Myocardial Involvement After Hospitalization for COVID-19 Complicated by Troponin Elevation : A Prospective, Multicenter, Observational Study

Dr Berry acknowledges British Heart Foundation support (grant RE/18/6134217). Dr Artico received funding from the European Association of Cardiovascular Imaging (EACVI research grant App000073878). Dr McCann is funded by an NIHR research professorship (RP-2017-08-ST2-007). Dr Manisty is funded by an NIHR clinician scientist award (CS-2015-15-003). Drs Ferreira, Piechnik, and Neubauer thank the NIHR Oxford Biomedical Research Centre for support of this study. Dr Bucciarelli-Ducci is supported in part by the NIHR Biomedical Research Centre at University Hospitals Bristol National Health Service Foundation Trust and the University of Bristol. Additional support was provided by the NIHR Leicester Biomedical Research Centre and the NIHR Leeds Clinical Research Facility. Dr Dweck is supported by the British Heart Foundation (grant FS/SCRF/21/32010). The authors thank the patients and staff who supported this project. Supported by NIHR and UK Research and Innovation (COV0254). West Yorkshire and Humber Clinical Research Network (CV070) funded patient information leaflet translation.Peer reviewedPublisher PD

Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images

BackgroundLate gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for non-invasive myocardial tissue characterisation. However, accurate segmentation of the left ventricular (LV) myocardium remains a challenge due to limited training data and lack of quality control. This study addresses these issues by leveraging generative adversarial networks (GAN)-generated virtual native enhancement (VNE) images to expand the training set and incorporating an automated quality control-driven (QCD) framework to improve segmentation reliability.MethodsA dataset comprising 4,716 LGE images (from 1,363 patients with hypertrophic cardiomyopathy and myocardial infarction) was used for development. To generate additional clinically validated data, LGE data were augmented with a GAN-based generator to produce VNE images. LV was contoured on these images manually by clinical observers. To create diverse candidate segmentations, the QCD framework involved multiple U-Nets, which were combined using statistical rank filters. The framework predicted the Dice Similarity Coefficient (DSC) for each candidate segmentation, with the highest predicted DSC indicating the most accurate and reliable result. The performance of the QCD ensemble framework was evaluated on both LGE and VNE test datasets (309 LGE/VNE images from 103 patients), assessing segmentation accuracy (DSC) and quality prediction (mean absolute error (MAE) and binary classification accuracy).ResultsThe QCD framework effectively and rapidly segmented the LV myocardium (<1 s per image) on both LGE and VNE images, demonstrating robust performance on both test datasets with similar mean DSC (LGE: 0.845±0.075; VNE: 0.845±0.071; p=ns). Incorporating GAN-generated VNE data into the training process consistently led to enhanced performance for both individual models and the overall framework. The quality control mechanism yielded a high performance (MAE=0.043, accuracy=0.951) emphasising the accuracy of the quality control-driven strategy in predicting segmentation quality in clinical settings. Overall, no statistical difference (p=ns) was found when comparing the LGE and VNE test sets across all experiments.ConclusionsThe QCD ensemble framework, leveraging GAN-generated VNE data and an automated quality control mechanism, significantly improved the accuracy and reliability of LGE segmentation, paving the way for enhanced and accountable diagnostic imaging in routine clinical use

Myocardial involvement after hospitalization for COVID-19 complicated by troponin elevation: a prospective, multicenter, observational study

Background: Acute myocardial injury in hospitalized patients with coronavirus disease 2019 (COVID-19) has a poor prognosis. Its associations and pathogenesis are unclear. Our aim was to assess the presence, nature, and extent of myocardial damage in hospitalized patients with troponin elevation. Methods: Across 25 hospitals in the United Kingdom, 342 patients with COVID-19 and an elevated troponin level (COVID+/troponin+) were enrolled between June 2020 and March 2021 and had a magnetic resonance imaging scan within 28 days of discharge. Two prospective control groups were recruited, comprising 64 patients with COVID-19 and normal troponin levels (COVID+/troponin−) and 113 patients without COVID-19 or elevated troponin level matched by age and cardiovascular comorbidities (COVID−/comorbidity+). Regression modeling was performed to identify predictors of major adverse cardiovascular events at 12 months. Results: Of the 519 included patients, 356 (69%) were men, with a median (interquartile range) age of 61.0 years (53.8, 68.8). The frequency of any heart abnormality, defined as left or right ventricular impairment, scar, or pericardial disease, was 2-fold greater in cases (61% [207/342]) compared with controls (36% [COVID+/troponin−] versus 31% [COVID−/comorbidity+]; P<0.001 for both). More cases than controls had ventricular impairment (17.2% versus 3.1% and 7.1%) or scar (42% versus 7% and 23%; P<0.001 for both). The myocardial injury pattern was different, with cases more likely than controls to have infarction (13% versus 2% and 7%; P<0.01) or microinfarction (9% versus 0% and 1%; P<0.001), but there was no difference in nonischemic scar (13% versus 5% and 14%; P=0.10). Using the Lake Louise magnetic resonance imaging criteria, the prevalence of probable recent myocarditis was 6.7% (23/342) in cases compared with 1.7% (2/113) in controls without COVID-19 (P=0.045). During follow-up, 4 patients died and 34 experienced a subsequent major adverse cardiovascular event (10.2%), which was similar to controls (6.1%; P=0.70). Myocardial scar, but not previous COVID-19 infection or troponin, was an independent predictor of major adverse cardiovascular events (odds ratio, 2.25 [95% CI, 1.12–4.57]; P=0.02). Conclusions: Compared with contemporary controls, patients with COVID-19 and elevated cardiac troponin level have more ventricular impairment and myocardial scar in early convalescence. However, the proportion with myocarditis was low and scar pathogenesis was diverse, including a newly described pattern of microinfarction. Registration: URL: https://www.isrctn.com; Unique identifier: 58667920

