Longitudinal Structural Magnetic Resonance Imaging Research Articles

Patterns of longitudinal subcortical atrophy over one year in amnestic mild cognitive impairment and its impact on cognitive performance: a preliminary study.

Amnestic mild cognitive impairment (aMCI) is a risk factor for dementia, and thus, it is of interest to enlighten specific brain atrophy patterns in aMCI patients. We aim to define the longitudinal atrophy pattern in subcortical structures and its effect on cognition in patients with aMCI. Twenty patients with aMCI and 20 demographically matched healthy controls with baseline and longitudinal structural magnetic resonance imaging scans and neuropsychological assessments were studied. The algorithm FIRST (FMRIB's integrated registration and segmentation tool) was used to obtain volumes of subcortical structures (thalamus, putamen, caudate nucleus, nucleus accumbens, globus pallidus, hippocampus, and amygdala). Correlations between volumes and cognitive performance were assessed. Compared with healthy controls, aMCI demonstrated subcortical atrophies in the hippocampus (p = 0.001), nucleus accumbens (p = 0.003), and thalamus (p = 0.003) at baseline. Significant associations were found for the baseline volumes of the thalamus, nucleus accumbens, and hippocampus with memory, the thalamus with visuospatial skills. aMCI demonstrated subcortical atrophies associated with cognitive deficits. The thalamus, nucleus accumbens, and hippocampus may provide additional diagnostic information for aMCI.

Longitudinal Neuroanatomical Increases from Early to One-Year Postpartum.

Preclinical studies have provided causal evidence that the postpartum period involves regional neuroanatomical changes in 'maternal' brain regions to support the transition to offspring caregiving. Few studies, in humans, have examined neuroanatomical changes from early to one-year postpartum with longitudinal neuroimaging data and their association with postpartum mood changes. In this study, we examined longitudinal changes in surface morphometry (cortical thickness and surface area) in regions previously implicated in the transition to parenthood. We also examined longitudinal volumetric neuroanatomical changes in three subcortical regions of the maternal brain: the hippocampus, amygdala, and ventral diencephalon. Twenty-four participants underwent longitudinal structural magnetic resonance imaging at 2-4 weeks and 1 year postpartum. Cortical thickness increased from early to one-year postpartum in the left (p = .003, Bonferroni corrected) and right (p = .02, Bonferroni corrected) superior frontal gyrus. No significant increases (or decreases) were observed in these regions for surface area. Volumetric increases, across the postpartum period, were found in the left amygdala (p = .001, Bonferroni corrected) and right ventral diencephalon (p = .01, Bonferroni corrected). An exploratory analysis of depressive symptoms found reductions in depressive symptoms from early postpartum to one-year postpartum were associated with greater cortical thickness in the superior frontal gyrus for both the left (p = .02) and right (p = .02) hemispheres. The findings expand our evidence of the neuroanatomical changes that occur across the postpartum period in humans and motivate future studies to examine how mood changes across this period are associated with cortical thickness of the superior frontal gyrus.

Multiple Stressors Induce Amygdalohippocampal Volume Reduction in Adult Male Rats as Detected by Longitudinal Structural Magnetic Resonance Imaging

BackgroundTraumatic events can cause long-lasting and uncontrollable fear and anxiety. Posttraumatic stress disorder is an intractable mental disorder, and neurobiological mechanisms using animal models are expected to help development of posttraumatic stress disorder treatment. In this study, we combined multiple stress (MS) and longitudinal in vivo magnetic resonance imaging to reveal the effects of long-lasting anxiety-like behaviors on adult male rat brains. MethodsTwelve male Wistar rats (8 weeks old) were exposed to the MS of 1-mA footshocks and forced swimming, while 12 control rats were placed in a plastic cage. Contextual fear conditioning with 0.1-mA footshocks in a context different from the MS was conducted 15 days after the MS for both groups. Three retention tests were administered after 24 hours and 9 and 16 days. Two magnetic resonance imaging scans were conducted, one on the day before MS induction and one the day after the third retention test, with a 32-day interval. ResultsThe MS group showed greater freezing responses than the control group in all retention tests. Whole-brain voxel-based morphometry analyses revealed reduced gray matter volume in the anterior amygdalohippocampal area in MS group rats compared with control rats. These volume changes were negatively associated with freezing time in the third retention test in the MS group. ConclusionsThese results suggest that individual variability in the amygdalohippocampal area may be related to long-lasting fear responses after severe stress.

Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach.

The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points. To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach. We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline. We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G > T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neurons and plays a role in controlling cell growth and differentiation. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Our deep learning model effectively extracted relevant neuroimaging features and predicted individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene.

Aberrant Hippocampal Development in Early-onset Mental Disorders and Promising Interventions: Evidence from a Translational Study

Early-onset mental disorders are associated with disrupted neurodevelopmental processes during adolescence. The methylazoxymethanol acetate (MAM) animal model, in which disruption in neurodevelopmental processes is induced, mimics the abnormal neurodevelopment associated with early-onset mental disorders from an etiological perspective. We conducted longitudinal structural magnetic resonance imaging (MRI) scans during childhood, adolescence, and adulthood in MAM rats to identify specific brain regions and critical windows for intervention. Then, the effect of repetitive transcranial magnetic stimulation (rTMS) intervention on the target brain region during the critical window was investigated. In addition, the efficacy of this intervention paradigm was tested in a group of adolescent patients with early-onset mental disorders (diagnosed with major depressive disorder or bipolar disorder) to evaluate its clinical translational potential. The results demonstrated that, compared to the control group, the MAM rats exhibited significantly lower striatal volume from childhood to adulthood (all P <0.001). In contrast, the volume of the hippocampus did not show significant differences during childhood (P >0.05) but was significantly lower than the control group from adolescence to adulthood (both P <0.001). Subsequently, rTMS was applied to the occipital cortex, which is anatomically connected to the hippocampus, in the MAM models during adolescence. The MAM-rTMS group showed a significant increase in hippocampal volume compared to the MAM-sham group (P <0.01), while the volume of the striatum remained unchanged (P >0.05). In the clinical trial, adolescents with early-onset mental disorders showed a significant increase in hippocampal volume after rTMS treatment compared to baseline (P <0.01), and these volumetric changes were associated with improvement in depressive symptoms (r = − 0.524, P = 0.018). These findings highlight the potential of targeting aberrant hippocampal development during adolescence as a viable intervention for early-onset mental disorders with neurodevelopmental etiology as well as the promise of rTMS as a therapeutic approach for mitigating aberrant neurodevelopmental processes and alleviating clinical symptoms.

Hypergraph convolutional network for longitudinal data analysis in Alzheimer's disease

Alzheimer's disease (AD) is an irreversible and progressive neurodegenerative disease. Longitudinal structural magnetic resonance imaging (sMRI) data have been widely used for tracking AD pathogenesis and diagnosis. However, existing methods tend to treat each time point equally without considering the temporal characteristics of longitudinal data. In this paper, we propose a weighted hypergraph convolution network (WHGCN) to use the internal correlations among different time points and leverage high-order relationships between subjects for AD detection. Specifically, we construct hypergraphs for sMRI data at each time point using the K-nearest neighbor (KNN) method to represent relationships between subjects, and then fuse the hypergraphs according to the importance of the data at each time point to obtain the final hypergraph. Subsequently, we use hypergraph convolution to learn high-order information between subjects while performing feature dimensionality reduction. Finally, we conduct experiments on 518 subjects selected from the Alzheimer's disease neuroimaging initiative (ADNI) database, and the results show that the WHGCN can get higher AD detection performance and has the potential to improve our understanding of the pathogenesis of AD.

Changes in gray matter volume following electroconvulsive therapy in adolescent depression with suicidal ideation: A longitudinal structural magnetic resonance imaging study.

