Artificial Intelligence-Based Approaches for Renal Structure Characterization in Computed Tomography Images

摘要 NIDDK R03小额助学金计划的目标是为Kline博士提供额外的资金，以扩大 在他的K奖上工作，并将他的专业知识应用于新的图像采集和与肾脏相关的问题 成像。克莱恩博士的工作激起了许多内部和外部调查人员的兴趣，并导致了 最近与鲁尔、德尼克和金博士的合作。与埃里克森博士一起，这个新的研究团队已经 准备了这份R03建议书，它利用了每个团队成员的独特专业知识。的关注点 这一建议是为了弥合显微观察和非侵入性评估之间的差距 放射成像。为此，我们建立了一个独特的肾脏CT成像数据集和 相应的活检测量肾单位密度。我们还生成了一个大型金本位数据库 肾脏、皮质区和延髓锥体的分割数据。利用这些现有数据，我们建议 为：(1)开发分割肾脏、分割单个髓质锥体和输入的工具 CT图像中成像视野之外的肾脏缺失部分，以及(Ii)建立成像 早期CKD的生物标志物，并将宏观成像结果与潜在的微观结构相关联。这 梅奥诊所致力于以下方面的卓越临床和研究环境将促进研究 改善患者护理，以及老化肾脏解剖研究(PI：规则)，这导致了 这一独特且具有良好特性的数据集。克莱恩博士在成像技术和成像方面的背景 处理过程使他特别适合进行这项研究。除了上述目标外，在 本研究项目结束后，克莱恩博士将提交一份极具竞争力的R01申请，扩展到 这项研究提案的发现。这一建议将极大地改善目前的分析 工作流程，以及对肾脏成像生物标记物预后能力的更好理解。 获得R03奖将极大地促进克莱恩博士转变为一名成功的独立研究人员 专注于开发腹部器官的新成像技术和图像分析技术 病理学。

ABSTRACT The goal of this R03 Small Grant Program for NIDDK is to provide additional funding for Dr. Kline to expand upon his work on his K award and apply his expertise to new image acquisitions and problems related to renal imaging. Dr. Kline’s work has piqued the interest of many internal and external investigators and has led to recent collaborations with Drs. Rule, Denic, and Kim. Together with Dr. Erickson, this new research team has prepared this R03 proposal which takes advantage of the unique expertise of each team member. The focus of this proposal is to bridge the gap between microscopic observations and those assessable non-invasively by radiological imaging. To do this, we have established a unique dataset of renal CT imaging data and corresponding biopsy measured nephron densities. We have also generated a large database of gold-standard segmentation data of kidneys, cortical regions, and medullary pyramids. Using this existing data, we propose to: (i) develop tools for segmentation of kidneys, segmentation of individual medullary pyramids, and imputing missing parts of the kidneys outside of the imaged field-of-view in the CT image, and (ii) to establish imaging biomarkers of early CKD, and correlate macroscopic imaging findings to underlying microscopic structure. This research will be facilitated by Mayo Clinic’s outstanding clinical and research environment dedicated to improving patient care, as well as the Aging Kidney Anatomy Study (PI: Rule), which led to the generation of this unique and well characterized dataset. Dr. Kline’s background in imaging technologies and image processing makes him particularly well suited to perform this research. In addition to the above aims, near the end of this research project Dr. Kline will submit a highly competitive R01 application expanding upon the findings from this research proposal. This proposal will lead to vast improvements to current analysis workflows, as well as an improved understanding of the prognostic power of renal imaging biomarkers. Obtaining this R03 Award will greatly facilitate Dr. Kline’s transition into a prosperous independent researcher focused on developing novel imaging technologies and image analysis techniques for abdominal organ pathologies.