Working memory during spontaneous migraine attacks: an fMRI study.

OBJECTIVE: To investigate the neural correlates of working memory during a spontaneous migraine attack compared to the interictal phase, using functional magnetic resonance imaging (fMRI). BACKGROUND: Cognitive disturbances are commonly observed during migraine attacks, particularly in the headache phase. However, the neural basis of these changes remains unknown. METHODS: In a fMRI within-subject test-retest design study, eleven women (32 years of age, average) with episodic migraine were evaluated twice, first during a spontaneous migraine attack, and again in a pain-free period. Each session consisted in a cognitive assessment and fMRI while performing a working memory task (N-back). RESULTS: Cognitive test scores were lower during the ictal session than in the pain-free session. Regions typically associated with working memory were activated during the N-back task in both sessions. A voxel wise between session comparison showed significantly greater activation in the left frontal pole and orbitofrontal cortex during the attack relative to the interictal phase. CONCLUSION: Migraine patients exhibited greater activation of the left frontal pole and orbitofrontal cortex while executing a verbal working memory task during a spontaneous migraine attack when compared to the interictal state. Given the association of these regions with pain processing and inhibitory control, these findings suggest that patients recruit inhibitory areas to accomplish the cognitive task during migraine attacks, a neural signature of their cognitive difficulties.

Impact of truncating diffusion MRI scans on diffusional kurtosis imaging.

OBJECTIVE: Diffusional kurtosis imaging (DKI) extends diffusion tensor imaging (DTI), characterizing non-Gaussian diffusion effects but requires longer acquisition times. To ensure the robustness of DKI parameters, data acquisition ordering should be optimized allowing for scan interruptions or shortening. Three methodologies were used to examine how reduced diffusion MRI scans impact DKI histogram-metrics: 1) the electrostatic repulsion model (OptEEM); 2) spherical codes (OptSC); 3) random (RandomTRUNC). MATERIALS AND METHODS: Pre-acquired diffusion multi-shell data from 14 female healthy volunteers (29±5 years) were used to generate reordered data. For each strategy, subsets containing different amounts of the full dataset were generated. The subsampling effects were assessed on histogram-based DKI metrics from tract-based spatial statistics (TBSS) skeletonized maps. To evaluate each subsampling method on simulated data at different SNRs and the influence of subsampling on in vivo data, we used a 3-way and 2-way repeated measures ANOVA, respectively. RESULTS: Simulations showed that subsampling had different effects depending on DKI parameter, with fractional anisotropy the most stable (up to 5% error) and radial kurtosis the least stable (up to 26% error). RandomTRUNC performed the worst while the others showed comparable results. Furthermore, the impact of subsampling varied across distinct histogram characteristics, the peak value the least affected (OptEEM: up to 5% error; OptSC: up to 7% error) and peak height (OptEEM: up to 8% error; OptSC: up to 11% error) the most affected. CONCLUSION: The impact of truncation depends on specific histogram-based DKI metrics. The use of a strategy for optimizing the acquisition order is advisable to improve DKI robustness to exam interruptions.

Brain perfusion imaging by multi-delay arterial spin labeling: Impact of modeling dispersion and interaction with denoising strategies and pathology.

PURPOSE: Arterial spin labeling (ASL) acquisitions at multiple post-labeling delays may provide more accurate quantification of cerebral blood flow (CBF), by fitting appropriate kinetic models and simultaneously estimating relevant parameters such as the arterial transit time (ATT) and arterial cerebral blood volume (aCBV). We evaluate the effects of denoising strategies on model fitting and parameter estimation when accounting for the dispersion of the label bolus through the vasculature in cerebrovascular disease. METHODS: We analyzed multi-delay ASL data from 17 cerebral small vessel disease patients (50 ± 9 y) and 13 healthy controls (52 ± 8 y), by fitting an extended kinetic model with or without bolus dispersion. We considered two denoising strategies: removal of structured noise sources by independent component analysis (ICA) of the control-label image timeseries; and averaging the repetitions of the control-label images prior to model fitting. RESULTS: Modeling bolus dispersion improved estimation precision and impacted parameter values, but these effects strongly depended on whether repetitions were averaged before model fitting. In general, repetition averaging improved model fitting but adversely affected parameter values, particularly CBF and aCBV near arterial locations in patients. This suggests that using all repetitions allows better noise estimation at the earlier delays. In contrast, ICA denoising improved model fitting and estimation precision while leaving parameter values unaffected. CONCLUSION: Our results support the use of ICA denoising to improve model fitting to multi-delay ASL and suggest that using all control-label repetitions improves the estimation of macrovascular signal contributions and hence perfusion quantification near arterial locations. This is important when modeling flow dispersion in cerebrovascular pathology.