ObjectiveWe aimed to investigate changes in whole-brain gray matter volumes (GMVs) before and after electroconvulsive therapy (ECT) in adolescents with major depressive disorder (MDD) and suicidal ideation (SI).MethodsThirty adolescents with MDD and SI were observed, and structural magnetic resonance imaging (sMRI) was performed at baseline and after ECT for each patient. But Twenty-five healthy controls (HCs) were scanned only at baseline. The voxel-based morphometry (VBM) techniques were used to examine GMVs.ResultsCompared with HCs, MDDs at baseline showed decreased GMVs in the left middle temporal gyrus, right superior temporal gyrus, right middle temporal gyrus, left precuneus, right precuneus, and left superior frontal gyrus. After ECT, MDDs showed increased GMVs in the right superior frontal gyrus and right superior temporal gyrus. Pearson’s correlation found that Beck Scale for Suicide Ideation (BSSI) scores at baseline were negatively correlated with GMVs in the left superior frontal gyrus and HAMD and BSSI scores after ECT were negatively correlated with GMVs in the right superior temporal gyrus.ConclusionFrontal–temporal–precuneus structure changes may be a potential cause of depressive and suicidal symptoms in adolescents. ECT may improve depressive and suicidal symptoms in adolescents by regulating brain structures to compensate original defects.

Longitudinal Structural MRI Data Prediction in Nondemented and Demented Older Adults via Generative Adversarial Convolutional Network

Alzheimer’s disease (AD) is the most common cause of dementia and threatens the health of millions of people. Early stage diagnosis of AD is critical for improving clinical outcomes and longitudinal magnetic resonance imaging (MRI) data collection can be used to monitor the progress of each patient. However, missing data is a common problem in longitudinal AD studies. The main factors come from subject dropouts and failed scans. This hinders the acquisition of longitudinal sequences that consist of multi-time-point magnetic resonance (MR) images at relatively uniform intervals. In this paper, we present a generative adversarial convolutional network to predict missing structural MRI data. In particular, we include multiple MRI scans as a temporal sequence collected at different times and determine the spatio-temporal relationship between the different scans in the proposed network. We adopt residual bottlenecks in the generator to decrease parameter values and deepen the network. In order to make full use of the longitudinal information, our discriminator classifies not only real MR images from generated MR images, but also fake sequences from real sequences in which the longitudinal MR images for all time points come from the dataset, only the last MR image comes from the generator. Results of our experiment show that our method performs more accurately for the longitudinal structural MRI data prediction of a brain afflicted with AD.

Alcohol's effects on the mouse brain are modulated by age and sex.

Binge alcohol consumption is common among adolescents and may impair normal brain development. Emerging, longitudinal studies in adolescents suggest that the effects of binge alcohol exposure on brain structure differ between sexes. To test the hypothesis that the effects of binge alcohol exposure on developmental brain growth trajectories are influenced by age of exposure and sex, adolescent and adult, male and female C57Bl/6 mice (n = 32), were exposed to a binge‐like ethanol (EtOH) exposure paradigm (i.e., 5 cycles of 2 on/2 off days of 5 g/kg EtOH intraperitoneal) or served as saline controls. Longitudinal structural magnetic resonance imaging was acquired at baseline, following binge EtOH exposure, and after 2 weeks of recovery. Alcohol treatment showed interactions with age and sex in altering whole brain volume: adolescents of both sexes demonstrated inhibited whole brain growth relative to their control counterparts, although significance was only attained in female mice which showed a larger magnitude response to EtOH compared to male mice. In region of interest analyses, the somatosensory cortex and cerebellum showed inhibited growth in male and female adolescent mice exposed to EtOH, but the difference relative to controls did not reach multiple comparison‐corrected statistical significance. These data suggest that in mice exposed to binge EtOH treatment, adolescent age of exposure and female sex may confer a higher risk to the detrimental effects of EtOH on brain structure and reinforce the need for direct testing of both sexes.

