A radiomics platform for computing imaging features from µCT images of Thoroughbred racehorse proximal sesamoid bones: Benchmark performance and evaluation. (7th August 2020)

• Record Type: Journal Article
• Authors: Basran, Parminder S.; Gao, Jonathan; Palmer, Scott; Reesink, Heidi L.
• Is Part Of: Equine veterinary journal. Volume 53:Number 2(2021)
• Page Start: 277
• Page End: 286
• Publication Date: 2020-08-07
• Subjects: horse -- CT imaging -- density -- epidemiology -- exercise -- morphology; Horses -- Diseases -- Periodicals; 636.108905
• DOI: 10.1111/evj.13321
• Languages: English
• ISSNs: 0425-1644

Abstract

Abstract: Background: Proximal sesamoid bone (PSB) fractures are the most common fatal musculoskeletal injury in North American racehorses. Computed tomography has the potential to detect morphological changes in bone structure but can be challenging to analyse reliably and quantitatively. Objectives: To develop a radiomics platform that allows the comparison of features from micro‐CTs (µCT) of PSBs in horses that sustained catastrophic fractures with horses that did not. To compare features calculated with a radiomics approach with features calculated from a previously published study that used quantitative µCT in the same specimens. Study design: Retrospective study of cadaver specimens of µCT images of PSBs using prospectively applied radiomics. Methods: Radiomics features were computed on standardised CT datasets to benchmark the software. Features from µCT images of PSBs from eight horses that sustained PSB fracture and eight controls were computed using the contralateral, intact forelimb from horses sustaining PSB fracture (cases, n = 19) and all available forelimbs for controls (n = 30). Two‐hundred and fifteen radiomic features were calculated, and similar or comparable features were compared with those reported in a previous study that used the same specimens. Results: Morphologic features computed with the radiomics approach, such as volume, minor axis dimensions and anisotropy were highly correlated with previously published data. A high number of imperceptible radiomic features, such as entropy, coarseness and histogram features were also found to be significantly different ( P < .01). The extent of the differences in image features for the cases and controls PSBs depends on radiomic calculation settings. Main limitations: Only datasets obtained from cadaver specimens were included in the study. Conclusions: A radiomics approach for analysing µCT images of PSBs was able to identify and reproduce differences in image features in cases and controls. Furthermore, radiomics revealed many more imperceptible image features between cases and control PSBs.