Gastro-esophageal reflux disease symptoms and demographic factors as a pre-screening tool for Barrett's esophagus.

BACKGROUND: Barrett's esophagus (BE) occurs as consequence of reflux and is a risk factor for esophageal adenocarcinoma. The current "gold-standard" for diagnosing BE is endoscopy which remains prohibitively expensive and impractical as a population screening tool. We aimed to develop a pre-screening tool to aid decision making for diagnostic referrals. METHODOLOGY/PRINCIPAL FINDINGS: A prospective (training) cohort of 1603 patients attending for endoscopy was used for identification of risk factors to develop a risk prediction model. Factors associated with BE in the univariate analysis were selected to develop prediction models that were validated in an independent, external cohort of 477 non-BE patients referred for endoscopy with symptoms of reflux or dyspepsia. Two prediction models were developed separately for columnar lined epithelium (CLE) of any length and using a stricter definition of intestinal metaplasia (IM) with segments ≥ 2 cm with areas under the ROC curves (AUC) of 0.72 (95%CI: 0.67-0.77) and 0.81 (95%CI: 0.76-0.86), respectively. The two prediction models included demographics (age, sex), symptoms (heartburn, acid reflux, chest pain, abdominal pain) and medication for "stomach" symptoms. These two models were validated in the independent cohort with AUCs of 0.61 (95%CI: 0.54-0.68) and 0.64 (95%CI: 0.52-0.77) for CLE and IM ≥ 2 cm, respectively. CONCLUSIONS: We have identified and validated two prediction models for CLE and IM ≥ 2 cm. Both models have fair prediction accuracies and can select out around 20% of individuals unlikely to benefit from investigation for Barrett's esophagus. Such prediction models have the potential to generate useful cost-savings for BE screening among the symptomatic population

Imaging Post-Infarct Myocardial Inflammation with ⁶⁸Ga-DOTATATE PET/MRI and insights into COVID-19 associated myocardial injury

