MDCT Quantification of hepatic tumor viability for assessment of cancer therapy

MDCT 量化肝肿瘤活力以评估癌症治疗

• 批准号: 8782327
• 负责人: Wenli Cai
• 金额: $ 22.28万
• 依托单位: IQ MEDICAL IMAGING, LLC
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-16 至 2016-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8782327
• 关键词: Aftercare; Agreement; Algorithms; Angiogenesis Inhibitors; Biological Markers; Cancer Center; Cause of Death; Cities; Classification; Client; Clinical; Clinical Research; Cloud Computing; Collaborations; Computer software; Cytotoxic Chemotherapy; Data; Detection; Development; Diagnosis; Diagnostic; Evaluation; Fostering; Funding; General Hospitals; Hepatic; Image; Image Analysis; Imagery; Intuition; Lesion; Letters; Licensing; Liver; Liver neoplasms; Malignant Neoplasms; Malignant neoplasm of liver; Massachusetts; Measurement; Measures; Medical Device; Medical Imaging; Molecular Target; Names; Necrosis; Oncologist; Online Systems; Outcome; Patients; Pattern; Performance; Phase; Primary carcinoma of the liver cells; Process; Progression-Free Survivals; Radiation therapy; Regulation; Running; Scientist; Solid Neoplasm; Staging; Surrogate Endpoint; Survival Rate; System; Technology; Testing; Therapeutic; Three-Dimensional Imaging; Time; Translations; Tumor Tissue; Tumor Volume; Validation; Venous; X-Ray Computed Tomography; base; cancer therapy; chemotherapy; cloud based; cost; detector; imaging modality; improved; innovation; interest; meetings; outcome forecast; parallel computer; point of care; prototype; public health relevance; quality assurance; research clinical testing; response; transmission process; treatment response; tumor; tumor progression; validation studies

DESCRIPTION (provided by applicant): Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy (more than 80%) and the third most common cause of death from cancer worldwide. Contrast-enhanced multi-phase multi-detector CT (MDCT) is a routine imaging modality for patients diagnosed with hepatic malignancy. The change of tumor size measured on single-phase (mostly portal-venous phase) MDCT images is used routinely for assessment of tumor response to treatment. With the advent of targeted cancer therapies (such as antiangiogenic treatment) over the past decade, the clinical outcome in the treatment of advanced HCC has been significantly improved. However, because of the difference in the mechanisms of therapies, measurement of tumors treated with targeted therapy does not necessarily accurately represent the change in viable tumor size due to the presence of necrosis. Therefore, the assessment of tumor response using tumor size alone may inadequately evaluate the treatment response for tumors like HCC when treated with targeted therapies. Instead of using tumor size alone to assess targeted therapies, we propose to develop an innovative quantitative imaging biomarker, denoted as hepatic tumor viability (HTV), using multi-phase hepatic MDCT images for quantification of viable and necrotic tumor tissues in addition to the size of liver and tumors for HCC patients treated with targeted therapies. This project will be built upon existing technologies for quantitative imaging analysis developed at the 3D Imaging Lab at the Massachusetts General Hospital (MGH). It will make use of the classification and segmentation algorithms developed by the co-PI for liver and liver tumors, which classifies viable/necrotic tumor regions by using pattern analysis of time-intensity curve (TIC) in multi-phase MDCT images. Project collaborators include oncologists specialized in targeted therapy for HCC (particular on antiangiogenic treatment) at the MGH Cancer Center, and imaging scientists specializing in quantitative imaging analysis from the 3D Imaging Lab at the MGH. The specific aims of the project are: (1) Development of HTV biomarker: We will develop the prototype HTV biomarker on a cloud-computing platform, including HTV-Server that is an automated HTV post-processing pipeline for the registration, classification and segmentation of liver, tumors and viable/necrotic tumor regions in multi-phase MDCT images, and HTV-Client that is a web-based user interface for interactive visualization, quantitative analysis, and point-of-care data access for the HTV quantification. (2) Evaluation of HTV biomarker: We will conduct a clinical study to evaluate the clinical performance of the proposed HTV biomarker in the prognosis of tumor progress and treatment response by using 50 advanced HCC cases treated with antiangiogenic therapies at the MGH Cancer Center. (3) Plan of project Phase II: We will establish the company processes to meet FDA regulations for translation and validation of the product in Phase II of the project. Our industrial collaborators (TeraRecon Inc, Intrasense) have shown their high level of interests in licensing or purchasing the proposed technology to integrate it into their medical imaging workstations.

描述（由申请人提供）：肝细胞癌（HCC）是最常见的原发性肝脏恶性肿瘤（超过 80%），也是全球第三大癌症死亡原因。对比增强多相多排 CT (MDCT) 是诊断患有肝脏恶性肿瘤的患者的常规成像方式。在单相（主要是门静脉相）MDCT 图像上测量的肿瘤大小的变化通常用于评估肿瘤对治疗的反应。过去十年，随着靶向癌症治疗（如抗血管生成治疗）的出现，晚期HCC治疗的临床效果得到了显着改善。然而，由于治疗机制的差异，用靶向治疗治疗的肿瘤的测量不一定准确代表由于坏死的存在而导致的存活肿瘤大小的变化。因此，仅使用肿瘤大小来评估肿瘤反应可能不足以评估 HCC 等肿瘤在接受靶向治疗时的治疗反应。我们建议开发一种创新的定量成像生物标志物，称为肝肿瘤生存力（HTV），而不是单独使用肿瘤大小来评估靶向治疗，除了大小之外，还使用多相肝 MDCT 图像对存活和坏死的肿瘤组织进行量化接受靶向治疗的 HCC 患者的肝脏和肿瘤的研究。该项目将建立在现有的定量成像分析技术的基础上 马萨诸塞州总医院 (MGH) 的 3D 成像实验室。它将利用共同PI开发的针对肝脏和肝脏肿瘤的分类和分割算法，通过使用多相MDCT图像中的时间强度曲线（TIC）的模式分析来对存活/坏死的肿瘤区域进行分类。项目合作者包括 MGH 癌症中心专门从事 HCC 靶向治疗（特别是抗血管生成治疗）的肿瘤学家，以及 MGH 3D 成像实验室专门从事定量成像分析的成像科学家。该项目的具体目标是： (1) HTV生物标记物的开发：我们将在云计算平台上开发原型HTV生物标记物，包括HTV-Server，它是用于注册、分类和分割的自动化HTV后处理管道多相 MDCT 图像中的肝脏、肿瘤和活/坏死肿瘤区域的图像，以及 HTV-Client，它是一个基于 Web 的用户界面，用于交互式可视化、定量分析和 HTV 定量的护理点数据访问。 (2) HTV生物标志物的评估：我们将通过使用MGH癌症中心接受抗血管生成治疗的50例晚期HCC病例进行临床研究，以评估拟议的HTV生物标志物在肿瘤进展预后和治疗反应中的临床表现。 (3)项目二期计划：我们将在项目二期建立公司流程以满足FDA法规对产品的翻译和验证。我们的工业合作者（TeraRecon Inc、Intrasense）对许可或购买拟议技术以将其集成到其医学成像工作站中表现出浓厚的兴趣。

项目成果

Iterative mesh transformation for 3D segmentation of livers with cancers in CT images.

用于 CT 图像中患有癌症的肝脏 3D 分割的迭代网格变换。

• DOI: 10.1016/j.compmedimag.2015.01.006
• 发表时间: 2015
• 期刊: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
• 作者: Lu,Difei;Wu,Yin;Harris,Gordon;Cai,Wenli
• 通讯作者: Cai,Wenli