Intracellular Volume Fraction Research Articles

Modelling pathological spread through the structural connectome in the frontotemporal dementia clinical spectrum.

The ability to predict the pathology spreading in patients with frontotemporal dementia (FTD) is crucial for early diagnosis and targeted interventions. This study examined the relationship between network vulnerability and longitudinal atrophy progression in FTD patients, using Network Diffusion Model (NDM) of pathology spread. Thirty behavioural-variant FTD (bvFTD), 13 semantic-variant primary progressive aphasia (svPPA), 14 nonfluent-variant PPA (nfvPPA) and 12 semantic behavioral variant FTD (sbvFTD) patients underwent longitudinal T1-weighted MRI. Fifty young controls (YC) (20-31 years) underwent multi-shell diffusion MRI scan. NDM was developed to model FTD pathology progression as a spreading process from a seed through the healthy structural connectome, using connectivity measures from fractional anisotropy (FA) and intra-cellular volume fraction (ICVF) in YC. Four disease epicenters were initially identified from the peaks of atrophy of each FTD variant: left insula (bvFTD), left temporal pole (svPPA), right temporal pole (sbvFTD) and left supplementary motor area (nfvPPA). Pearson's correlations were calculated between NDM-predicted atrophy in YC and the observed longitudinal atrophy in FTD patients over a follow-up of 24 months. The NDM was then run for all the 220 brain seeds to verify whether the four epicenters were among those that yielded the highest correlation. Using NDM, predictive maps in YC showed pathology progression from the peaks of atrophy in svPPA, nfvPPA, and sbvFTD over 24-months. svPPA exhibited early involvement of left temporal and occipital lobes, progressing to extensive left hemisphere impairment. nfvPPA and sbvFTD similarly spread bilaterally to frontal, sensorimotor, and temporal regions, with sbvFTD additionally affecting the right hemisphere. Moreover, the NDM-predicted atrophy of each region was positively correlated to longitudinal real atrophy, with a greater effect in svPPA and sbvFTD. In bvFTD, the model starting from the left insula (the peak of atrophy) demonstrated a highly left-lateralized pattern, with pathology spreading to frontal, sensorimotor, temporal, and basal ganglia regions, with minimal extension to the contralateral hemisphere by 24 months. However, unlike the atrophy peaks observed in the other three phenotypes, the left insula did not show the strongest correlation between the estimated and actual atrophy. Instead, the bilateral superior frontal gyrus emerged as optimal seeds for modelling atrophy spread, showing the highest correlation ranking in both hemispheres. Overall, NDM applied on ICVF connectome yielded higher correlations relative to NDM applied on FA maps. The NDM implementation using cross-sectional structural connectome is a valuable tool to predict atrophy patterns and pathology spreading in FTD clinical variants.

Causal relationships between cortical brain structural alterations and migraine subtypes: a bidirectional Mendelian randomization study of 2,347 neuroimaging phenotypes

BackgroundPrevious studies have shown that migraines are associated with brain structural changes. However, the causal relationships between these changes and migraine, as well as its subtypes, migraine with aura (MA) and migraine without aura (MO), remain largely unclear.MethodsWe utilized genome-wide association study (GWAS) summary statistics from European cohorts for 2,347 cortical structural magnetic resonance imaging (MRI) phenotypes, derived from both T1-weighted and diffusion tensor imaging scans (n = 36,663), with migraine and its subtypes (n = 147,970–375,752). Cortical phenotypes included both macrostructural (e.g., cortical thickness, surface area) and microstructural (e.g., fractional anisotropy, mean diffusivity) features. Genetic correlations were first assessed to identify significant associations, followed by bidirectional Mendelian randomization (MR) analyses to determine causal relationships between these brain phenotypes and migraine, as well as its subtypes (MA and MO). Sensitivity analyses were applied to ensure the robustness of the results.ResultsGenetic correlation analysis identified 510 significant associations between cortical structural phenotypes and migraine across 401 distinct traits. Forward MR analysis revealed nine significant causal effects of cortical structural changes on migraine risk. Specifically, increased cortical thickness and local gyrification index in specific cortical regions were associated with a decreased risk of overall migraine, MA, and MO, while intracellular volume fraction and orientation diffusion index in specific regions increased the risk of MA and MO. Reverse MR analysis demonstrated that MA causally increased mean diffusivity in the insular and frontal opercular cortex. Sensitivity analyses confirmed the robustness of these findings, with no evidence of horizontal pleiotropy or heterogeneity.ConclusionThis study identifies causal relationships between cortical neuroimaging phenotypes and migraine, highlighting potential biomarkers for migraine diagnosis, treatment, and prevention.

