Voxel-wise Analysis Research Articles

Cerebral white matter myelination is associated with longitudinal changes in processing speed across the adult lifespan

Abstract Myelin's role in processing speed is pivotal, as it facilitates efficient neural conduction. Its decline could significantly affect cognitive efficiency during aging. In this work, myelin content was quantified using our advanced MRI method of myelin water fraction (MWF) mapping. We examined the relationship between MWF at the time of MRI and retrospective longitudinal change in processing speed among 121 cognitively unimpaired participants, aged 22 to 94 years, from the Baltimore Longitudinal Study of Aging and the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (mean follow-up duration of 4.3 ± 6.3 years) using linear mixed-effects models, adjusting for demographics. We found that higher MWF values correlated with longitudinally better-maintained processing speed, with particularly significant associations in several white matter regions. Detailed voxel-wise analysis provided further insight into the specific white matter tracts involved. This research underscores the essential role of myelin in preserving processing speed and highlights its potential as a sensitive biomarker for interventions targeting age-related cognitive decline, thereby offering a foundation for preventative strategies in neurological health.

Visualizing the association between the location and prognosis of isocitrate dehydrogenase wild-type glioblastoma: a voxel-wise Cox regression analysis with open-source datasets.

This study examined the correlation between tumor location and prognosis in patients with glioblastoma using magnetic resonance images of various isocitrate dehydrogenase (IDH) wild-type glioblastomas from The Cancer Imaging Archive (TCIA). The relationship between tumor location and prognosis was visualized using voxel-wise Cox regression analysis. Participants with IDH wild-type glioblastoma were selected, and their survival and demographic data and tumor characteristics were collected from TCIA datasets. Post-contrast-enhanced T1-weighted imaging, T2-fluid attenuated inversion recovery imaging, and tumor segmentation data were also compiled. Following affine registration of each image and tumor segmentation region of interest to the MNI standard space, a voxel-wise Cox regression analysis was conducted. This analysis determined the association of the presence or absence of the tumor with the prognosis in each voxel after adjusting for the covariates. The study included 769 participants of 464 men and 305 women (mean age, 63years ± 12 [standard deviation]). The hazard ratio map indicated that tumors in the medial frontobasal region and around the third and fourth ventricles were associated with poorer prognoses, underscoring the challenges of complete resection and treatment accessibility in these areas regardless of the tumor volume. Conversely, tumors located in the right temporal and occipital lobes had favorable prognoses. This study showed an association between tumor location and prognosis. These findings may assist clinicians in developing more precise and effective treatment plans for patients with glioblastoma to improve their management.

BIOM-27. VOXEL-WISE SURVIVAL ANALYSIS IN GLIOBLASTOMA: TUMOR PROBABILITY MAPS REVEAL CRITICAL REGIONS NEAR WHITE MATTER TRACTS

Abstract BACKGROUND Glioblastoma is the most aggressive primary brain tumor, characterized by rapid growth and poor prognosis. Understanding spatial determinants of survival in GBM is crucial for improving prognostic accuracy and treatment strategies. Our study employs voxel-wise survival analysis (VSA) of tumor probability maps (TPMs) derived from MRI to identify high-risk brain regions. TPMs are generated through radio-pathomic mapping and can predict non-enhancing tumor regions not captured by traditional imaging. We aim to determine if high tumor probability regions are near previously identified critical white matter (WM) tracts and assess their impact on survival outcomes. METHODS We analyzed data from 374 GBM patients from the UCSF-PDGM-v2 dataset. Using a pretrained radio-pathomic model, TPMs were predicted based on T1, T1C, ADC, and FLAIR MRI sequences. All TPMs were rigidly registered to MNI space using ANTs. A Cox proportional hazards model was applied voxel-wise to assess the association between tumor probability and overall survival (OS). A p-value map was generated, thresholded, and cluster corrected (p < 0.05) for further analysis. RESULTS The VSA revealed that high tumor probability regions were significantly associated with poorer OS in GBM. Gray matter (GM) regions near WM tracts with high tumor probability showed markedly reduced survival. GM regions adjacent to the left IFOF (p < 0.05, HR = 1.19, 845 vs. 961 days for high/low TPM), Corpus Callosum Forceps Minor (p = 0.0001, HR = 1, 740 vs. 902 days), Body of the Corpus Callosum (p = 0.005, HR = 0.97, 748 vs. 798 days for high/low TPM) and other WM tracts, such as the left thalamic radiation superior and left reticulospinal tracts had similar trends. CONCLUSIONS Our study demonstrates that regions with high tumor probability, particularly those in the GM near critical WM tracts, are strongly associated with worse overall survival in GBM patients.

