AutoRegister: A system for enhancing the accuracy of tumor change detection

描述（由申请人提供）：本项目拟构建一个基于软件的集成系统，用于提高肿瘤变化检测的准确性。该系统被称为AutoRegister，将被部署在临床磁共振成像（MRI）扫描仪平台上，其目的是自动将患者的大脑扫描与先前的脑扫描对齐。 扫描，使得随后的离线肿瘤测量不具有仅由不同切片取向引入的误差。虽然在功能上类似于当前的自动对准技术， 与西门子AutoAlign一样，所提出的技术对这种基于对象非特定界标的技术的固有噪声不敏感。此外，所提出的技术基于一种新的配准算法，该算法不受异常解剖结构（例如肿瘤）的影响，而异常解剖结构通常会对AutoAlign等技术产生不利影响。在美国，估计每年有13，000人死于原发性中枢神经系统肿瘤。标准和实验性治疗依赖于肿瘤大小变化的准确测量，以评估治疗反应并指导临床试验的过程。该项目将建立在马萨诸塞州总医院（MGH）Martinos生物医学成像中心开发的现有技术基础上。它将利用co-PI设计的新型3D MR图像配准算法，该算法在受试者内和模态内具有高度准确性，并忽略不可能精确匹配的体素，例如肿瘤组织和周围部分体积效应。项目合作者包括那些在西门子MRI扫描仪接口方面具有专业知识的人员，这些扫描仪用于开发原始AutoAlign工具。该项目的第一个目标是开发一个基于笔记本电脑的平台，连接到西门子MRI扫描仪控制台，能够检索患者的先前扫描，将其与会话内的自定义“侦察”扫描RU配准（对齐），并将“切片处方”发送到扫描仪，以便随后的会话内肿瘤检测扫描与先前的肿瘤检测扫描对齐，透明地提高了神经肿瘤学家或神经放射学家的下游工作流程的准确性。该项目的第二个目的是评估和验证自动注册系统的性能。进行胶质母细胞瘤治疗的单独即将进行的临床试验的合作者将包括在会话内测试-重测范例中比较AutoRegister与AutoAlign和手动对齐所需的扫描集。其他合作者将标记每个图像集中的肿瘤变化，以便随后进行比较。第三个目标是计划和建立公司流程，以满足FDA关于预期商业产品的法规。在该项目的第二阶段，该技术将被移植到直接在扫描仪上运行，并在更大的数据集上重新验证，这样该技术就可以被扫描仪制造商许可或收购。西门子公司的一位代表提供了一份拟议项目的支持信，表明他们对许可或购买拟议技术的高度兴趣。

DESCRIPTION (provided by applicant): This project proposes to build an integrated software-based system for enhancing the accuracy of tumor change detection. The intent of the system, called AutoRegister, which is to be deployed on a clinical magnetic resonance imaging (MRI) scanner platform, is to automate the alignment of a patient's brain scan with that of a prior scan, such that subsequent offline tumor measurements do not have error introduced solely by differing slice orientation. While functionally similar to current auto-alignment technologies such as Siemens AutoAlign, the proposed technology is not sensitive to the inherent noise of such subject-nonspecific landmark- based techniques. Additionally the proposed technology is based upon a novel registration algorithm that is immune to outlier anatomy, such as a tumor, which often adversely affects techniques such as AutoAlign. In the United States, there are an estimated 13,000 deaths per year due to tumors in the primary central nervous system. Standard and experimental therapies rely on accurate measurement of tumor size change to assess treatment response and guide the course of a clinical trial. The project will build upon a foundation of existing technology developed at the Martinos Center for Biomedical Imaging at the Massachusetts General Hospital (MGH). It will make use of a novel 3D MR image registration algorithm designed by the co-PI, which is highly accurate within-subject and within-modality, and ignores voxels where no accurate match is possible, such as tumor tissue and surrounding partial-volume effects. Project collaborators include those with expertise in Siemens MRI scanner interfacing for slice prescription that developed the original AutoAlign tool. The firs aim of the project is to develop a laptop-based platform to connect to a Siemens MRI scanner console, able to retrieve a patient's prior scan, register (align) it with a custom 'scout' scan ru within-session, and send a 'slice prescription' to the scanner such that the subsequent within-session tumor-detection scans are aligned with the prior tumor-detection scan, transparently improving the accuracy of the downstream workflow of the neuro-oncologist or neuroradiologist. The second aim of the project is to evaluate and validate the performance of the AutoRegister system. Collaborators conducting a separate upcoming clinical trial of a glioblastoma treatment will include the set of scans necessary to compare AutoRegister to AutoAlign and manual-alignment, in a within-session test-retest paradigm. Other collaborators will label the tumor change in each image set, for subsequent comparison. The third aim is to plan and establish the company processes necessary to meet FDA regulations covering the anticipated commercial product. In Phase II of the project, the technology will be ported to run directly on the scanner and re-validated on a larger dataset, such that the technology may be licensed or acquired by a scanner manufacturer. A Siemens representative has provided a Letter of Support of the proposed project, indicating their high level of interest in licensing or purchasing the proposed technology.