Association Between Taurine Level in the Hippocampus and Major Depressive Disorder in Young Women: A Proton Magnetic Resonance Spectroscopy Study at 7T.

BACKGROUND: Major depressive disorder (MDD) is characterized by depressed mood or loss of interest or pleasure. Generally, women are twice as likely as men to have depression. Taurine, a type of amino acid, plays critical roles in neuronal generation, differentiation, arborization, and formation of synaptic connections. Importantly, it enhances proliferation and synaptogenesis in the hippocampus. When injected into animals, taurine has an antidepressant effect. However, there is no in vivo evidence to show an association between taurine concentration in the human brain and the development of MDD. METHODS: Forty-one unmedicated young women with MDD (ages 18-29) and 43 healthy control participants matched for gender and age were recruited in South Korea. Taurine concentration was measured in the hippocampus, anterior cingulate cortex, and occipital cortex of the MDD and healthy control groups using proton magnetic resonance spectroscopy at 7T. Analysis of covariance was used to examine differences in taurine concentration, adjusting for age as a covariate. RESULTS: Taurine concentration in the hippocampus was lower (F1,75 = 5.729, p = .019, Δη2 = 0.073) for the MDD group (mean [SEM] = 0.91 [0.06] mM) than for the healthy control group (1.13 [0.06] mM). There was no significant difference in taurine concentration in the anterior cingulate cortex or occipital cortex between the two groups. CONCLUSIONS: This study demonstrates that a lower level of taurine concentration in the hippocampus may be a novel characteristic of MDD.

Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation.

OBJECTIVES: The Image Biomarker Standardization Initiative has helped improve the computational reproducibility of MRI radiomics features. Nonetheless, the MRI sequences and features with high imaging reproducibility are yet to be established. To determine reproducible multiparametric MRI radiomics features across test-retest, multi-scanner, and computational reproducibility comparisons, and to evaluate their clinical value in brain tumor diagnosis. METHODS: To assess reproducibility, T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) were acquired from three 3-T MRI scanners using standardized phantom, and radiomics features were extracted using two computational algorithms. Reproducible radiomics features were selected when the concordance correlation coefficient value above 0.9 across multiple sessions, scanners, and computational algorithms. Random forest classifiers were trained with reproducible features (n = 117) and validated in a clinical cohort (n = 50) to evaluate whether features with high reproducibility improved the differentiation of glioblastoma from primary central nervous system lymphomas (PCNSLs). RESULTS: Radiomics features from T2WI demonstrated higher repeatability (65-94%) than those from DWI (38-48%) or T1WI (2-92%). Across test-retest, multi-scanner, and computational comparisons, T2WI provided 41 reproducible features, DWI provided six, and T1WI provided two. The performance of the classification model with reproducible features was higher than that using non-reproducible features in both training set (AUC, 0.916 vs. 0.877) and validation set (AUC, 0.957 vs. 0.869). CONCLUSION: Radiomics features with high reproducibility across multiple sessions, scanners, and computational algorithms were identified, and they showed higher diagnostic performance than non-reproducible radiomics features in the differentiation of glioblastoma from PCNSL. CLINICAL RELEVANCE STATEMENT: By identifying the radiomics features showing higher multi-machine reproducibility, our results also demonstrated higher radiomics diagnostic performance in the differentiation of glioblastoma from PCNSL, paving the way for further research designs and clinical application in neuro-oncology. KEY POINTS: • Highly reproducible radiomics features across multiple sessions, scanners, and computational algorithms were identified using phantom and applied to clinical diagnosis. • Radiomics features from T2-weighted imaging were more reproducible than those from T1-weighted and diffusion-weighted imaging. • Radiomics features with good reproducibility had better diagnostic performance for brain tumors than features with poor reproducibility.

Relationship between disproportionately enlarged subarachnoid-space hydrocephalus and white matter tract integrity in normal pressure hydrocephalus.

