Improved Breast DCE MRI with SWIFT

使用 SWIFT 改进乳房 DCE MRI

• 批准号: 7672970
• 负责人: Curtis Andrew Corum
• 金额: $ 26.14万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7672970
• 关键词: Acceleration; Acoustics; Address; Area; Benign; Biopsy; Breast; Cancer Patient; Contrast Media; Data; Detection; Development; Diagnosis; Diagnostic; Disease; Evaluation; Failure; Fatty acid glycerol esters; Female; Financial compensation; Fourier Transform; Gadolinium DTPA; Goals; Image; Imaging Techniques; Immune; Immunity; Implant; Kinetics; Lesion; Magnetic Resonance Imaging; Malignant - descriptor; Measurement; Measures; Medical Imaging; Meta-Analysis; Methods; Modeling; Motion; Noise; Pathologic; Patients; Performance; Phase; Physiologic pulse; Population; Predisposition; Process; Property; Protons; Radial; Ramp; Relaxation; Research; Resolution; Sampling; Scanning; Scheme; Series; Specificity; Staging; Testing; Three-Dimensional Image; Time; Tissues; Ursidae Family; Validation; Woman; Work; base; breast cancer diagnosis; breast lesion; digital; experience; imaging modality; improved; magnetic field; malignant breast neoplasm; novel; pharmacokinetic model; prospective; public health relevance; reconstruction; volunteer

DESCRIPTION (provided by applicant): Today's medical imaging methods have insufficient specificity for reliable differentiation between benign and malignant breast lesions in patients. Pathologic evaluation is currently the only way to obtain a definitive diagnosis. This research will use a novel method of magnetic resonance imaging (MRI), Sweep Imaging with Fourier Transform (SWIFT), at very high magnetic field (4 Tesla) to distinguish malignant from benign breast lesions. Specificity will be gained from improved temporal resolution and contrast kinetic parameter extraction measured non-invasively with proton (1H) MRI. In addition to high temporal resolution and immunity to T2* effects at even the highest contrast agent concentrations, SWIFT offers several other improvements. The 3D radial sampling scheme is motion-correctable with simple k-space based processing. Due to the smooth rotating gradient trajectory, SWIFT is immune to gradient group delay, gradient ramp based errors, and produces orders of magnitude fewer eddy currents than other rapid radial sequences. Another extremely desirable effect of the smooth gradient is that SWIFT is extremely quiet, leading to an improved patient experience and fewer failures to scan. Breast lesions will be visualized by dynamic contrast-enhanced three-dimensional MRI and simultaneously processed into high-temporal resolution / low-spatial resolution, high-spatial resolution / low temporal-resolution, or mixed image series. Since data from a single scan can be formatted into variable spatial and temporal resolutions, the total imaging time can be reduced compared with standard MRI scanning methods. SWIFT MRI measurements will be correlated with biopsy results to determine whether this MRI sequence accurately identifies and characterizes malignant lesions in breast patients. This research will reveal whether the SWIFT sequence bears new capabilities in medical imaging for breast cancer diagnosis. PUBLIC HEALTH RELEVANCE: The proposed research is aimed at improving the accuracy of detection and determination of extent of disease in women suspected of having breast cancer. It should also help reduce cases where a woman is told she has breast cancer in error.

描述（由申请人提供）：当今的医学成像方法不足以在患者​​的良性和恶性乳腺病变之间可靠地差异化。病理评估目前是获得确定诊断的唯一方法。这项研究将使用一种新型的磁共振成像方法（MRI），在非常高的磁场（4 Tesla）处扫除具有傅立叶变换（Swift）的扫描成像，以区分恶性剂和良性乳腺病变。通过质子（1H）MRI无创测量的时间分辨率和对比动力学参数提取，将获得特异性。除了以最高的对比度浓度以最高的时间分辨率和对T2*效果的免疫力外，Swift还提供了其他一些改进。 3D径向采样方案是可与简单的基于K空间处理的运动校正的。由于旋转梯度轨迹平滑，Swift不受梯度组延迟，基于梯度坡道的误差的免疫，并且比其他快速径向序列产生的涡流级数要少。光滑梯度的另一个极为理想的效果是，Swift非常安静，导致患者的经历改善，扫描失败较少。乳房病变将通过动态对比增强的三维MRI来可视化，并同时处理成高颞分辨率 /低空间分辨率，高空间分辨率 /低时间分辨率或混合图像系列。由于可以将来自单个扫描的数据格式化为可变的空间和时间分辨率，因此与标准MRI扫描方法相比，可以减少总成像时间。 SWIFT MRI测量结果将与活检结果相关，以确定该MRI序列是否准确鉴定并表征了乳腺癌患者的恶性病变。这项研究将揭示Swift序列在乳腺癌诊断的医学成像中是否具有新的功能。公共卫生相关性：拟议的研究旨在提高涉嫌患有乳腺癌的妇女的检测和确定疾病程度的准确性。它还应该有助于减少妇女被告知乳腺癌错误的病例。