Magnetic Resonance Imaging Data Research Articles

Analysis of the clinical features and prognosis of neuro-Behcet's syndrome in 5 children

Objective: To investigate the clinical features and prognosis of neuro-Behçet's syndrome (NBS) in children. Method: The clinical, brain magnetic resonance imaging and laboratory data of 5 children with NBS diagnosed in the Department of Pediatrics, General Hospital of Ningxia Medical University and Department of Rheumatology and Immunology, Children's Hospital Affiliated to Capital Institute of Pediatrics from April 2014 to April 2024 were analyzed retrospectively. The follow-up method was retrospective outpatient or inpatient visit to evaluate the treatment effect of NBS. Result: Among the 5 NBS cases, 2 were male and 3 were female. The age of admission ranged from 8 to 17 years, the time from onset to diagnosis was 2 days to 4 years. Two patients had dizziness, headache and convulsions during the treatment of NBS, 1 patient had disturbance of consciousness, 1 patient gradually developed aphasia, limb movement disorder, dysphagia and muscle weakness after 4 years of Behcet's syndrome, and 1 patient had no clinical symptoms. C-reactive protein and erythrocyte sedimentation rate were increased in 4 cases, and cerebrospinal fluid white blood cells and immunoglobulin G were increased in 1 case. Brain magnetic resonance imaging of 4 children showed multiple lesions, including bilateral frontal lobe, occipital lobe, parietal lobe, periventricular and corpus callosum lesions. Brain magnetic resonance imaging showed multiple demyelinating diseases in 1 case, and cervical and thoracic magnetic resonance imaging showed slender cervical and thoracic spinal cord. All patients were treated with corticosteroids combined with immunosuppressants or biological agents. The children were followed up for 6 months to 4 years, and 4 cases had good treatment results, and 1 case finally gave up treatment. Conclusions: The clinical manifestations of NBS are not specific, and brain magnetic resonance imaging shows that the lesion location and morphology are not specific. NBS children treated with corticosteroids combined with immunosuppressive agents or biological agents have a good prognosis.

Youth Generalized Anxiety and Brain Activation States During Socioemotional Processing.

The brain enters distinct activation states to support differential cognitive and emotional processes, but little is known about how brain activation states differ in youths with clinical anxiety. To characterize brain activation states during socioemotional processing (movie stimuli) and assess associations between state characteristics and movie features and anxiety symptoms. The Healthy Brain Network is an ongoing cross-sectional study of individuals aged 5 to 21 years experiencing difficulties in school, of whom approximately 45% met criteria for a lifetime anxiety disorder diagnosis. Data used in this study are from the first 9 releases (collected in a nonclinical research setting in the New York City metropolitan area from 2015 to 2020) and include 620 youths aged 5 to 15 years (53% of whom met criteria for a lifetime anxiety disorder diagnosis) who watched an emotional video during functional magnetic resonance imaging and completed questionnaires and clinical evaluation. Of those with functional magnetic resonance imaging data, 432 youths aged 7 to 15 years also self-reported on anxiety symptoms. Data were processed and analyzed between February 2020 and August 2024. A hidden Markov model was trained to identify brain activation states across participants during video watching. Time spent in each state and the moment-to-moment probability of being in each state were extracted. Videos were annotated for emotion-specific and nonspecific information using the EmoCodes system. Self-reported anxiety symptoms were assessed using the Screen for Child Anxiety Related Disorders. Time spent in each state across the video and during and outside of peaks in negative content correlated with generalized and social anxiety scores. Among the 620 youths in the overall analysis, 369 were male and the mean (SD) age was 10.4 (2.8) years. In the anxiety symptom analysis, 263 of 432 youths were male and the mean (SD) age was 11.5 (2.2) years. Three brain activation states were identified: a high somatomotor activation state (state 1), a high cingulo-opercular network activation state (state 2), and a high ventral attention and default mode state (state 3). The probability of being in state 3 was correlated with video content that was more negative, quieter, and with less visual motion (ρ < 0.08; P < .001). Increased generalized anxiety was associated with greater time in state 3 (B, 0.10; 95% CI, 0.01 to 0.20; false discovery rate [FDR]-corrected P = .048) and less time in state 2 (B, -0.11; 95% CI, -0.21 to -0.02; FDR-corrected P = .048) when negative social cues were present. Youths entered 3 distinct brain activation states during movie watching, and youths with anxiety spent more time in a state with high ventral attention and default activation during negative socioemotional processing. Youths high in generalized anxiety may be more engaged in deeply processing negative emotional content, which may influence self-regulation. Interventions that focus on changing physiological and psychological state during negative social interactions in youths with anxiety should be considered.

