the neuropsychological profile of a group of DMD and BMD boys without cognitive impairment with an assessment of their executive functions; 2) explore the structural connectivity in DMD, BMD, and age-matched controls focusing on cortico-subcortical tracts that connect frontal cortex, basal ganglia, and cerebellum via the thalamus; 3) explore possible correlations between altered structural connectivity and clinical neuropsychological measures.

Materials and methods

This pilot study included 15 boys (5 DMD subjects, 5 BMD subjects, and 5 age-matched typically developing, TD). They were assessed using a neuropsychological assessment protocol including cognitive and executive functioning assessment and performed a 1.5T MRI brain exam including advance Diffusion Weighted Imaging (DWI) method for tractography. Structural connectivity measurements were extracted along three specific tracts: Cortico-Ponto-Cerebellar Tract (CPCT), Cerebellar-Thalamic Tract (CTT), and Superior Longitudinal Fasciculus (SLF). Cortical-Spinal Tract (CST) was selected for reference, as control tract.

Results

Regarding intellectual functioning, a major impairment in executive functions compared to the general intellectual functioning was observed both for DMD (mean score = 86.20; SD = 11.54) and for BMD children (mean score = 88; SD = 3.67). Mean FA resulted tendentially always lower in DMD compared to both BMD and TD groups for all the examined tracts. The differences in FA were statistically significant for the right CTT (DMD vs BMD, p = 0.002, and DMD vs TD, p = 0.0015) and the right CPCT (DMD vs TD, p = 0.008). Concerning DMD, significant correlations emerged between FA-R-CTT and intellectual quotients (FIQ, p = 0.044; ρs = 0.821), and executive functions (Denomination Total, p = 0.044, ρs = 0.821; Inhibition Total, p = 0.019, ρs = 0.900). BMD showed a significant correlation between FA-R-CPCT and working memory index (p = 0.007; ρs = 0.949).

Discussion and conclusion

In this pilot study, despite the limitation of sample size, the findings support the hypothesis of the involvement of a cerebellar-thalamo-cortical loop for the neuropsychological profile of DMD, as the CTT and the CPCT are involved in the network and the related brain structures are known to be implied in executive functions. Our results suggest that altered WM connectivity and reduced fibre organization in cerebellar tracts, probably due to the lack of dystrophin in the brain, may render less efficient some neuropsychological functions in children affected by dystrophinopathies. The wider multicentric study could help to better establish the role of cerebellar connectivity in neuropsychological profile for dystrophinopathies, identifying possible novel diagnostic and prognostic biomarkers.

Development of brain atlases for early-to-middle adolescent collision-sport athletes

Human brains develop across the life span and largely vary in morphology. Adolescent collision-sport athletes undergo repetitive head impacts over years of practices and competitions, and therefore may exhibit a neuroanatomical trajectory different from healthy adolescents in general. However, an unbiased brain atlas targeting these individuals does not exist. Although standardized brain atlases facilitate spatial normalization and voxel-wise analysis at the group level, when the underlying neuroanatomy does not represent the study population, greater biases and errors can be introduced during spatial normalization, confounding subsequent voxel-wise analysis and statistical findings. In this work, targeting early-to-middle adolescent (EMA, ages 13-19) collision-sport athletes, we developed population-specific brain atlases that include templates (T1-weighted and diffusion tensor magnetic resonance imaging) and semantic labels (cortical and white matter parcellations). Compared to standardized adult or age-appropriate templates, our templates better characterized the neuroanatomy of the EMA collision-sport athletes, reduced biases introduced during spatial normalization, and exhibited higher sensitivity in diffusion tensor imaging analysis. In summary, these results suggest the population-specific brain atlases are more appropriate towards reproducible and meaningful statistical results, which better clarify mechanisms of traumatic brain injury and monitor brain health for EMA collision-sport athletes.

High spatial resolution nerve-specific DTI protocol outperforms whole-brain DTI protocol for imaging the trigeminal nerve in healthy individuals

