Diffusion Metrics Research Articles

Deep learning with diffusion MRI as in vivo microscope reveals sex-related differences in human white matter microstructure

Biological sex is a crucial variable in neuroscience studies where sex differences have been documented across cognitive functions and neuropsychiatric disorders. While gross statistical differences have been previously documented in macroscopic brain structure such as cortical thickness or region size, less is understood about sex-related cellular-level microstructural differences which could provide insight into brain health and disease. Studying these microstructural differences between men and women paves the way for understanding brain disorders and diseases that manifest differently in different sexes. Diffusion MRI is an important in vivo, non-invasive methodology that provides a window into brain tissue microstructure. Our study develops multiple end-to-end classification models that accurately estimates the sex of a subject using volumetric diffusion MRI data and uses these models to identify white matter regions that differ the most between men and women. 471 male and 560 female healthy subjects (age range, 22–37 years) from the Human Connectome Project are included. Fractional anisotropy, mean diffusivity and mean kurtosis are used to capture brain tissue microstructure characteristics. Diffusion parametric maps are registered to a standard template to reduce bias that can arise from macroscopic anatomical differences like brain size and contour. This study employ three major model architectures: 2D convolutional neural networks, 3D convolutional neural networks and Vision Transformer (with self-supervised pretraining). Our results show that all 3 models achieve high sex classification performance (test AUC 0.92–0.98) across all diffusion metrics indicating definitive differences in white matter tissue microstructure between males and females. We further use complementary model architectures to inform about the pattern of detected microstructural differences and the influence of short-range versus long-range interactions. Occlusion analysis together with Wilcoxon signed-rank test is used to determine which white matter regions contribute most to sex classification. The results indicate that sex-related differences manifest in both local features as well as global features / longer-distance interactions of tissue microstructure. Our highly consistent findings across models provides new insight supporting differences between male and female brain cellular-level tissue organization particularly in the central white matter.

Identification of diffusion, kurtosis, and propagator MRI markers of Alzheimer’s disease pathology in post-mortem human tissue

Abstract Alzheimer’s disease (AD) is an irreversible degenerative brain disease affecting 6.7 million Americans and while the hallmark AD pathologies of plaques and tangles follow a stereotyped progression during the course of the disease, clinical markers for early diagnosis are lacking and approximately 20% of all AD cases are ultimately misdiagnosed. Conventional clinical MRI is capable of reporting severe brain atrophy, but fails to recognize earlier biomarkers associated with more subtle cellular and molecular changes. Microstructural Magnetic Resonance Imaging (MRI) techniques are promising to address this challenge and may sensitively detect and distinguish tissue degeneration, tauopathies, and beta amyloid plaques to improve accuracy of diagnosis and enable early detection. The objective of this study was to identify and compare the most promising microstructural markers of AD pathology over a range of diffusion and relaxometry-based MRI techniques from conventional to advanced. To accomplish this, we performed MRI microscopy of post-mortem human temporal lobe specimens (n = 14) at high resolution and image quality and evaluated the relative influence of metrics across multiple microstructural MRI frameworks using principal component analysis (PCA). We performed additional correlation analysis between metrics identified by PCA and clinical neuropathology scores of Braak stage and plaque and tangle load. Hippocampal diffusion and restriction metrics contributed most to the first principal component, and the correlation with Braak score was positive for diffusivity and negative for restriction metrics. Additionally, the MAP-MRI propagator anisotropy (PA) metric of microscale anisotropy was strongly and negatively correlated with AD pathology while the conventional fractional anisotropy (FA) metric showed little or no correspondence and there was not a strong association between FA and PA by PCA. Entorhinal cortex findings were minimal except for reported increases in restriction due to plaque content. Taken together, our findings suggest that microstructural MRI metrics of restriction and diffusion are most prominent and may reflect degenerative processes in AD brain tissue and that microscale anisotropy may be more advantageous than conventional FA for the detection of subtle and earlier cellular changes in AD.

Diffusion magnetic resonance imaging of cerebrospinal fluid dynamics: Current techniques and future advancements.

