Functional MRI Measures Research Articles

Information Flow Pattern in Early Mild Cognitive Impairment Patients.

Purpose: To investigate the brain information flow pattern in patients with early mild cognitive impairment (EMCI) and explore its potential ability of differentiation and prediction for EMCI.Methods: In this study, 49 patients with EMCI and 40 age- and sex-matched healthy controls (HCs) with available resting-state functional MRI images and neurological measures [including the neuropsychological evaluation and cerebrospinal fluid (CSF) biomarkers] were included from the Alzheimer's Disease Neuroimaging Initiative. Functional MRI measures including preferred information flow direction between brain regions and preferred information flow index of each brain region parcellated by the Atlas of Intrinsic Connectivity of Homotopic Areas (AICHA) were calculated by using non-parametric multiplicative regression-Granger causality analysis (NPMR-GCA). Edge- and node-wise Student's t-test was conducted for between-group comparison. Support vector classification was performed to differentiate EMCI from HC. The least absolute shrinkage and selection operator (lasso) regression were used to evaluate the predictive ability of information flow measures for the neurological state.Results: Compared to HC, disturbed preferred information flow directions between brain regions involving default mode network (DMN), executive control network (ECN), somatomotor network (SMN), and visual network (VN) were observed in patients with EMCI. An altered preferred information flow index in several brain regions (including the thalamus, posterior cingulate, and precentral gyrus) was also observed. Classification accuracy of 80% for differentiating patients with EMCI from HC was achieved by using the preferred information flow directions. The preferred information flow directions have a good ability to predict memory and executive function, level of amyloid β, tau protein, and phosphorylated tau protein with the high Pearson's correlation coefficients (r > 0.7) between predictive and actual neurological measures.Conclusion: Patients with EMCI were presented with a disturbed brain information flow pattern, which could help clinicians to identify patients with EMCI and assess their neurological state.

Neuroimmune signatures in chronic low back pain subtypes.

We recently showed that patients with different chronic pain conditions (such as chronic low back pain, fibromyalgia, migraine and Gulf War illness) demonstrated elevated brain and/or spinal cord levels of the glial marker 18-kDa translocator protein (TSPO), which suggests that neuroinflammation might be a pervasive phenomenon observable across multiple aetiologically heterogeneous pain disorders. Interestingly, the spatial distribution of this neuroinflammatory signal appears to exhibit a degree of disease specificity (e.g. with respect to the involvement of the primary somatosensory cortex), suggesting that different pain conditions may exhibit distinct 'neuroinflammatory signatures'. To explore this hypothesis further, we tested whether neuroinflammatory signal can characterize putative aetiological subtypes of chronic low back pain patients based on clinical presentation. Specifically, we explored neuroinflammation in patients whose chronic low back pain either did or did not radiate to the leg (i.e. 'radicular' versus 'axial' back pain). Fifty-four patients with chronic low back pain, 26 with axial back pain [43.7 ± 16.6 years old (mean ± SD)] and 28 with radicular back pain (48.3 ± 13.2 years old), underwent PET/MRI with 11C-PBR28, a second-generation radioligand for TSPO. 11C-PBR28 signal was quantified using standardized uptake values ratio (validated against volume of distribution ratio; n = 23). Functional MRI data were collected simultaneously to the 11C-PBR28 data (i) to functionally localize the primary somatosensory cortex back and leg subregions; and (ii) to perform functional connectivity analyses (in order to investigate possible neurophysiological correlations of the neuroinflammatory signal). PET and functional MRI measures were compared across groups, cross-correlated with one another and with the severity of 'fibromyalgianess' (i.e. the degree of pain centralization, or 'nociplastic pain'). Furthermore, statistical mediation models were used to explore possible causal relationships between these three variables. For the primary somatosensory cortex representation of back/leg, 11C-PBR28 PET signal and functional connectivity to the thalamus were: (i) higher in radicular compared to axial back pain patients; (ii) positively correlated with each other; (iii) positively correlated with fibromyalgianess scores, across groups; and finally (iv) fibromyalgianess mediated the association between 11C-PBR28 PET signal and primary somatosensory cortex-thalamus connectivity across groups. Our findings support the existence of 'neuroinflammatory signatures' that are accompanied by neurophysiological changes and correlate with clinical presentation (in particular, with the degree of nociplastic pain) in chronic pain patients. These signatures may contribute to the subtyping of distinct pain syndromes and also provide information about interindividual variability in neuroimmune brain signals, within diagnostic groups, that could eventually serve as targets for mechanism-based precision medicine approaches.

