Twenty-five pitfalls in the analysis of diffusion MRI data

Advanced breast diffusion-weighted imaging: what are the next steps? A proposal from the EUSOBI International Breast Diffusion-weighted Imaging working group

OBJECTIVES

This study by the EUSOBI International Breast Diffusion-weighted Imaging (DWI) working group aimed to evaluate the current and future applications of advanced DWI in breast imaging.

METHODS

A literature search and a comprehensive survey of EUSOBI members to explore the clinical use and potential of advanced DWI techniques and a literature search were involved. Advanced DWI approaches such as intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and diffusion tensor imaging (DTI) were assessed for their current status and challenges in clinical implementation.

RESULTS

Although a literature search revealed an increasing number of publications and growing academic interest in advanced DWI, the survey revealed limited adoption of advanced DWI techniques among EUSOBI members, with 32% using IVIM models, 17% using non-Gaussian diffusion techniques for kurtosis analysis, and only 8% using DTI. A variety of DWI techniques are used, with IVIM being the most popular, but less than half use it, suggesting that the study identified a gap between the potential benefits of advanced DWI and its actual use in clinical practice.

CONCLUSION

The findings highlight the need for further research, standardization and simplification to transition advanced DWI from a research tool to regular practice in breast imaging. The study concludes with guidelines and recommendations for future research directions and clinical implementation, emphasizing the importance of interdisciplinary collaboration in this field to improve breast cancer diagnosis and treatment.

CLINICAL RELEVANCE STATEMENT

Advanced DWI in breast imaging, while currently in limited clinical use, offers promising improvements in diagnosis, staging, and treatment monitoring, highlighting the need for standardized protocols, accessible software, and collaborative approaches to promote its broader integration into routine clinical practice.

KEY POINTS

Increasing number of publications on advanced DWI over the last decade indicates growing research interest. EUSOBI survey shows that advanced DWI is used primarily in research, not extensively in clinical practice. More research and standardization are needed to integrate advanced DWI into routine breast imaging practice.

Structure-function coupling in white matter uncovers the hypoconnectivity in autism spectrum disorder

BACKGROUND

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder associated with alterations in structural and functional coupling in gray matter. However, despite the detectability and modulation of brain signals in white matter, the structure-function coupling in white matter in autism remains less explored.

METHODS

In this study, we investigated structural-functional coupling in white matter (WM) regions, by integrating diffusion tensor data that contain fiber orientation information from WM tracts, with functional connectivity tensor data that reflect local functional anisotropy information. Using functional and diffusion magnetic resonance images, we analyzed a cohort of 89 ASD and 63 typically developing (TD) individuals from the Autism Brain Imaging Data Exchange II (ABIDE-II). Subsequently, the associations between structural-functional coupling in WM regions and ASD severity symptoms assessed by Autism Diagnostic Observation Schedule-2 were examined via supervised machine learning in an independent test cohort of 29 ASD individuals. Furthermore, we also compared the performance of multi-model features (i.e. structural-functional coupling) with single-model features (i.e. functional or structural models alone).

RESULTS

In the discovery cohort (ABIDE-II), individuals with ASD exhibited widespread reductions in structural-functional coupling in WM regions compared to TD individuals, particularly in commissural tracts (e.g. corpus callosum), association tracts (sagittal stratum), and projection tracts (e.g. internal capsule). Notably, supervised machine learning analysis in the independent test cohort revealed a significant correlation between these alterations in structural-functional coupling and ASD severity scores. Furthermore, compared to single-model features, the integration of multi-model features (i.e., structural-functional coupling) performed best in predicting ASD severity scores.

CONCLUSION

This work provides novel evidence for atypical structural-functional coupling in ASD in white matter regions, further refining our understanding of the critical role of WM networks in the pathophysiology of ASD.

Brain color-coded diffusion imaging: Utility of ACPC reorientation of gradients in healthy subjects and patients

BACKGROUND AND OBJECTIVE

The common structural interpretation of diffusion color-encoded (DCE) maps assumes that the brain is aligned with the gradients of the MRI machine. This is seldom achieved in the field, leading to incorrect red (R), green (G) and blue (B) DCE values for the expected orientation of fiber bundles. We studied the virtual reorientation of gradients according to the anterior commissure - posterior commissure (ACPC) system on the RGB derivatives.

METHODS

We measured mean ± standard deviation of average, standard deviation, skewness and kurtosis of RGB derivatives, before (rO) and after (acpcO) gradient reorientation, in one healthy-subject group with head routinely positioned (HS-routine), and in two patient groups, one with essential tremor (ET-Opti), and one with Parkinson's disease (PD-Opti), with head position optimized according to ACPC before acquisition. We studied the pitch, roll and yaw angles of reorientation, and we compared rO and acpcO conditions, and groups (ad hoc statistics).

RESULTS

Pitch (maximum in the HS-routine group) was greater than roll and yaw. After reorientation of gradients, in the HS-routine group, DCE average increased, and Stddev, skewness and kurtosis decreased; R, G and B average increased, and R and B skewness and kurtosis decreased. By contrast, in the ET-Opti group and the PD-Opti group, R, G and B, average and Stddev increased, and skewness and kurtosis decreased. In both rO and acpcO conditions, in the ET-Opti and PD-Opti groups, average and standard deviation were higher, while skewness and kurtosis were lower.

CONCLUSIONS

DCE map interpretability depends on brain orientation. Reorientation realigns gradients with the anatomic and physiologic position of the head and brain, as exemplified.

In Humans, Insulo-striate Structural Connectivity is Largely Biased Toward Either Striosome-like or Matrix-like Striatal Compartments

The insula is an integral component of sensory, motor, limbic, and executive functions, and insular dysfunction is associated with numerous human neuropsychiatric disorders. Insular efferents project widely, but insulo-striate projections are especially numerous. The targets of these insulo-striate projections are organized into tissue compartments, the striosome and matrix. These striatal compartments have distinct embryologic origins, afferent and efferent connectivity, dopamine pharmacology, and susceptibility to injury. Striosome and matrix appear to occupy separate sets of cortico-striato-thalamo-cortical loops, so a bias in insulo-striate projections toward one compartment may also embed an insular subregion in distinct regulatory and functional networks. Compartment-specific mapping of insulo-striate structural connectivity is sparse; the insular subregions are largely unmapped for compartment-specific projections. In 100 healthy adults, diffusion tractography was utilized to map and quantify structural connectivity between 19 structurally-defined insular subregions and each striatal compartment. Insulo-striate streamlines that reached striosome-like and matrix-like voxels were concentrated in distinct insular zones (striosome: rostro- and caudoventral; matrix: caudodorsal) and followed different paths to reach the striatum. Though tractography was generated independently in each hemisphere, the spatial distribution and relative bias of striosome-like and matrix-like streamlines were highly similar in the left and right insula. 16 insular subregions were significantly biased toward 1 compartment: 7 toward striosome-like voxels and 9 toward matrix-like voxels. Striosome-favoring bundles had significantly higher streamline density, especially from rostroventral insular subregions. The biases in insulo-striate structural connectivity that were identified mirrored the compartment-specific biases identified in prior studies that utilized injected tract tracers, cytoarchitecture, or functional MRI. Segregating insulo-striate structural connectivity through either striosome or matrix may be an anatomic substrate for functional specialization among the insular subregions.

Magnetic Resonance Imaging Biomarkers of Muscle

This review is focused on the current status of quantitative MRI (qMRI) of skeletal muscle. The first section covers the techniques of qMRI in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1-weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, and diffusion tensor imaging to emerging qMRI features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMRI of muscle; the intent is to demonstrate the utility of qMRI in different disease states of the muscle rather than a complete comprehensive survey.

What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review

ABSTRACT

Chronic pain is a pervasive and debilitating condition with increasing implications for public health, affecting millions of individuals worldwide. Despite its high prevalence, the underlying neural mechanisms and pathophysiology remain only partly understood. Since its introduction 35 years ago, brain diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool to investigate changes in white matter microstructure and connectivity associated with chronic pain. This review synthesizes findings from 58 articles that constitute the current research landscape, covering methods and key discoveries. We discuss the evidence supporting the role of altered white matter microstructure and connectivity in chronic primary pain conditions, highlighting the importance of studying multiple chronic pain syndromes to identify common neurobiological pathways. We also explore the prospective clinical utility of diffusion MRI, such as its role in identifying diagnostic, prognostic, and therapeutic biomarkers. Furthermore, we address shortcomings and challenges associated with brain diffusion MRI in chronic primary pain studies, emphasizing the need for the harmonization of data acquisition and analysis methods. We conclude by highlighting emerging approaches and prospective avenues in the field that may provide new insights into the pathophysiology of chronic pain and potential new therapeutic targets. Because of the limited current body of research and unidentified targeted therapeutic strategies, we are forced to conclude that further research is required. However, we believe that brain diffusion MRI presents a promising opportunity for enhancing our understanding of chronic pain and improving clinical outcomes.