EPCO-03. METABOLIC INSIGHT INTO GLIOMA HETEROGENEITY: MAPPING WHOLE EXOME SEQUENCING TOIN VIVO IMAGING WITH STEREOTACTIC LOCALIZATION AND DEEP LEARNING

Abstract Intra-tumoral heterogeneity (ITH) complicates the diagnosis and treatment of glioma, partly due to the diverse metabolic profiles driven by genomic alterations. While multiparametric imaging captures spatial and functional variations enabling ITH characterization, it falls short in assessing the metabolic activities underpinning phenotypic differences. This gap stems from the challenge of integrating easily accessible, co-located pathology and genomic data with metabolic insights. This study presents a multi-faceted approach combining stereotactic biopsy with clinical open-craniotomy for sample collection, voxel-wise analysis of MR images, regression-based GAM, and whole-exome sequencing. The aim is to demonstrate the potential of machine learning algorithms to predict variations in cellular and molecular tumor characteristics. This retrospective study enrolled ten treatment-naïve patients with radiologically confirmed glioma who underwent multiparametric MR scans (T1W, T1W-CE, T2W, T2W-FLAIR, DWI) prior to surgery. During craniotomy, at least one stereotactic biopsy was collected from each patient, with the screenshots of sample locations saved for spatial registration to pre-surgical MR data. Whole-exome sequencing was performed on flash-frozen tumor samples, prioritizing five glioma-related genes: IDH1, TP53, EGFR, PIK3CA, and NF1. Regression was implemented with a GAM using a univariate shape function for each predictor. Standard ROC analyses were used to evaluate detection, with AUC calculated for each gene target and MR contrast combination. Mean AUC for five gene targets and 31 MR contrast combinations was 0.75±0.11, with individual AUCs as high as 0.96 for IDH1 and TP53 with T2W-FLAIR and ADC, and 0.99 for EGFR with T2W and ADC. An average AUC of 0.85 across the five mutations was achieved using the combination of T1W, T2W-FLAIR, and ADC. These results suggest the possibility of predicting exome-wide mutation events from non-invasive, in vivo imaging by combining stereotactic localization of glioma samples with a semi-parametric deep learning method. This approach holds potential for refining targeted therapy by better addressing the genomic heterogeneity of glioma tumors.

Localized FDG loss in lung cancer lesions

BackgroundAnalysis of [18F]-Fluorodeoxyglucose (FDG) kinetics in cancer has been most often limited to the evaluation of the average uptake over relatively large volumes. Nevertheless, tumor lesions also contain inflammatory infiltrates whose cells are characterized by a significant radioactivity washout due to the hydrolysis of FDG-6P catalyzed by glucose-6P phosphatase. The present study aimed to verify whether voxel-wise compartmental analysis of dynamic imaging can identify tumor regions characterized by tracer washout. The study included 11 patients with lung cancer submitted to PET/CT imaging for staging purposes. Tumour was defined by drawing a volume of interest loosely surrounding the lesion and considering all inside voxels with a standardized uptake value (SUV) > 40% of the maximum. Eight whole-body scans were repeated after 20 min of dynamic imaging centered on the heart. Six parametric maps were generated progressively by computing a Patlak regression line for each voxel. Each analysis considered a different set of frames: starting with all eight frames, then the last seven frames, and so on, down to the last three frames.ResultsDelaying the starting point of the compartmental analysis revealed a progressive increase in the prevalence of voxels with a negative slope. In the most delayed parametric map, these voxels represented 0.5–4.5% (median 2%) of the tumor volume. This effect was independent of tumor size and was predominantly located at the lesion borders.ConclusionsThe voxel-wise parametric maps provided by compartmental analysis identify a measurable volume characterized by radioactivity washout. The spatial localization of this pattern is compatible with the recognized preferential site of inflammatory infiltrates populating the tumor stroma and might improve the power of FDG imaging in monitoring the effectiveness of treatments aimed at empowering the host immune response against cancer.Trial registration: ClinicalTrials. The study was approved by the local ethical committee and it represented a single Institution ancillary trial within the expanded-access program for Nivolumab. NCT02475382. Registered 2015-06-16. URL: https://clinicaltrials.gov/study/NCT02475382?id=NCT02475382.&rank=1

Pain-Discriminating Information Decoded From Spatiotemporal Patterns of Hemodynamic Responses Measured by fMRI in the Human Brain.

