Semi-supervised learning with natural language processing for right ventricle classification in echocardiography - a scalable approach

We created a deep learning model, trained on text classified by natural language processing (NLP), to assess right ventricular (RV) size and function from echocardiographic images. We included 12,684 examinations with corresponding written reports for text classification. After manual annotation of 1489 reports, we trained an NLP model to classify the remaining 10,651 reports. A view classifier was developed to select the 4-chamber or RV-focused view from an echocardiographic examination (n\ua0=\ua0539). The final models were two image classification models trained on the predicted labels from the combined manual annotation and NLP models and the corresponding echocardiographic view to assess RV function (training set\ua0n\ua0=\ua011,008) and size (training set\ua0n\ua0=\ua09951. The text classifier identified impaired RV function with 99% sensitivity and 98% specificity and RV enlargement with 98% sensitivity and 98% specificity. The view classification model identified the 4-chamber view with 92% accuracy and the RV-focused view with 73% accuracy. The image classification models identified impaired RV function with 93% sensitivity and 72% specificity and an enlarged RV with 80% sensitivity and 85% specificity; agreement with the written reports was substantial (both κ\ua0=\ua00.65). Our findings show that models for automatic image assessment can be trained to classify RV size and function by using model-annotated data from written echocardiography reports. This pipeline for auto-annotation of the echocardiographic images, using a NLP model with medical reports as input, can be used to train an image-assessment model without manual annotation of images and enables fast and inexpensive expansion of the training dataset when needed

Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies

To develop a fully automatic model capable of reliably quantifying epicardial adipose tissue (EAT) volumes and attenuation in large scale population studies to investigate their relation to markers of cardiometabolic risk. Non-contrast cardiac CT images from the SCAPIS study were used to train and test a convolutional neural network based model to quantify EAT by: segmenting the pericardium, suppressing noise-induced artifacts in the heart chambers, and, if image sets were incomplete, imputing missing EAT volumes. The model achieved a mean Dice coefficient of 0.90 when tested against expert manual segmentations on 25 image sets. Tested on 1400 image sets, the model successfully segmented 99.4% of the cases. Automatic imputation of missing EAT volumes had an error of less than 3.1% with up to 20% of the slices in image sets missing. The most important predictors of EAT volumes were weight and waist, while EAT attenuation was predicted mainly by EAT volume. A model with excellent performance, capable of fully automatic handling of the most common challenges in large scale EAT quantification has been developed. In studies of the importance of EAT in disease development, the strong co-variation with anthropometric measures needs to be carefully considered

Studies on carotid plaque vulnerability using contrast enhanced ultrasound

ABSTRACT Background and Aim: Contrast-enhanced ultrasound is a method to examine neovessels that may be present inside the atherosclerotic plaque of the carotid arteries. These neovessels are believed to be involved in the process leading to embolic stroke. The aim of this thesis is to: I /Develop methodology for contrast enhanced ultrasound examination of carotid plaques and to develop a software program for quantification of the examination. II /Investigate the correlation between neovessels and inflammation in plaques, using PET/CT. III / Investigate the correlation between neovessels and plaque components using MRI. IV / Comparing ultrasound and MRI in detecting and measuring of carotid plaques. Methods: The papers of this thesis are performed on volunteers recruited through several different databases. The contrast-enhanced ultrasound method has been developed and optimized within the framework of the thesis. For comparison, conventional ultrasound, PET / CT and MRI has been used. Results: The method we have developed for contrast-enhanced ultrasound is reproducible and reliable. Increased amount of neovessels is more common in subjects with a history of stroke or transient ischemic attack and neovessels are correlated to increased inflammation. Neovessels are less common in plaques with a large lipid-rich necrotic core. Two dimensional imaging using ultrasound does not correctly capture the complex 3D plaque anatomy. MRI is comparable to ultrasound in finding plaque with a height of at least 2.5 mm, but in detection of smaller plaques ultrasound performs better. Multiple plaques seen on ultrasound are usually a misinterpretation of the true anatomy that can be better visualized using MRI. Plaque height measured using ultrasound is slightly more accurate and more feasible than plaque area to estimate the plaque volume measured using MRI. Conclusion: Contrast-enhanced ultrasound can be used to measure and quantify neovessels in carotid plaques. The quantity of neovessels correlates with the degree of inflammation, a marker for plaque vulnerability. However, the size of the lipid core, another marker of plaque vulnerability, has an inverse correlation to neovessels. Future studies should in more detail examine the exact localization of neovessels in relation to the lipid core. Also, future studies should examine the quality of neovessels since they can have different propensity to cause damage. Small plaques can be undetectable by MRI but in plaques greater than 2.5 mm in height, ultrasound and magnetic resonance imaging have similar sensitivity to detect plaques. If using ultrasound, plaque height is the best way to estimate the volume of the carotid artery plaque

Retinopati och återfall i stroke hos typ 2 diabetespatienter och matchade kontroller

The datamaterial consists of 445 patients with type 2 diabetes mellitus and a matched control group of 445 patients without diabetes, who had all suffered their first stroke or TIA. The aims of the material is to study if retinopathy increases the risk of stroke recurrence in stroke patients with type 2 diabetes. Also, to study if stroke patients with type 2 diabetes have an increased risk of stroke recurrence compared to non-diabetics and if stroke patients with type 2 diabetes, regardless of retinopathy, have a higher incidence of carotid stenosis. Also, to study if stroke patients with type 2 diabetes retinopathy have increased incidence of carotid stenosis.Datamaterialet består av 445 patienter med typ 2 diabetes och en matchad kontrollgrupp med 445 patienter utan diabetes, som alla har haft stroke eller TIA

Estimating the value of novel interventions for Parkinson's disease: An early decision-making model with application to dopamine cell replacement.