Normal pressure hydrocephalus (NPH) patients had altered white matter tract integrities on diffusion tensor imaging (DTI). Previous studies suggested disproportionately enlarged subarachnoid space hydrocephalus (DESH) as a prognostic sign of NPH. We examined DTI indices in NPH subgroups by DESH severity and clinical symptoms. This retrospective case-control study included 33 NPH patients and 33 age-, sex-, and education-matched controls. The NPH grading scales (0-12) were used to rate neurological symptoms. Patients with NPH were categorized into two subgroups, high-DESH and low-DESH groups, by the average value of the DESH scale. DTI indices, including fractional anisotropy, were compared across 14 regions of interest (ROIs). The high-DESH group had increased axial diffusivity in the lateral side of corona radiata (1.43 ± 0.25 vs. 1.72 ± 0.25, p = 0.04), and showed decreased fractional anisotropy and increased mean, and radial diffusivity in the anterior and lateral sides of corona radiata and the periventricular white matter surrounding the anterior horn of lateral ventricle. In patients with a high NPH grading scale, fractional anisotropy in the white matter surrounding the anterior horn of the lateral ventricle was significantly reduced (0.36 ± 0.08 vs. 0.26 ± 0.06, p = 0.03). These data show that DESH may be a biomarker for DTI-detected microstructural alterations and clinical symptom severity.

Major Intraoperative Complications During Minimally Invasive Esophagectomy.

BACKGROUND: Studies have shown minimally invasive esophagectomy (MIE) to be a feasible surgical technique in treating esophageal carcinoma. Postoperative complications have been extensively reviewed, but literature focusing on intraoperative complications is limited. The main objective of this study was to report major intraoperative complications and 90-day mortality during MIE for cancer. METHODS: Data were collected retrospectively from 10 European esophageal surgery centers. All intention-to-treat, minimally invasive laparoscopic/thoracoscopic esophagectomies with gastric conduit reconstruction for esophageal and GE junction cancers operated on between 2003 and 2019 were reviewed. Major intraoperative complications were defined as loss of conduit, erroneous transection of vascular structures, significant injury to other organs including bowel, heart, liver or lung, splenectomy, or other major complications including intubation injuries, arrhythmia, pulmonary embolism, and myocardial infarction. RESULTS: Amongst 2862 MIE cases we identified 98 patients with 101 intraoperative complications. Vascular injuries were the most prevalent, 41 during laparoscopy and 19 during thoracoscopy, with injuries to 18 different vessels. There were 24 splenic vascular or capsular injuries, 11 requiring splenectomies. Four losses of conduit due to gastroepiploic artery injury and six bowel injuries were reported. Eight tracheobronchial lesions needed repair, and 11 patients had significant lung parenchyma injuries. There were 2 on-table deaths. Ninety-day mortality was 9.2%. CONCLUSIONS: This study offers an overview of the range of different intraoperative complications during minimally invasive esophagectomy. Mortality, especially from intrathoracic vascular injuries, appears significant.

Deep Learning of Time-Signal Intensity Curves from Dynamic Susceptibility Contrast Imaging Enables Tissue Labeling and Prediction of Survival in Glioblastoma.

BACKGROUND AND PURPOSE: An autoencoder can learn representative time-signal intensity patterns to provide tissue heterogeneity measures using dynamic susceptibility contrast MR imaging. The aim of this study was to investigate whether such an autoencoder-based pattern analysis could provide interpretable tissue labeling and prognostic value in isocitrate dehydrogenase (IDH) wild-type glioblastoma. MATERIALS AND METHODS: Preoperative dynamic susceptibility contrast MR images were obtained from 272 patients with IDH wild-type glioblastoma (training and validation, 183 and 89 patients, respectively). The autoencoder was applied to the dynamic susceptibility contrast MR imaging time-signal intensity curves of tumor and peritumoral areas. Representative perfusion patterns were defined by voxelwise K-means clustering using autoencoder latent features. Perfusion patterns were labeled by comparing parameters with anatomic reference tissues for baseline, signal drop, and percentage recovery. In the validation set (n = 89), a survival model was created from representative patterns and clinical predictors using Cox proportional hazard regression analysis, and its performance was calculated using the Harrell C-index. RESULTS: Eighty-nine patients were enrolled. Five representative perfusion patterns were used to characterize tissues as high angiogenic tumor, low angiogenic/cellular tumor, perinecrotic lesion, infiltrated edema, and vasogenic edema. Of these, the low angiogenic/cellular tumor (hazard ratio, 2.18; P = .047) and infiltrated edema patterns (hazard ratio, 1.88; P = .009) in peritumoral areas showed significant prognostic value. The combined perfusion patterns and clinical predictors (C-index, 0.72) improved prognostication when added to clinical predictors (C-index, 0.55). CONCLUSIONS: The autoencoder perfusion pattern analysis enabled tissue characterization of peritumoral areas, providing heterogeneity and dynamic information that may provide useful prognostic information in IDH wild-type glioblastoma.

