Symmetrical Brain Research Articles

Imaging features of 10 patients with toxic encephalopathy caused by diquat

Objective: To explore the CT and MRI imaging findings of diquat toxic encephalopathy. Methods: CT and MRI imaging features of 10 patients with diquat poisoning encephalopathy who had been clinically diagnosed were retrospectively reviewed. Results: CT was performed in all 10 patients, and MRI was performed in 8 patients. In 10 patients, 7 had positive signs on CT, and 8 patients with MRI examination had abnormal changes in the images. The main CT findings were symmetrical hypodensity in bilateral cerebellar hemisphere, brainstem, thalamus and basal ganglia, and swelling of brain tissue. The main MRI findings were symmetrical lesions and brain edema in the deep nuclei of cerebellar hemisphere, brainstem, thalamus and basal ganglia, low signal on T1WI, high signal on T2WI and T2-FLAIR, and cytotoxic edema on diffusion weighted imaging (DWI) . On review after treatment, both CT and MRI showed resorption of the lesion, which narrowed in size. Conclusion: The imaging findings of diquat poisoning encephalopathy are characteristic and the location of the lesion is characteristic, and CT and MRI have a certain diagnostic value in diquat poisoning encephalopathy, which is important for clinical treatment.

In vivo symmetric multi-contrast MRI brain templates and atlas for spontaneously hypertensive rats.

Spontaneously hypertensive rats (SHRs) are a valuable animal model of essential hypertension. The increasing use of SHRs in neuroimaging has generated an urgent demand for a template set that provides a reference for advanced data analysis. Structural T2-weighted magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and functional MRI scans that were used to build the template set were obtained from 8 SHRs longitudinally scanned in vivo at 10, 24 and 52weeks of age. These symmetric multi-contrast templates were constructed by iterative registration and averaging. The cortical atlas was derived from the Tohoku atlas, and the subcortical regions were manually delineated based on the templates. A set of SHR brain images named the Hebei Medical University rat brain template set (HRT) comprised 3D symmetric T2WI, raw T2-weighted signal with no added diffusion weighting (B0), fractional anisotropy (FA), mean diffusivity (MD) and blood oxygen level-dependent (BOLD) templates; tissue probability maps (TPMs) of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF); and a whole-brain atlas with 163 labels. We quantitatively validated the template and characterized the longitudinal changes in brain morphology in different brain tissues as SHRs aged. To our knowledge, the HRT is the first MRI template set for SHRs. We believe that the HRT can serve as a beneficial tool for precise analysis of the SHR brain using structural and functional MRI, which can promote neuroimaging studies on essential hypertension.

Whole-exome sequencing identified novel variants in three Chinese Leigh syndrome pedigrees.

Leigh syndrome (LS), the most common mitochondrial disease in early childhood, usually manifests variable neurodegenerative symptoms and typical brain magnetic resonance imaging (MRI) lesions. To date, pathogenic variants in more than 80 genes have been identified. However, there are still many cases without molecular diagnoses, and thus more disease-causing variants need to be unveiled. Here, we presented three clinically suspected LS patients manifesting neurological symptoms including developmental delay, hypotonia, and epilepsy during the first year of age, along with symmetric brain lesions on MRI. We explored disease-associated variants in patients and their nonconsanguineous parents by whole-exome sequencing and subsequent Sanger sequencing verification. Sequencing data revealed three pairs of disease-associated compound heterozygous variants: c.1A>G (p.Met1?) and 409G>C (p.Asp137His) in SDHA, c.1253G>A (p.Arg418His) and 1300C>T (p.Leu434Phe) in NARS2, and c.5C>T (p.Ala2Val) and 773T>G (p.Leu258Trp) in ECHS1. Among them, the likely pathogenic variants c.409G>C (p.Asp137His) in SDHA, c.1300C>T (p.Leu434Phe) in NARS2, and c.773T>G (p.Leu258Trp) in ECHS1 were newly identified. Segregation analysis indicated the possible disease-causing nature of the novel variants. In silico prediction and three-dimensional protein modeling further suggested the potential pathogenicity of these variants. Our discovery of novel variants expands the gene variant spectrum of LS and provides novel evidence for genetic counseling.

Diagnosis of obsessive-compulsive disorder via spatial similarity-aware learning and fused deep polynomial network.

