Advances in Image Processing for Epileptogenic Zone Detection with MRI.

Focal epilepsy is a common and severe neurologic disorder. Neuroimaging aims to identify the epileptogenic zone (EZ), preferably as a macroscopic structural lesion. For approximately a third of patients with chronic drug-resistant focal epilepsy, the EZ cannot be precisely identified using standard 3.0-T MRI. This may be due to either the EZ being undetectable at imaging or the seizure activity being caused by a physiologic abnormality rather than a structural lesion. Computational image processing has recently been shown to aid radiologic assessments and increase the success rate of uncovering suspicious regions by enhancing their visual conspicuity. While structural image analysis is at the forefront of EZ detection, physiologic image analysis has also been shown to provide valuable information about EZ location. This narrative review summarizes and explains the current state-of-the-art computational approaches for image analysis and presents their potential for EZ detection. Current limitations of the methods and possible future directions to augment EZ detection are discussed.

Neuroimaging of Anxiety in Parkinson's Disease: A Systematic Review.

BACKGROUND: The aim of this systematic review was (1) to identify the brain regions involved in anxiety in Parkinson's disease (PD) based on neuroimaging studies and (2) to interpret the findings against the background of dysfunction of the fear circuit and limbic cortico-striato-thalamocortical circuit. METHODS: Studies assessing anxiety symptoms in PD patients and studies using magnetic resonance imaging, positron emission tomography, or single-photon emission computed tomography were included. RESULTS: The severity of anxiety was associated with changes in the fear circuit and the cortico-striato-thalamocortical limbic circuit. In the fear circuit, a reduced gray-matter volume of the amygdala and the anterior cingulate cortex (ACC); an increased functional connectivity (FC) between the amygdala and orbitofrontal cortex (OFC) and hippocampus and between the striatum and the medial prefrontal cortex (PFC), temporal cortex, and insula; and a reduced FC between the lateral PFC and the OFC, hippocampus, and amygdala were reported. In the cortico-striato-thalamocortical limbic circuit, a reduced FC between the striatum and ACC; a reduced dopaminergic and noradrenergic activity in striatum, thalamus, and locus coeruleus; and a reduced serotoninergic activity in the thalamus were reported. CONCLUSION: To conclude, anxiety is associated with structural and functional changes in both the hypothesized fear and the limbic cortico-striato-thalamocortical circuits. These circuits overlap and may well constitute parts of a more extensive pathway, of which different parts play different roles in anxiety. The neuropathology of PD may affect these circuits in different ways, explaining the high prevalence of anxiety in PD and also the associated cognitive, motor, and psychiatric symptoms. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Predictive value of functional MRI and EEG in epilepsy diagnosis after a first seizure.

It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest. In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group. The sensitivity, specificity, and AUC (mean ±â€¯SD) of the regression model including metrics from both modalities were 74 ±â€¯19%, 82 ±â€¯18%, and 0.75 ±â€¯0.12, respectively. Positive and negative predictive values (mean ±â€¯SD) of the regression model with both EEG and fMRI features are 84 ±â€¯14% and 78 ±â€¯12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05). Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample.

Wavelet entropy of BOLD time series: An application to Rolandic epilepsy.

PURPOSE: To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. MATERIALS AND METHODS: The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated. Using a model time series consisting of multiple harmonics and nonstationary components, the wavelet entropy was compared with Shannon and spectral (Fourier-based) entropy. As an application, the wavelet entropy in 22 children with Rolandic epilepsy was compared to 22 age-matched healthy controls. The images were obtained by performing resting-state functional magnetic resonance imaging (fMRI) using a 3T system, an 8-element receive-only head coil, and an echo planar imaging pulse sequence ( T2*-weighted). The wavelet entropy was also compared to spectral entropy, regional homogeneity, and Shannon entropy. RESULTS: Wavelet entropy was found to identify the nonstationary components of the model time series. In Rolandic epilepsy patients, a significantly elevated wavelet entropy was observed relative to controls for the whole cerebrum (P = 0.03). Spectral entropy (P = 0.41), regional homogeneity (P = 0.52), and Shannon entropy (P = 0.32) did not reveal significant differences. CONCLUSION: The wavelet entropy measure appeared more sensitive to detect abnormalities in cerebral fluctuations represented by nonstationary effects in the BOLD time series than more conventional measures. This effect was observed in the model time series as well as in Rolandic epilepsy. These observations suggest that the brains of children with Rolandic epilepsy exhibit stronger nonstationary temporal signal fluctuations than controls. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1728-1737.

