Behind Traditional Semi-quantitative Scores of Myocardial Perfusion Imaging: An Eye on Niche Parameters

Prognostic Value of Resting Left Ventricular Sphericity Indexes in Coronary Artery Disease With Preserved Ejection Fraction

BACKGROUND

Adverse left ventricular remodeling is a significant cardiovascular predictor for patients with coronary artery disease and preserved left ventricular ejection fraction (LVEF). However, the remodeling indexes reflecting left ventricular spherization by myocardial perfusion imaging are underexplored.

METHODS AND RESULTS

727 patients (mean age 59.8±13.5 years, 329 women) diagnosed or suspected coronary artery disease with preserved LVEF who underwent resting myocardial perfusion imaging were retrospectively enrolled. The myocardial perfusion imaging findings including the total perfusion deficit and sphericity indexes (shape index (SI) and eccentricity index (EI) obtained from gated (QGS) and non-gated (QPS) images) were collected. Major adverse cardiovascular events (MACE) were followed up for 45.1±22.0 months. All patients were divided into 4 subgroups based on total perfusion deficit at 10% and LVEF at 65%. Univariable comparative analyses were performed in 5 cohorts (all patients and 4 subgroups). Patients who experienced MACE displayed higher SI and/or lower EI (all P<0.05). Kaplan-Meier survival analyses suggested significant differences for SIQPS in all 5 cohorts, for EIQPS and EIQGS in 4 cohorts, and for end-systolic and end-diastolic SIQGS in 3 cohorts (all P<0.05). Multivariate Cox analysis showed that abnormal SI and EI remained statistically significant predictors for MACE after adjusting for total perfusion deficit, LVEF, and other confounding factors.

CONCLUSIONS

For patients diagnosed or suspected of coronary artery disease with preserved or supra-normal LVEF, resting sphericity indexes by myocardial perfusion imaging displayed incremental long-term prognostic value. Among these indicators, SIQPS is particularly promising across different perfusion or preserved functional conditions.

Cardiac MRI segmentation using shifted-window multilayer perceptron mixer networks

Objectives. In this work, we proposed a deep-learning segmentation algorithm for cardiac magnetic resonance imaging to aid in contouring of the left ventricle, right ventricle, and Myocardium (Myo).Approach.We proposed a shifted window multilayer perceptron (Swin-MLP) mixer network which is built upon a 3D U-shaped symmetric encoder-decoder structure. We evaluated our proposed network using public data from 100 individuals. The network performance was quantitatively evaluated using 3D volume similarity between the ground truth contours and the predictions using Dice score coefficient, sensitivity, and precision as well as 2D surface similarity using Hausdorff distance (HD), mean surface distance (MSD) and residual mean square distance (RMSD). We benchmarked the performance against two other current leading edge networks known as Dynamic UNet and Swin-UNetr on the same public dataset.Results.The proposed network achieved the following volume similarity metrics when averaged over three cardiac segments: Dice = 0.952 ± 0.017, precision = 0.948 ± 0.016, sensitivity = 0.956 ± 0.022. The average surface similarities were HD = 1.521 ± 0.121 mm, MSD = 0.266 ± 0.075 mm, and RMSD = 0.668 ± 0.288 mm. The network shows statistically significant improvement in comparison to the Dynamic UNet and Swin-UNetr algorithms for most volumetric and surface metrics withp-value less than 0.05. Overall, the proposed Swin-MLP mixer network demonstrates better or comparable performance than competing methods.Significance.The proposed Swin-MLP mixer network demonstrates more accurate segmentation performance compared to current leading edge methods. This robust method demonstrates the potential to streamline clinical workflows for multiple applications.

Prognostic value of heart rate reserve in patients with suspected coronary artery disease undergoing stress myocardial perfusion imaging

BACKGROUND

Chronotropic incompetence is common in patients with cardiovascular disease and is associated with increased risk of adverse events. We assessed the incremental prognostic value of heart rate reserve (HRR) over stress myocardial perfusion single-photon emission computed tomography (MPS) findings in patients with suspected coronary artery disease (CAD).

METHODS

We studied 866 patients with suspected CAD undergoing exercise stress-MPS as part of their diagnostic program. The primary study endpoint was all-cause mortality. All patients were followed for at least 5 years. HRR was calculated as the difference between peak exercise and resting HR, divided by the difference of age-predicted maximal and resting HR and expressed as percentage.

RESULTS

During 7 years follow-up, 61 deaths occurred, with a 7% cumulative event rate. Patients experiencing death were older (P < .001), and had a higher prevalence of male gender (P < .001) and diabetes (P < .05). Patients with event also had lower values of HRR (65% ± 27% vs 73% ± 18%, P < .0001) and higher prevalence of stress-induced myocardial ischemia (25% vs 8%, P < .0001). Male gender, HRR and stress-induced ischemia were independent predictors of all-cause mortality (all P < .01). HRR improved the prognostic power of a model including clinical data and MPS findings, increasing the global χ2 from 66 to 82 (P < .005).

CONCLUSIONS

Chronotropic incompetence has independent and incremental prognostic value in predicting all-cause mortality in patients with suspected CAD undergoing exercise stress-MPS. Hence, the evaluation of HRR may further improve patients' risk stratification.