Kynurenines increase MRS metabolites in basal ganglia and decrease resting-state connectivity in frontostriatal reward circuitry in depression

Inflammation is associated with the development of anhedonia in major depression (MD), but the pathway by which inflammatory molecules gain access to the brain and lead to anhedonia is not clear. Molecules of the kynurenine pathway (KP), which is activated by inflammation, readily influx into the brain and generate end products that alter brain chemistry, disrupt circuit functioning, and result in the expression of inflammatory behaviors such as anhedonia. We examined the impact of plasma and CSF KP metabolites on brain chemistry and neural function using multimodal neuroimaging in 49 depressed subjects. We measured markers of glial dysfunction and distress including glutamate (Glu) and myo-inositol in the left basal ganglia using magnetic resonance spectroscopy (MRS); metrics of local activity coherence (regional homogeneity, ReHo) and functional connectivity from resting-state functional MRI measures; and anhedonia from the Inventory for Depressive Symptoms-Self Report Version (IDS-SR). Plasma kynurenine/tryptophan (KYN/TRP) ratio and cerebrospinal fluid (CSF) 3-hydroxykynurenine (3HK) were associated with increases in left basal ganglia myo-inositol. Plasma kynurenic acid (KYNA) and KYNA/QA were associated with decreases and quinolinic acid (QA) with increases in left basal ganglia Glu. Plasma and CSF KP were associated with decreases in ReHo in the basal ganglia and dorsomedial prefrontal regions (DMPFC) and impaired functional connectivity between these two regions. DMPFC-basal ganglia mediated the effect of plasma and CSF KP on anhedonia. These findings highlight the pathological impact of KP system dysregulation in mediating inflammatory behaviors such as anhedonia.

Diffusion Weighted Imaging and T2 Mapping Detect Inflammatory Response in the Renal Tissue during Ischemia Induced Acute Kidney Injury in Different Mouse Strains and Predict Renal Outcome.

To characterize ischemia reperfusion injury (IRI)-induced acute kidney injury (AKI) in C57BL/6 (B6) and CD1-mice by longitudinal functional MRI-measurement of edema formation (T2-mapping) and inflammation (diffusion weighted imaging (DWI)). IRI was induced with unilateral right renal pedicle clamping for 35min. 7T-MRI was performed 1 and 14 days after surgery. DWI (7 b-values) and multiecho TSE sequences (7 TE) were acquired. Parameters were quantified in relation to the contralateral kidney on day 1 (d1). Renal MCP-1 and IL-6-levels were measured by qPCR and serum-CXCL13 by ELISA. Immunohistochemistry for fibronectin and collagen-4 was performed. T2-increase on d1 was higher in the renal cortex (127 ± 5% vs. 94 ± 6%, p < 0.01) and the outer stripe of the outer medulla (141 ± 9% vs. 111 ± 9%, p < 0.05) in CD1, indicating tissue edema. Medullary diffusivity was more restricted in CD1 than B6 (d1: 73 ± 3% vs. 90 ± 2%, p < 0.01 and d14: 77 ± 5% vs. 98 ± 3%, p < 0.01). Renal MCP-1 and IL-6-expression as well as systemic CXCL13-release were pronounced in CD1 on d1 after IRI. Renal fibrosis was detected in CD1 on d14. T2-increase and ADC-reduction on d1 correlated with kidney volume loss on d14 (r = 0.7, p < 0.05; r = 0.6, p < 0.05) and could serve as predictive markers. T2-mapping and DWI evidenced higher susceptibility to ischemic AKI in CD1 compared to B6.

Quantitative muscle MRI biomarkers in Duchenne muscular dystrophy: cross-sectional correlations with age and functional tests.

