Garry Gold - US grants

musculoskeletal system; technology /technique development; radiology; magnetic resonance imaging; biomedical resource; bioengineering /biomedical engineering;

technology /technique; musculoskeletal system; radiology; biomedical resource; bioengineering /biomedical engineering; magnetic resonance imaging; bioimaging /biomedical imaging;

Introduction: Diffusion-weighted imaging of cartilage may provide insight into normal cartilage structure, cartilage defects, and transplants. Specifically, diffusion-weighted images may demonstrate structural orientation of the collagen fibers. We have developed a method for imaging diffusion effects in articular cartilage. Materials and Methods: The diffusion-weighted imaging sequence for cartilage uses conventional Stejskal-Tanner diffusion gradients, a circular echo-planar readout trajectory, and a spiral navigator pulse to reduce motion effects. Since the T2 relaxation time of cartilage is short, echo time is kept to a minimum (51 ms) while still allowing diffusion weighting to be applied. In-plane spatial resolution is 1.3 x 1.4 mm. Nine slices can be acquired in about 5 minutes. B-values were 0, 393, and 486 s/mm^2. All imaging was done on a 1.5T GE Signa with Echospeed gradients. Results: Ten normal volunteers and one patient with a cartilage transplant have been studied. Normal articular cartilage shows an apparent diffusion coefficient (ADC) ranging from 1 to 2x10^-3 mm^2/s, which compares well with literature results obtained on cartilage/bone plug specimens. ADC values increase in normal cartilage going from the cartilage/bone interface to the joint surface. Conclusion: In-vivo diffusion-weighted imaging of articular cartilage can be performed on a conventional whole-body scanner. This type of imaging may yield new information about the orientation and type of collagen fibers present. It may be possible to follow the development and integration of chondrocyte transplants, and to distinguish fibrocartilage from hyaline cartilage at the transplant site.

urinary tract; radiology; magnetic resonance imaging; bioengineering /biomedical engineering; biomedical resource; bioimaging /biomedical imaging;

DESCRIPTION (provided by applicant): The goal of this proposal is to develop and validate a comprehensive examination of osteoarthritis. Osteoarthritis is a leading cause of chronic disability on the United States, affecting approximately 10% of those over 30 years old. Over the past 20 years, study of osteoarthritis with imaging has been primarily limited to evaluation with radiography. Magnetic Resonance Imaging (MRI), with its multi-planar capability and multiple contrast mechanisms, has emerged as the most promising non-invasive method to study osteoarthritis. The examination of osteoarthritis includes easement of articular cartilage integrity as well as other important structures. Osteoarthritis affects many joints, but is most evident in the knee. MRI has the potential to non-invasively evaluate both cartilage morphology and physiology, which is crucial to follow the effects of new osteoarthritis therapies. Current methods, however, suffer from long scan times that limit the amount of information that can be acquired in a reasonable examination time. As a result, there is a gap between what is feasible and what is currently applied in osteoarthritis studies. Our goal in this proposal is to eliminate the gap between the potential of MRI and current practice in evaluation of articular cartilage in osteoarthritis. Our group has pioneered many of the components that will be useful in the comprehensive evaluation of cartilage morphology and physiology in osteoarthritis, including rapid imaging of cartilage structure and rapid relaxation time measurements. In this proposal we will integrate those components and validate them into a comprehensive thirty-minute knee MRI exam for osteoarthritis progression.

DESCRIPTION (provided by applicant): The long-term goal of this research is to develop and validate novel imaging and biomechanical modeling techniques to identify factors that contribute to joint injury and disease in individual patients. The first aim of this research is to develop and validate a system to quantify joint kinematics in vivo using real-time magnetic resonance imaging (MRI). Real-time (MRI) provides a unique imaging modality to investigate the motion of healthy and pathological joints. The second aim is to develop an image-based modeling pipeline to estimate cartilage stress in vivo under physiological loading conditions. Finally, we will use this modeling framework to investigate the etiology of a common musculoskeletal disorder, patellofemoral (PF) pain. To achieve these aims, we will first improve the spatial and temporal resolution of the real-time MRI for musculoskeletal imaging. A rigid-body tracking technique will then be used to extract three-dimensional motion of bones from the real-time images. The accuracy of this system will be tested by tracking the motion of an MR-compatible dynamic phantom. An image-based finite element (FE) modeling pipeline will then be developed to incorporate patient-specific cartilage material properties obtained from MRI. A cadaver study will be carried out to correlate T1 and T2 relaxation times of cartilage from MRI with cartilage stiffness. Muscle forces for the FE model will be estimated using a musculoskeletal model that takes into account patient-specific muscle activation patterns. Finally, these imaging and modeling tools will be used to evaluate the mechanical etiology of PF pain. We will test a common clinical hypothesis, that PF pain is related to increased cartilage stress. We will estimate in vivo cartilage stress in a group of PF pain patients (n=40) and a group of pain-free controls (n=20) during static and dynamic squatting tasks. We will investigate a number of factors that may influence the cartilage stress, including: PF joint maltracking, contact area, joint contact forces, altered cartilage stiffness, and cartilage thickness. Musculoskeletal injuries and diseases are serious public health issues. The knee joint is particularly susceptible to injuries, which can lead to prolonged periods of inactivity, accelerated onset and progression of osteoarthritis and other health problems. The novel imaging and biomechanical modeling techniques developed in this research will be used to improve the diagnosis and treatment of a range of musculoskeletal disorders.