Association of concussion history with psychiatric symptoms, limbic system structure, and kynurenine pathway metabolites in healthy, collegiate-aged athletes

Psychiatric outcomes are commonly observed in individuals with repeated concussions, though their underlying mechanism is unknown. One potential mechanism linking concussion with psychiatric symptoms is inflammation-induced activation of the kynurenine pathway, which is thought to play a role in the pathogenesis of mood disorders. Here, we investigated the association of prior concussion with multiple psychiatric-related outcomes in otherwise healthy male and female collegiate-aged athletes (N = 212) with varying histories of concussion recruited from the community. Specially, we tested the hypotheses that concussion history is associated with worse psychiatric symptoms, limbic system structural abnormalities (hippocampal volume, white matter microstructure assessed using neurite orientation dispersion and density imaging; NODDI), and elevations in kynurenine pathway (KP) metabolites (e.g., Quinolinic acid; QuinA). Given known sex-effects on concussion risk and recovery, psychiatric outcomes, and the kynurenine pathway, the moderating effect of sex was considered for all analyses. More concussions were associated with greater depression, anxiety, and anhedonia symptoms in female athletes (ps ≤ 0.005) and greater depression symptoms in male athletes (p = 0.011). More concussions were associated with smaller bilateral hippocampal tail (ps < 0.010) and left hippocampal body (p < 0.001) volumes across male and female athletes. Prior concussion was also associated with elevations in the orientation dispersion index (ODI) and lower intracellular volume fraction in several white matter tracts including the in uncinate fasciculus, cingulum-gyrus, and forceps major and minor, with evidence of female-specific associations in select regions. Regarding serum KP metabolites, more concussions were associated with elevated QuinA in females and lower tryptophan in males (ps ≤ 0.010). Finally, serum levels of QuinA were associated with elevated ODI (male and female athletes) and worse anxiety symptoms (females only), while higher ODI in female athletes and smaller hippocampal volumes in male athletes were associated with more severe anxiety and depression symptoms (ps ≤ 0.05). These data suggest that cumulative concussion is associated with psychiatric symptoms and limbic system structure in healthy athletes, with increased susceptibility to these effects in female athletes. Moreover, the associations of outcomes with serum KP metabolites highlight the KP as one potential molecular pathway underlying these observations.

Application of preoperative advanced diffusion magnetic resonance imaging in evaluating the postoperative recurrence of lower grade gliomas

BackgroundRecurrence of lower grade glioma (LrGG) appeared to be unavoidable despite considerable research performed in last decades. Thus, we evaluated the postoperative recurrence within two years after the surgery in patients with LrGG by preoperative advanced diffusion magnetic resonance imaging (dMRI).Materials and methods48 patients with lower-grade gliomas (23 recurrence, 25 nonrecurrence) were recruited into this study. Different models of dMRI were reconstructed, including apparent fiber density (AFD), white matter tract integrity (WMTI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), Bingham NODDI and standard model imaging (SMI). Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) was used to construct a multiparametric prediction model for the diagnosis of postoperative recurrence.ResultsThe parameters derived from each dMRI model, including AFD, axon water fraction (AWF), mean diffusivity (MD), mean kurtosis (MK), fractional anisotropy (FA), intracellular volume fraction (ICVF), extra-axonal perpendicular diffusivity (De⊥), extra-axonal parallel diffusivity (De∥) and free water fraction (fw), showed significant differences between nonrecurrence group and recurrence group. The extra-axonal perpendicular diffusivity (De⊥) had the highest area under curve (AUC = 0.885), which was significantly higher than others. The variable importance for the projection (VIP) value of De⊥ was also the highest. The AUC value of the multiparametric prediction model merging AFD, WMTI, DTI, DKI, NODDI, Bingham NODDI and SMI was up to 0.96.ConclusionPreoperative advanced dMRI showed great efficacy in evaluating postoperative recurrence of LrGG and De⊥ of SMI might be a valuable marker.

Detecting Cellular Microstructural Changes of Liver Fibrosis with Time-Dependent Diffusion MRI.

Background The potential of time-dependent diffusion MRI in imaging the progression from liver fibrosis to cirrhosis has not been established. Purpose To assess the effectiveness of time-dependent diffusion MRI in mapping the microstructure and characterizing cellular attributes during the progression of liver fibrosis to cirrhosis and to investigate its potential in grading liver fibrosis. Materials and Methods This prospective study, performed between December 2022 and October 2023, used 60 rats to establish a liver fibrosis model by means of diethylnitrosamine administration, with five additional rats serving as control animals. Time-dependent diffusion MRI was performed with equivalent diffusion time of 5.4, 10.7, and 69.3 msec on a 3.0-T scanner. Time-dependent diffusion MRI-based microstructural parameters, including cell diameter, intracellular volume fraction (ICVF), cellularity, and extracellular diffusivity, were estimated with use of the imaging microstructural parameters using limited spectrally edited diffusion, or IMPULSED, model. The fitted microstructural parameters were validated with histopathologic measurements. Results All 60 rats developed liver fibrosis, with a noticeable decrease in cell diameter and an increase in ICVF and cellularity observed as liver fibrosis progressed. The diameter measured at pathologic examination ranged from 11.4 μm to 35.4 μm, aligning with the range of 12.4-33.4 μm observed in time-dependent diffusion MRI, which indicated a strong correlation (r = 0.84; P < .001). The quantified ICVF at pathologic examination ranged from 0.28 to 0.89 and varied from 0.23 to 0.85 at time-dependent diffusion MRI, showing a high correlation (r = 0.62; P < .001). The cellularity observed at pathologic examination increased from 0.74 to 5.85, while the cellularity measured at time-dependent diffusion MRI ranged from 0.77 to 3.70, showing a correlation (r = 0.44; P < .001). Conclusion This study revealed the changes in quantitative microstructural mapping across the spectrum from liver fibrosis to cirrhosis. Cell diameter, ICVF, and cellularity are reliable markers for liver fibrosis, with diameter and ICVF presenting good discrimination ability. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Matos and Metens in this issue.