Measuring subtle leakage of the blood-brain barrier in cerebrovascular disease with DCE-MRI: Test-retest reproducibility and its influencing factors.

PURPOSE: Increased blood-brain barrier (BBB) permeability has been shown to play a significant role in the pathophysiology of cerebrovascular disease and it may provide an early functional marker of progression or treatment effects. The aim of the study was to investigate the test-retest reproducibility and influencing factors of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in measuring subtle leakage in patients with cerebrovascular disease. MATERIAL AND METHODS: DCE-MRI (3T) was performed on two separate days in 16 patients (age 66 ± 9 years) with cerebrovascular disease, prospectively. The leakage rate was quantified for white matter (WM) and gray matter (GM) using the Patlak graphical approach with individual vascular input functions (VIFs). Furthermore, the influence of session-averaged VIFs, the average of the VIFs obtained on two days, and shorter scan times (range 5-25 minutes) on the reproducibility were evaluated in WM and GM. RESULTS: Coefficients of variation (CV) ≤14.4% (WM and GM), intraclass correlation coefficients (ICCs) of 0.77 (WM) and 0.49 (GM), were observed for the leakage rate. Session-averaged VIFs hardly affected these results (CV ≤13.4%). The repeatability coefficients (RCs) of the leakage rate decreased from 2.7·10-3 to 0.4·10-3 min-1 in WM (P < 0.01) and 4.4·10-3 to 0.9·10-3 min-1 in GM (P < 0.01) with increasing scan time (range 5-25 minutes). CONCLUSION: Based on the moderate CVs and moderate-to-excellent ICCs, we demonstrate that measuring subtle BBB leakage using DCE-MRI is moderate-to-excellent reproducible. Longer scan times improve the reproducibility. The provided RCs at various scan times may assist future clinical studies investigating BBB leakage using DCE-MRI. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:159-166.

Towards prognostic biomarkers from BOLD fluctuations to differentiate a first epileptic seizure from new-onset epilepsy.

OBJECTIVE: The diagnosis of epilepsy cannot be reliably made prior to a patient's second seizure in most cases. Therefore, adequate diagnostic tools are needed to differentiate subjects with a first seizure from those with a seizure preceding the onset of epilepsy. The objective was to explore spontaneous blood oxygen level-dependent (BOLD) fluctuations in subjects with a first-ever seizure and patients with new-onset epilepsy (NOE), and to find characteristic biomarkers for seizure recurrence after the first seizure. METHODS: We examined 17 first-seizure subjects, 19 patients with new-onset epilepsy (NOE), and 18 healthy controls. All subjects underwent clinical investigation and received electroencephalography and resting-state functional magnetic resonance imaging (MRI). The BOLD time series were analyzed in terms of regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFFs). RESULTS: We found significantly stronger amplitudes (higher fALFFs) in patients with NOE relative to first-seizure subjects and healthy controls. The frequency range of 73-198 mHz (slow-3 subband) appeared most useful for discriminating patients with NOE from first-seizure subjects. The ReHo measure did not show any significant differences. SIGNIFICANCE: The fALFF appears to be a noninvasive measure that characterizes spontaneous BOLD fluctuations and shows stronger amplitudes in the slow-3 subband of patients with NOE relative first-seizure subjects and healthy controls. A larger study population with follow-up is required to determine whether fALFF holds promise as a potential biomarker for identifying subjects at increased risk to develop epilepsy.

Blood-Brain Barrier Leakage in Patients with Early Alzheimer Disease.