Cerebrospinal fluid (CSF) plays a critical role in metabolic waste clearance from the brain, requiring its circulation throughout various brain pathways, including the ventricular system, subarachnoid spaces, para-arterial spaces, interstitial spaces, and para-venous spaces. The complexity of CSF circulation has posed a challenge in obtaining noninvasive measurements of CSF dynamics. The assessment of CSF dynamics throughout its various circulatory pathways is possible using diffusion magnetic resonance imaging (MRI) with optimized sensitivity to incoherent water movement across the brain. This review presents an overview of both established and emerging diffusion MRI techniques designed to measure CSF dynamics and their potential clinical applications. The discussion offers insights into the optimization of diffusion MRI acquisition parameters to enhance the sensitivity and specificity of diffusion metrics on underlying CSF dynamics. Lastly, we emphasize the importance of cautious interpretations of diffusion-based imaging, especially when differentiating between tissue- and fluid-related changes or elucidating structural versus functional alterations.

Spatial profiling of in vivo diffusion-weighted MRI parameters in the healthy human kidney.

Diffusion-weighted MRI is a technique that can infer microstructural and microcirculatory features from biological tissue, with particular application to renal tissue. There is extensive literature on diffusion tensor imaging (DTI) of anisotropy in the renal medulla, intravoxel incoherent motion (IVIM) measurements separating microstructural from microcirculation effects, and combinations of the two. However, interpretation of these features and adaptation of more specific models remains an ongoing challenge. One input to this process is a whole organ distillation of corticomedullary contrast of diffusion metrics, as has been explored for other renal biomarkers. In this work, we probe the spatial dependence of diffusion MRI metrics with concentrically layered segmentation in 11 healthy kidneys at 3 T. The metrics include those from DTI, IVIM, a combined approach titled "REnal Flow and Microstructure AnisotroPy (REFMAP)", and a multiply encoded model titled "FC-IVIM" providing estimates of fluid velocity and branching length. Fractional anisotropy decreased from the inner kidney to the outer kidney with the strongest layer correlation in both parenchyma (including cortex and medulla) and medulla with Spearman correlation coefficients and p-values (r, p) of (0.42, <0.001) and (0.37, <0.001), respectively. Also, dynamic parameters derived from the three models significantly decreased with a high correlation from the inner to the outer parenchyma or medulla with (r, p) ranges of (0.46-0.55, <0.001). These spatial trends might find implications for indirect assessments of kidney physiology and microstructure using diffusion MRI.

Widespread White Matter Abnormalities in Concussed Athletes Detected by 7T Diffusion Magnetic Resonance Imaging.

Sports-related concussions may cause white matter injuries and persistent post-concussive symptoms (PPCS). We hypothesized that athletes with PPCS would have neurocognitive impairments and white matter abnormalities that could be revealed by advanced neuroimaging using ultra-high field strength diffusion tensor (DTI) and diffusion kurtosis (DKI) imaging metrics and cerebrospinal fluid (CSF) biomarkers. A cohort of athletes with PPCS severity limiting the ability to work/study and participate in sport school and/or social activities for ≥6 months completed 7T magnetic resonance imaging (MRI) (morphological T1-weighed volumetry, DTI and DKI), extensive neuropsychological testing, symptom rating, and CSF biomarker sampling. Twenty-two athletes with PPCS and 22 controls were included. Concussed athletes performed below norms and significantly lower than controls on all but one of the psychometric neuropsychology tests. Supratentorial white and gray matter, as well as hippocampal volumes did not differ between concussed athletes and controls. However, of the 72 examined white matter tracts, 16% of DTI and 35% of DKI metrics (in total 28%) were significantly different between concussed athletes and controls. DKI fractional anisotropy and axial kurtosis were increased, and DKI radial diffusivity and radial kurtosis decreased in concussed athletes when compared with controls. CSF neurofilament light (NfL; an axonal injury marker), although not glial fibrillary acidic protein, correlated with several diffusion metrics. In this first 7T DTI and DKI study investigating PPCS, widespread microstructural alterations were observed in the white matter, correlating with CSF markers of axonal injury. More white matter changes were observed using DKI than using DTI. These white matter alterations may indicate persistent pathophysiological processes following concussion in sport.

