INCIDENTAL CORONARY ARTERY CALCIUM REPORTING ON CHEST CT SCANS USING NATURAL LANGUAGE PROCESSING: INSIGHTS FROM VETERANS HEALTH ADMINISTRATION

IF 4.3 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS American journal of preventive cardiology Pub Date : 2024-09-01 DOI:10.1016/j.ajpc.2024.100763
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引用次数: 0

Abstract

Therapeutic Area

ASCVD/CVD Risk Assessment

Background

Coronary artery calcium (CAC) is the strongest predictor of cardiovascular events. CAC can be identified on non-cardiac chest CTs, but reporting is inconsistent. We developed a natural language processing (NLP) algorithm to identify incidental CAC reporting on non-gated chest CT reports and described patterns in CAC reporting across the Veterans Health Administration (VHA).

Methods

We identified non-cardiac CT scan reports across the VHA between 2006-2024. We developed an NLP algorithm by creating Regex rules to detect mentions of CAC (none, mild, moderate, severe, or unclassified). We manually annotated 1,060 reports as the gold standard for algorithm development. We iteratively refined an NLP algorithm based on accuracy with the development scans. We validated the algorithm's performance on an independent sample of 1,000 scans and applied the algorithm to all non-cardiac chest CTs in the VHA over the study period. We described the frequency of CAC reporting over time in addition to facility-level variation.

Results

Across 1,000 validation reports, the algorithm had a sensitivity of 99% and a positive predictive value (PPV) of 94% for CAC being mentioned in the CT report. Among reports in which CAC was mentioned, the algorithm had a 99% sensitivity and 97% PPV for correctly noting the presence of CAC. The algorithm had a 96% accuracy for correctly detecting the reported CAC severity.
There were 6,825,889 non-cardiac chest CTs between January 2006 and March 2024 in the VHA. The presence or absence of CAC was described in 2,519,296 reports (37%). CAC reporting was highest among lung cancer screening CTs (49%). CAC reporting increased over time (Table). In 2023, reporting ranged from 0% to 63% across 128 VA facilities.
Among CTs that reported CAC presence or absence, CAC was described as present on 2,425,416 reports (96%). Among CTs that reported CAC presence, CAC severity was unclassified in 56%, mild in 16%, moderate in 13%, and severe in 15% of scans.

Conclusions

CAC is not reported on a majority of non-cardiac chest CTs in a large national cohort, but reporting is increasing over time. Strategies to improve CAC reporting or leverage emerging automated CAC detection algorithms are needed.
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使用自然语言处理报告胸部 CT 扫描中偶然出现的冠状动脉钙化:退伍军人健康管理局的见解
治疗领域心血管疾病/心血管疾病风险评估背景冠状动脉钙化(CAC)是预测心血管事件的最有力指标。非心脏胸部 CT 可识别出 CAC,但报告并不一致。我们开发了一种自然语言处理 (NLP) 算法来识别非门控胸部 CT 报告中的偶然 CAC 报告,并描述了退伍军人健康管理局 (VHA) 中 CAC 报告的模式。我们开发了一种 NLP 算法,通过创建 Regex 规则来检测 CAC 的提及情况(无、轻度、中度、重度或未分类)。我们手动注释了 1,060 份报告,作为算法开发的黄金标准。我们根据开发扫描的准确性反复改进 NLP 算法。我们在 1,000 份扫描的独立样本上验证了该算法的性能,并将该算法应用于研究期间 VHA 的所有非心脏胸部 CT。结果在 1000 份验证报告中,该算法对 CT 报告中提及 CAC 的灵敏度为 99%,阳性预测值 (PPV) 为 94%。在提到 CAC 的报告中,该算法正确指出 CAC 存在的灵敏度为 99%,PPV 为 97%。2006 年 1 月至 2024 年 3 月期间,VHA 共进行了 6,825,889 次非心脏胸部 CT 检查。2006年1月至2024年3月期间,美国退伍军人事务部共进行了6,825,889次非心脏胸部CT检查,其中2,519,296份报告(37%)描述了是否存在CAC。在肺癌筛查 CT 中,CAC 报告率最高(49%)。CAC 报告随时间推移而增加(表)。2023 年,128 家退伍军人机构的报告率从 0% 到 63% 不等。在报告是否存在 CAC 的 CT 中,有 2425416 份报告(96%)将 CAC 描述为存在。在报告存在 CAC 的 CT 中,CAC 严重程度未分类的占 56%,轻度的占 16%,中度的占 13%,重度的占 15%。需要制定策略来改进 CAC 报告或利用新出现的自动 CAC 检测算法。
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来源期刊
American journal of preventive cardiology
American journal of preventive cardiology Cardiology and Cardiovascular Medicine
CiteScore
6.60
自引率
0.00%
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0
审稿时长
76 days
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