Indirect structural changes and reduced controllability after temporal lobe epilepsy resection.

OBJECTIVE: To understand the potential behavioral and cognitive effects of mesial temporal resection for temporal lobe epilepsy (TLE) a method is required to characterize network-wide functional alterations caused by a discrete structural disconnection. The objective of this study was to investigate network-wide alterations in brain dynamics of patients with TLE before and after surgical resection of the seizure focus using average regional controllability (ARC), a measure of the ability of a node to influence network dynamics. METHODS: Diffusion-weighted imaging (DWI) data were acquired in 27 patients with drug-resistant unilateral mesial TLE who underwent selective amygdalohippocampectomy. Imaging data were acquired before and after surgery and a presurgical and postsurgical structural connectome was generated from whole-brain tractography. Edge-wise strength, node strength, and node ARC were compared before and after surgery. Direct and indirect edge-wise strength changes were identified using patient-specific simulated resections. Direct edges were defined as primary edges disconnected by the resection zone itself. Indirect edges were secondary measured edge strength changes. Changes in node strength and ARC were then related to both direct and indirect edge changes. RESULTS: We found nodes with significant postsurgical changes in both node strength and ARC surrounding the resection zone (paired t tests, p < .05, Bonferroni corrected). ARC identified additional postsurgical changes in nodes outside of the resection zone within the ipsilateral occipital lobe, which were associated with indirect edge-wise strength changes of the postsurgical network (Fisher's exact test, p < .001). These indirect edge-wise changes were facilitated through the "hub" nodes including the thalamus, putamen, insula, and precuneus. SIGNIFICANCE: Discrete network disconnection from TLE resection results in widespread structural and functional changes not predicted by disconnection alone. These can be well characterized by dynamic controllability measures such as ARC and may be useful for investigating changes in brain function that may contribute to seizure recurrence and behavioral or cognitive changes after surgery.

Structural disconnection relates to functional changes after temporal lobe epilepsy surgery.

Epilepsy surgery consists of surgical resection of the epileptic focus and is recommended for patients with drug-resistant focal epilepsy. However, focal brain lesions can lead to effects in distant brain regions. Similarly, the focal resection in temporal lobe epilepsy surgery has been shown to lead to functional changes distant from the resection. Here we hypothesize that there are changes in brain function caused by temporal lobe epilepsy surgery in regions distant from the resection that are due to their structural disconnection from the resected epileptic focus. Therefore, the goal of this study was to localize changes in brain function caused by temporal lobe epilepsy surgery and relate them to the disconnection from the resected epileptic focus. This study takes advantage of the unique opportunity that epilepsy surgery provides to investigate the effects of focal disconnections on brain function in humans, which has implications in epilepsy and broader neuroscience. Changes in brain function from pre- to post-epilepsy surgery were quantified in a group of temporal lobe epilepsy patients (n = 36) using a measure of resting state functional MRI activity fluctuations. We identified regions with significant functional MRI changes that had high structural connectivity to the resected region in healthy controls (n = 96) and patients based on diffusion MRI. The structural disconnection from the resected epileptic focus was then estimated using presurgical diffusion MRI and related to the functional MRI changes from pre- to post-surgery in these regions. Functional MRI activity fluctuations increased from pre- to post-surgery in temporal lobe epilepsy in the two regions most highly structurally connected to the resected epileptic focus in healthy controls and patients-the thalamus and the fusiform gyrus ipsilateral to the side of surgery (PFWE < 0.05). Broader surgeries led to larger functional MRI changes in the thalamus than more selective surgeries (P < 0.05), but no other clinical variables were related to functional MRI changes in either the thalamus or fusiform. The magnitude of the functional MRI changes in both the thalamus and fusiform increased with a higher estimated structural disconnection from the resected epileptic focus when controlling for the type of surgery (P < 0.05). These results suggest that the structural disconnection from the resected epileptic focus may contribute to the functional changes seen after epilepsy surgery. Broadly, this study provides a novel link between focal disconnections in the structural brain network and downstream effects on function in distant brain regions.

Functional alterations in bipartite network of white and grey matters during aging.