Advanced diffusion MRI provides evidence for altered axonal microstructure and gradual peritumoral infiltration in GBM in comparison to brain metastases

PurposeIn contrast to peritumoral edema in metastases, GBM is histopathologically characterized by infiltrating tumor cells within the T2 signal alterations. We hypothesized that depending on the distance from the outline of the contrast-enhancing tumor we might reveal imaging evidence of gradual peritumoral infiltration in GBM and predominantly vasogenic edema around metastases. We thus investigated the gradual change of advanced diffusion metrics with the peritumoral zone in metastases and GBM.MethodsIn 30 patients with GBM and 28 with brain metastases, peritumoral T2 hyperintensity was segmented in 33% partitions based on the total volume beginning at the enhancing tumor margin and divided into inner, middle and outer zones. Diffusion Tensor Imaging (DTI)-derived fractional anisotropy and mean diffusivity as well as Diffusion Microstructure Imaging (DMI)-based parameters Dax-intra, Dax-extra, V‑CSF and V-intra were employed to assess group-wise differences between inner and outer zones as well as within-group gradients between the inner and outer zones.ResultsIn metastases, fractional anisotropy and Dax-extra were significantly reduced in the inner zone compared to the outer zone (FA p = 0.01; Dax-extra p = 0.03). In GBM, we noted a reduced Dax-extra and significantly lower intraaxonal volume fraction (Dax-extra p = 0.008, V‑intra p = 0.006) accompanied by elevated axial intraaxonal diffusivity in the inner zone (p = 0.035). Between-group comparison of the outer to the inner zones revealed significantly higher gradients in metastases over GBM for FA (p = 0.04) as well as the axial diffusivity in the intra- (p = 0.02) and extraaxonal compartment (p < 0.001).ConclusionOur findings provide evidence of gradual alterations within the peritumoral zone of brain tumors. These are compatible with predominant (vasogenic) edema formation in metastases, whereas our findings in GBM are in line with an axonal destructive component in the immediate peritumoral area and evidence of tumor cell infiltration with accentuation in the tumor’s vicinity.

Assessment of white matter microstructure integrity in subacute postconcussive vestibular dysfunction using NODDI

Abstract Vestibular symptoms, such as dizziness and balance impairment, are frequently reported following mild traumatic brain injury (mTBI) and are associated with a protracted recovery, yet the underlying neuroanatomical substrates remain unclear. The present study utilized advanced diffusion MRI (dMRI) techniques including both conventional diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) to investigate microstructural white matter integrity in individuals with postconcussive vestibular dysfunction (PCVD) within the subacute injury period (median of 35 days from injury; IQR of 23). Study participants included 23 individuals with subacute PCVD and 37 healthy control subjects who underwent imaging and comprehensive clinical vestibular testing. Between-group voxelwise analysis of differences in white matter revealed areas of higher intra-neurite volume fraction (VIn) and isotropic volume fraction (VIso) within PCVD subjects compared to controls, which involved overlapping regions within the left hemisphere of the brain. Affected areas of higher VIn and VIso included the superior longitudinal fasciculus (SLF) and superior and posterior corona radiata (SCR and PCR, respectively). We examined the relationship between clinical vestibular measures and diffusion metrics including DTI (fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD] and axial diffusivity [AD]) and NODDI (intraneurite volume fraction [VIn], isotropic volume fraction [VIso], dispersion anisotropy [DA], orientation dispersion indexTotal/Primary/Secondary [ODIT/P/S]) within 32 regions-of-interest. Clinical vestibular measures included self-reported measures, including the Dizziness Handicap Inventory, Visual Vertigo Analog Scale, and Vestibular/Ocular-Motor Screening, as well as objective vestibular testing using the sensory organization test. Significant correlations were found with clinical measures across all diffusion maps (except DA), within various regions of interest (ROIs), including SLF, SCR, and PCR. These results implicate several important association bundles that may potentiate sensory processing dysfunction related to PCVD. Whether these neuroanatomical differences found within the subacute phase of PCVD are in response to injury or represent preexisting structural variations that increase vulnerability to sensory processing dysfunction is unclear and remains an active area of study.

Neurite orientation dispersion and density imaging reveals abnormal white matter and glymphatic function in active young boxers.