Obsessive-compulsive disorder (OCD) is a type of hereditary mental illness, which seriously affect the normal life of the patients. Sparse learning has been widely used in detecting brain diseases objectively by removing redundant information and retaining monitor valuable biological characteristics from the brain functional connectivity network (BFCN). However, most existing methods ignore the relationship between brain regions in each subject. To solve this problem, this paper proposes a spatial similarity-aware learning (SSL) model to build BFCNs. Specifically, we embrace the spatial relationship between adjacent or bilaterally symmetric brain regions via a smoothing regularization term in the model. We develop a novel fused deep polynomial network (FDPN) model to further learn the powerful information and attempt to solve the problem of curse of dimensionality using BFCN features. In the FDPN model, we stack a multi-layer deep polynomial network (DPN) and integrate the features from multiple output layers via the weighting mechanism. In this way, the FDPN method not only can identify the high-level informative features of BFCN but also can solve the problem of curse of dimensionality. A novel framework is proposed to detect OCD and unaffected first-degree relatives (UFDRs), which combines deep learning and traditional machine learning methods. We validate our algorithm in the resting-state functional magnetic resonance imaging (rs-fMRI) dataset collected by the local hospital and achieve promising performance.

A Simulation on Relation between Power Distribution of Low-Frequency Field Potentials and Conducting Direction of Rhythm Generator Flowing through 3D Asymmetrical Brain Tissue

Although the power of low-frequency oscillatory field potentials (FP) has been extensively applied previously, few studies have investigated the influence of conducting direction of deep-brain rhythm generator on the power distribution of low-frequency oscillatory FPs on the head surface. To address this issue, a simulation was designed based on the principle of electroencephalogram (EEG) generation of equivalent dipole current in deep brain, where a single oscillatory dipole current represented the rhythm generator, the dipole moment for the rhythm generator’s conducting direction (which was orthogonal and rotating every 30 degrees and at pointing to or parallel to the frontal lobe surface) and the (an)isotropic conduction medium for the 3D (a)symmetrical brain tissue. Both the power above average (significant power value, SP value) and its space (SP area) of low-frequency oscillatory FPs were employed to respectively evaluate the strength and the space of the influence. The computation was conducted using the finite element method (FEM) and Hilbert transform. The finding was that either the SP value or the SP area could be reduced or extended, depending on the conducting direction of deep-brain rhythm generator flowing in the (an)isotropic medium, suggesting that the 3D (a)symmetrical brain tissue could decay or strengthen the spatial spread of a rhythm generator conducting in a different direction.

Neuropsychological and neuroimaging characteristics of classical superficial siderosis.

To define the neuropsychological and neuroimaging characteristics of classicalinfratentorial superficial siderosis (iSS), a rare but disabling disorder defined by hemosiderin deposition affecting the superficial layers of the cerebellum, brainstem and spinal cord, usually associated with a slowly progressive neurological syndrome of deafness, ataxia and myelopathy. We present the detailed neuropsychological and neuroimaging findings in 16 patients with iSS (mean age 57years; 6 female). Cognitive impairment was present in 8/16 (50%) of patients: executive dysfunction was the most prevalent (44%), followed by impairment of visual recognition memory (27%); other cognitive domains were largely spared. Disease symptom duration was significantly correlated with the number of cognitive domains impaired (r = 0.59, p = 0.011). Mood disorders were also common (anxiety 62%, depression 38%, both 69%) but not associated with disease symptom duration. MRI findings revealed siderosis was not only in infratentorial brain regions, but also in characteristic widespread symmetrical supratentorial brain regions, independent of disease duration and degree of cognitive impairment. The presence of small vessel disease markers was very low and did not account for the cognitive impairment observed. Neuropsychological disturbances are common in iSS and need to be routinely investigated. The lack of association between the anatomical extent of hemosiderin and cognitive impairment or disease duration suggests that hemosiderin itself is not directly neurotoxic. Additional biomarkers of iSS disease severity and progression are needed for future research and clinical trials.

The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity.

The Developing Human Connectome Project is an Open Science project that provides the first large sample of neonatal functional MRI data with high temporal and spatial resolution. These data enable mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organization in humans. Here, we characterize in unprecedented detail the maturation and integrity of resting state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm). First, we applied group independent component analysis to define 11 RSNs in term-born infants scanned at 43.5–44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37–43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder, which occur frequently in preterm children. Overall, we found a robust, modular, symmetrical functional brain organization at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.