Brain imaging traits and epilepsy: Unraveling causal links via mendelian randomization.

Epilepsy, a complex neurological disorder, is closely linked with structural and functional irregularities in the brain. However, the causal relationship between brain imaging-derived phenotypes (IDPs) and epilepsy remains unclear. This study aimed to investigate this relationship by employing a two-sample bidirectional Mendelian randomization (MR) approach. The analysis involved 3935 cerebral IDPs from the UK Biobank and all documented cases of epilepsy (all epilepsies) cohorts from the International League Against Epilepsy, with further validation through replication and meta-analyses using epilepsy Genome-Wide Association Studies datasets from the FinnGen database. Additionally, a multivariate MR analysis framework was utilized to assess the direct impact of IDPs on all epilepsies. Furthermore, we performed a bidirectional MR analysis to investigate the relationship between the IDPs identified in all epilepsies and the 15 specific subtypes of epilepsy. The study identified significant causal links between four IDPs and epilepsy risk. Decreased fractional anisotropy in the left inferior longitudinal fasciculus was associated with a higher risk of epilepsy (odds ratio [OR]: 0.89, p=3.31×10-5). Conversely, increased mean L1 in the left posterior thalamic radiation (PTR) was independently associated with a heightened epilepsy risk (OR: 1.14, p=4.72×10-5). Elevated L3 in the left cingulate gyrus was also linked to an increased risk (OR: 1.09, p=.03), while decreased intracellular volume fraction in the corpus callosum was correlated with higher epilepsy risk (OR: 0.94, p=1.15×10-4). Subtype analysis revealed that three of these IDPs are primarily associated with focal epilepsy (FE). Notably, increased L1 in the left PTR was linked to an elevated risk of hippocampal sclerosis (HS) and lesion-negative FE, whereas elevated L3 in the left cingulate gyrus was associated with HS-related FE. Our research offers genetic evidence for a causal link between brain IDPs and epilepsy. These results enhance our understanding of the structural brain changes associated with the onset and progression of epilepsy.

Assessing Visual Pathway White Matter Degeneration in Primary Open‐Angle Glaucoma Using Multiple MRI Morphology and Diffusion Metrics

BackgroundPrimary open‐angle glaucoma (POAG), a leading cause of irreversible blindness, is associated with neurodegeneration in the visual pathway, but the underlying pathophysiology remains incompletely resolved.PurposeTo characterize macro‐ and microstructural white matter abnormalities in optic tract (OT) and optic radiation (OR) of POAG.Study typeProspective.PopulationsA total of 34 POAG patients (21 males, 13 females) and 25 healthy controls (HCs) (16 males, nine females).Field Strength/Sequence3 T; multiband spin‐echo echo planar diffusion spectrum imaging (DSI).AssessmentWe compared multiple morphology metrics, including volume, area, length, and shape metrics, as well as diffusion metrics such as diffusion tensor imaging (fractional anisotropy [FA], mean diffusivity, radial diffusivity, and axial diffusivity), mean apparent propagator (mean squared displacement, q‐space inverse variance, return‐to‐origin probability, return‐to‐axis probabilities [RTAP] and return‐to‐plane probabilities, non‐Gaussianity, perpendicular non‐Gaussianity, parallel non‐Gaussianity), and neurite orientation dispersion and density imaging (intracellular volume fraction, orientation dispersion index [ODI], and isotropic volume fraction of the OT and OR).Statistical TestsStatistical comparisons and classifications employed linear mixed model and logistic regression. Diagnostic performance was assessed using area under the receiver operating characteristic curve (AUC). P‐value &lt;0.05 was statistically significant.ResultsMorphology analysis in POAG revealed a lower span in the OR (29.43 ± 2.30 vs. 30.59 ± 2.01, 3.8%) and OT (19.73 ± 2.21 vs. 20.68 ± 1.37, 4.6%), and a higher curl (3.03 ± 0.22 vs. 2.90 ± 0.16, 4.5%) in OT. Diffusion metrics revealed lower mean FA (OR: 0.328 ± 0.03 vs. 0.340 ± 0.018, 3.5%; OT: 0.255 ± 0.022 vs. 0.268 ± 0.018, 4.9%) and lower mean RTAP (OR: 5.919 ± 0.529 vs. 6.216 ± 0.489, 4.8%; OT: 4.089 ± 0.402 vs. 4.280 ± 0.353, 4.5%), with higher mean ODI in the OT (0.448 ± 0.029 vs. 0.433 ± 0.025, 3.5%). Combined models, incorporating these MRI metrics, effectively discriminated POAG from HCs, achieving AUCs of 0.84 for OR and 0.83 for OT.Data ConclusionsDSI‐derived morphology and diffusion metrics demonstrated macro‐ and micro abnormalities in the visual pathway, providing insights into POAG‐related neurodegeneration.Level of Evidence2Technical EfficacyStage 3