A "glympse" into neurodegeneration: Diffusion MRI and cerebrospinal fluid aquaporin-4 for the assessment of glymphatic system in Alzheimer's disease and other dementias

The glymphatic system (GS) is a whole-brain perivascular network, consisting of three compartments: the periarterial and perivenous spaces and the interposed brain parenchyma. GS dysfunction has been implicated in neurodegenerative diseases, particularly Alzheimer's disease (AD). So far, comprehensive research on GS in humans has been limited by the absence of easily accessible biomarkers. Recently, promising non-invasive methods based on magnetic resonance imaging (MRI) along with aquaporin-4 (AQP4) quantification in the cerebrospinal fluid (CSF) were introduced for an indirect assessment of each of the three GS compartments. We recruited 111 consecutive subjects presenting with symptoms suggestive of degenerative cognitive decline, who underwent 3 T MRI scanning including multi-shell diffusion-weighted images. Forty nine out of 111 also underwent CSF examination with quantification of CSF-AQP4. CSF-AQP4 levels and MRI measures-including perivascular spaces (PVS) counts and volume fraction (PVSVF), white matter free water fraction (FW-WM) and mean kurtosis (MK-WM), diffusion tensor imaging analysis along the perivascular spaces (DTI-ALPS) (mean, left and right)-were compared among patients with AD (n = 47) and other neurodegenerative diseases (nAD = 24), patients with stable mild cognitive impairment (MCI = 17) and cognitively unimpaired (CU = 23) elderly people. Two runs of analysis were conducted, the first including all patients; the second after dividing both nAD and AD patients into two subgroups based on gray matter atrophy as a proxy of disease stage. Age, sex, years of education, and scanning time were included as confounding factors in the analyses. Considering the whole cohort, patients with AD showed significantly higher levels of CSF-AQP4 (exp(b) = 2.05, p = .005) and FW-WM FW-WM (exp(b) = 1.06, p = .043) than CU. AQP4 levels were also significantly higher in nAD in respect to CU (exp(b) = 2.98, p < .001). CSF-AQP4 and FW-WM were significantly higher in both less atrophic AD (exp(b) = 2.20, p = .006; exp(b) = 1.08, p = .019, respectively) and nAD patients (exp(b) = 2.66, p = .002; exp(b) = 1.10, p = .019, respectively) compared to CU subjects. Higher total (exp(b) = 1.59, p = .013) and centrum semiovale PVS counts (exp(b) = 1.89, p = .016), total (exp(b) = 1.50, p = .036) and WM PVSVF (exp(b) = 1.89, p = .005) together with lower MK-WM (exp(b) = 0.94, p = .006), mean and left ALPS (exp(b) = 0.91, p = .043; exp(b) = 0.88, p = .010 respectively) were observed in more atrophic AD patients in respect to CU. In addition, more atrophic nAD patients exhibited higher levels of AQP4 (exp(b) = 3.39, p = .002) than CU. Our results indicate significant changes in putative MRI biomarkers of GS and CSF-AQP4 levels in AD and in other neurodegenerative dementias, suggesting a close interaction between glymphatic dysfunction and neurodegeneration, particularly in the case of AD. However, the usefulness of some of these biomarkers as indirect and standalone indices of glymphatic activity may be hindered by their dependence on disease stage and structural brain damage.

Advanced Brain Imaging in Central Nervous System Demyelinating Diseases

In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.

Pre-excitation gradients for eddy current nulled convex optimized diffusion encoding (Pre-ENCODE)

PURPOSE

To evaluate the use of pre-excitation gradients for eddy current-nulled convex optimized diffusion encoding (Pre-ENCODE) to mitigate eddy current-induced image distortions in diffusion-weighted MRI (DWI).

METHODS

DWI sequences using monopolar (MONO), ENCODE, and Pre-ENCODE were evaluated in terms of the minimum achievable echo time (TE  min $$ {}_{\mathrm{min}} $$ ) and eddy current-induced image distortions using simulations, phantom experiments, and in vivo DWI in volunteers (N = 6 $$ N=6 $$ ).

RESULTS

Pre-ENCODE provided a shorter TE  min $$ {}_{\mathrm{min}} $$ than MONO (71.0± $$ \pm $$ 17.7ms vs. 77.6± $$ \pm $$ 22.9ms) and ENCODE (71.0± $$ \pm $$ 17.7ms vs. 86.2± $$ \pm $$ 14.2ms) in 100% $$ \% $$ of the simulated cases for a commercial 3T MRI system with b-values ranging from 500 to 3000 s/mm  2 $$ {}^2 $$ and in-plane spatial resolutions ranging from 1.0 to 3.0mm  2 $$ {}^2 $$ . Image distortion was estimated by intravoxel signal variance between diffusion encoding directions near the phantom edges and was significantly lower with Pre-ENCODE than with MONO (10.1% $$ \% $$ vs. 22.7% $$ \% $$ ,p = 6 - 5 $$ p={6}^{-5} $$ ) and comparable to ENCODE (10.1% $$ \% $$ vs. 10.4% $$ \% $$ ,p = 0 . 12 $$ p=0.12 $$ ). In vivo measurements of apparent diffusion coefficients were similar in global brain pixels (0.37 [0.28,1.45]× 1 0 - 3 $$ \times 1{0}^{-3} $$ mm  2 $$ {}^2 $$ /s vs. 0.38 [0.28,1.45]× 1 0 - 3 $$ \times 1{0}^{-3} $$ mm  2 $$ {}^2 $$ /s,p = 0 . 25 $$ p=0.25 $$ ) and increased in edge brain pixels (0.80 [0.17,1.49]× 1 0 - 3 $$ \times 1{0}^{-3} $$ mm  2 $$ {}^2 $$ /s vs. 0.70 [0.18,1.48]× 1 0 - 3 $$ \times 1{0}^{-3} $$ mm  2 $$ {}^2 $$ /s,p = 0 . 02 $$ p=0.02 $$ ) for MONO compared to Pre-ENCODE.

CONCLUSION

Pre-ENCODE mitigated eddy current-induced image distortions for diffusion imaging with a shorter TE  min $$ {}_{\mathrm{min}} $$ than MONO and ENCODE.

Connectome reorganization associated with temporal lobe pathology and its surgical resection

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and interindividual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.

Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source tool mrQA

Pooling data across diverse sources acquired by multisite consortia requires compliance with a predefined reference protocol i.e., ensuring different sites and scanners for a given project have used identical or compatible MR physics parameter values. Traditionally, this has been an arduous and manual process due to difficulties in working with the complicated DICOM standard and lack of resources allocated towards protocol compliance. Moreover, issues of protocol compliance is often overlooked for lack of realization that parameter values are routinely improvised/modified locally at various sites. The inconsistencies in acquisition protocols can reduce SNR, statistical power, and in the worst case, may invalidate the results altogether. An open-source tool, mrQA was developed to automatically assess protocol compliance on standard dataset formats such as DICOM and BIDS, and to study the patterns of non-compliance in over 20 open neuroimaging datasets, including the large ABCD study. The results demonstrate that the lack of compliance is rather pervasive. The frequent sources of non-compliance include but are not limited to deviations in Repetition Time, Echo Time, Flip Angle, and Phase Encoding Direction. It was also observed that GE and Philips scanners exhibited higher rates of non-compliance relative to the Siemens scanners in the ABCD dataset. Continuous monitoring for protocol compliance is strongly recommended before any pre/post-processing, ideally right after the acquisition, to avoid the silent propagation of severe/subtle issues. Although, this study focuses on neuroimaging datasets, the proposed tool mrQA can work with any DICOM-based datasets.

A comparison of white matter microstructure and correlates with neuropsychological measures in younger and older adults

OBJECTIVE

With a globally aging population, there is a need to better understand how brain structure relates to function in healthy older and younger adults.

METHODS

34 healthy participants divided into older (17; Mean = 70.9, SD = 5.4) and younger adults (17; Mean = 28.1, SD = 2.8) underwent diffusion-weighted imaging and neuropsychological assessment, including the California Verbal Learning Test 2nd Edition and the Trail Making Test (TMT-A and TMT-B). Differences in white matter microstructure for older and younger adults and the association between DTI metrics (fractional anisotropy, FA; mean diffusivity, MD) and cognitive performance were analyzed using tract-based spatial statistics (p < 0.05, corrected).