Effects of childhood trauma on sustained attention in major depressive disorder: the mediating role of brain activity and functional connectivity

BackgroundSustained attention deficits were reported more significant in patients with major depressive disorder (MDD) than in healthy controls (HCs), and are pivotal in both the development and aggravation of depression. Childhood trauma is also common in MDD and the exposure to childhood trauma may impede sustained attention and increase the treatment resistance in MDD. However, the underlying neuro-mechanisms link the childhood trauma to sustained attention deficits in MDD remain unclear.MethodsWe collected resting-state functional magnetic resonance imaging data, and measured childhood trauma severity using the Childhood Trauma Questionnaire and sustained attention using the Continuous Performance Test, Identical Pairs version. After excluding subjects with significant head movement, 45 MDDs and 54 HCs were included in the analysis. We compared fractional amplitude of low-frequency fluctuation (fALFF) between the groups, conducted whole-brain correlation analysis between the fALFF and sustained attention in the MDD group, and defined significant regions as the regions of interest for the seed-to-whole brain functional connectivity (FC) analysis. We further performed mediation analyses to investigate the relationships among the childhood trauma, fALFF and FC values, and the level of sustained attention in the MDD group.ResultsCompared with HCs, MDDs exhibited higher fALFF in the right middle frontal gyrus and left inferior frontal gyrus, and lower fALFF in the bilateral insular cortex, left medial orbital superior frontal gyrus and left angular gyrus (ANG.L). Whole-brain correlation analysis showed that impaired sustained attention was associated with increased fALFF in the left postcentral gyrus (PoCG.L), and FC of PoCG.L-left precentral gyrus (PreCG.L) and ANG.L-right superior temporal gyrus (STG.R) in the MDD group. Furthermore, mediation analyses showed that the fALFF in PoCG.L, and FC of PoCG.L-PreCG.L and ANG.L-STG.R mediated the relationship between the childhood trauma and sustained attention in the MDD group.ConclusionThe fALFF in PoCG.L, and FC of PoCG.L-PreCG.L and ANG.L-STG.R might be potential neural substrate in the association between the childhood trauma and poor sustained attention in the MDDs, and might serve as potential intervention targets for the treatment of sustained attention deficits in MDDs with childhood trauma history.

Radiological Perspectives in Congenital Sensorineural Hearing Loss: Insights from Cochlear Implant Candidates

Objectives: Congenital hearing loss is a significant health concern, with diverse etiologies encompassing cochlear and cochleovestibular pathologies. Preoperative radiological evaluation in cochlear implant candidates is pivotal for treatment planning. We aim to elucidate the spectrum of radiological findings in patients with congenital hearing loss undergoing cochlear implant assessment. Methods: An analysis included 389 sensorineural hearing loss (SNHL) patients who underwent cochlear implantation at a tertiary university hospital, of which 177 were congenital SNHL. Computed tomography (CT) and magnetic resonance imaging (MRI) data were meticulously assessed for diverse congenital pathologies, focusing on congenital malformations. Results: In the congenital SNHL group, comprising 177 patients (80 females and 97 males), congenital cochleovestibular malformations were evident in 56 ears of 29 cases. Different congenital cochleovestibular malformations, ranging from labyrinthine aplasia to isolated large vestibular aqueducts, were detected. Among the various anomalies, incomplete partitions and cochlear hypoplasia emerged as more frequent patterns. Conclusions: This study offers a comprehensive radiological analysis of congenital SNHL patients undergoing cochlear implantation, revealing a spectrum of anomalies. It demonstrates the diverse nature of anomalies affecting the external auditory canal, middle ear structures, and cochleovestibular system. These insights provide a deeper understanding of congenital SNHL and contribute to developing informed treatment strategies.