Joint estimation of compartment-specific T2 relaxation and tumor microstructure using multi-TE IMPULSED MRI.

This study aims to assess how T2 heterogeneity biases IMPULSED-derived metrics of tissue microstructure in solid tumors and evaluate the potential of estimating multi-compartmental T2 and microstructural parameters simultaneously. This study quantifies the impact of T2 relaxation on IMPULSED-derived microstructural parameters using computer simulations and in vivo multi-TE IMPULSED MRI in five tumor models, including brain, breast, prostate, melanoma, and colon cancer. A comprehensive T2 + IMPULSED method was developed to fit multi-compartmental T2 and microstructural parameters simultaneously. A Bayesian model selection approach was carried out voxel-wisely to determine if the T2 heterogeneity needs to be included in IMPULSED MRI in cancer. Simulations suggest that T2 heterogeneity has a minor effect on the estimation of d in tissues with intermediate or high cell density, but significantly biases the estimation of with low cell density. For the in vivo animal experiments, all IMPULSED metrics except are statistically independent on TE. For B16 tumors, the IMPULSED-derived exhibited a notable increase with longer TEs. For MDA-MB-231 tumors, IMPULSED-derived showed a significant increase with increasing TEs. The T2 + IMPULSED-derived of all five tumor models are consistently smaller than . The findings from this study highlight two key observations: (i) TE has a negligible impact on IMPULSED-derived cell sizes, and (ii) the TE-dependence of IMPULSED-derived intracellular volume fractions used in T2 + IMPULSED modeling to estimate and . These insights contribute to the ongoing development and refinement of non-invasive MRI techniques for measuring cell sizes.

Mapping the neurodevelopmental predictors of psychopathology.

Neuroimaging research has uncovered a multitude of neural abnormalities associated with psychopathology, but few prediction-based studies have been conducted during adolescence, and even fewer used neurobiological features that were extracted across multiple neuroimaging modalities. This gap in the literature is critical, as deriving accurate brain-based models of psychopathology is anessential steptowards understanding key neural mechanisms and identifying high-risk individuals. As such, we trained adaptive tree-boosting algorithms on multimodal neuroimaging features from the Lifespan Human Connectome Developmental (HCP-D) sample that contained 956 participants between the ages of 8 to 22 years old. Our feature space consisted of 1037 anatomical, 1090 functional, and 192 diffusion MRI features, which were used to derive models that separately predicted internalizing symptoms, externalizing symptoms, and the general psychopathology factor. We found that multimodal models were the most accurate, but all brain-based models of psychopathology yielded out-of-sample predictions that were weakly correlated with actual symptoms (r2 < 0.15). White matter microstructural properties, including orientation dispersion indices and intracellular volume fractions, were the most predictive of general psychopathology, followed by cortical thickness and functional connectivity. Spatially, the most predictive features of general psychopathology were primarily localized within the default mode and dorsal attention networks. These results were mostly consistent across all dimensions of psychopathology, except orientation dispersion indices and the default mode network were not as heavily weighted in the prediction of internalizing and externalizing symptoms. Taken with prior literature, it appears that neurobiological features are an important part of the equation for predicting psychopathology but relying exclusively on neural markers is clearly not sufficient, especially among adolescent samples with subclinical symptoms. Consequently, risk factor models of psychopathology may benefit from incorporating additional sources of information that have also been shown to explain individual differences, such as psychosocial factors, environmental stressors, and genetic vulnerabilities.

Mapping macrostructural and microstructural brain alterations in patients with neuronal intranuclear inclusion disease.

