Advanced MR Imaging and Image Analytics as a Precision Medicine Tool to Manage ADPKD

先进的 MR 成像和图像分析作为管理 ADPKD 的精准医学工具

• 批准号: 10259833
• 负责人: Timothy Lee Kline
• 金额: $ 11.23万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2023-03-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10259833
• 关键词: 3-Dimensional; Abdomen; Affect; Age; Anatomy; Animals; Architecture; Area; Autosomal Dominant Polycystic Kidney; Basic Science; Biological Markers; Biology; Biometry; Blood Vessels; Classification; Clinic; Clinical; Clinical Management; Clinical Research; Consumption; Cyst; Data; Databases; Disease; Disease Marker; Disease Progression; Educational workshop; Effectiveness of Interventions; End stage renal failure; Environment; FarGo; Fibrosis; Genetic; Genetic Programming; Geometry; Goals; Gold; Grant; Hepatic Cyst; Image; Image Analysis; Imaging Techniques; Imaging technology; Informatics; Institution; Intervention; K-Series Research Career Programs; Kidney; Knowledge; Liver; Magnetic Resonance; Magnetic Resonance Imaging; Measurement; Measures; Medical; Medical Imaging; Mendelian disorder; Mentored Research Scientist Development Award; Mentors; Mentorship; Microscopic; Monitor; National Institute of Diabetes and Digestive and Kidney Diseases; Nephrology; Organ; Pathology; Patient Care; Patient imaging; Patients; Pattern; Pattern Recognition; Performance; Perfusion; Phase; Phenotype; Physics; Physiologic pulse; Physiology; Polycystic Kidney Diseases; Process; Prognosis; Protocols documentation; Publications; Radiology Specialty; Renal Blood Flow; Renal Tissue; Renal function; Reproducibility; Research; Research Personnel; Research Proposals; Resolution; Spin Labels; Standardization; Structure; Study models; Suggestion; Techniques; Testing; Texture; Time; Training; Translating; Treatment Effectiveness; Writing; automated segmentation; base; bioimaging; career; clinical practice; cost; deep learning; disease diagnosis; educational atmosphere; functional decline; human model; image processing; imaging biomarker; imaging modality; improved; insight; interest; kidney vascular structure; knowledge base; novel imaging technology; outcome prediction; precision medicine; pressure; prognostic value; radiological imaging; renal artery; research study; shear stress; symposium; tool

ABSTRACT The goal of this NIDDK Mentored Research Scientist Development Award is to provide an organized scientific and educational environment for Dr. Timothy Kline to begin his transition into an independent research career focused on developing novel imaging technologies and image analysis techniques for abdominal organ pathologies. This proposal outlines a five-year training plan at Mayo Clinic under the primary mentorship of Dr. Bradley Erickson and a Mentoring Team comprised of accomplished researchers in the fields of: biology, nephrology, genetics, radiology, informatics; medical physics, biostatistics, image processing, and physiology. The focus of this proposal is to improve both research studies and disease prognosis for autosomal dominant polycystic kidney disease (ADPKD) patients through biomedical imaging techniques. It is well understood that imaging is essential for ADPKD diagnosis, monitoring, and outcome prediction. Clinical studies utilize total kidney volume (TKV) (as measured by MRI as an image-based biomarker) to follow the progression of ADPKD, as larger TKVs have been shown to correlate with worse prognosis in both human and animal-model studies. However, there are challenges with using TKV as a marker of disease progression. For one, it is a simplification of the disease state and does not inform on microscopic disease processes that are involved with piecemeal destruction of healthy renal tissue. In addition, measurements of TKVs are time consuming, costly, and poorly standardized. The introduction of automated approaches for measuring TKV will: greatly improve measurement throughput, significantly reduce costs associated with performing research studies, allow accurate and reproducible measurements to be obtained both within and across institutions; facilitate the search for new imaging biomarkers. The specific aims of this project are to: (i) develop and validate automated tools to characterize renal structure, such as TKV and cystic burden; (ii) explore new imaging biomarkers by image texture feature analysis and pattern recognition techniques; and (iii) develop a new technique to measure renal blood flow. This research will be facilitated by Mayo Clinic's outstanding clinical and research environment dedicated to improving patient care, as well as the Mayo Clinic Translational PKD Center, which focuses on translating basic science research into improvements in the management and treatment of ADPKD patients. Dr. Kline's background in imaging technologies and image processing makes him particularly suited to perform this research. In addition to the above aims, Dr. Kline will: 1) develop a strong knowledge base in both nephrology and radiology by attending relevant rounds, seminars, and national conferences; 2) enhance his knowledge of medical imaging, biology, physiology, genetics, and programming through coursework and mentoring; 3) attend workshops focused on grant and publication writing; and 4) 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 new imaging biomarkers of ADPKD. Obtaining this K Award will greatly facilitate Dr. Kline's transition into a prosperous independent research career.

