Abstract Aims Pre-capillary pulmonary hypertension (PHTN), typically due to intrinsic pulmonary pathology, requires right heart catheterization (RHC) for diagnosis. ePLAR, the echocardiographic pulmonary to left atrial ratio [calculated: tricuspid regurgitation maximum velocity (TRVmax) divided by mitral valve E to e′ wave ratio (E/e′)], has been demonstrated as a promising non-invasive surrogate for characterization of pre-capillary PHTN. As such, this study aimed to further evaluate the diagnostic utility of ePLAR in a large cohort of patients with PHTN. Methods and results All RHCs between 2018 and 2023 across three tertiary centres were retrospectively reviewed. Patients with PHTN were characterized as pre-capillary or post-capillary (isolated or combined). Concurrent ePLAR was calculated. ROC analysis evaluated the accuracy of ePLAR in detecting pre-capillary PHTN. Overall, 2235 patients had PHTN by RHC, mean age 63.5 ± 14.7 years, 53.5% male. Of these, 43.3% had pre-capillary PHTN. ROC analysis demonstrated ePLAR to have good accuracy in detection of pre-capillary PHTN (AUC 0.760), with a cutoff of 0.20 m/s demonstrating a sensitivity and specificity of 77% and 60% respectively. This persisted on sensitivity analysis for contemporaneous investigations and for right ventricular function. Conclusion In this large cohort, ePLAR was validated as an accurate tool for identifying patients with pre-capillary PHTN. This widely available, non-invasive, and reproducible parameter can have an important role in the work up of PHTN and may guide the need for invasive testing.
The association between sodium-glucose cotransporter 2 inhibitor treatment and survival in patients with cancer therapy-related cardiac dysfunction
ABSTRACTBackgroundPrior studies have documented that patients with colorectal cancer (CRC) are at an increased risk of cardiovascular disease (CVD).ObjectivesTo examine coronary artery calcium (CAC) as a marker of subclinical atherosclerosis and its association with major adverse cardiovascular events (MACE) in patients with CRC across the cancer treatment trajectory.MethodsAdults with newly diagnosed CRC were enrolled in the prospective ColoCare study from 2017 to 2024. CAC was measured from routine diagnostic computed tomography (CT) and positron emission tomography‐CT scans at CRC diagnosis until 5 years post‐diagnosis. Atherosclerosis was defined as the presence of CAC. We used multivariable‐adjusted Fine and Gray models to assess the association between CAC and MACE risk, accounting for competing risks.ResultsAmong 300 CRC patients, the most common CVD risk factors at cancer diagnosis were hypertension (37%), hyperlipidemia (24%), and diabetes (14%). During follow‐up (median = 5.3 years), 75 (25%) individuals experienced MACE: stroke (3%), new/worsening HF (9%), HF exacerbation requiring hospitalization (2%), coronary revascularization (3%), and death (19%). Among individuals with imaging at baseline (n = 101), 37 (36.6%) had CAC, and statins were not prescribed in 11 (55.0%) patients with moderate/high CAC. For those with serial imaging (n = 61), 31.1% showed worsening CAC and 3% developed new CAC. Baseline CAC conferred a higher risk of MACE (HR = 4.79; 95% CI: 1.05–21.75, p = 0.04) after accounting for cancer‐related deaths as a competing risk.ConclusionsSubclinical atherosclerosis and MACE are common among patients with CRC. Integrating CAC from routine cancer imaging can identify patients who may benefit from cardio‐preventive treatment.
Utility of Cardiac CT for Cardiomyopathy Phenotyping
Cardiac computed tomography (CT) has rapidly advanced, becoming an invaluable tool for diagnosing and prognosticating various cardiovascular diseases. While echocardiography and cardiac magnetic resonance imaging (CMR) remain the gold standards for myocardial assessment, modern CT technologies offer enhanced spatial resolution, making it an essential tool in clinical practice. Cardiac CT has expanded beyond coronary artery disease evaluation, now playing a key role in assessing cardiomyopathies and structural heart diseases. Innovations like photon-counting CT enable precise estimation of myocardial extracellular volume, facilitating the detection of infiltrative disorders and myocardial fibrosis. Additionally, CT-based myocardial strain analysis allows for the classification of impaired myocardial contractility, while quantifying cardiac volumes and function remains crucial in cardiomyopathy evaluation. This review explores the emerging role of cardiac CT in cardiomyopathy phenotyping, emphasizing recent technological advancements.
Applications of Artificial Intelligence for the Prediction and Diagnosis of Cancer Therapy-Related Cardiac Dysfunction in Oncology Patients
Cardiovascular diseases and cancer are the leading causes of morbidity and mortality in modern society. Expanding cancer therapies that have improved prognosis may also be associated with cardiotoxicity, and extended life span after survivorship is associated with the increasing prevalence of cardiovascular disease. As such, the field of cardio-oncology has been rapidly expanding, with an aim to identify cardiotoxicity and cardiac disease early in a patient who is receiving treatment for cancer or is in survivorship. Artificial intelligence is revolutionizing modern medicine with its ability to identify cardiac disease early. This article comprehensively reviews applications of artificial intelligence specifically applied to electrocardiograms, echocardiography, cardiac magnetic resonance imaging, and nuclear imaging to predict cardiac toxicity in the setting of cancer therapies, with a view to reduce early complications and cardiac side effects from cancer therapies such as chemotherapy, radiation therapy, or immunotherapy.