i) Post-Infarct Myocardial Inflammation and Imaging Background: Inflammation and its resolution modulate post-infarct myocardial injury. An excessive or prolonged inflammatory phase after myocardial infarction (MI) may contribute to adverse cardiac remodelling. 68Ga-DOTATATE is a PET radiotracer with high affinity for somatostatin receptor subtype 2 (SST2), which has been shown to be up-regulated in pro-inflammatory macrophages. Aims: To investigate the role of hybrid 68Ga-DOTATATE PET/MRI for tracking post-infarct myocardial inflammation and predicting adverse cardiac remodelling post-MI, as well as to identify potential systemic and blood biomarker correlates of myocardial 68Ga-DOTATATE PET signal. Methods: In a prospective observational cohort study, participants with recent MI underwent hybrid 68Ga-DOTATATE PET/MRI within 2 weeks of infarction (t0), and again after 3 months (t3M). Participants additionally underwent CT coronary angiography at baseline, and a full cardiac MRI scan at 1 year (t1Y). Participants with a prior history of MI, heart failure, previous coronary intervention or bypass grafting, were excluded. Blood samples were taken at the time of imaging for the quantification of circulating immune cell subsets using mass cytometry by time-of-flight (CyTOF) and for serum proteomic analysis. 68Ga-DOTATATE maximum Standardised Uptake Values (SUVmax) were derived for myocardial segments with late gadolinium enhancement (LGE; “infarct”) as well as for segments without LGE and myocardium remote from the infarct. Assessments of regional wall motion; segmental strain and T1/T2 mapping values; left ventricular volumes and biplane ejection fraction, were performed from cardiac MRI at t0 and t1Y. Regions of interest for quantification of 68Ga-DOTATATE PET signal were also derived for the ascending and descending aorta, vertebrae and non-culprit coronary arteries. *Ex vivo*, cardiac histological specimens from patients with a recent history of MI or ischaemic cardiomyopathy were immuno-stained for SST2, CD3, CD80, CD206/mannose receptor and CD68. Results: 38 participants in total were recruited (mean age 60 [SD 9] years; 32 [84%] male and 6 [16%] female), of whom 22 (58%) had ST elevation MI and 16 (42%) had non-ST elevation MI. The mean peak troponin at baseline was 16665ng/L (range 408 to >25,000ng/L) and the mean LVEF on pre-discharge echocardiogram was 49% (range 28%-61%). 36 (95%) participants had a follow-up 68Ga-DOTATATE PET/MRI at t3M and all 38 participants had a full cardiac MRI at t1Y. At t0, 68Ga-DOTATATE PET signal demonstrated a clear ability to distinguish infarct from remote myocardial regions. Furthermore, on segmental analysis, akinetic or hypo-kinetic myocardial segments has a significantly higher mean SUVmax than normo-kinetic segments. Segmental myocardial 68Ga-DOTATATE SUV also significantly correlated with peak segmental strain and segmental T1 values. At t3M, there was a significant decline in infarct 68Ga-DOTATATE SUV, in keeping with resolving myocardial inflammation, which was paralleled by a decline in high sensitivity Troponin, high sensitivity C reactive protein and NTproBNP levels. Immunostaining of histological specimens from patients with recent MI or ischaemic cardiomyopathy revealed co-localisation of SST2 with CD68, supporting the conclusion that the myocardial 68Ga-DOTATATE PET signal was derived, at least in part, from macrophages. After multivariable adjustment, the mean SUVmax of the infarct at t3M, but not t0, was significantly positively associated with left ventricular dilatation at t1Y (delta EDVi; p=0.038). The t3M/t0 ratio of the mean infarct SUVmax appeared to be an even stronger predictor of volumetric remodelling outcome. After statistical feature selection and multiple comparisons adjustments, a number of biomarkers were associated with the post-MI myocardial PET signal, including serum programmed death-ligand 1 (PD-L1) levels at both t0 and t3M which were significantly negatively associated with the mean SUVmax of the infarct at t3M. Conclusions: This is the first prospective study of serial 68Ga-DOTATATE PET/MRI in patients after MI. Our results indicate that 68Ga-DOTATATE PET is a useful tool for assessing post-infarct myocardial inflammation and that higher persistent 68Ga-DOTATATE PET signal at t3M may be linked to adverse remodelling outcomes. We further identify several biomarkers including serum PD-L1 levels at t0 and t3M as a potentially useful predictor of *in situ* myocardial inflammation as quantified by 68Ga-DOTATATE PET. ii) COVID-19 related myocardial injury and imaging Background: Cardiac injury is a well-recognised complication of acute COVID-19 infection, with varied aetiologies ranging from myocarditis to endothelial dysfunction, micro-embolic phenomena and acute coronary syndromes. While persistent cardiac symptoms in patients with post-acute COVID-19 syndrome (PACS) are also common, the underlying cause is less well understood. A variety of imaging abnormalities have been described on cardiac magnetic resonance imaging (MRI) in the post-COVID setting and immune system dysregulation has been implicated both in determining acute disease severity as well in the development of PASC. To our knowledge, only one previously published study has specifically examined the link between cardiac imaging abnormalities after COVID-19 infection and immune profiling of the affected individuals, which was also limited to quantification of peripheral immune cell populations. Aims: To examine cardiac involvement associated with COVID-19 infection using imaging and deep immunophenotyping employing mass cytometry by time-of-flight (CyTOF) as well as serum proteomic analysis. Methods: Participants who had a history of COVID-19 infection and suspected cardiac involvement but no prior history of myocardial infarction or heart failure and no history of recent systemic immunosuppression, were recruited between October 2020 and February 2022. Participants were recruited on the basis of either troponin I (TnI) elevation (>99th percentile upper reference limit), new onset heart failure not attributable to another cause or unexplained ongoing cardiac symptoms after their initial COVID-19 infection. Participants underwent full cardiac MRI with late gadolinium enhancement (LGE) imaging, peripheral blood cell immunophenotyping using mass cytometry by time-of-flight (CyTOF) and serum proteomic analysis (Olink® Target 96 Inflammation Panel). Results: 21 participants (mean age 47 (SD 13) years, 71% female) were enrolled, who either had PACS (n=17), suspected acute COVID myocarditis (n=2), or new-onset heart failure attributed to prior COVID infection (n=2). MRI showed a non-ischaemic pattern of LGE and/or visually overt myocardial oedema in 8 (38%) patients, including 5 (24%) with PACS. A further patient had impaired ventricular function in the absence of LGE. In total, 9 (43%) patients had MRI abnormalities defined as either a non-ischaemic pattern of LGE, oedema or ventricular impairment. Participants with MRI abnormalities exhibited differences in CyTOF and proteomic biomarker expression compared with participants without such abnormalities, including: increased CCL3, CCL4, CCL7 (MCP-3), CXCL1, FGF21, FGF23, IL-13, PD-L1 and ST1A1 levels, as well as CD4+ Th2-like cells; but decreased CD8+ T effector memory cells, including PD1+ CD8+ T cells and CD8+ αβ T cells. Using Lasso regression analysis including all baseline clinical characteristics, higher CCL7 (MCP-3) levels and lower CD8+ TEM cells were the strongest predictors of an abnormal MRI finding, with a composite AUC of 0.96. Conclusions: Cardiac involvement after COVID-19 infection in patients with MRI abnormalities is associated with CCL7 (MCP-3) elevation, a chemokine known to be important in viral myocarditis, as well as decreased CD8+ T effector memory cells. These findings potentially give insight into the pathogenesis of cardiac-specific involvement post-COVID-19.British Heart Foundation Wellcome Trus

Integrated cardiovascular assessment of atherosclerosis using PET/MRI.

