MRI Diffusion in Tumors using Oscillating Gradients

摘要/概要 这次修订后的竞争性更新旨在延长以前资助的技术发展 验证和应用一种新的基于扩散的MR成像技术，定量时间扩散 光谱（qTDS），其提供关于组织微结构的独特信息，并且特别地可以揭示 治疗后肿瘤的早期变化。在上一个周期中，我们开发了这种创新方法， 表明它是细胞尺寸和组织微观结构变化的敏感指标， 在细胞密度或肿瘤体积发生明显变化之前，在细胞分裂和凋亡期间发生。作为 因此，qTDS在评估特定治疗方案是否有效方面具有相当大的潜力， 可以为患者选择最佳疗法和减少可避免的副作用提供信息。QTDS是 基于对应于不同空间的不同时间尺度上的水扩散速率的测量， 尺寸.我们以前已经证明它可以检测细胞内结构和细胞大小的变化， 密度，在细胞培养物和动物模型中，在治疗过程的早期，并且没有一些 影响其他扩散技术的混杂因素，如细胞膜渗透性的变化。我们 我进行了理论分析，计算机模拟，细胞和体内动物研究，以了解 影响qTDS测量的因素，并已实施了第一个实际的qTDS采集上的一个 人体3 T扫描仪在目前的建议中，我们的目标是扩展我们以前的工作，并使用qTDS作为体内 用于非侵入性表征特定细胞变化的成像技术， 只能通过侵入性活检评估。我们建议在癌症的细胞和动物模型中验证qTDS， 确定qTDS是否能够在特异性免疫反应早期检测治疗诱导的细胞大小变化。 治疗方案。我们还建议通过证明其在临床上的表现来翻译qTDS。 预测乳腺癌的新辅助治疗反应。我们假设qTDS能够 表征与治疗诱导的细胞凋亡相关的不同细胞变化，从而提供了一种治疗方法。 在治疗的早期阶段评估肿瘤反应的创新和独特的手段。我们的具体目标是： [i]在乳腺癌转基因小鼠模型中，我们将定量绘制体内肿瘤细胞大小和密度， 并使用定量的、共配准的 组织学：[ii]在不同靶向药物治疗的乳腺癌小鼠模型中，我们将评估qTDS， 能够检测治疗诱导的细胞凋亡并预测治疗功效的成像生物标志物 在治疗早期：[iii]在人类乳腺癌患者中，我们将评估qTDS作为以下指标的成像生物标志物： 评估乳腺肿瘤对新辅助化疗的早期反应并预测治疗后的疗效 通过将成像数据与临床和病理相关联， 应答所提出的qTDS方法具有测量体内细胞大小变化并改善细胞生长的潜力。 评估治疗反应，从而有助于个性化的临床癌症护理。

Abstract / Summary This revised competitive renewal seeks to extend the technical developments of the previous funding period to validate and apply a novel diffusion-based MR imaging technique, quantitative temporal diffusion spectroscopy (qTDS), that provides unique information on tissue microstructure and in particular can reveal early changes in tumors after treatment. In the previous cycle we developed this innovative method and showed it is a sensitive indicator of changes in cell dimensions and tissue microstructure such as those that occur with cell division and during apoptosis, before frank changes occur in cell density or tumor volume. As such, qTDS has considerable potential for assessing whether specific treatment regimens are working, and so may inform the selection of optimal therapies for patients and the reduction of avoidable side-effects. QTDS is based on measurements of water diffusion rates over different time scales corresponding to different spatial dimensions. We have previously shown it can detect changes in intracellular structure and cell sizes and density, in cell cultures and in animal models, early in the course of a treatment and without some of the confounding factors that affect other diffusion techniques, such as changes in cell membrane permeability. We have performed theoretical analyses, computer simulations, and cell and in vivo animal studies, to understand the factors that affect qTDS measurements, and have implemented the first practical qTDS acquisitions on a human 3T scanner. In the current proposal we aim to extend our previous work and use qTDS as an in vivo imaging technique for non-invasive characterization of specific cellular changes which are currently assessable only via invasive biopsy. We propose to validate qTDS in cell and animal models of cancer, and determine whether qTDS is capable of detecting treatment-induced cell size changes early in specific therapeutic regimens. We also propose to translate qTDS clinically by demonstrating its performance in predicting neoadjuvant treatment response in breast cancer. We hypothesize that qTDS is capable of characterizing the distinct cellular changes associated with treatment-induced apoptosis, thereby providing an innovative and unique means of assessing tumor response at an early stage of therapy. Our specific aims are: [i] in a transgenic mouse model of breast cancer, we will quantitatively map tumor cell size and density in vivo, and validate the qTDS derived parameters on a voxel by voxel basis using using quantitative, co-registered histology: [ii] in mouse models of breast cancer treated by different targeted drugs, we will evaluate qTDS as an imaging biomarker capable of detecting treatment-induced apoptosis and predicting treatment efficacy early during therapy: [iii] In human breast cancer patients, we will evaluate qTDS as an imaging biomarker for assessing breast tumor early response to neoadjuvant chemotherapy and predicting treatment efficacy after the first and subsequent cycles of treatment by correlating imaging data with clinical and pathological responses. The proposed qTDS method has the potential to measure cell size changes in vivo and improve the assessment of treatment response and thereby contribute to personalized clinical cancer care.