A long-term cost-effectiveness model for early decision-making and estimation of outcomes of novel therapeutic procedures for Parkinson's disease (PD) was developed based on the Hoehn and Yahr (HY) stages of PD. Results provided support for model validity. Model application to a future dopamine cell replacement therapy indicated long-term cost offsets and gains in quality-adjusted life years (QALYs) in early onset PD (HY III-IV), as compared to standard drug therapy. The maximum price premium (i.e., profit or compensation for developmental costs) for the intervention to remain cost-effective was estimated to EURO12000-64000 according to cost-per-QALY thresholds of EURO38000-70000 and depending on whether all or only medical direct costs are considered. The study illustrates the value of early health economic modeling and the described model shows promise as a means to estimate outcomes and aid decision-making regarding novel interventions for PD. (c) 2006 Elsevier Ltd. All rights reserved

Does retinopathy predict stroke recurrence in type 2 diabetes patients: A retrospective study?

AimsTo study if retinopathy increases the risk of stroke recurrence in stroke patients with type 2 diabetes. Also, to study if stroke patients with type 2 diabetes have an increased risk of stroke recurrence compared to non-diabetics and if stroke patients with type 2 diabetes, regardless of retinopathy, have a higher incidence of carotid stenosis. Also, to study if stroke patients with type 2 diabetes retinopathy have increased incidence of carotid stenosis.MethodsWe included 445 patients with type 2 diabetes mellitus and a matched control group of 445 patients without diabetes, who had all suffered their first stroke or TIA. Information on retinopathy, risk factors and stroke recurrence were obtained from registers and medical records.ResultsRetinopathy did not increase the risk of stroke recurrence in diabetes patients, HR 0.89 (0.51-1.53), p = 0.67. The risk of stroke recurrence was not increased in diabetics compared to non-diabetes. Diabetes patients had an increased prevalence of carotid stenosis compared to non-diabetics, 1.69 (1.15-2.48), p = 0.008. The prevalence of carotid stenosis in diabetics with retinopathy was not increased compared to diabetics without retinopathy.ConclusionRetinopathy is not a predictor of stroke recurrence or carotid stenosis in type 2 diabetes patients

Increased Vascularization in the Vulnerable Upstream Regions of Both Early and Advanced Human Carotid Atherosclerosis.

Vascularization of atherosclerotic plaques has been linked to plaque vulnerability. The aim of this study was to test if the vascularization was increased in upstream regions of early atherosclerotic carotid plaques and also to test if the same pattern of vascularization was seen in complicated, symptomatic plaques.We enrolled 45 subjects with early atherosclerotic lesions for contrast enhanced ultrasound and evaluated the percentage of plaque area in a longitudinal ultrasound section which contained contrast agent. Contrast-agent uptake was evaluated in both the upstream and downstream regions of the plaque. We also collected carotid endarterectomy specimens from 56 subjects and upstream and downstream regions were localized using magnetic resonance angiography and analyzed using histopathology and immunohistochemistry.Vascularization was increased in the upstream regions of early carotid plaques compared with downstream regions (30% vs. 23%, p = 0.033). Vascularization was also increased in the upstream regions of advanced atherosclerotic lesions compared with downstream regions (4.6 vs. 1.4 vessels/mm2, p = 0.001) and was associated with intra-plaque hemorrhage and inflammation.Vascularization is increased in the upstream regions of both early and advanced plaques and is in advanced lesions mainly driven by inflammation

Boxplot of the number of CD34-stained vessels/mm² in preatheromas (AHA III) and advanced atheromas (AHA IV-VI).

<p>Boxplot of the number of CD34-stained vessels/mm² in preatheromas (AHA III) and advanced atheromas (AHA IV-VI).</p

Histological plaque features and immunostaining in upstream and downstream regions.

<p>Histological plaque features and immunostaining in upstream and downstream regions.</p

Increased Vascularization in the Vulnerable Upstream Regions of Both Early and Advanced Human Carotid Atherosclerosis - Fig 1

<p>CEUS image of the carotid artery (A) with a plaque in the near wall. The plaque border is marked with orange and the upstream/downstream divider as a purple line (lines have been enhanced for clarification). B: CQP image with the mean pixel intensity. Automatically excluded areas marked green. C: CQP image with pixels with mean intensity above threshold level marked white.</p