Cloud quantitative imaging for whole-body tumor burden in neurofibromatoses

神经纤维瘤全身肿瘤负荷的云定量成像

• 批准号: 9762866
• 负责人: Wenli Cai
• 金额: $ 71.94万
• 依托单位: IQ MEDICAL IMAGING, LLC
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9762866
• 关键词: Agreement; Algorithms; Cancer Center; Clinic; Clinical; Clinical Research; Clinical Services; Cloud Computing; Communities; Computer software; Data Collection; Development; Disease; Documentation; Evaluation; Evaluation Studies; Funding; General Hospitals; Goals; Hospitals; Image Analysis; Infrastructure; Internet; Intuition; Letters; Licensing; Life; Magnetic Resonance Imaging; Massachusetts; Measurement; Medical Device; Medical Imaging; Methods; Modeling; Monitor; NF1 gene; Names; Nerve Sheath Tumors; Neurofibromatoses; Patients; Performance; Phase; Plexiform Neurofibroma; Predisposition; Preparation; Privatization; Progression-Free Survivals; Recovery; Regulation; Reporting; Reproducibility; Running; Schwannomatosis; Sensitivity and Specificity; Site; Small Business Technology Transfer Research; Software Tools; Structure; System; Techniques; Technology; Three-Dimensional Imaging; Time; Translating; Translations; Tumor Burden; Tumor Volume; Validation; Vendor; base; clinical translation; cloud platform; cost; deep learning; end of life; follow-up; imaging modality; improved; interest; neurogenetics; predict clinical outcome; prospective; prototype; quantitative imaging; research clinical testing; software as a service; software development; treatment response; tumor; tumor progression; virtual; whole body imaging

Project Summary / Abstract The neurofibromatoses (NFs), including NF1, NF2, and schwannomatosis, are a group of autosomal-dominant neurogenetic disorders characterized by a predisposition in virtually 100% of patients to develop multiple nerve sheath tumors. The determination of tumor burden on magnetic resonance imaging (MRI) is indispensable for the longitudinal management of NF patients, which includes life-long follow-up for the monitoring of tumor progression and the assessment of treatment response. However, volumetric quantification of NF tumors is not a clinical routine because of the technical challenges in the accurate and reproducible segmentation of highly-irregular and infiltrating NF tumors, in particular plexiform neurofibromas on MRI. The goal of this STTR project is to develop cloud quantitative imaging (CQI) for NF software, denoted as CQI-NF, which will provide the technical and clinical service for volumetric quantification of NF tumors on whole-body and regional MRI via "virtualization" (cloud computing) technology. The product developed in this STTR will provide access to this technology for the NF clinical community nationwide and worldwide without the excessive cost to maintain on-site advanced volumetric imaging analysis software and hardware. This project will be built upon existing technologies for volumetric imaging analysis developed on the software platform “3DQI” in the 3D Imaging Lab at Massachusetts General Hospital (MGH), and will be evaluated using 200 longitudinal whole-body and regional MRI cases collected from the NF community worldwide. The specific aims of this Phase II project are: (1) Development of CQI-NF system: We will continue to develop the CQI-NF system prototyped in our Phase I project to improve the accuracy and efficiency of segmentation by paralleling dynamic-threshold level set (DT level set) in multi-server platform, combining deep-learning in DT level set for the segmentation of NF tumors, and to translate the CQI-NF system from 3DQI/NF into a private cloud platform (such as TeraRecon's iNtuition CLOUD) for the provision of volumetric quantification of NF using a software-as-a-service (SaaS) model in the NF community. (2) Evaluation of CQI-NF system: We will conduct a retrospective clinical study to evaluate the accuracy and reproducibility of the CQI-NF system in the longitudinal monitoring of 200 NF patients collected at MGH Cancer Center and our clinical collaborators worldwide in the NF community. (3) Preparation of FDA 510(k) clearance submission: We will establish the quality management system for CQI-NF to meet FDA regulation, and prepare the required documentation for FDA 510(k) clearance submission for the long-term project goal of clinical translation of CQI-NF. The successful development and validation of the proposed CQI-NF system will have a high clinical impact in the NF community by providing a cloud-computing infrastructure for the volumetric imaging analysis of NF on MRI, which is not available in current clinical routine, thereby leading to a substantial advance in the longitudinal management of NF patients.

项目摘要 /摘要 神经纤维瘤（NFS），包括NF1，NF2和Schwannomatisoise，是一组常染色体主导者 神经遗传疾病的特征是几乎100％患者发育多个神经的特征 护套肿瘤。在磁共振成像（MRI）上确定肿瘤燃烧（MRI）是必不可少的 NF患者的纵向管理，其中包括终身监测肿瘤的随访 进展和治疗反应的评估。但是，NF肿瘤的体积定量不是 临床例程是因为在准确且可重复的分割方面面临技术挑战 高度刺激和浸润的NF肿瘤，特别是MRI上的丛状神经纤维瘤。 该STTR项目的目的是为NF软件开发云定量成像（CQI），称为 CQI-NF，它将提供技术和临床服务，用于对NF肿瘤的体积定量 全身和区域MRI通过“虚拟化”（云计算）技术。在此开发的产品 STTR将为全国NF临床社区和全球范围内提供该技术的访问权限 维护现场高级体积成像分析软件和硬件的过多成本。这个项目 将建立在用于在软件平台上开发的体积成像分析的现有技术的基础上 马萨诸塞州综合医院（MGH）的3D成像实验室中的“ 3DQI”，将使用200 从全球NF社区收集的纵向全身和区域MRI案例。 该第二阶段项目的具体目的是：（1）开发CQI-NF系统：我们将继续发展 CQI-NF系统在我们的I阶段项目中进行了原型，以提高分割的准确性和效率 多服务器平台中的平行动态阈值级集（DT级集），结合了DT中的深度学习 将NF肿瘤分割的水平设置，并将CQI-NF系统从3DQI/NF转换为私有 云平台（例如Terarecon的Intuition Cloud），用于使用NF的体积定量 NF社区中的软件即服务（SaaS）模型。 （2）评估CQI-NF系统：我们将进行一次 回顾性临床研究，以评估纵向中CQI-NF系统的准确性和繁殖 监测在MGH癌症中心收集的200名NF患者以及我们在NF的全球临床合作者 社区。 （3）FDA 510（k）清算提交的准备：我们将建立质量管理 CQI-NF符合FDA法规的系统，并准备FDA 510（k）清算的所需文档 提交CQI-NF临床翻译的长期项目目标。 拟议的CQI-NF系统的成功开发和验证将对 NF社区通过提供云计算基础架构，用于MRI上NF的体积成像分析， 这在当前的临床例程中不可用，从而导致了纵向的重大进步 NF患者的管理。

项目成果

Ten-Year Follow-up of Internal Neurofibroma Growth Behavior in Adult Patients With Neurofibromatosis Type 1 Using Whole-Body MRI.

使用全身 MRI 对 1 型神经纤维瘤病成年患者的内部神经纤维瘤生长行为进行十年随访。

• DOI: 10.1212/wnl.0000000000201535
• 发表时间: 2023
• 期刊: Neurology
• 影响因子: 9.9
• 作者: Ly,KIna;Merker,VanessaL;Cai,Wenli;Bredella,MiriamA;Muzikansky,Alona;Thalheimer,RaquelD;Da,JenniferLiwei;Orr,ChristinaC;Herr,HamiltonP;Morris,MaryE;Chang,ConnieY;Harris,GordonJ;Plotkin,ScottR;Jordan,JustinT
• 通讯作者: Jordan,JustinT