Ragetly Chantal A, Griffon Dominique J, Thomas Jason E, Mostafa Ayman A, