Quantitative Multimodal Image Guidance for Improved Liver Cancer Treatment

定量多模态图像指导改善肝癌治疗

基本信息

批准号：
9982672
负责人：
JAMES S DUNCAN
金额：
$ 60.16万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-08-01 至 2022-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9982672
关键词：
Acidity Acidosis Address Advanced Development Angiography Biochemical Biological Markers Blood Vessels Blood flow Cancer Etiology Cancer Patient Catheters Cellularity Cessation of life Chemoembolization Classification Clinic Clinical Data Data Analyses Deposition Development Diagnosis Dictionary Disease Drug Delivery Systems Drug Targeting Drug usage Edema Emulsions Environment Epidemic Evaluation Excision Future Goals Grant Hepatitis B Hepatitis C High Dose Chemotherapy Hypoxia Image Image Analysis Imaging Techniques Imaging technology Incidence Industrialization Intervention Learning Liver neoplasms Local Therapy Machine Learning Magnetic Resonance Imaging Malignant Neoplasms Malignant neoplasm of liver Maps Measures Mediating Methodology Methods Modification Multimodal Imaging Necrosis Normal tissue morphology Obesity Oils Oncology Operative Surgical Procedures Outcome Outcome Assessment Patient Care Patient-Focused Outcomes Patients Pattern Pharmaceutical Preparations Phase Physiological Preparation Property Recurrence Roentgen Rays Role Stage at Diagnosis Structure System Technology Therapeutic Embolization Tissues Translational Research Translations Transplantation Treatment outcome Tumor Markers Tumor Tissue Tumor-Derived Tweens Vascularization Visualization Work X-Ray Computed Tomography angiogenesis arm base cancer cell cancer therapy chemotherapy clinical practice cone-beam computed tomography contrast imaging curative treatments extracellular feeding image guided image guided intervention image processing image registration imaging biomarker improved improved outcome innovative technologies learning strategy machine learning method minimally invasive nonalcoholic steatohepatitis nonlinear regression novel novel strategies novel therapeutics outcome prediction palliative personalized cancer therapy random forest response systemic toxicity targeted delivery treatment guidelines treatment strategy tumor tumor microenvironment tumor progression

项目摘要

Project Summary/Abstract Liver cancer is the second most common cause of cancer-related death worldwide and is likely to grow even more in the next decade given the epidemic levels of hepatitis B and C and the emergence of non-alcoholic steatohepatitis (NASH) due to obesity in the US. Most liver cancer patients present with disease that cannot be treated surgically. Minimally invasive, catheter-based, intra-arterial therapies such as TACE (transarterial chemoembolization) have become the mainstay therapy and are included in all treatment guidelines because of their ability to achieve local tumor control and extend survival. TACE overcomes the problem of chemoresistance in cancer cells by delivering high dose chemotherapy through image guidance and embolization of the tumor feeding blood vessel. TACE most commonly uses an oily medium (Lipiodol) as a radiopaque drug delivery mate- rial by creating an emulsion between drugs and oil. The recent introduction of drug-eluting bead (DEB) technol- ogy provides an opportunity to achieve the goal of controlled and sustainable drug release to tumors, which was not possible with oily TACE. Although TACE clearly improves patient survival, limitations still exist – speciﬁcally, incomplete treatment and tumor recurrence – attributed to the stimulation of angiogenesis. Most of these issues can be addressed with a greater understanding of the tumor microenvironment, in particular the relationship that exists between hypoxia, acidosis and angiogenesis. In fact, the development of imaging biomarkers reﬂecting changes within the tumor microenvironment is increasingly being pursued to individualize cancer therapies and increase their potency. Yet, our ability to characterize the tumor microenvironment using current imaging tech- nology is extremely limited. TACE has had to rely on 2D X-ray angiography until recently when the emergence of intra-procedural dual phase cone beam CT (DP-CBCT) contributed signiﬁcantly to improving tumor visualization, microcatheter guidance, and treatment endpoint. It is precisely through the longstanding close partnership be- tween Philips, Johns Hopkins and now Yale that this technology was optimized and became broadly accepted as the new standard of practice for TACE, demonstrating the prompt successful translation of research ﬁndings to clinical practice. However, the targeting of tumors and assessment of outcomes continues to be limited, relying on qualitative/semi-quantitative enhancement patterns from DP-CBCT and single parameter MR images. The unique partnership between Yale & Philips provides innovative technology that will directly enhance the role of image-guided intervention and address this unmet need by quantitatively characterizing the tumor microenvi- ronment and tumor tissue composition in order to maximize treatment potency and improve outcomes. We will integrate advanced, multiparameter MR with active CBCT imaging and create valuable biomarkers derived from novel machine learning methods for image and data analysis. By providing essential, quantitative information, drug delivery to tumors can be maximized because it will be based on inherent tumor properties. In the same way, the assessment of therapy will be much more precise and therefore useful to identify responders.

项目概要/摘要肝癌是全球第二大癌症相关死亡原因，并且甚至可能增长鉴于乙型肝炎和丙型肝炎的流行程度以及非酒精性肝炎的出现，未来十年还会有更多在美国，大多数肝癌患者都患有由肥胖引起的脂肪性肝炎 (NASH)。进行微创、基于导管的动脉内治疗，例如 TACE（经动脉化疗）。化疗栓塞术）已成为主要治疗方法，并包含在所有治疗指南中，因为他们实现局部肿瘤控制和延长生存期的能力克服了化疗耐药性问题。通过图像引导和肿瘤栓塞提供高剂量化疗来治疗癌细胞 TACE 最常使用油性介质（碘化油）作为不透射线的药物输送材料。最近推出的药物洗脱珠 (DEB) 技术通过在药物和油之间形成乳液来实现。 ogy 提供了实现肿瘤受控和可持续药物释放目标的机会，该目标是尽管 TACE 明显提高了患者的生存率，但仍然存在局限性——具体来说，治疗不彻底和肿瘤复发——大多数问题是由于刺激血管生成造成的。可以通过更好地了解肿瘤微环境来解决，特别是与肿瘤微环境之间的关系缺氧、酸中毒和血管生成之间存在的关系实际上反映了影像学生物标志物的发展。人们越来越多地追求肿瘤微环境的变化，以实现个体化的癌症治疗和然而，我们利用当前的成像技术来表征肿瘤微环境的能力。直到最近 TACE 的出现，技术才极其有限。术中双相锥形束 CT (DP-CBCT) 显着改善肿瘤可视化，微导管引导和治疗终点正是通过长期密切的合作伙伴关系而实现的。在飞利浦、约翰霍普金斯大学和现在的耶鲁大学之间，这项技术得到了优化并被广泛接受 TACE 的新实践标准，展示了研究成果迅速成功转化为然而，临床实践中，肿瘤靶向和结果评估仍然有限。 DP-CBCT 和单参数 MR 图像的定性/半定量增强模式。耶鲁大学与飞利浦之间的独特合作关系提供的创新技术将直接增强图像引导干预并通过定量描述肿瘤微环境来解决这一未满足的需求我们将研究环境和肿瘤组织成分，以最大限度地提高治疗效力并改善结果。将先进的多参数 MR 与主动 CBCT 成像相结合，并创建有价值的生物标志物用于图像和数据分析的新颖机器学习方法通过提供必要的定量信息，可以最大限度地向肿瘤输送药物，因为这将基于肿瘤的固有特性。这样，治疗的评估将更加精确，因此有助于识别反应者。