The neurological effects and underlying pathophysiological mechanisms of sports-related concussion (SRC) in active young boxers remain poorly understood. This study aims to investigate the impairment of white matter microstructure and assess changes in glymphatic function following SRC by utilizing neurite orientation dispersion and density imaging (NODDI) on young boxers who have sustained SRC. A total of 60 young participants were recruited, including 30 boxers diagnosed with SRC and 30 healthy individuals engaging in regular exercise. The assessment of whole-brain white matter damage was conducted using diffusion metrics, while the evaluation of glymphatic function was performed through diffusion tensor imaging (DTI) analysis along the perivascular space (DTI-ALPS) index. A two-sample t-test was utilized to examine group differences in DTI and NODDI metrics. Spearman correlation and generalized linear mixed models were employed to investigate the relationship between clinical assessments of SRC and NODDI measurements. Significant alterations were observed in DTI and NODDI metrics among young boxers with SRC. Additionally, the DTI-ALPS index in the SRC group exhibited a significantly higher value than that of the control group (left side: 1.58 vs. 1.48, PFDR=0.009; right side: 1.61 vs. 1.51, PFDR=0.02). Moreover, it was observed that the DTI-ALPS index correlated with poorer cognitive test results among boxers in this study population. Repetitive SRC in active young boxers is associated with diffuse white matter injury and glymphatic dysfunction, highlighting the detrimental impact on brain health. These findings highlight the importance of long-term monitoring of the neurological health of boxers.

A novel indicator to predict the outcome of percutaneous stereotactic radiofrequency rhizotomy for trigeminal neuralgia patients: diffusivity metrics of MR-DTI

AbstractMagnetic resonance-diffusion tensor imaging (MR-DTI) has been used in the microvascular decompression and gamma knife radiosurgery in trigeminal neuralgia (TN) patients; however, use of percutaneous stereotactic radiofrequency rhizotomy (PSR) to target an abnormal trigeminal ganglion (ab-TG) is unreported. Fractional anisotropy (FA), mean and radial diffusivity (MD and RD, respectively), and axial diffusivity (AD) of the trigeminal nerve (CNV) were measured in 20 TN patients and 40 healthy control participants immediately post PSR, at 6-months, and at 1 year. Longitudinal alteration of the diffusivity metrics and any correlation with treatment effects, or prognoses, were analyzed. In the TN group, either low FA (value &lt; 0.30) or a decreased range compared to the adjacent FA (dFA) &gt; 17% defined an ab-TG. Two-to-three days post PSR, all 15 patients reported decreased pain scores with increased FA at the ab-TG (P &lt; 0.001), but decreased MD and RD (P &lt; 0.01 each). Treatment remained effective in 10 of 14 patients (71.4%) and 8 of 12 patients (66.7%) at the 6-month and 1-year follow-ups, respectively. In patients with ab-TGs, there was a significant difference in treatment outcomes between patients with low FA values (9 of 10; 90%) and patients with dFA (2 of 5; 40%) (P &lt; 0.05). MR-DTI with diffusivity metrics correlated microstructural CNV abnormalities with PSR outcomes. Of all the diffusivity metrics, FA could be considered a novel objective quantitative indicator of treatment effects and a potential indicator of PSR effectiveness in TN patients.

Glymphatic System Dysfunction Underlying Schizophrenia Is Associated With Cognitive Impairment.

Despite the well-documented structural and functional brain changes in schizophrenia, the potential role of glymphatic dysfunction remains largely unexplored. This study investigates the glymphatic system's function in schizophrenia, utilizing diffusion tensor imaging (DTI) to analyze water diffusion along the perivascular space (ALPS), and examines its correlation with clinical symptoms. A cohort consisting of 43 people with schizophrenia and 108 healthy controls was examined. We quantified water diffusion metrics along the x-, y-, and z-axis in both projection and association fibers to derive the DTI-ALPS index, a proxy for glymphatic activity. The differences in the ALPS index between groups were analyzed using a 2-way ANCOVA controlling for age and sex, while partial correlations assessed the association between the ALPS index and clinical variables. People with schizophrenia showed a significantly reduced DTI-ALPS index across the whole brain and within both hemispheres (F = 9.001, P = .011; F = 10.024, P = .011; F = 5.927, P = .044; false discovery rate corrected), indicating potential glymphatic dysfunction in schizophrenia. The group by cognitive performance interaction effects on the ALPS index were not observed. Moreover, a lower ALPS index was associated with poorer cognitive performance on specific neuropsychological tests in people with schizophrenia. Our study highlights a lower ALPS index in schizophrenia, correlated with more pronounced cognitive impairments. This suggests that glymphatic dysfunction may contribute to the pathophysiology of schizophrenia, offering new insights into its underlying mechanisms.

