DOI: 10.5061/dryad.8w9ghx3sk
title: Data from: Subchondral bone fatigue injury in the parasagittal condylar grooves of the third metacarpal bone in Thoroughbred racehorses elevates site-specific strain concentration

description: Condylar stress fracture of the distal end of the third
 metacarpal/metatarsal (MC3/MT3) bones is a major cause of Thoroughbred
 racehorse injury and euthanasia worldwide. Functional adaptation to
 exercise and fatigue damage lead to structural changes in the subchondral
 bone that include increased modeling (resulting in sclerotic bone tissue)
 and  targeted remodeling repair (resulting in focal resorption
 spaces in the parasagittal groove). Whether these focal structural
 changes, as detectable by standing computed  tomography (sCT),
 lead to elevated strain at the common site of condylar stress fracture has
 not been demonstrated. Therefore, the goal of the present study was to
 compare full-field three-dimensional (3D) strain on the distopalmar aspect
 of MC3 bone specimens with and without focal subchondral bone injury
 (SBI). Thirteen forelimb specimens were collected from racing
 Thoroughbreds for mechanical testing ex vivo and underwent sCT.
 Subsequently, full-field displacement and strain at the joint surface were
 determined using stereo digital image correlation. Strain concentration
 was observed in the parasagittal groove (PSG) of the loaded
 condyles, and those with SBI in the PSG showed higher strain
 rates in this region than control bones. PSG strain rate in condyles with
 PSG SBI was more sensitive to CT density distribution in
 comparison with condyles with no sCT-detectable injury. Findings
 from this study help to interpret structural changes in the subchondral
 bone due to fatigue damage and to assess risk of incipient stress
 fracture in a patient-specific manner.
description: Please refer to the linked research article for detailed
 explanation of the methods.
description: # Subchondral bone fatigue injury in the parasagittal condylar grooves of
 the third metacarpal bone in Thoroughbred racehorses elevates
 site-specific strain concentration
 [https://doi.org/10.5061/dryad.8w9ghx3sk](https://doi.org/10.5061/dryad.8w9ghx3sk) This dataset contains raw and processed experimental data from mechanical testing of condyles of MC3 bone of Thoroughbred racehorses, and their CT densities acquired with Equina Asto CT. For best results, download all the files, scripts, and zipped folders (unzip them after) and put them all in the same directory. ## Description of the data and file structure 1- Raw experimental data are organized as follows: Name of folders that contain the unprocessed raw experimental data begins with *rawData_* and continues with the condyle ID. For example: *rawData_POD2*, *rawData_CTRL5*, etc. These folders include images of the calibration object that is a grid of 2-mm spaced dots attached to a 1.5 inch (38.1 mm) diameter cylinder, testing videos from the paired cameras recorded at 30 frames per second, and force-displacement transient data from the testing machine with units of N (for force) and mm (for displacement). Please note that all units are included in the MTS data files. In each of these folders the data is organized in separate folders for force-displacement-time data from the mechanical testing system (*MTS*), videos for all force- and displacement-controlled tests and calibration image for camera-1 (*Pi1*) and camera-2 (*Pi2*). Post-failure images are in the root of each folder. 2- Processed data are organized as follows: Name of folders that contain the processed data with MultiDIC v.1.1.0 in MATLAB R2022a ([https://github.com/MultiDIC/MultiDIC](https://github.com/MultiDIC/MultiDIC)) starts with the specimen ID, the specific loading protocol, and the date the test was performed. For example: *92f2_LF_MC_5kN_2022_Nov10.* Specimen ID for all condyles can be found in **specimenID.txt**. In each of these folders the data is organized as follows (please note that all displacements are in mm): * *2D_DIC*: ROI mask and 2D DIC results (output of STEP2 of MultiDIC) processed with subset size of 25 pixels and grid density of 12 pixels * *3D_DIC*: 3D reconstructed results (output of STEP3 of MultiDIC) * *3D_postProc*: processed 3D results (output of STEP4 of MultiDIC) * *calibObj*: calibration images from the camera pair and a script that rotates them as needed * *DLT*: output of STEP1 of MultiDIC * *frame extraction*: videos from the camera pair, force-displacement-time data from MTS, and custom scripts to pull frames from the valley- to peak-displacement in the last loading cycle (the pulled frame numbers can be found in the scripts), and one script to plot the MTS force-displacement-time data. * *Speckles_lastVtoP*: images from the camera pair for every other frame in the last valley to peak displacement (76 frames from each camera) * *subset25-12*: saved results of DIC analysis with subset radius of 25 pixels and gradient density of 12 pixels (apart) within the subset. 3D DIC results can be reproduced by either processing the raw data, or by loading the processed data in the *3D_postProc* folder by running the **plot3DDICPPresults.m** in the *lib_MultiDIC* folder of the MultiDIC package ([https://github.com/MultiDIC/MultiDIC](https://github.com/MultiDIC/MultiDIC)). 3- CT density data of all tested condyles can be found in the folder *voxel_density_data*. 4- All figures and results shown in the linked research article can be reproduced by running **main_ExpDataPP.m** in MATLAB (by either loading the *.mat* files for saving time or by allowing the script to read all the results from scratch), that requires a few other scripts and functions to work: * **get_all_testing_inputs.m** All experiments with the specimen ID and their group information and the locations of where the strain was pulled from are included in this script, in addition to the DIC correlation cutoff. * **parasagROI_filter.m** This is a function that filters strain data and keep only those that are within the specified spatial location range. * **corrCoeff_filter.m** This is a function that filters strain data and keep only those that are within the specified correlation coefficient range. * **readDICdata.m** This is a function that reads the MultiDIC output data from all experiments and prepares them for post-processing. The unit for strain is changed to % here and all the post-processed strain in the statistical analyzes are reported in %. * **readHUdata.m** (inside the folder *voxel_density_data*) This is a function that reads the CT density data for all specimens. The unit for CT density is HU in the "**_grayvalues.txt" files. * **HU_freq_graph.m** (inside the folder *voxel_density_data*) This is a script that plots CT density distributions (probability density function) for all specimens. ## Code/Software All scripts and functions were developed and can be run with MATLAB R2022a and R2023a.