The effects of normal aging on functional connectivity (FC) within various brain networks of gray matter (GM) have been well-documented. However, the age effects on the networks of FC between white matter (WM) and GM, namely WM-GM FC, remains unclear. Evaluating crucial properties, such as global efficiency (GE), for a WM-GM FC network poses a challenge due to the absence of closed triangle paths which are essential for assessing network properties in traditional graph models. In this study, we propose a bipartite graph model to characterize the WM-GM FC network and quantify these challenging network properties. Leveraging this model, we assessed the WM-GM FC network properties at multiple scales across 1,462 cognitively normal subjects aged 22-96 years from three repositories (ADNI, BLSA and OASIS-3) and investigated the age effects on these properties throughout adulthood and during late adulthood (age ≥70 years). Our findings reveal that (1) heterogeneous alterations occurred in region-specific WM-GM FC over the adulthood and decline predominated during late adulthood; (2) the FC density of WM bundles engaged in memory, executive function and processing speed declined with age over adulthood, particularly in later years; and (3) the GE of attention, default, somatomotor, frontoparietal and limbic networks reduced with age over adulthood, and GE of visual network declined during late adulthood. These findings provide unpresented insights into multi-scale alterations in networks of WM-GM functional synchronizations during normal aging. Furthermore, our bipartite graph model offers an extendable framework for quantifying WM-engaged networks, which may contribute to a wide range of neuroscience research.

Increased microglia activation in late non-central nervous system cancer survivors links to chronic systemic symptomatology.

Prolonged inflammatory expression within the central nervous system (CNS) is recognized by the brain as a molecular signal of "sickness", that has knock-on effects to the blood-brain barrier, brain-spinal barrier, blood-cerebrospinal fluid barrier, neuro-axonal structures, neurotransmitter activity, synaptic plasticity, neuroendocrine function, and resultant systemic symptomatology. It is concurred that the inflammatory process associated with cancer and cancer treatments underline systemic symptoms present in a large portion of survivors, although this concept is largely theoretical from disparate and indirect evidence and/or clinical anecdotal reports. We conducted a proof-of-concept study to link for the first time late non-CNS cancer survivors presenting chronic systemic symptoms and the presence of centralized inflammation, or neuroinflammation, using TSPO-binding PET tracer [11 C]-PBR28 to visualize microglial activation. We compared PBR28 SUVR in 10 non-CNS cancer survivors and 10 matched healthy controls. Our data revealed (1) microglial activation was significantly higher in caudate, temporal, and occipital regions in late non-central nervous system/CNS cancer survivors compared to healthy controls; (2) increased neuroinflammation in cancer survivors was not accompanied by significant differences in plasma cytokine markers of peripheral inflammation; (3) increased neuroinflammation was not accompanied by reduced fractional anisotropy, suggesting intact white matter microstructural integrity, a marker of neurovascular fiber tract organization; and (4) the presentation of chronic systemic symptoms in cancer survivors was significantly connected with microglial activation. We present the first data empirically supporting the concept of a peripheral-to-centralized inflammatory response in non-CNS cancer survivors, specifically those previously afflicted with head and neck cancer. Following resolution of the initial peripheral inflammation from the cancer/its treatments, in some cases damage/toxification to the central nervous system occurs, ensuing chronic systemic symptoms.

Anterior hippocampal dysfunction in early psychosis: a 2-year follow-up study.

BACKGROUND: Cross-sectional studies indicate that hippocampal function is abnormal across stages of psychosis. Neural theories of psychosis pathophysiology suggest that dysfunction worsens with illness stage. Here, we test the hypothesis that hippocampal function is impaired in the early stage of psychosis and declines further over the next 2 years. METHODS: We measured hippocampal function over 2 years using a scene processing task in 147 participants (76 individuals in the early stage of a non-affective psychotic disorder and 71 demographically similar healthy control individuals). Two-year follow-up was completed in 97 individuals (50 early psychosis, 47 healthy control). Voxelwise longitudinal analysis of activation in response to scenes was carried out within a hippocampal region of interest to test for group differences at baseline and a group by time interaction. RESULTS: At baseline, we observed lower anterior hippocampal activation in the early psychosis group relative to the healthy control group. Contrary to our hypothesis, hippocampal activation remained consistent and did not show the predicted decline over 2 years in the early psychosis group. Healthy controls showed a modest reduction in hippocampal activation after 2 years. CONCLUSIONS: The results of this study suggest that hippocampal dysfunction in early psychosis does not worsen over 2 years and highlight the need for longer-term longitudinal studies.

Sound Level Changes the Auditory Cortical Activation Detected with Functional Near-Infrared Spectroscopy.

BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is a viable non-invasive technique for functional neuroimaging in the cochlear implant (CI) population; however, the effects of acoustic stimulus features on the fNIRS signal have not been thoroughly examined. This study examined the effect of stimulus level on fNIRS responses in adults with normal hearing or bilateral CIs. We hypothesized that fNIRS responses would correlate with both stimulus level and subjective loudness ratings, but that the correlation would be weaker with CIs due to the compression of acoustic input to electric output. METHODS: Thirteen adults with bilateral CIs and 16 with normal hearing (NH) completed the study. Signal-correlated noise, a speech-shaped noise modulated by the temporal envelope of speech stimuli, was used to determine the effect of stimulus level in an unintelligible speech-like stimulus between the range of soft to loud speech. Cortical activity in the left hemisphere was recorded. RESULTS: Results indicated a positive correlation of cortical activation in the left superior temporal gyrus with stimulus level in both NH and CI listeners with an additional correlation between cortical activity and perceived loudness for the CI group. The results are consistent with the literature and our hypothesis. CONCLUSIONS: These results support the potential of fNIRS to examine auditory stimulus level effects at a group level and the importance of controlling for stimulus level and loudness in speech recognition studies. Further research is needed to better understand cortical activation patterns for speech recognition as a function of both stimulus presentation level and perceived loudness.

Characterization of resting functional MRI activity alterations across epileptic foci and networks.

Brain network alterations have been studied extensively in patients with mesial temporal lobe epilepsy (mTLE) and other focal epilepsies using resting-state functional magnetic resonance imaging (fMRI). However, little has been done to characterize the basic fMRI signal alterations caused by focal epilepsy. Here, we characterize how mTLE affects the fMRI signal in epileptic foci and networks. Resting-state fMRI and diffusion MRI were collected from 47 unilateral mTLE patients and 96 healthy controls. FMRI activity, quantified by amplitude of low-frequency fluctuations, was increased in the epileptic focus and connected regions in mTLE. Evidence for spread of this epileptic fMRI activity was found through linear relationships of regional activity across subjects, the association of these relationships with functional connectivity, and increased activity along white matter tracts. These fMRI activity increases were found to be dependent on the epileptic focus, where the activity was related to disease severity, suggesting the focus to be the origin of these pathological alterations. Furthermore, we found fMRI activity decreases in the default mode network of right mTLE patients with different properties than the activity increases found in the epileptic focus. This work provides insights into basic fMRI signal alterations and their potential spread across networks in focal epilepsy.

Interindividual Signatures of fMRI Temporal Fluctuations.

The complexity and variability of human brain activity, such as quantified from Functional Magnetic Resonance Imaging (fMRI) time series, have been widely studied as potential markers of healthy and pathological states. However, the extent to which fMRI temporal features exhibit stable markers of inter-individual differences in brain function across healthy young adults is currently an open question. In this study, we draw upon two widely used time-series measures-a nonlinear complexity measure (sample entropy; SampEn) and a spectral measure of low-frequency content (fALFF)-to capture dynamic properties of resting-state fMRI in a large sample of young adults from the Human Connectome Project. We observe that these two measures are closely related, and that both generate reproducible patterns across brain regions over four different fMRI runs, with intra-class correlations of up to 0.8. Moreover, we find that both metrics can uniquely differentiate subjects with high identification rates (ca. 89%). Canonical correlation analysis revealed a significant relationship between multivariate brain temporal features and behavioral measures. Overall, these findings suggest that regional profiles of fMRI temporal characteristics may provide stable markers of individual differences, and motivate future studies to further probe relationships between fMRI time series metrics and behavior.

Integrating the BIDS Neuroimaging Data Format and Workflow Optimization for Large-Scale Medical Image Analysis.