RESULTS

Older adults had significantly lower FA and higher MD than younger adults in widespread brain regions. There was a significant negative correlation between executive function (TMT-B) and MD for older adults in the right superior/anterior corona radiata and the corpus callosum. No significant relationship was detected between DTI metrics and executive function in younger adults or with memory performance in either group.

CONCLUSIONS

The findings underscore the need to examine brain-behaviour relationships as a function of age. Future studies should include comprehensive assessments in larger lifespan samples to better understand the aging brain.

A review of diffusion MRI in mood disorders: mechanisms and predictors of treatment response

By measuring the molecular diffusion of water molecules in brain tissue, diffusion MRI (dMRI) provides unique insight into the microstructure and structural connections of the brain in living subjects. Since its inception, the application of dMRI in clinical research has expanded our understanding of the possible biological bases of psychiatric disorders and successful responses to different therapeutic interventions. Here, we review the past decade of diffusion imaging-based investigations with a specific focus on studies examining the mechanisms and predictors of therapeutic response in people with mood disorders. We present a brief overview of the general application of dMRI and key methodological developments in the field that afford increasingly detailed information concerning the macro- and micro-structural properties and connectivity patterns of white matter (WM) pathways and their perturbation over time in patients followed prospectively while undergoing treatment. This is followed by a more in-depth summary of particular studies using dMRI approaches to examine mechanisms and predictors of clinical outcomes in patients with unipolar or bipolar depression receiving pharmacological, neurostimulation, or behavioral treatments. Limitations associated with dMRI research in general and with treatment studies in mood disorders specifically are discussed, as are directions for future research. Despite limitations and the associated discrepancies in findings across individual studies, evolving research strongly indicates that the field is on the precipice of identifying and validating dMRI biomarkers that could lead to more successful personalized treatment approaches and could serve as targets for evaluating the neural effects of novel treatments.

Advances in DTI studies for diagnoses and treatment of obsessive-compulsive disorder

This review summarizes the current state of neuroimaging research on obsessive-compulsive disorder (OCD) using diffusion tensor imaging (DTI), which allows for the examination of white matter abnormalities in the brain. DTI studies on individuals with obsessive-compulsive disorder (OCD) consistently demonstrate widespread reductions in white matter integrity in various regions of the brain, including the corpus callosum, anterior and posterior cingulate cortex, and prefrontal cortex, which are involved in emotion regulation, decision-making, and cognitive control. However, the reviewed studies often have small sample sizes, and findings vary between studies, highlighting the need for larger and more standardized studies. Furthermore, discerning between causal and consequential effects of OCD on white matter integrity poses a challenge. Addressing this issue may be facilitated through longitudinal studies, including those evaluating the impact of treatment interventions, to enhance the accuracy of DTI data acquisition and processing, thereby improving the validity and comparability of study outcomes. In summary, DTI studies provide valuable insights into the neural circuits and connectivity disruptions in OCD, and future studies may benefit from standardized data analysis and larger sample sizes to determine whether structural abnormalities could be potential biomarkers for early identification and treatment of OCD.

Differential Effects of Aging on Regional Corpus Callosum Microstructure and the Modifying Influence of Pulse Pressure

The corpus callosum is composed of several subregions, distinct in cellular and functional organization. This organization scheme may render these subregions differentially vulnerable to the aging process. Callosal integrity may be further compromised by cardiovascular risk factors, which negatively influence white matter health. Here, we test for heterochronicity of aging, hypothesizing an anteroposterior gradient of vulnerability to aging that may be altered by the effects of cardiovascular health. In 174 healthy adults across the adult lifespan (mean age = 53.56 ± 18.90; range, 20-94 years old, 58.62% women), pulse pressure (calculated as participant's systolic minus diastolic blood pressure) was assessed to determine cardiovascular risk. A deterministic tractography approach via diffusion-weighted imaging was utilized to extract fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) from each of five callosal subregions, serving as estimates of microstructural health. General linear models tested the effects of age, hypertension, and pulse pressure on these cross-sectional metrics. We observed no significant effect of hypertensive diagnosis on callosal microstructure. We found a significant main effect of age and an age-pulse pressure interaction whereby older age and elevated pulse pressure were associated with poorer FA, AD, and RD. Age effects revealed nonlinear components and occurred along an anteroposterior gradient of severity in the callosum. This gradient disappeared when pulse pressure was considered. These results indicate that age-related deterioration across the callosum is regionally variable and that pulse pressure, a proxy of arterial stiffness, exacerbates this aging pattern in a large lifespan cohort.

Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected

HIV exposed-uninfected (HEU) infants and children are at risk of developmental delays as compared to HIV uninfected unexposed (HUU) populations. The effects of exposure to in utero HIV and ART regimens on the HEU the developing brain are not well understood. In a cohort of 2-week-old newborns, we used diffusion tensor imaging (DTI) tractography and graph theory to examine the influence of HIV and ART exposure in utero on neonate white matter integrity and organisation. The cohort included HEU infants born to mothers who started ART before conception (HEUpre) and after conception (HEUpost), as well as HUU infants from the same community. We investigated HIV exposure and ART duration group differences in DTI metrics (fractional anisotropy (FA) and mean diffusivity (MD)) and graph measures across white matter. We found increased MD in white matter connections involving the thalamus and limbic system in the HEUpre group compared to HUU. We further identified reduced nodal efficiency in the basal ganglia. Within the HEUpost group, we observed reduced FA in cortical-subcortical and cerebellar connections as well as decreased transitivity in the hindbrain area compared to HUU. Overall, our analysis demonstrated distinct alterations in white matter integrity related to the timing of maternal ART initiation that influence regional brain network properties.

In humans, insulo-striate structural connectivity is largely biased toward either striosome-like or matrix-like striatal compartments

The insula is an integral component of sensory, motor, limbic, and executive functions, and insular dysfunction is associated with numerous human neuropsychiatric disorders. Insular afferents project widely, but insulo-striate projections are especially numerous. The targets of these insulo-striate projections are organized into tissue compartments, the striosome and matrix. These striatal compartments have distinct embryologic origins, afferent and efferent connectivity, dopamine pharmacology, and susceptibility to injury. Striosome and matrix appear to occupy separate sets of cortico-striato-thalamo-cortical loops, so a bias in insulo-striate projections towards one compartment may also embed an insular subregion in distinct regulatory and functional networks. Compartment-specific mapping of insulo-striate structural connectivity is sparse; the insular subregions are largely unmapped for compartment-specific projections. In 100 healthy adults, we utilized probabilistic diffusion tractography to map and quantify structural connectivity between 19 structurally-defined insular subregions and each striatal compartment. Insulo-striate streamlines that reached striosome-like and matrix-like voxels were concentrated in distinct insular zones (striosome: rostro- and caudoventral; matrix: caudodorsal) and followed different paths to reach the striatum. Though tractography was generated independently in each hemisphere, the spatial distribution and relative bias of striosome-like and matrix-like streamlines were highly similar in the left and right insula. 16 insular subregions were significantly biased towards one compartment: seven toward striosome-like voxels and nine toward matrix-like voxels. Striosome-favoring bundles had significantly higher streamline density, especially from rostroventral insular subregions. The biases in insulo-striate structural connectivity we identified mirrored the compartment-specific biases identified in prior studies that utilized injected tract tracers, cytoarchitecture, or functional MRI. Segregating insulo-striate structural connectivity through either striosome or matrix may be an anatomic substrate for functional specialization among the insular subregions.

Superficial white matter microstructural imaging method based on time-space fractional-order diffusion

Objective. Microstructure imaging based on diffusion magnetic resonance signal is an advanced imaging technique that enablesin vivomapping of the brain's microstructure. Superficial white matter (SWM) plays an important role in brain development, maturation, and aging, while fewer microstructure imaging methods address the SWM due to its complexity. Therefore, this study aims to develop a diffusion propagation model to investigate the microstructural characteristics of the SWM region.Approach. In this paper, we hypothesize that the effect of cell membrane permeability and the water exchange between soma and dendrites cannot be neglected for typical clinical diffusion times (20 ms Collapse

Key Words

• anomalous diffusion
• diffusion magnetic resonance imaging
• fractional diffusion equation
• microstructure imaging
• superficial white matter

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MESH Headings Collapse

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Affiliation(s)

Jianglin He School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China
Yuanjun Wang School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China

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Eddy current-induced artifact correction in high b-value ex vivo human brain diffusion MRI with dynamic field monitoring

PURPOSE

To investigate whether spatiotemporal magnetic field monitoring can correct pronounced eddy current-induced artifacts incurred by strong diffusion-sensitizing gradients up to 300 mT/m used in high b-value diffusion-weighted (DW) EPI.