Role of White Matter Abnormalities in the Relationship Between Microbleed Burden and Cognitive Impairment in Cerebral Amyloid Angiopathy.

BACKGROUND: Cerebral amyloid angiopathy (CAA) often presents as cognitive impairment, but the mechanism of cognitive decline is unclear. Recent studies showed that number of microbleeds were associated with cognitive decline. OBJECTIVE: We aimed to investigate how microbleeds contribute to cognitive impairment in association with white matter tract abnormalities or cortical thickness in CAA. METHODS: This retrospective comparative study involved patients with probable CAA according to the Boston criteria (Aß+ CAA) and patients with Alzheimer's disease (Aß+ AD), all of whom showed severe amyloid deposition on amyloid PET. Using mediation analysis, we investigated how FA or cortical thickness mediates the correlation between the number of lobar microbleeds and cognition. RESULTS: We analyzed 30 patients with Aß+ CAA (age 72.2±7.6, female 53.3%) and 30 patients with Aß+ AD (age 71.5±7.6, female 53.3%). The two groups showed similar degrees of cortical amyloid deposition in AD-related regions. The Aß+ CAA group had significantly lower FA values in the clusters of the posterior area than did the Aß+ AD group(family-wise error-corrected p < 0.05). The correlation between the number of lobar microbleeds and visuospatial function was indirectly mediated by white matter tract abnormality of right posterior thalamic radiation (PTR) and tapetum, while lobar microbleeds and language function was indirectly mediated by the abnormality of left PTR and sagittal stratum. Cortical thickness did not mediate the association between lobar microbleeds and cognition. CONCLUSION: This result supports the hypothesis that microbleeds burden leads to white matter tract damage and subsequent cognitive decline in CAA.

A case of remarkable response to atezolizumab in ALK-translocated metastatic lung adenocarcinoma.

The development of resistance to tyrosine kinase inhibitors (TKIs) in metastatic non-small cell lung cancer (NSCLC) with oncogenic driver mutations highlights the challenge in improving the survival of these patients. The standard of care for ALK-rearranged advanced NSCLC refractory to various generations of ALK TKIs falls back to the use of chemotherapy and the prognosis remains poor. We report the case of a 41-year-old lady with an ALK-translocated metastatic lung adenocarcinoma, who demonstrated good response to an immune checkpoint inhibitor, atezolizumab in combination with bevacizumab and chemotherapy (pemetrexed and carboplatin), following disease progression on three generations of ALK TKIs. Six months into treatment, she continues to show improvement in her health-related quality of life and is tolerating treatment well. Our case suggests that this treatment regimen is a potential treatment option for TKI-refractory driver-mutated NSCLC.

Extrahippocampal Radiomics Analysis Can Potentially Identify Laterality in Patients With MRI-Negative Temporal Lobe Epilepsy.