A robust medical image computing infrastructure must host massive multimodal archives, perform extensive analysis pipelines, and execute scalable job management. An emerging data format standard, the Brain Imaging Data Structure (BIDS), introduces complexities for interfacing with XNAT archives. Moreover, workflow integration is combinatorically problematic when matching large amount of processing to large datasets. Historically, workflow engines have been focused on refining workflows themselves instead of actual job generation. However, such an approach is incompatible with data centric architecture that hosts heterogeneous medical image computing. Distributed automation for XNAT toolkit (DAX) provides large-scale image storage and analysis pipelines with an optimized job management tool. Herein, we describe developments for DAX that allows for integration of XNAT and BIDS standards. We also improve DAX's efficiencies of diverse containerized workflows in a high-performance computing (HPC) environment. Briefly, we integrate YAML configuration processor scripts to abstract workflow data inputs, data outputs, commands, and job attributes. Finally, we propose an online database-driven mechanism for DAX to efficiently identify the most recent updated sessions, thereby improving job building efficiency on large projects. We refer the proposed overall DAX development in this work as DAX-1 (DAX version 1). To validate the effectiveness of the new features, we verified (1) the efficiency of converting XNAT data to BIDS format and the correctness of the conversion using a collection of BIDS standard containerized neuroimaging workflows, (2) how YAML-based processor simplified configuration setup via a sequence of application pipelines, and (3) the productivity of DAX-1 on generating actual HPC processing jobs compared with earlier DAX baseline method. The empirical results show that (1) DAX-1 converting XNAT data to BIDS has similar speed as accessing XNAT data only; (2) YAML can integrate to the DAX-1 with shallow learning curve for users, and (3) DAX-1 reduced the job/assessor generation latency by finding recent modified sessions. Herein, we present approaches for efficiently integrating XNAT and modern image formats with a scalable workflow engine for the large-scale dataset access and processing.

Characterizing effects of age, sex and psychosis symptoms on thalamocortical functional connectivity in youth.

The thalamus is composed of multiple nuclei densely connected with the cortex in an organized manner, forming parallel thalamocortical networks critical to sensory, motor, and cognitive functioning. Thalamocortical circuit dysfunction has been implicated in multiple neurodevelopmental disorders, including schizophrenia, which also often exhibit sex differences in prevalence, clinical characteristics, and neuropathology. However, very little is known about developmental and sex effects on thalamocortical networks in youth. The present study characterized the effects of age, sex and psychosis symptomatology in anatomically constrained thalamocortical networks in a large community sample of youth (n = 1100, aged 8-21) from the Philadelphia Neurodevelopmental Cohort (PNC). Cortical functional connectivity of seven anatomically defined thalamic nuclear groups were examined: anterior, mediodorsal, ventral lateral, ventral posterolateral, pulvinar, medial and lateral geniculate nuclear groups. Age and sex effects were characterized using complementary thalamic region-of-interest (ROI) to cortical ROI and voxel-wise analyses. Effects of clinical symptomatology were analyzed by separating youth into three groups based on their clinical symptoms; typically developing youth (n = 298), psychosis spectrum youth (n = 320), and youth with other psychopathologies (n = 482). As an exploratory analysis, association with PRIME scores were used as a dimensional measure of psychopathology. Age effects were broadly characterized by decreasing connectivity with sensory/motor cortical areas, and increasing connectivity with heteromodal prefrontal and parietal cortical areas. This pattern was most pronounced for thalamic motor and sensory nuclei. Females showed greater connectivity between multiple thalamic nuclear groups and the visual cortex compared to males, while males showed greater connectivity with the inferior frontal and orbitofrontal cortices. Youth with psychosis spectrum symptoms showed a subtle decrease in thalamic connectivity with the premotor and prefrontal cortices. Across all youth, greater PRIME scores were associated with lower connectivity between the prefrontal cortex and mediodorsal thalamus. By characterizing typical development in anatomically constrained thalamocortical networks, this study provides an anchor for conceptualizing disruptions to the integrity of these networks observed in neurodevelopmental disorders.

PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images.

PURPOSE: Diffusion weighted MRI imaging (DWI) is often subject to low signal-to-noise ratios (SNRs) and artifacts. Recent work has produced software tools that can correct individual problems, but these tools have not been combined with each other and with quality assurance (QA). A single integrated pipeline is proposed to perform DWI preprocessing with a spectrum of tools and produce an intuitive QA document. METHODS: The proposed pipeline, built around the FSL, MRTrix3, and ANTs software packages, performs DWI denoising; inter-scan intensity normalization; susceptibility-, eddy current-, and motion-induced artifact correction; and slice-wise signal drop-out imputation. To perform QA on the raw and preprocessed data and each preprocessing operation, the pipeline documents qualitative visualizations, quantitative plots, gradient verifications, and tensor goodness-of-fit and fractional anisotropy analyses. RESULTS: Raw DWI data were preprocessed and quality checked with the proposed pipeline and demonstrated improved SNRs; physiologic intensity ratios; corrected susceptibility-, eddy current-, and motion-induced artifacts; imputed signal-lost slices; and improved tensor fits. The pipeline identified incorrect gradient configurations and file-type conversion errors and was shown to be effective on externally available datasets. CONCLUSIONS: The proposed pipeline is a single integrated pipeline that combines established diffusion preprocessing tools from major MRI-focused software packages with intuitive QA.