Functional magnetic resonance imaging (fMRI) has been widely used in studying the neural mechanisms of pain in the human brain, primarily focusing on where in the brain pain-elicited neural activities occur (i.e., the spatial distribution of pain-related brain activities). However, the temporal dynamics of pain-elicited hemodynamic responses (HDRs) measured by fMRI may also contain information specific to pain processing but have been largely neglected. Using high temporal resolution fMRI (TR = 0.8 s) data acquired from 62 healthy participants, in the present study we aimed to test whether pain-distinguishing information could be decoded from the spatial pattern of the temporal dynamics (i.e., the spatiotemporal pattern) of HDRs elicited by painful stimuli. Specifically, the peak latency and the response duration were used to characterize the temporal dynamics of HDRs to painful laser stimuli and non-painful electric stimuli, and then were compared between the two conditions (i.e., pain and no-pain) using a voxel-wise univariate analysis and a multivariate pattern analysis. Furthermore, we also tested whether the two temporal characteristics of pain-elicited HDRs and their spatial patterns were associated with pain-related behaviors. We found that the spatial patterns of HDR peak latency and response duration could successfully discriminate pain from no-pain. Interestingly, we also observed that the Pain Vigilance and Awareness Questionnaire (PVAQ) scores were correlated with the average response duration in bilateral insula and secondary somatosensory cortex (S2) and could also be predicted from the across-voxel spatial patterns of response durations in the middle cingulate cortex and middle frontal gyrus only during painful condition but not during non-painful condition. These findings indicate that the spatiotemporal pattern of pain-elicited HDRs may contain pain-specific information and highlight the importance of studying the neural mechanisms of pain by taking advantage of the high sensitivity of fMRI to both spatial and temporal information of brain responses.

Longitudinal Evolution of the Brain Microstructure in Cirrhotic Patients on Diffusion Kurtosis Imaging.

Although improvement of cognitive function after liver transplantation has been demonstrated in several neuropsychological studies, there is limited research on longitudinal changes in the cirrhotic patients' brain structure before and after transplantation. To investigate longitudinal changes of brain microstructure in cirrhotic patients using diffusion kurtosis imaging (DKI). Prospective. A total of 153 cirrhosis patients, comprising 60 hepatic encephalopathy (HE) patients (16 females/44 males) and 93 no-HE patients (35 females/58 males), along with 93 healthy controls (HCs) (53 females/40 males) were enrolled. Subsequently, 58 recipients completed 1-month postoperative follow-up, 29 patients completed 1-, 3-months, and 17 patients completed 1-, 3-, 6-month follow-up. Spin-echo single-shot echo-planar sequence using a 3.0 T scanner. Diffusion kurtosis estimator software was used to estimate the DKI parameter maps by a MR imaging physicist (Y.-Y.C. with 12 years of experience). The diffusion metrics (eg, radial kurtosis [RK], mean kurtosis, fractional anisotropy, mean diffusivity) of the patients before transplantation were compared with those of the HCs using voxel-wise analysis of variance (ANOVA), along with t tests for post hoc analysis. Linear mixed-effects models were applied to the longitudinal data. We imposed a cluster level Family Wise Error (FWE) correction rate of PFWE = 0.05 with voxel-wise cutoff of P = 0.001 together with a cluster-size cutoff of N ≥ 56, and generated smoothness estimates from the preprocessed data using the mixed-model autocorrelation function. The RK metrics of the patients decreased significantly in the anterior cingulate cortex (HE/no-HE < HC, ANOVA-F = 21.91). After transplantation, the RK of the pallidum showed a continuous upward trend (time effect T = 11.26); whereas the RK of the right postcentral gyrus showed a continuous downward trend (time effect T = -9.56). In addition, the RK in superior longitudinal fasciculus showed new-onset decrease after transplantation. Longitudinal changes in DKI metrics reveal the course of brain microstructural changes before and after transplantation in cirrhotic patients, potentially associated with cognitive alterations after surgery. 1 TECHNICAL EFFICACY: Stage 4.

Cognitive Impact of β-Amyloid Load in the Rapid Eye Movement Sleep Behavior Disorder-Lewy Body Disease Continuum.