DESCRIPTION (provided by applicant): The long-term goal of this research is to develop and validate novel imaging and biomechanical modeling techniques to identify factors that contribute to joint injury and disease in individual patients. The first aim of this research is to develop and validate a system to quantify joint kinematics in vivo using real-time magnetic resonance imaging (MRI). Real-time (MRI) provides a unique imaging modality to investigate the motion of healthy and pathological joints. The second aim is to develop an image-based modeling pipeline to estimate cartilage stress in vivo under physiological loading conditions. Finally, we will use this modeling framework to investigate the etiology of a common musculoskeletal disorder, patellofemoral (PF) pain. To achieve these aims, we will first improve the spatial and temporal resolution of the real-time MRI for musculoskeletal imaging. A rigid-body tracking technique will then be used to extract three-dimensional motion of bones from the real-time images. The accuracy of this system will be tested by tracking the motion of an MR-compatible dynamic phantom. An image-based finite element (FE) modeling pipeline will then be developed to incorporate patient-specific cartilage material properties obtained from MRI. A cadaver study will be carried out to correlate T1 and T2 relaxation times of cartilage from MRI with cartilage stiffness. Muscle forces for the FE model will be estimated using a musculoskeletal model that takes into account patient-specific muscle activation patterns. Finally, these imaging and modeling tools will be used to evaluate the mechanical etiology of PF pain. We will test a common clinical hypothesis, that PF pain is related to increased cartilage stress. We will estimate in vivo cartilage stress in a group of PF pain patients (n=40) and a group of pain-free controls (n=20) during static and dynamic squatting tasks. We will investigate a number of factors that may influence the cartilage stress, including: PF joint maltracking, contact area, joint contact forces, altered cartilage stiffness, and cartilage thickness. Musculoskeletal injuries and diseases are serious public health issues. The knee joint is particularly susceptible to injuries, which can lead to prolonged periods of inactivity, accelerated onset and progression of osteoarthritis and other health problems. The novel imaging and biomechanical modeling techniques developed in this research will be used to improve the diagnosis and treatment of a range of musculoskeletal disorders.

Age; Anatomic; Anatomical Sciences; Anatomy; Anterior; Area; Arm; Arthritis, Degenerative; CRISP; Care, Health; Cartilage; Cartilage Matrix; Cartilage, Articular; Cartilagenous Tissue; Cell Communication and Signaling; Cell Signaling; Collagen; Computer Programs; Computer Retrieval of Information on Scientific Projects Database; Computer software; Cone; Cones (Eye); Cones (Retina); Custom; Degenerative polyarthritis; Deposit; Deposition; Detection; Early Diagnosis; Feasibility Studies; Frequencies (time pattern); Frequency; Funding; Grant; Healthcare; History; Image; Institution; Intracellular Communication and Signaling; Investigators; Knee; Knee bone; Lateral; Location; MR Imaging; MR Tomography; MRI; Magnetic Resonance Imaging; Magnetic Resonance Imaging Scan; Maps; Measurement; Measures; Medial; Medical Imaging, Magnetic Resonance / Nuclear Magnetic Resonance; Methods; Methods and Techniques; Methods, Other; NIH; NMR Imaging; NMR Tomography; Na element; National Institutes of Health; National Institutes of Health (U.S.); Nuclear Magnetic Resonance Imaging; Osteoarthritis; Osteoarthrosis; Pain; Painful; Patella; Photoreceptors, Cone; Physiologic pulse; Proteoglycan; Pulse; Pulse taking; Radio; Recording of previous events; Relaxation; Research; Research Personnel; Research Resources; Researchers; Resolution; Resources; Retinal Cone; Scanning; Science of Anatomy; Signal Transduction; Signal Transduction Systems; Signaling; Slice; Sodium; Software; Source; Structure of articular cartilage; Surface; Techniques; Thick; Thickness; Thinking; Thinking, function; Time; United States National Institutes of Health; Upper arm; Zeugmatography; anatomy; articular cartilage; biological signal transduction; computer program/software; cone cell; degenerative joint disease; drug discovery; early detection; healthy volunteer; hypertrophic arthritis; imaging; in vivo; intervention development; size; therapy development; treatment development; volunteer