Clinical and radiologic criteria to predict endoscopic third ventriculostomy success in non-communicating pediatric hydrocephalus

ObjectiveEndoscopic third ventriculocisternostomy (ETV) became the relevant treatment option for non-communicating pediatric hydrocephalus. ETV success was predicted in relation to age, diagnosis, and previous shunt implantation. Radiological factors are usually taken for indication decision-making. The aim of this study is to investigate radiological signs of non-communicating hydrocephalus for ETV success in a single-center retrospective analysis.Patients and methodsETV interventions were collected from a 10-year period (2010–2019) from our institution. Clinical patient characteristics such as prematurity, age, diagnosis, and previous shunt treatment and follow-up in terms of possible shunt implantation or revision surgeries were investigated. Radiological data was retrieved from the in-house PACS system to analyze preoperative signs for non­communicating hydrocephalus such as ventricular size, pressure gradients at the third ventricle, and any signs of obstruction from internal towards external cerebral spinal fluid communication. Fisher’s test was used to demonstrate the significance of each individual predictor. A multivariable model was built using the backward elimination method with multiple logistic regression.ResultsFrom 136 ETV interventions, 95 met the inclusion criteria (age < 18 years; > 6-month follow-up; MR image data availability, treatment goal for shunt independence). In chi-square statistical evaluation of single parameters age > 6 months (OR 32.5; 95% CI 4.8–364), ventricular width (FOHR < 0.56; OR 6.1; 95% CI 2.2–16.3) and non-post-hemorrhagic hydrocephalus as underlying diagnosis (OR 13.1; 95% CI 1.9–163) showed significant increased odds ratio for shunt independence during follow-up. Logistic regression analysis for multiple parameters showed age > 6 months (OR 29.3; 95% CI 4.1–606) together with outward bulged lamina terminalis (OR 4.6; 95% CI 1.2–19.6), smaller FOHR (continuous parameter; OR 2.83 × 10−5; 95% CI 4.7 × 10−9–0.045), and non-4th-ventricular-outlet obstruction (4thVOO; OR 0.31; 95% CI 0.09–1.02) as significant factors for ETV success.ConclusionETV has become a relevant treatment for non-communicating hydrocephalus, with typical MR image characteristics. Analyzing radiological markers as predictors for success smaller ventricular width and outward displaced lamina terminalis was relevant in combination with age > 6 months. Since the analysis is based on single-center experience, a larger cohort of patients with a multi-center approach should further investigate the combined clinical and radiological criteria.

Prediction of soft tissue sarcoma grading using intratumoral habitats and a peritumoral radiomics nomogram: a multi-center preliminary study

BackgroundAccurate identification of pathologic grade before operation is helpful for guiding clinical treatment decisions and improving the prognosis for soft tissue sarcoma (STS).PurposeTo construct and assess a magnetic resonance imaging (MRI)-based radiomics nomogram incorporating intratumoral habitats (subregions of clusters of voxels containing similar features) and peritumoral features for the preoperative prediction of the pathological grade of STS.MethodsThe MRI data of 145 patients with STS (74 low-grade and 71 high-grade) from 4 hospitals were retrospectively collected, including enhanced T1-weighted and fat-suppressed-T2-weighted sequences. The patients were divided into training cohort (n = 102) and validation cohort (n = 43). K-means clustering was used to divide intratumoral voxels into three habitats according to signal intensity. A number of radiomics features were extracted from tumor-related regions to construct radiomics prediction signatures for seven subgroups. Logistic regression analysis identified peritumoral edema as an independent risk factor. A nomogram was created by merging the best radiomics signature with the peritumoral edema. We evaluated the performance and clinical value of the model using area under the curve (AUC), calibration curves, and decision curve analysis.ResultsA multi-layer perceptron classifier model based on intratumoral habitats and peritumoral features combined gave the best radiomics signature, with an AUC of 0.856 for the validation cohort. The AUC of the nomogram in the validation cohort was 0.868, which was superior to the radiomics signature and the clinical model established by peritumoral edema. The calibration curves and decision curve analyses revealed good calibration and a high clinical application value for this nomogram.ConclusionThe MRI-based nomogram is accurate and effective for predicting preoperative grading in patients with STS.

A multi-stage feature selection method to improve classification of potential super-agers and cognitive decliners using structural brain MRI data-a UK biobank study.

