Coronary vascular function in females with history of hypertensive disorders of pregnancy an oxygenation-sensitive cardiovascular magnetic resonance imaging study

Abstract

Abstract Background Hypertensive disorders of pregnancy (HDP), including gestational hypertension and preeclampsia, have been associated with increased risk for cardiovascular disease decades after HDP pregnancy. HDP is thought to unmask pre-existing cardiovascular risk in the mother; and in addition HDP triggers a cascade of inflammatory and oxidative stress which leads to vascular endothelial dysfunction and abnormalities in cardiac structure and function evident early post-partum that may persist sub-clinically. Oxygenation-sensitive cardiovascular magnetic resonance (OS-CMR) is an emerging approach that can identify dynamic changes of myocardial oxygenation as a marker for coronary vascular function. The objective of this study was to assess coronary vascular function in females with history of HDP using OS-CMR. Methods We analyzed data from two short axis OS-CMR slices in 20 females with history of HDP, including gestational hypertension, preeclampsia and HELLP syndrome (hemolysis, elevated liver enzymes, and low platelets) and 20 healthy controls with history of normal pregnancy acquired on a 1.5T MRI scanner. Images were analyzed using a prototype tissue oxygenation module. The images were normalized for signal intensity to both ventricular blood pools. We used both traditional statistics and feature selection machine learning algorithms to select for predictive biomarkers in the dataset. Finally, we used a random forest classifier model for disease classification. We report area under the receiver operating curve (AUROC) as a metric for diagnostic accuracy. Results Global breathing-induced myocardial oxygenation reserve (B-MORE) of the mid left ventricular slice was significantly reduced in HDP females (-1.6 ± 14.8) when compared to healthy controls (11.3 ± 17.2, p=0.03), when normalized to ventricular blood pools (Figure 1A). Our feature selection algorithm selected the signal intensity during end-systole normalized to the series as the most predictive biomarker. Our model, which integrated data from >3,300 discrete data points per participant, correctly differentiated healthy controls from women with HDP history with a 90% ± 3% AUROC accuracy, indicating high sensitivity and specificity (Figure 1B). Conclusion Compared to healthy controls, females with history of HDP have abnormal coronary vascular function, as shown by reduced myocardial oxygenation on OS-CMR. Combining advanced machine learning approaches can further enhance the potential application of OS-CMR to risk stratify females with adverse pregnancy outcomes susceptible to future cardiovascular disease.