METHODS

A dynamic field camera equipped with 16 1 H NMR field probes was first used to characterize field perturbations caused by residual eddy currents from diffusion gradients waveforms in a 3D multi-shot EPI sequence on a 3T Connectom scanner for different gradient strengths (up to 300 mT/m), diffusion directions, and shots. The efficacy of dynamic field monitoring-based image reconstruction was demonstrated on high-gradient strength, submillimeter resolution whole-brain ex vivo diffusion MRI. A 3D multi-shot image reconstruction framework was developed that incorporated the nonlinear phase evolution measured with the dynamic field camera.

RESULTS

Phase perturbations in the readout induced by residual eddy currents from strong diffusion gradients are highly nonlinear in space and time, vary among diffusion directions, and interfere significantly with the image encoding gradients, changing the k-space trajectory. During the readout, phase modulations between odd and even EPI echoes become non-static and diffusion encoding direction-dependent. Superior reduction of ghosting and geometric distortion was achieved with dynamic field monitoring compared to ghosting reduction approaches such as navigator- and structured low-rank-based methods or MUSE followed by image-based distortion correction with the FSL tool "eddy."

CONCLUSION

Strong eddy current artifacts characteristic of high-gradient strength DW-EPI can be well corrected with dynamic field monitoring-based image reconstruction.

White matter fiber integrity and structural brain network topology: implications for balance function in postischemic stroke patients

Previous studies have suggested that ischemic stroke can result in white matter fiber injury and modifications in the structural brain network. However, the relationship with balance function scores remains insufficiently explored. Therefore, this study aims to explore the alterations in the microstructural properties of brain white matter and the topological characteristics of the structural brain network in postischemic stroke patients and their potential correlations with balance function. We enrolled 21 postischemic stroke patients and 21 age, sex, and education-matched healthy controls (HC). All participants underwent balance function assessment and brain diffusion tensor imaging. Tract-based spatial statistics (TBSS) were used to compare the fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity of white matter fibers between the two groups. The white matter structural brain network was constructed based on the automated anatomical labeling atlas, and we conducted a graph theory-based analysis of its topological properties, including global network properties and local node properties. Additionally, the correlation between the significant structural differences and balance function score was analyzed. The TBSS results showed that in comparison to the HC, postischemic stroke patients exhibited extensive damage to their whole-brain white matter fiber tracts (P < 0.05). Graph theory analysis showed that in comparison to the HC, postischemic stroke patients exhibited statistically significant reductions in the values of global efficiency, local efficiency, and clustering coefficient, as well as an increase in characteristic path length (P < 0.05). In addition, the degree centrality and nodal efficiency of some nodes in postischemic stroke patients were significantly reduced (P < 0.05). The white matter fibers of the entire brain in postischemic stroke patients are extensively damaged, and the topological properties of the structural brain network are altered, which are closely related to balance function. This study is helpful in further understanding the neural mechanism of balance function after ischemic stroke from the white matter fiber and structural brain network topological properties.

Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected

HIV exposed-uninfected (HEU) infants and children are at risk of developmental delays as compared to uninfected unexposed (HUU) populations. The effects of exposure to in utero HIV and ART regimens on the HEU the developing brain are not well understood. In a cohort of 2-week-old newborns, we used diffusion tensor imaging (DTI) tractography and graph theory to examine the influence of HIV and ART exposure in utero on neonate white matter integrity and organisation. The cohort included HEU infants born to mothers who started ART before conception (HEUpre) and after conception (HEUpost), as well as HUU infants from the same community. We investigated HIV exposure and ART duration group differences in DTI metrics (fractional anisotropy (FA) and mean diffusivity (MD)) and graph measures across white matter. We found increased MD in white matter connections involving the thalamus and limbic system in the HEUpre group compared to HUU. We further identified reduced nodal efficiency in the basal ganglia. Within the HEUpost group, we observed reduced FA in cortical-subcortical and cerebellar connections as well as decreased transitivity in the hindbrain area compared to HUU. Overall, our analysis demonstrated distinct alterations in white matter integrity related to the timing of maternal ART initiation that influence regional brain network properties.

Free water alterations in different inflammatory subgroups in schizophrenia

BACKGROUND

Accumulating evidence suggests that inflammatory dysregulation both in blood and the brain is implicated in the pathogenesis of schizophrenia. Alterations in peripheral cytokines are not evident in all patients and there may be discrete altered inflammatory subgroups in schizophrenia. Recent studies using a novel and in vivo free-water imaging to detect inflammatory processes, have shown increased free water in white matter in schizophrenia. However, no studies to date have investigated the free water alterations in different inflammatory subgroups in schizophrenia.

METHODS

Forty-four patients with schizophrenia and 49 controls were recruited. The serum levels of interleukin-1 beta (IL-1β), IL-6, IL-10, and IL-12p70 were measured and used for cluster analysis with K-means and hierarchical algorithms. Diffusion tensor imaging (DTI) images were collected for all participants and voxel-wise free water and fractional anisotropy of tissue (FA-t) were compared between groups with Randomise running in FSL. Partial correlation analysis was employed to explore the association of the peripheral cytokine levels with free water.

RESULTS

We identified two statistically quantifiable discrete subgroups of patients based on the cluster analysis of cytokine measures. The peripheral levels of IL-1β (P < 0.001), IL-10 (P = 0.041), and IL-12p70 (P < 0.001) showed significant differences between the two different inflammatory subgroups. In the inflammatory subgroup with a predominantly higher IL-1β level, increased free water values in white matter were found mainly in the left posterior limb of the internal capsule, posterior corona radiata, and partly in the left sagittal stratum. These affected areas did not overlap with the regions that showed significant free water differences between patients and healthy controls. In the inflammatory subgroup with lower IL-1β levels, peripheral IL-1β was significantly associated with free water values in white matter while no such association was detected in the patient group.

CONCLUSIONS

Localized free water differences were demonstrated between the two identified inflammatory subgroups in our data, and free water appears to be a feasible in vivo neuroimaging biomarker guiding the target of inflammatory intervention and development of new therapeutic strategies in an individualized manner in schizophrenia.

Efficiency and Accuracy Evaluation of Multiple Diffusion-Weighted MRI Techniques Across Different Scanners

BACKGROUND

The choice between different diffusion-weighted imaging (DWI) techniques is difficult as each comes with tradeoffs for efficient clinical routine imaging and apparent diffusion coefficient (ADC) accuracy.

PURPOSE

To quantify signal-to-noise-ratio (SNR) efficiency, ADC accuracy, artifacts, and distortions for different DWI acquisition techniques, coils, and scanners.

STUDY TYPE

Phantom, in vivo intraindividual biomarker accuracy between DWI techniques and independent ratings.

POPULATION/PHANTOMS

NIST diffusion phantom. 51 Patients: 40 with prostate cancer and 11 with head-and-neck cancer at 1.5 T FIELD STRENGTH/SEQUENCE: Echo planar imaging (EPI): 1.5 T and 3 T Siemens; 3 T Philips. Distortion-reducing: RESOLVE (1.5 and 3 T Siemens); Turbo Spin Echo (TSE)-SPLICE (3 T Philips). Small field-of-view (FOV): ZoomitPro (1.5 T Siemens); IRIS (3 T Philips). Head-and-neck and flexible coils.

ASSESSMENT

SNR Efficiency, geometrical distortions, and susceptibility artifacts were quantified for different b-values in a phantom. ADC accuracy/agreement was quantified in phantom and for 51 patients. In vivo image quality was independently rated by four experts.

STATISTICAL TESTS

QIBA methodology for accuracy: trueness, repeatability, reproducibility, Bland-Altman 95% Limits-of-Agreement (LOA) for ADC. Wilcoxon Signed-Rank and student tests on P < 0.05 level.

RESULTS

The ZoomitPro small FOV sequence improved b-image efficiency by 8%-14%, reduced artifacts and observer scoring for most raters at the cost of smaller FOV compared to EPI. The TSE-SPLICE technique reduced artifacts almost completely at a 24% efficiency cost compared to EPI for b-values ≤500 sec/mm2 . Phantom ADC 95% LOA trueness were within ±0.03 × 10-3  mm2 /sec except for small FOV IRIS. The in vivo ADC agreement between techniques, however, resulted in 95% LOAs in the order of ±0.3 × 10-3  mm2 /sec with up to 0.2 × 10-3  mm2 /sec of bias.