Dynamic Relationship Between Interhemispheric Functional Connectivity and Corticospinal Tract Changing Pattern After Subcortical Stroke

Background and PurposeIncreased interhemispheric resting-state functional connectivity (rsFC) between the bilateral primary motor cortex (M1) compensates for corticospinal tract (CST) impairment, which facilitates motor recovery in chronic subcortical stroke. However, there is a lack of data on the evolution patterns and correlations between M1–M1 rsFC and diffusion indices of CSTs with different origins after subcortical stroke and their relations with long-term motor outcomes.MethodsA total of 44 patients with subcortical stroke underwent longitudinal structural and functional magnetic resonance imaging (MRI) examinations and clinical assessments at four time points. Diffusion tensor imaging was used to extract fractional anisotropy (FA) values of the affected CSTs with different origins. Resting-state functional MRI was used to calculate the M1–M1 rsFC. Longitudinal patterns of functional and anatomic changes in connections were explored using a linear mixed-effects model. Dynamic relationships between M1–M1 rsFC and FA values of the affected specific CSTs and the impact of these variations on the long-term motor outcomes were analyzed in patients with subcortical stroke.ResultsStroke patients showed a significantly decreased FA in the affected specific CSTs and a gradually increasing M1–M1 rsFC from the acute to the chronic stage. The FA of the affected M1 fiber was negatively correlated with the M1–M1 rsFC from the subacute to the chronic stage, FA of the affected supplementary motor area fiber was negatively correlated with the M1–M1 rsFC in the subacute stage, and FA of the affected M1 fiber in the acute stage was correlated with the long-term motor recovery after subcortical stroke.ConclusionOur findings show that the FA of the affected M1 fiber in the acute stage had the most significant correlation with long-term motor recovery and may be used as an imaging biomarker for predicting motor outcomes after stroke. The compensatory role of the M1–M1 rsFC enhancement may start from the subacute stage in stroke patients with CST impairment.

Cortical Thickness Changes After Computerized Working Memory Training in Patients With Mild Cognitive Impairment.

BackgroundAdaptive computerized working memory (WM) training has shown favorable effects on cerebral cortical thickness as compared to non-adaptive training in healthy individuals. However, knowledge of WM training-related morphological changes in mild cognitive impairment (MCI) is limited.ObjectiveThe primary objective of this double-blind randomized study was to investigate differences in longitudinal cortical thickness trajectories after adaptive and non-adaptive WM training in patients with MCI. We also investigated the genotype effects on cortical thickness trajectories after WM training combining these two training groups using longitudinal structural magnetic resonance imaging (MRI) analysis in Freesurfer.MethodMagnetic resonance imaging acquisition at 1.5 T were performed at baseline, and after four- and 16-weeks post training. A total of 81 individuals with MCI accepted invitations to undergo 25 training sessions over 5 weeks. Longitudinal Linear Mixed effect models investigated the effect of adaptive vs. non-adaptive WM training. The LME model was fitted for each location (vertex). On all statistical analyzes, a threshold was applied to yield an expected false discovery rate (FDR) of 5%. A secondary LME model investigated the effects of LMX1A and APOE-ε4 on cortical thickness trajectories after WM training.ResultsA total of 62 participants/patients completed the 25 training sessions. Structural MRI showed no group difference between the two training regimes in our MCI patients, contrary to previous reports in cognitively healthy adults. No significant structural cortical changes were found after training, regardless of training type, across all participants. However, LMX1A-AA carriers displayed increased cortical thickness trajectories or lack of decrease in two regions post-training compared to those with LMX1A-GG/GA. No training or training type effects were found in relation to the APOE-ε4 gene variants.ConclusionThe MCI patients in our study, did not have improved cortical thickness after WM training with either adaptive or non-adaptive training. These results were derived from a heterogeneous population of MCI participants. The lack of changes in the cortical thickness trajectory after WM training may also suggest the lack of atrophy during this follow-up period. Our promising results of increased cortical thickness trajectory, suggesting greater neuroplasticity, in those with LMX1A-AA genotype need to be validated in future trials.

Mapping cerebral atrophic trajectory from amnestic mild cognitive impairment to Alzheimer's disease.