Purpose To investigate whether the blood-brain barrier (BBB) leaks blood-circulating substances in patients with early forms of Alzheimer disease (AD), and if so, to examine the extent and pattern of leakage. Materials and Methods This study was approved by the local medical ethical committees of the Maastricht University Medical Center and Leiden University Medical Center, and written informed consent was obtained from all subjects. For this pilot study, 16 patients with early AD and 17 healthy age-matched control subjects underwent dynamic contrast material-enhanced magnetic resonance (MR) imaging sequence with dual time resolution for 25 minutes. The Patlak graphical approach was used to quantify the BBB leakage rate and local blood plasma volume. Subsequent histogram analysis was used to determine the volume fraction of the leaking brain tissue. Differences were assessed with linear regression analysis, adjusted for confounding variables. Results The BBB leakage rate was significantly higher in patients compared with that in control subjects in the total gray matter (P < .05) and cortex (P = .03). Patients had a significantly higher volume fraction of the leaking brain tissue in the gray matter (P = .004), normal-appearing white matter (P < .04), deep gray matter (P = .01), and cortex (P = .004). When all subjects were considered, scores on the Mini-Mental State Examination decreased significantly with increasing leakage in the deep gray matter (P = .007) and cortex (P < .05). Conclusion The results of this study showed global BBB leakage in patients with early AD that is associated with cognitive decline. A compromised BBB may be part of a cascade of pathologic events that eventually lead to cognitive decline and dementia. ©RSNA, 2016 Online supplemental material is available for this article.

Glutamate concentrations vary with antiepileptic drug use and mental slowing.

OBJECTIVE: Although antiepileptic drugs (AEDs) are effective in suppressing epileptic seizures, they also induce (cognitive) side effects, with mental slowing as a general effect. This study aimed to assess whether concentrations of MR detectable neurotransmitters, glutamate and GABA, are associated with mental slowing in patients with epilepsy taking AEDs. METHODS: Cross-sectional data were collected from patients with localization-related epilepsy using a variety of AEDs from three risk categories, i.e., AEDs with low, intermediate, and high risks of developing cognitive problems. Patients underwent 3T MR spectroscopy, including a PRESS (n=55) and MEGA-PRESS (n=43) sequence, to estimate occipital glutamate and GABA concentrations, respectively. The association was calculated between neurotransmitter concentrations and central information processing speed, which was measured using the Computerized Visual Searching Task (CVST) and compared between the different risk categories. RESULTS: Combining all groups, patients with lower processing speeds had lower glutamate concentrations. Patients in the high-risk category had a lower glutamate concentration and lower processing speed compared with patients taking low-risk AEDs. Patients taking intermediate-risk AEDs also had a lower glutamate concentration compared with patients taking low-risk AEDs, but processing speed did not differ significantly between those groups. No associations were found between the GABA concentration and risk category or processing speed. CONCLUSIONS: For the first time, a relation is shown between glutamate concentration and both mental slowing and AED use. It is suggested that the reduced excitatory action, reflected by lowered glutamate concentrations, may have contributed to the slowing of information processing in patients using AEDs with higher risks of cognitive side effects.

Effect of spineboard and headblocks on the image quality of head CT scans.

Trauma patients at risk for, or suspected of, spinal injury are frequently transported to hospital using full spinal immobilisation. At the emergency department, immobilisation is often maintained until radiological work-up is completed. In this study, we examined how these devices for spinal stabilization influence visual image quality. Image quality was judged for both patient CT scans and phantom CT scans. CT scans of 217 patients were assessed retrospectively by two radiologists for visual scoring of image quality, scoring both quantity and impact of artifacts caused by the immobilization devices. For the phantom CT scans, eight set-ups were made, using a vacuum mattress without headblocks and a rigid and a soft-layered spineboard without headblocks, with standard soft-foam headblocks, or with new design headblocks. Overall, artifacts were found in 67 % of CT scans of patients on immobilization devices, which hampered diagnosis in 10 % of the cases. In the phantom CT scans, artifacts were present in all set-ups with one or more devices present and were seen in 20 % of all scan slices. The presence of headblocks resulted in more artifacts in both the patient CT scans and the phantom CT scans. Considerable effort should therefore be made to adjust the design of the immobilization devices and to remove the headblocks before CT scans are made.