Abstract P330: Optimizing Predictions of Infarct Core Using Machine Learning

Introduction: Evaluation of infarct core by advanced neuroimaging has facilitated patient selection for endovascular stroke therapy (EST), however the accuracy of machine-learning analysis compared to these modalities remains unexplored. We test the performance of computed tomography-Alberta Stroke Program Early Computed Tomography Score (CT- ASPECTS) vs. Computed Tomography Perfusion (CTP)-RAPID, vs. an extension of our novel machine-learning model, Deep Symmetry-sensitive Network (DeepSymNet [ref]), using the final infarct volume (FIV) in patients with rapid and successful endovascular reperfusion as the gold standard. Methods and Materials: We identified consecutive patients with large vessel occlusion acute ischemic stroke that underwent EST with TICI 2b/3 reperfusion. FIV was determined by volumetric measurements on 24-48h DWI MRI. The DeepSymNet algorithm combines symmetric and absolute brain representations and had been trained to predict CTP-RAPID core size from CTA source images acquired at presentation. Performance at predicting FIV was determined by Pearson’s correlation for CT- ASPECTS, CTP-RAPID, and DeepSymNet. Data are presented as median [IQR]. Results: Among the 76 patients that met inclusion criteria, 55.2% were male, the median age was 68 years [54-77], and 32.8% were White. 71% of the patients demonstrated an MCA occlusion, and 55% of all occlusions were left-sided. Median ASPECTS on presentation was 8 [7-8.5] and the median FIV was 10 mL [2-37]. ASPECTS, CTP-RAPID and DeepSymNet all correlated with FIV, with comparable performances from ASPECTS (R 2 =-0.398) and CTP-RAPID (R 2 =0.403) and superior performance by DeepSymNet (R 2 =-0.606)(Table). Conclusions: The DeepSymNet machine learning model analyzing CTA source images demonstrated superior performance to ASPECTS and CTP-RAPID in FIV prediction. These findings suggest machine learning models may provide improved predictions of infarct core and selection for EST.

Encefalopatía necrotizante aguda asociada a influenza A

La encefalopatía necrotizante aguda (ENA) es una patología rara, caracterizada por compromiso de conciencia y presencia de múltiples lesiones encefálicas simétricas localizadas principalmente en tálamo. Se asocia a alta letalidad e importantes secuelas.Objetivo: Describir el caso de un paciente escolar con ENA asociada a influenza-A con evolución favorable.Caso Clínico: Paciente de 6 años de edad, con historia de 3 días de evolución de síntomas respiratorios altos asociados a fiebre (39 °C). Veinticuatro horas previo a la consulta destacaba compromiso de conciencia cualicuantitativo. Se realizó punción lumbar con proteinorraquia leve. En resonancia magnética (RM) se identificó focos de restricción a la difusión bilaterales de distribución simétrica, talámicos, en cuerpos mamilares, periacueductales, de tegmento pontino, hipocampales y en ambas cápsulas externas, asociado a componente hemorrágico y edema vasogénico, sugerente de ENA. Recibió tratamiento empírico con metilprednisolona y oseltamivir. Posteriormente, se recibió resultado positivo para virus influenzaAH1. Dado diagnóstico, se decidió administrar inmunoglobulina, evolucionando lento pero favorablemente. Al alta levemente bradipsíquico, con disminución de agudeza visual, lenguaje espontáneo y marcha con apoyo. A los 6 meses de seguimiento presentaba lenguaje y marcha normales, persistiendo alteración visual a derecha.Conclusión: Nuestro paciente presentó una ENA cuyo diagnóstico y manejo oportunos se asociaron a una favorable evolución neurológica en el largo plazo. Si bien la ENA es una patología infrecuente, la morbimortalidad asociada es altísima, por lo que resulta de gran importancia tener un alto grado de sospecha, a fin de solicitar estudio imagenológico dirigido, buscar causas infecciosas relacionadas e iniciar un manejo oportuno.

Separability of Acute Cerebral Infarction Lesions in CT Based Radiomics: Toward Artificial Intelligence-Assisted Diagnosis.

