用于人工智能的PET血流灌注成像注册研究（REFINE PET）：原理与设计。

The REgistry of Flow and Perfusion Imaging for Artificial INtelligEnce with PET (REFINE PET): Rationale and Design.

作者信息

Ramirez Giselle, Lemley Mark, Shanbhag Aakash, Kwiecinski Jacek, Miller Robert J H, Kavanagh Paul B, Liang Joanna X, Dey Damini, Slipczuk Leandro, Travin Mark I, Alexanderson Erick, Carvajal-Juarez Isabel, Packard René R S, Al-Mallah Mouaz, Einstein Andrew J, Feher Attila, Acampa Wanda, Knight Stacey, Le Viet T, Mason Steve, Sanghani Rupa, Wopperer Samuel, Chareonthaitawee Panithaya, Buechel Ronny R, Rosamond Thomas L, deKemp Robert A, Berman Daniel S, Di Carli Marcelo F, Slomka Piotr J

机构信息

Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA.

出版信息

medRxiv. 2025 Jul 11:2025.07.10.25330435. doi: 10.1101/2025.07.10.25330435.

DOI:10.1101/2025.07.10.25330435

PMID:40672503

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12265749/

Abstract

RATIONALE

The REgistry of Flow and Perfusion Imaging for Artificial INtelligEnce with PET (REFINE PET) was established to aggregate PET and associated computed tomography (CT) images with clinical data from hospitals around the world into one comprehensive research resource.

METHODS

REFINE PET is a multicenter, international registry that contains both clinical and imaging data. The PET scans were processed using QPET software (Cedars-Sinai Medical Center, Los Angeles, CA), while the CT scans were processed using deep learning (DL) to detect coronary artery calcium (CAC). Patients were followed up for the occurrence of major adverse cardiovascular events (MACE), which include death, myocardial infarction, unstable angina, and late revascularization (>90 days from PET).

RESULTS

The REFINE PET registry currently contains data for 35,588 patients from 14 sites, with additional patient data and sites anticipated. Comprehensive clinical data (including demographics, medical history, and stress test results) were integrated with more than 2200 imaging variables across 42 categories. The registry is poised to address a broad range of clinical questions, supported by correlating invasive angiography (within 6 months of MPI) in 5972 patients and a total of 9252 major adverse cardiovascular events during a median follow-up of 4.2 years.

CONCLUSION

The REFINE PET registry leverages the integration of clinical, multimodality imaging, and novel quantitative and AI tools to advance the role of PET/CT MPI in diagnosis and risk stratification.

摘要

原理

建立用于人工智能与正电子发射断层扫描的血流灌注成像注册库（REFINE PET），旨在将来自世界各地医院的正电子发射断层扫描（PET）及相关计算机断层扫描（CT）图像与临床数据整合为一个综合研究资源。

方法

REFINE PET是一个多中心国际注册库，包含临床和影像数据。PET扫描使用QPET软件（加利福尼亚州洛杉矶市雪松西奈医疗中心）进行处理，而CT扫描则使用深度学习（DL）来检测冠状动脉钙化（CAC）。对患者进行主要不良心血管事件（MACE）发生情况的随访，MACE包括死亡、心肌梗死、不稳定型心绞痛和晚期血运重建（PET检查后>90天）。

结果

REFINE PET注册库目前包含来自14个地点的35588名患者的数据，预计还会有更多患者数据和地点加入。综合临床数据（包括人口统计学、病史和压力测试结果）与42个类别的2200多个影像变量相结合。该注册库准备解决一系列广泛的临床问题，5972名患者的有创血管造影（在心肌灌注显像6个月内）以及在中位随访4.2年期间共9252例主要不良心血管事件为此提供了支持。