Objective: The objective of the study was to investigate whether radiomics features of extrahippocampal regions differ between patients with epilepsy and healthy controls, and whether any differences can identify patients with magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE). Methods: Data from 36 patients with hippocampal sclerosis (HS) and 50 healthy controls were used to construct a radiomics model. A total of 1,618 radiomics features from the affected hippocampal and extrahippocampal regions were compared with features from healthy controls and the unaffected side of patients. Using a stepwise selection method with a univariate t-test and elastic net penalization, significant predictors for identifying TLE were separately selected for the hippocampus (H+) and extrahippocampal region (H-). Each model was independently validated with an internal set of MRI-negative adult TLE patients (n = 22) and pediatric validation cohort with MRI-negative TLE (n = 20) from another tertiary center; diagnostic performance was calculated using area under the curve (AUC) of the receiver-operating-characteristic curve analysis. Results: Forty-eight significant H+ radiomic features and 99 significant H- radiomic features were selected from the affected side of patients and used to create a hippocampus model and an extrahippocampal model, respectively. Texture features were the most frequently selected feature. Training set showed slightly higher accuracy between hippocampal (AUC = 0.99) and extrahippocampal model (AUC = 0.97). In the internal validation and external validation sets, the extrahippocampal model (AUC = 0.80 and 0.92, respectively) showed higher diagnostic performance for identifying the affected side of patients than the hippocampus model (AUC = 0.67 and 0.69). Significance: Radiomics revealed extrahippocampal abnormality in the affected side of patients with TLE and could potentially help to identify MRI-negative TLE. Classification of Evidence: Class IV Criteria for Rating Diagnostic Accuracy Studies.

FDG-PET patterns associated with ideomotor apraxia and imitation apraxia in patients with corticobasal syndrome.

INTRODUCTION: Apraxia is a core clinical feature of corticobasal syndrome (CBS). Among the subtypes of apraxia, ideomotor and imitation apraxia are frequently found in CBS. However, little is known about the brain networks that are characteristic of each apraxia subtype or their clinical implication. In this study, we used 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to explore the specific patterns of glucose hypometabolism that are characteristic of apraxia subtypes by focusing on ideomotor and imitation apraxia. METHODS: We compared the areas of glucose hypometabolism in the brains of 52 patients with CBS and 13 healthy controls, both as a whole and according to apraxia subtypes. In addition, we investigated the relationship between the apraxia subtypes and the clinical phenotype of CBS. RESULTS: In patients with CBS, common hypometabolism was observed in the frontal gyrus, precentral gyrus and caudate regardless of apraxia subtypes. In particular, ideomotor apraxia was associated with hypometabolism in the angular gyrus, while imitation apraxia was associated with hypometabolism in the posterior part including the postcentral gyrus, precuneus, and posterior cingulate gyrus. Patients who showed both ideomotor and imitation apraxia were more likely to show the typical features of CBS and progressive supranuclear palsy compared with patients showing only one type of apraxia. CONCLUSION: Group comparison analysis using FDG-PET revealed distinct pathways of ideomotor and imitation apraxia in CBS. These findings add to our understanding of the brain networks underlying apraxia in association with the clinical features of CBS.

Early Impairment in the Ventral Visual Pathway Can Predict Conversion to Dementia in Patients With Amyloid-negative Amnestic Mild Cognitive Impairment.

BACKGROUND: Around 15% to 20% of patients with clinically probable Alzheimer disease have been found to have no significant Alzheimer pathology on amyloid positron emission tomography. A previous study showed that conversion to dementia from amyloid-negative mild cognitive impairment (MCI) was observed in up to 11% of patients, drawing attention to this condition. OBJECT: We gathered the detailed neuropsychological and neuroimaging data of this population to elucidate factors for conversion to dementia from amyloid-negative amnestic MCI. METHODS: This study was a single-institutional, retrospective cohort study of amyloid-negative MCI patients over age 50 with at least 36 months of follow-up. All subjects underwent detailed neuropsychological testing, 3 tesla brain magnetic resonance imaging), and fluorine-18(18F)-florbetaben amyloid positron emission tomography scans. RESULTS: During the follow-up period, 39 of 107 (36.4%) patients converted to dementia from amnestic MCI. The converter group had more severe impairment in all visual memory tasks. The volumetric analysis revealed that the converter group had significantly reduced total hippocampal volume on the right side, gray matter volume in the right lateral temporal, lingual gyri, and occipital pole. CONCLUSION: Our study showed that reduced gray matter volume related to visual memory processing may predict clinical progression in this amyloid-negative MCI population.

Dual HER2 blockade with lapatinib and trastuzumab in combination with chemotherapy in metastatic gastroesophageal adenocarcinoma.

The development of resistance to trastuzumab in HER2-positive gastroesophageal cancer remains a problem. The use of dual HER2 blockade to overcome this is a therapeutic strategy that should be researched more extensively.

Patient-reported outcomes after oesophagectomy in the multicentre LASER study.

