Browsing by Subject "Ischemic heart disease"

Now showing 1 - 5 of 5
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    30-minute CMR for common clinical indications: a Society for Cardiovascular Magnetic Resonance white paper
    (BMC, 2022-03-01) Raman, Subha V.; Markl, Michael; Patel, Amit R.; Bryant, Jennifer; Allen, Bradley D.; Plein, Sven; Seiberlich, Nicole; Medicine, School of Medicine
    Background: Despite decades of accruing evidence supporting the clinical utility of cardiovascular magnetic resonance (CMR), adoption of CMR in routine cardiovascular practice remains limited in many regions of the world. Persistent use of long scan times of 60 min or more contributes to limited adoption, though techniques available on most scanners afford routine CMR examination within 30 min. Incorporating such techniques into standardize protocols can answer common clinical questions in daily practice, including those related to heart failure, cardiomyopathy, ventricular arrhythmia, ischemic heart disease, and non-ischemic myocardial injury. BODY: In this white paper, we describe CMR protocols of 30 min or shorter duration with routine techniques with or without stress perfusion, plus specific approaches in patient and scanner room preparation for efficiency. Minimum requirements for the scanner gradient system, coil hardware and pulse sequences are detailed. Recent advances such as quantitative myocardial mapping and other add-on acquisitions can be incorporated into the proposed protocols without significant extension of scan duration for most patients. Conclusion: Common questions in clinical cardiovascular practice can be answered in routine CMR protocols under 30 min; their incorporation warrants consideration to facilitate increased access to CMR worldwide.
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    Comparison of Troponin Elevation, Prior Myocardial Infarction, and Chest Pain in Acute Ischemic Heart Failure
    (Elsevier, 2020-05) Freitas, Cassandra; Wang, Xuesong; Ge, Yin; Ross, Heather J.; Austin, Peter C.; Pang, Peter S.; Ko, Dennis T.; Farkouh, Michael E.; Stukel, Therese A.; McMurray, John J.V.; Lee, Douglas S.; Emergency Medicine, School of Medicine
    Background: Patients with heart failure (HF) with concomitant ischemic heart disease (IHD) have not been well characterized. We examined survival of patients with ischemic HF syndrome (IHFS), defined as presentation with acute HF and concomitant features suggestive of IHD. Methods: Patients were included if they presented with acute HF to hospitals in Ontario, Canada. IHD was defined by any of the following criteria: angina/chest pain, prior myocardial infarction (MI), or troponin elevation that was above the upper limit of normal (mild) or suggestive of cardiac injury. Deaths were determined after hospital presentation. Results: Of 5353 patients presenting with acute HF, 4088 (76.4%) exhibited features of IHFS. Patients with IHFS demonstrated a higher rate of 30-day (hazard ratio [HR], 1.89; 95% confidence interval [CI], 1.33-2.68) and 1-year death (HR, 1.16, 95% CI, 1.00-1.35) compared with those with nonischemic HF. Troponin elevation demonstrated the strongest association with mortality. Mildly elevated troponin was associated with increased hazard over 30-day (HR, 1.77; 95% CI, 1.12-2.81) and 1-year (HR, 1.63; 95% CI, 1.38-1.93) mortality. Troponins indicative of cardiac injury were associated with increased hazard of death over 30 days (HR, 2.33; 95% CI, 1.63-3.33) and 1 year (HR, 1.40; 95% CI, 1.21-1.61). The association between elevated troponin and higher mortality at 30 days was similar in left ventricular ejection fraction subcategories of HF with reduced ejection fraction, HF with mildly reduced ejection fraction, or HF with preserved ejection fraction (P interaction = 0.588). After multivariable adjustment, prior MI and angina were not associated with higher mortality risk. Conclusions: In acute HF, elevated troponin, but not prior MI or angina, was associated with a higher risk of 30-day and 1-year mortality irrespective of left ventricular ejection fraction.
