Core C: Imaging Core

核心C：成像核心

基本信息

批准号：
10555684
负责人：
MICHAEL C NEVITT
金额：
$ 119.29万
依托单位：
BOSTON UNIVERSITY MEDICAL CAMPUS
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-06-01 至 2028-02-29
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10555684
关键词：
Address Adherence Adopted Agreement Ancillary Study Archives Arthralgia Attention Cartilage Certification Clinic Collaborations Data Data Analyses Data Set Degenerative polyarthritis Disease Dose Ensure Evolution Feedback Funding Glean Goals Grant Hand Image Joints Knee Limb structure Lower Extremity Machine Learning Magnetic Resonance Imaging Manuals Measurement Methods Modeling Monitor Musculoskeletal Pain Pathogenesis Pathology Performance Positioning Attribute Procedures Protocols documentation Radiology Specialty Reader Reading Research Personnel Roentgen Rays Role Secure Site Structure Symptoms System Training Training Programs Update Weight-Bearing state Work X-Ray Computed Tomography clinical center computerized data processing data de-identification data management data sharing deep learning digital experience image processing imaging modality insight learning strategy novel operation programs quality assurance ultrasound

Address Adherence Adopted Agreement Ancillary Study Archives Arthralgia Attention Cartilage Certification Clinic Collaborations Data Data Analyses Data Set Degenerative polyarthritis Disease Dose Ensure Evolution Feedback Funding Glean Goals Grant Hand Image Joints Knee Limb structure Lower Extremity Machine Learning Magnetic Resonance Imaging Manuals Measurement Methods Modeling Monitor Musculoskeletal Pain Pathogenesis Pathology Performance Positioning Attribute Procedures Protocols documentation Radiology Specialty Reader Reading Research Personnel Roentgen Rays Role Secure Site Structure Symptoms System Training Training Programs Update Weight-Bearing state Work X-Ray Computed Tomography clinical center computerized data processing data de-identification data management data sharing deep learning digital experience image processing imaging modality insight learning strategy novel operation programs quality assurance ultrasound

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项目摘要

ABSTRACT Imaging Core Large scale knee imaging in MOST, including from MRI, radiographs and dual energy CT (DECT), has catalyzed insights into the evolution of structural disease and the relation of structural pathology to joint pain in OA. In the MOST4 program, expanded use of new imaging modalities including low-dose weight bearing CT of the lower limb and DECT will add to the richness of these assessments. Deriving valid insights from these imaging modalities requires attention to the quality of the images acquired and similar focus on the analysis and processing of the imaging data. The Imaging Core will provide for all of these imaging modalities rigorous oversight of the quality of the images and of the information gleaned from them. In doing so, the Imaging Core will enrich immeasurably insights provided by MOST4. The overall goals of the Imaging Core for MOST4 are to: 1) ensure the high quality and completeness of images acquired by the clinical centers, including 1.5T MRI of the knee (at MOST4 V1 and V2), and a group of images at MOST4 V1, including hand X-rays and weight-bearing CT of the knees and other lower limb joints, and ultrasound and DECT of the knee; 2) oversee the reading centers to ensure the high quality of data derived from the images; 3) and provide analysis ready reading center data and images needed for all four MOST4 Projects and other approved MOST projects. The Imaging Core will achieve these goals by adapting and updating methods honed and successfully applied during the past 19 years over three funding cycles of MOST. By achieving these goals, the Imaging Core will ensure that MOST4 has the high-quality joint imaging data that is essential to achieving a deeper understanding of the role of specific joint structures in OA pathogenesis, of the inter-relationship between changes in different structures and how they are in turn related to joint symptoms. The Imaging Core will also use deep learning methods to combine data from MOST3 DECT and MRI images for exploratory analyses of the role of intra-articular crystals in co-localized cartilage loss.

抽象成像核心大多数大型膝盖成像，包括MRI，X光片和双能CT（DECT），已催化洞悉结构疾病的演变以及结构病理与OA关节疼痛的关系。在大多数4个程序，扩展的新成像方式的使用，包括低剂量重轴承CT 肢体和DECT将增加这些评估的丰富性。从这些成像中获得有效的见解模式需要注意所获得图像质量的质量，并类似地关注分析和成像数据的处理。成像核心将为所有这些成像方式提供严格监督图像的质量和从中收集的信息。这样，成像核心将丰富大多数4提供的无可估量的见解。大多数成像核心的总体目标是： 1）确保临床中心获得的图像的高质量和完整性，包括1.5T MRI 膝盖（最多4 V1和V2），以及最多的4 V1图像，包括手X射线和重量膝盖和其他下肢关节的CT，膝盖的超声和直接； 2）监督阅读中心以确保图像得出的高质量数据； 3）并提供分析就绪阅读中心所有四个大多数项目以及其他批准的大多数项目所需的数据和图像。成像核心将通过调整和更新方法在过去19年中磨练和成功应用的方法来实现这些目标超过三个大多数资金周期。通过实现这些目标，成像核心将确保大多数4具有高质量的关节成像数据，这对于更深入了解特定关节的作用至关重要 OA发病机理中的结构，不同结构变化之间的相互关系以及它们如何反过来又与关节症状有关。成像核心还将使用深度学习方法来组合数据从大多数3个DECT和MRI图像中，用于探索性分析关节内晶体在共定位中的作用软骨损失。