Cognitive aging is described as the age-related decline in areas such as memory, executive function, reasoning, and processing speed. Super-Agers, adults over 80 years old, have cognitive function performance comparable to middle-aged adults. To improve cognitive reserve and potentially decrease Alzheimer's disease (AD) risk, it is essential to contrast changes in regional brain volumes between "Positive-Agers" who have superior cognitive performance compared to their age peers but are not 80 years old yet and aging adults who show cognitive decline (i.e., "Cognitive Decliners"). Using longitudinal cognitive tests over 7-9 years in UK Biobank, principal component analysis (PCA) was first applied to four cognitive domains to create a general cognition (GC) composite score. The GC score was then used to identify latent cognitive groups. Given cognitive groups as the target variable and structural magnetic resonance imaging (sMRI) data and demographics as predictors, we developed a multi-stage feature selection algorithm to identify the most important features. We then trained a Random Forest (RF) classifier on the final set of 54 selected sMRI and covariate predictors to distinguish between Positive-Agers and Cognitive Decliners. The RF model achieved an AUC of 73%. The top 6 features were age, education, brain total surface area, the area of pars orbitalis, mean intensity of the thalamus, and superior frontal gyrus surface area. Prediction of cognitive trajectory types using sMRI may improve our understanding of successful cognitive aging.

The Effect of Modular Degeneracy on Neuroimaging Data.

Introduction: The concept of community structure, based on modularity, is widely used to address many systems-level queries. However, its algorithm, based on the maximization of the modularity index Q, suffers from degeneracy problem, which yields a set of different possible solutions. Methods: In this work, we explored the degeneracy effect of modularity principle on resting-state functional magnetic resonance imaging (rsfMRI) data, when it is used to parcellate the cingulate cortex using data from the Human Connectome Project. We proposed a new iterative approach to address this limitation. Results: Our results show that current modularity approaches furnish a variety of different solutions, when these algorithms are repeated, leading to different number of subdivisions for the cingulate cortex. Our new proposed method, however, overcomes this limitation and generates more stable solution for the final partition. Conclusion: With this new method, we were able to mitigate the degeneracy problem and offer a tool to use modularity in a more reliable manner, when applying it to rsfMRI data.

A Prostate Imaging-Reporting and Data System version 2.1-based predictive model for clinically significant prostate cancer diagnosis.

To develop and validate a Prostate Imaging-Reporting and Data System (PI-RADS) version 2.1 (v2.1)-based predictive model for diagnosis of clinically significant prostate cancer (csPCa), integrating clinical and multiparametric magnetic resonance imaging (mpMRI) data, and compare its performance with existing models. We retrospectively analysed data from patients who underwent prospective mpMRI assessment using the PI-RADS v2.1 scoring system and biopsy at our institution between April 2019 and December 2023. A 'Clinical Baseline' model using patient demographics and laboratory results and an 'MRI Added' model additionally incorporating PI-RADS v2.1 scores and prostate volumes were created and validated on internal and external patients. Both models were compared against two previously published MRI-based algorithms for csPCa using area under the receiver operating characteristic curve (AUC) and decision curve analysis. A total of 1319 patients across internal and external cohorts were included. Our 'MRI Added' model demonstrated significantly improved discriminative ability (AUCinternal 0.88, AUCexternal 0.79) compared to our 'Clinical Baseline' model (AUCinternal 0.75, AUCexternal 0.68) (P < 0.001). The 'MRI Added' model also showed higher net benefits across various clinical threshold probabilities and compared to a 'biopsy all' approach, it reduced unnecessary biopsies (defined as biopsies without Gleason Grade Group ≥2 csPCa) by 27% in the internal cohort and 10% in the external cohort at a risk threshold of 25%. However, there was no significant difference in predictive ability and reduction in unnecessary biopsies between our model and comparative ones developed for PI-RADS v2 and v1. Our PI-RADS v2.1-based mpMRI model significantly enhances csPCa prediction, outperforming the traditional clinical model in accuracy and reduction of unnecessary biopsies. It proves promising across diverse patient populations, establishing an updated, integrated approach for detection and management of prostate cancer.