Alzheimer's disease (AD) patients suffer progressive cerebral atrophy before dementia onset. However, the region-specific atrophic processes and the influences of age and apolipoprotein E (APOE) on atrophic trajectory are still unclear. By mapping the region-specific nonlinear atrophic trajectory of whole cerebrum from amnestic mild cognitive impairment (aMCI) to AD based on longitudinal structural magnetic resonance imaging data from Alzheimer's disease Neuroimaging Initiative (ADNI) database, we unraveled a quadratic accelerated atrophic trajectory of 68 cerebral regions from aMCI to AD, especially in the superior temporal pole, caudate, and hippocampus. Besides, interaction analyses demonstrated that APOE ε4 carriers had faster atrophic rates than noncarriers in 8 regions, including the caudate, hippocampus, insula, etc.; younger patients progressed faster than older patients in 32 regions, especially for the superior temporal pole, hippocampus, and superior temporal gyrus; and 15 regions demonstrated complex interaction among age, APOE, and disease progression, including the caudate, hippocampus, etc. (P < 0.05/68, Bonferroni correction). Finally, Cox proportional hazards regression model based on the identified region-specific biomarkers could effectively predict the time to AD conversion within 10years. In summary, cerebral atrophic trajectory mapping could help a comprehensive understanding of AD development and offer potential biomarkers for predicting AD conversion.

The latent factor structure underlying regional brain volume change and its relation to cognitive change in older adults.

Late-life changes in cognition and brain integrity are both highly multivariate, time-dependent processes that are essential for understanding cognitive aging and neurodegenerative disease outcomes. The present study seeks to identify a latent variable model capable of efficiently reducing a multitude of structural brain change magnetic resonance imaging (MRI) measurements into a smaller number of dimensions. We further seek to demonstrate the validity of this model by evaluating its ability to reproduce patterns of coordinated brain volume change and to explain the rate of cognitive decline over time. We used longitudinal cognitive data and structural MRI scans, obtained from a diverse sample of 358 participants (Mage = 74.81, SD = 7.17), to implement latent variable models for measuring brain change and to estimate the effects of these brain change factors on cognitive decline. Results supported a bifactor model for brain change with four group factors (prefrontal, temporolimbic, medial temporal, and posterior association) and one general change factor (global atrophy). Atrophy in the global (β = 0.434, SE = 0.070), temporolimbic (β = 0.275, SE = 0.085), and medial temporal (β = 0.240, SE = 0.085) factors were the strongest predictors of global cognitive decline. Overall, the brain change model explained 59% of the variance in global cognitive slope. The current results suggest that brain change across 27 bilateral regions of interest can be grouped into five change factors, three of which (global gray matter, temporolimbic, and medial temporal lobe atrophy) are strongly associated with cognitive decline. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Divergent effects of irradiation on brain cortical morphology in patients with nasopharyngeal carcinoma: one-year follow-up study using structural magnetic resonance imaging.

Increasing evidence indicates that radiotherapy (RT)-induced brain cortical deficits may play a critical role in developing radiation encephalopathy in patients with nasopharyngeal carcinoma (NPC). However, the evolutional processes of RT-induced cortical injury have not been sufficiently investigated. This study investigates RT-induced effects on cortical morphology using longitudinal structural magnetic resonance imaging (MRI) in NPC patients. Using MRI-based morphometry with surface-based measures, we evaluated the longitudinal alterations of cortical volume (CV), cortical thickness (CT), and cortical surface area (CSA) in 104 NPC patients at pre-RT (n=104), within 3 months post-RT (n=92), 6 months post-RT (n=71), and 9-12 months post-RT (n=52). Twenty healthy controls were also evaluated in parallel. Linear mixed models were used to investigate the trajectories of RT-related changes in cortical brain morphology and its association with irradiation dose, with healthy controls data being used to construct a normal age-related benchmark. The level of statistical significance was set at P<0.05, corrected for multiple comparisons. The results showed that RT-related longitudinal alterations in cortical morphology underwent two diverse patterns during the first year of follow up in NPC patients. The temporal cortices (including the bilateral superior temporal gyrus, middle temporal gyrus, temporal pole, parahippocampal and fusiform gyrus, and the right inferior temporal and right transverse temporal gyrus), the basal occipital cortices (the right lingual gyrus and lateral occipital gyrus), and the basal frontal cortices (the right lateral orbitofrontal gyrus) showed time-dependent attenuation in cortical morphology indices. Furthermore, these effects on multiple cortices were dose-dependent, suggesting they were RT-associated. In contrast, in the left rostral middle frontal gyrus, there was a time-dependent increase in CT. Our preliminary findings revealed divergent effects of irradiation on cortical brain morphology. These results contribute to a more comprehensive understanding of the underlying neural mechanisms of irradiation-related neurotoxic effects on cortical brain morphology and will help guide the investigation of critically neuroprotective strategies.