Discovering Trends in the Digitalization of Shipping: An Exploratory Study into Trends Using Natural Language Processing

This study investigates digitalization in the shipping industry by analyzing over 500 industry presentations from an eight-year span to discern key trends and nascent signals. Employing optical character recognition, advanced natural language processing techniques, and similarity metrics, the research enhances topic interpretability. Through Theil–Sen regressions and diffusion metrics, it identifies trends and emerging signals, noting a rise in interest in smart ports and supply chain management, signaling a shift toward more intelligent technology integration. However, attention to supply chain management shows a decline. The research tracks a shift from broad technology themes to specific areas like cybersecurity and blockchain, reflecting a narrative pivot to tackle particular digital challenges and opportunities. The study detects weak signals, including terms like “subsea” and “drone”, suggesting forthcoming industry innovations and shifts, notably toward ESG considerations. An additional machine learning analysis corroborates findings on key topics like energy efficiency and crew welfare, also spotlighting virtual disaster recovery and ERP projects as emerging areas of interest. This work aids in comprehending the fluid digitalization landscape in shipping, highlighting the sector’s ongoing evolution, and underscoring the need for further inquiry into autonomous shipping and related domains.

Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions.

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions, this IRB-approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. A General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) was employed to acquire two DTI (diffusion tensor imaging) sequences of the left knee on each child at 3T: an in-plane 2.0 × 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel; neither had an intersection gap. For image acquisition, a multi-band DTI with a fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 s/mm2) was utilized. The MR vendor-provided a commercially available DL model which was applied with 75% noise reduction settings to the same subject DTI sequences at different spatial resolutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for the femur and tibia at each spatial resolution. Differences were evaluated using Wilcoxon-signed ranked test and Bland-Altman plots. When comparing DL versus non-denoised diffusion metrics in femur and tibia using the 2 mm × 2 mm × 3 mm voxel dimension, there were no significant differences between tract count (p = 0.1, p = 0.14) tract volume (p = 0.1, p = 0.29) or tibial tract length (p = 0.16); femur tract length exhibited a significant difference (p < 0.01). All diffusion metrics (tract count, volume, length, and fractional anisotropy (FA)) derived from the DL-reconstructed scans, were significantly different from the non-denoised scan DTI metrics in both the femur and tibial physes using the 2 mm3 voxel size (p < 0.001). DL reconstruction resulted in a significant decrease in femorotibial FA for both voxel dimensions (p < 0.01). Leveraging denoising algorithms could address the drawbacks of lower signal-to-noise ratios (SNRs) associated with smaller voxel volumes and capitalize on their better spatial resolutions, allowing for more accurate quantification of diffusion metrics.

416 MRI Findings in Preterm Infants Associated with Strabismus

OBJECTIVES/GOALS: Prematurity and perinatal brain injury are known risk factors for strabismus. In this study, we sought to understand the link between neonatal neuroimaging measures in very preterm infants and the emergence of strabismus later in life. Study findings may inform if neonatal brain MRI could serve as a prognostic tool for this visual disorder. METHODS/STUDY POPULATION: This study draws from a longitudinal cohort of very preterm infants (VPT, &lt; 30 weeks gestation, range 23 – 29 weeks) who underwent an MRI scan at 36 to 43 weeks postmenstrual age (PMA). Anatomic and diffusion MRI data were collected for each child . A subset of thirty-three patients in this cohort had records of an eye exam, which were reviewed for a history of strabismus. Patients with MRI scans demonstrating cystic periventricular leukomalacia or grade III/IV intraventricular hemorrhage were classified as having brain injury. Clinical variables with a known association to strabismus or diffusion metrics were included in a multivariable logistic regression model. Diffusion tractography metrics were screened for association with strabismus on univariable analysis prior to inclusion in the regression model. RESULTS/ANTICIPATED RESULTS: A total of 17/33 (51.5%) patients developed strabismus. A logistic regression model including gestational age, PMA at MRI, retinopathy of prematurity (ROP) stage, brain injury, and fractional anisotropy of the right optic radiation was significant at the .001 level according to the chi-square statistic. The model predicted 88% of responses correctly. Each decrease of 0.01 in the fractional anisotropy of the right optic radiation increased the odds of strabismus by a factor of 1.5 (95% CI 1.03 – 2.06; p = .03). Patients with brain injury had 15.8 times higher odds of strabismus (95% CI 1.1 – 216.5; p = .04). Gestational age (OR 1.7; 95% CI 0.9 – 3.3; p = .1) and stage of ROP (OR 0.6; 95% CI 0.2 – 2.0; p = .4) were not significant predictors of strabismus in the multivariable model. DISCUSSION/SIGNIFICANCE: Our findings suggest that strabismus in VPT patients may be related to specific changes in brain structure in the neonatal period. The identified association between neonatal optic radiation microstructure and strabismus supports the possibility of using brain MRI in very preterm infants to prognosticate visual and ocular morbidity.