DATA CONCLUSION

ZoomitPro for Siemens and TSE SPLICE for Philips resulted in a trade-off between efficiency and artifacts. Phantom ADC quality control largely underestimated in vivo accuracy: significant ADC bias and variability was found between techniques in vivo.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

An imaging review of the hippocampus and its common pathologies

The hippocampus is a complex structure located in the mesial temporal lobe that plays a critical role in cognitive and memory-related processes. The hippocampal formation consists of the dentate gyrus, hippocampus proper, and subiculum, and its importance in the neural circuitry makes it a key anatomic structure to evaluate in neuroimaging studies. Advancements in imaging techniques now allow detailed assessment of hippocampus internal architecture and signal features that has improved identification and characterization of hippocampal abnormalities. This review aims to summarize the neuroimaging features of the hippocampus and its common pathologies. It provides an overview of the hippocampal anatomy on magnetic resonance imaging and discusses how various imaging techniques can be used to assess the hippocampus. The review explores neuroimaging findings related to hippocampal variants (incomplete hippocampal inversion, sulcal remnant and choroidal fissure cysts), and pathologies of neoplastic (astrocytoma and glioma, ganglioglioma, dysembryoplastic neuroepithelial tumor, multinodular and vacuolating neuronal tumor, and metastasis), epileptic (mesial temporal sclerosis and focal cortical dysplasia), neurodegenerative (Alzheimer's disease, progressive primary aphasia, and frontotemporal dementia), infectious (Herpes simplex virus and limbic encephalitis), vascular (ischemic stroke, arteriovenous malformation, and cerebral cavernous malformations), and toxic-metabolic (transient global amnesia and opioid-associated amnestic syndrome) etiologies.

The effects of physical activity on white matter microstructure in children with overweight or obesity: The ActiveBrains randomized clinical trial

Background

Emerging research supports the idea that physical activity benefits brain development. However, the body of evidence focused on understanding the effects of physical activity on white matter microstructure during childhood is still in its infancy, and further well-designed randomized clinical trials are needed.

Aim

This study aimed: (i) to investigate the effects of a 20-week physical activity intervention on global white matter microstructure in children with overweight or obesity, and (ii) to explore whether the effect of physical activity on white matter microstructure is global or restricted to a particular set of white matter bundles.

Methods

In total, 109 children aged 8 to 11 years with overweight or obesity were randomized and allocated to either the physical activity program or the control group. Data were collected from November 2014 to June 2016, with diffusion tensor imaging (DTI) data processing and analyses conducted between June 2017 and November 2021. Images were pre-processed using the Functional Magnetic Resonance Imaging (MRI) of the Brain´s Software Library (FSL) and white matter properties were explored by probabilistic fiber tractography and tract-based spatial statistics (TBSS).

Results

Intention-to-treat analyses were performed for all children who completed the pre-test and post-test DTI assessment, with good quality DTI data (N = 89). Of them, 83 children (10.06±1.11 years, 39 % girls, intervention group=44) met the per-protocol criteria (attended at least 70 % of the recommended sessions). Our probabilistic fiber tractography analysis did not show any effects in terms of global and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) in the per-protocol or intention-to-treat analyses. Additionally, we did not observe any effects on the voxel-wise DTI parameters (i.e., FA and MD) using the most restricted TBSS approach (i.e., per protocol analyses and p-corrected image with a statistical threshold of p < 0.05). In the intention-to-treat analysis, we found that our physical activity program had a borderline effect (p-corrected image with a statistical threshold of p < 0.1) on 7 different clusters, including a cluster in the corpus callosum.

Conclusion

We conclude that a 20-week physical activity intervention was not enough to induce changes in global and tract-specific white matter during childhood. The effects of physical activity on white matter microstructure could be restricted to local changes in several white matter tracts (e.g., the body of the corpus callosum). However, our results were not significant, and more interventions are needed to determine whether and how physical activity affects white matter microstructure during childhood.

Can hubs of the human connectome be identified consistently with diffusion MRI?

Recent years have seen a surge in the use of diffusion MRI to map connectomes in humans, paralleled by a similar increase in processing and analysis choices. Yet these different steps and their effects are rarely compared systematically. Here, in a healthy young adult population (n = 294), we characterized the impact of a range of analysis pipelines on one widely studied property of the human connectome: its degree distribution. We evaluated the effects of 40 pipelines (comparing common choices of parcellation, streamline seeding, tractography algorithm, and streamline propagation constraint) and 44 group-representative connectome reconstruction schemes on highly connected hub regions. We found that hub location is highly variable between pipelines. The choice of parcellation has a major influence on hub architecture, and hub connectivity is highly correlated with regional surface area in most of the assessed pipelines (ρ > 0.70 in 69% of the pipelines), particularly when using weighted networks. Overall, our results demonstrate the need for prudent decision-making when processing diffusion MRI data, and for carefully considering how different processing choices can influence connectome organization.

Diffusion MRI with free gradient waveforms on a high-performance gradient system: Probing restriction and exchange in the human brain

The dependence of the diffusion MRI signal on the diffusion time carries signatures of restricted diffusion and exchange. Here we seek to highlight these signatures in the human brain by performing experiments using free gradient waveforms designed to be selectively sensitive to the two effects. We examine six healthy volunteers using both strong and ultra-strong gradients (80, 200 and 300 mT/m). In an experiment featuring a large set of 150 gradient waveforms with different sensitivities to restricted diffusion and exchange, our results reveal unique and different time-dependence signatures in grey and white matter. Grey matter was characterised by both restricted diffusion and exchange and white matter predominantly by restricted diffusion. Exchange in grey matter was at least twice as fast as in white matter, across all subjects and all gradient strengths. The cerebellar cortex featured relatively short exchange times (115 ms). Furthermore, we show that gradient waveforms with tailored designs can be used to map exchange in the human brain. We also assessed the feasibility of clinical applications of the method used in this work and found that the exchange-related contrast obtained with a 25-minute protocol at 300 mT/m was preserved in a 4-minute protocol at 300 mT/m and a 10-minute protocol at 80 mT/m. Our work underlines the utility of free waveforms for detecting time dependence signatures due to restricted diffusion and exchange in vivo, which may potentially serve as a tool for studying diseased tissue.

Assessing individual variability of the entorhinal subfields in health and disease

Investigating interindividual variability is a major field of interest in neuroscience. The entorhinal cortex (EC) is essential for memory and affected early in the progression of Alzheimer's disease (AD). We combined histology ground-truth data with ultrahigh-resolution 7T ex vivo MRI to analyze EC interindividual variability in 3D. Further, we characterized (1) entorhinal shape as a whole, (2) entorhinal subfield range and midpoints, and (3) subfield architectural location and tau burden derived from 3D probability maps. Our results indicated that EC shape varied but was not related to demographic or disease factors at this preclinical stage. The medial intermediate subfield showed the highest degree of location variability in the probability maps. However, individual subfields did not display the same level of variability across dimensions and outcome measure, each providing a different perspective. For example, the olfactory subfield showed low variability in midpoint location in the superior-inferior dimension but high variability in anterior-posterior, and the subfield entorhinal intermediate showed a large variability in volumetric measures but a low variability in location derived from the 3D probability maps. These findings suggest that interindividual variability within the entorhinal subfields requires a 3D approach incorporating multiple outcome measures. This study provides 3D probability maps of the individual entorhinal subfields and respective tau pathology in the preclinical stage (Braak I and II) of AD. These probability maps illustrate the subfield average and may serve as a checkpoint for future modeling.

Automated motion artifact detection in early pediatric diffusion MRI using a convolutional neural network

Diffusion MRI (dMRI) is a widely used method to investigate the microstructure of the brain. Quality control (QC) of dMRI data is an important processing step that is performed prior to analysis using models such as diffusion tensor imaging (DTI) or neurite orientation dispersion and density imaging (NODDI). When processing dMRI data from infants and young children, where intra-scan motion is common, the identification and removal of motion artifacts is of the utmost importance. Manual QC of dMRI data is (1) time-consuming due to the large number of diffusion directions, (2) expensive, and (3) prone to subjective errors and observer variability. Prior techniques for automated dMRI QC have mostly been limited to adults or school-age children. Here, we propose a deep learning-based motion artifact detection tool for dMRI data acquired from infants and toddlers. The proposed framework uses a simple three-dimensional convolutional neural network (3DCNN) trained and tested on an early pediatric dataset of 2,276 dMRI volumes from 121 exams acquired at 1 month and 24 months of age. An average classification accuracy of 95% was achieved following four-fold cross-validation. A second dataset with different acquisition parameters and ages ranging from 2-36 months (consisting of 2,349 dMRI volumes from 26 exams) was used to test network generalizability, achieving 98% classification accuracy. Finally, to demonstrate the importance of motion artifact volume removal in a dMRI processing pipeline, the dMRI data were fit to the DTI and NODDI models and the parameter maps were compared with and without motion artifact removal.

