The proposed research aims to advance innovative methods for the evaluation of patients who have sustained comminuted intra-articular fractures. The risk of post-traumatic osteoarthritis (PTOA), a late complication with substantial lifelong morbidity and disability, is related to the intensity of the joint trauma accompanying these fractures. Current methods for assessing the severity of joint injury are limited, irreproducible, and generally qualitative, hindering the evaluation of new treatments aimed at avoiding PTOA. Until the severity of the initial injury can be objectively measured, it will remain a substantial confounder hindering meaningful investigation. A global objective of the proposed work is to establish physically-grounded, non-invasive techniques to quantify intra-articular fracture severity. CT-derived measures of the mechanical energy expended in a given fracture provide an index of the mechanical insult to the joint. They do not account for localization of fragmentation, or fragment displacement and dispersal, critical factors reflecting the risk of PTOA, as this requires presently unavailable knowledge of the positions that the dispersed fragments originally occupied in the intact bone. Deducing this information entails, in effect, solving a three-dimensional (3-D) puzzle, a task for which suitable computational algorithms have recently begun to emerge. This new capability holds the potential to greatly advance the manner in which comminuted intra-articular fractures are assessed, facilitating investigation of new treatments (primarily biologic) aimed at restoring the health of at-risk articular tissues.
Two specific aims will be pursued to advance 3-D puzzle solving methods for this use.
Specific Aim 1 is to generate representative fracture fragmentation in test specimens machined from a bone surrogate material, and encased in a soft tissue surrogate. Fragment volumetric and surface data will be obtained from CT scans (intended clinical use), with fragments in their spontaneously-displaced/interspersed positions, and duplicate surface data will be obtained from ensuing laser scans of individual fragments (gold standard). Working from these data, the accuracy of fracture fragment segmentation, and 3-D puzzle solution accuracy in reconstructing the known pre- fracture specimen geometry, will be determined.
Specific Aim 2 is to obtain 3-D puzzle solutions, and associated fracture severity indices, working from an existing series of tibial plafond fracture cases for which three to five year outcome data will be available. Fracture severity metrics will be correlated with a clinical rank ordering of severity, and in turn with the clinical incidence of PTOA, and with functional outcome measures. ? ?

Public Health Relevance

Patients sustaining severe limb trauma in which bones are highly fragmented and the fracture extends into an articular joint such as the ankle or knee, have a generally poor prognosis, with eventual arthritis as a common disabling outcome. Lacking objective measures of fracture severity, surgeons presently rely upon subjective impressions to guide treatment of these patients, hindering progress toward forestalling post-traumatic arthritis. A 3-D puzzle solving approach yields new, objective measures of articular fracture severity, providing a novel framework for statistically robust clinical/translational studies of new treatments to reduce the risk of post-traumatic arthritis. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21AR054015-01A2
Application #
7529183
Study Section
Musculoskeletal Tissue Engineering Study Section (MTE)
Program Officer
Lester, Gayle E
Project Start
2008-07-01
Project End
2010-03-31
Budget Start
2008-07-01
Budget End
2009-03-31
Support Year
1
Fiscal Year
2008
Total Cost
$201,537
Indirect Cost
Name
University of Iowa
Department
Orthopedics
Type
Schools of Medicine
DUNS #
062761671
City
Iowa City
State
IA
Country
United States
Zip Code
52242
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