Resting-state hippocampal networks related to language processing reveal unique patterns in temporal lobe epilepsy.

OBJECTIVE: Patients with temporal lobe epilepsy (TLE) commonly experience a broad range of language impairments. These deficits are thought to arise from repeated seizure activity that damages language regions. However, connectivity between the seizure onset region in the hippocampus and regions related to language processing has rarely been studied, and could also have a strong impact on language function. The purpose of this study was to use resting-state functional connectivity (FC) measures to assess hippocampal network patterns and their relation to language abilities in patients with right TLE (RLTE), left TLE (LTLE), and healthy controls. METHODS: Presurgical resting-state 3T functional MRI data were acquired from 40 patients with mesial TLE (27 RTLE, 13 LTLE) and 54 controls. The regions of interest were the anterior and posterior bilateral hippocampi and eleven regions grouped by frontal or temporo-parietal locations, including large areas of language-related cortex. FC values were computed with the right/left anterior and posterior hippocampi as the seeds and frontal and temporo-parietal regions as targets. Resting-state lateralization indices were also calculated (LI-Rest), and all FC measures were correlated to neuropsychological language scores and measures related to manifestation of epilepsy including age of onset, duration of disease, monthly seizure frequency, and hippocampal volume. RESULTS: We found significant group differences between the anterior hippocampi and temporo-parietal regions closest to the seizure focus, in which RTLE and LTLE showed stronger connectivity to their contralateral hippocampus, while controls showed similar connectivity to both hippocampi. In addition, LI-Rest demonstrated significantly more right lateralization in LTLE compared to RTLE for temporo-parietal regions only. In LTLE, we found significant associations between stronger hippocampal network resting-state FC and later age of onset and decreased left anterior hippocampal volume. SIGNIFICANCE: The results of our study indicate that the presence of TLE impacts hippocampal-temporo-parietal networks relevant to language processing.

Detection of synchronous brain activity in white matter tracts at rest and under functional loading.

Functional MRI based on blood oxygenation level-dependent (BOLD) contrast is well established as a neuroimaging technique for detecting neural activity in the cortex of the human brain. While detection and characterization of BOLD signals, as well as their electrophysiological and hemodynamic/metabolic origins, have been extensively studied in gray matter (GM), the detection and interpretation of BOLD signals in white matter (WM) remain controversial. We have previously observed that BOLD signals in a resting state reveal structure-specific anisotropic temporal correlations in WM and that external stimuli alter these correlations and permit visualization of task-specific fiber pathways, suggesting variations in WM BOLD signals are related to neural activity. In this study, we provide further strong evidence that BOLD signals in WM reflect neural activities both in a resting state and under functional loading. We demonstrate that BOLD signal waveforms in stimulus-relevant WM pathways are synchronous with the applied stimuli but with various degrees of time delay and that signals in WM pathways exhibit clear task specificity. Furthermore, resting-state signal fluctuations in WM tracts show significant correlations with specific parcellated GM volumes. These observations support the notion that neural activities are encoded in WM circuits similarly to cortical responses.

Inhalable Thioflavin S for the Detection of Amyloid Beta Deposits in the Retina.

We present an integrated delivery technology herein employing the aerosolized method to repurpose thioflavin S for imaging amyloid beta (Abeta) deposits in the retina as a surrogate of Abeta in the brain for early detection of Alzheimer's disease. The data showed that wild type (WT) mice also have Abeta deposits in the retinae, albeit much less than 5XFAD mice. Further, only in 5XFAD mice, significant Abeta deposits were found associated with retinal ganglion cells (RGCs) in whole-mount and cross-section data. Furthermore, the fluorescent signal depicted from thioflavin S corroborates with Abeta immunohistochemistry staining information. Overall, this probe delivery via inhalation method is also applicable to other Abeta-binding molecules, such as Congo red, curcumin, and thioflavin T. The advantage of imaging retinal amyloid deposits compared to the brain counterparts is that the eye is easily accessible by in vivo imaging and it reduces the effort to design a probe that must cross the formidable blood-brain barrier.