Quantitative Validation of the Correlation Between Optimized Pyramidal Tract Delineation After Brain Shift Compensation and Direct Electrical Subcortical Stimulation During Brain Tumor Surgery

It remains unclear whether tractography of pyramidal tracts is correlated with the intraoperative direct electrical subcortical stimulation (DESS), and brain shift further complicates the issue. The objective of this research is to quantitatively verify the correlation between optimized tractography (OT) of pyramidal tracts after brain shift compensation and DESS during brain tumor surgery. OT was performed for 20 patients with lesions in proximity to the pyramidal tracts based on preoperative diffusion-weighted magnetic resonance imaging. During surgery, tumor resection was guided by DESS. A total of 168 positive stimulation points and their corresponding stimulation intensity thresholds were recorded. Using the brain shift compensation algorithm based on hierarchical B-spline grids combined with a Gaussian resolution pyramid, we warped the preoperative pyramidal tract models and used receiver operating characteristic (ROC) curves to investigate the reliability of our brain shift compensation method based on anatomic landmarks. Additionally, the minimum distance between the DESS points and warped OT (wOT) model was measured and correlated with DESS intensity threshold. Brain shift compensation was achieved in all cases, and the area under the ROC curve was 0.96 in the registration accuracy analysis. The minimum distance between the DESS points and the wOT model was found to have a significantly high correlation with the DESS stimulation intensity threshold (r = 0.87, P < 0.001), with a linear regression coefficient of 0.96. Our OT method can provide comprehensive and accurate visualization of the pyramidal tracts for neurosurgical navigation and was quantitatively verified by intraoperative DESS after brain shift compensation.

The Challenge of Diffusion Magnetic Resonance Imaging in Cerebral Palsy: A Proposed Method to Identify White Matter Pathways

Cerebral palsy (CP), a neuromotor disorder characterized by prenatal brain lesions, leads to white matter alterations and sensorimotor deficits. However, the CP-related diffusion neuroimaging literature lacks rigorous and consensual methodology for preprocessing and analyzing data due to methodological challenges caused by the lesion extent. Advanced methods are available to reconstruct diffusion signals and can update current advances in CP. Our study demonstrates the feasibility of analyzing diffusion CP data using a standardized and open-source pipeline. Eight children with CP (8-12 years old) underwent a single diffusion magnetic resonance imaging (MRI) session on a 3T scanner (Achieva 3.0T (TX), Philips Healthcare Medical Systems, Best, The Netherlands). Exclusion criteria were contraindication to MRI and claustrophobia. Anatomical and diffusion images were acquired. Data were corrected and analyzed using Tractoflow 2.3.0 version, an open-source and robust tool. The tracts were extracted with customized procedures based on existing atlases and freely accessed standardized libraries (ANTs, Scilpy). DTI, CSD, and NODDI metrics were computed for each tract. Despite lesion heterogeneity and size, we successfully reconstructed major pathways, except for a participant with a larger lesion. Our results highlight the feasibility of identifying and quantifying subtle white matter pathways. Ultimately, this will increase our understanding of the clinical symptoms to provide precision medicine and optimize rehabilitation.

Lateralization of major white matter tracts during infancy is time-varying and tract-specific

Lateralization patterns are a major structural feature of brain white matter and have been investigated as a neural architecture that indicates and supports the specialization of cognitive processing and observed behaviors, e.g. language skills. Many neurodevelopmental disorders have been associated with atypical lateralization, reinforcing the need for careful measurement and study of this structural characteristic. Unfortunately, there is little consensus on the direction and magnitude of lateralization in major white matter tracts during the first months and years of life-the period of most rapid postnatal brain growth and cognitive maturation. In addition, no studies have examined white matter lateralization in a longitudinal pediatric sample-preventing confirmation of if and how white matter lateralization changes over time. Using a densely sampled longitudinal data set from neurotypical infants aged 0-6 months, we aim to (i) chart trajectories of white matter lateralization in 9 major tracts and (ii) link variable findings from cross-sectional studies of white matter lateralization in early infancy. We show that patterns of lateralization are time-varying and tract-specific and that differences in lateralization results during this period may reflect the dynamic nature of lateralization through development, which can be missed in cross-sectional studies.

Diffusion-weighted Breast MRI at 3 Tesla: Improved Lesion Visibility and Image Quality with a Combination of Water-excitation and Spectral Fat Saturation

RATIONALE AND OBJECTIVES

In breast MRI with diffusion-weighted imaging (DWI), fat suppression is essential for eliminating the dominant lipid signal. This investigation evaluates a combined water-excitation-spectral-fatsat method (WEXfs) versus standard spectral attenuated inversion recovery (SPAIR) in high-resolution 3-Tesla breast MRI.

MATERIALS AND METHODS

Multiparametric breast MRI with 2 echo-planar DWI sequences was performed in 83 patients (50.1 ± 12.6 years) employing either WEXfs or SPAIR for fat signal suppression. Three radiologists assessed overall DWI quality and delineability of 88 focal lesions (28 malignant, 60 benign) on images with b values of 800 and 1600 s/mm2, as well as apparent diffusion coefficient (ADC) maps. For each fat suppression method and b value, the longest lesion diameter was determined in addition to measuring the signal intensity in DWI and ADC value in standardized regions of interest.

RESULTS

Regardless of b values, image quality (all p < 0.001) and lesion delineability (all p ≤ 0.003) with WEXfs-DWI were deemed superior compared to SPAIR-DWI in benign and malignant lesions. Irrespective of lesion characterization, WEXfs-DWI provided superior signal-to-noise, contrast-to-noise and signal-intensity ratios with 1600 s/mm2 (all p ≤ 0.05). The lesion size difference between contrast-enhanced T1 subtraction images and DWI was smaller for WEXfs compared to SPAIR fat suppression (all p ≤ 0.007). The mean ADC value in malignant lesions was lower for WEXfs-DWI (p < 0.001), while no significant ADC difference was ascertained between both techniques in benign lesions (p = 0.947).

CONCLUSION

WEXfs-DWI provides better subjective and objective image quality than standard SPAIR-DWI, resulting in a more accurate estimation of benign and malignant lesion size.

Metabolic syndrome and adiposity: Risk factors for decreased myelin in cognitively healthy adults

Metabolic syndrome (MetS) is a cluster of conditions that affects ∼25% of the global population, including excess adiposity, hyperglycemia, dyslipidemia, and elevated blood pressure. MetS is one of major risk factors not only for chronic diseases, but also for dementia and cognitive dysfunction, although the underlying mechanisms remain poorly understood. White matter is of particular interest in the context of MetS due to the metabolic vulnerability of myelin maintenance, and the accumulating evidence for the importance of the white matter in the pathophysiology of dementia. Therefore, we investigated the associations of MetS risk score and adiposity (combined body mass index and waist circumference) with myelin water fraction measured with myelin water imaging. In 90 cognitively and neurologically healthy adults (20-79 years), we found that both high MetS risk score and adiposity were correlated with lower myelin water fraction in late-myelinating prefrontal and associative fibers, controlling for age, sex, race, ethnicity, education and income. Our findings call for randomized clinical trials to establish causality between MetS, adiposity, and myelin content, and to explore the potential of weight loss and visceral adiposity reduction as means to support maintenance of myelin integrity throughout adulthood, which could open new avenues for prevention or treatment of cognitive decline and dementia.

versaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database

The lack of "gold standards" in Diffusion Weighted Imaging (DWI) makes validation cumbersome. To tackle this task, studies use translational analysis where results in humans are benchmarked against findings in other species. Non-Human Primates (NHP) are particularly interesting for this, as their cytoarchitecture is closely related to humans. However, tools used for processing and analysis must be adapted and finely tuned to work well on NHP images. Here, we propose versaFlow, a modular pipeline implemented in Nextflow, designed for robustness and scalability. The pipeline is tailored to in vivo NHP DWI at any spatial resolution; it allows for maintainability and customization. Processes and workflows are implemented using cutting-edge and state-of-the-art Magnetic Resonance Imaging (MRI) processing technologies and diffusion modeling algorithms, namely Diffusion Tensor Imaging (DTI), Constrained Spherical Deconvolution (CSD), and DIstribution of Anisotropic MicrOstructural eNvironments in Diffusion-compartment imaging (DIAMOND). Using versaFlow, we provide an in-depth study of the variability of diffusion metrics computed on 32 subjects from 3 sites of the Primate Data Exchange (PRIME-DE), which contains anatomical T1-weighted (T1w) and T2-weighted (T2w) images, functional MRI (fMRI), and DWI of NHP brains. This dataset includes images acquired over a range of resolutions, using single and multi-shell gradient samplings, on multiple scanner vendors. We perform a reproducibility study of the processing of versaFlow using the Aix-Marseilles site's data, to ensure that our implementation has minimal impact on the variability observed in subsequent analyses. We report very high reproducibility for the majority of metrics; only gamma distribution parameters of DIAMOND display less reproducible behaviors, due to the absence of a mechanism to enforce a random number seed in the software we used. This should be taken into consideration when future applications are performed. We show that the PRIME-DE diffusion data exhibits a great level of variability, similar or greater than results obtained in human studies. Its usage should be done carefully to prevent instilling uncertainty in statistical analyses. This hints at a need for sufficient harmonization in acquisition protocols and for the development of robust algorithms capable of managing the variability induced in imaging due to differences in scanner models and/or vendors.