What the Musculoskeletal Radiologist Needs to Know About the Vascular Anatomy of the Spine and Spinal Cord.

This article describes the vascular anatomy of the spine and spinal cord, highlighting key structures and anatomical variations relevant to musculoskeletal radiologists. It covers the arterial and venous drainage systems, along with examples of vascular conditions affecting the spine. Understanding the vascular anatomy of the spine and spinal cord is crucial for accurate interpretation of imaging studies and safe spinal interventional procedures. Imaging techniques for evaluating vascular pathology of the spine are discussed and compared. Understanding vascular anatomy and the most common vascular disorders will lead to an accurate diagnosis and suggest the appropriate type of study needed for further characterization and/or patient management.

Impact of white-matter mask selection on DTI histogram-based metrics as potential biomarkers in cerebral small vessel disease.

OBJECTIVE: Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small vessel disease (SVD), but methods and results have varied across studies. This work aims to assess the impact of mask selection for extracting histogram-based metrics of fractional anisotropy (FA) and mean diffusivity (MD) on their sensitivity as SVD biomarkers. METHODS: DTI data were collected from 17 SVD patients and 12 healthy controls. FA and MD maps were estimated; from these, histograms were computed on two whole-brain white-matter masks: normal-appearing white-matter (NAWM) and mean FA tract skeleton (TBSS). Histogram-based metrics (median, peak height, peak width, peak value) were extracted from the FA and MD maps. These were compared between groups and correlated with the patients' cognitive scores (executive function and processing speed). RESULTS: White-matter mask selection significantly impacted FA and MD histogram metrics. In particular, significant interactions were found between Mask and Group for FA peak height (p = 0.027), MD Median (p = 0.035) and MD peak width (p = 0.047); indicating that the mask used affected their ability to discriminate between groups. In fact, MD peak width showed a significant 8.8% increase in patients when using TBSS (p = 0.037), but not when using NAWM (p = 0.69). Moreover, the mask may have an effect on the correlations with cognitive measures. Nevertheless, MD peak width (TBSS: r = - 0.75, NAWM: r = - 0.71) and MD peak height (TBSS: r = 0.65, NAWM: r = 0.62) remained significantly correlated with executive function, regardless of the mask. CONCLUSION: The impact of the processing methodology, in particular the choice of white-matter mask, highlights the need for standardized MRI data-processing pipelines.

Calibration of arterial spin labeling data-potential pitfalls in post-processing.

PURPOSE: To assess the impact of the different post-processing options in the calibration of arterial spin labeling (ASL) data on perfusion quantification and its reproducibility. THEORY AND METHODS: Absolute quantification of perfusion measurements is one of the promises of ASL techniques. However, it is highly dependent on a calibration procedure that involves a complex processing pipeline for which no standardized procedure has been fully established. In this work, we systematically compare the main ASL calibration methods as well as various post-processing calibration options, using 2 data sets acquired with the most common sequences, pulsed ASL and pseudo-continuous ASL. RESULTS: Significant and sometimes large discrepancies in ASL perfusion quantification were obtained when using different post-processing calibration options. Nevertheless, when using a set of theoretically based and carefully chosen options, only small differences were observed for both reference tissue and voxelwise methods. The voxelwise and white matter reference tissue methods were less sensitive to post-processing options than the cerebrospinal fluid reference tissue method. However, white matter reference tissue calibration also produced poorer reproducibility results. Moreover, it may also not be an appropriate reference in case of white matter pathology. CONCLUSION: Poor post-processing calibration options can lead to large errors in perfusion quantification, and a complete description of the calibration procedure should therefore be reported in ASL studies. Overall, our results further support the voxelwise calibration method proposed by the ASL white paper, particularly given the advantage of being relatively simple to implement and intrinsically correcting for the coil sensitivity profile.

Standards for European training requirements in interventional neuroradiology : Guidelines by the Division of Neuroradiology/Section of Radiology European Union of Medical Specialists (UEMS), in cooperation with the Division of Interventional Radiology/UEMS, the European Society of Neuroradiology (ESNR), and the European Society of Minimally Invasive Neurological Therapy (ESMINT).

This document sets out standards for training in Interventional Neuroradiology (INR) in Europe. These standards have been developed by a working group of the European Society of Neuroradiology (ESNR) and the European Society of Minimally Invasive Neurological Therapy (ESMINT) on the initiative and under the umbrella of the Division of Neuroradiology/Section of Radiology of the European Union of Medical Specialists (UEMS).