Neurophysiological correlates of dissociative symptoms.

OBJECTIVE: Dissociation is a mental process with psychological and somatoform manifestations, which is closely related to hypnotic suggestibility and essentially shows the ability to obtain distance from reality. An increased tendency to dissociate is a frequently reported characteristic of patients with functional neurological symptoms and syndromes (FNSS), which account for a substantial part of all neurological admissions. This review aims to investigate what heart rate variability (HRV), EEG and neuroimaging data (MRI) reveal about the nature of dissociation and related conditions. METHODS: Studies reporting HRV, EEG and neuroimaging data related to hypnosis, dissociation and FNSS were identified by searching the electronic databases Pubmed and ScienceDirect. RESULTS: The majority of the identified studies concerned the physiological characteristics of hypnosis; relatively few investigations on dissociation related FNSS were identified. General findings were increased parasympathetic functioning during hypnosis (as measured by HRV), and lower HRV in patients with FNSS. The large variety of EEG and functional MRI investigations with diverse results challenges definite conclusions, but evidence suggests that subcortical as well as (pre)frontal regions serve emotion regulation in dissociative conditions. Functional connectivity analyses suggest the presence of altered brain networks in patients with FNSS, in which limbic areas have an increased influence on motor preparatory regions. CONCLUSIONS: HRV, EEG and (functional) MRI are sensitive methods to detect physiological changes related to dissociation and dissociative disorders such as FNSS, and can possibly provide more information about their aetiology. The use of such measures could eventually provide biomarkers for earlier identification of patients at risk and appropriate treatment of dissociative conditions.

DeepFLAIR: A neural network approach to mitigate signal and contrast loss in temporal lobes at 7 Tesla FLAIR images.

BACKGROUND AND PURPOSE: Higher magnetic field strength introduces stronger magnetic field inhomogeneities in the brain, especially within temporal lobes, leading to image artifacts. Particularly, T2-weighted fluid-attenuated inversion recovery (FLAIR) images can be affected by these artifacts. Here, we aimed to improve the FLAIR image quality in temporal lobe regions through image processing of multiple contrast images via machine learning using a neural network. METHODS: Thirteen drug-resistant MR-negative epilepsy patients (age 29.2 ± 9.4y, 5 females) were scanned on a 7 T MRI scanner. Magnetization-prepared (MP2RAGE) and saturation-prepared with 2 rapid gradient echoes, multi-echo gradient echo with four echo times, and the FLAIR sequence were acquired. A voxel-wise neural network was trained on extratemporal-lobe voxels from the acquired structural scans to generate a new FLAIR-like image (i.e., deepFLAIR) with reduced temporal lobe inhomogeneities. The deepFLAIR was evaluated in temporal lobes through signal-to-noise (SNR), contrast-to-noise (CNR) ratio, the sharpness of the gray-white matter boundary and joint-histogram analysis. Saliency mapping demonstrated the importance of each input image per voxel. RESULTS: SNR and CNR in both gray and white matter were significantly increased (p < 0.05) in the deepFLAIR's temporal ROIs, compared to the FLAIR. The gray-white matter boundary sharpness was either preserved or improved in 10/13 right-sided temporal regions and was found significantly increased in the ROIs. Multiple image contrasts were influential for the deepFLAIR reconstruction with the MP2RAGE second inversion image being the most important. CONCLUSIONS: The deepFLAIR network showed promise to restore the FLAIR signal and reduce contrast attenuation in temporal lobe areas. This may yield a valuable tool, especially when artifact-free FLAIR images are not available.

Frontal lobe connectivity and cognitive impairment in pediatric frontal lobe epilepsy.