The impact of blood pressure variability on coronary arterial lumen dimensions as assessed by optical coherence tomography in patients with ST-elevation myocardial infarction

BACKGROUND:Patients with ST-elevation Myocardial Infarction treated by primary percutaneous coronary intervention (PPCI) experience drastic hemodynamic systemic changes (i.e., blood pressure) during the different phases of the procedure. Optical coherence tomography is often used to unveil the underlying cause of STEMI (pre-PCI) and to optimize stent implantation (post-PCI). The impact of blood pressure variability on coronary lumen remains uncertain. This study aimed to investigate the relationship between blood pressure variability, before and after PCI, and coronary arterial lumen dimensions of the infarct-related artery. METHODS:We measured systolic, diastolic and mean arterial blood pressure (SBP, DBP, and MAP; respectively) at pre- and post-PCI. Frequency-domain optical coherence tomography (FD-OCT) imaging was performed at the same time points. Offline quantitative image analyses were performed to assess the average and minimum lumen area (LA). Δ blood pressure (after and before the PCI) was then calculated. RESULTS:A total of 14 ST-segment elevation myocardial infarction (STEMI) patients were included. 84.2% of enrolled patients were male with a mean age of (58 ± 10.7 years). Roughly two-thirds (57.8%) had hypertension. The mean SBP was (112.6 mm Hg ± 16.1) and (117.2 mm Hg ± 20.9), pre- and post-stenting, respectively; the range of the observed SBP differences (between pre- and post-PCI) went from -25 to +23 mm Hg. Pre- and post-stenting mean average LA were (7.1 ± 2.5 mm2 and 6.8 ± 2.3 mm2; respectively). There were poor correlations between ΔSBP and Δ mean minimum LA. A similar pattern was observed with ΔDBP and ΔMAP. CONCLUSION:Despite significant hemodynamic variability, the difference in lumen cross-sectional area, between pre- and post-coronary artery stenting was minimal. This study supports the use of OCT lumen areas to inform clinical decisions during PPCI

Angiography-derived index of microcirculatory resistance as a novel, pressure-wire-free tool to assess coronary microcirculation in ST elevation myocardial infarction

Immediate assessment of coronary microcirculation during treatment of ST elevation myocardial infarction (STEMI) may facilitate patient stratification for targeted treatment algorithms. Use of pressure-wire to measure the index of microcirculatory resistance (IMR) is possible but has inevitable practical restrictions. We aimed to develop and validate angiography-derived index of microcirculatory resistance (IMRangio) as a novel and pressure-wire-free index to facilitate assessment of the coronary microcirculation. 45 STEMI patients treated with primary percutaneous coronary intervention (pPCI) were enrolled. Immediately before stenting and at completion of pPCI, IMR was measured within the infarct related artery (IRA). At the same time points, 2 angiographic views were acquired during hyperaemia to measure quantitative flow ratio (QFR) from which IMRangio was derived. In a subset of 15 patients both IMR and IMRangio were also measured in the non-IRA. Patients underwent cardiovascular magnetic resonance imaging (CMR) at 48 h for assessment of microvascular obstruction (MVO). IMRangio and IMR were significantly correlated (ρ: 0.85, p < 0.001). Both IMR and IMRangio were higher in the IRA rather than in the non-IRA (p = 0.01 and p = 0.006, respectively) and were higher in patients with evidence of clinically significant MVO (> 1.55% of left ventricular mass) (p = 0.03 and p = 0.005, respectively). Post-pPCI IMRangio presented and area under the curve (AUC) of 0.96 (CI95% 0.92-1.00, p < 0.001) for prediction of post-pPCI IMR > 40U and of 0.81 (CI95% 0.65-0.97, p < 0.001) for MVO > 1.55%. IMRangio is a promising tool for the assessment of coronary microcirculation. Assessment of IMR without the use of a pressure-wire may enable more rapid, convenient and cost-effective assessment of coronary microvascular function