Near infra-red fluorescence-guidance for percutaneous sclerotherapy of thoracic duct leak.

Treatment of thoracic duct leaks can be very challenging. Intractable chlye leaks may require image-guided methods to increase the likelihood of treatment success. Near infra-red fluorescence is an easy-to-use nonionizing imaging method that has been described to detect thoracic duct leaks in open surgery or thoracoscopic interventions, yet no application to percutaneous sclerotherapy has been described. The authors suggest near infra-red fluorescence as a feasible and useful tool to guide percutaneous sclerotherapy.

Looking at Fog Computing for E-Health through the Lens of Deployment Challenges and Applications.

Fog computing is a distributed infrastructure where specific resources are managed at the network border using cloud computing principles and technologies. In contrast to traditional cloud computing, fog computing supports latency-sensitive applications with less energy consumption and a reduced amount of data traffic. A fog device is placed at the network border, allowing data collection and processing to be physically close to their end-users. This characteristic is essential for applications that can benefit from improved latency and response time. In particular, in the e-Health field, many solutions rely on real-time data to monitor environments, patients, and/or medical staff, aiming at improving processes and safety. Therefore, fog computing can play an important role in such environments, providing a low latency infrastructure. The main goal of the current research is to present fog computing strategies focused on electronic-Health (e-Health) applications. To the best of our knowledge, this article is the first to propose a review in the scope of applications and challenges of e-Health fog computing. We introduce some of the available e-Health solutions in the literature that focus on latency, security, privacy, energy efficiency, and resource management techniques. Additionally, we discuss communication protocols and technologies, detailing both in an architectural overview from the edge devices up to the cloud. Differently from traditional cloud computing, the fog concept demonstrates better performance in terms of time-sensitive requirements and network data traffic. Finally, based on the evaluation of the current technologies for e-Health, open research issues and challenges are identified, and further research directions are proposed.

Standards of Practice in Acute Ischemic Stroke Intervention International Recommendations.

After five positive randomized controlled trials showed benefit of mechanical thrombectomy in the management of acute ischemic stroke with emergent large-vessel occlusion, a multi-society meeting was organized during the 17th Congress of the World Federation of Interventional and Therapeutic Neuroradiology in October 2017 in Budapest, Hungary. This multi-society meeting was dedicated to establish standards of practice in acute ischemic stroke intervention aiming for a consensus on the minimum requirements for centers providing such treatment. In an ideal situation, all patients would be treated at a center offering a full spectrum of neuroendovascular care (a level 1 center). However, for geographical reasons, some patients are unable to reach such a center in a reasonable period of time. With this in mind, the group paid special attention to define recommendations on the prerequisites of organizing stroke centers providing medical thrombectomy for acute ischemic stroke, but not for other neurovascular diseases (level 2 centers). Finally, some centers will have a stroke unit and offer intravenous thrombolysis, but not any endovascular stroke therapy (level 3 centers). Together, these level 1, 2, and 3 centers form a complete stroke system of care. The multi-society group provides recommendations and a framework for the development of medical thrombectomy services worldwide.

Fourier modeling of the BOLD response to a breath-hold task: Optimization and reproducibility.

Cerebrovascular reactivity (CVR) reflects the capacity of blood vessels to adjust their caliber in order to maintain a steady supply of brain perfusion, and it may provide a sensitive disease biomarker. Measurement of the blood oxygen level dependent (BOLD) response to a hypercapnia-inducing breath-hold (BH) task has been frequently used to map CVR noninvasively using functional magnetic resonance imaging (fMRI). However, the best modeling approach for the accurate quantification of CVR maps remains an open issue. Here, we compare and optimize Fourier models of the BOLD response to a BH task with a preparatory inspiration, and assess the test-retest reproducibility of the associated CVR measurements, in a group of 10 healthy volunteers studied over two fMRI sessions. Linear combinations of sine-cosine pairs at the BH task frequency and its successive harmonics were added sequentially in a nested models approach, and were compared in terms of the adjusted coefficient of determination and corresponding variance explained (VE) of the BOLD signal, as well as the number of voxels exhibiting significant BOLD responses, the estimated CVR values, and their test-retest reproducibility. The brain average VE increased significantly with the Fourier model order, up to the 3rd order. However, the number of responsive voxels increased significantly only up to the 2nd order, and started to decrease from the 3rd order onwards. Moreover, no significant relative underestimation of CVR values was observed beyond the 2nd order. Hence, the 2nd order model was concluded to be the optimal choice for the studied paradigm. This model also yielded the best test-retest reproducibility results, with intra-subject coefficients of variation of 12 and 16% and an intra-class correlation coefficient of 0.74. In conclusion, our results indicate that a Fourier series set consisting of a sine-cosine pair at the BH task frequency and its two harmonics is a suitable model for BOLD-fMRI CVR measurements based on a BH task with preparatory inspiration, yielding robust estimates of this important physiological parameter.