Aim:Using baseline data from a clinical trial of domagrozumab in Duchenne muscular dystrophy, we evaluated the correlation between functional measures and quantitative MRI assessments of thigh muscle.Patients & methods:Analysis included timed functional tests, knee extension/strength and North Star Ambulatory Assessment. Patients (n = 120) underwent examinations of one thigh, with MRI sequences to enable measurements of muscle volume (MV), MV index, mean T2 relaxation time via T2-mapping and fat fraction.Results:MV was moderately correlated with strength assessments. MV index, fat fraction and T2-mapping measures had moderate correlations (r ∼ 0.5) to all functional tests, North Star Ambulatory Assessment and age.Conclusion:The moderate correlation between functional tests, age and baseline MRI measures supports MRI as a biomarker in Duchenne muscular dystrophy clinical trials. Trial registration: ClinicalTrials.gov, NCT02310763; registered 4 November 2014.

Network Damage Predicts Clinical Worsening in Multiple Sclerosis: A 6.4-Year Study.

ObjectiveIn multiple sclerosis (MS), clinical impairment is likely due to both structural damage and abnormal brain function. We assessed the added value of integrating structural and functional network MRI measures to predict 6.4-year MS clinical disability deterioration.MethodsBaseline 3D T1-weighted and resting-state functional MRI scans were obtained from 233 patients with MS and 77 healthy controls. Patients underwent a neurologic evaluation at baseline and at 6.4-year median follow-up (interquartile range = 5.06–7.51 years). At follow-up, patients were classified as clinically stable/worsened according to disability changes. In relapsing-remitting (RR) MS, secondary progressive (SP) MS conversion was evaluated. Global brain volumetry was obtained. Furthermore, independent component analysis identified the main functional connectivity (FC) and gray matter (GM) network patterns.ResultsAt follow-up, 105/233 (45%) patients were clinically worsened; 26/157 (16%) patients with RRMS evolved to SPMS. The treatment-adjusted random forest model identified normalized GM and brain volumes, decreased FC between default-mode networks, increased FC of the left precentral gyrus in the sensorimotor network (SMN), and GM atrophy in the fronto-parietal network (false discovery rate [FDR]-corrected p = range 0.01–0.09) as predictors of clinical worsening (out-of-bag [OOB] accuracy = 0.74). An expected contribution of baseline disability was also present (FDR-p = 0.01). Baseline disability, normalized GM volume, and GM atrophy in the SMN (FDR-p = range 0.01–0.09) were independently associated with SPMS conversion (OOB accuracy = 0.84). At receiver operating characteristic analysis, including network MRI variables improved disability worsening (p = 0.05) and SPMS conversion (p = 0.02) prediction.ConclusionsIntegration of MRI network measures helped determining the relative contributions of global/local GM damage and functional reorganization to clinical deterioration in MS.

Subtyping relapsing-remitting multiple sclerosis using structural MRI.

Subtyping relapsing-remitting multiple sclerosis (RRMS) patients may help predict disease progression and triage patients for treatment. We aimed to subtype RRMS patients by structural MRI and investigate their clinical significances. 155 relapse-remitting MS (RRMS) and 210 healthy controls (HC) were retrospectively enrolled with structural 3DT1, diffusion tensor imaging (DTI) and resting-state functional MRI. Z scores of cortical and deep gray matter volumes (CGMV and DGMV) and white matter fractional anisotropy (WM-FA) in RRMS patients were calculated based on means and standard deviations of HC. We defined RRMS as "normal" (-2 < z scores of both GMV and WM-FA), DGM (z scores of DGMV < -2), and DGM-plus types (z scores of DGMV and [CGMV or WM-FA] < -2) according to combinations of z scores compared to HC. Expanded disability status scale (EDSS), cognitive and functional MRI measurements, and conversion rate to secondary progressive MS (SPMS) at 5-year follow-up were compared between subtypes. 77 (49.7%) patients were "normal" type, 37 (23.9%) patients were DGM type and 34 (21.9%) patients were DGM-plus type. 7 (4.5%) patients who were not categorized into the above types were excluded. DGM-plus type had the highest EDSS. Both DGM and DGM-plus types had more severe cognitive impairment than "normal" type. Only DGM-plus type showed decreased functional MRI measures compared to HC. A higher conversion ratio to SPMS in DGM-plus type (55%) was identified compared to "normal" type (14%, p < 0.001) and DGM type (20%, p = 0.005). Three MRI-subtypes of RRMS were identified with distinct clinical and imaging features and different prognosis.