Nonlinear Gradient Field Estimation in Diffusion MRI Tensor Simulation.

Gradient nonlinearities not only induce spatial distortion in magnetic resonance imaging (MRI), but also introduce discrepancies between intended and acquired diffusion sensitization in diffusion weighted (DW) MRI. Advances in scanner performance have increased the importance of correcting gradient nonlinearities. The most common approaches for gradient nonlinear field estimations rely on phantom calibration field maps which are not always feasible, especially on retrospective data. Here, we derive a quadratic minimization problem for the complete gradient nonlinear field (L(r)). This approach starts with corrupt diffusion signal and estimates the L(r) in two scenarios: (1) the true diffusion tensor known and (2) the true diffusion tensor unknown (i.e., diffusion tensor is estimated). We show the validity of this mathematical approach, both theoretically and through tensor simulation. The estimated field is assessed through diffusion tensor metrics: mean diffusivity (MD), fractional anisotropy (FA), and principal eigenvector (V1). In simulation with 300 diffusion tensors, the study shows the mathematical model is not ill-posed and remains stable. We find when the true diffusion tensor is known (1) the change in determinant of the estimated L(r) field and the true field is near zero and (2) the median difference in estimated L(r) corrected diffusion metrics to true values is near zero. We find the results of L(r) estimation are dependent on the level of L(r) corruption. This work provides an approach to estimate gradient field without the need for additional calibration scans. To the best of our knowledge, the mathematical derivation presented here is novel.

Neuroimaging Findings in US Government Personnel and Their Family Members Involved in Anomalous Health Incidents

US government personnel stationed internationally have reported anomalous health incidents (AHIs), with some individuals experiencing persistent debilitating symptoms. To assess the potential presence of magnetic resonance imaging (MRI)-detectable brain lesions in participants with AHIs, with respect to a well-matched control group. This exploratory study was conducted at the National Institutes of Health (NIH) Clinical Center and the NIH MRI Research Facility between June 2018 and November 2022. Eighty-one participants with AHIs and 48 age- and sex-matched control participants, 29 of whom had similar employment as the AHI group, were assessed with clinical, volumetric, and functional MRI. A high-quality diffusion MRI scan and a second volumetric scan were also acquired during a different session. The structural MRI acquisition protocol was optimized to achieve high reproducibility. Forty-nine participants with AHIs had at least 1 additional imaging session approximately 6 to 12 months from the first visit. AHIs. Group-level quantitative metrics obtained from multiple modalities: (1) volumetric measurement, voxel-wise and region of interest (ROI)-wise; (2) diffusion MRI-derived metrics, voxel-wise and ROI-wise; and (3) ROI-wise within-network resting-state functional connectivity using functional MRI. Exploratory data analyses used both standard, nonparametric tests and bayesian multilevel modeling. Among the 81 participants with AHIs, the mean (SD) age was 42 (9) years and 49% were female; among the 48 control participants, the mean (SD) age was 43 (11) years and 42% were female. Imaging scans were performed as early as 14 days after experiencing AHIs with a median delay period of 80 (IQR, 36-544) days. After adjustment for multiple comparisons, no significant differences between participants with AHIs and control participants were found for any MRI modality. At an unadjusted threshold (P < .05), compared with control participants, participants with AHIs had lower intranetwork connectivity in the salience networks, a larger corpus callosum, and diffusion MRI differences in the corpus callosum, superior longitudinal fasciculus, cingulum, inferior cerebellar peduncle, and amygdala. The structural MRI measurements were highly reproducible (median coefficient of variation <1% across all global volumetric ROIs and <1.5% for all white matter ROIs for diffusion metrics). Even individuals with large differences from control participants exhibited stable longitudinal results (typically, <±1% across visits), suggesting the absence of evolving lesions. The relationships between the imaging and clinical variables were weak (median Spearman ρ = 0.10). The study did not replicate the results of a previously published investigation of AHIs. In this exploratory neuroimaging study, there were no significant differences in imaging measures of brain structure or function between individuals reporting AHIs and matched control participants after adjustment for multiple comparisons.