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    Improved robustness for deep learning-based segmentation of multi-center myocardial perfusion cardiovascular MRI datasets using data-adaptive uncertainty–guided space-time analysis
    (Elsevier, 2024) Yalcinkaya, Dilek M.; Youssef, Khalid; Heydari, Bobak; Wei, Janet; Merz, C. Noel Bairey; Judd, Robert; Dharmakumar, Rohan; Simonetti, Orlando P.; Weinsaft, Jonathan W.; Raman, Subha V.; Sharif, Behzad; Medicine, School of Medicine
    Background: Fully automatic analysis of myocardial perfusion cardiovascular magnetic resonance imaging datasets enables rapid and objective reporting of stress/rest studies in patients with suspected ischemic heart disease. Developing deep learning techniques that can analyze multi-center datasets despite limited training data and variations in software (pulse sequence) and hardware (scanner vendor) is an ongoing challenge. Methods: Datasets from three medical centers acquired at 3T (n = 150 subjects; 21,150 first-pass images) were included: an internal dataset (inD; n = 95) and two external datasets (exDs; n = 55) used for evaluating the robustness of the trained deep neural network (DNN) models against differences in pulse sequence (exD-1) and scanner vendor (exD-2). A subset of inD (n = 85) was used for training/validation of a pool of DNNs for segmentation, all using the same spatiotemporal U-Net architecture and hyperparameters but with different parameter initializations. We employed a space-time sliding-patch analysis approach that automatically yields a pixel-wise "uncertainty map" as a byproduct of the segmentation process. In our approach, dubbed data-adaptive uncertainty-guided space-time (DAUGS) analysis, a given test case is segmented by all members of the DNN pool and the resulting uncertainty maps are leveraged to automatically select the "best" one among the pool of solutions. For comparison, we also trained a DNN using the established approach with the same settings (hyperparameters, data augmentation, etc.). Results: The proposed DAUGS analysis approach performed similarly to the established approach on the inD (Dice score for the testing subset of inD: 0.896 ± 0.050 vs 0.890 ± 0.049; p = n.s.) whereas it significantly outperformed on the exDs (Dice for exD-1: 0.885 ± 0.040 vs 0.849 ± 0.065, p < 0.005; Dice for exD-2: 0.811 ± 0.070 vs 0.728 ± 0.149, p < 0.005). Moreover, the number of image series with "failed" segmentation (defined as having myocardial contours that include bloodpool or are noncontiguous in ≥1 segment) was significantly lower for the proposed vs the established approach (4.3% vs 17.1%, p < 0.0005). Conclusion: The proposed DAUGS analysis approach has the potential to improve the robustness of deep learning methods for segmentation of multi-center stress perfusion datasets with variations in the choice of pulse sequence, site location, or scanner vendor.
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    Improved Robustness for Deep Learning-based Segmentation of Multi-Center Myocardial Perfusion MRI Datasets Using Data Adaptive Uncertainty-guided Space-time Analysis
    (ArXiv, 2024-08-09) Yalcinkaya, Dilek M.; Youssef, Khalid; Heydari, Bobak; Wei, Janet; Merz, Noel Bairey; Judd, Robert; Dharmakumar, Rohan; Simonetti, Orlando P.; Weinsaft, Jonathan W.; Raman, Subha V.; Sharif, Behzad; Medicine, School of Medicine
    Background: Fully automatic analysis of myocardial perfusion MRI datasets enables rapid and objective reporting of stress/rest studies in patients with suspected ischemic heart disease. Developing deep learning techniques that can analyze multi-center datasets despite limited training data and variations in software (pulse sequence) and hardware (scanner vendor) is an ongoing challenge. Methods: Datasets from 3 medical centers acquired at 3T (n = 150 subjects; 21,150 first-pass images) were included: an internal dataset (inD; n = 95) and two external datasets (exDs; n = 55) used for evaluating the robustness of the trained deep neural network (DNN) models against differences in pulse sequence (exD-1) and scanner vendor (exD-2). A subset of inD (n = 85) was used for training/validation of a pool of DNNs for segmentation, all using the same spatiotemporal U-Net