Internal reliability of blame-related functional MRI measures in major depressive disorder

BackgroundIn major depressive disorder (MDD), self-blame-related fMRI measures have shown the potential to be used as prognostic markers for recurrence risk. Like most potential fMRI markers, however, their reliability is unclear. Here, we probed the internal reliability of self-blame-related fMRI measures, as well as the impact of different modelling approaches on reliability metrics and validity. MethodsInternal consistency (i.e. split-half reliability) was calculated for blood oxygen level-dependent (BOLD) responses and psychophysiological interactions (PPI) related to self-blame-related biases in medication-free remitted MDD participants (n = 81) and healthy controls (n = 41). Trial-length was modelled using three durations (0, 2 and 5 s), which was convolved with the haemodynamic response function (HRF) with and without time and dispersion derivatives. Intraclass correlation coefficients (ICCs) were calculated for simple contrasts examining activation to self-blaming emotions and other-blaming emotions and the more complex contrast of the subtraction-based difference between self- and other-blaming emotions within the following a priori ROIs: right superior anterior temporal lobe seed region, anterior subgenual cingulate cortex, posterior subgenual cortex and right striatum / pallidum. ResultsAcross ROIs, we obtained fair reliability (ICC ≥ 0.40) for simple, but poor reliability (ICC < 0.40) for more complex fMRI measures related to self-blame. Despite this low internal consistency of complex measures at the individual level, we observed robust activation at the group-level, reproducing previously published results. ConclusionsWhile simple BOLD contrasts had fair reliability, previously employed PPI models had poor reliability and simple connectivity measures lacked predictive validity. This calls for the development of functional connectivity measures that strike a better balance between reliability and validity for future clinical applications, which require robust measures at the individual rather than group-level.

Structural, Functional MRI Measures Improve Prediction of Multiple Sclerosis Long-Term Worsening

The reconciliation of primary and useful attractive reverberation imaging (MRI) gauges fundamentally further developed expectation of long haul clinical deteriorating in patients with numerous scleroses (MS), as indicated by study discoveries distributed in Neurology: Neuroimmunology and Neuroinflammation. Presently, there is a functioning discussion in regards to the force of traditional MRI for foreseeing the clinical course of MS. As of late, there have been endeavors to work on the prescient worth of MRI in MS by assessing clinically significant mind compartments, including dark matter (GM), key white matter (WM) lots, and the spinal line. Furthermore, the planning of utilitarian and primary mind networks has likewise been viewed as conceivably clinically pertinent.

Rationale and Design of the PAIRED Trial: Partnered Dance Aerobic Exercise as a Neuroprotective, Motor, and Cognitive Intervention in Parkinson's Disease.

Parkinson's disease (PD), an intractable condition impairing motor and cognitive function, is imperfectly treated by drugs and surgery. Two priority issues for many people with PD are OFF-time and cognitive impairment. Even under best medical management, three-fourths of people with PD experience “OFF-time” related to medication-related motor fluctuations, which severely impacts both quality of life and cognition. Cognitive deficits are found even in newly diagnosed people with PD and are often intractable. Our data suggest that partnered dance aerobic exercise (PDAE) reduces OFF-time on the Movement Disorders Society Unified Parkinson Disease Rating Scale-IV (MDS-UPDRS-IV) and ameliorates other disease features, which motivate the PAIRED trial. PDAE provides AE during an improvisational, cognitively engaging rehabilitative physical activity. Although exercise benefits motor and cognitive symptoms and may be neuroprotective for PD, studies using robust biomarkers of neuroprotection in humans are rare. We propose to perform a randomized, controlled trial in individuals with diagnosed mild–moderate PD to compare the efficacy of PDAE vs. walking aerobic exercise (WALK) for OFF-time, cognition, and neuroprotection. We will assess neuroprotection with neuromelanin-sensitive MRI (NM-MRI) and iron-sensitive (R2*) MRI sequences to quantify neuromelanin loss and iron accumulation in substantia nigra pars compacta (SNc). We will use these biomarkers, neuromelanin loss, and iron accumulation, as tools to chart the course of neurodegeneration in patients with PD who have undergone long-term (16 months) intervention. We will randomly assign 102 individuals with mild–moderate PD to 16 months of PDAE or WALK. The 16-month intervention period will consist of Training (3 months of biweekly sessions) and Maintenance (13 months of weekly sessions) phases. We will assess participants at baseline, 3 months (immediately post-Training), and 16 months (immediately post-Maintenance) for OFF-time and behaviorally and physiologically measured cognition. We will acquire NM-MRI and R2* imaging data at baseline and 16 months to assess neuroprotection. We will (1) examine effects of Training and Maintenance phases of PDAE vs. WALK on OFF-time, (2) compare PDAE vs. WALK at 3 and 16 months on behavioral and functional MRI (fMRI) measures of spatial cognition, and (3) compare PDAE vs. WALK for effects on rates of neurodegeneration.

