Automated Assessment of Pelvic Longitudinal Rotation Using Computer Vision in Canine Hip Dysplasia Screening

Canine hip dysplasia (CHD) screening relies on accurate positioning in the ventrodorsal hip extended (VDHE) view, as even mild pelvic rotation can affect CHD scoring and impact breeding decisions. This study aimed to assess the association between pelvic rotation and asymmetry in obturator foramina areas (AOFAs) and to develop a computer vision model for automated AOFA measurement. In the first part, 203 radiographs were analyzed to examine the relationship between pelvic rotation, assessed through asymmetry in iliac wing and obturator foramina widths (AOFWs), and AOFAs. A significant association was found between pelvic rotation and AOFA, with AOFW showing a stronger correlation (<i>R</i><sup>2</sup> = 0.92, <i>p</i> < 0.01). AOFW rotation values were categorized into minimal (n = 71), moderate (n = 41), marked (n = 37), and extreme (n = 54) groups, corresponding to mean AOFA ± standard deviation values of 33.28 ± 27.25, 54.73 ± 27.98, 85.85 ± 41.31, and 160.68 ± 64.20 mm<sup>2</sup>, respectively. ANOVA and post hoc testing confirmed significant differences in AOFA across these groups (<i>p</i> < 0.01). In part two, the dataset was expanded to 312 images to develop the automated AOFA model, with 80% allocated for training, 10% for validation, and 10% for testing. On the 32 test images, the model achieved high segmentation accuracy (Dice score = 0.96; Intersection over Union = 0.93), closely aligning with examiner measurements. Paired <i>t</i>-tests indicated no significant differences between the examiner and model's outputs (<i>p</i> > 0.05), though the Bland-Altman analysis identified occasional discrepancies. The model demonstrated excellent reliability (ICC = 0.99) with a standard error of 17.18 mm<sup>2</sup>. A threshold of 50.46 mm<sup>2</sup> enabled effective differentiation between acceptable and excessive pelvic rotation. With additional training data, further improvements in precision are expected, enhancing the model's clinical utility.

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Publication Details

Journal
Veterinary Sciences
Published
2024-12-07
DOI
https://doi.org/10.3390/vetsci11120630
Citations
2
Primary Topic
Hip disorders and treatments
Type
article
Field-Weighted Citation Impact
1.15

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article

Automated Assessment of Pelvic Longitudinal Rotation Using Computer Vision in Canine Hip Dysplasia Screening

Manuel Ferreira, Sofia Alves‐Pimenta, Pedro Franco-Gonçalo, Bruno Colaço et al.
2 citations
Veterinary Sciences
Hip disorders and treatments
1.15
article

Automated Assessment of Pelvic Longitudinal Rotation Using Computer Vision in Canine Hip Dysplasia Screening

Manuel Ferreira, Sofia Alves‐Pimenta, Pedro Franco-Gonçalo, Bruno Colaço, Pedro Leite, Mário Ginja, Fintan J. McEvoy, Lio Gonçalves, Vítor Filipe
article en
2 citations

Abstract

Canine hip dysplasia (CHD) screening relies on accurate positioning in the ventrodorsal hip extended (VDHE) view, as even mild pelvic rotation can affect CHD scoring and impact breeding decisions. This study aimed to assess the association between pelvic rotation and asymmetry in obturator foramina areas (AOFAs) and to develop a computer vision model for automated AOFA measurement. In the first part, 203 radiographs were analyzed to examine the relationship between pelvic rotation, assessed through asymmetry in iliac wing and obturator foramina widths (AOFWs), and AOFAs. A significant association was found between pelvic rotation and AOFA, with AOFW showing a stronger correlation (<i>R</i><sup>2</sup> = 0.92, <i>p</i> < 0.01). AOFW rotation values were categorized into minimal (n = 71), moderate (n = 41), marked (n = 37), and extreme (n = 54) groups, corresponding to mean AOFA ± standard deviation values of 33.28 ± 27.25, 54.73 ± 27.98, 85.85 ± 41.31, and 160.68 ± 64.20 mm<sup>2</sup>, respectively. ANOVA and post hoc testing confirmed significant differences in AOFA across these groups (<i>p</i> < 0.01). In part two, the dataset was expanded to 312 images to develop the automated AOFA model, with 80% allocated for training, 10% for validation, and 10% for testing. On the 32 test images, the model achieved high segmentation accuracy (Dice score = 0.96; Intersection over Union = 0.93), closely aligning with examiner measurements. Paired <i>t</i>-tests indicated no significant differences between the examiner and model's outputs (<i>p</i> > 0.05), though the Bland-Altman analysis identified occasional discrepancies. The model demonstrated excellent reliability (ICC = 0.99) with a standard error of 17.18 mm<sup>2</sup>. A threshold of 50.46 mm<sup>2</sup> enabled effective differentiation between acceptable and excessive pelvic rotation. With additional training data, further improvements in precision are expected, enhancing the model's clinical utility.

Veterinary SciencesVol. 11(12)
University of Copenhagen (DK), University of Trás-os-Montes and Alto Douro (PT), INESC TEC (PT)
Universidade de Trás-os-Montes e Alto Douro, Fundação para a Ciência e a Tecnologia, European Regional Development Fund
Openalex Percentile: Top 19%
Hip disorders and treatments
1.15
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