Clinical and instrumental characteristics of mild traumatic brain injury and acubarotrauma due to the impact of an explosive shock wave

BACKGROUND: Traumatic brain injuries are widespread and need to be studied, having a serious impact on health and the economy. Every year, about 69 million people experience traumatic brain injuries, including road accidents and military conflicts. A number of studies show that up to 20% of veterans who have returned from Iraq and Afghanistan, got a mild head injury. 83% of those hospitalized between 2001 and 2018 had a mild traumatic brain injuries. Pathophysiological processes in traumatic brain injuries include axon loss and demyelination, which disrupts the functioning of neural networks and manifests itself in the form of instability, cognitive decline, and mental changes. The causes of instability can be associated with damage to the vestibular apparatus, conducting pathways and connections of the cerebellum and cortical analyzers, which can be detected by modern neuroimaging methods. Stabilometry using a power platform is a promising diagnostic method for light therapy. traumatic brain injuries, which allows you to study the equilibrium function. AIM: to determine the clinical and instrumental characteristics of mild traumatic brain injury and acubarotrauma due to the impact of a shock blast wave separately and in combination. MATERIALS AND METHODS: 66 patients were selected (n = 66) aged 18 to 56 years (38.28 ± 9.98 years) who were exposed to a shock wave. Of these, 28 (42.4%) patients with mild traumatic brain injury (group 1), 21 (31.8%) patients with isolated acubarotrauma (group 2), with a combination of mild traumatic brain injury and acubarotrauma in 17 (25.8%) patients (group 3). Age, presence of chronic diseases, neurological status, neuropsychological examination, stabilometric examination, computed tomography and magnetic resonance imaging of the brain were evaluated. The table editor (MS Excel 2019) was used for statistical data processing and the program for medical and biological research (STATISTICA 12). RESULTS: the diagnosis of mild traumatic brain injury and acubarotrauma was established based on clinical recommendations. In the neurological status of all patients in groups 1 and 3, scattered organic symptoms were detected. In group 2, patients had a few isolated unstable neurological signs. According to neuropsychological testing, there was a deterioration in the results in group 3 compared to the group 1 and 2 (p 0.05). A stabilometric study showed that in group 3 significantly worse indicators of the speed of the general center of pressure, the area of the statokinesiogram with both open and closed eyes were noted compared to the other groups (p 0.05). According to the data of magnetic resonance imaging of the brain, including using SWI/SWAN sequences, diffuse micro-hemorrhages in the brain substance were not detected in the study groups. CONCLUSION: the main characteristics of mild traumatic brain injury in combination with acubarotrauma include pronounced postural instability, deterioration of stabilometric parameters and cognitive functions.

Thalamic changes in patients with chronic facial pain.

To investigate structural alterations in the thalamus in patients with primary trigeminal neuralgia and provide a detailed perspective on thalamic remodeling in response to chronic pain at the level of individual thalamic nuclei. METHODS: We analyzed a sample of 62 patients with primary trigeminal neuralgia who underwent surgical treatment, along with 28 healthy participants. Magnetic resonance imaging (MRI) data were acquired using a 3T system equipped with a 16-channel receiver head coil. Segmentation of the thalamic nuclei was performed using FreeSurfer 7.2.0. We divided the group of patients with trigeminal neuralgia into two subgroups: those with right-sided pain and those with left-sided pain. Each subgroup was compared to a control group by means of one-way ANOVA. Associations between morphometric and clinical variables were assessed with Spearman correlation coefficient. Our results revealed significant gray matter volume changes in thalamic nuclei among patients with trigeminal neuralgia. Notably, the intralaminar nuclei (centromedian/parafascicular) and nuclei associated with visual and auditory signal processing (lateral and medial geniculate bodies) exhibited significant alterations, contrasting with the ventral group nuclei involved in nociceptive processing. Additionally, we found no substantial volume increase in any of the studied nuclei following successful surgical intervention 6 months later. The volumes of thalamic nuclei were negatively correlated with pain intensity and disease duration. The results of this study, although preliminary, hold promise for clinical applications as they reveal previously unknown structural alterations in the thalamus that occur in patients with chronic trigeminal neuralgia.