Parsing impulsivity in individuals with anxiety and depression who use Cannabis

BackgroundIndividuals with anxiety/depression may impulsively use cannabis to acutely induce positive affect and attenuate aversive mood states. However, few studies have attempted to parse impulsivity displayed by anxious/depressed cannabis users. This investigation examined what aspects of impulsivity characterize those individuals using self-report and functional MRI (fMRI) measures. MethodsIndividuals with any lifetime anxiety/depression diagnoses and problematic cannabis use (“Anx/Dep+CB”; n=42) were compared to a propensity score-matched group with very low cannabis use (“Anx/Dep-lowCB”; n=42), and a healthy control group (n=37). Impulsivity was measured using the UPPS-P Impulsivity Questionnaire and the Stop Signal Task (SST) during fMRI. For UPPS-P, regression models estimated group-by-impulsivity subscale interactions with post-hoc pairwise tests. For the SST, similar regression models were estimated with four a-priori regions of interest (ROIs; right opercularis, orbitalis, dorsal and ventral anterior insula) during stop-success and stop-failure processing. Null SST findings were followed up using Bayes factor analysis to quantify the evidence in support of the null hypothesis. ResultsFor the UPPS-P, a significant group-by-subscale interaction indicated that the Anx/Dep+CB group exhibited higher levels of impulsivity on the negative- and positive-urgency subscales relative to both comparison groups. Higher negative-urgency correlated with heavier lifetime cannabis use across groups. For the SST, there were no ROI task activation differences. Bayes factor analysis determined the null findings were at least three times more likely than the alternative hypothesis for all ROIs. ConclusionsImpulsivity under periods of heightened affect, but not motor response inhibitions, characterized anxious/depressed individuals who use cannabis.

Disturbances across whole brain networks during reward anticipation in an abstinent addiction population

The prevalent spatial distribution of abnormalities reported in cognitive fMRI studies in addiction suggests there are extensive disruptions across whole brain networks. Studies using resting state have reported disruptions in network connectivity in addiction, but these studies have not revealed characteristics of network functioning during critical psychological processes that are disrupted in addiction populations. Analytic methods that can capture key features of whole brain networks during psychological processes may be more sensitive in revealing additional and widespread neural disturbances in addiction, that are the provisions for relapse risk, and targets for medication development. The current study compared a substance addiction (ADD; n = 83) group in extended abstinence with a control (CON; n = 68) group on functional MRI (voxel-wise activation) and global network (connectivity) measures related to reward anticipation on a monetary incentive delay task. In the absence of group differences on MID performance, the ADD group showed reduced activation predominantly across temporal and visual regions, but not across the striatum. The ADD group also showed disruptions in global network connectivity (lower clustering coefficient and higher characteristic path length), and significantly less connectivity across a sub-network comprising frontal, temporal, limbic and striatal nodes. These results show that an addiction group in extended abstinence exhibit localised disruptions in brain activation, but more extensive disturbances in functional connectivity across whole brain networks. We propose that measures of global network functioning may be more sensitive in highlighting latent and more widespread neural disruptions during critical psychological processes in addiction and other psychiatric disorders.

The Representation of Two-Body Shapes in the Human Visual Cortex.

