Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model

Abstract

Background and aims Current non-invasive screening methods for cardiac allograft rejection have shown limited discrimination and are yet to be broadly integrated into heart transplant care. Given electrocardiogram (ECG) changes have been reported with severe cardiac allograft rejection, this study aimed to develop a deep learning model, a form of artificial intelligence, to detect allograft rejection using the 12-lead ECG (AI-ECG). Methods and Results Heart transplant recipients were identified across three Mayo Clinic sites between 1998 and 2021. Twelve-lead digital ECG data and endomyocardial biopsy results were extracted from medical records. Allograft rejection was defined as moderate or severe acute cellular rejection (ACR) based on International Society for Heart and Lung Transplantation guidelines. The extracted data (7,590 unique ECG-biopsy pairs, belonging to 1,427 patients) was partitioned into training (80%), validation (10%), and test sets (10%) such that each patient was included in only one partition. Model performance metrics were based on the test set (n = 140 patients; 758 ECG-biopsy pairs). The AI-ECG detected ACR with an area under the receiver operating curve (AUC) of 0.84 (95% CI: 0.78-0.90) and 95% (19/20; 95% CI: 75%-100%) sensitivity. A prospective proof-of-concept screening study (n = 56; 97 ECG-biopsy pairs) showed the AI-ECG detected ACR with AUC = 0.78 (95% CI: 0.61-0.96) and 100% (2/2; 95% CI: 16%-100%) sensitivity. Conclusion An AI-ECG model is effective for detection of moderate to severe ACR in heart transplant recipients. Our findings could improve transplant care by providing a rapid, non-invasive, and potentially remote screening option for cardiac allograft function.

What Else Can AI See in a Digital ECG?

“…What is most important, after this somewhat limited study, is to make it clear that a positive AI-ECG-based screening result is not intended to dictate therapeutic intervention but rather to support the need for confirmatory testing by endomyocardial biopsy. And a negative AI-ECG screening result would be reassuring and, in the absence of other clinical evidence of rejection, would allow the biopsy to be postponed at the discretion of the attending physician [18].…”

“…Valvular diseases [11] Left ventricular hypertrophy [12] Onset of atrial fibrillation [13,14] Risk of sudden cardiac death [15] Biological age of the patient [16] Concentration of sex hormones [17] Heart transplant rejection [18] Cardiovascular complications of liver transplantation [19] Effects of cardiac resynchronization therapy [20] Pulmonary embolism [21] Identity verification [22]…”