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

基于人工智能的计算机断层扫描图像中肾脏结构表征方法

• 批准号: 10040835
• 负责人: Timothy Lee Kline
• 金额: $ 11.34万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10040835
• 关键词: Abdomen; Affect; Aging; Albuminuria; Anatomy; Area; Arteries; Artificial Intelligence; Autosomal Dominant Polycystic Kidney; Award; Biopsy; Chronic Kidney Failure; Clinic; Clinical Research; Collaborations; Communities; Computer Vision Systems; Data; Data Set; Databases; Detection; Development; Disease; Early Diagnosis; Environment; Fibrosis; Funding; Generations; Goals; Gold; Grant; Health; Hepatic Cyst; Hour; Hypertension; Image; Image Analysis; Imaging technology; Individual; K-Series Research Career Programs; Kidney; Kidney Diseases; Machine Learning; Magnetic Resonance Imaging; Measurement; Measures; Methods; Microscopic; National Institute of Diabetes and Digestive and Kidney Diseases; Nephrons; Organ; Outcome; Pathology; Patient Care; Patient imaging; Patients; Polycystic Kidney Diseases; Radiologic Finding; Renal Blood Flow; Reproducibility; Research; Research Personnel; Research Project Grants; Research Proposals; Resources; Risk; Scanning; Semantics; Services; Stenosis; Structure; Surveys; Techniques; Technology; Time; Transplantation; Tubular formation; Visit; Work; X-Ray Computed Tomography; automated analysis; automated image analysis; automated segmentation; base; clinical decision-making; clinical practice; deep learning; density; early detection biomarkers; graft failure; image processing; imaging biomarker; imaging modality; improved; interest; interstitial; kidney biopsy; learning strategy; living kidney donor; member; microscopic imaging; non-invasive imaging; novel; novel imaging technology; personalized decision; precision medicine; prognostic value; programs; radiological imaging; research clinical testing; tool

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.

摘要