BACKGROUND: Data on the long-term symptom burden in patients surviving oesophageal cancer surgery are scarce. The aim of this study was to identify the most prevalent symptoms and their interactions with health-related quality of life. METHODS: This was a cross-sectional cohort study of patients who underwent oesophageal cancer surgery in 20 European centres between 2010 and 2016. Patients had to be disease-free for at least 1 year. They were asked to complete a 28-symptom questionnaire at a single time point, at least 1 year after surgery. Principal component analysis was used to assess for clustering and association of symptoms. Risk factors associated with the development of severe symptoms were identified by multivariable logistic regression models. RESULTS: Of 1081 invited patients, 876 (81.0 per cent) responded. Symptoms in the preceding 6 months associated with previous surgery were experienced by 586 patients (66.9 per cent). The most common severe symptoms included reduced energy or activity tolerance (30.7 per cent), feeling of early fullness after eating (30.0 per cent), tiredness (28.7 per cent), and heartburn/acid or bile regurgitation (19.6 per cent). Clustering analysis showed that symptoms clustered into six domains: lethargy, musculoskeletal pain, dumping, lower gastrointestinal symptoms, regurgitation/reflux, and swallowing/conduit problems; the latter two were the most closely associated. Surgical approach, neoadjuvant therapy, patient age, and sex were factors associated with severe symptoms. CONCLUSION: A long-term symptom burden is common after oesophageal cancer surgery.

Utility of 7 Tesla Magnetic Resonance Imaging in Patients With Epilepsy: A Systematic Review and Meta-Analysis.

Objective: 7 Tesla magnetic resonance imaging (MRI) enables high resolution imaging and potentially improves the detection of morphologic abnormalities in patients with epilepsy. However, its added value compared with conventional 1.5T and 3.0T MRI is unclear. We reviewed the evidence for the use of 7 Tesla MRI in patients with epilepsy and compared the detection rate of focal lesions with clinical MRI. Methods: Clinical retrospective case studies were identified using the indexed text terms "epilepsy" AND "magnetic resonance imaging" OR "MR imaging" AND "7T" OR "7 Tesla" OR "7T" in Medline (2002-September 1, 2020) and Embase (1999-September 1, 2020). The study setting, MRI protocols, qualitative, and quantitative assessment were systematically reviewed. The detection rate of morphologic abnormalities on MRI was reported in each study in which surgery was used as the reference standard. Meta-analyses were performed using a univariate random-effects model in diagnostic performance studies with patients that underwent both 7T MRI and conventional MRI. Results: Twenty-five articles were included (467 patients and 167 healthy controls) consisting of 10 case studies, 10 case-control studies, 4 case series, and 1 cohort study. All studies included focal epilepsy; 12 studies (12/25, 48%) specified the disease etiology and 4 studies reported focal but non-lesional (MRI-negative on 1.5/3.0T) epilepsy. 7T MRI showed superior detection and delineation of morphologic abnormalities in all studies. In nine comparative studies, 7T MRI had a superior detection rate of 65% compared with the 22% detection rate of 1.5T or 3.0T. Significance: 7T MRI is useful for delineating morphologic abnormalities with a higher detection rate compared with conventional clinical MRI. Most studies were conducted using a case series or case study; therefore, a cohort study design with clinical outcomes is necessary. Classification of Evidence: Class IV Criteria for Rating Diagnostic Accuracy Studies.

Clinical Features and Brain MRI Findings in Korean Patients with AGel Amyloidosis.

