Trends in clinical validation and usage of US Food and Drug Administration-cleared artificial intelligence algorithms for medical imaging
Trends in clinical validation and usage of US Food and Drug Administration-cleared artificial intelligence algorithms for medical imaging
复制标题
DOI：
10.1016/j.crad.2022.09.122
复制
发表时间：
2023-01-11
影响因子：
2.6
通讯作者：
Bai, H. X.
中科院分区：
文献类型：
--
作者：
Khunte, M.;Chae, A.;Bai, H. X.
目的：研究美国食品药品监督管理局（FDA）批准的人工智能（AI）医疗成像设备的现状，并确定临床验证策略的趋势。材料和方法：进行了一项回顾性研究，分析了从美国放射学会（ACR）数据科学研究所AI Central数据库，以确定FDA批准与医学成像相关的AI产品的趋势。每个设备的产品和临床验证信息都是从其各自的公开510（k）摘要或重新分类申请提交中收集的，具体取决于其授权类型。结果：总体而言，数据库包括2008年至2021年11月期间FDA批准的共计151种AI算法。在审查的151份FDA摘要中，97份（64.2%）报告了使用临床数据来验证其器械，6份（4%）报告了研究参与者的人口统计数据，8份（5.3%）报告了所用机器的规格。共有51件（33.8%）AI器械将其临床数据描述为多中心，3件（2%）为单中心，其余97件（64.2%）未详细说明。在78（51.6%）FDA summarized.CONCLUSION：广泛的AI算法已开发用于医学成像的地面真理用于临床验证。大多数器械的FDA摘要都提到了其使用临床数据和患者病例进行器械确认;然而，很少有器械披露了其临床研究中使用的患者人口统计学或机器规格，这可能导致一些消费者质疑其外部确认。(c)2022年皇家放射科医师学院。由爱思唯尔有限公司出版。保留所有权利。
AIM: To examine the current landscape of US Food and Drug Administration (FDA)-approved artificial intelligence (AI) medical imaging devices and identify trends in clinical validation strategy.MATERIALS AND METHODS: A retrospective study was conducted that analysed data extracted from the American College of Radiology (ACR) Data Science Institute AI Central database as of November 2021 to identify trends in FDA clearance of AI products related to medical imaging. Product and clinical validation information of each device was gathered from their respective public 510(k) summary or de novo request submission, depending on their type of authorisation.RESULTS: Overall, the database included a total of 151 AI algorithms that were cleared by the FDA between 2008 and November 2021. Out of the 151 FDA summaries reviewed, 97 (64.2%) reported the use of clinical data to validate their device, with six (4%) revealing study participant demographics, and eight (5.3%) reporting the specifications of the machines used. A total of 51 (33.8%) AI devices characterised their clinical data as multicentre, three (2%) as single-centre, and the remaining 97 (64.2%) did not specify. The ground truth used for clinical validation was specified in 78 (51.6%) FDA summaries.CONCLUSION: A wide breadth of AI algorithms has been developed for medical imaging. Most of the FDA summaries of the devices mention their use of clinical data and patient cases for device validation; however, few devices revealed the patient demographics or machine specifications used in their clinical studies, which may lead some consumers to question their external validation.(c) 2022 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.