Rapid eye movement sleep behavior disorder (RBD) is linked to the diffuse-malignant subtype and higher cognitive burden in Lewy body disease (LBD). This study explores brain β-amyloid deposition and its association with cognitive decline across the RBD-LBD continuum. Patients with isolated RBD (iRBD), Parkinson's disease with probable RBD (PDRBD), and dementia with Lewy bodies with probable RBD (DLBRBD) underwent 18F-florbetaben positron emission tomography, 3T magnetic resonance imaging scans, and comprehensive neuropsychological assessments. Subjects were categorized as cognitively normal (NC), mild cognitive impairment (MCI), or dementia. Global and regional standardized uptake value ratios (SUVR) were estimated in predefined cognitive volumes of interest (VOI) derived from voxel-wise comparison analysis among the cognitive groups, namely the prefrontal, parietal, precentral cortices, lingual gyrus, and supplementary motor area. Generalized linear models assessed the relationship between 18F-florbetaben SUVRs and neuropsychological testing, adjusting for age and sex. Subgroup analysis focused on the polysomnography-confirmed iRBD-continuum subset (n = 41) encompassing phenoconverters and nonconverters in our prospective iRBD cohort. Eighty-six subjects were classified as follows: 14 NC, 54 MCI, and 18 dementia. The proportion of positive β-amyloid scans increased with advanced cognitive stages (P = 0.038). β-Amyloid signals in cognitive VOIs were elevated in subgroups showing impairment in Trail-Making Test B (TMT-B). A linear association between TMT-B z score and global cortical β-amyloid levels was observed in the iRBD-continuum subset (P = 0.013). Cortical β-amyloid accumulates with declines in executive function within the RBD-LBD continuum. TMT-B performance may be a useful marker associating with β-amyloid load, particularly in the iRBD population. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Trial of the cerebral perfusion response to sodium nitrite infusion in patients with acute subarachnoid haemorrhage using arterial spin labelling MRI

Aneurysmal subarachnoid haemorrhage (SAH) is a devastating subset of stroke. One of the major determinants of outcome is an evolving multifactorial injury occurring in the first 72 hours, known as early brain injury. Reduced nitric oxide (NO) bioavailability and an associated disruption to cerebral perfusion is believed to play an important role in this process. We sought to explore this relationship, by examining the effect on cerebral perfusion of the in vivo manipulation of NO levels using an exogenous NO donor (sodium nitrite).We performed a double blind placebo controlled randomised experimental medicine study of the cerebral perfusion response to sodium nitrite infusion during the early brain injury period in 15 low grade (World Federation of Neurosurgeons grade 1–2) SAH patients. Patients were randomly assigned to receive sodium nitrite at 10 mcg/kg/min or saline placebo. Assessment occurred following endovascular aneurysm occlusion, mean time after ictus 66h (range 34–90h). Cerebral perfusion was quantified before infusion commencement and after 3 hours, using multi-post labelling delay (multi-PLD) vessel encoded pseudocontinuous arterial spin labelling (VEPCASL) magnetic resonance imaging (MRI).Administration of sodium nitrite was associated with a significant increase in average grey matter cerebral perfusion. Group level voxelwise analysis identified that increased perfusion occurred within regions of the brain known to exhibit enhanced vulnerability to injury. These findings highlight the role of impaired NO bioavailability in the pathophysiology of early brain injury.

Contribution of resting-state functional connectivity of the subgenual anterior cingulate to prediction of antidepressant efficacy in patients with major depressive disorder

This study investigated how resting-state functional connectivity (rsFC) of the subgenual anterior cingulate cortex (sgACC) predicts antidepressant response in patients with major depressive disorder (MDD). Eighty-seven medication-free MDD patients underwent baseline resting-state functional MRI scans. After 12 weeks of escitalopram treatment, patients were classified into remission depression (RD, n = 42) and nonremission depression (NRD, n = 45) groups. We conducted two analyses: a voxel-wise rsFC analysis using sgACC as a seed to identify group differences, and a prediction model based on the sgACC rsFC map to predict treatment efficacy. Haufe transformation was used to interpret the predictive rsFC features. The RD group showed significantly higher rsFC between the sgACC and regions in the fronto-parietal network (FPN), including the bilateral dorsolateral prefrontal cortex (DLPFC) and bilateral inferior parietal lobule (IPL), compared to the NRD group. These sgACC rsFC measures correlated positively with symptom improvement. Baseline sgACC rsFC also significantly predicted treatment response after 12 weeks, with a mean accuracy of 72.64% (p < 0.001), mean area under the curve of 0.74 (p < 0.001), mean specificity of 0.82, and mean sensitivity of 0.70 in 10-fold cross-validation. The predictive voxels were mainly within the FPN. The rsFC between the sgACC and FPN is a valuable predictor of antidepressant response in MDD patients. These findings enhance our understanding of the neurobiological mechanisms underlying treatment response and could help inform personalized treatment strategies for MDD.