7T quantitative magnetization transfer (qMT) of cortical gray matter in multiple sclerosis correlates with cognitive impairment.

Cognitive impairment (CI) is a major manifestation of multiple sclerosis (MS) and is responsible for extensively hindering patient quality of life. Cortical gray matter (cGM) damage is a significant contributor to CI, but is poorly characterized by conventional MRI let alone with quantitative MRI, such as quantitative magnetization transfer (qMT). Here we employed high-resolution qMT at 7T via the selective inversion recovery (SIR) method, which provides tissue-specific indices of tissue macromolecular content, such as the pool size ratio (PSR) and the rate of MT exchange (kmf). These indices could represent expected demyelination that occurs in the presence of gray matter damage. We utilized selective inversion recovery (SIR) qMT which provides a low SAR estimate of macromolecular-bulk water interactions using a tailored, B1 and B0 robust inversion recovery (IR) sequence acquired at multiple inversion times (TI) at 7T and fit to a two-pool model of magnetization exchange. Using this sequence, we evaluated qMT indices across relapsing-remitting multiple sclerosis patients (N = 19) and healthy volunteers (N = 37) and derived related associations with neuropsychological measures of cognitive impairment. We found a significant reduction in kmf in cGM of MS patients (15.5%, p = 0.002), unique association with EDSS (ρ = -0.922, p = 0.0001), and strong correlation with cognitive performance (ρ = -0.602, p = 0.0082). Together these findings indicate that the rate of MT exchange (kmf) may be a significant biomarker of cGM damage relating to CI in MS.

Multiple sclerosis lesions affect intrinsic functional connectivity of the spinal cord.

Patients with multiple sclerosis present with focal lesions throughout the spinal cord. There is a clinical need for non-invasive measurements of spinal cord activity and functional organization in multiple sclerosis, given the cord's critical role in the disease. Recent reports of spontaneous blood oxygenation level-dependent fluctuations in the spinal cord using functional MRI suggest that, like the brain, cord activity at rest is organized into distinct, synchronized functional networks among grey matter regions, likely related to motor and sensory systems. Previous studies looking at stimulus-evoked activity in the spinal cord of patients with multiple sclerosis have demonstrated increased levels of activation as well as a more bilateral distribution of activity compared to controls. Functional connectivity studies of brain networks in multiple sclerosis have revealed widespread alterations, which may take on a dynamic trajectory over the course of the disease, with compensatory increases in connectivity followed by decreases associated with structural damage. We build upon this literature by examining functional connectivity in the spinal cord of patients with multiple sclerosis. Using ultra-high field 7 T imaging along with processing strategies for robust spinal cord functional MRI and lesion identification, the present study assessed functional connectivity within cervical cord grey matter of patients with relapsing-remitting multiple sclerosis (n = 22) compared to a large sample of healthy controls (n = 56). Patient anatomical images were rated for lesions by three independent raters, with consensus ratings revealing 19 of 22 patients presented with lesions somewhere in the imaged volume. Linear mixed models were used to assess effects of lesion location on functional connectivity. Analysis in control subjects demonstrated a robust pattern of connectivity among ventral grey matter regions as well as a distinct network among dorsal regions. A gender effect was also observed in controls whereby females demonstrated higher ventral network connectivity. Wilcoxon rank-sum tests detected no differences in average connectivity or power of low frequency fluctuations in patients compared to controls. The presence of lesions was, however, associated with local alterations in connectivity with differential effects depending on columnar location. The patient results suggest that spinal cord functional networks are generally intact in relapsing-remitting multiple sclerosis but that lesions are associated with focal abnormalities in intrinsic connectivity. These findings are discussed in light of the current literature on spinal cord functional MRI and the potential neurological underpinnings.

Modelling the growth of popliteal artery aneurysms.

BACKGROUND: Popliteal artery aneurysms (PAAs) comprise up to 85 per cent of all peripheral aneurysms. Few longitudinal studies track their progression. This study aimed to track the growth of asymptomatic PAAs in a hospital-based ultrasound service, and compare models of aneurysm growth. METHODS: This retrospective single-centre cohort study included patients who had a PAA on arterial duplex ultrasound imaging of the lower limbs between 1 January 2011 and 1 January 2016. Progression of PAA size and progression to event or intervention were the primary outcome measures. RESULTS: Some 282 images were analysed: 47 limbs with PAA were included in a cohort of 32 patients (15 had bilateral PAAs). Twenty patients also had an abdominal aortic aneurysm (AAA). Linear multilevel modelling estimated that PAA growth was 2·4 (95 per cent c.i. 1·6 to 3·7) mm a year. Growth was estimated at 0·8 (0·1 to 1·5) mm per year in patients without an AAA and 3·5 (2·9 to 4·2) mm per year in those with a known AAA (previous open repair, previous endovascular aneurysm repair or AAA under surveillance) (P < 0·001). CONCLUSION: Growth rates of PAA were heterogeneous but were optimally predicted by multilevel modelling. Patients with an existing AAA may have faster PAA progression than those without.

Sex Differences in Brain Regions Modulating Pain Among Older Adults: A Cross-Sectional Resting State Functional Connectivity Study.

Objective: A long-standing hypothesis is that when compared with males, females may be at increased risk of experiencing greater pain sensitivity and unpleasantness. The purpose of this study was to examine sex differences in pain psychophysics and resting state functional connectivity (RSFC) in core pain regions in an age- and sex-matched sample of healthy older adults. Design: Between groups, cross-sectional. Setting: Vanderbilt University and Medical Center. Subjects: The sample in the analyses reported here consisted of 19 cognitively intact males matched with 19 cognitively intact females of similar ages (median ages: females = 70 years, males = 68 years). Methods: Psychophysical assessment of experimental thermal pain and RSFC. Results: There were no significant differences in perceptual thresholds or unpleasantness ratings in response to thermal stimuli. Older males showed greater RSFC between the affective and sensory networks and between affective and descending modulatory networks. Conversely, older females showed greater RSFC between the descending modulatory network and both sensory and affective networks. The strongest evidence for sex differences emerged in the associations of thermal pain with RSFC between the anterior cingulate cortex (ACC) and amygdala and between the ACC and periaqueductal gray matter in older females relative to older males. Conclusions: We found no differences in pain sensitivity or pain affect between older males and older females. Additionally, we found that older females exhibited a greater association between thermal pain sensitivity and RSFC signal between regions typically associated with pain affect and the descending modulatory system. One interpretation of these findings is that older females may better engage the descending pain modulatory system. This better engagement possibly translates into older females having similar perceptual thresholds for temperature sensitivity and unpleasantness associated with mild and moderate pain. These findings contrast with studies demonstrating that younger females find thermal pain more sensitive and more unpleasant.

Towards Portable Large-Scale Image Processing with High-Performance Computing.

High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software development and expansion, and (3) scalable spider deployment compatible with HPC clusters and local workstations.

Magnetic resonance imaging connectivity for the prediction of seizure outcome in temporal lobe epilepsy.

OBJECTIVE: Currently, approximately 60-70% of patients with unilateral temporal lobe epilepsy (TLE) remain seizure-free 3 years after surgery. The goal of this work was to develop a presurgical connectivity-based biomarker to identify those patients who will have an unfavorable seizure outcome 1-year postsurgery. METHODS: Resting-state functional and diffusion-weighted 3T magnetic resonance imaging (MRI) was acquired from 22 unilateral (15 right, 7 left) patients with TLE and 35 healthy controls. A seizure propagation network was identified including ipsilateral (to seizure focus) and contralateral hippocampus, thalamus, and insula, with bilateral midcingulate and precuneus. Between each pair of regions, functional connectivity based on correlations of low frequency functional MRI signals, and structural connectivity based on streamline density of diffusion MRI data were computed and transformed to metrics related to healthy controls of the same age. RESULTS: A consistent connectivity pattern representing the network expected in patients with seizure-free outcome was identified using eight patients who were seizure-free at 1-year postsurgery. The hypothesis that increased similarity to the model would be associated with better seizure outcome was tested in 14 other patients (Engel class IA, seizure-free: n = 5; Engel class IB-II, favorable: n = 4; Engel class III-IV, unfavorable: n = 5) using two similarity metrics: Pearson correlation and Euclidean distance. The seizure-free connectivity model successfully separated all the patients with unfavorable outcome from the seizure-free and favorable outcome patients (p = 0.0005, two-tailed Fisher's exact test) through the combination of the two similarity metrics with 100% accuracy. No other clinical and demographic predictors were successful in this regard. SIGNIFICANCE: This work introduces a methodologic framework to assess individual patients, and demonstrates the ability to use network connectivity as a potential clinical tool for epilepsy surgery outcome prediction after more comprehensive validation.