抽象的 NIDDK指导研究科学家发展奖的目标是提供有组织的科学 蒂莫西·克莱恩（Timothy Kline）博士开始过渡到独立研究职业的教育环境 专注于开发腹部器官的新型成像技术和图像分析技术 病理。该提案在博士的主要指导下概述了梅奥诊所的五年培训计划。 布拉德利·埃里克森（Bradley Erickson）和一支由以下领域的研究人员组成：生物学， 肾脏学，遗传学，放射学，信息学；医学物理学，生物统计学，图像处理和生理学。 该提案的重点是改善研究和疾病预后的常染色体优势 多囊肾脏疾病（ADPKD）患者通过生物医学成像技术。众所周知 成像对于ADPKD诊断，监测和结果预测至关重要。临床研究利用总数 肾脏体积（TKV）（由MRI作为基于图像的生物标志物测量）遵循 ADPKD，因为已显示较大的TKV与人类和动物模型的预后较差相关 研究。但是，将TKV用作疾病进展的标志存在挑战。首先，这是一个 简化了疾病状态，并且不告知与微观疾病的过程有关 健康的肾组织破坏。此外，TKV的测量是耗时，昂贵的， 并且标准化不佳。引入测量TKV的自动化方法将：大大改善 测量吞吐量，显着降低与进行研究相关的成本，允许 在机构内部和跨机构内获得的准确且可重复的测量值；促进 搜索新的成像生物标志物。该项目的具体目的是：（i）开发和验证自动化 表征肾脏结构的工具，例如TKV和囊性负担； （ii）通过 图像纹理特征分析和图案识别技术； （iii）开发一种新技术 测量肾血流。这项研究将由Mayo诊所的杰出临床和研究促进 致力于改善患者护理的环境以及梅奥诊所转化PKD中心，该中心 专注于将基础科学研究转化为改进ADPKD的管理和治疗 患者。 Kline博士在成像技术和图像处理方面的背景使他特别适合 进行这项研究。除上述目的外，克莱恩博士还将：1）在 通过参加相关的回合，研讨会和民族会议，肾脏学和放射学既有； 2）增强 他对医学成像，生物学，生理学，遗传学和编程的了解， 指导； 3）参加专注于赠款和出版写作的研讨会； 4）提交竞争激烈 R01应用程序扩展了该研究建议的发现。该提议将导致广泛 改进当前分析工作流程，以及对预后能力的改进理解 ADPKD的新成像生物标志物。获得此K奖将极大地促进Kline博士的过渡到 繁荣的独立研究职业。

项目成果

Abdominal Imaging in ADPKD: Beyond Total Kidney Volume.

• DOI: 10.3390/jcm12155133
• 发表时间: 2023-08-05
• 期刊: Journal of clinical medicine
• 影响因子: 3.9

AI in the Loop: functionalizing fold performance disagreement to monitor automated medical image segmentation workflows.

• DOI: 10.3389/fradi.2023.1223294
• 发表时间: 2023
• 期刊: Frontiers in radiology
• 作者: Gottlich, Harrison C.;Korfiatis, Panagiotis;Gregory, Adriana V.;Kline, Timothy L.
• 通讯作者: Kline, Timothy L.

Effect of Dataset Size and Medical Image Modality on Convolutional Neural Network Model Performance for Automated Segmentation: A CT and MR Renal Tumor Imaging Study.

• DOI: 10.1007/s10278-023-00804-1
• 发表时间: 2023-08
• 期刊: JOURNAL OF DIGITAL IMAGING
• 影响因子: 4.4
• 作者: Gottlich, Harrison C.;Gregory, Adriana V.;Sharma, Vidit;Khanna, Abhinav;Moustafa, Amr U.;Lohse, Christine M.;Potretzke, Theodora A.;Korfiatis, Panagiotis;Potretzke, Aaron M.;Denic, Aleksandar;Rule, Andrew D.;Takahashi, Naoki;Erickson, Bradley J.;Leibovich, Bradley C.;Kline, Timothy L.
• 通讯作者: Kline, Timothy L.

In vivo magnetic resonance imaging techniques for structural and functional characterization of murine model kidneys.

• DOI: 10.1016/bs.mcb.2019.05.007
• 发表时间: 2019
• 期刊: Methods in cell biology
• 作者: T. Kline