DESCRIPTION (provided by applicant): The goal of this project is to improve magnetic resonance imaging (MRI) for the detection and treatment of osteoarthritis (OA). Current routine OA imaging methods only show the late changes of the disease after irreversible tissue loss has occurred. The techniques developed here will allow investigators and clinicians to track progress of the disease before tissue loss has occurred, leading to better treatments of joint injuries, faster drug discovery, and improved scientific understanding of OA progression. Relevance: MRI is widely regarded as the most sensitive method for assessing early changes due to OA. Many different MRI methods have been studied, including methods sensitive to potentially reversible changes occurring early in the disease process, but not all are practical for routine exams. Our research will develop the hardware and software necessary for the routine assessment of the earliest changes of the disease in cartilage and other joint tissues. This also will enable development and testing of treatments for this disorder. Approach: The proposed effort addresses the technical challenges to using MRI methods that are sensitive to early changes in OA. Our approach is to develop new cutting-edge methods to make MRI more sensitive to the morphological and biochemical study of OA. Specifically, we aim to (1) develop more sensitive methods of 3D imaging for quantifying the morphology of the whole knee joint, including both cartilage and other important structures, (2) develop methods for quantitative 3D imaging of cartilage glycosaminoglycan content with sodium MRI and, (3) demonstrate, in a clinical study, that our new methods are highly sensitive to early, potentially reversible changes of OA. At the end of the funding period, we will have developed and validated methods to efficiently study the progression of OA in order to improve clinical outcomes, aid development of disease-modifying therapies, and improve scientific understanding of OA. PUBLIC HEALTH RELEVANCE: Osteoarthritis is a common, debilitating disorder without an effective disease-modifying treatment. Magnetic resonance imaging (MRI) is the most accurate non-invasive method of assessing early disease changes caused by osteoarthritis. This research will develop advanced MRI methods that are sensitive to early osteoarthritic changes for improved clinical outcomes, drug development, and understanding of the disease process.

DESCRIPTION (provided by applicant): This is a new application for a Midcareer Investigator Award in Patient-Oriented Research (K24). The applicant, Dr. Garry Gold, is a physician-scientist, Associate Professor of Radiology, Bioengineering, and Orthopedics at Stanford University. Over the past 10 years, Dr. Gold has developed expertise in several advanced musculoskeletal imaging and biomechanics techniques and applied these to the study of osteoarthritis and joint diseases. This has led to his developing an independent patient- oriented research (POR) career. He has received two independent research awards from the NIH that use MR techniques to investigate the pathophysiology of musculoskeletal diseases (both are from NIBIB). Dr. Gold has a 10-year history of mentoring junior clinician scientists, postdoctoral fellows, medical students, graduate students, and undergraduates - all performing POR. In addition, Dr. Gold has active collaborations with many NIH-funded investigators in the area of musculoskeletal research and imaging. The current application requests funding (40% salary) for 5 years. This funding will guarantee that the candidate will have at least 50% protected time to conduct his ongoing research and to continue to mentor clinician scientists performing POR. This award will free time now devoted to administrative and clinical responsibilities to focus more on his research and mentoring activities over the next 5 years. In addition to working on the two ongoing NIH-funded projects, Dr. Gold will obtain additional training in advanced MR collection and analysis methods. This will allow the candidate to develop new approaches to apply to the imaging of musculoskeletal diseases. Given the outstanding resources and collaborations at Stanford, these novel projects are expected to be either renewed or to lead to new directions in orthopedic research, and significantly contribute to our scientific understanding of these disabling conditions. PUBLIC HEALTH RELEVANCE: Musculoskeletal diseases such as osteoarthritis have a tremendous impact on the individual and society as a whole. We need better imaging tools to detect these diseases at an early, treatable stage. This K24 award will permit the PI to increase his efforts in mentoring junior investigators in patient-oriented research, and to conduct research to improve detection, understanding, and treatment of patients with musculoskeletal disease.

