3D Printed Moulds Encompassing Carbon Composite Electrodes to Conduct Multi-Site Monitoring in the Entire Colon

The activity of the colon is regulated by chemical signalling, of which serotonin (5- HT) is a key transmitter. Monitoring of mucosal 5-HT overflow has been achieved to date using microelectrodes on small segment of colonic tissue, however little is known if such measurements are reflective with regards to 5-HT signalling from the entire colon. This study focused on developing an electrochemical array device that could be utilised to conduct multi-site measurements of 5-HT overflow from the entire colon. A 3D printed mould was fabricated that could house 6 multi-wall carbon nanotube composite electrodes and provide a fixed distance between the electrodes and the tissue along the entire length of the colon. The electrodes were assessed for sensitivity, stability and crosstalk before conducting in vitro measurements using colons obtained from 6 and 24 month old mice. As composite electrodes can have a high degree of variability, normalisation factors were required between electrodes for a given array. The device had the sensitivity and stability required for 5-HT measurements from intestinal tissue. Regio-specific changes in 5-HT overflow were observed with age, where increases in 5-HT overflow were observed in the distal colon due to an impairment/loss in the serotonin transporter (SERT). Our strategy can be utilised to develop arrays of varying sizes and geometries which can offerpractical solutions for large scale tissue measurements

Interstitial cell network volume is reduced in the terminal bowel of ageing mice

Ageing is associated with impaired neuromuscular function of the terminal gastrointestinal (GI) tract, which can result in chronic constipation, faecal impaction and incontinence. Interstitial cells of cajal (ICC) play an important role in regulation of intestinal smooth muscle contraction. However, changes in ICC volume with age in the terminal GI tract (the anal canal including the anal sphincter region and rectum)have not been studied. Here, the distribution, morphology and network volume of ICC in the terminal GI tract of 3‐to 4‐month‐old and 26‐to 28‐month‐old C57BL/6mice were investigated. ICC were identified by immunofluorescence labelling of wholemount preparations with an antibody against c‐Kit. ICC network volume was measured by software‐based 3D volume rendering of confocal Z stacks. A significant reduction in ICC network volume per unit volume of muscle was measured in aged animals. No age‐associated change in ICC morphology was detected. The thickness of the circular muscle layer of the anal sphincter region and rectum increased with age, while that in the distal colon decreased. These results suggest that ageing is associated with a reduction in the network volume of ICC in the terminal GI tract, which may influence the normal function of these regions

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

Large, labeled datasets have driven deep learning methods to achieve expert-level performance on a variety of medical imaging tasks. We present CheXpert, a large dataset that contains 224,316 chest radiographs of 65,240 patients. We design a labeler to automatically detect the presence of 14 observations in radiology reports, capturing uncertainties inherent in radiograph interpretation. We investigate different approaches to using the uncertainty labels for training convolutional neural networks that output the probability of these observations given the available frontal and lateral radiographs. On a validation set of 200 chest radiographic studies which were manually annotated by 3 board-certified radiologists, we find that different uncertainty approaches are useful for different pathologies. We then evaluate our best model on a test set composed of 500 chest radiographic studies annotated by a consensus of 5 board-certified radiologists, and compare the performance of our model to that of 3 additional radiologists in the detection of 5 selected pathologies. On Cardiomegaly, Edema, and Pleural Effusion, the model ROC and PR curves lie above all 3 radiologist operating points. We release the dataset to the public as a standard benchmark to evaluate performance of chest radiograph interpretation models. The dataset is freely available at https://stanfordmlgroup.github.io/competitions/chexpert .Comment: Published in AAAI 201

The effects of a transjugular intrahepatic portosystemic shunt on the diagnosis of hepatocellular cancer.

Background and aimsTransjugular intrahepatic portosystemic shunt (TIPS) may be placed to treat complications of portal hypertension by creating a conduit between the hepatic and portal vein. The diagnosis of hepatocellular carcinoma (HCC) is typically made by multiphasic imaging studies demonstrating arterial enhancement with washout on arterial, portal venous, and delayed phase imaging. The aim of our study was to determine how the presence of TIPS would affect the imaging diagnosis of HCC.MethodsThis was a single-center electronic database review of all patients who underwent multiphasic imaging with MRI or CT scan for HCC screening between January 2000 and July 2017 and who were subsequently diagnosed with HCC. Data collected included patient demographics, liver disease characteristics including CPT score, MELD-Na, AFP, type of imaging, tumor stage, and lab values at the time of HCC diagnosis. The diagnosis of HCC was made using LI-RADS criteria on contrast-enhanced CT or MR imaging and confirmed by chart abstraction as documented by the treating clinician. Demographic and imaging characteristics for HCC patients with and without TIPS were compared.ResultsA total of 279 patients met eligibility criteria for the study, 37 (13.2%) of whom had TIPS placed prior to diagnosis of HCC. There was no significant difference in demographics or liver disease characteristics between patients with and without TIPS. Compared to cirrhotic patients with no TIPS prior to HCC diagnosis, patients with TIPS had significantly more scans with a longer duration of surveillance until HCC diagnosis. However, LI-RADS criteria and stage of HCC at diagnosis were not significantly different between both groups. There were no differences in outcomes including liver transplant and survival.ConclusionThe presence of TIPS does not lead to a delayed diagnosis of HCC. It is associated, however, with greater duration of time from first scan to diagnosis of HCC