Anemia-associated smaller brain volume and sex differences: a cross-sectional study of magnetic resonance imaging in brain health checkups

IntroductionAnemia is a risk factor for dementia development. However, few studies have examined the relationship between brain volume and anemia. This study aimed to analyze the association between anemia and brain volume using magnetic resonance imaging data from brain health checkups.MethodParticipants underwent brain health checkups between January 2015 and March 2022. Blood samples were collected to measure hemoglobin concentrations and mean corpuscular volumes. The modified Mini-Mental State Examination (MMSE) was used to evaluate cognitive function. Magnetic resonance images were analyzed using voxel-based Morphometry to evaluate the overall patterns of brain volume. After extracting the principal components (PCs) from PC analysis, we investigated their association with MMSE scores and anemia.ResultsThis study included 1,029 participants and identified principal components, representing smaller volume in the frontal lobe (PC1), and smaller volume in the limbic system to the temporal lobe (PC2). A higher PC2 score was significantly associated with a lower MMSE score. Male participants with anemia had smaller bilateral PC1 volumes and left hippocampal volumes, and female participants with anemia had smaller bilateral PC2 volumes and hippocampus volumes.DiscussionPC2 may represent the extent of disease affecting limbic system volume, such as Alzheimer’s disease. Our results suggest that anemia may be associated with smaller volumes in the limbic system, especially in women. Further studies are required to determine which type of anemia is more strongly correlated with smaller brain volumes.

Modelling of Human Cerebral Blood Vessels for Improved Surgical Training: Image Processing and 3D Printing

Human cerebral blood vessels are highly intricate and significantly contribute to brain function support. In the surgical process of these vessels, the neurosurgeons will basically employ magnetic resonance imaging (MRI) as an imaging media to understand the location of the disorder, the anatomical position of vessels, and a guide in the surgical process. However, the usage of MRI data remains a challenge for surgeons in understanding anatomical structures in greater detail, as well as the limitations of training in handling difficult cases. This study aims to provide further technology, combining three-dimensional (3D) image models and 3D printing to accommodate the lack of visualization and pre-operative simulation using MRI data. First, the MRI data would be exported to a software 3D slicer that has the ability to process images with a threshold method to segment the required body parts and generate 3D models. Then, the 3D model of blood vessels would be imprinted using the SLA method to provide the complex anatomical structures of blood vessels. The results from both 3D image modeling and 3D printing have been validated and have dimensions similar to those of the MRI data, indicating that this work is highly accurate. This work significantly helps the surgeons to have a better plan for the surgery steps, identify potential issues before the procedure begins, and develop more precise approaches.

Levator Veli Palatini Muscle Ratio Is a Clinically Significant Anatomic Predictor for Velopharyngeal Surgical Need.

Velopharyngeal insufficiency (VPI) poses challenges for normal speech production, often necessitating surgical intervention. Determining optimal candidates for surgery remains complex and requires a nuanced understanding of underlying anatomic factors contributing to VPI. This study aimed to identify anatomic predictors that drive surgical recommendations for VPI. Prospective observational cohort study. Pediatric tertiary care hospital. Magnetic resonance imaging data were acquired from 150 children (aged 4-17) to identify anatomic predictors of VPI and surgical need. Fourteen velopharyngeal variables were measured in the oblique coronal and midsagittal imaging planes. Calculations included differences in levator veli palatini (LVP) muscle angles of origin, mean extravelar length, differences between left and right extravelar segments, the VP Needs ratio, and a newly developed LVP ratio. Multivariate logistic regression models with k-fold cross validation were utilized to identify anatomic profiles predictive of VPI and receiving a surgical recommendation. The models demonstrated high accuracy, sensitivity, and specificity. Among anatomic variables, the LVP ratio emerged as the strongest determinant of surgical need (β = 11.256, p < .001). Notably, an increase in the LVP ratio of 0.10 is associated with a 3.08-fold increase in the likelihood of receiving a surgical recommendation. LVP ratios above 1.0 were significant for both VPI classification and surgical need. The LVP ratio significantly differentiates individuals with VPI and is predictive of surgical need for VPI management. Inclusion of the LVP ratio into clinical evaluations may refine patient stratification, enabling more precise surgical decision-making tailored to individual anatomic variations.

Low Penetrance Sarcomere Variants Contribute to Additive Risk in Hypertrophic Cardiomyopathy.

