Fabbri Giorgia, Magrin Luisa, Gottardo Flaviana, Armato Leonardo, Contiero Barbara, Gianesella Matteo, Fiore Enrico
Department of Animal Medicine, Production and Health (MAPS), University of Padua, Viale dell'Università, Legnaro, PD, Italy.
Front Vet Sci. 2022 Jul 29;9:899253. doi: 10.3389/fvets.2022.899253. eCollection 2022.
Claw disorders are a relevant welfare issue in the cattle industry, fast and accurate diagnoses are essential for successful treatment and prevention. The present study aimed to develop an equation to assess the presence of solar hemorrhages from real-time ultrasound images texture analysis at slaughter. Eighty-eight hind feet were collected at the slaughterhouse from 44 Holstein male veal calves. The claws were trimmed by a veterinarian hoof-trimmer, approximately 30 min after the calves' slaughter, and classified into healthy and affected by solar hemorrhages. At the same time, ultrasound images were collected for each claw. Sole soft tissues' thickness was measured, and texture analysis was performed using MaZda software. The resulting parameters from sole soft tissues' measurements and texture analysis were screened with a stepwise linear discriminant analysis using the absence or presence (0/1) of solar hemorrhages as the dependent variable. Results from the stepwise analysis identified 9 variables (among 279) as predictors, and an equation was developed and used to predict the presence or absence of solar hemorrhages on the scanned claws by binary measure: values ≤0.5 counted as 0, while those >0.5 as 1. Validation of the equation was performed by testing predicted lesions (LESpred) against the clinically evaluated lesions (LESeval) with a confusion matrix, a ROC analysis, and a precision-recall curve. Results of the present study suggest that the equation proposed has a good potential for detecting effectively hemorrhages of the sole by ultrasound imaging texture means, and could be used to monitor unsatisfactory housing and management conditions at the farm level, and for early management intervention and prevention.
蹄病是养牛业中一个重要的福利问题，快速准确的诊断对于成功治疗和预防至关重要。本研究旨在开发一个方程，通过对屠宰时的实时超声图像进行纹理分析来评估蹄底出血的情况。在屠宰场从44头荷斯坦雄性犊牛身上采集了88只后蹄。在犊牛屠宰后约30分钟，由兽医蹄修剪师修剪蹄爪，并将其分为健康和患有蹄底出血两类。同时，为每个蹄爪采集超声图像。测量蹄底软组织厚度，并使用MaZda软件进行纹理分析。以是否存在蹄底出血（0/1）作为因变量，通过逐步线性判别分析筛选出蹄底软组织测量和纹理分析得到的参数。逐步分析结果确定了9个变量（共279个变量）作为预测因子，并开发了一个方程，用于通过二元测量预测扫描蹄爪上是否存在蹄底出血：值≤0.5计为0，而值>0.5计为1。通过使用混淆矩阵、ROC分析和精确召回曲线，将预测病变（LESpred）与临床评估病变（LESeval）进行比较，对方程进行验证。本研究结果表明，所提出的方程具有通过超声成像纹理手段有效检测蹄底出血的良好潜力，可用于监测农场层面不理想的饲养和管理条件，并用于早期管理干预和预防。
