Advanced Diffusion Imaging for Management of Renal Cancer: Oncologic Control and Renal Functional Reserve - Resubmission - 1

项目摘要 肾癌是严重的死亡率和发病率的来源，不仅由于原发性恶性肿瘤，而且还由于 肾部分切除术后肾功能丧失（有时导致慢性肾病）。方法 因此，非侵入性地监测肾功能并预测其对这种功能下降的鲁棒性， 高要求。弥散加权磁共振成像很好地准备发挥这一作用，作为一个辅助肾癌患者的 现有临床MR检查。我们的团队一直处于先进的肾脏弥散磁共振成像研究的前沿 对比度，包括从微循环中分离微结构的方法（体素内非相干运动 （IVIM））和评估微观各向异性（扩散张量成像（DTI））。最近的一项综合办法 （REFMAP）共同收集这些对比，允许评估微结构和微循环 各向异性我们建议将该复合数据集应用于原发性肾脏疾病的侵袭性分类， 并评估和预测术后肾功能。 将进行IVIM-MRI以表征原发性病变的侵袭性。REFMAP-MRI方案 将用于评价肾癌患者术前和1年随访时，与标准 临床检查（测量肾小球滤过率、蛋白尿）。横截面相关性将验证 作为肾功能探针的REFMAP-MRI技术的标志物，以及预测 将确定发生肾功能下降的患者。

PROJECT SUMMARY Renal cancer is a source of severe mortality and morbidity, not only due to the primary malignancy but also due to loss of renal function (sometimes leading to chronic kidney disease) after partial nephrectomy. Methods to noninvasively monitor renal function and predict its robustness against this decline of function are therefore in high demand. Diffusion-weighted MRI is well poised to play this role as an adjunct to renal cancer patients' existing clinical MR workup. Our group has been at the forefront of research into advanced renal diffusion MRI contrast, including methods to separate microstructure from microcirculation (intravoxel incoherent motion (IVIM)) and assess microscopic anisotropy (diffusion tensor imaging (DTI)). A recent comprehensive approach (REFMAP) collects these contrasts jointly, allowing assessment of microstructural and microcirculation anisotropy. We propose to apply this composite dataset both to classify aggressiveness of the primary renal lesion and to assess and predict post-surgical renal function. IVIM-MRI will be performed to characterize the aggressiveness of the primary lesion. The REFMAP-MRI protocol will be used to evaluate renal cancer patients before surgery and at 1 year follow up, in comparison with standard clinical workup (measured glomerular filtration rate, proteinuria). Cross-sectional correlation will validate the markers of the REFMAP-MRI technique as probes of renal function, and those baseline values predicting which patients experience renal function decline will be identified.