PURPOSE: Cognitive impairment is frequent in children with frontal lobe epilepsy (FLE), but its etiology is unknown. With functional magnetic resonance imaging (fMRI), we have explored the relationship between brain activation, functional connectivity, and cognitive functioning in a cohort of pediatric patients with FLE and healthy controls. METHODS: Thirty-two children aged 8-13 years with FLE of unknown cause and 41 healthy age-matched controls underwent neuropsychological assessment and structural and functional brain MRI. We investigated to which extent brain regions activated in response to a working memory task and assessed functional connectivity between distant brain regions. Data of patients were compared to controls, and patients were grouped as cognitively impaired or unimpaired. KEY FINDINGS: Children with FLE showed a global decrease in functional brain connectivity compared to healthy controls, whereas brain activation patterns in children with FLE remained relatively intact. Children with FLE complicated by cognitive impairment typically showed a decrease in frontal lobe connectivity. This decreased frontal lobe connectivity comprised both connections within the frontal lobe as well as connections from the frontal lobe to the parietal lobe, temporal lobe, cerebellum, and basal ganglia. SIGNIFICANCE: Decreased functional frontal lobe connectivity is associated with cognitive impairment in pediatric FLE. The importance of impairment of functional integrity within the frontal lobe network, as well as its connections to distant areas, provides new insights in the etiology of the broad-range cognitive impairments in children with FLE.

White matter network abnormalities are associated with cognitive decline in chronic epilepsy.

Patients with chronic epilepsy frequently display cognitive comorbidity and might have widespread network abnormalities outside the epileptic zone, which might affect a variety of cognitive functions and global intelligence. We aimed to study the role of white matter connectivity in cognitive comorbidity. Thirty-nine patients with nonsymptomatic localization-related epilepsy and varying degrees of cognitive impairment and 23 age-matched healthy controls were included. Whole brain white matter networks were constructed from fiber tractography. Weighted graph theoretical analysis was performed to study white matter network abnormalities associated with epilepsy and cognition. Patients with severe cognitive impairment showed lower clustering (a measure of brain network segregation) and higher path length (a measure of brain network integration) compared with the healthy controls and patients with little or no cognitive impairment, whereas whole brain white matter volume did not differ. Correlation analyses revealed that IQ and cognitive impairment were strongly associated with clustering and path lengths. This study revealed impaired white matter connectivity, associated with cognitive comorbidity in patients with chronic epilepsy. As whole brain white matter volumes were preserved in the patient group, our results suggest an important role for the network topology rather than volumetric changes, in epilepsy with cognitive decline.

Functional connectivity of dissociation in patients with psychogenic non-epileptic seizures.

INTRODUCTION: Psychogenic non-epileptic seizures (PNES) resemble epileptic seizures, but lack epileptiform brain activity. Instead, the cause is assumed to be psychogenic. An abnormal coping strategy may be exhibited by PNES patients, as indicated by their increased tendency to dissociate. Investigation of resting-state networks may reveal altered routes of information and emotion processing in PNES patients. The authors therefore investigated whether PNES patients differ from healthy controls in their resting-state functional connectivity characteristics and whether these connections are associated with the tendency to dissociate. METHODS: 11 PNES patients without psychiatric comorbidity and 12 healthy controls underwent task-related paradigms (picture-encoding and Stroop paradigms) and resting-state functional MRI (rsfMRI). Global cognitive performance was tested using the Raven's Matrices test and participants completed questionnaires for evaluating dissociation. Functional connectivity analysis on rsfMRI was based on seed regions extracted from task-related fMRI activation maps. RESULTS: The patients displayed a significantly lower cognitive performance and significantly higher dissociation scores. No significant differences were found between the picture-encoding and Stroop colour-naming activation maps between controls and patients with PNES. However, functional connectivity maps from the rsfMRI were statistically different. For PNES patients, stronger connectivity values between areas involved in emotion (insula), executive control (inferior frontal gyrus and parietal cortex) and movement (precentral sulcus) were observed, which were significantly associated with dissociation scores. CONCLUSION: The abnormal, strong functional connectivity in PNES patients provides a neurophysiological correlate for the underlying psychoform and somatoform dissociation mechanism where emotion can influence executive control, resulting in altered motor function (eg, seizure-like episodes).

Microstructural and functional MRI studies of cognitive impairment in epilepsy.

