TISSUE CHARACTERIZATION WITH SLAB SCAN DIFFUSIION MRI

使用板扫描扩散 MRI 进行组织表征

• 批准号: 6540187
• 负责人: Stephan E Maier
• 金额: $ 29.15万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-15 至 2004-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6540187
• 关键词: bioimaging /biomedical imaging; biopsy; brain cell; brain neoplasms; cell differentiation; clinical research; contrast media; histopathology; human subject; magnetic resonance imaging; method development; neoplastic cell; prognosis; stroke; tissue /cell culture

In medical imaging, tissue characterization is fundamental for the assessment of brain tumor pathology and morphology. On T1 or T2- weighted MR images obtained without contrast agents., distinction of pathologic tissue from normal tissue often is limited. Excellent contrast, however, results from diffusion weighted MR imaging in the case of acute stroke. Moreover, tensor diffusion weighting over a considerable wider range than typically used, it has been demonstrated that diffusion in brain tissue is described better with two diffusion components. This finding, referred to as multi--component diffusion, may be due to separate water compartments, such as the extra- and intra-cellular water pools, or due to micro-structural features Preliminary data obtained with line scan diffusion imaging (LSDI) in brain tumors indicates that the two apparent diffusion co-efficients (ADC) and their respective amplitudes permit a clear differentiation among tumor, surrounding edema, and normal tissue. Images based on these parameters, together with the detailed mapping of the fiber tracts through diffusion tensor imaging, provide a tissue characterization that is very suitable for the assessment of brain tumor pathology and morphology. A principal goal of the research proposed here is to implement a fast diffusion imaging technique, referred to as slab scan diffusion imaging (SSDI), for tensor and multi-component ADC tissue characterization of the entire brain volume in a scan time of a few minutes. The proposed diffusion imaging technique does not require cardiac gating or post processing for the suppression of motion artifacts. With SSDI, contrary to single-shot echo planar diffusion-weighted imaging, distortion artifacts in areas of large susceptibility variations are minimal. Diffusion tensor and multi-component ADC data will be collected in normal volunteers and in patients with different brain tumors. Normal tissue values and their respective direction variability (anisotropy) will be established with the ADC data obtained in normal subjects. Tissue separations with diffusion tensor data and multi- component ADC parameters can be compared with tumor margins established by the use of contrast agents and conventional T1-weighted MR imaging. The plan is to correlate the diffusion tensor data and multi- component ADC parameters with the specific tumor pathologies, malignancy guide, and different components of a tumor, i.e., necrotic part, margin, and infiltrated surrounding tissue. The study, therefore, proposes direct applications of basic research to clinical situations demanding the highest possible sensitivity and specific for invasive treatment of other therapeutic decisions.

在医学成像中，组织表征是评估脑肿瘤病理学和形态学的基础。在没有造影剂的情况下获得的 T1 或 T2 加权 MR 图像上，病理组织与正常组织的区别通常是有限的。然而，在急性中风的情况下，弥散加权磁共振成像可以产生出色的对比度。此外，张量扩散加权的范围比通常使用的范围要宽得多，已经证明用两个扩散分量可以更好地描述脑组织中的扩散。这一发现被称为多成分扩散，可能是由于独立的水室，例如细胞外和细胞内水池，或者是由于微观结构特征通过线扫描扩散成像（LSDI）获得的初步数据脑肿瘤中的两个表观扩散系数 (ADC) 及其各自的幅度可以清楚地区分肿瘤、周围水肿和正常组织。基于这些参数的图像，加上通过扩散张量成像对纤维束进行详细映射，提供了非常适合评估脑肿瘤病理学和形态学的组织表征。这里提出的研究的主要目标是实施一种快速扩散成像技术，称为平板扫描扩散成像 (SSDI)，用于在几分钟的扫描时间内对整个大脑体积进行张量和多分量 ADC 组织表征。所提出的扩散成像技术不需要心脏门控或后处理来抑制运动伪影。使用 SSDI，与单次回波平面扩散加权成像相反，磁敏感度变化较大的区域中的失真伪影最小。将在正常志愿者和患有不同脑肿瘤的患者中收集弥散张量和多分量 ADC 数据。正常组织值及其各自的方向变异性（各向异性）将根据在正常受试者中获得的 ADC 数据来确定。具有扩散张量数据和多分量 ADC 参数的组织分离可以与通过使用造影剂和传统 T1 加权 MR 成像建立的肿瘤边缘进行比较。该计划是将扩散张量数据和多分量 ADC 参数与特定的肿瘤病理、恶性肿瘤指南和肿瘤的不同组成部分（即坏死部分、边缘和浸润的周围组织）相关联。因此，该研究建议将基础研究直接应用于需要最高可能灵敏度的临床情况，并且针对其他治疗决策的侵入性治疗。

项目成果

Monitoring response to convection-enhanced taxol delivery in brain tumor patients using diffusion-weighted magnetic resonance imaging.

• 发表时间: 2001-07
• 期刊: Cancer research
• 影响因子: 11.2
• 作者: Y. Mardor;Yiftach Roth;Z. Lidar;Tali Jonas;Raphael Pfeffer;Stephan E. Maier;M. Faibel;D. Nass;Moshe Hadani;Arie Orenstein;Jack S. Cohen;Zvi Ram