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心脏植入式电子设备制造商的影像学识别:智能手机起搏器识别应用与X线标识对比

Radiographic Identification of Cardiac Implantable Electronic Device Manufacturer: Smartphone Pacemaker-ID Application Versus X-ray Logo.

作者信息

Boyle Bridget, Love Charles J, Marine Joseph E, Chrispin Jonathan, Barth Andreas S, Rickard John W, Spragg David D, Berger Ronald, Calkins Hugh, Sinha Sunil K

机构信息

Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH, USA.

出版信息

J Innov Card Rhythm Manag. 2022 Aug 15;13(8):5104-5110. doi: 10.19102/icrm.2022.130803. eCollection 2022 Aug.

Abstract

Radiographic identification of the cardiac implantable electronic device (CIED) manufacturer facilitates urgent interrogation of an unknown CIED. In the past, we relied on visualizing a manufacturer-specific X-ray logo. Recently, a free smartphone application ("Pacemaker-ID") was made available. A photograph of a chest X-ray was subjected to an artificial intelligence (AI) algorithm that uses manufacturer characteristics (canister shape, battery design) for identification. We sought to externally validate the accuracy of this smartphone application as a point-of-care (POC) diagnostic tool, compare on-axis to off-axis photo accuracy, and compare it to X-ray logo visualization for manufacturer identification. We reviewed operative reports and chest X-rays in 156 pacemaker and 144 defibrillator patients to visualize X-ray logos and to test the application with 3 standard (on-axis) and 4 non-standard (off-axis) photos (20° cranial; caudal, leftward, and rightward). Contingency tables were created and chi-squared analyses (P < .05) were completed for manufacturer and CIED type. The accuracy of the application was 91.7% and 86.3% with single and serial application(s), respectively; 80.7% with off-axis photos; and helpful for all manufacturers (range, 85.4%-96.6%). Overall, the application proved superior to the X-ray logo, visualized in 56% overall (P < .0001) but varied significantly by manufacturer (range, 7.7%-94.8%; P < .00001). The accuracy of the Pacemaker-ID application is consistent with reports from its creators and superior to X-ray logo visualization. The accuracy of the application as a POC tool can be enhanced and maintained with further AI training using recent CIED models. Some manufacturers can enhance their X-ray logos by improving placement and design.

摘要

通过放射成像识别心脏植入式电子设备(CIED)的制造商有助于对未知的CIED进行紧急问询。过去,我们依靠观察特定于制造商的X线标识来识别。最近,一款免费的智能手机应用程序(“起搏器识别”)问世了。胸部X线照片被输入一种人工智能(AI)算法,该算法利用制造商的特征(罐体形状、电池设计)进行识别。我们试图从外部验证这款智能手机应用程序作为即时医疗(POC)诊断工具的准确性,比较正位照片与非正位照片的识别准确性,并将其与通过X线标识进行制造商识别的方法进行比较。我们回顾了156例起搏器患者和144例除颤器患者的手术报告及胸部X线片,以观察X线标识,并使用3张标准(正位)照片和4张非标准(非正位)照片(头侧20°;尾侧、左侧和右侧)对该应用程序进行测试。针对制造商和CIED类型创建了列联表并完成了卡方分析(P < 0.05)。该应用程序单次应用和连续应用时的准确率分别为91.7%和86.3%;非正位照片的准确率为80.7%;对所有制造商都有帮助(范围为85.4%-96.6%)。总体而言,该应用程序被证明优于X线标识,X线标识的总体可视化率为56%(P < 0.0001),但不同制造商之间差异显著(范围为7.7%-94.8%;P < 0.00001)。“起搏器识别”应用程序的准确性与开发者的报告一致,且优于X线标识可视化。通过使用最新的CIED模型进行进一步的AI训练,可以提高并保持该应用程序作为POC工具的准确性。一些制造商可以通过改进放置位置和设计来增强其X线标识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6484/9436398/636bb9f4a8a5/icrm-13-5104-g001.jpg

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