Structural, Functional, and Molecular Imaging of Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder associated with both genetic and environmental risks. Neuroimaging approaches have been widely employed to parse the neurophysiological mechanisms underlying ASD, and provide critical insights into the anatomical, functional, and neurochemical changes. We reviewed recent advances in neuroimaging studies that focused on ASD by using magnetic resonance imaging (MRI), positron emission tomography (PET), or single-positron emission tomography (SPECT). Longitudinal structural MRI has delineated an abnormal developmental trajectory of ASD that is associated with cascading neurobiological processes, and functional MRI has pointed to disrupted functional neural networks. Meanwhile, PET and SPECT imaging have revealed that metabolic and neurotransmitter abnormalities may contribute to shaping the aberrant neural circuits of ASD. Future large-scale, multi-center, multimodal investigations are essential to elucidate the neurophysiological underpinnings of ASD, and facilitate the development of novel diagnostic biomarkers and better-targeted therapy.

Early or Late Gestational Exposure to Maternal Immune Activation Alters Neurodevelopmental Trajectories in Mice: An Integrated Neuroimaging, Behavioral, and Transcriptional Study

BackgroundExposure to maternal immune activation (MIA) in utero is a risk factor for neurodevelopmental disorders later in life. The impact of the gestational timing of MIA exposure on downstream development remains unclear. MethodsWe characterized neurodevelopmental trajectories of mice exposed to the viral mimetic poly I:C (polyinosinic:polycytidylic acid) either on gestational day 9 (early) or on day 17 (late) using longitudinal structural magnetic resonance imaging from weaning to adulthood. Using multivariate methods, we related neuroimaging and behavioral variables for the time of greatest alteration (adolescence/early adulthood) and identified regions for further investigation using RNA sequencing. ResultsEarly MIA exposure was associated with accelerated brain volume increases in adolescence/early adulthood that normalized in later adulthood in the striatum, hippocampus, and cingulate cortex. Similarly, alterations in anxiety-like, stereotypic, and sensorimotor gating behaviors observed in adolescence normalized in adulthood. MIA exposure in late gestation had less impact on anatomical and behavioral profiles. Multivariate maps associated anxiety-like, social, and sensorimotor gating deficits with volume of the dorsal and ventral hippocampus and anterior cingulate cortex, among others. The most transcriptional changes were observed in the dorsal hippocampus, with genes enriched for fibroblast growth factor regulation, autistic behaviors, inflammatory pathways, and microRNA regulation. ConclusionsLeveraging an integrated hypothesis- and data-driven approach linking brain-behavior alterations to the transcriptome, we found that MIA timing differentially affects offspring development. Exposure in late gestation leads to subthreshold deficits, whereas exposure in early gestation perturbs brain development mechanisms implicated in neurodevelopmental disorders.

A Bayesian latent spatial model for mapping the cortical signature of progression to Alzheimer's disease

Prior studies have shown that atrophy in vulnerable cortical regions is associated with an increased risk of progression to clinical dementia. In this work, we utilize the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to investigate the relationship between the temporally changing spatial topography of cortical thickness and conversion from mild cognitive impairment to Alzheimer's disease (AD). We develop a novel Bayesian latent spatial model that employs the spatial information underlying the thickness effects across the cortical surface. The proposed method facilitates the development of imaging markers by reliably quantifying and mapping the regional vulnerability to AD progression across the cortical surface. Simulation results showed substantial gains in statistical power and estimation performance by accounting for the spatial structure of the association. Using MRI data from ADNI, we examined the topographic patterns of anatomic regions where cortical thinning is associated with an increased risk of developing AD.