TBSS++: A novel computational method for Tract-Based Spatial Statistics

Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. One of the most common computations in dMRI involves cross-subject tract-specific analysis, whereby dMRI-derived biomarkers are compared between cohorts of subjects. The accuracy and reliability of these studies hinges on the ability to compare precisely the same white matter tracts across subjects. This is an intricate and error-prone computation. Existing computational methods such as Tract-Based Spatial Statistics (TBSS) suffer from a host of shortcomings and limitations that can seriously undermine the validity of the results. We present a new computational framework that overcomes the limitations of existing methods via (i) accurate segmentation of the tracts, and (ii) precise registration of data from different subjects/scans. The registration is based on fiber orientation distributions. To further improve the alignment of cross-subject data, we create detailed atlases of white matter tracts. These atlases serve as an unbiased reference space where the data from all subjects is registered for comparison. Extensive evaluations show that, compared with TBSS, our proposed framework offers significantly higher reproducibility and robustness to data perturbations. Our method promises a drastic improvement in accuracy and reproducibility of cross-subject dMRI studies that are routinely used in neuroscience and medical research.

Along-Tract Statistical Mapping of Microstructural Abnormalities in Bipolar Disorder: A Pilot Study

Investigating brain circuitry involved in bipolar disorder (BD) is key to discovering brain biomarkers for genetic and interventional studies of the disorder. Even so, prior research has not provided a fine-scale spatial mapping of brain microstructural differences in BD. In this pilot diffusion MRI dataset, we used BUndle ANalytics (BUAN)-a recently developed analytic approach for tractography-to extract, map, and visualize the profile of microstructural abnormalities on a 3D model of fiber tracts in people with BD (N=38) and healthy controls (N=49), and investigate along-tract white matter (WM) microstructural differences between these groups. Using the BUAN pipeline, BD was associated with lower mean fractional anisotropy (FA) in fronto-limbic and interhemispheric pathways and higher mean FA in posterior bundles relative to controls.Clinical Relevance- BUAN combines tractography and anatomical information to capture distinct along-tract effects on WM microstructure that may aid in classifying diseases based on anatomical differences.

Physical activity and the brain myelin content in humans

New imaging sequences and biophysical models allow adopting magnetic resonance imaging (MRI) for in vivo myelin mapping in humans. Understanding myelination and remyelination processes in the brain is fundamental from the perspective of proper design of physical exercise and rehabilitation schemes that aim to slow down demyelination in the aging population and to induce remyelination in patients with neurodegenerative diseases. Therefore, in this review we strive to provide a state-of-the art summary of the existing MRI studies in humans focused on the effects of physical activity on myelination/remyelination. We present and discuss four cross-sectional and four longitudinal studies and one case report. Physical activity and an active lifestyle have a beneficial effect on the myelin content in humans. Myelin expansion can be induced in humans throughout the entire lifespan by intensive aerobic exercise. Additional research is needed to determine (1) what exercise intensity (and cognitive novelty, which is embedded in the exercise scheme) is the most beneficial for patients with neurodegenerative diseases, (2) the relationship between cardiorespiratory fitness and myelination, and (3) how exercise-induced myelination affect cognitive abilities.

Structural brain connectivity predicts early acute pain after mild traumatic brain injury

ABSTRACT

Mild traumatic brain injury (mTBI), is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute postinjury pain is important because it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 157 patients with mTBI, following a motorized vehicle collision. We extracted white matter structural connectivity networks and used a machine learning approach to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamiccortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in 2 independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6 months after the collision still predicted mTBI pain at that timepoint (n = 36). These white matter connections were associated with 2 nociceptive psychophysical outcomes tested at a remote body site-namely, conditioned pain modulation and magnitude of suprathreshold pain-and with pain sensitivity questionnaire scores. Our findings demonstrate a stable white matter network, the properties of which determine an important amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

The anatomical networks based on probabilistic structurally connectivity in bipolar disorder across mania, depression, and euthymic states

BACKGROUNDS

There have pieces of evidence of the distinct aberrant functional network topology profile in bipolar disorder (BD) across mania, depression, and euthymic episodes. However, the underlying anatomical network topology pattern in BD across different episodes is unclear.

METHODS

We calculated the whole-brain probabilistic structurally connectivity across 143 subjects (72 with BD [34 depression; 13 mania; 25 euthymic] and 53 healthy controls), and used graph theory to examine the trait- and state-related topology alterations of the structural connectome in BD. The correlation analysis was further conducted to explore the relationship between detected network measures and clinical symptoms.

RESULTS

There no omnibus alteration of any global network metrics were observed across all diagnostic groups. In the regional network metrics level, bipolar depression showed increased clustering coefficient in the right lingual gyrus compared with all other groups, and the increased clustering coefficient in the right lingual gyrus positively correlated with depression, anxiety, and illness burden symptoms but negatively correlated with mania symptoms; manic and euthymic patients showed decreased clustering coefficient in the left inferior occipital gyrus compared with HCs.

LIMITATIONS

The moderate sample size of all patient groups (especially for subjects with mania) might have contributed to the negative findings of the trait feature in this study.

CONCLUSIONS

We demonstrated the altered regional connectivity pattern in the occipital lobe of the bipolar depression and mania episode, especially the lingual gyrus. The association of the clustering coefficient in the lingual gyrus with clinical symptoms helps monitor the state of BD.

Quantitative MRI in leukodystrophies

Leukodystrophies constitute a large and heterogeneous group of genetic diseases primarily affecting the white matter of the central nervous system. Different disorders target different white matter structural components. Leukodystrophies are most often progressive and fatal. In recent years, novel therapies are emerging and for an increasing number of leukodystrophies trials are being developed. Objective and quantitative metrics are needed to serve as outcome measures in trials. Quantitative MRI yields information on microstructural properties, such as myelin or axonal content and condition, and on the chemical composition of white matter, in a noninvasive fashion. By providing information on white matter microstructural involvement, quantitative MRI may contribute to the evaluation and monitoring of leukodystrophies. Many distinct MR techniques are available at different stages of development. While some are already clinically applicable, others are less far developed and have only or mainly been applied in healthy subjects. In this review, we explore the background, current status, potential and challenges of available quantitative MR techniques in the context of leukodystrophies.

Current State of Diffusion-Weighted Imaging and Diffusion Tensor Imaging for Traumatic Brain Injury Prognostication

Advanced imaging techniques are needed to assist in providing a prognosis for patients with traumatic brain injury (TBI), particularly mild TBI (mTBI). Diffusion tensor imaging (DTI) is one promising advanced imaging technique, but has shown variable results in patients with TBI and is not without limitations, especially when considering individual patients. Efforts to resolve these limitations are being explored and include developing advanced diffusion techniques, creating a normative database, improving study design, and testing machine learning algorithms. This article will review the fundamentals of DTI, providing an overview of the current state of its utility in evaluating and providing prognosis in patients with TBI.

Integrating multimodality magnetic resonance imaging to the Allen Mouse Brain Common Coordinate Framework

High-resolution magnetic resonance imaging (MRI) affords unique image contrasts to nondestructively probe the tissue microstructure; validation of MRI findings with conventional histology is essential to better understand the MRI contrasts. However, the dramatic difference in the spatial resolution and image contrast of these two techniques impedes accurate comparison between MRI metrics and traditional histology. To better validate various MRI metrics, we acquired whole mouse brain multigradient recalled-echo and multishell diffusion MRI datasets at 25-μm isotropic resolution. The recently developed Allen Mouse Brain Common Coordinate Framework (CCFv3) provides opportunities to integrate multimodal and multiscale datasets of the whole mouse brain in a common three-dimensional (3D) space. The T2*, quantitative susceptibility mapping, diffusion tensor imaging, and neurite orientation dispersion and density imaging parameters were compared with both serial two-photon tomography images and 3D Nissl staining images in the CCFv3 at the same spatial resolution. The correlation between MRI and Nissl staining strongly depends on different metrics and different regions of the brain. Integrating different imaging modalities to the same space may substantially improve our understanding of the complexity of the brain at different scales.