Reproducibility of the quantification of arterial and tissue contributions in multiple postlabeling delay arterial spin labeling.

PURPOSE: To evaluate the reproducibility of estimation of cerebral blood flow (CBF), bolus arrival time (BAT), and arterial blood volume (aBV) from arterial spin labeling (ASL) data acquired at multiple postlabeling delays (PLDs). MATERIALS AND METHODS: CBF, BAT, and aBV parameters were estimated from flow-suppressed and nonflow-suppressed multiple-PDL PICORE-Q2TIPS ASL using model-based Bayesian and least-squares fitting frameworks, and aBV was also obtained from a model-free approach. Reproducibility of these parameters was assessed by computing the within- and between-subject coefficients of variability (CVw and CVb). RESULTS: CVw and CVb were comparable across model-based approaches, but were greater for the aBV from the model-free approach. Overall, the Bayesian model estimation procedure was found to provide the best compromise between reliability and reproducibility, yielding CVw/CVb values of 21/21, 3/4, and 24/26% for CBF, BAT, and aBV, respectively. Although a CBF range of 45 mL/100g/min to 59 mL/100g/min was found on average and a BAT of 0.7-1.0 seconds across methods, the corresponding maps were comparable in terms of the parameters' spatial distributions, and in particular in the identification of macrovascular locations, as assessed through comparison with time-of-flight images. CONCLUSION: Reproducible estimates of CBF, BAT, and aBV values can be obtained from non-macroflow-suppressed ASL using both least-squares and Bayesian model-based methods.

Localization of the hand motor area by arterial spin labeling and blood oxygen level-dependent functional magnetic resonance imaging.

The new clinically available arterial spin labeling (ASL) perfusion imaging sequences present some advantages relatively to the commonly used blood oxygen level-dependent (BOLD) method for functional brain studies using magnetic resonance imaging (MRI). In particular, regional cerebral blood flow (CBF) changes are thought to be more directly related with neuronal activation. In this study, we aimed to investigate the accuracy of the functional localization of the hand motor area obtained by simultaneous CBF and BOLD contrasts provided by ASL functional MRI (fMRI) and compare it with a standard BOLD fMRI protocol. For this purpose, we measured the distance between the center of gravity of the activation clusters obtained with each contrast (CBF, BOLD(ASL), and Standard BOLD) and 11 positions defined on a well-established anatomical landmark of the hand motor area (the omega in the axial plane of the precentral gyrus). We found that CBF measurements were significantly closer to the anatomical landmark than the ones obtained using either simultaneous BOLD(ASL) or standard BOLD contrasts. Moreover, we also observed reduced intersubject variability of the functional localization, as well as percent signal change, for CBF relative to both BOLD contrast measurements. In conclusion, our results add further evidence in support to the notion that CBF provides a more accurate localization of motor activation than BOLD contrast, indicating that ASL may be an appropriate technique for clinical fMRI studies.

Imaging Approach to Venous Sinus Thrombosis.

Cerebral venous thrombosis (CVT) is a rare cerebrovascular disease caused by an occlusion of the cerebral venous sinuses or cortical veins. It has a favorable prognosis if diagnosed and treated early. CVT can be difficult to diagnose on clinical grounds, and imaging plays a key role. We discuss clinical features and provide an overview of current neuroimaging methods and findings in CTV.

Altered functional connectivity in a sensorimotor-insular network during spontaneous migraine attacks: A resting-state FMRI study.

BACKGROUND: Previous functional magnetic resonance imaging studies have identified brain-connectivity alterations across multiple regions in people with migraine when compared to healthy controls. Few studies have focused on such changes throughout the different phases of the migraine cycle. We aimed to investigate functional connectivity during spontaneous occurring episodic migraine attacks, in comparison to interictal periods. METHODS: Eleven women with episodic migraine without aura underwent two sessions of resting-state fMRI, during and outside of a spontaneous migraine attack. Functional connectivity changes were assessed across canonical resting-state networks, identified by independent component analysis. Significantly altered connectivity was correlated with migraine attack symptoms. RESULTS: Decreased functional connectivity between subregions of the sensorimotor network (specifically, the primary somatosensory and motor cortices) and the posterior insula, bilaterally, was found during attacks. In both sessions, the functional connectivity between these regions was lower in patients who usually suffered longer attacks. DISCUSSION: The sensorimotor and insular regions are involved in nociceptive, autonomic, and somatosensory processing so the finding of reduced connectivity between these structures within a migraine attack is likely associated to the perception of pain and the heighten sensitivity to stimuli experienced in this disorder.