This study aims at analyzing the separability of acute cerebral infarction lesions which were invisible in CT. 38 patients, who were diagnosed with acute cerebral infarction and performed both CT and MRI, and 18 patients, who had no positive finding in either CT or MRI, were enrolled. Comparative studies were performed on lesion and symmetrical regions, normal brain and symmetrical regions, lesion, and normal brain regions. MRI was reconstructed and affine transformed to obtain accurate lesion position of CT. Radiomic features and information gain were introduced to capture efficient features. Finally, 10 classifiers were established with selected features to evaluate the effectiveness of analysis. 1301 radiomic features were extracted from candidate regions after registration. For lesion and their symmetrical regions, there were 280 features with information gain greater than 0.1 and 2 features with information gain greater than 0.3. The average classification accuracy was 0.6467, and the best classification accuracy was 0.7748. For normal brain and their symmetrical regions, there were 176 features with information gain greater than 0.1, 1 feature with information gain greater than 0.2. The average classification accuracy was 0.5414, and the best classification accuracy was 0.6782. For normal brain and lesions, there were 501 features with information gain greater than 0.1 and 1 feature with information gain greater than 0.5. The average classification accuracy was 0.7480, and the best classification accuracy was 0.8694. In conclusion, the study captured significant features correlated with acute cerebral infarction and confirmed the separability of acute lesions in CT, which established foundation for further artificial intelligence-assisted CT diagnosis.

Midline Thalamic Damage Associated with Alcohol-Use Disorders: Disruption of Distinct Thalamocortical Pathways and Function.

The thalamus, a significant part of the diencephalon, is a symmetrical and bilateral central brain structure. The thalamus is subdivided into three major groups of nuclei based on their function: sensorimotor nuclei (or principal/relay nuclei), limbic nuclei and nuclei bridging these two domains. Anatomically, nuclei within the thalamus are described by their location, such as anterior, medial, lateral, ventral, and posterior. In this review, we summarize the role of medial and midline thalamus in cognition, ranging from learning and memory to flexible adaptation. We focus on the discoveries in animal models of alcohol-related brain damage, which identify the loss of neurons in the medial and midline thalamus as drivers of cognitive dysfunction associated with alcohol use disorders. Models of developmental ethanol exposure and models of adult alcohol-related brain damage and are compared and contrasted, and it was revealed that there are similar (anterior thalamus) and different (intralaminar [adult exposure] versus ventral midline [developmental exposure]) thalamic pathology, as well as disruptions of thalamo-hippocampal and thalamo-cortical circuits. The final part of the review summarizes approaches to recover alcohol-related brain damage and cognitive and behavioral outcomes. These approaches include pharmacological, nutritional and behavioral interventions that demonstrated the potential to mitigate alcohol-related damage. In summary, the medial/midline thalamus is a significant contributor to cognition function, which is also sensitive to alcohol-related brain damage across the life span, and plays a role in alcohol-related cognitive dysfunction.

Clinically based score predicting cryptogenic NORSE at the early stage of status epilepticus.

ObjectiveTo determine whether a clinically based score predicts cryptogenic new-onset refractory status epilepticus (C-NORSE) at the early stage of status epilepticus (SE) with prominent motor symptoms (SE-M) of unclear etiology.MethodsThe score (range 0–6) included 6 clinical features: highly refractoriness to antiseizure drugs, previously healthy individual, presence of prodromal fever, absence of prodromal psychobehavioral or memory alterations, absence of dyskinesias, and symmetric brain MRI abnormalities (the first 2 mandatory). We retrospectively assessed the usefulness of a high scale score (≥5) in predicting C-NORSE in 83 patients with SE-M of unclear etiology, who underwent testing for neuronal surface antibodies (NS-Abs) between January 2007, and December 2019.ResultsThirty-one (37.3%) patients had a high score. Patients with a high score had more frequent prodromal fever (28/31 vs 24/52), mechanical ventilatory support (31/31 vs 36/52), and symmetric MRI abnormalities (26/31 vs 12/52), had less frequent involuntary movements (2/31 vs 30/52), and had absent prodromal psychobehavioral alterations (0/31 vs 27/52), CSF oligoclonal band detection (0/27 vs 11/38), tumor association (0/31 vs 13/52), or NS-Abs (0/31 vs 29/52) than those with a low score (<5). Thirty-three patients (median age, 27 years; 18 [54.5%] female) were finally regarded as C-NORSE. The sensitivity and specificity of a high score for predicting C-NORSE were 93.9% (95% CI 0.87–0.94) and 100% (95% CI 0.95–1.00), respectively.ConclusionsPatients with a high score in the indicated scale are more likely to have C-NORSE, making it a useful diagnostic tool at the early stage of SE-M before antibody test results become available.

Mitochondrial Proteome of Affected Glutamatergic Neurons in a Mouse Model of Leigh Syndrome.

Defects in mitochondrial function lead to severe neuromuscular orphan pathologies known as mitochondrial disease. Among them, Leigh Syndrome is the most common pediatric presentation, characterized by symmetrical brain lesions, hypotonia, motor and respiratory deficits, and premature death. Mitochondrial diseases are characterized by a marked anatomical and cellular specificity. However, the molecular determinants for this susceptibility are currently unknown, hindering the efforts to find an effective treatment. Due to the complex crosstalk between mitochondria and their supporting cell, strategies to assess the underlying alterations in affected cell types in the context of mitochondrial dysfunction are critical. Here, we developed a novel virus-based tool, the AAV-mitoTag viral vector, to isolate mitochondria from genetically defined cell types. Expression of the AAV-mitoTag in the glutamatergic vestibular neurons of a mouse model of Leigh Syndrome lacking the complex I subunit Ndufs4 allowed us to assess the proteome and acetylome of a subset of susceptible neurons in a well characterized model recapitulating the human disease. Our results show a marked reduction of complex I N-module subunit abundance and an increase in the levels of the assembly factor NDUFA2. Transiently associated non-mitochondrial proteins such as PKCδ, and the complement subcomponent C1Q were also increased in Ndufs4-deficient mitochondria. Furthermore, lack of Ndufs4 induced ATP synthase complex and pyruvate dehydrogenase (PDH) subunit hyperacetylation, leading to decreased PDH activity. We provide novel insight on the pathways involved in mitochondrial disease, which could underlie potential therapeutic approaches for these pathologies.

Novel ECHS1 mutations in Leigh syndrome identified by whole-exome sequencing in five Chinese families: case report

BackgroundShort-chain enoyl-CoA hydratase deficiency (ECHS1D), also known as ECHS1 deficiency, is a rare inborn metabolic disorder with clinical presentations characterized by Leigh syndrome (LS). Thirty-four different pathogenic mutations have been identified from over 40 patients to date.Case presentationHere, we report five Chinese patients with clinical syndromes typified as LS. Despite different initial symptoms, all patients presented developmental regression, dystonia, common radiological features such as symmetrical bilateral brain abnormalities, and similar metabolic results such as elevated plasma lactate and 2,3-dihydroxy-2-methylbutyrate. Utilizing whole-exome sequencing (WES), we identified eight distinct variants in ECHS1, with six novel variants, and the remaining two variants have been previously reported. Interestingly, one of the six novel variants, c.463G > A (p.Gly155Ser), was detected in three patients from unrelated families, suggesting a potential founder effect already described for a few mutations in LS. Incorporating both genetic analysis and medical results, including magnetic resonance imaging (MRI), electroencephalography (EEG), and biochemical testing, our study enriched the mutation spectrum of the ECHS1 gene and confirmed the phenotypic presentations of LS.ConclusionsThe severity of ECHS1 deficiency seems to vary. It was affected by both genetics and external environmental factors that lead to increased metabolism. Our study enriched the mutation spectrum of the ECHS1 gene, confirmed the phenotypic presentations, and highlighted the importance of the valine catabolic pathway in Leigh syndrome. Further studies are required to examine the potential founder mutation c.463G > A (p.Gly155Ser) and the role of ECHS1 in relevant pathways.

Functional Aspects of Hypothalamic Asymmetry

Anatomically, the brain is a symmetric structure. However, growing evidence suggests that certain higher brain functions are regulated by only one of the otherwise duplicated (and symmetric) brain halves. Hemispheric specialization correlates with phylogeny supporting intellectual evolution by providing an ergonomic way of brain processing. The more complex the task, the higher are the benefits of the functional lateralization (all higher functions show some degree of lateralized task sharing). Functional asymmetry has been broadly studied in several brain areas with mirrored halves, such as the telencephalon, hippocampus, etc. Despite its paired structure, the hypothalamus has been generally considered as a functionally unpaired unit, nonetheless the regulation of a vast number of strongly interrelated homeostatic processes are attributed to this relatively small brain region. In this review, we collected all available knowledge supporting the hypothesis that a functional lateralization of the hypothalamus exists. We collected and discussed findings from previous studies that have demonstrated lateralized hypothalamic control of the reproductive functions and energy expenditure. Also, sporadic data claims the existence of a partial functional asymmetry in the regulation of the circadian rhythm, body temperature and circulatory functions. This hitherto neglected data highlights the likely high-level ergonomics provided by such functional asymmetry.

