# 3-D Visualization and Prediction of Vertebral Fractures

> **NIH NIH R01** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2020 · $4,376

## Abstract

Vertebral fractures are the most common type of osteoporotic fracture, afflicting one in three women and one in
six men over the age of 50. Despite their high prevalence, sensitive and specific estimates of vertebral fracture
risk have remained elusive. The limitations of current approaches for estimating vertebral strength and fracture
risk, which rely heavily on measurement of the average bone mineral density (BMD), are widely recognized.
However, alternative methods have been lacking with respect to validation and clear advantages over the
“average BMD” approach. Our recent data address this critical gap in knowledge and translation by
demonstrating the use of clinically feasible measurements made from quantitative computed tomography
(QCT) scans to enhance predictions of vertebral failure. Using QCT-derived measures of the distribution of
bone tissue throughout the vertebra, we have found that the magnitude of the intra-vertebral heterogeneity in
BMD provides improved predictions of vertebral strength and is lower in women with vs. without vertebral
fracture. These data also indicate that multiple, characteristic spatial distributions (“patterns”) of BMD within the
vertebra can confer high bone strength, and that the associations between these patterns and strength may be
modulated by the severity of degeneration in the adjacent intervertebral discs (IVDs). We now propose to
define relationships among intra-vertebral heterogeneity in BMD, vertebral failure, and IVD degeneration in
population-based studies and complementary ex vivo studies. Aim #1 will use a case-control study design with
previously acquired QCT scans in men and women enrolled in the Framingham Heart Study (FHS)
Multidetector QCT study to test the hypothesis that decreased magnitude of heterogeneity is associated with
increased risk of prevalent fracture. Aim #2 will use an age- and sex-stratified, random sample from the FHS
QCT cohort to determine associations between the spatial distribution of BMD and IVD health, followed by ex
vivo studies that define how these associations can influence vertebral strength. Our dual hypotheses in Aim
#2 are that the spatial patterns of BMD are associated with IVD health and that vertebral strength depends on
the congruence between the spatial BMD pattern and the load distribution supplied by the IVDs. Aim #3 will
continue our clinically focused, biomechanical investigations via a novel experimental approach that provides
much-needed evaluation of the accuracy of QCT-based finite element (FE) models of vertebral failure. This
aim will test the hypothesis that the accuracy of the FE predictions is improved by incorporating clinically
obtainable assessments of IVD health. Together, these Aims are a major step towards reducing the burden of
vertebral fracture. This work partners a cost-effective study of the phenomenon of intra-vertebral heterogeneity
in a community-dwelling population with case-control and laboratory studies of the biomechani...

## Key facts

- **NIH application ID:** 10086296
- **Project number:** 3R01AR054620-11S1
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Elise F Morgan
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $4,376
- **Award type:** 3
- **Project period:** 2020-05-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10086296

## Citation

> US National Institutes of Health, RePORTER application 10086296, 3-D Visualization and Prediction of Vertebral Fractures (3R01AR054620-11S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10086296. Licensed CC0.

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