architecture and hyperparameters but with different parameter initializations. We employed a space-time sliding-patch analysis approach that automatically yields a pixel-wise "uncertainty map" as a byproduct of the segmentation process. In our approach, dubbed Data Adaptive Uncertainty-Guided Space-time (DAUGS) analysis, a given test case is segmented by all members of the DNN pool and the resulting uncertainty maps are leveraged to automatically select the "best" one among the pool of solutions. For comparison, we also trained a DNN using the established approach with the same settings (hyperparameters, data augmentation, etc.). Results: The proposed DAUGS analysis approach performed similarly to the established approach on the internal dataset (Dice score for the testing subset of inD: 0.896 ± 0.050 vs. 0.890 ± 0.049; p = n.s.) whereas it significantly outperformed on the external datasets (Dice for exD-1: 0.885 ± 0.040 vs. 0.849 ± 0.065, p < 0.005; Dice for exD-2: 0.811 ± 0.070 vs. 0.728 ± 0.149, p < 0.005). Moreover, the number of image series with "failed" segmentation (defined as having myocardial contours that include bloodpool or are noncontiguous in ≥1 segment) was significantly lower for the proposed vs. the established approach (4.3% vs. 17.1%, p < 0.0005). Conclusions: The proposed DAUGS analysis approach has the potential to improve the robustness of deep learning methods for segmentation of multi-center stress perfusion datasets with variations in the choice of pulse sequence, site location or scanner vendor.
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    The Significance of Historical Troponin Elevation in Acute Heart Failure: Not as Reassuring as Previously Assumed
    (Wiley, 2023) Harrison, Nicholas E.; Ehrman, Robert; Pang, Peter; Armitage, Sarah; Abidov, Aiden; Perkins, Daniel; Peacock, Johnathon; Montelauro, Nicholas; Gupta, Sushane; Favot, Mark J.; Levy, Phillip; Emergency Medicine, School of Medicine
    Background: Historical cardiac troponin (cTn) elevation is commonly interpreted as lessening the significance of current cTn elevations at presentation for acute heart failure (AHF). Evidence for this practice is lacking. Our objective was to determine the incremental prognostic significance of historical cTn elevation compared to cTn elevation and ischemic heart disease (IHD) history at presentation for AHF. Methods: A total of 341 AHF patients were prospectively enrolled at five sites. The composite primary outcome was death/cardiopulmonary resuscitation, mechanical cardiac support, intubation, new/emergent dialysis, and/or acute myocardial infarction (AMI)/percutaneous coronary intervention (PCI)/coronary artery bypass grafting (CABG) at 90 days. Secondary outcomes were 30-day AMI/PCI/CABG and in-hospital AMI. Logistic regression compared outcomes versus initial emergency department (ED) cTn, the most recent electronic medical record cTn, estimated glomerular filtration rate, age, left ventricular ejection fraction, and IHD history (positive, negative by prior coronary workup, or unknown/no prior workup). Results: Elevated cTn occurred in 163 (49%) patients, 80 (23%) experienced the primary outcome, and 29 had AMI (9%). cTn elevation at ED presentation, adjusted for historical cTn and other covariates, was associated with the primary outcome (adjusted odds ratio [aOR] 2.39, 95% confidence interval [CI] 1.30-4.38), 30-day AMI/PCI/CABG, and in-hospital AMI. Historical cTn elevation was associated with greater odds of the primary outcome when IHD history was unknown at ED presentation (aOR 5.27, 95% CI 1.24-21.40) and did not alter odds of the outcome with known positive (aOR 0.74, 95% CI 0.33-1.70) or negative IHD history (aOR 0.79, 95% CI 0.26-2.40). Nevertheless, patients with elevated ED cTn were more likely to be discharged if historical cTn was also elevated (78% vs. 32%, p = 0.025). Conclusions: Historical cTn elevation in AHF patients is a harbinger of worse outcomes for patients who have not had a prior IHD workup and should prompt evaluation for underlying ischemia rather than reassurance for discharge. With known IHD history, historical cTn elevation was neither reassuring nor detrimental, failing to add incremental prognostic value to current cTn elevation alone.