Advancing MRI technology for early diagnosis of liver metastases

推进 MRI 技术用于肝转移的早期诊断

• 批准号: 10524177
• 负责人: Maria I. Altbach
• 金额: $ 7.34万
• 依托单位: UNIVERSITY OF ARIZONA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10524177
• 关键词: 3-Dimensional; Abdomen; Accounting; Adopted; Affect; Algorithms; Arizona; Benign; Breathing; Cessation of life; Chelating Agents; Clinic; Clinical; Clinical Trials; Colorectal; Colorectal Cancer; Country; Data; Detection; Diagnosis; Diagnostic; Discrimination; Disease; Drops; Early Diagnosis; Engineering; Excision; Foundations; Gadolinium; Goals; Image; Image Analysis; Image Enhancement; Imaging Techniques; Imaging technology; Incidence; Industry; Knowledge; Lesion; Life; Liver; Liver neoplasms; Location; Magnetic Resonance Imaging; Malignant - descriptor; Malignant Neoplasms; Medical; Metastatic Neoplasm to the Liver; Methods; Motion; Neoplasm Metastasis; Operative Surgical Procedures; Outcome; Patient Selection; Patients; Phase; Physiological; Population; Precision therapeutics; Radial; Reproducibility; Research; Resectable; Resolution; Scanning; Scheme; Scientist; Sensitivity and Specificity; Techniques; Technology; Test Result; Translations; Treatment outcome; Universities; Unresectable; Variant; Work; accurate diagnosis; alternative treatment; base; cancer imaging; care outcomes; clinical practice; clinical translation; colon cancer patients; contrast enhanced; contrast imaging; cost; data acquisition; deep neural network; design; diagnostic accuracy; diagnostic value; efficacy evaluation; flexibility; image processing; image reconstruction; imaging facilities; imaging modality; improved; industry partner; liver imaging; new technology; next generation; novel; personalized care; reconstruction; research clinical testing; soft tissue; spatiotemporal; tumor; tumor specificity

Abstract Liver is commonly involved in metastatic disease in colorectal cancer (CRC) and knowledge about the presence and location of these tumors affects treatment decisions. In patients with CRC, surgical or ablative treatment of liver metastases improves overall survival. Early diagnosis of colorectal metastases (i.e. while lesions are small) is expected to improve treatment outcomes by increasing the number of subjects that can undergo surgical resection or by identifying subjects early on, when non-surgical options are an alternative treatment. Magnetic Resonance Imaging (MRI) is regarded as the most effective imaging modality for the detection and characterization of liver neoplasms; T2-weighted (T2w) and T1-weighted (T1w) images - combined with administration of a gadolinium chelate agent and multi-phase dynamic contrast enhancement (DCE) - are the foundational acquisitions used for the detection and characterization of liver tumors. However, challenges remain for the detection and characterization of small lesions due to factors including inadequate spatial resolution, partial volume effects, physiological motion, and variations in timing of contrast arrival in DCE imaging. In this academic-industrial partnership the scientific and engineering teams at the University of Arizona and Siemens Medical Solutions are coming together to develop robust radial MRI techniques for T2w/T2 mapping and DCE imaging of the liver to improve detection and characterization of small tumors with the goal of bringing these techniques to routine clinical practice. The proposed work is based on a radial turbo spin- echo technique pioneered by the team at the University of Arizona for abdominal imaging and a radial stack-of-stars technique with continuous acquisition for DCE imaging. The specific aims of the partnership are: Aim 1: To develop radial T2w acquisition and reconstruction techniques with efficient full coverage of the liver for small tumor detection and accurate T2 quantification for tumor characterization. Aim 2: To implement a self-navigated 3D radial stack-of-stars technique for continuous acquisition of DCE data and retrospective reconstruction of the dynamic phases. Aim 3: To conduct a clinical evaluation of the techniques from Aims 1 and 2 against conventional T2w and DCE techniques. Aim 4: To streamline translation of the new radial methods to the clinic by developing a computationally efficient reconstruction pipeline. The endpoints of our study include technical advances in MRI acquisitions that markedly overcome limitations of current liver MRI for the diagnosis of early metastases. We expect our proposal to yield technology improvements that will increase precision of care and outcomes in patients with metastatic malignancies, in particular those with colorectal cancer.

抽象的 肝脏通常与结直肠癌 (CRC) 的转移性疾病有关，并且相关知识 这些肿瘤的存在和位置会影响治疗决策。在结直肠癌患者中， 肝转移的手术或消融治疗可提高总体生存率。早期诊断 结直肠转移（即病变较小）预计可通过以下方式改善治疗结果： 增加可以接受手术切除的受试者数量或通过识别受试者 早期，当非手术选择是一种替代治疗方法时。磁共振成像 (MRI) 被认为是检测和表征最有效的成像方式 肝脏肿瘤； T2 加权 (T2w) 和 T1 加权 (T1w) 图像 - 结合 钆螯合剂的施用和多相动态对比度增强 (DCE) - 是用于肝脏检测和表征的基础采集 肿瘤。然而，由于小病变的检测和表征仍然存在挑战 因素包括空间分辨率不足、部分体积效应、生理运动和 DCE 成像中造影剂到达时间的变化。在这种学术与工业合作伙伴关系中 亚利桑那大学和西门子医疗解决方案公司的科学和工程团队 共同开发用于 T2w/T2 映射和 DCE 成像的强大径向 MRI 技术 肝脏，以改善小肿瘤的检测和表征，目标是带来 将这些技术纳入常规临床实践。所提出的工作是基于径向涡轮自旋 亚利桑那大学团队首创的回声技术用于腹部成像和 用于 DCE 成像的连续采集的径向恒星堆栈技术。具体目标 合作伙伴关系是： 目标 1：开发径向 T2w 采集和重建技术 高效全覆盖肝脏小肿瘤检测和肿瘤准确T2定量 表征。目标 2：实现自导航 3D 径向星堆叠技术 DCE 数据的连续采集和动态相位的回顾性重建。目的 3：针对目标 1 和 2 的技术相对于传统 T2w 进行临床评估 和 DCE 技术。目标 4：通过以下方式简化新放射治疗方法向临床的转化： 开发计算高效的重建管道。我们研究的终点包括 MRI 采集技术的进步显着克服了当前肝脏 MRI 的局限性 早期转移的诊断。我们希望我们的提案能够带来技术改进 这将提高转移性​​恶性肿瘤患者的护理精度和结果， 特别是那些患有结直肠癌的人。