Effect of metacognitive interpersonal therapy on brain structural connectivity in borderline personality disorder: Results from the CLIMAMITHE randomized clinical trial

BackgroundRecently, we showed that Metacognitive Interpersonal Therapy (MIT) is effective in improving clinical symptoms in borderline personality disorder (BPD). Here, we investigated whether the effect of MIT on clinical features is associated to microstructural changes in brain circuits supporting core BPD symptoms. MethodsForty-seven BPD were randomized to MIT or structured clinical management, and underwent a clinical assessment and diffusion-weighted imaging before and after the intervention. Fractional anisotropy (FA), mean, radial, and axial diffusivities maps were computed using FSL toolbox. Microstructural changes were assessed (i) voxel-wise, with tract based spatial statistics (TBSS) and (ii) ROI-wise, in the triple network system (default mode, salience, and executive control networks). The effect of MIT on brain microstructure was assessed with paired tests using FSL PALM (voxel-wise), Linear Mixed-Effect Models or Generalized Linear Mixed Models (ROI-wise). Associations between microstructural and clinical changes were explored with linear regression (voxel-wise) and correlations (ROI-wise). ResultsThe voxel-wise analysis showed that MIT was associated with increased FA in the bilateral thalamic radiation and left associative tracts (p < .050, family-wise error rate corrected). At network system level, MIT increased FA and both interventions reduced AD in the executive control network (p = .05, uncorrected). LimitationsThe DTI metrics can't clarify the nature of axonal changes. ConclusionsOur results indicate that MIT modulates brain structural connectivity in circuits related to associative and executive control functions. These microstructural changes may denote activity-dependent plasticity, possibly representing a neurobiological mechanism underlying MIT effects. Trial registrationClinicalTrials.govNCT02370316 (https://clinicaltrials.gov/study/NCT02370316).

Reward neurocircuitry predicts longitudinal changes in alcohol use following trauma exposure

BackgroundTrauma is a risk factor for developing maladaptive alcohol use. Preclinical research has shown that stress alters the processing of midbrain and striatal reward and incentive signals. However, little research has been conducted on alterations in reward-related neurocircuitry post-trauma in humans. Neuroimaging markers may be particularly useful as they can provide insight into the mechanisms that may make an individual vulnerable to developing trauma-related psychopathologies. This study aimed to identify reward-related neural correlates associated with changes in alcohol use after trauma exposure. MethodsParticipants were recruited from U.S. emergency departments for the AURORA study (N=286, 178 female). Trauma-related change in alcohol use at 8 weeks post-trauma relative to pre-trauma was quantified as a change in 30-day total drinking per the PhenX Toolkit Alcohol 30-Day Quantity and Frequency Measure. Reward-related neurocircuitry activation and functional connectivity (FC) were assessed 2 weeks post-trauma using fMRI during a monetary reward task using region of interest and whole-brain voxelwise analyses. ResultsGreater increase in alcohol use from pre-trauma to 8 weeks post-trauma was predicted by (1) greater ventral tegmental area (VTA) and (2) greater cerebellum activation during Gain>Loss trials measured 2 weeks post-trauma and (3) greater seed-based FC between the VTA and lateral occipital cortex and precuneus. ConclusionsAltered VTA activation and FC early post-trauma may be associated with reward-seeking and processing, contributing to greater alcohol use post-trauma. These data provide novel evidence of neural correlates that underlie increased alcohol use early post-trauma that may be targeted via early interventions to prevent the development of maladaptive alcohol use.

Characteristics of locus coeruleus functional connectivity network in patients with comorbid migraine and insomnia