Neuronal intranuclear inclusion disease (NIID) is a rare complex neurodegenerative disorder presents with various radiological features. The study aimed to investigate the structural abnormalities in NIID using multi-shell diffusion MR. Twenty-eight patients with adult-onset NIID and 32 healthy controls were included. Volumetric and diffusion MRI measures, including volume, fractional anisotropy (FA), mean diffusivity (MD), intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF) of six brain structures, including cortex, subcortical GM, cerebral WM, cerebellar GM and WM, and brainstem, were obtained and compared between NIID and healthy controls. Associations between MRI measures and clinical variables were investigated. Brain lesions of NIID included corticomedullary junction lesions on DWI, confluent leukoencephalopathy, lesions on callosum, cerebellar middle peduncle, cerebellar paravermal area and brainstem, and brain atrophy. Compared to healthy controls, NIID showed extensive volume loss of all the six brain regions (all p < 0.001); lower FA in cerebral WM (p < 0.001); higher MD in all WM regions; lower ODI in cortex (p < 0.001); higher ODI in subcortical GM (p < 0.001) and brainstem (p = 0.016); lower ICVF in brainstem (p = 0.001), and cerebral WM (p < 0.001); higher ISOVF in all the brain regions (p < 0.001). Higher MD of cerebellar WM was associated with worse cognitive level as evaluated by MoCA scores (p = 0.011). NIID patients demonstrated widespread brain atrophy but heterogeneous diffusion alterations. Cerebellar WM integrity impairment was correlated with the cognitive decline. The findings of the current study offer a sophisticated picture of brain structural alterations in NIID.

Mediating and moderating effects of plasma proteomic biomarkers on the association between poor oral health problems and brain white matter microstructural integrity: the UK Biobank study.

The plasma proteome can mediate associations between periodontal disease (Pd) and brain white matter integrity (WMI). We screened 5089 UK Biobank participants aged 40-70 years for poor oral health problems (POHP). We examined the association between POHP and WMI (fractional anisotropy (FA), mean diffusivity (MD), Intracellular Volume Fraction (ICVF), Isotropic Volume Fraction (ISOVF) and Orientation Diffusion (OD)), decomposing the total effect through the plasma proteome of 1463 proteins into pure mediation, pure interaction, neither, while adjusting for socio-demographic and cardiovascular health factors. Similarly, structural equations modeling (SEM) was conducted. POHP was more prevalent among men (12.3% vs. 9.6%), and was associated with lower WMI on most metrics, in a sex-specific manner. Of 15 proteins strongly associated with POHP, growth differentiation factor 15 (GDF15) and WAP four-disulfide core domain 2 (WFDC2; also known as human epididymis protein 4; HE4) were consistent mediators. Both proteins mediated 7-8% of total POHP effect on FAmean. SEM yielded significant total effects for FAmean, MDmean and ISOVFmean in full models, with %mediated by common latent factor (GDF15 and WFDC2) ranging between 13% (FAmean) and 19% (ISOVFmean). For FA, mediation by this common factor was found for 16 of 49 tract-specific and global mean metrics. Protein metabolism, immune system, and signal transduction were the most common pathways for mediational effects. POHP was associated with poorer WMI, which was partially mediated by GDF15 and WFDC2.

Age dictates brain functional connectivity and axonal integrity following repetitive mild traumatic brain injuries in mice

Traumatic brain injuries (TBI) present a major public health challenge, demanding an in-depth understanding of age-specific symptoms and risk factors. Aging not only significantly influences brain function and plasticity but also elevates the risk of hospitalizations and death following TBIs. Repetitive mild TBIs (rmTBI) compound these issues, resulting in cumulative and long-term brain damage in the brain. In this study, we investigate the impact of age on brain network changes and white matter properties following rmTBI by employing a multi-modal approach that integrates resting-state functional magnetic resonance imaging (rsfMRI), graph theory analysis, diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI). Our hypothesis is that the effects of rmTBI are worsened in aged animals, with this group showing more pronounced alterations in brain connectivity and white matter structure. Utilizing the closed-head impact model of engineered rotational acceleration (CHIMERA) model, we conducted rmTBIs or sham (control) procedures on young (2.5–3-months-old) and aged (22-months-old) male and female mice to model high-risk groups. Functional and structural imaging unveiled age-related reductions in communication efficiency between brain regions, while injuries induced opposhigh-risking effects on the small-world index across age groups, influencing network segregation. Functional connectivity analysis also identified alterations in 79 out of 148 brain regions by age, treatment (sham vs. rmTBI), or their interaction. Injuries exerted pronounced effects on sensory integration areas, including insular and motor cortices. Age-related disruptions in white matter integrity were observed, indicating alterations in various diffusion directions (mean diffusivity, radial diffusivity, axial diffusivity, and fractional anisotropy) and density neurite properties (dispersion index, intracellular and isotropic volume fraction). Neuroinflammation, assessed through Iba-1 and GFAP markers, correlated with higher dispersion in the optic tract, suggesting a neuroinflammatory response in injured aged animals compared to sham aged. These findings offer insight into the interplay between age, injuries, and brain connectivity, shedding light on the long-term consequences of rmTBI.