Classically, hypertrophic cardiomyopathy (HCM) has been viewed as a single-gene (monogenic) disease caused by pathogenic variants in sarcomere genes. Pathogenic sarcomere variants are individually rare and convey high risk for developing HCM (highly penetrant). Recently, important polygenic contributions have also been characterized. Low penetrance sarcomere variants (LowSVs) at intermediate frequencies and effect sizes have not been systematically investigated. We hypothesize that LowSVs may be common in HCM with substantial influence on disease risk and severity. Among all sarcomere variants observed in the Sarcomeric Human Cardiomyopathy Registry (SHaRe), we identified putative LowSVs defined by (1) population frequency greater than expected for highly penetrant (monogenic) HCM (allele frequency >5×10-5 in the Genome Aggregation Database, gnomAD) and (2) moderate enrichment (>2×) in patients with HCM compared with gnomAD. LowSVs were examined for their association with disease severity and clinical outcomes. Functional effects of selected LowSVs were assessed using induced pluripotent stem cell-derived cardiomyocytes. Association of LowSVs with HCM-adjacent traits in the general population was tested using UK Biobank cardiac magnetic resonance imaging data. Among 6045 patients and 1159 unique variants in sarcomere genes, 12 LowSVs were identified. LowSVs were collectively common in the general population (1:350) and moderately enriched in HCM (aggregate odds ratio, 14.9 [95% CI, 12.5-17.9]). Isolated LowSVs were associated with an older age of HCM diagnosis and fewer adverse events. However, LowSVs in combination with a pathogenic sarcomere variant conferred higher morbidity (eg, composite adverse event hazard ratio, 5.4 [95% CI, 3.0-9.8] versus single pathogenic sarcomere variant, 2.0 [95% CI, 1.8-2.2]; P<0.001). An intermediate functional impact was validated for 2 specific LowSVs-MYBPC3 c.442G>A (partial splice gain) and TNNT2 c.832C>T (intermediate effect on contractile mechanics). Cardiac magnetic resonance imaging analysis of the general population revealed 5 of 12 LowSVs were significantly associated with HCM-adjacent traits without overt HCM. This study establishes a new class of low penetrance sarcomere variants that are relatively common in the population. When penetrant, isolated LowSVs cause mild HCM. In combination with pathogenic sarcomere variants, LowSVs markedly increase disease severity, supporting a clinically significant additive effect. Last, LowSVs also contribute to age-related remodeling even in the absence of overt HCM.

Functional Connectivity Biomarker Extraction for Schizophrenia Based on Energy Landscape Machine Learning Techniques.

Brain connectivity represents the functional organization of the brain, which is an important indicator for evaluating neuropsychiatric disorders and treatment effects. Schizophrenia is associated with impaired functional connectivity but characterizing the complex abnormality patterns has been challenging. In this work, we used resting-state functional magnetic resonance imaging (fMRI) data to measure functional connectivity between 55 schizophrenia patients and 63 healthy controls across 246 regions of interest (ROIs) and extracted the disease-related connectivity patterns using energy landscape (EL) analysis. EL analysis captures the complexity of brain function in schizophrenia by focusing on functional brain state stability and region-specific dynamics. Age, sex, and smoker demographics between patients and controls were not significantly different. However, significant patient and control differences were found for the brief psychiatric rating scale (BPRS), auditory perceptual trait and state (APTS), visual perceptual trait and state (VPTS), working memory score, and processing speed score. We found that the brains of individuals with schizophrenia have abnormal energy landscape patterns between the right and left rostral lingual gyrus, and between the left lateral and orbital area in 12/47 regions. The results demonstrate the potential of the proposed imaging analysis workflow to identify potential connectivity biomarkers by indexing specific clinical features in schizophrenia patients.

Diagnostic errors in assessing magnetic resonance imaging semiotics of primary extracerebral tumors: a case series

Primary extracerebral tumors are represented by benign and malignant neoplasms of the meninges and cranial nerves. Their presurgical differential diagnosis is based on the analysis of magnetic resonance imaging semiotics. The critically significant aspects for classifying tumors of this group include the following: neoplasm structure, contrast enhancement type, delimiting from the brain tissue, and relationship with the meninges or cranial nerves. Differential diagnosis of extracerebral tumors based on visual analysis of magnetic resonance imaging data is generally not challenging because most tumors have typical magnetic resonance imaging semiotics. However, in cases with atypical magnetic resonance imaging signs, reliable differentiation of tumors can be challenging. Moreover, the greatest complexity is the differentiation of meningioma grades, distinction between solitary fibrous tumors and meningiomas, and identification of the tumor type when localized in the cerebellopontine angles. The case series presented the most typical features leading to errors in the differential diagnosis of primary extracerebral tumors. All the presented tumors were verified with postsurgical histological examination. The analysis of the case reports demonstrates that a review of the combined semiotic signs can lower the number of diagnostic errors.