Human social nature has shaped visual perception. A signature of the relationship between vision and sociality is a particular visual sensitivity to social entities such as faces and bodies. We asked whether human vision also exhibits a special sensitivity to spatial relations that reliably correlate with social relations. In general, interacting people are more often situated face-to-face than back-to-back. Using functional MRI and behavioral measures in female and male human participants, we show that visual sensitivity to social stimuli extends to images including two bodies facing toward (vs away from) each other. In particular, the inferior lateral occipital cortex, which is involved in visual-object perception, is organized such that the inferior portion encodes the number of bodies (one vs two) and the superior portion is selectively sensitive to the spatial relation between bodies (facing vs nonfacing). Moreover, functionally localized, body-selective visual cortex responded to facing bodies more strongly than identical, but nonfacing, bodies. In this area, multivariate pattern analysis revealed an accurate representation of body dyads with sharpening of the representation of single-body postures in facing dyads, which demonstrates an effect of visual context on the perceptual analysis of a body. Finally, the cost of body inversion (upside-down rotation) on body recognition, a behavioral signature of a specialized mechanism for body perception, was larger for facing versus nonfacing dyads. Thus, spatial relations between multiple bodies are encoded in regions for body perception and affect the way in which bodies are processed.SIGNIFICANCE STATEMENT Human social nature has shaped visual perception. Here, we show that human vision is not only attuned to socially relevant entities, such as bodies, but also to socially relevant spatial relations between those entities. Body-selective regions of visual cortex respond more strongly to multiple bodies that appear to be interacting (i.e., face-to-face), relative to unrelated bodies, and more accurately represent single body postures in interacting scenarios. Moreover, recognition of facing bodies is particularly susceptible to perturbation by upside-down rotation, indicative of a particular visual sensitivity to the canonical appearance of facing bodies. This encoding of relations between multiple bodies in areas for body-shape recognition suggests that the visual context in which a body is encountered deeply affects its perceptual analysis.

Differential brain mechanisms during reading human vs. machine translated fiction and news texts

Few neuroimaigng studies on reading comprehension have been conducted under natural reading settings. In this study, we showed texts presented in a natural way during functional MRI (fMRI) measurements to reveal brain areas sensitive to reading comprehension. Specifically, this paradigm independently manipulated two holistic features of article style: text genre and translation style, a qualitative index of how typical word choices and arrangements are made in daily use of the language. Specifically, articles from The New York Times (news) and Reader’s Digest (fiction) translated from English to Mandarin Chinese either by human experts or machine (Google Translate) were used to investigate the correlation of brain activity across participants during article reading. We found that bi-hemispheric visual cortex, precuneus, and occipito-parietal junction show significantly correlated hemodynamics across participants regardless of translation style and article genre. Compared to machine translation, reading human expert translation elicited more reliable fMRI signals across participants at precuneus, potentially because narrative representations and contents can be coherently presented over tens of seconds. We also found significantly stronger inter-subject correlated fMRI signals at temporal poles and fusiform gyri in fiction reading than in news reading. This may be attributed to more stable empathy processing across participants in fiction reading. The degree of stability of brain responses across subjects at extra-linguistic areas was found correlated with subjective rating on the text fluency. The functional connectivity between these areas was modulated by text genre and translation style. Taken together, our imaging results suggested stable and selective neural substrates associated with comprehending holistic features of written narratives.

Determination of right ventricular function with adjusted systolic to diastolic duration ratio after transannular patch repair of tetralogy of Fallot.

Early detection of right ventricular dysfunction after transannular patch for tetralogy of Fallot (TOF-TAP) is essential for management. To evaluate echocardiographic metrics of ventricular function correlate with functional MRI measurements, in patients with TOF-TAP. A retrospective review of patients with TOF-TAP between 2007 and 2017 who had an echocardiogram and MRI within six months were analyzed. Systolic to diastolic ratio (SD ratio) was measured from the tricuspid regurgitation and adjusted for heart rate. Tricuspid Annular Plane Systolic Excursion (TAPSE), Fractional Area Change (FAC), and shortening fraction (SF) were additionally measured. Echocardiographic measurements were correlated with MRI assessment of right ventricular ejection fraction (RVEF), left ventricular ejection fraction (LVEF), right ventricular end-diastolic volume index (RVEDi), and right to left ventricle volume ratio (RV/LV). Of the 53 patients (mean age 12.8years) that met inclusion criteria, 45 (85%) had available TR jets for SD ratio analysis. The HR adjusted SD ratio negatively correlated with RVEF (r=-.359, P=.016), LVEF (r=-.317, P=.038) and positively with RV/LV EDV ratio (r=.347, P=.024). TAPSE, FAC, and SF measurements did not show significant correlation. In patients with TOF-TAP, there is a moderate negative correlation between heart rate adjusted SD ratio and MRI metrics of ventricular function, suggesting that decreased filling time is a marker for reduced right ventricular function. The SD ratio may be a useful echocardiographic tool for serial evaluation of in this population.