Subcortical-cortical white matter connectivity in adults with autism spectrum disorder and schizophrenia patients

Autism spectrum disorder (ASD) and schizophrenia (SZ) are neuropsychiatric disorders that overlap in symptoms associated with social-cognitive impairment. Alterations of the cingulate cortex, subcortical, medial-temporal, and orbitofrontal structures are frequently reported in both disorders. In this study, we examined white-matter connectivity between these structures in adults with ASD and SZ patients compared with their respective neurotypical controls and indirectly with each other, using probabilistic and local DTI tractography. This exploratory study utilized publicly available neuroimaging databases, of adults with ASD (ABIDE II; n = 28) and SZ (COBRE; n = 38), age-gender matched neurotypicals (NT) and associated phenotypic data. Tractography was performed using Freesurfer and MRtrix software, and diffusion metrics of white-matter tracts between cingulate-, orbitofrontal- cortices, subcortical structures, parahippocampal, entorhinal cortex were assessed. In ASD, atypical diffusivity parameters were found in the isthmus cingulate and parahippocampal connectivity to subcortical and rostral-anterior cingulate, which were also associated with IQ and social skills (SRS). In contrast, atypical diffusivity parameters were observed between the medial-orbitofrontal cortex and subcortical structures in SZ, and were associated with executive function (i.e., IQ, processing speed) and emotional regulation. Overall, the results suggest that defects in the isthmus cingulate, medial-orbitofrontal, and striato-limbic white matter connectivity may help unravel the neural underpinnings of executive and social-emotional dysfunction at the core of neuropsychiatric disorders.

Comparison of diffusion MRI methods in the study of structural reorganization of the brain in the early post-stroke period

Current research in the field of neuroimaging is focused on the possibilities of using data from various diffusion MR models: diffusion tensor visualization (DTI), diffusion-curtosis visualization (DKI), diffusion-spectral visualization (DSI), generalized q-sample visualization (GQI), Q-ball visualization (QBI) in the assessment reorganization of the brain. The purpose of this study is to compare the results of dynamic observation of post–stroke brain reorganization by diffusion MR models (DTI, DKI). Material and methods. Dynamic MR examination of the brain of 129 patients was performed on a Ingenia 3.0 T (Philips, Netherlands) on 1–3 days, 7–10 days, 3–4 months after the manifestation of stroke according to a routine protocol (DWI-EPI, FLAIR-SPIR, T2-WI, T1W-TFE) with DTI method. The stroke was verified and DTI, GQI, and DKI maps were built. Results and discussion It was showed that the fractional anisotropy (FA) of DTI significantly changed from 1–3 days to 7–10 days in the stroke area; the mean, axial and radial diffusions increased in the affected area over the three studies. For DKI model – the curtosis FA significantly changed in the lesion area by 3–4 months; the mean curtosis decreased by the second observation in the stroke area, axial curtosis decreased in the same area throughout all studies; radial kurtosis significantly increased in the affected area throughout the study. The results confirm the world data and also indicate that diffusion metrics can interpret the neuroplasticity of the brain in various diseases, however, this requires further study. The applied diffusion models indicated the reorganization of the ischemic area and the intact contralateral area. The use of diffusion models for the dynamic assessment is a promising direction in the study of the neuroplasticity mechanisms.

Purpose in life as a resilience factor for brain health: diffusion MRI findings from the Midlife in the U.S. study.