BackgroundMigraine and insomnia are prevalent conditions that often co-occur, each exacerbating the other and substantially impacting the quality of life. The locus coeruleus (LC), a brainstem region responsible for norepinephrine synthesis, participates in pain modulation, sleep/wake cycles, and emotional regulation, rendering it a potential nexus in the comorbidity of migraine and insomnia. Disruptions in the LC-noradrenergic system have been hypothesized to contribute to the comorbidities of migraine and insomnia, although neuroimaging evidence in humans remains scarce. In this study, we aimed to investigate the intrinsic functional connectivity (FC) network of the LC in patients with comorbid migraine and subjective chronic insomnia and patients with migraine with no insomnia (MnI) using resting-state functional magnetic resonance imaging (rs-fMRI) and seed-based FC analyses.MethodsIn this cross-sectional study, 30 patients with comorbid migraine and chronic insomnia (MI), 30 patients with MnI, and 30 healthy controls (HCs) were enrolled. Participants underwent neuropsychological testing and rs-fMRI. The LC-FC network was constructed using seed-based voxel-wise FC analysis. To identify group differences in LC-FC networks, voxel-wise covariance analysis was conducted with sex and age as covariates. Subsequently, a partial correlation analysis was conducted to probe the clinical relevance of aberrant LC-FC in patients with MI and MnI.ResultsExcept for the insomnia score, no other significant difference was detected in demographic characteristics and behavioral performance between the MI and MnI groups. Compared with HCs, patients with MI exhibited altered LC-FC in several brain regions, including the dorsomedial prefrontal cortex (DMPFC), anterior cerebellum, dorsolateral prefrontal cortex (DLPFC), thalamus, and parahippocampal gyrus (PHG). Lower FC between the LC and DLPFC was associated with greater insomnia severity, whereas higher FC between the LC and DMPFC was linked to longer migraine attack duration in the MI group.ConclusionOur findings reveal the presence of aberrant LC-FC networks in patients with MI, providing neuroimaging evidence of the interplay between these conditions. The identified LC-FC alterations may serve as potential targets for therapeutic interventions and highlight the importance of considering the LC-noradrenergic system in the management of MI.

Differences in brain structure and cognitive performance between patients with long-COVID and those with normal recovery

BackgroundThe pathophysiology of protracted symptoms after COVID-19 is unclear. This study aimed to determine if long-COVID is associated with differences in baseline characteristics, markers of white matter diffusivity in the brain, and lower scores on objective cognitive testing. MethodsIndividuals who experienced COVID-19 symptoms for more than 60 days post-infection (long-COVID) (n = 56) were compared to individuals who recovered from COVID-19 within 60 days of infection (normal recovery) (n = 35). Information regarding physical and mental health, and COVID-19 illness was collected. The National Institute of Health Toolbox Cognition Battery was administered. Participants underwent magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI). Tract-based spatial statistics were used to perform a whole-brain voxel-wise analysis on standard DTI metrics (fractional anisotropy, axial diffusivity, mean diffusivity, radial diffusivity), controlling for age and sex. NIH Toolbox Age-Adjusted Fluid Cognition Scores were used to compare long-COVID and normal recovery groups, covarying for Age-Adjusted Crystallized Cognition Scores and years of education. False discovery rate correction was applied for multiple comparisons. ResultsThere were no significant differences in age, sex, or history of neurovascular risk factors between the groups. The long-COVID group had significantly (p < 0.05) lower mean diffusivity than the normal recovery group across multiple white matter regions, including the internal capsule, anterior and superior corona radiata, corpus callosum, superior fronto-occiptal fasciculus, and posterior thalamic radiation. However, the effect sizes of these differences were small (all β<|0.3|) and no significant differences were found for the other DTI metrics. Fluid cognition composite scores did not differ significantly between the long-COVID and normal recovery groups (p > 0.05). ConclusionsDifferences in diffusivity between long-COVID and normal recovery groups were found on only one DTI metric. This could represent subtle areas of pathology such as gliosis or edema, but the small effect sizes and non-specific nature of the diffusion indices make pathological inference difficult. Although long-COVID patients reported many neuropsychiatric symptoms, significant differences in objective cognitive performance were not found.

A detailed analysis of body composition in relation to cardiopulmonary exercise test indices

A cardiopulmonary exercise test (CPET) is a test assessing an individual’s physiological response during exercise. Results may be affected by body composition, which is best evaluated through imaging techniques like magnetic resonance imaging (MRI). The aim of this study was to assess relationships between body composition and indices obtained from CPET. A total of 234 participants (112 female), all aged 50 years, underwent CPETs and whole-body MRI scans (> 1 million voxels). Voxel-wise statistical analysis of tissue volume and fat content was carried out with a method called Imiomics and related to the CPET indices peak oxygen consumption (V̇O2peak), V̇O2peak scaled by body weight (V̇O2kg) and by total lean mass (V̇O2lean), ventilatory efficiency (V̇E/V̇CO2-slope), work efficiency (ΔV̇O2/ΔWR) and peak exercise respiratory exchange ratio (RERpeak). V̇O2peak showed the highest positive correlation with volume of skeletal muscle. V̇O2kg negatively correlated with tissue volume in subcutaneous fat, particularly gluteal fat. RERpeak negatively correlated with tissue volume in skeletal muscle, subcutaneous fat, visceral fat and liver. Some associations differed between sexes: in females ΔV̇O2/ΔWR correlated positively with tissue volume of subcutaneous fat and V̇E/V̇CO2-slope with tissue volume of visceral fat, and, in males, V̇O2peak correlated positively to lung volume. In conclusion, voxel-based Imiomics provided detailed insights into how CPET indices were related to the tissue volume and fat content of different body structures.