Olfactory training affects the correlation between brain structure and functional connectivity.

and background: Neuroimaging studies have increasingly found functional connectivity (FC) changes and structural cortical abnormalities in patients with post-traumatic anosmia (PTA). Training and repeated exposure to odorants lead to enhanced olfactory capability. This study is conducted to investigate the correlations between FC and cortical thickness on the olfaction-related regions of the brain in PTA after olfactory training (OT). Twenty-five PTA patients were randomly divided in three groups: (1) 9 control patients who did not receive any training, (2) 9 patients underwent classical OT by 4 fixed odors, and (3) 7 patients underwent modified OT coming across 4 sets of 4 different odors sequentially. Before and after the training period, all patients performed olfactory function tests, and magnetic resonance imaging (MRI). Sniffin' Sticks test was used to assess olfactory function. MRI data were analyzed using functional connectivity analysis and brain morphometry. Modified OT resulted in heightened activation in the medial orbitofrontal cortex and anterior cingulate cortex and increased FC between the piriform cortex (PIRC) and the caudate cortex. Conversely, classical OT induced increased activation in the insula cortex and greater FC between the PIRC and the pre-central gyrus. Furthermore, after OT, both training groups achieved significantly improved scores in the changes in brain connectivity associated with OT, which were attributable to anatomical measures. This study demonstrates that intensive olfactory training can enhance functional connectivity, and this improvement correlates with structural changes in the brain's olfactory processing areas.

Aberrant network topological structure of sensorimotor superficial white-matter system in major depressive disorder.

White-matter tracts play a pivotal role in transmitting sensory and motor information, facilitating interhemispheric communication and integrating different brain regions. Meanwhile, sensorimotor disturbance is a common symptom in patients with major depressive disorder (MDD). However, the role of aberrant sensorimotor white-matter system in MDD remains largely unknown. Herein, we investigated the topological structure alterations of white-matter morphological brain networks in 233 MDD patients versus 257 matched healthy controls (HCs) from the DIRECT consortium. White-matter networks were derived from magnetic resonance imaging (MRI) data by combining voxel-based morphometry (VBM) and three-dimensional discrete wavelet transform (3D-DWT) approaches. Support vector machine (SVM) analysis was performed to discriminate MDD patients from HCs. The results indicated that the network topological changes in node degree, node efficiency, and node betweenness were mainly located in the sensorimotor superficial white-matter system in MDD. Using network nodal topological properties as classification features, the SVM model could effectively distinguish MDD patients from HCs. These findings provide new evidence to highlight the importance of the sensorimotor system in brain mechanisms underlying MDD from a new perspective of white-matter morphological network.

Capturing inter-individual variability in stress dynamics with heart rate traces reveals activity in the bilateral hippocampus, amygdala, and insula

Abstract Abnormalities in the neural mechanisms of the stress response have the potential to serve as a transdiagnostic marker for stress-related disorders. This potential is rooted in the highly individual and dynamic stress response, which poses a challenge to classical experimentally informed models that focus on specific phases, conditions, or stimuli during a stress task. Here, we integrate individual heart rates (HR) as an immanent index of the stress-response and combine these with functional magnetic resonance imaging (fMRI) data. In this study, 83 healthy participants completed a multimodal psychosocial imaging stress task comprising three different task phases (PreStress, Stress, and PostStress), with each phase consisting of five 60 s blocks of active task interleaved with 40 s of rest, and simultaneous recordings of pulse plethysmography. Participants were asked to solve mental calculations and were exposed to negative social feedback during the Stress phase. We estimated a general linear model (GLM) with individual heart rates averaged per active block as a single parametric modulator of the task regressor across all 15 active blocks irrespective of the task phase. Results revealed a negative correlation between HR and activation in the bilateral amygdala and anterior hippocampus as well as deactivation in the default mode network. Positive correlations with HR were detected in the bilateral insular cortex, bilateral angular gyrus, and parts of the inferior and superior parietal lobes. In summary, our findings emphasize the utility of integrating the commonly assessed cardiovascular stress response (here: HR) as an immediate index of the participant’s stress status. We conclude that by such integration, brain regions involved in regulating the acute stress response, such as the anterior hippocampus and amygdala, are detected more sensitively by tracking the individual’s “stress wave” rather than treating every experimental block uniformly. Our approach may serve as a complementary analysis to the task-regressor based model.