? DESCRIPTION (provided by applicant): Osteoarthritis (OA) is the leading cause of disability worldwide. The inability of non-invasive techniques to quantify disease progression has limited understanding of the pathogenesis of OA. While numerous magnetic resonance imaging (MRI) methods have been proposed for imaging OA, analysis is often limited to a single tissue or performed using subjective scoring systems. We propose advanced three-dimensional MRI methods as well as advanced analysis tools to quantitatively study the spatial and temporal progression of OA across different tissues in the knee joint. This work will lead to a new understanding of OA pathogenesis by revealing relationships between changes in multiple tissues of the entire joint over time. This project aims to develop 3D imaging tools based on MRI to sensitively track changes of OA in all joint tissues simultaneously. Our specific aims are to (1 develop a robust ultra-short echo time based quantitative DESS method to obtain high-resolution 3D maps of apparent diffusion coefficient (ADC), T2 and T2* in multiple joint tissues, (2) Improve the signal and resolution of whole-joint sodium MRI at 3T using a novel phased array coil, (3) Develop and validate novel 3D analysis tools that will allow us to quantify changes in knee joint tissues spatially and over time and (4) Validate the ability of our protocol and analysis tools to quantitatively detect changes over time in the knees of subjects with OA of the knee. The innovation of this work lies in the development of novel imaging and analysis techniques that simultaneously offer quantitative measures of tissue integrity in cartilage, meniscus, synovium, and bone marrow. This novel data acquisition will be paired with an innovative three-dimensional analysis approach that will allow quantitative assessment of multiple joint tissues at a single time point and over time. The significance of this work is that e will be able to sensitively and quantitatively track changes of OA over time with accurate registration of multiple joint tissues. This will lead to new insights into OA pathogenesis and progression, as we will be able to relate changes in adjacent joint tissues and across time in subjects with OA.

? DESCRIPTION (provided by applicant): The joint most often implicated in lower extremity osteoarthritis (OA) is the knee, where major symptoms include pain and stiffness. Skeletal tissues are regulated by their mechanical environment and receptors within bone and soft tissue that respond to mechanical stimulation are believed to play a major role in joint pain. One potential pathway for the onset and progression of OA is due to abnormal joint kinematics, resulting in elevated joint stress and cartilage damage. Treatments that alter mechanical stresses and metabolic activity in bone may be an effective strategy to alleviate pain in these patients. However, clinicians are unable to diagnose or treat these `pathomechanics' as they lack the tools to assess weight-bearing knee function and tissue stress. The overarching goal of this research is to develop novel weight-bearing computed tomography (CT) imaging to support a quantitative measure of knee joint health that measures both morphology and mechanics of the joint. As a first step towards this goal, we will research and optimize a new, very high resolution (210 µm isotropic), C-arm CT-based imaging test that will measure cartilage deformation as a function of time with the subject standing in a fully weight-bearing position. We hypothesize that a mechanical model of the deformation-load curve will provide a sensitive and early imaging biomarker of OA status due to differences in cartilage material properties and their response to mechanical loading. We will optimize the acquisition of the deformation-time curve in ex vivo cadaver knees, and conduct a 40-subject preliminary study to demonstrate the potential sensitivity of the new imaging biomarker to distinguish between non-OA and different stages of OA progression. We believe that our new joint health test will enable testing of patient-specific treatment strategies that may slow or reverse the progression of knee OA.

Project Summary Osteoarthritis (OA) is the leading cause of disability worldwide. The inability of non-invasive techniques to quantify disease progression has limited understanding of the pathogenesis of OA. While numerous magnetic resonance imaging (MRI) methods have been proposed for imaging OA, sensitivity to bone metabolism has been limited. We propose to develop advanced three-dimensional PET-MRI methods for bone and soft tissue metabolism to study the response of the tissues in the joint to changes in knee load. This work will lead to a new understanding of OA pathogenesis by revealing relationships between changes in cartilage and bone metabolism over time. This project aims to develop PET-MRI methods to sensitively track changes of OA in response to biomechanical loading. Our specific aims are to (1) Develop accurate, reproducible and dose-optimized kinetic models of dynamic 18F-NaF PET-MRI for quantitative bilateral whole joint imaging using deep learning and advanced MR coil technology, (2) Study the relationship between resting state bone metabolism and biomechanics using PET- MRI and (3) Perform a longitudinal study to assess the response of our new imaging methods to changes in joint biomechanics from gait retraining. The innovation of this work lies in the development of novel imaging techniques that simultaneously offer quantitative measures of tissue physiology in cartilage and bone using PET-MRI. The significance of this work is that we will be able to sensitively and quantitatively track changes in bone metabolism and soft tissue microstructure due to changes in biomechanical loading in the knee joint over time. This will provide new and more sensitive imaging tools to assess the responses of the joint to biomechanical interventions to treat OA such as gait retraining, bracing, or high tibial osteotomy.

Project Summary Osteoarthritis (OA) is an enormous clinical problem and worldwide cause of disability. Development of new therapies for OA is hampered by a lack of sensitive imaging tests that respond to changes in disease status. Recently FDA and CE approved clinical knee 7T MRI has the potential to add sensitivity and specificity to advanced MRI biomarkers of OA progression. This project will compare changes seen at 3T and 7T across two different vendors systems and assess the potential for 7T MRI to improve our ability to study and develop new disease- modifying therapies. This study will enhance future studies and clinical exams at 7T and can be used to improve routine 3T MRI though machine learning reconstruction and enhanced understanding of OA disease mechanisms. Understanding the relative strengths of 3T and 7T MRI in this important clinical application is critical to developing new disease-modifying treatments for patients with OA.