Rest Tremor in Parkinson's Disease Is Associated with Ipsilateral Striatal Dopamine Transporter Binding.

The cardinal motor symptoms of Parkinson's disease (PD) include rigidity, bradykinesia, and rest tremor. Rigidity and bradykinesia correlate with contralateral nigrostriatal degeneration and striatal dopamine deficit, but association between striatal dopamine function and rest tremor has remained unclear. The aim of this study was to investigate the possible link between dopamine function and rest tremor using Parkinson's Progression Markers Initiative dataset, the largest prospective neuroimaging cohort of patients with PD. Clinical, [123I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane ([123I]FP-CIT) single photon emission computed tomography (SPECT), and structural magnetic resonance imaging data from 354 early PD patients and 166 healthy controls were included in this study. We employed a novel approach allowing nonlinear registration of individual scans accurately to a standard space and voxelwise analyses of the association between motor symptoms and striatal dopamine transporter (DAT) binding. Severity of both rigidity and bradykinesia was negatively associated with contralateral striatal DAT binding (PFWE < 0.05 [FWE, family-wise error corrected]). However, rest tremor amplitude was positively associated with increased ipsilateral DAT binding (PFWE < 0.05). The association between rest tremor and binding remained the same controlling for Hoehn & Yahr stage, Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III score, bradykinesia-rigidity score, or motor phenotype. The association between rest tremor and binding was independent of bradykinesia-rigidity and replicated using 2-year follow-up data (PFWE < 0.05). In agreement with the existing literature, we did not find a consistent association between rest tremor and contralateral dopamine defect. However, our results demonstrate a link between rest tremor and increased or less decreased ipsilateral DAT binding. Our findings provide novel information about the association between dopaminergic function and parkinsonian rest tremor. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Diffusion tensor imaging in Behcet's disease with and without neurological involvement patients: evaluation of microstructural white matter abnormality with a tract-based spatial statistical analysis.

This study aims to assess the microstructural abnormalities in white matter (WM) among Behcet's disease (BD) patients, both with and without neurological involvement, utilising tract-based spatial statistics (TBSS) to elucidate the underlying causes of WM microstructural changes. This prospective study comprised 43 BD patients without neurological involvement, 15 neuro-Behcet's disease (NBD) patients with normal conventional MRI, and 54 healthy controls matched for age and sex. TBSS was applied in this diffusion tensor imaging study to conduct a whole-brain voxel-wise analysis of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) of WM. Compared to the control group, BD patients exhibited decreased FA and increased MD and RD in nearly all WM tracts, along with increased AD in the left corticospinal tract (CST), left inferior longitudinal fasciculus (ILF), and left superior longitudinal fasciculus (SLF). NBD patients also showed a widespread decrease in FA and increased MD and RD, similar to BD patients without neurological involvement. Additionally, NBD patients had increased AD in the left CST, left ILF, left SLF, left inferior fronto-occipital fasciculus (IFOF), and right CST. Compared to BD patients without neurological involvement, NBD patients exhibited a greater reduction in FA and an increase in MD and RD in WM tracts, with no significant differences in AD. These results suggest that the main mechanism of microstructural changes in the WM of BD patients may be related to impaired fibre integrity, demyelination, and decreased myelin sheath integrity. This study demonstrated BD patients without neurological involvement and NBD patients a decrease in FA and an increase in MD and RD were observed in larger areas of major WM tracts, while an increase in AD values was observed in fewer tracts. Our findings may be useful in understanding the pathophysiology underlying subclinical parenchymal involvement and neurological dysfunction in BD patients and the management of BD patients.

From Phantoms to Patients: Improved Fusion and Voxel-Wise Analysis of Diffusion-Weighted Imaging and FDG-Positron Emission Tomography in Positron Emission Tomography/Magnetic Resonance Imaging for Combined Metabolic-Diffusivity Index (cDMI).

