背景：癌症治疗相关心脏功能障碍（CTRCD）的风险分层策略依赖于专门成像的连续监测，限制了其可扩展性。我们的目的是研究人工智能 (AI) 在心电图 (ECG) 图像中的应用，作为成像风险生物标志物的替代品，及其与早期 CTRCD 的关联。方法：在美国的卫生系统（2013-2023）中，我们确定了 1,550 名接受蒽环类药物和/或曲妥珠单抗治疗乳腺癌的无心肌病患者（年龄 60 [IQR:51-69] 岁，1223 [78.9%] 女性）或非霍奇金淋巴瘤，且在治疗前 ≤12 个月内进行过心电图检查。我们将经过验证的左心室收缩功能障碍 (LVSD) AI 模型部署到基线心电图图像，并根据 AI-ECG LVSD 概率 <0.01、0.01 至 0.1 和 ≥0.1（阳性筛查）定义低、中和高风险组）， 分别。我们探讨了治疗后 12 个月内与早期 CTRCD（新发心肌病、心力衰竭或左心室射血分数 [LVEF]<50%）或 LVEF<40% 的关联。在机械分析中，我们在 15 天内进行的研究中评估了整体纵向应变 (GLS) 和 AI-ECG LVSD 概率之间的关联。结果：在 1,550 名无已知心肌病的患者中（中位随访时间：14.1 [IQR：13.4-17.1] 个月），83 名 (5.4%)、562 名 (36.3%) 和 905 名 (58.4%) 被分类为高、中和基线 AI-ECG 风险较低。高风险与低风险 AI-ECG 筛查（≥0.1 vs <0.01）与 CTRCD 发生率升高 3.4 倍和 13.5 倍相关（adj.HR 3.35 [95%CI:2.25-4.99]）和 LVEF分别 <40%（调整 HR 13.52 [95%CI：5.06-36.10]）。事后分析支持 CTRCD 事件发生后 6 至 12 个月内 AI-ECG 概率的纵向增加。在 1,428 个时间相关的超声心动图和 ECG 中，AI-ECG LVSD 概率与较差的 GLS 相关（GLS -19% [IQR：-21 至 -17%]，概率 <0.1，至 -15% [IQR：-15 至 - 9%] ≥0.5 [p<0.001]）。结论：应用于基线心电图图像的 AI 可以对乳腺癌或非霍奇金淋巴瘤治疗中与蒽环类药物或曲妥珠单抗暴露相关的早期 CTRCD 风险进行分层。

Background: Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intelligence (AI) to electrocardiographic (ECG) images as a surrogate for imaging risk biomarkers, and its association with early CTRCD. Methods: Across a U.S.-based health system (2013-2023), we identified 1,550 patients (age 60 [IQR:51-69] years, 1223 [78.9%] women) without cardiomyopathy who received anthracyclines and/or trastuzumab for breast cancer or non-Hodgkin lymphoma and had ECG performed ≤12 months before treatment. We deployed a validated AI model of left ventricular systolic dysfunction (LVSD) to baseline ECG images and defined low, intermediate, and high-risk groups based on AI-ECG LVSD probabilities of <0.01, 0.01 to 0.1, and ≥0.1 (positive screen), respectively. We explored the association with early CTRCD (new cardiomyopathy, heart failure, or left ventricular ejection fraction [LVEF]<50%), or LVEF<40%, up to 12 months post-treatment. In a mechanistic analysis, we assessed the association between global longitudinal strain (GLS) and AI-ECG LVSD probabilities in studies performed within 15 days of each other. Results: Among 1,550 patients without known cardiomyopathy (median follow-up: 14.1 [IQR:13.4-17.1] months), 83 (5.4%), 562 (36.3%) and 905 (58.4%) were classified as high, intermediate, and low risk by baseline AI-ECG. A high- vs low-risk AI-ECG screen (≥0.1 vs <0.01) was associated with a 3.4-fold and 13.5-fold higher incidence of CTRCD (adj.HR 3.35 [95%CI:2.25-4.99]) and LVEF<40% (adj.HR 13.52 [95%CI:5.06-36.10]), respectively. Post-hoc analyses supported longitudinal increases in AI-ECG probabilities within 6-to-12 months of a CTRCD event. Among 1,428 temporally-linked echocardiograms and ECGs, AI-ECG LVSD probabilities were associated with worse GLS (GLS -19% [IQR:-21 to -17%] for probabilities <0.1, to -15% [IQR:-15 to -9%] for ≥0.5 [p<0.001]). Conclusions: AI applied to baseline ECG images can stratify the risk of early CTRCD associated with anthracycline or trastuzumab exposure in the setting of breast cancer or non-Hodgkin lymphoma therapy.