Impact of susceptibility-induced distortion correction on perfusion imaging by pCASL with a segmented 3D GRASE readout.

PURPOSE: The consensus for the clinical implementation of arterial spin labeling (ASL) perfusion imaging recommends a segmented 3D Gradient and Spin-Echo (GRASE) readout for optimal signal-to-noise-ratio (SNR). The correction of the associated susceptibility-induced geometric distortions has been shown to improve diagnostic precision, but its impact on ASL data has not been systematically assessed and it is not consistently part of pre-processing pipelines. Here, we investigate the effects of susceptibility-induced distortion correction on perfusion imaging by pseudo-continuous ASL (pCASL) with a segmented 3D GRASE readout. METHODS: Data acquired from 28 women using pCASL with 3D GRASE at 3T was analyzed using three pre-processing options: without distortion correction, with distortion correction, and with spatial smoothing (without distortion correction) matched to control for blurring effects induced by distortion correction. Maps of temporal SNR (tSNR) and relative perfusion were analyzed in eight regions-of-interest (ROIs) across the brain. RESULTS: Distortion correction significantly affected tSNR and relative perfusion across the brain. Increases in tSNR were like those produced by matched spatial smoothing in most ROIs, indicating that they were likely due to blurring effects. However, that was not the case in the frontal and temporal lobes, where we also found increased relative perfusion with distortion correction even compared with matched spatial smoothing. These effects were found in both controls and patients, with no interactions with the participant group. CONCLUSION: Correction of susceptibility-induced distortions significantly impacts ASL perfusion imaging using a segmented 3D GRASE readout, and this step should therefore be considered in ASL pre-processing pipelines. This is of special importance in clinical studies, reporting perfusion across ROIs defined on relatively undistorted images and when conducting group analyses requiring the alignment of images across different subjects.

Physical Activity Self-Report Is Not Reliable Among Subjects with Mild Vascular Cognitive Impairment: The AFIVASC Study.

BACKGROUND: The World Health Organization (WHO) recommends a minimum of 150 minutes of moderate physical activity per week. Adherence to these recommendations is difficult to assess. OBJECTIVE: We aimed to evaluate the validity of self-reported physical activity in mild vascular cognitive impairment (mVCI) and whether physical activity was associated with cognitive status, by using baseline data from a randomized controlled trial. METHODS: A hundred and four subjects with mVCI were included (mean age 72 years; 51% women). Subjects underwent neurological, physical, and comprehensive neuropsychological assessments. Adherence to WHO physical activity recommendations was evaluated using both self-reported information and objective measures (accelerometry). RESULTS: There was poor agreement (kappa = 0.106) between self-report of following WHO recommendations and actually fulfilling them according to accelerometry. Only 16.6% of participants reported following WHO recommendations and displayed compatible values according to the accelerometer. Participants whose accelerometry values confirmed adherence to WHO recommendations had better performance in a global measure of cognition, attention, and mental speed processing. In multiple regression analyses, education and accelerometry values in accordance with WHO recommendations were independently associated with the global measure of cognition, attention, and processing speed, controlling for sex, age, and depressive symptoms. Accelerometry results were not associated with memory and executive functions. CONCLUSION: In this sample of mVCI subjects, self-reported physical activity displayed poor agreement with accelerometry values, suggesting that objective measures of physical activity are preferable. Physical activity (performed, at least, according to WHO recommendations) was associated with better cognitive performance overall.

Cerebral Air Embolism: The Importance of Computed Tomography Evaluation.

Cerebral air embolism (CAE) is a serious disease, often underdiagnosed due to nonspecific neurological findings and clinical and imaging unawareness. Early diagnosis is crucial for a prompt specific treatment, which differs from other types of brain infarcts. Immediate computed tomography (CT) scan is the imaging technique of choice, allowing to depict acute intracranial air, most commonly seen in the high convexity along cortical grooves, in a sulcal subarachnoid gyriform pattern. The use of thin-slice (thickness of 5 mm or smaller) and the measurement of air attenuation coefficient can reduce false-negative studies. Hyperbaric oxygen therapy (HBOT) is the first-line treatment for CAE and may affect the outcome. We report four cases of iatrogenic CAE and review the literature.