Diffusion tensor imaging (DTI) can provide markers of axonal micro-structure of the trigeminal nerve (cranial nerve five [CNV]), which may be affected in trigeminal neuralgia (TN) and other disorders. Previous attempts to image CNV have used low spatial resolution DTI protocols designed for whole-brain acquisition that are susceptible to errors from partial volume effects, particularly with adjacent cerebrospinal fluid (CSF). The purpose of this study was to develop a nerve-specific DTI protocol in healthy subjects that provides more accurate CNV tractography and diffusion quantification than whole-brain protocols. Four DTI protocols were compared in five healthy individuals (age 22-45 years, three males) on a 3 T Siemens Prisma MRI scanner: two newly developed nerve-specific high resolution (1.2 x 1.2 x 1.2 = 1.7 mm³ ) DTI protocols without (3.5 minutes) and with CSF suppression (fluid-attenuated inversion recovery [FLAIR]; 7.5 minutes) with limited slice-coverage, and two typical whole-brain protocols with either isotropic (2 x 2 x 2 = 8 mm³ ) or thicker slice anisotropic (1.9 x 1.9 x 3 = 10.8 mm³ ) voxels. Deterministic tractography was used to identify the CNV and quantify bilateral fractional anisotropy (FA), and mean (MD), axial (AD) and radial diffusivity (RD). CNV volume was determined by manual tracing on T1-weighted images. High spatial resolution nerve-specific protocols yielded better delineation of CNV, with less distortions and blurring, and markedly different diffusion parameters (42% higher FA, 35% lower MD, 27% lower RD and 43% lower AD) compared with the two lower resolution whole-brain protocols. The anisotropic whole-brain protocol showed a positive correlation between CNV FA and volume. The high resolution nerve-specific protocol with FLAIR yielded additional reductions in CNV AD and MD with a value of 1.0 x 10^-3 mm² /s, approaching that expected for healthy young adult white matter. In conclusion, high resolution nerve-specific DTI with FLAIR enhances the identification of CNV and provides more accurate quantification of diffusion compared with lower resolution whole-brain approaches.

White matter hyperintensities induce distal deficits in the connected fibers

White matter hyperintensities (WMH) are common in elderly individuals and cause brain network deficits. However, it is still unclear how the global brain network is affected by the focal WMH. We aimed to investigate the diffusion of WMH-related deficits along the connecting white matters (WM). Brain magnetic resonance imaging data and neuropsychological evaluations of 174 participants (aged 74 ± 5 years) were collected and analyzed. For each participant, WMH lesions were segmented using a deep learning method, and 18 major WM tracts were reconstructed using automated quantitative tractography. The diffusion characteristics of distal WM tracts (with the WMH penumbra excluded) were calculated. Multivariable linear regression analysis was performed. We found that a high burden of tract-specific WMH was related to worse diffusion characteristics of distal WM tracts in a wide range of WM tracts, including the forceps major (FMA), forceps minor (FMI), anterior thalamic radiation (ATR), cingulum cingulate gyrus (CCG), corticospinal tract (CST), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus-parietal (SLFP), superior longitudinal fasciculus-temporal (SLFT), and uncinate fasciculus (UNC). Furthermore, a higher mean diffusivity (MD) of distal tracts was linked to worse attention and executive function in the FMI, right CCG, left ILF, SLFP, SLFT, and UNC. The effect of WMH on the microstructural integrity of WM tracts may propagate along tracts to distal regions beyond the penumbra and might eventually affect attention and executive function.

Diffusion properties of the fornix assessed by deterministic tractography shows age, sex, volume, cognitive, hemispheric, and twin relationships in young adults from the Human Connectome Project

The fornix is the primary efferent pathway of the hippocampus and plays a central role in memory circuitry. Diffusion tensor imaging has shown changes in the fornix with typical development and aging. Here, the fornix was investigated in 903 healthy young adult participants aged 22-36 years old from the high-spatial resolution 1.25 mm isotropic Human Connectome Project (HCP) diffusion dataset. Manual deterministic tractography was used to assess relationships between fornix diffusion parameters and age, sex, laterality, hippocampus volume, memory scores, and genetic effects in a subgroup of mono- and dizygotic twins. Fornix diffusion metrics were weakly correlated with age over the given age span. While significant hemispheric and sex differences were observed (greater fractional anisotropy (FA) and volume in the right hemisphere; greater FA and volume in females), there was great overlap between the groups. Hippocampus volume measurements showed greater volume in the right hemisphere, were found to be larger in males, and were weakly correlated with fornix FA and volume. Interestingly, all fornix diffusion measurements correlated strongly with fornix volume, suggesting the presence of partial volume effects despite the high-spatial resolution of the data. Both fornix diffusion parameters and hippocampal volumes were able to explain some variance (0.6-5.5%) in the memory tests evaluated. The fornix diffusion parameters were influenced by both genetic and shared environmental factors, displaying greater variability in dizygotic than in monozygotic twins. These findings provide a comprehensive depiction of the fornix in healthy, young individuals, upon which future typical development/aging and pathological studies could anchor.

The sensitivity of diffusion MRI to microstructural properties and experimental factors

Diffusion MRI is a non-invasive technique to study brain microstructure. Differences in the microstructural properties of tissue, including size and anisotropy, can be represented in the signal if the appropriate method of acquisition is used. However, to depict the underlying properties, special care must be taken when designing the acquisition protocol as any changes in the procedure might impact on quantitative measurements. This work reviews state-of-the-art methods for studying brain microstructure using diffusion MRI and their sensitivity to microstructural differences and various experimental factors. Microstructural properties of the tissue at a micrometer scale can be linked to the diffusion signal at a millimeter-scale using modeling. In this paper, we first give an introduction to diffusion MRI and different encoding schemes. Then, signal representation-based methods and multi-compartment models are explained briefly. The sensitivity of the diffusion MRI signal to the microstructural components and the effects of curvedness of axonal trajectories on the diffusion signal are reviewed. Factors that impact on the quality (accuracy and precision) of derived metrics are then reviewed, including the impact of random noise, and variations in the acquisition parameters (i.e., number of sampled signals, b-value and number of acquisition shells). Finally, yet importantly, typical approaches to deal with experimental factors are depicted, including unbiased measures and harmonization. We conclude the review with some future directions and recommendations on this topic.