Multimodal spatiotemporal graph neural networks for improved prediction of 30-day all-cause hospital readmission

Measures to predict 30-day readmission are considered an important quality factor for hospitals as accurate predictions can reduce the overall cost of care by identifying high risk patients before they are discharged. While recent deep learning-based studies have shown promising empirical results on readmission prediction, several limitations exist that may hinder widespread clinical utility, such as (a) only patients with certain conditions are considered, (b) existing approaches do not leverage data temporality, (c) individual admissions are assumed independent of each other, which is unrealistic, (d) prior studies are usually limited to single source of data and single center data. To address these limitations, we propose a multimodal, modality-agnostic spatiotemporal graph neural network (MM-STGNN) for prediction of 30-day all-cause hospital readmission that fuses multimodal in-patient longitudinal data. By training and evaluating our methods using longitudinal chest radiographs and electronic health records from two independent centers, we demonstrate that MM-STGNN achieves AUROC of 0.79 on both primary and external datasets. Furthermore, MM-STGNN significantly outperforms the current clinical reference standard, LACE+ score (AUROC=0.61), on the primary dataset. For subset populations of patients with heart and vascular disease, our model also outperforms baselines on predicting 30-day readmission (e.g., 3.7 point improvement in AUROC in patients with heart disease). Lastly, qualitative model interpretability analysis indicates that while patients' primary diagnoses were not explicitly used to train the model, node features crucial for model prediction directly reflect patients' primary diagnoses. Importantly, our MM-STGNN is agnostic to node feature modalities and could be utilized to integrate multimodal data for triaging patients in various downstream resource allocation tasks

Systematic review and meta-analysis investigating the diagnostic yield of dual-energy CT for renal mass assessment

OBJECTIVE. The objective of our study was to perform a systematic review and meta-analysis to evaluate the diagnostic accuracy of dual-energy CT (DECT) for renal mass evaluation. MATERIALS AND METHODS. In March 2018, we searched MEDLINE, Cochrane Database of Systematic Reviews, Embase, and Web of Science databases. Analytic methods were based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Pooled estimates for sensitivity, specificity, and diagnostic odds ratios were calculated for DECT-based virtual monochromatic imaging (VMI) and iodine quantification techniques as well as for conventional attenuation measurements from renal mass CT protocols. I 2 was used to evaluate heterogeneity. The methodologic quality of the included studies and potential bias were assessed using items from the Quality Assessment Tool for Diagnostic Accuracy Studies 2 (QUADAS-2). RESULTS. Of the 1043 articles initially identified, 13 were selected for inclusion (969 patients, 1193 renal masses). Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for VMI were 87% (95% CI, 80–92%; I 2 , 92.0%), 93% (95% CI, 90–96%; I 2 , 18.0%), and 183.4 (95% CI, 30.7–1093.4; I 2 , 61.6%), respectively. Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for iodine quantification were 99% (95% CI, 97–100%; I 2 , 17.6%), 91% (95% CI, 89–94%; I 2 , 84.2%), and 511.5 (95% CI, 217–1201; I 2 , 0%). No significant differences in AUCs were found when comparing iodine quantification to conventional attenuation measurements (p = 0.79). CONCLUSION. DECT yields high accuracy for renal mass evaluation. Determination of iodine content with the iodine quantification technique shows diagnostic accuracy similar to conventional attenuation measurements from renal mass CT protocols. The iodine quantification technique may be used to characterize incidental renal masses when a dedicated renal mass protocol is not available

Evaluation of chimeric antigen receptor T cell therapy in non-human primates infected with SHIV or SIV.

Achieving a functional cure is an important goal in the development of HIV therapy. Eliciting HIV-specific cellular immune responses has not been sufficient to achieve durable removal of HIV-infected cells due to the restriction on effective immune responses by mutation and establishment of latent reservoirs. Chimeric antigen receptor (CAR) T cells are an avenue to potentially develop more potent redirected cellular responses against infected T cells. We developed and tested a range of HIV- and SIV-specific chimeric antigen receptor (CAR) T cell reagents based on Env-binding proteins. In general, SHIV/SIV CAR T cells showed potent viral suppression in vitro, and adding additional CAR molecules in the same transduction resulted in more potent viral suppression than single CAR transduction. Importantly, the primary determinant of virus suppression potency by CAR was the accessibility to the Env epitope, and not the neutralization potency of the binding moiety. However, upon transduction of autologous T cells followed by infusion in vivo, none of these CAR T cells impacted either acquisition as a test of prevention, or viremia as a test of treatment. Our study illustrates limitations of the CAR T cells as possible antiviral therapeutics