Brain effects of mild COVID-19 in healthy young adults: A pilot study

Rationale and objectivesThis study examined the brain effects of mild severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection which are incompletely understood. Our objective was to ascertain within-person changes associated with mild coronavirus disease 2019 (COVID-19) in otherwise healthy adults. Materials and methodsWe leveraged existing pre-pandemic baseline neuroimaging and neurocognitive data, and collected follow-up data from uninfected controls and individuals with prior mild COVID-19, during December 2020 and January 2021, when vaccines were not yet available. We compared change during follow-up in patients (n = 5) versus controls (n = 15). ResultsWe identified a decrease of intracellular volume fraction (ICVF), decrease of isotropic volume fraction (ISO) and decrease of orientation dispersion index (ODI) in multiple inferior frontal regions of interest in COVID-19 patients; this longitudinal change was significantly different from the control group which demonstrated increases in equivalent measures. This pattern suggests injury with neuronal loss and/or inflammation as underlying mechanisms. Neurocognitive studies identified a pattern of cognitive decline (processing speed, executive function, verbal learning, working memory) in patients, that did not reach significance. ConclusionOur pilot data suggests that mild COVID-19 may result in brain pathology and impact neurocognitive function in younger adults in a manner parallel to prior findings in older individuals. Though findings may not generalize to other SARS-CoV-2 variants, larger longitudinal studies of mild COVID-19 should be undertaken to understand the potential clinical implications of these findings over the longer term.

Genetic evidence supports a causal relationship between air pollution and brain imaging-derived phenotypes

BackgroundObservational studies have reported associations between air pollutants and brain imaging-derived phenotypes (IDPs); however, whether this relationship is causal remains uncertain. MethodsWe conducted bidirectional two-sample Mendelian randomization (MR) analyses to explore the causal relationships between 5 types of air pollutants (N=423,796 to 456,380 individuals) and 587 reliable IDPs (N=33,224 individuals). Two-step MR was also conducted to assess whether the identified effects are mediated through the modulation of circulating cytokines (N=8293). ResultsWe found genetic evidence supporting the association of nitrogen oxides (NOx) with mean intra-cellular volume fraction (ICVF) in the left uncinate fasciculus (IVW β=-0.42, 95 % CI −0.62 to −0.23, P=1.51×10−5) and mean fractional anisotropy (FA) in the left uncinate fasciculus (IVW β=-0.42, 95 % CI −0.62 to −0.21, P=4.89×10−5). In further two-step MR analyses, we did not find evidence that genetic predictions of any circulating cytokines mediated the association between NOx and IDPs. ConclusionThis study provides evidence for the association between air pollutants and brain IDPs, emphasizing the importance of controlling air pollution to improve brain health.

Brain lesion microstructure in neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein disease.

Neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) diagnosis are based on the presence of serological and magnetic resonance imaging (MRI) biomarkers. Diffusion tensor imaging (DTI), neurites orientation dispersion and density imaging (NODDI), and the Spherical Mean Technique (SMT) may be helpful to provide a microstructural characterization of the different types of white matter lesions and give an insight about their different pathological mechanisms. The aim of the study was to characterize microstructural differences between brain typical lesions (TLs) and nontypical lesions (nTLs). A total of 17 NMOSD and MOGAD patients [9 Aquaporin4 (AQP4)+NMO, 2 seronegative-NMO, 6 MOGAD] underwent MRI scans on a 3 Tesla MAGNETON PRISMA. Diffusion parameters (fractional anisotropy; mean diffusivity [MD]; intracellular volume fraction [ICVF]; extra-neurite transverse diffusivity; and extra-neurite MD; neurite signal fraction) were obtained using DTI, NODDI, and SMT. Microstructural parameters within lesions were compared through a generalized linear model using age, sex, and total lesion volume as covariates. In NMOSD/MOGAD whole cohort (total lesions=477), TLs showed increased MD and decreased ICVF compared to nTLs (p<.05), indicating higher inflammation and axonal loss. Similar results were found also in the AQP4+NMO subgroup (decreased ICVF, p<.05). Furthermore, in NMOSD/MOGAD whole cohort and in AQP4+NMO subgroup, TLs showed a trend toward higher EXRATRANS than nTLs, suggesting a more severe degree of demyelination within TLs. TLs and nTLs in NMOSD/MOGAD showed different diffusion MRI-derived microstructural features, with TLs showing a more severe degree of inflammation and fiber disruption with respect to nTLs.

Multiparametric Characterization and Spatial Distribution of Different MS Lesion Phenotypes.