Alterations in Microstructure and Local Fiber Orientation of White Matter Are Associated with Outcome after Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) can have long-lasting consequences. We investigated white matter (WM) alterations at 6-12 months following mTBI using diffusion tensor imaging (DTI) and assessed if the alterations associate with outcome. Eighty-five patients with mTBI underwent diffusion-weighted magnetic resonance imaging (MRI) on average 8 months post-injury and patients' outcome was assessed at the time of imaging using the Glasgow Outcome Scale-Extended (GOS-E). Additionally, 30 age-matched patients with extracranial orthopedic injuries were used as control subjects. Voxel-wise analysis of the data was performed using a tract-based spatial statistics (TBSS) approach and differences in microstructural metrics between groups were investigated. Further, the susceptibility of the abnormalities to specific fiber orientations was investigated by analyzing the first eigenvector of the diffusion tensor in the voxels with significant differences. We found significantly lower fractional anisotropy (FA) and higher mean diffusivity (MD) and radial diffusivity (RD) in patients with mTBI compared with control subjects, whereas no significant differences were observed in axial diffusivity (AD) between the groups. The differences were present bilaterally in several WM regions and correlated with outcome. Moreover, multiple clusters were found in the principal fiber orientations of the significant voxels in anisotropy, and similar orientation patterns were found for the diffusivity metrics. These directional clusters correlated with patients' functional outcome. Our study showed that mTBI is associated with WM changes at the chronic stage and these alterations occur in several WM regions. In addition, several significant clusters of WM alterations in specific fiber orientations were found and these clusters were associated with outcome.

Free water: A marker of age-related modifications of the cingulum white matter and its association with cognitive decline

Diffusion MRI is extensively used to investigate changes in white matter microstructure. However, diffusion measures within white matter tissue can be affected by partial volume effects due to cerebrospinal fluid and white matter hyperintensities, especially in the aging brain. In previous aging studies, the cingulum bundle that plays a central role in the architecture of the brain networks supporting cognitive functions has been associated with cognitive deficits. However, most of these studies did not consider the partial volume effects on diffusion measures. The aim of this study was to evaluate the effect of free water elimination on diffusion measures of the cingulum in a group of 68 healthy elderly individuals. We first determined the effect of free water elimination on conventional DTI measures and then examined the effect of free water elimination on verbal fluency performance over 12 years. The cingulum bundle was reconstructed with a tractography pipeline including a white matter hyperintensities mask to limit the negative impact of hyperintensities on fiber tracking algorithms. We observed that free water elimination increased the ability of conventional DTI measures to detect associations between tissue diffusion measures of the cingulum and changes in verbal fluency in older individuals. Moreover, free water content and mean diffusivity measured along the cingulum were independently associated with changes in verbal fluency. This suggests that both tissue modifications and an increase in interstitial isotropic water would contribute to cognitive decline. These observations reinforce the importance of using free water elimination when studying brain aging and indicate that free water itself could be a relevant marker for age-related cingulum white matter modifications and cognitive decline.

Functional and Structural Connectome Features for Machine Learning Chemo-Brain Prediction in Women Treated for Breast Cancer with Chemotherapy

Breast cancer is the leading cancer among women worldwide, and a high number of breast cancer patients are struggling with psychological and cognitive disorders. In this study, we aim to use machine learning models to discriminate between chemo-brain participants and healthy controls (HCs) using connectomes (connectivity matrices) and topological coefficients. Nineteen female post-chemotherapy breast cancer (BC) survivors and 20 female HCs were recruited for this study. Participants in both groups received resting-state functional magnetic resonance imaging (rs-fMRI) and generalized q-sampling imaging (GQI). Logistic regression (LR), decision tree classifier (CART), and xgboost (XGB) were the models we adopted for classification. In connectome analysis, LR achieved an accuracy of 79.49% with the functional connectomes and an accuracy of 71.05% with the structural connectomes. In the topological coefficient analysis, accuracies of 87.18%, 82.05%, and 83.78% were obtained by the functional global efficiency with CART, the functional global efficiency with XGB, and the structural transitivity with CART, respectively. The areas under the curves (AUCs) were 0.93, 0.94, 0.87, 0.88, and 0.84, respectively. Our study showed the discriminating ability of functional connectomes, structural connectomes, and global efficiency. We hope our findings can contribute to an understanding of the chemo brain and the establishment of a clinical system for tracking chemo brain.