Atherosclerosis is a systemic inflammatory disease typified by the development of lipid-rich atheroma (plaques), the rupture of which are a major cause of myocardial infarction and stroke. Anatomical evaluation of the plaque considering only the degree of luminal stenosis overlooks features associated with vulnerable plaques, such as high-risk morphological features or pathophysiology, and hence risks missing vulnerable or ruptured non-stenotic plaques. Consequently, there has been interest in identifying these markers of vulnerability using either MRI for morphology, or positron emission tomography (PET) for physiological processes involved in atherogenesis. The advent of hybrid PET/MRI scanners offers the potential to combine the strengths of PET and MRI to allow comprehensive assessment of the atherosclerotic plaque. This review will discuss the principles and technical aspects of hybrid PET/MRI assessment of atherosclerosis, and consider how combining the complementary modalities of PET and MRI has already furthered our understanding of atherogenesis, advanced drug development, and how it may hold potential for clinical application.National Institute of Health Research Wellcome Trust EPSR

Using machine learning to predict carotid artery symptoms from CT angiography: a radiomics and deep learning approach

ABSTRACT PURPOSE: To assess radiomics and deep learning (DL) methods in identifying symptomatic Carotid Artery Disease (CAD) from carotid CT angiography (CTA) images. We further compare the performance of these novel methods to the conventional calcium score. METHODS Carotid CT angiography (CTA) images from symptomatic patients (ischaemic stroke / transient ischaemic attack within the last 3 months) and asymptomatic patients were analysed. Carotid arteries were classified into culprit, non-culprit and asymptomatic. The calcium score was assessed using the Agatston method. 93 radiomic features were extracted from regions-of-interest drawn on 14 consecutive CTA slices. For DL, convolutional neural networks (CNNs) with and without transfer learning were trained directly on CTA slices. Predictive performance was assessed over 5-fold cross validated AUC scores. SHAP and GRAD-CAM algorithms were used for explainability. RESULTS 132 carotid arteries were analysed (41 culprit, 41 non-culprit, and 50 asymptomatic). For asymptomatic vs symptomatic arteries, radiomics attained a mean AUC of 0.96(±0.02), followed by DL 0.86(±0.06) and then calcium 0.79(±0.08). For culprit vs non-culprit arteries, radiomics achieved a mean AUC of 0.75(±0.09), followed by DL 0.67(±0.10) and then calcium 0.60(±0.02). For multi-class classification, the mean AUCs were 0.95(±0.07), 0.79(±0.05), and 0.71(±0.07) for radiomics, DL and calcium, respectively. Explainability revealed consistent patterns in the most important radiomic features. CONCLUSIONS: Our study highlights the potential of novel image analysis techniques in extracting quantitative information beyond calcification in the identification of CAD. Though further work is required, the transition of these novel techniques into clinical practice may eventually facilitate better stroke risk stratification

CT pericoronary adipose tissue density predicts coronary allograft vasculopathy and adverse clinical outcomes after cardiac transplantation.

AIMS: To assess pericoronary adipose tissue (PCAT) density on Coronary Computed Tomography Angiography (CCTA) as a marker of inflammatory disease activity in coronary allograft vasculopathy (CAV). METHODS AND RESULTS: PCAT density, lesion volumes, and total vessel volume-to-myocardial mass ratio (V/M) were retrospectively measured in 126 CCTAs from 94 heart transplant patients (mean age 49 [SD 14.5] years, 40% female) who underwent imaging between 2010 to 2021; age and sex-matched controls; and patients with atherosclerosis. PCAT density was higher in transplant patients with CAV (n = 40; -73.0 HU [SD 9.3]) than without CAV (n = 86; -77.9 HU [SD 8.2]), and controls (n = 12; -86.2 HU [SD 5.4]), p < 0.01 for both. Unlike patients with atherosclerotic coronary artery disease (n = 32), CAV lesions were predominantly non-calcified, comprised of mostly fibrous or fibrofatty tissue. V/M was lower in patients with CAV than without (32.4 mm3/g [SD 9.7] vs. 41.4 mm3/g [SD 12.3], p < 0.0001). PCAT density and V/M improved the ability to predict CAV from AUC 0.75 to 0.85 when added to donor age and donor hypertension status (p < 0.0001). PCAT density above -66 HU was associated with a greater incidence of all-cause mortality (OR 18.0 [95%CI 3.25-99.6], p < 0.01) and the composite endpoint of death, CAV progression, acute rejection, and coronary revascularization (OR 7.47 [95%CI 1.8-31.6], p = 0.01) over 5.3 (SD 2.1) years. CONCLUSIONS: Heart transplant patients with CAV have higher PCAT density and lower V/M than those without. Increased PCAT density is associated with adverse clinical outcomes. These CCTA metrics could be useful for diagnosis and monitoring of CAV severity

The coefficients, weights and odds ratios of selected predictors for BE.

<p>^*n/a: not applicable.</p

Summary of the predictors for BE in the external validation cohort^*.

<p>^*Data shown are mean (SD) for continuous variables and number (percentage) for categorical variables.</p

Demographic characteristics according to endoscopic BE and pathological BE in the training cohort^*.

<p>^*Data shown are mean (SD) for continuous variables and number (percentage) for categorical variables</p>†<p>P for trend test.</p

ROC curve for a) endoscopically visible CLE of any length independent of histology (AUC: 0.61), b) segment containing IM≥2 cm (AUC: 0.64) in the external validation cohort (N = 477).

<p>ROCs curve were developed using the risk scores which are calculated by the weights of different predictors. The weights were developed based on the coefficients of predictors in the backward logistic regression model in the training cohort.</p