Comparison of bolus versus continuous thermodilution derived indices of microvascular dysfunction in revascularized coronary syndromes

Background: The assessment of coronary microvascular dysfunction (CMD) using invasive methods is a field of growing interest, however the preferred method remains debated. Bolus and continuous thermodilution are commonly used methods, but weak agreement has been observed in patients with angina with non-obstructive coronary arteries (ANOCA). This study examined their agreement in revascularized acute coronary syndromes (ACS) and chronic coronary syndromes (CCS) patients. Objective: To compare bolus thermodilution and continuous thermodilution indices of CMD in revascularized ACS and CCS patients and assess their diagnostic agreement at pre-defined cut-off points. Methods: Patients from two centers underwent paired bolus and continuous thermodilution assessments after revascularization. CMD indices were compared between the two methods and their agreements at binary cut-off points were assessed. Results: Ninety-six patients and 116 vessels were included. The mean age was 64 ± 11 years, and 20 (21 %) were female. Overall, weak correlations were observed between the Index of Microcirculatory Resistance (IMR) and continuous thermodilution microvascular resistance (Rµ) (rho = 0.30p = 0.001). The median coronary flow reserve (CFR) from continuous thermodilution (CFRcont) and bolus thermodilution (CFRbolus) were 2.19 (1.76–2.67) and 2.55 (1.50–3.58), respectively (p < 0.001). Weak correlation and agreement were observed between CFRcont and CFRbolus (rho = 0.37, p < 0.001, ICC 0.228 [0.055–0.389]). When assessed at CFR cut-off values of 2.0 and 2.5, the methods disagreed in 41 (35 %) and 45 (39 %) of cases, respectively. Conclusions: There is a significant difference and weak agreement between bolus and continuous thermodilution-derived indices, which must be considered when diagnosing CMD in ACS and CCS patients

Datasheet1_Quality control-driven deep ensemble for accountable automated segmentation of cardiac magnetic resonance LGE and VNE images.pdf

BackgroundLate gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for non-invasive myocardial tissue characterisation. However, accurate segmentation of the left ventricular (LV) myocardium remains a challenge due to limited training data and lack of quality control. This study addresses these issues by leveraging generative adversarial networks (GAN)-generated virtual native enhancement (VNE) images to expand the training set and incorporating an automated quality control-driven (QCD) framework to improve segmentation reliability.MethodsA dataset comprising 4,716 LGE images (from 1,363 patients with hypertrophic cardiomyopathy and myocardial infarction) was used for development. To generate additional clinically validated data, LGE data were augmented with a GAN-based generator to produce VNE images. LV was contoured on these images manually by clinical observers. To create diverse candidate segmentations, the QCD framework involved multiple U-Nets, which were combined using statistical rank filters. The framework predicted the Dice Similarity Coefficient (DSC) for each candidate segmentation, with the highest predicted DSC indicating the most accurate and reliable result. The performance of the QCD ensemble framework was evaluated on both LGE and VNE test datasets (309 LGE/VNE images from 103 patients), assessing segmentation accuracy (DSC) and quality prediction (mean absolute error (MAE) and binary classification accuracy).ResultsThe QCD framework effectively and rapidly segmented the LV myocardium (ConclusionsThe QCD ensemble framework, leveraging GAN-generated VNE data and an automated quality control mechanism, significantly improved the accuracy and reliability of LGE segmentation, paving the way for enhanced and accountable diagnostic imaging in routine clinical use.</p

Comparison of bolus versus continuous thermodilution derived indices of microvascular dysfunction in revascularized coronary syndromes

Background: The assessment of coronary microvascular dysfunction (CMD) using invasive methods is a field of growing interest, however the preferred method remains debated. Bolus and continuous thermodilution are commonly used methods, but weak agreement has been observed in patients with angina with non-obstructive coronary arteries (ANOCA). This study examined their agreement in revascularized acute coronary syndromes (ACS) and chronic coronary syndromes (CCS) patients. Objective: To compare bolus thermodilution and continuous thermodilution indices of CMD in revascularized ACS and CCS patients and assess their diagnostic agreement at pre-defined cut-off points.  Methods: Patients from two centers underwent paired bolus and continuous thermodilution assessments after revascularization. CMD indices were compared between the two methods and their agreements at binary cut-off points were assessed.  Results: Ninety-six patients and 116 vessels were included. The mean age was 64 ± 11 years, and 20 (21 %) were female. Overall, weak correlations were observed between the Index of Microcirculatory Resistance (IMR) and continuous thermodilution microvascular resistance (Rµ) (rho = 0.30p = 0.001). The median coronary flow reserve (CFR) from continuous thermodilution (CFRcont) and bolus thermodilution (CFRbolus) were 2.19 (1.76–2.67) and 2.55 (1.50–3.58), respectively (p Conclusions: There is a significant difference and weak agreement between bolus and continuous thermodilutionderived indices, which must be considered when diagnosing CMD in ACS and CCS patients.  </p