Basal Ganglia Compensatory White Matter Changes on DTI in Alzheimer's Disease

The volume reduction of the gray matter structures in patients with Alzheimer's disease is often accompanied by an asymmetric increase in the number of white matter fibers located close to these structures. The present study aims to investigate the white matter structure changes in the motor basal ganglia in Alzheimer's disease patients compared to healthy controls using diffusion tensor imaging. The amounts of tracts, tract length, tract volume, quantitative anisotropy, and general fractional anisotropy were measured in ten patients with Alzheimer's disease and ten healthy controls. A significant decrease in the number of tracts and general fractional anisotropy was found in patients with Alzheimer's disease compared to controls in the right caudate nucleus, while an increase was found in the left and the right putamen. Further, a significant decrease in the structural volume of the left and the right putamen was observed. An increase in the white matter diffusion tensor imaging parameters in patients with Alzheimer's disease was observed only in the putamen bilaterally. The right caudate showed a decrease in both the diffusion tensor imaging parameters and the volume in Alzheimer's disease patients. The right pallidum showed an increase in the diffusion tensor imaging parameters but a decrease in volume in Alzheimer's disease patients.

A framework for focal and connectomic mapping of transiently disrupted brain function

The distributed nature of the neural substrate, and the difficulty of establishing necessity from correlative data, combine to render the mapping of brain function a far harder task than it seems. Methods capable of combining connective anatomical information with focal disruption of function are needed to disambiguate local from global neural dependence, and critical from merely coincidental activity. Here we present a comprehensive framework for focal and connective spatial inference based on sparse disruptive data, and demonstrate its application in the context of transient direct electrical stimulation of the human medial frontal wall during the pre-surgical evaluation of patients with focal epilepsy. Our framework formalizes voxel-wise mass-univariate inference on sparsely sampled data within the statistical parametric mapping framework, encompassing the analysis of distributed maps defined by any criterion of connectivity. Applied to the medial frontal wall, this transient dysconnectome approach reveals marked discrepancies between local and distributed associations of major categories of motor and sensory behaviour, revealing differentiation by remote connectivity to which purely local analysis is blind. Our framework enables disruptive mapping of the human brain based on sparsely sampled data with minimal spatial assumptions, good statistical efficiency, flexible model formulation, and explicit comparison of local and distributed effects.

Symmetric data-driven fusion of diffusion tensor MRI: Age differences in white matter

In the past 20 years, white matter (WM) microstructure has been studied predominantly using diffusion tensor imaging (DTI). Decreases in fractional anisotropy (FA) and increases in mean (MD) and radial diffusivity (RD) have been consistently reported in healthy aging and neurodegenerative diseases. To date, DTI parameters have been studied individually (e.g., only FA) and separately (i.e., without using the joint information across them). This approach gives limited insights into WM pathology, increases the number of multiple comparisons, and yields inconsistent correlations with cognition. To take full advantage of the information in a DTI dataset, we present the first application of symmetric fusion to study healthy aging WM. This data-driven approach allows simultaneous examination of age differences in all four DTI parameters. We used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) in cognitively healthy adults (age 20-33, n = 51 and age 60-79, n = 170). Four-way mCCA + jICA yielded one high-stability modality-shared component with co-variant patterns of age differences in RD and AD in the corpus callosum, internal capsule, and prefrontal WM. The mixing coefficients (or loading parameters) showed correlations with processing speed and fluid abilities that were not detected by unimodal analyses. In sum, mCCA + jICA allows data-driven identification of cognitively relevant multimodal components within the WM. The presented method should be further extended to clinical samples and other MR techniques (e.g., myelin water imaging) to test the potential of mCCA+jICA to discriminate between different WM disease etiologies and improve the diagnostic classification of WM diseases.

Model-based reconstructions for intravoxel incoherent motion and diffusion tensor imaging parameter map estimations

Intravoxel incoherent motion (IVIM) imaging and diffusion tensor imaging (DTI) facilitate noninvasive quantification of tissue perfusion and diffusion. Both are promising biomarkers in various diseases and a combined acquisition is therefore desirable. This comes with challenges, including noisy parameter maps and long scan times, especially for the perfusion fraction f and pseudo-diffusion coefficient D*. A model-based reconstruction has the potential to overcome these challenges. As a first step, our goal was to develop a model-based reconstruction framework for IVIM and combined IVIM-DTI parameter estimation. The IVIM and IVIM-DTI models were implemented in the PyQMRI model-based reconstruction framework and validated with simulations and in vivo data. Commonly used voxel-wise nonlinear least-squares fitting was used as the reference. Simulations with the IVIM and IVIM-DTI models were performed with 100 noise realizations to assess accuracy and precision. Diffusion-weighted data were acquired for IVIM reconstruction in the liver (n = 5), as well as for IVIM-DTI in the kidneys (n = 5) and lower-leg muscles (n = 6) of healthy volunteers. The median and interquartile range (IQR) values of the IVIM and IVIM-DTI parameters were compared to assess bias and precision. With model-based reconstruction, the parameter maps exhibited less noise, which was most pronounced in the f and D* maps, both in the simulations and in vivo. The bias values in the simulations were comparable between model-based reconstruction and the reference method. The IQR was lower with model-based reconstruction compared with the reference for all parameters. In conclusion, model-based reconstruction is feasible for IVIM and IVIM-DTI and improves the precision of the parameter estimates, particularly for f and D* maps.

Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review

Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.

Along-Tract Statistical Mapping of Microstructural Abnormalities in Bipolar Disorder: A Pilot Study

Investigating brain circuitry involved in bipolar disorder (BD) is key to discovering brain biomarkers for genetic and interventional studies of the disorder. Even so, prior research has not provided a fine-scale spatial mapping of brain microstructural differences in BD. In this pilot diffusion MRI dataset, we used BUndle ANalytics (BUAN), a recently developed analytic approach for tractography, to extract, map, and visualize the profile of microstructural abnormalities on a 3D model of fiber tracts in people with BD (N=38) and healthy controls (N=49), and investigate along-tract white matter (WM) microstructural differences between these groups. Using the BUAN pipeline, BD was associated with lower mean Fractional Anisotropy (FA) in fronto-limbic and interhemispheric pathways and higher mean FA in posterior bundles relative to controls. BUAN combines tractography and anatomical information to capture distinct along-tract effects on WM microstructure that may aid in classifying diseases based on anatomical differences.

Tractography-Enhanced Biopsy of Central Core Motor Eloquent Tumours: A Simulation-Based Study

Safe Trajectory planning for navigation guided biopsy (nBx) of motor eloquent tumours (METs) is important to minimise neurological morbidity. Preliminary clinical data suggest that visualisation of the corticospinal tract (CST) and its relation to the tumour may aid in planning a safe trajectory. In this article we assess the impact of tractography in nBx planning in a simulation-based exercise. This single centre cross-sectional study was performed in March 2021 including 10 patients with METs divided into 2 groups: (1) tractography enhanced group (T-nBx; n = 5; CST merged with volumetric MRI); (2) anatomy-based group (A-nBx; n = 5; volumetric MRI only). A biopsy target was chosen on each tumour. Volunteer neurosurgical trainees had to plan a suitable biopsy trajectory on a Stealth S8® workstation for all patients in a single session. A trajectory safety index (TSI) was devised for each trajectory. Data collection and analysis included a comparison of trajectory planning time, trajectory/lobe changes and TSI. A total of 190 trajectories were analysed based on participation from 19 trainees. Mean trajectory planning time for the entire cohort was 225.1 ± 21.97 s. T-nBx required shorter time for planning (p = 0.01). Mean trajectory changes and lobe changes made per biopsy were 3.28 ± 0.29 and 0.45 ± 0.08, respectively. T-nBx required fewer trajectory/lobe changes (p = 0.01). TSI was better in the presence of tractography than A-nBx (p = 0.04). Neurosurgical experience of trainees had no significant impact on the measured parameters despite adjusted analysis. Irrespective of the level of neurosurgical training, surgical planning of navigation guided biopsy for METs may be achieved in less time with a safer trajectory if tractography imaging is available.