Feature Tracking software offers measurements of myocardial strain, velocities and displacement from cine cardiovascular magnetic resonance (CMR) images. We used it to record deformation parameters in healthy adults and compared values to those obtained by tagging.

Nationally, symptomatic heart failure affects 1.5-2% of Canadians, incurs $3 billion in hospital costs annually and the global burden is expected to double in the next 1–2 decades. The current one-year mortality rate after diagnosis of heart failure remains high at >25%. Consequently, new therapeutic strategies need to be developed for this debilitating condition.

In non-cardioembolic stroke patients, the cardiac manifestations of high blood pressure are of particular interest. Emerging data suggest that echocardiographically determined left ventricular hypertrophy is independently associated with risk of ischemic stroke. The primary objective of this study was to evaluate the frequency of different patterns of left ventricular (LV) remodeling and hypertrophy in a group of consecutive patients admitted with non-cardioembolic stroke or transient ischemic attack (TIA). In particular, we were interested in how often the relative wall thickness (RWT) was abnormal in patients with normal LV mass index (LVMI). As both abnormal RWT and LVMI indicate altered LV remodeling, the secondary objective of this research was to study whether a significant number of patients would be missing the diagnosis of LV remodeling if the RWT is not measured. All patients were referred within 48 hours after a stroke or a TIA for a clinically indicated transthoracic echocardiogram. The echocardiographic findings of consecutive patients with non-cardioembolic stroke or TIA were analyzed. All necessary measurements were performed in 368 patients, who were enrolled in the study. Mean age was 63.7 ± 12.5 years, 64.4% men. Concentric remodeling carried the highest frequency, 49.2%, followed by concentric hypertrophy, 30.7%, normal pattern, 15.5%, and eccentric hypertrophy, 4.1%. The frequency of abnormal left ventricular RWT (80.4%) was significantly higher than that of abnormal LVMI (35.3%), (McNemar P < 0.05). In this group of non-cardioembolic stroke patients, abnormal LV remodeling as assessed by relative wall thickness is very frequent. As RWT was often found without increased LV mass, the abnormal left ventricular geometry may be missed if RWT is not measured or reported.

Background: There are limited data on what is the minimum change that can be detected in cancer patients undergoing treatment with cardiotoxic drugs and are referred for monitoring left ventricular (LV) function. Objective: To assess the variability in the measurement of LV volumes and ejection fraction (EF) in contrast echocardiography and to determine the minimum detectable difference (MDD) between two EF measurements that can be deemed significant. Methods: A total of 150 patients were divided into three groups according to EF (EF 60%). Each group consisted of 50 randomly selected cancer patients who underwent contrast echocardiography between July 2010 and May 2014. Repeated measurements of LV volumes and EF were performed offline by a sonographer and a cardiologist. Inter-observer variability was assessed by analysis of variance. Measurement error was estimated by standard error of measurement and MDD. Results: The 95% confidence interval with a single measurement of EF was 2 percentage points in the groups of patients with EF 60%, and 2.5 percentage points for patients with EF 53–60%. The MDD for EF, end-diastolic volume and end-systolic volume that could be recognized with 95% confidence interval were 4 percentage points, 7 mL and 4 mL, respectively. Conclusion: Contrast echocardiography is a reliable tool for serial measurements of EF to monitor cardiotoxicity due to chemotherapy. In a high-volume echocardiography laboratory with experienced staff, the MDD for EF of 4 percentage points on a good-quality recording demonstrates the high reproducibility of the Simpson’s method using contrast echocardiography.

Background: Echocardiography is crucial to understanding cardiac function in the Intensive Care Unit (ICU), often by measuring the left ventricular ejection fraction (LVEF). Traditionally, measures of LVEF are completed as part of a comprehensive examination by an expert sonographer or cardiologist, but front-line practitioners increasingly perform focused point-of-care estimates of LVEF while managing life-threatening illness. The two main echocardiographic windows used to grossly estimate LVEF are parasternal and apical windows. Artificial intelligence (AI) algorithms have recently been developed to assist non-experts in obtaining and interpreting point-of-care ultrasound (POCUS) echo images. We tested the feasibility, accuracy and reliability of novice users estimating LVEF using POCUS-AI echo. Methods: A total of 30 novice users (most never holding an ultrasound probe before) received 2 h of instruction, then scanned ICU patients (10 patients, 80 scans) using the Exo Iris POCUS probe with AI guidance tool. They were permitted up to 5 min to attempt parasternal long axis (PLAX) and apical 4 chamber (A4C) views. AI-reported LVEF results from these scans were compared to gold-standard LVEF obtained by an expert echo sonographer. To further assess accuracy, this sonographer also scanned another 65 patients using Exo Iris POCUS-AI vs. conventional protocol. Results: Novices obtained images sufficient to estimate LVEF in 96% of patients in <5 min. Novices obtained PLAX views significantly faster than A4C (1.5 min vs. 2.3 min). Inter-rater reliability of LVEF estimation was very high (ICC 0.88–0.94) whether images were obtained by novices or experts. In n = 65 patients, POCUS-AI LVEF was highly specific for a decreased LVEF ≤ 40% (SP = 90% for PLAX) but only moderately sensitive (SN = 56–70%). Conclusions: Estimating cardiac LVEF from AI-enhanced POCUS is highly feasible even for novices in ICU settings, particularly using the PLAX view. POCUS-AI LVEF results were highly consistent whether performed by novice or expert. When AI detected a decreased LVEF, it was highly accurate, although a normal LVEF reported by POCUS-AI was not necessarily reassuring. This POCUS-AI tool could be clinically useful to rapidly confirm a suspected low LVEF in an ICU patient. Further improvements to sensitivity for low LVEF are needed.