The goal of this study is to use a novel magnetic resonance imaging (MRI) test to determine if assessment of proximal femur microarchitecture has added value as a biomarker of bone quality and hip fracture risk. Hip or proximal femur fracture is the most devastating type of osteoporotic fracture, affecting 300,000 Americans and accounting for $12 billion in healthcare costs annually. There is a critical need for an improved method to assess proximal femur bone quality in vivo. 54% of women who suffer hip fractures are misclassified by dual- energy x-ray absorptiometry as not osteoporotic. And though the FRAX calculator, clinical factors (e.g. fall risk, immobility), and macrostructural hip assessment have proven highly valuable, the detection of subjects at risk for hip fracture remains a challenge. Bone microarchitecture, a key determinant of bone strength included in the disease definition of osteoporosis, has never been studied in the proximal femur in vivo because of a lack of means to assess it. We have achieved a technical breakthrough: using a novel 26 element receive detector (which boosts signal-to-noise ratio), we have successfully imaged individual trabeculae composing proximal femur microarchitecture on a clinical 3 T MRI scanner in vivo. We will now apply this tool in a clinical study.
Our specific aims (SA) are to: 1) Determine how proximal femur microarchitecture changes with aging in post- menopausal women without fracture (n = 100). We hypothesize that higher age will correlate with lower femoral neck cortical thickness, trabecular thickness, number, connectivity, plate-to-rod ratio, and lower whole proximal femur stiffness and ultimate strength. 2) Determine how proximal femur microarchitecture is deranged in post-menopausal women with femoral neck fracture (n = 100). We hypothesize that fracture cases will demonstrate lower femoral neck cortical thickness, trabecular thickness, number, connectivity, plate-to-rod ratio, and lower whole proximal femur stiffness and ultimate strength compared to SA1 controls. 3) Determine the added value of microarchitecture, beyond FRAX/known clinical risk factors, for classifying subjects without and with hip fracture. Our main hypothesis is that adding microarchitecture to a baseline logistic regression model containing FRAX and clinical risk factors will improve model accuracy for classification of fracture status. Our secondary hypothesis is that a model of microarchitecture, FRAX, and clinical risk factors will be more accurate for classification of fracture status than a model of macrostructure, FRAX, and clinical risk factors. If successful, this study will: 1) provid new insight into the pathogenesis and means for prevention of hip fracture; and 2) determine whether microarchitectural assessment allows detection of high-risk hip fracture patients who currently escape detection. If validated in a longitudinal study, this MRI test could be used as an additional research/clinical care tool to determine whether an individual should or should not receive therapy, or be suitable for clinical trial enrollment. It could also be used as a novel too to monitor the effects of different interventions on proximal femur microarchitecture and strength.

Public Health Relevance

The detection of subjects at risk for osteoporotic hip fracture remains a challenge. Our goal is to apply a new, high-resolution MRI test to determine: 1) how deterioration in proximal femur microarchitecture contributes to hip fracture risk and 2) whether assessment of proximal femur microarchitecture has added value, beyond current methods, for the detection of subjects with poor proximal femur bone quality in need of osteoporosis therapy.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR066008-04
Application #
9325447
Study Section
Skeletal Biology Structure and Regeneration Study Section (SBSR)
Program Officer
Lester, Gayle E
Project Start
2014-09-01
Project End
2019-08-31
Budget Start
2017-09-01
Budget End
2018-08-31
Support Year
4
Fiscal Year
2017
Total Cost
Indirect Cost
Name
New York University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016
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