Validation of a spatially variant resolution model for small animal brain PET studies

In small animal positron emission tomography (PET) studies, given the spatial resolution of preclinical PET scanners, quantification in small regions can be challenging. Moreover, in scans where animals are placed away from the center of the field of view (CFOV), e.g. in simultaneous scans of multiple animals, quantification accuracy can be compromised due to the loss of spatial resolution towards the edge of the FOV. Here, we implemented a spatially variant resolution model to improve quantification in small regions and to allow simultaneous scanning of multiple animals without compromising quantification accuracy. The scanner’s point spread function (PSF) was characterized across the FOV and modelled using a spatially variant and asymmetric Gaussian function. The spatially variant PSF (SVPSF) was then used for resolution modelling in the iterative reconstruction. To assess the image quality, a line source phantom in a cold and warm background, as well as mouse brain [18F]FDG scans, were performed. The SVPSF and the vendor’s maximum a posteriori (MAP3D) reconstructions produced uniform spatial resolution across the scanner FOV, but MAP3D resulted in lower spatial resolution. The line sources recovery coefficient using SVPSF was similar at the CFOV and at the edge of the FOV. In contrast, the other tested reconstructions produced lower recovery coefficient at the edge of the FOV. In mouse brain reconstructions, less spill-over from hot regions to cold regions, as well as more symmetric regional brain uptake was observed using SVPSF. The contrast in brain images was the highest using SVPSF, in mice scanned at the CFOV and off-center. Incorporation of a spatially variant resolution model for small animal brain PET improves quantification accuracy in small regions and produces consistent image spatial resolution across the FOV. Therefore, simultaneous scanning of multiple animals can benefit by using spatially variant resolution modelling.

Accuracy of radiologists, nonradiologists, and laypeople for identifying children with cerebral cortical atrophy from "Mercator map" curved reconstructions of MRIs of the brain.

Background:Using text reports to communicate bilateral, symmetric, and zonal cortical brain atrophy in children with term hypoxic ischemic injury (HII) to parents and legal professionals contesting compensation rights can be difficult. Using standard cross-sectional images for explaining bilateral, regional brain imaging to laypeople is also challenging. A single flattened image of the brain surface, much like a map of the earth is derived from a globe, can be generated from curved reconstruction of magnetic resonance imaging (MRI) scans, i.e., a Mercator map. Laypeople's ability to identify abnormal “Mercator brain maps,” without prior training, requires evaluation before use in nonmedical settings. Aim:To determine the sensitivity and specificity of laypeople in detecting abnormal pediatric Mercator flat-earth maps of the brain, without prior training. Methods and Materials:10 Mercator brain maps were provided to 111 participants individually. The maps comprised 5 HII, 1 cortical dysplasia, and 4 normal cases. Participants were required to identify the abnormal scans. Sensitivity and specificity overall and for participants’ subgroups were calculated. Results:Overall sensitivity and specificity were 67% and 80%, respectively. General radiologists (n = 12) had sensitivity and specificity of 91.2% and 94.6%, respectively. Laypeople (n = 54) had a sensitivity of 67% and specificity of 80%. Conclusion:The high specificity and sensitivity of radiologists validated the technique for distinguishing abnormal scans, regarding cortical pathology. High specificity of laypeople for identifying abnormal brains using Mercator maps indicates that this is a viable communication tool for demonstrating cortical MRI abnormalities of HII in children to laypersons.