MS lesions exhibit varying degrees of axonal and myelin damage. A comprehensive description of lesion phenotypes could contribute to an improved radiologic evaluation of smoldering inflammation and remyelination processes. This study aimed to identify in vivo distinct MS lesion types using quantitative susceptibility mapping and susceptibility mapping-weighted imaging and to characterize them through T1-relaxometry, myelin mapping, and diffusion MR imaging. The spatial distribution of lesion phenotypes in relation to ventricular CSF was investigated. MS lesions of 53 individuals were categorized into iso- or hypointense lesions, hyperintense lesions, and paramagnetic rim lesions, on the basis of their appearance on quantitative susceptibility mapping alone, according to published criteria, and with the additional support of susceptibility mapping-weighted imaging. Susceptibility values, T1-relaxation times, myelin and free water fractions, intracellular volume fraction, and the orientation dispersion index were compared among lesion phenotypes. The distance of the geometric center of each lesion from the ventricular CSF was calculated. Eight hundred ninety-six MS lesions underwent the categorization process using quantitative susceptibility mapping and susceptibility mapping-weighted imaging. The novel use of susceptibility mapping-weighted images, which revealed additional microvasculature details, led us to re-allocate several lesions to different categories, resulting in a 35.6% decrease in the number of paramagnetic rim lesions, a 22.5% decrease in hyperintense lesions, and a 17.2% increase in iso- or hypointense lesions, with respect to the categorization based on quantitative susceptibility mapping only. The outcome of the categorization based on the joint use of quantitative susceptibility mapping and susceptibility mapping-weighted imaging was that 44.4% of lesions were iso- or hypointense lesions, 47.9% were hyperintense lesions, and 7.7% were paramagnetic rim lesions. A worsening gradient was observed from iso- or hypointense lesions to hyperintense lesions to paramagnetic rim lesions in T1-relaxation times, myelin water fraction, free water fraction, and intracellular volume fraction. Paramagnetic rim lesions were located closer to ventricular CSF than iso- or hypointense lesions. The volume of hyperintense lesions was associated with a more severe disease course. Quantitative susceptibility mapping and susceptibility mapping-weighted imaging allow in vivo classification of MS lesions into different phenotypes, characterized by different levels of axonal and myelin loss and spatial distribution. Hyperintense lesions and paramagnetic rim lesions, which have the most severe microstructural damage, were more often observed in the periventricular WM and were associated with a more severe disease course.

Generative AI for Rapid Diffusion MRI with Improved Image Quality, Reliability and Generalizability

Abstract We use generative AI to enable rapid diffusion MRI (dMRI) with high fidelity, reproducibility, and generalizability across clinical and research settings. We employ a Swin UNEt Transformers (SWIN) model, trained on Human Connectome Project (HCP) data (n=1021) and conditioned on registered T1 scans, to perform generalized dMRI denoising. We also qualitatively demonstrate super-resolution with artificially downsampled HCP data. Remarkably, SWIN can be fine-tuned for an out-of-domain dataset with a single example scan, as we demonstrate on dMRI of children with neurodevelopmental disorders (n=40), adults with acute traumatic brain injury (n=40), and adolescents with intracerebral hemorrhage due to vascular malformations undergoing resection (n = 8), each cohort scanned on different scanner models with different imaging protocols at different sites. This robustness to scan acquisition parameters, patient populations, scanner types, and sites eliminates the advantages of self-supervised methods over our fully-supervised generative AI approach. We exceed current state-of-the-art denoising methods in accuracy and test-retest reliability of rapid diffusion tensor imaging (DTI) requiring only 90 seconds of scan time. SWIN denoising also achieves dramatic improvements over the state-of-the-art for test-retest reliability of intracellular volume fraction and free water fraction measurements and can remove heavy-tail noise, improving biophysical modeling fidelity. SWIN enables rapid diffusion MRI with unprecedented accuracy and reliability, especially at high diffusion-weighting for probing biological tissues at microscopic spatial scales. The code and model are publicly available at https://github.com/ucsfncl/dmri-swin.

Improving Microstructural Estimation in Time-Dependent Diffusion MRI With a Bayesian Method.

Accurately fitting diffusion-time-dependent diffusion MRI (td-dMRI) models poses challenges due to complex and nonlinear formulas, signal noise, and limited clinical data acquisition. Introduce a Bayesian methodology to refine microstructural fitting within the IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion) model and optimize the prior distribution within the Bayesian framework. Retrospective. Involving 69 pediatric patients (median age 6 years, interquartile range [IQR] 3-9 years, 61% male) with 41 low-grade and 28 high-grade gliomas, of which 76.8% were identified within the brainstem or cerebellum. 3 T, oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE). The Bayesian method's performance in fitting cell diameter ( ), intracellular volume fraction ( ), and extracellular diffusion coefficient ( ) was compared against the NLLS method, considering simulated and experimental data. The tumor region-of-interest (ROI) were manually delineated on the b0 images. The diagnostic performance in distinguishing high- and low-grade gliomas was assessed, and fitting accuracy was validated against H&E-stained pathology. T-test, receiver operating curve (ROC), area under the curve (AUC) and DeLong's test were conducted. Significance considered at P < 0.05. Bayesian methodology manifested increased accuracy with robust estimates in simulation (RMSE decreased by 29.6%, 40.9%, 13.6%, and STD decreased by 29.2%, 43.5%, and 24.0%, respectively for , , and compared to NLLS), indicating fewer outliers and reduced error. Diagnostic performance for tumor grade was similar in both methods, however, Bayesian method generated smoother microstructural maps (outliers ratio decreased by 45.3% ± 19.4%) and a marginal enhancement in correlation with H&E staining result (r = 0.721 for compared to r = 0.698 using NLLS, P = 0.5764). The proposed Bayesian method substantially enhances the accuracy and robustness of IMPULSED model estimation, suggesting its potential clinical utility in characterizing cellular microstructure. 3 TECHNICAL EFFICACY: Stage 1.

