Applying a deep learning algorithm to standard chest X-rays doubled the risk of future heart failure hospitalization in patients predicted to have pulmonary hypertension, with a hazard ratio of 1.9.
Cohort (n=900)
No
Does an artificial intelligence deep learning model applied to standard chest X-rays accurately predict elevated pulmonary artery pressure and risk of heart failure in patients with suspected pulmonary hypertension?
A deep learning algorithm applied to standard chest X-rays can identify elevated pulmonary artery pressure with modest accuracy and stratify the risk of future heart failure events.
Effect estimate: HR 1.9 (95% CI 1.5-2.4)
Absolute Event Rate: 37% vs 22%
p-value: p=<0.001
Abstract Accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely treatment. We hypothesized that application of artificial intelligence (AI) to the chest X-ray (CXR) could identify elevated pulmonary artery pressure (PAP) and stratify the risk of heart failure hospitalization with PH. We retrospectively enrolled a total of 900 consecutive patients with suspected PH. We trained a convolutional neural network to identify patients with elevated PAP (> 20 mmHg) as the actual value of PAP. The endpoints in this study were admission or occurrence of heart failure with elevated PAP. In an independent evaluation set for detection of elevated PAP, the area under curve (AUC) by the AI algorithm was significantly higher than the AUC by measurements of CXR images and human observers (0.71 vs. 0.60 and vs. 0.63, all p < 0.05). In patients with AI predicted PH had 2-times the risk of heart failure with PH compared with those without AI predicted PH. This preliminary work suggests that applying AI to the CXR in high risk groups has limited performance when used alone in identifying elevated PAP. We believe that this report can serve as an impetus for a future large study.
Kusunose et al. (Tue,) conducted a cohort in pulmonary hypertension (n=900). deep learning algorithm for chest X-ray vs. standard chest X-ray measurements and human observers was evaluated on admission or occurrence of heart failure with elevated pulmonary artery pressure (HR 1.9, 95% CI 1.5-2.4, p=<0.001). Applying a deep learning algorithm to standard chest X-rays doubled the risk of future heart failure hospitalization in patients predicted to have pulmonary hypertension, with a hazard ratio of 1.9.