Abstract WP83: Validation of a Relative Non-Contrast CT Map to Detect Early Ischemic Changes in Acute Stroke

Background: Discerning signs of early infarct on the non-contrast CT (NCCT) can be difficult. To facilitate interpretation of the NCCT we previously developed a technique to generate symmetry ratio maps of the NCCT (rNCCT maps) on which subtle (≥5%) differences in density between symmetric brain regions are enhanced. We sought to validate the rNCCT map against other measures of early infarction in a large cohort. Methods: rNCCT maps were generated for 146 ischemic stroke patients. We assessed how often a neurologist’s interpretation of the NCCT was changed when provided with the rNCCT map. The neurologist was blinded to CTP and DWI but was given the infarct hemisphere. In addition, using the 24-hour DWI as the gold standard, we assessed the sensitivity, specificity and volumetric accuracy of the rNCCT-defined infarct core and compared this to the test characteristics of CTP-defined infarct core (CBF&lt;38% threshold). Results: Addition of rNCCT overlay map changed clinician’s initial read 64.4% of the time (95% CI 56-72%); the rNCCT identified new areas of ischemia not appreciated on blinded review 86.2% of the time (95% CI 78-92%) and in 35.1% helped rule out early ischemia where the reader was unsure of its presence (95% CI 26-45%). In the 53 patients with reperfusion and follow-up MRI, specificity of rNCCT for final lesion volume was 99.5% for rNCCT [98.5-99.8%] vs. 99.8% [IQR 98.8-99.9%] for CTP (P=0.08). Sensitivity for rNCCT was 19.9% [7.1-28.1%] vs. 17.5% [4.7-32.2%] for CTP (P=0.56). Conclusions: This study validates the rNCCT map for detection of early ischemic changes. It is more quantitative and objective than a clinician’s read of the NCCT alone. The sensitivity and specificity for detecting early ischemic changes on rNCCT were comparable to those achieved with CTP. This indicates that the rNCCT could be a valuable tool in the evaluation of acute stroke patients.

Aberrant resting-state interhemispheric functional connectivity in patients with postpartum depression

The aim of this study is to investigate the alterations of interhemispheric functional connectivity in patients with postpartum depression (PPD) during resting state, and their potential correlations with clinical severity. Twenty- eight patients with PPD and twenty-five matched healthy postpartum (HP) women within 4 weeks after delivery were recruited and performed resting-state functional magnetic resonance imaging(fMRI) scans. Voxel-mirrored homotopic connectivity (VMHC), which is useful for exploring interhemispheric functional connectivity, and has been widely utilized to identify abnormal functional connectivity between the symmetrical brain regions in many diseases, was calculated in the present study, and intergroup VMHC differences in the voxel manner were analyzed. Correlations between VMHC values and clinical variables were also analyzed. Compared with HP, patients with PPD exhibited significantly decreased VMHC values in bilateral dorsomedial prefrontal cortex (dmPFC), dorsal anterior cingulate cortex (dACC) and orbitofrontal cortex (OFC). Furthermore, VMHC values within the dmPFC negatively correlated with the Edinburgh postpartum depression scale (EPDS) score. These findings suggested that functional coordination between several homotopic brain regions were impaired in patients with PPD. This study provided evidences of aberrant interhemispheric connectivity within brain regions involved in the maternal care network in PPD, and may contribute to the further understanding of the neural mechanism underlying PPD.

Unsupervised Algorithm for Brain Anomalies Localization in Electromagnetic Imaging

A brain anomaly localization algorithm in an unsupervised machine learning (ML) framework is presented for electromagnetic brain imaging. The method is based on expected value estimation and takes the advantage of the highly symmetrical human brain. The algorithm processes signals collected from pairs of antennas that are positioned symmetrically around the head, discretizes the imaging domain into pixels, and computes the statistical fields between the antennas on the left and right sides of the head. Then, it concatenates their intensities along the axis normal to the imaging domain to compute the expected value for every pixel. The computed expected values are merged into a matrix containing expected values for all pixels. Pixels with higher intensity show the likelihood of an anomaly being present at that location. The assumption on brain symmetry from the electromagnetic perspective was tested on healthy volunteers using a 14-element array system with a working frequency band of 0.5 - 2.0 GHz. The obtained average similarity is 92% and it confirms the validity of the assumption. The same system is used to test the algorithm on different scenarios in simulations and experiments using realistic 3D head phantoms designed based on MRIs of real patients. The imaging results demonstrate the capability of the proposed algorithm to localize bleeding and estimate its size with less than 10% error in less than a minute, which makes it suitable for real-time use in emergency stroke scenarios.