PURPOSE: AGel amyloidosis is systemic amyloidosis caused by pathogenic variants in the GSN gene. In this study, we sought to characterize the clinical and brain magnetic resonance image (MRI) features of Korean patients with AGel amyloidosis. MATERIALS AND METHODS: We examined 13 patients with AGel amyloidosis from three unrelated families. Brain MRIs were performed in eight patients and eight age- and sex-matched healthy controls. Therein, we analyzed gray and white matter content using voxel-based morphometry (VBM), tract-based spatial statistics (TBSS), and FreeSurfer. RESULTS: The median age at examination was 73 (interquartile range: 64-76) years. The median age at onset of cutis laxa was 20 (interquartile range: 15-30) years. All patients over that age of 60 years had dysarthria, cutis laxa, dysphagia, and facial palsy. Two patients in their 30s had only mild cutis laxa. The median age at dysarthria onset was 66 (interquartile range: 63.5-70) years. Ophthalmoparesis was observed in three patients. No patient presented with muscle weakness of the limbs. Axial fluid-attenuated inversion recovery images of the brain showed no significant differences between the patient and control groups. Also, analysis of VBM, TBSS, and FreeSurfer revealed no significant differences in cortical thickness between patients and healthy controls at the corrected significance level. CONCLUSION: Our study outlines the clinical manifestations of prominent bulbar palsy and early-onset cutis laxa in 13 Korean patients with AGel amyloidosis and confirms that AGel amyloidosis mainly affects the peripheral nervous system rather than the central nervous system.

Diagnostic accuracy of Doppler ultrasound for detecting hepatic artery stenosis after liver transplantation.

AIM: To evaluate the diagnostic accuracy of Doppler ultrasound (DUS) in detecting hepatic artery stenosis (HAS) after liver transplantation using computed tomography angiography (CTA) as the reference standard. MATERIALS AND METHODS: This study included data from January 2005 to November 2017, where DUS of the hepatic artery of living and deceased donor liver grafts were compared with the reference standard, CTA. DUS parameters, such as intrahepatic artery (IHA) peak systolic velocity (PSV), resistive index (RI), systolic acceleration time (SAT); and extrahepatic artery (EHA) PSV were taken. The optimum cut-off was estimated using area under the receiver operating characteristic curve (AUC). Multivariable logistic regression analysis was developed to predict HAS. RESULTS: Ninety-nine liver transplant cases were retrieved, 50 met the inclusion criteria where nine patients had significant HAS. HAS patients had a significantly low IHAPSV with a cut-off of 35.1 cm/s (sensitivity 53.8%, specificity 78.4%, AUC 0.701). IHARI had a significantly low RI with a cut-off 0.585 (sensitivity 86.7%, specificity 85.4%, AUC 0.913). The IHASAT cut-off was 0.045 seconds (sensitivity 80%, specificity 91.4%, AUC 0.857). The EHAPSV cut-off was 197.4 cm/s (sensitivity 50%, specificity 99.1%, AUC 0.648). The prediction model using DUS parameters IHARI and IHASAT demonstrated good discrimination with an AUC of 0.930 (95% CI: 0.843, 1.000; sensitivity 93.3%, specificity 88%). CONCLUSION: A prediction model using the DUS parameters IHARI and IHASAT showed good diagnostic accuracy of 88.6% for monitoring liver transplant patients. If validated externally, this DUS model could be utilised to diagnose HAS in liver transplant recipients.

The cerebellum could serve as a potential imaging biomarker of dementia conversion in patients with amyloid-negative amnestic mild cognitive impairment.

BACKGROUND AND PURPOSE: As part of network-specific neurodegeneration, changes in cerebellar gray matter (GM) volume and impaired cerebello-cerebral functional networks have been reported in Alzheimer disease (AD). Compared with healthy controls, a volume loss in the cerebellum has been observed in patients with continuum of AD. However, little is known about the anatomical or functional changes in patients with clinical AD but no brain amyloidosis. We aimed to identify the relationship between cerebellar volume and dementia conversion of amyloid-negative mild cognitive impairment (MCI). METHODS: This study was a retrospective cohort study of patients over the age 50 years with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center with no less than a 36-month follow-up period. All subjects underwent detailed neuropsychological tests, 3 T brain magnetic resonance imaging scans including three-dimensional T1 imaging, and fluorine-18[F18 ]-florbetaben amyloid positron emission tomography scans. A spatially unbiased atlas template of the cerebellum and brainstem was used for analyzing cerebellar GM volume. RESULTS: During the 36 months of follow-up, 39 of 107 (36.4%) patients converted to dementia from amnestic MCI. The converter group had more severe impairments in all visual memory tasks. In terms of volumetric analysis, reduced crus I/II volume adjusted with total intracranial volume, and age was observed in the converter group. CONCLUSIONS: Significant cerebellar GM atrophy involving the bilateral crus I/II may be a novel imaging biomarker for predicting dementia progression in amyloid-negative amnestic MCI patients.

