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.

摘要 这个NIDDK指导研究科学家发展奖的目标是提供一个有组织的科学 蒂莫西·克莱恩博士开始他的过渡到一个独立的研究生涯 专注于开发腹部器官的新型成像技术和图像分析技术， 病理学。该建议书概述了马约诊所在Dr. 布拉德利埃里克森和一个指导团队组成的领域有成就的研究人员：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常染色体显性遗传的研究和疾病预后。 多囊肾病（ADPKD）患者通过生物医学成像技术。很好理解的是 影像学检查对于ADPKD的诊断、监测和预后预测至关重要。临床研究使用总数 肾脏体积（TKV）（通过MRI测量，作为基于图像的生物标志物），以跟踪 ADPKD，因为在人类和动物模型中，较大的TKV与预后较差相关 问题研究然而，使用TKV作为疾病进展的标志物存在挑战。首先，它是一个 疾病状态的简化，并没有提供与疾病相关的微观疾病过程的信息。 对健康肾组织的破坏。此外，TKV的测量是耗时的、昂贵的， 标准化程度低。采用自动化方法测量TKV将： 测量吞吐量，显著降低与执行研究相关的成本， 在机构内部和机构之间获得准确和可重复的测量结果;促进 寻找新的成像生物标志物。该项目的具体目标是：（一）开发和验证自动化 表征肾脏结构的工具，如TKV和囊性负荷;（ii）通过以下方法探索新的成像生物标志物： 图像纹理特征分析和模式识别技术;以及（iii）开发一种新技术， 测量肾血流量。这项研究将促进马约诊所的杰出的临床和研究 致力于改善患者护理的环境，以及马约诊所翻译PKD中心， 重点是将基础科学研究转化为ADPKD管理和治疗的改进 患者克莱恩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。除了上述目标，克莱恩博士将：1）发展强大的知识基础， 肾脏病学和放射学通过参加相关的回合，研讨会和国家会议; 2）加强 他的医学成像，生物学，生理学，遗传学，并通过课程编程的知识， 指导; 3）参加专注于赠款和出版物写作的研讨会;以及4）提交一份极具竞争力的 R 01应用扩展了本研究提案的结果。这项提议将导致巨大的 对当前分析工作流程的改进，以及对预后能力的更好理解 ADPKD的新成像生物标志物。获得这个K奖将大大促进克莱恩博士的过渡到一个 独立的研究生涯。

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