mi2b2 Enabled Pediatric Radiological Decision Support

mi2b2 启用儿科放射决策支持

• 批准号: 8272742
• 负责人: RANDY Lyanne GOLLUB
• 金额: $ 76.13万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8272742
• 关键词: Acute; Address; Adoption; Age; Algorithms; Atlases; Biological Markers; Biology; Biomedical Computing; Boston; Brain; Brain Diseases; Childhood; Chronic; Clinical; Clinical Management; Clinical Research; Collection; Communities; Computer software; Computerized Medical Record; Coupling; Data; Data Set; Decision Support Systems; Development; Diagnostic; Diffusion weighted imaging; Disease; Foundations; Funding; General Hospitals; Gold; Government; Grant; Growth; Health Insurance Portability and Accountability Act; Healthcare; Hospitals; Image; Image Analysis; Imagery; Imaging technology; Individual; Infant; Informatics; Information Systems; Institution; International; Laboratories; Magnetic Resonance Imaging; Massachusetts; Medical; Medical Education; Medical Imaging; Metric; Mining; Online Systems; Patient Care; Patients; Pediatric Hospitals; Performance; Picture Archiving and Communication System; Positron-Emission Tomography; Radiology Specialty; Reading; Research; Research Infrastructure; Research Personnel; Resources; Retrieval; Scanning; Scientist; Secure; Software Tools; Speed; Technology; Testing; Time; Training; Translational Research; Translations; Ultrasonography; Vendor; Weight; Woman; Work; base; bench to bedside; billing data; bioimaging; catalyst; clinical care; clinical practice; cohort; comparative; health care delivery; imaging informatics; improved; open source; patient privacy; point of care; radiologist; repository; tool

DESCRIPTION (provided by applicant): We propose to extend the recently developed Medical Imaging Informatics Bench to Bedside (mi2b2) Workbench software to make medical images collected during routine clinical care available to clinical translational investigators. Today, this gold mine of patient information is not easily available. Well characterized medical images from clinical repositories would be an extremely valuable resource for clinical translational investigators who have specific ideas that require testing in large sets of images from many patients with different diseases. Our hospitals are international leaders in the development and deployment of advanced biomedical imaging technologies (MRI, high speed CT, ultrasound, PET and others) for clinical practice. The Picture Archive and Communication Systems (PACS) within each of the Departments of Radiology in our participating hospitals (Massachusetts General Hospital, Brigham and Women's Hospital, and Children's Hospital Boston) contain a wealth of medical images that often equal the quality of available clinical research imaging data, and greatly exceed its volume in terms of the number of patients and disease types. Though immediately extensible to other research applications and diagnostic scenarios, we apply our approach first to the difficult task of interpreting pediatric brain magnetc resonance images (MRI). The proposed Pediatric MRI module and Harvard Catalyst Radiological Decision Support toolkit that host it are targeted to address the immediate clinical challenge of understanding "normal" because normal is a constantly moving target, changing rapidly with brain development. These free and open source software tools are natural extensions of currently funded government projects. This includes software from two National Centers for Biomedical Computing; Informatics for Integrating Biology & the Bedside (i2b2) which provides tools that extract and integrate data in a secure, HIPAA compliant manner from electronic medical records, laboratory data, billing information systems and the National Alliance for Medical Image Computing (NAMIC), which provides tools for medical image analysis including registration, visualization and computation of individual subject and large cohort data sets and will form the foundation for the Harvard Catalyst Radiological Decision Support Toolkit. PUBLIC HEALTH RELEVANCE: The software tools developed by this proposal will enable monumental steps forward by making available to research scientists expensive medical images collected during routine clinical care and image analysis tools customized for large scale cohorts along with a wealth of data about associated patient illness that can be used for studies of nearly all medical diseases. To provide an explicit example of the profound impact this software can have to transform healthcare delivery we will develop and deploy the Harvard Catalyst RDS toolkit with a Pediatric MRI module based on neurodevelopmental MRI atlases for structural and diffusion weighted imaging data. These software tools will improve clinical management of babies with acute and chronic brain disorders. This grant provides the way for tens of thousands of images to be used for research with careful protection of patient privacy while working harmoniously within the culture of most radiology departments that are oriented around managing the images strictly for clinical care.

描述（由申请人提供）：我们建议将最近开发的医学成像信息学工作台扩展到床边（mi2 b2）诊断软件，以使临床翻译研究者可以使用常规临床护理期间收集的医学图像。如今，患者信息的这座金矿并不容易获得。来自临床资料库的具有良好特征的医学图像对于临床翻译研究人员来说是一个非常有价值的资源，他们有特定的想法，需要在来自许多不同疾病患者的大量图像中进行测试。我们的医院在开发和部署用于临床实践的先进生物医学成像技术（MRI、高速CT、超声、PET等）方面处于国际领先地位。我们参与的医院（马萨诸塞州总医院、布里格姆妇女医院和波士顿儿童医院）的每个放射科的图像存档和通信系统（PACS）包含大量的医学图像，这些图像的质量通常与可用的临床研究成像数据相当，并且在患者数量和疾病类型方面大大超过其容量。虽然可以立即扩展到其他研究应用和诊断场景，但我们首先将我们的方法应用于解释儿科脑磁共振图像（MRI）的困难任务。拟议的儿科MRI模块和托管该模块的哈佛Catalyst放射学决策支持工具包旨在解决理解“正常”的直接临床挑战，因为正常是一个不断移动的目标，随着大脑发育而迅速变化。这些免费和开源软件工具是目前政府资助项目的自然延伸。这包括来自两个国家生物医学计算中心的软件; Informatics for Integrating Biology & the Bedside（i2 b2）提供了从电子病历、实验室数据、计费信息系统中以安全、符合HIPAA的方式提取和整合数据的工具，以及提供医学图像分析工具的国家医学图像计算联盟（NAMIC），包括配准，可视化和计算单个主题和大型队列数据集，并将形成哈佛催化剂放射性决策支持工具包的基础。 公共卫生相关性：该提案开发的软件工具将通过向研究科学家提供在常规临床护理期间收集的昂贵医学图像和为大规模队列定制的图像分析工具沿着可用于几乎所有医学疾病研究的有关患者疾病的丰富数据，从而向前迈出巨大的一步。为了提供一个明确的例子，说明该软件对医疗保健服务的深刻影响，我们将开发和部署哈佛Catalyst RDS工具包，其中包含一个儿科MRI模块，该模块基于神经发育MRI图谱，用于结构和弥散加权成像数据。这些软件工具将改善患有急性和慢性脑部疾病的婴儿的临床管理。这项拨款为成千上万的图像提供了用于研究的方式，同时仔细保护患者隐私，同时在大多数放射科的文化中和谐地工作，这些部门的文化是围绕着严格管理临床护理的图像。