Irradiation-related longitudinal white matter atrophy underlies cognitive impairment in patients with nasopharyngeal carcinoma

To longitudinally investigate alterations in cerebral white matter volume as a function of irradiation dose and time after standard radiotherapy in nasopharyngeal carcinoma patients and to determine how these alterations are related to radiotherapy-associated neurocognitive dysfunction.A total of 120 nasopharyngeal carcinoma patients were included in the present study. Longitudinal structural magnetic resonance imaging was performed at pre-radiotherapy and 1-3, 6, and 9-12months post-radiotherapy. Twenty healthy controls were recruited and followed up with in parallel. Structural images were processed via FreeSurfer. The Montreal Cognitive Assessment was performed to evaluate cognitive function of the participants. Linear mixed models and general linear models were used to evaluate different trajectories and the relationship between white matter volume and cognition in patients and controls within approximately 12months of follow-up.Selective and time-dependent white matter atrophy was observed in the right parahippocampal gyrus, right inferior temporal gyrus, right middle temporal gyrus, right fusiform gyrus, and left insular cortex in post-radiotherapy patients compared to the controls. Moreover, radiotherapy-associated white matter atrophy in the right parahippocampal gyrus exhibited a dose-dependent pattern, whereas radiotherapy-associated white matter atrophy in the right inferior temporal gyrus was correlated with progressive cognitive impairment in patients.Taken together, our findings illustrate that white matter volume alterations can be used as a potential biomarker to detect radiotherapy-related subtle brain injury in nasopharyngeal carcinoma patients, which may help further elucidate the pathogenesis of radiation-induced cognitive decline and facilitate studies on cognition-sparing radiotherapy.

Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression.

Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer’s disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathogenesis. We propose a framework for longitudinal clustering that simultaneously: 1) incorporates whole brain data, 2) leverages unequal visits per individual, 3) compares clusters with a control group, 4) allows for study confounding effects, 5) provides cluster visualization, 6) measures clustering uncertainty. We used amyloid-β positive AD and negative healthy subjects, three longitudinal structural magnetic resonance imaging scans (cortical thickness and subcortical volume) over two years. We found three distinct longitudinal AD brain atrophy patterns: one typical diffuse pattern (n=34, 47.2%), and two atypical patterns: minimal atrophy (n=23 31.9%) and hippocampal sparing (n=9, 12.5%). We also identified outliers (n=3, 4.2%) and observations with uncertain classification (n=3, 4.2%). The clusters differed not only in regional distributions of atrophy at baseline, but also longitudinal atrophy progression, age at AD onset, and cognitive decline. A framework for the longitudinal assessment of variability in cohorts with several neuroimaging measures was successfully developed. We believe this framework may aid in disentangling distinct subtypes of AD from disease staging.

Leptin predicts cortical and subcortical gray matter volume recovery in alcohol dependent patients: A longitudinal structural magnetic resonance imaging study

The neuroprotective effects of leptin and its role in addictive disorders has been highlighted by several recent studies. However, its potential effects on morphological alterations in alcohol dependence are yet to be investigated.Associations between leptin and the longitudinal courses of gray matter volume (GMV) and cortical thickness (CT) were investigated in N = 62 alcohol-dependent patients that underwent structural magnetic resonance imaging after a mean abstinence of 12 (baseline) and 27 days (follow-up) respectively. Blood samples were collected at baseline to determine leptin levels. A cohort of N = 74 healthy individuals served as a reference sample.At baseline, alcohol-dependent patients compared to healthy controls displayed smaller GMV in the insula, parts of the superior, middle and inferior frontal gyri and hippocampal regions and thinner CT in the insula, parts of the superior and middle frontal cortices, the lateral orbitofrontal cortex and parts of the occipital and lingual cortices that partially recovered during abstinence (pFWE < 0.05). In alcohol-dependent patients, leptin was a significant predictor of GMV and CT recovery in the areas that showed the strongest whole-brain effects, specifically GMV in the right insula (R2 = 0.070, pFDR = 0.040) and left inferior frontal triangular gyrus (R2 = 0.076, pFDR = 0.040), as well as CT in the left insula (R2 = 0.158, pFDR = 0.004) and right superior frontal cortex (R2 = 0.180, pFDR = 0.004). Present results support the role of leptin in predicting GMV and CT recovery during the first month of abstinence in alcohol-dependent patients.