CEST MRI with distribution-based analysis for assessment of early stage disease activity in a mouse model of multiple sclerosis: An initial study.

Imaging biomarkers that can detect pathological changes at an early stage of multiple sclerosis (MS) may allow earlier therapeutic intervention with an improved outcome. Using a mouse model of MS, termed as experimental autoimmune encephalomyelitis (EAE), we performed chemical exchange saturation transfer (CEST) MRI at a very early stage before symptom onset (6days post-induction) for assessment of changes in tissues that appear "normal" with conventional MRI. The collected CEST Z-spectra signals (Ssat /S0 ) were analyzed using a histogram-guided method to determine the contributions from various offset frequencies. Histogram analysis showed that EAE mice exhibit a more heterogeneous distribution with lower peak heights in the hindbrain compared with naïve mice at saturation offsets of 1 and 2ppm. At these two offsets, both the mean Ssat /S0 and the mean MTRasym values in the cerebellum and brain stem are significantly different between EAE and naïve mice (P<0.05). Immunofluorescent staining validated the presence of neuroinflammation, with IBA1-positive cells detected throughout the hindbrain including the cerebellum and brain stem. Follow-up MRI at the symptom onset (score=1.5-2.5, 13days post-induction) confirmed gadolinium-enhanced periventricular lesions. CEST Z-spectra signals also changed by this time. The proposed three-level histogram-oriented analysis is simple to execute and robust for detecting subtle changes in Z-spectra signals, which does not require a priori knowledge of damage locations or contributing offset components. CEST MRI signals at 1 and 2ppm were sensitive to the subtle pathological changes at an early stage in EAE mice, and have potential as novel imaging biomarkers complementary to functional and physiological MRI measures.

Baseline Frontoparietal Task-Related BOLD Activity as a Predictor of Improvement in Clinical Symptoms at 1-Year Follow-Up in Recent-Onset Psychosis.

The early course of illness in psychotic disorders is highly variable, and predictive biomarkers of treatment response have been lacking. Trial and error remains the basis for care in early psychosis, and poor outcomes are common. Early prediction of nonimprovement in response to treatment could help identify those who would benefit from alternative and/or supplemental interventions. The goal of this study was to evaluate the ability of functional MRI (fMRI) measures of cognitive control-related brain circuitry collected at baseline to predict symptomatic response in patients after 1 year. Patients with recent-onset (<2 years) psychotic disorders (N=82) in early psychosis specialty care were classified as improvers (>20% improvement in total score on the Brief Psychiatric Rating Scale [BPRS] at 1-year follow-up compared with baseline) or as nonimprovers. Behavioral (d' context) and fMRI (proactive control-associated activation in a priori frontoparietal regions of interest) measures of cognitive control were then evaluated on their ability to predict BPRS improvement using linear and logistic regression. Cognitive control-associated measures significantly predicted BPRS improvement and improver status, with 70% positive predictive value, 60% negative predictive value, and 66% accuracy. Only the fMRI-based measure (and not the behavioral measure) significantly predicted status. These results suggest that frontoparietal activation during cognitive control performance at baseline significantly predicts subsequent symptomatic improvement during early psychosis specialty care. Potential implications for fMRI-based personalized patient treatment are discussed.

Brain functional organization and structure in patients with arteriovenous malformations.