Hybrid positron emission tomography/magnetic resonance imaging (PET/MR) opens new possibilities in multimodal multiparametric (m2p) image analyses. But even the simultaneous acquisition of positron emission tomography (PET) and magnetic resonance imaging (MRI) does not guarantee perfect voxel-by-voxel co-registration due to organs and distortions, especially in diffusion-weighted imaging (DWI), which would be, however, crucial to derive biologically meaningful information. Thus, our aim was to optimize fusion and voxel-wise analyses of DWI and standardized uptake values (SUVs) using a novel software for m2p analyses. Using research software, we evaluated the precision of image co-registration and voxel-wise analyses including the rigid and elastic 3D registration of DWI and [18F]-Fluorodeoxyglucose (FDG)-PET from an integrated PET/MR system. We analyzed DWI distortions with a volume-preserving constraint in three different 3D-printed phantom models. A total of 12 PET/MR-DWI clinical datasets (bronchial carcinoma patients) were referenced to the T1 weighted-DIXON sequence. Back mapping of scatterplots and voxel-wise registration was performed and compared to the non-optimized datasets. Fusion was rated using a 5-point Likert scale. Using the 3D-elastic co-registration algorithm, geometric shapes were restored in phantom measurements; the measured ADC values did not change significantly (F = 1.12, p = 0.34). Reader assessment showed a significant improvement in fusion precision for DWI and morphological landmarks in the 3D-registered datasets (4.3 ± 0.2 vs. 4.6 ± 0.2, p = 0.009). Most pronounced differences were noted for the chest wall (p = 0.006), tumor (p = 0.007), and skin contour (p = 0.014). Co-registration increased the number of plausible ADC and SUV combinations by 25%. The volume-preserving elastic 3D registration of DWI significantly improved the precision of fusion with anatomical sequences in phantom and clinical datasets. The research software allowed for a voxel-wise analysis and visualization of [18F]FDG-PET/MR data as a "combined diffusivity-metabolic index" (cDMI). The clinical value of the optimized PET/MR biomarker can thus be tested in future PET/MR studies.

Investigating the impact of lumping heterogenous conduct problems: aggression and rule-breaking rely on distinct spontaneous brain activity.

Accumulating evidence suggests that aggression and rule-breaking may have distinct origins. However, grouping these heterogeneous behaviors into a single dimension labelled Conduct Problems (CP) has become the norm rather than the exception. Yet, the neurobiological features that differentiate aggression and rule-breaking remain largely unexplored. Using a large sample of children and adolescents (n = 1360, 6-18 years old), we examined the common and specific brain activity between CP, aggression, and rule-breaking behaviors. Analyses were conducted using fMRI resting-state data from a 10-minute session to explore the correlations between low frequency fluctuations and both broad and fine-grained CP dimensions. The broad CP dimension was associated with deficits in the precentral gyrus, superior temporal gyrus, and tempo-parietal junction. However, only the superior temporal gyrus was shared between aggression and rule-breaking. Activity of the precentral gyrus was mainly associated with rule-breaking, and the temporo-parietal cortex with aggression. More importantly, voxel-wise analyses on fine-grained dimensions revealed additional specific effects that were initially obscured when using a broad CP dimension. Finally, we showed that the findings specific to aggression and rule-breaking may be related to distinct brain networks and mental functions, especially ventral attention/sensorimotor processes and default mode network/social cognitions, respectively. The current study highlights that aggression and rule-breaking may be related to distinct local and distributed neurobiological markers. Overall, using fine-grained dimensions may provide a clearer picture of the role of neurobiological correlates in CP and their invariance across measurement levels. We advocate for adopting a more thorough examination of the lumping/splitting effect across neuroimaging studies on CP.

Omics-derived biological modules reflect metabolic brain changes in Alzheimer's disease.

Brain glucose hypometabolism, indexed by the fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging, is a metabolic signature of Alzheimer's disease (AD). However, the underlying biological pathways involved in these metabolic changes remain elusive. Here, we integrated [18F]FDG-PET images with blood and hippocampal transcriptomic data from cognitively unimpaired (CU, n=445) and cognitively impaired (CI, n=749) individuals using modular dimension reduction techniques and voxel-wise linear regression analysis. Our results showed that multiple transcriptomic modules are associated with brain [18F]FDG-PET metabolism, with the top hits being a protein serine/threonine kinase activity gene cluster (peak-t(223)=4.86, P value<0.001) and zinc-finger-related regulatory units (peak-t(223)=3.90, P value<0.001). By integrating transcriptomics with PET imaging data, we identified that serine/threonine kinase activity-associated genes and zinc-finger-related regulatory units are highly associated with brain metabolic changes in AD. We conducted an integrated analysis of system-based transcriptomics and fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) at the voxel level in Alzheimer's disease (AD). The biological process of serine/threonine kinase activity was the most associated with [18F]FDG-PET in the AD brain. Serine/threonine kinase activity alterations are associated with brain vulnerable regions in AD [18F]FDG-PET. Zinc-finger transcription factor targets were associated with AD brain [18F]FDG-PET metabolism.