High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy With Cardiovascular Deep Learning

Figures

• 

  Figure 1.. Deep Learning Workflow Combining Evaluation of Ventricular Dimensions and Suspicion for Underdiagnosed Diseases A, The deep learning algorithm used parasternal long-axis echocardiogram video as input to derive key points and estimate ventricular dimensions. After identifying patients with left ventricular hypertrophy (LVH), the deep learning workflow used a video-based architecture to distinguish common causes of LVH. B, Correlation of human annotations vs model predictions for ventricular dimensions in data sets from Stanford Health Care (SHC; n = 1200), Cedars-Sinai Medical Center (CSMC; n = 1309), and Unity Imaging Collaborative (n = 1791). C, Model variation on the 3 data sets vs human clinical annotation variation. Middle lines represent means; upper and lower bounds of the boxes, 25th and 75th percentiles; and points, values greater than 1.5 times the IQR. D, Receiver operating characteristic curves for diagnosis of amyloidosis in the SHC validation (n = 813) and test (n = 812) sets. AS indicates aortic stenosis; AUC, area under the curve; CA, cardiac amyloid; HCM, hypertrophic cardiomyopathy; HTN, hypertension; IVS, intraventricular septum; LVID, LV internal dimension;…

• 

  Figure 2.. Beat-to-Beat Evaluation of Ventricular Dimensions A, Model prediction of key points on an individual frame of parasternal long-axis video. B, Frame-by-frame prediction of wall thickness and ventricular dimension and automated detection of systole and diastole allowing for beat-to-beat prediction of ventricular hypertrophy. C, Waterfall plot of individual video variation in beat-to-beat evaluation of ventricular hypertrophy (n = 2320) in the internal test data set. Each video is represented by multiple points along a line representing the measurement of each beat and a line signifying the range of predictions. IVS indicates intraventricular septum; IVSd, intraventricular septum (diastole); LVID, left ventricular internal dimension; LVIDd, left ventricular internal dimension (diastole); LVPW, left ventricular posterior wall.

• 

  Figure 3.. Performance of Disease Cause Classification in the Independent External Validation Cohort A, Receiver operating characteristic curves for detection of cardiac amyloidosis and hypertrophic cardiomyopathy in the Cedars-Sinai Medical Center independent external test set (n = 2351). B, Precision-recall curves for detection of amyloidosis and hypertrophic cardiomyopathy. C, Representative images for selected cases and controls for each cause. AP indicates average precision; AUC, area under the curve.