Collins Simon N, Dyson Sue J, Murray Rachel C, Newton J Richard, Burden Faith, Trawford Andrew F
Centre for Equine Studies, Animal Health Trust, Lanwades Park, Newmarket, Suffolk, CB8 7UU, England.
Am J Vet Res. 2012 Aug;73(8):1207-18. doi: 10.2460/ajvr.73.8.1207.
To establish and validate an objective method of radiographic diagnosis of anatomic changes in laminitic forefeet of donkeys on the basis of data from a comprehensive series of radiographic measurements.
85 donkeys with and 85 without forelimb laminitis for baseline data determination; a cohort of 44 donkeys with and 18 without forelimb laminitis was used for validation analyses.
For each donkey, lateromedial radiographic views of 1 weight-bearing forelimb were obtained; images from 11 laminitic and 2 nonlaminitic donkeys were excluded (motion artifact) from baseline data determination. Data from an a priori selection of 19 measurements of anatomic features of laminitic and nonlaminitic donkey feet were analyzed by use of a novel application of multivariate statistical techniques. The resultant diagnostic models were validated in a blinded manner with data from the separate cohort of laminitic and nonlaminitic donkeys.
Data were modeled, and robust statistical rules were established for the diagnosis of anatomic changes within laminitic donkey forefeet. Component 1 scores ≤ -3.5 were indicative of extreme anatomic change, and scores from -2.0 to 0.0 denoted modest change. Nonlaminitic donkeys with a score from 0.5 to 1.0 should be considered as at risk for laminitis.
Results indicated that the radiographic procedures evaluated can be used for the identification, assessment, and monitoring of anatomic changes associated with laminitis. Screening assessments by use of this method may enable early detection of mild anatomic change and identification of at-risk donkeys.
基于一系列全面的X线测量数据，建立并验证一种用于诊断驴蹄叶炎前蹄解剖学变化的客观X线诊断方法。
85头患有前肢蹄叶炎和85头未患前肢蹄叶炎的驴用于确定基线数据；44头患有前肢蹄叶炎和18头未患前肢蹄叶炎的驴组成的队列用于验证分析。
对每头驴，获取1个负重前肢的内外侧X线片；在确定基线数据时，排除11头蹄叶炎驴和2头非蹄叶炎驴的图像（运动伪影）。通过使用多元统计技术的新应用，分析从蹄叶炎和非蹄叶炎驴蹄的解剖特征中预先选择的19项测量数据。所得诊断模型用来自蹄叶炎和非蹄叶炎驴的单独队列的数据进行盲法验证。
对数据进行建模，并建立了用于诊断蹄叶炎驴前蹄解剖学变化的稳健统计规则。成分1得分≤ -3.5表示解剖学变化极端，得分在-2.0至0.0之间表示变化适中。得分在0.5至1.0之间的非蹄叶炎驴应被视为有患蹄叶炎的风险。
结果表明，所评估的X线检查程序可用于识别、评估和监测与蹄叶炎相关的解剖学变化。使用该方法进行筛查评估可早期发现轻度解剖学变化并识别有风险的驴。