Cognitive impairment is the most common comorbidity in children with epilepsy, but its pathophysiology and predisposing conditions remain unknown. Clinical epilepsy characteristics are not conclusive in determining cognitive outcome. Because many children with epilepsy do not have macrostructural magnetic resonance imaging (MRI) abnormalities, the underlying substrate for cognitive impairment may be found at the microstructural or functional level. In the last two decades, new MRI techniques have been developed that have the potential to visualize microstructural or functional abnormalities associated with cognitive impairment. These include volumetric MRI, voxel-based morphometry (VBM), diffusion tensor imaging (DTI), MR spectroscopy (MRS), and functional MRI (fMRI). All of these techniques have shed new light on various aspects associated with, or underlying, cognitive impairment, although their use in epilepsy has been limited and focused mostly on adults. Therefore, in this review, the use of all these different MRI techniques to unravel cognitive impairment in epilepsy is discussed both in adults and children with epilepsy. Volumetric MRI and VBM have revealed significant volume losses in the area of the seizure focus as well as in distant areas. DTI adds evidence of loss of integrity of connections from the seizure focus to distant areas as well as between distant areas. MRS and fMRI have shown impaired function both in the area of the seizure focus as well as in distant structures. For this review we have compiled and compared findings from the various techniques to conclude that cognitive impairment in epilepsy results from a network disorder in which the (micro)structures as well as the functionality can be disturbed.

Dual-energy CT of the brain and intracranial vessels.

OBJECTIVE: The purpose of this review is to summarize the principles and applications of dual-energy CT in evaluation of the brain and the intracranial blood vessels. CONCLUSION: One major advantage of dual-energy CT is the capability of material differentiation. In general, this property can be applied to bone removal in CT angiography for easier and faster postprocessing. In neuroradiology, material decomposition allows detection of hemorrhage on contrast-enhanced CT scans and facilitates the search for the underlying pathologic mechanism of hematomas. The combination of low radiation dose and advantageous spectral information (blood vs contrast) from these datasets justifies broad clinical implementation of dual-energy CT in neuroradiology.

Structural brain changes in migraine.

CONTEXT: A previous cross-sectional study showed an association of migraine with a higher prevalence of magnetic resonance imaging (MRI)-measured ischemic lesions in the brain. OBJECTIVE: To determine whether women or men with migraine (with and without aura) have a higher incidence of brain lesions 9 years after initial MRI, whether migraine frequency was associated with progression of brain lesions, and whether progression of brain lesions was associated with cognitive decline. DESIGN, SETTING, AND PARTICIPANTS: In a follow-up of the 2000 Cerebral Abnormalities in Migraine, an Epidemiological Risk Analysis cohort, a prospective population-based observational study of Dutch participants with migraine and an age- and sex-matched control group, 203 of the 295 baseline participants in the migraine group and 83 of 140 in the control group underwent MRI scan in 2009 to identify progression of MRI-measured brain lesions. Comparisons were adjusted for age, sex, hypertension, diabetes, and educational level. The participants in the migraine group were a mean 57 years (range, 43-72 years), and 71% were women. Those in the control group were a mean 55 years (range, 44-71 years), and 69% were women. MAIN OUTCOME MEASURES Progression of MRI-measured cerebral deep white matter hyperintensities, infratentorial hyperintensities, and posterior circulation territory infarctlike lesions. Change in cognition was also measured. RESULTS: Of the 145 women in the migraine group, 112 (77%) vs 33 of 55 women (60%) in the control group had progression of deep white matter hyperintensities (adjusted odds ratio [OR], 2.1; 95%CI, 1.0-4.1; P = .04). There were no significant associations of migraine with progression of infratentorial hyperintensities: 21 participants (15%) in the migraine group and 1 of 57 participants (2%) in the control group showed progression (adjusted OR, 7.7; 95% CI, 1.0-59.5; P = .05) or new posterior circulation territory infarctlike lesions: 10 of 203 participants (5%) in the migraine group but none of 83 in the control group (P = .07). There was no association of number or frequency of migraine headaches with progression of lesions. There was no significant association of high vs nonhigh deep white matter hyperintensity load with change in cognitive scores (-3.7 in the migraine group vs 1.4 in the control group; 95% CI, -4.4 to 0.2; adjusted P = .07). CONCLUSIONS: In a community-based cohort followed up after 9 years, women with migraine had a higher incidence of deep white matter hyperintensities but did not have significantly higher progression of other MRI-measured brain changes. There was no association of migraine with progression of any MRI-measured brain lesions in men.