Altered Effective Connectivity within the Fronto-Limbic Circuitry in Response to Negative Emotional Task in Female Patients with Major Depressive Disorder.

Background: Major depressive disorder (MDD) is a mood disorder associated with disruptions in emotional control. Previous studies have investigated abnormal regional activity and connectivity within the fronto-limbic circuit. However, condition-specific connectivity changes and their association with the pathophysiology of MDD remain unexplored. This study investigated effective connectivity in the fronto-limbic circuit induced by negative emotional processing from patients with MDD. Methods: Thirty-four unmedicated female patients with MDD and 28 healthy participants underwent event-related functional magnetic resonance imaging at 7T while viewing emotionally negative and neutral images. Brain regions whose dynamics are driven by experimental conditions were identified by using statistical parametric mapping. Effective connectivity among regions of interest was then estimated by using dynamic causal modeling. Results: Patients with MDD had lower activation of the orbitofrontal cortex (OFC) and higher activation of the parahippocampal gyrus (PHG) than healthy controls (HC). In association with these regional changes, we found that patients with MDD did not have significant modulatory connections from the primary visual cortex (V1) to OFC, whereas those connections of HC were significantly positively modulated during negative emotional processing. Regarding the PHG activity, patients with MDD had greater modulatory connection from the V1, but reduced negative modulatory connection from the OFC, compared with healthy participants. Conclusions: These results imply that disrupted effective connectivity among regions of the OFC, PHG, and V1 may be closely associated with the impaired regulation of negative emotional processing in the female patients with MDD.

Fit-for-Discharge Criteria after Esophagectomy: An International Expert Delphi Consensus.

There are no internationally recognized criteria available to determine preparedness for hospital discharge after esophagectomy. This study aims to achieve international consensus using Delphi methodology. The expert panel consisted of 40 esophageal surgeons spanning 16 countries and 4 continents. During a 3-round, web-based Delphi process, experts voted for discharge criteria using 5-point Likert scales. Data were analyzed using descriptive statistics. Consensus was reached if agreement was ≥75% in round 3. Consensus was achieved for the following basic criteria: nutritional requirements are met by oral intake of at least liquids with optional supplementary nutrition via jejunal feeding tube. The patient should have passed flatus and does not require oxygen during mobilization or at rest. Central venous catheters should be removed. Adequate analgesia at rest and during mobilization is achieved using both oral opioid and non-opioid analgesics. All vital signs should be normal unless abnormal preoperatively. Inflammatory parameters should be trending down and close to normal (leucocyte count ≤12G/l and C-reactive protein ≤80 mg/dl). This multinational Delphi survey represents the first expert-led process for consensus criteria to determine 'fit-for-discharge' status after esophagectomy. Results of this Delphi survey may be applied to clinical outcomes research as an objective measure of short-term recovery. Furthermore, standardized endpoints identified through this process may be used in clinical practice to guide decisions regarding patient discharge and may help to reduce the risk of premature discharge or prolonged admission.

Deep-learned time-signal intensity pattern analysis using an autoencoder captures magnetic resonance perfusion heterogeneity for brain tumor differentiation.

Current image processing methods for dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) do not capture complex dynamic information of time-signal intensity curves. We investigated whether an autoencoder-based pattern analysis of DSC MRI captured representative temporal features that improves tissue characterization and tumor diagnosis in a multicenter setting. The autoencoder was applied to the time-signal intensity curves to obtain representative temporal patterns, which were subsequently learned by a convolutional neural network. This network was trained with 216 preoperative DSC MRI acquisitions and validated using external data (n = 43) collected with different DSC acquisition protocols. The autoencoder applied to time-signal intensity curves and clustering obtained nine representative clusters of temporal patterns, which accurately identified tumor and non-tumoral tissues. The dominant clusters of temporal patterns distinguished primary central nervous system lymphoma (PCNSL) from glioblastoma (AUC 0.89) and metastasis from glioblastoma (AUC 0.95). The autoencoder captured DSC time-signal intensity patterns that improved identification of tumoral tissues and differentiation of tumor type and was generalizable across centers.