A greater sense of purpose in life is associated with several health benefits relevant for active aging, but the mechanisms remain unclear. We evaluated if purpose in life was associated with indices of brain health. We examined data from the Midlife in the United States (MIDUS) Neuroscience Project. Diffusion weighted magnetic resonance imaging data (n=138; mean age 65.2 years, age range 48-95; 80 females; 37 black, indigenous, and people of color) were used to estimate microstructural indices of brain health such as axonal density, and axonal orientation. The seven-item purpose in life scale was used. Permutation analysis of linear models was used to examine associations between purpose in life scores and the diffusion metrics in white matter and in the bilateral hippocampus, adjusting for age, sex, education, and race. Greater sense of purpose in life was associated with brain microstructural features consistent with better brain health. Positive associations were found in both white matter and the right hippocampus, where multiple convergent associations were detected. The hippocampus is a brain structure involved in learning and memory that is vulnerable to stress but retains the capacity to grow and adapt through old age. Our findings suggest pathways through which an enhanced sense of purpose in life may contribute to better brain health and promote healthy aging. Since purpose in life is known to decline with age, interventions and policy changes that facilitate a greater sense of purpose may extend and improve the brain health of individuals and thus improve public health.

MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal

Data harmonization is necessary for removing confounding effects in multi-site diffusion image analysis. One such harmonization method, LinearRISH, scales rotationally invariant spherical harmonic (RISH) features from one site (“target”) to the second (“reference”) to reduce confounding scanner effects. However, reference and target site designations are not arbitrary and resultant diffusion metrics (fractional anisotropy, mean diffusivity) are biased by this choice. In this work we propose MidRISH: rather than scaling reference RISH features to target RISH features, we project both sites to a mid-space. We validate MidRISH with the following experiments: harmonizing scanner differences from 37 matched patients free of cognitive impairment, and harmonizing acquisition and study differences on 117 matched patients free of cognitive impairment. We find that MidRISH reduces bias of reference selection while preserving harmonization efficacy of LinearRISH. Users should be cautious when performing LinearRISH harmonization. To select a reference site is to choose diffusion metric effect-size. Our proposed method eliminates the bias-inducing site selection step.

Analysis of white matter tract integrity using diffusion kurtosis imaging reveals the correlation of white matter microstructural abnormalities with cognitive impairment in type 2 diabetes mellitus.

This study aimed to identify disruptions in white matter integrity in type 2 diabetes mellitus (T2DM) patients by utilizing the white matter tract integrity (WMTI) model, which describes compartment-specific diffusivities in the intra- and extra-axonal spaces, and to investigate the relationship between WMTI metrics and clinical and cognitive measurements. A total of 73 patients with T2DM and 57 healthy controls (HCs) matched for age, sex, and education level were enrolled and underwent diffusional kurtosis imaging and cognitive assessments. Tract-based spatial statistics (TBSS) and atlas-based region of interest (ROI) analysis were performed to compare group differences in diffusional metrics, including fractional anisotropy (FA), mean diffusivity (MD), axonal water fraction (AWF), intra-axonal diffusivity (Daxon), axial extra-axonal space diffusivity (De,//), and radial extra-axonal space diffusivity (De,⊥) in multiple white matter (WM) regions. Relationships between diffusional metrics and clinical and cognitive functions were characterized. In the TBSS analysis, the T2DM group exhibited decreased FA and AWF and increased MD, De,∥, and De,⊥ in widespread WM regions in comparison with the HC group, which involved 56.28%, 32.07%, 73.77%, 50.47%, and 75.96% of the mean WM skeleton, respectively (P < 0.05, TFCE-corrected). De,⊥ detected most of the WM changes, which were mainly located in the corpus callosum, internal capsule, external capsule, corona radiata, posterior thalamic radiations, sagittal stratum, cingulum (cingulate gyrus), fornix (stria terminalis), superior longitudinal fasciculus, and uniform fasciculus. Additionally, De,⊥ in the genu of the corpus callosum was significantly correlated with worse performance in TMT-A (β = 0.433, P < 0.001) and a longer disease duration (β = 0.438, P < 0.001). WMTI is more sensitive than diffusion tensor imaging in detecting T2DM-related WM microstructure abnormalities and can provide novel insights into the possible pathological changes underlying WM degeneration in T2DM. De,⊥ could be a potential imaging marker in monitoring disease progression in the brain and early intervention treatment for the cognitive impairment in T2DM.