背景:心脏淀粉样变性的诊断可以通过使用骨扫描示踪剂的闪烁扫描非侵入性地建立,但视觉评估是主观的,会导致误诊。我们旨在开发和验证一种人工智能(AI)系统,用于标准化和可靠地筛查心脏淀粉样变性提示摄取,并评估其预后价值。使用跨多个示踪剂和扫描仪的99mTc闪烁显像数据的跨国数据库。
方法:在本回顾性研究中,国际,多中心,交叉示踪剂开发和验证研究,来自9个中心的16241名患者进行了19401次扫描:奥地利的一家医院(2010年1月4日至2020年8月19日连续招募),伦敦的五个医院,英国(2014年10月1日至2022年9月29日连续招聘),中国的两个中心(2021年1月1日至2022年10月31日的部分扫描),和意大利的一个中心(2011年1月1日至2023年5月23日的部分扫描)。数据集包括所有涉及全身99mTc闪烁显像的患者,并具有前视功能,以及目前用于识别心脏淀粉样变性提示摄取的所有99mTc标记的示踪剂。排除标准为小于2小时的图像采集(99mTc-3,3-二膦酰基-1,2-丙二羧酸,99mTc-羟基亚甲基二膦酸盐,和99mTc-亚甲基二膦酸盐)或在示踪剂注射后少于1小时(99mTc-焦磷酸盐),并且如果患者的影像学和临床数据无法联系起来。地面实况注释来自至少三名独立专家的集中核心实验室共识阅读(CN,TT-W,和JN)。使用来自一个中心(奥地利)的数据开发了用于检测与心脏淀粉样变相关的高级心脏示踪剂摄取的AI系统,并在其余中心进行了独立验证。多重酶,进行了多读者研究和医学算法审核,以评估与AI相比的临床医生表现,并评估和纠正故障模式。在连续招募的队列中,使用cox比例风险模型对每个队列单独和组合队列进行了系统预测死亡率的预后价值测试。
结果:在奥地利9176例患者中,心脏淀粉样变性提示摄取阳性病例的患病率为142例(2%),英国6763名患者中有125名(2%),中国102例患者中有63例(62%),意大利队列中200名患者中的103名(52%)。在奥地利队列中,交叉验证性能显示曲线下面积(AUC)为1·000(95%CI1·000-1·000)。独立验证得出英国的AUC为0·997(0·993-0·999),中国人的0·925(0·871-0·971),和1·000(0·999-1·000)的意大利队列。在多酶多读者研究中,在200例病例中,有22例(11%)有5名医生不同意(Fleiss\'kappa0·89),平均AUC为0·946(95%CI0·924-0·967),低于AI(AUC0·997[0·991-1·000],p=0·0040)。医疗算法审计证明了该系统在人口统计学因素方面的稳健性,示踪剂,扫描仪,和中心。AI的预测是总死亡率的独立预后(调整后的风险比1·44[95%CI1·19-1·74],p<0·0001)。
结论:基于AI的心脏淀粉样变性提示摄取量筛查是可靠的,消除了评分者之间的差异,并预示着预后价值,对身份识别有潜在的影响,转介,和管理途径。
背景:辉瑞。
BACKGROUND: The diagnosis of cardiac
amyloidosis can be established non-invasively by scintigraphy using bone-avid tracers, but visual assessment is subjective and can lead to misdiagnosis. We aimed to develop and validate an artificial intelligence (AI) system for standardised and reliable screening of cardiac amyloidosis-suggestive uptake and assess its prognostic value, using a multinational database of 99mTc-scintigraphy data across multiple tracers and scanners.
METHODS: In this retrospective, international, multicentre, cross-tracer development and validation
study, 16 241 patients with 19 401 scans were included from nine centres: one hospital in Austria (consecutive recruitment Jan 4, 2010, to Aug 19, 2020), five hospital sites in London, UK (consecutive recruitment Oct 1, 2014, to Sept 29, 2022), two centres in China (selected scans from Jan 1, 2021, to Oct 31, 2022), and one centre in Italy (selected scans from Jan 1, 2011, to May 23, 2023). The dataset included all patients referred to whole-body 99mTc-scintigraphy with an anterior view and all 99mTc-labelled tracers currently used to identify cardiac amyloidosis-suggestive uptake. Exclusion criteria were image acquisition at less than 2 h (99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid, 99mTc-hydroxymethylene diphosphonate, and 99mTc-methylene diphosphonate) or less than 1 h (99mTc-pyrophosphate) after tracer injection and if patients\' imaging and clinical data could not be linked. Ground truth annotation was derived from centralised core-lab consensus reading of at least three independent experts (CN, TT-W, and JN). An AI system for detection of cardiac amyloidosis-associated high-grade cardiac tracer uptake was developed using data from one centre (Austria) and independently validated in the remaining centres. A multicase, multireader
study and a medical algorithmic audit were conducted to assess clinician performance compared with AI and to evaluate and correct failure modes. The system\'s prognostic value in predicting mortality was tested in the consecutively recruited cohorts using cox proportional hazards models for each cohort individually and for the combined cohorts.
RESULTS: The prevalence of cases positive for cardiac
amyloidosis-suggestive uptake was 142 (2%) of 9176 patients in the Austrian, 125 (2%) of 6763 patients in the UK, 63 (62%) of 102 patients in the Chinese, and 103 (52%) of 200 patients in the Italian cohorts. In the Austrian cohort, cross-validation performance showed an area under the curve (AUC) of 1·000 (95% CI 1·000-1·000). Independent validation yielded AUCs of 0·997 (0·993-0·999) for the UK, 0·925 (0·871-0·971) for the Chinese, and 1·000 (0·999-1·000) for the Italian cohorts. In the multicase multireader
study, five physicians disagreed in 22 (11%) of 200 cases (Fleiss\' kappa 0·89), with a mean AUC of 0·946 (95% CI 0·924-0·967), which was inferior to AI (AUC 0·997 [0·991-1·000], p=0·0040). The medical algorithmic audit demonstrated the system\'s robustness across demographic factors, tracers, scanners, and centres. The AI\'s predictions were independently prognostic for overall mortality (adjusted hazard ratio 1·44 [95% CI 1·19-1·74], p<0·0001).
CONCLUSIONS: AI-based screening of cardiac amyloidosis-suggestive uptake in patients undergoing scintigraphy was reliable, eliminated inter-rater variability, and portended prognostic value, with potential implications for identification, referral, and management pathways.
BACKGROUND: Pfizer.