Developmental in nature, brain arteriovenous malformations (AVM) have the potential to affect whole brain organization. Here we investigated the impact of AVM on functional and structural brain organization using resting-state functional MRI (rsfMRI) and cortical thickness measures. We investigated brain functional organization and structure using rsfMRI in conjunction with cortical thickness analyses in 23 patients with cerebral arteriovenous malformations (AVMs) and 20 healthy control subjects. Healthy controls showed the expected anti-correlation between activity in the default mode network (DMN) and frontal areas that are part of the attentional control network. By contrast, patients demonstrated a disruption of this anti-correlation. Disruptions to this anti-correlation were even observed in a subgroup of patients with lesions remote from the main nodes of the DMN and were unrelated to differences in perfusion. Functional connectivity differences were accompanied by reduced cortical thickness in frontal attentional areas in patients compared to the controls. These results contribute to the discussion that AVMs affect whole brain networks and not simply the area surrounding the lesion.

Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction

The specificity and sensitivity of resting state functional MRI (rs-fMRI) measurements depend on preprocessing choices, such as the parcellation scheme used to define regions of interest (ROIs). In this study, we critically evaluate the effect of brain parcellations on machine learning models applied to rs-fMRI data. Our experiments reveal an intriguing trend: On average, models with stochastic parcellations consistently perform as well as models with widely used atlases at the same spatial scale. We thus propose an ensemble learning strategy to combine the predictions from models trained on connectivity data extracted using different (e.g., stochastic) parcellations. We further present an implementation of our ensemble learning strategy with a novel 3D Convolutional Neural Network (CNN) approach. The proposed CNN approach takes advantage of the full-resolution 3D spatial structure of rs-fMRI data and fits non-linear predictive models. Our ensemble CNN framework overcomes the limitations of traditional machine learning models for connectomes that often rely on region-based summary statistics and/or linear models. We showcase our approach on a classification (autism patients versus healthy controls) and a regression problem (prediction of subject's age), and report promising results.

Neuropathological correlates of structural and functional imaging biomarkers in 4-repeat tauopathies.

Neurodegenerative dementia syndromes are characterized by spreading of pathological protein deposition along syndrome-specific neural networks. Structural and functional MRI measures can assess the integrity of these networks and have been proposed as biomarkers of disease progression for clinical trials. The relationship between in vivo imaging measures and pathological features, at the single subject level, remains largely unknown. Patient-specific maps of atrophy and seed-based intrinsic connectivity disruption, as compared to normal controls, were obtained for 27 patients subsequently diagnosed with progressive supranuclear palsy (n = 16, seven males, age at death 68.9 ± 6.0 years, imaging-to-pathology interval = 670.2 ± 425.1 days) or corticobasal degeneration (n = 11, two males, age at death 66.7 ± 5.4 years, imaging-to-pathology interval = 696.2 ± 482.2 days). A linear mixed effect model with crossed random effects was used to test regional and single-subject level associations between post-mortem regional measures of neurodegeneration and tau inclusion burden, on the one hand, and regional volume loss and seed-based intrinsic connectivity reduction, on the other. A significant association was found between tau inclusion burden and in vivo volume loss, at the regional level and independent of neurodegeneration severity, in both progressive supranuclear palsy [n = 340 regions; beta 0.036; 95% confidence interval (CI): 0.001, 0.072; P = 0.046] and corticobasal degeneration (n = 215 regions; beta 0.044; 95% CI: 0.009, 0.079; P = 0.013). We also found a significant association between post-mortem neurodegeneration and in vivo volume loss in both progressive supranuclear palsy (n = 340 regions; beta 0.155; 95% CI: 0.061, 0.248; P = 0.001) and corticobasal degeneration (n = 215 regions; beta 0.277; 95% CI: 0.104, 0.450; P = 0.002). We found a significant association between regional neurodegeneration and intrinsic connectivity dysfunction in corticobasal degeneration (n = 215 regions; beta 0.074; 95% CI: 0.005, 0.143; P = 0.035), but no other associations between post-mortem measures of tauopathy and intrinsic connectivity dysfunction reached statistical significance. Our data suggest that in vivo structural imaging measures reflect independent contributions from neurodegeneration and tau burden in progressive supranuclear palsy and corticobasal degeneration. Seed-based measures of intrinsic connectivity dysfunction showed less reliable predictive value when used as in vivo biomarkers of tauopathy. The findings provide important guidance for the use of imaging biomarkers as indirect in vivo assays of microscopic pathology.