Postmortem Fetal Temperature Estimation with Magnetic Resonance Imaging: Apparent Diffusion Coefficient Measurements in the Vitreous Body and Cerebrospinal Fluid.

OBJECTIVES: Magnetic resonance imaging (MRI) is increasingly used in postmortem fetal imaging. Several factors influence the quality of MRI in this setting, such as small size, autolytic and maceration changes, and temperature. Knowing the fetal temperature at the time of scanning can improve the MRI interpretation. Temperature can be calculated using diffusion-weighted imaging with measurements of the apparent diffusion coefficient (ADC) in the cerebrospinal fluid (CSF). However, this is complicated by small ventricle size and hemorrhage and, therefore, may be unreliable in postmortem imaging. The current study evaluated the feasibility and reliability of using the ADC for temperature measurements of the vitreous body compared to that of CSF. MATERIALS AND METHODS: Two lambs were scanned postmortem at five different time points over 28 hours. Furthermore, 10 stillborn fetuses were scanned once, at 4 to 62 hours after birth. The temperature was measured with a digital thermometer and calculated using the ADCs of the vitreous body (lambs and fetuses) and CSF (fetuses). RESULTS: There was an excellent correlation between measured and calculated temperatures in vitreous bodies of lambs (r = 0.997, P < 0.001) and fetuses (r = 0.970, P < 0.001). The correlation between measured and calculated temperatures in the CSF was poor (r = 0.522, P = 0.122). CONCLUSION: The calculation of the temperature based on the ADC of the vitreous body is feasible and reliable for postmortem fetal imaging.

The application of CT for 3D visualization of concealed bodies.

In forensic radiology, computed tomography (CT) is often used as a medical imaging technique to identify the cause and manner of death of deceased victims of a possible crime. In this study, medical imaging is used to examine concealed bodies and packaging materials. Medical imaging techniques, mainly CT scan, were used to scan packaged or concealed bodies inside containers to identify clues and evidence indicating whether a crime might have been committed. Also, scene integrity and scene safety along with a systematic search for relevant evidentiary items value were considered. Eighteen concealed bodies that had been assessed using medical imaging techniques between 2010 and 2018 at the request of the Dutch National Police were selected. The file records of each case contained imaging data, a photographic record of the unpacking procedure, a list of all items and traces found in the package, and the forensic pathology report. The images were assessed with respect to the different aspects of the case and through a systematic approach. The packages included adult males, adult females, newborn infants, and animals. All human cases were related to criminal offences. In nine adult cases, evidence of a possible violent death could be determined using CT imaging. The cause of death in newborn infants, however, could not be determined. In cases of dismemberment, the completeness of the body could be determined by CT imaging, and the cutting surfaces of bones could be matched on CT images. Regarding scene safety and integrity, in this study all relevant macroscopic items were detected on the CT images. The CT-scans were supplemented with fiduciary markers to better map CT data with the real objects. This information in combination with 2D and 3D images provided the forensic investigator with information on how to unwrap the package layer by layer and help determine different types of packaging materials. Different textiles could not always be identified. The orientation of the body within the packages was provided in all cases, and advice could be given on the optimal approach to access the contents. The overall detection rate of items was 78%. This is one of the first studies to illustrate the contribution of medical imaging, specifically CT scan, to the analysis of concealed bodies and packaging materials prior to unpacking. This demonstrates its contribution to a systematic approach of the investigation by ensuring the safety and health of the investigator while documenting and maintaining the integrity of the crime scene. Imaging also provides information that can be helpful to determine whether a crime might have been committed and reducing the risk of damaging a concealed body. Medical imaging also provides the forensic investigator with information to draw up a workplan prior to unpacking, minimising loss of evidence and determining whether different forensic specialists (e.g., digital or DNA) are needed. It is therefore strongly recommended to use medical imaging, especially CT scanning, before opening a package containing a concealed body.