Association of Gene Expression and Tremor Network Structure.

Transcriptomic changes in the essential tremor (ET)-associated cerebello-thalamo-cortical "tremor network" and their association to brain structure have not been investigated. The aim was to characterize molecular changes associated with network-level imaging-derived phenotypes (IDP) found in ET. We performed an imaging-transcriptomic study in British adults using imaging-genome-wide association study summary statistics (UK Biobank "BIG40" cohort; n = 33,224, aged 40-69 years). We imputed imaging-transcriptomic associations for 184 IDPs and analyzed functional enrichment of gene modules and aggregate network-level phenotypes. Validation was performed in cerebellar-tissue RNA-sequencing data from ET patients and controls (n = 55). Among 237,896 individual predicted gene expression levels for 6063 unique genes/transcripts, we detected 2269 genome-wide significant associations (Bonferroni P < 2.102e-7, 0.95%). These were concentrated in intracellular volume fraction measures of white matter pathways and in genes with putative links to tremor (MAPT, ARL17A, KANSL1, SPPL2C, LRRC37A4P, PLEKHM1, and FMNL1). Whole-tremor-network cortical thickness was associated with a gene module linked to mitochondrial organization and protein quality control (r = 0.91, P = 2e-70), whereas white-gray T1-weighted magnetic resonance imaging (MRI) contrast in the tremor network was associated with a gene module linked to sphingolipid synthesis and ethanolamine metabolism (r = -0.90, P = 2e-68). Imputed association effect sizes and RNA-sequencing log-fold change in the validation dataset were significantly correlated for cerebellar peduncular diffusion MRI phenotypes, and there was a close overlap of significant associations between both datasets for gray matter phenotypes (χ2 = 6.40, P = 0.006). The identified genes and processes are potential treatment targets for ET, and our results help characterize molecular changes that could in future be used for patient treatment selection or prognosis prediction. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

White Matter Hyperintensities and Microstructural Alterations in Contact Sport Athletes from Adolescence to Early Midlife.

Studies have demonstrated associations between cumulative concussion and repetitive head impact exposure (RHI) through contact sports with white matter (WM) alterations later in life. The course of WM changes associated with exposure earlier in the lifespan is unclear. This study investigated alterations in white matter (WM hyperintensity [WMH] volume and microstructural changes) associated with concussion and RHI exposure from adolescence to early midlife, as well as the interaction between exposure and age cohort (i.e., adolescent/young adult compared with early midlife athlete cohorts) on WM outcomes. Participating football players included an adolescent/young adulthood cohort (n = 82; Mage = 18.4 ± 1.7) and an early midlife cohort (37 former collegiate players approximately 15 years removed from sport; Mage = 37.7 ± 1.4). Years of football participation and number of prior concussions were exposures of interest. White matter outcomes included log-transformed manually segmented total WMH volume and neurite orientation dispersion and density imaging metrics of microstructure/organization (isotropic volume fraction [Viso], intracellular volume fraction [Vic], and orientation dispersion [OD]). Regression models were fit to test the effects of concussion history, years of football participation, and age cohort by years of football participation with WM outcomes. Spearman's correlations assessed associations between significant WM metrics and measures of cognitive and psychological function. A significant age cohort by years of participation effect was observed for whole brain white matter OD, B = -0.002, SE = 0.001, p = 0.001. The interaction was driven by a negative association between years of participation and OD within the younger cohort, B = -0.001, SE = 0.0004, p = 0.008, whereas a positive association between participation and OD in the early midlife cohort, B = 0.001, SE = 0.0003, p = 0.039, was observed. Follow-up ROI analyses showed significant interaction effects for OD in the body of the corpus callosum, genu of the corpus callosum, cingulum, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, and posterior thalamic radiation (p values <0.05). Greater concussion history was significantly associated with greater Viso in the early midlife cohort, B = 0.001, SE = 0.0002, p = 0.010. Years of participation and concussion history were not associated with WMH volume, p values >0.05. Performance on a measure of executive function was significantly associated with years of participation, ρ = 0.34, p = 0.04, and a trend was observed for OD, ρ = 0.28, p = 0.09 in the early midlife cohort only. The global characterization of white matter changes associated with years of football participation were broadly similar and stable from adolescence through early midlife (i.e., microstructural alterations, but not macroscopic lesions). An inverse association between years of participation and orientation dispersion across age cohorts may represent a process of initial recovery/reorganization proximal to sport, followed by later reduction of white matter coherence.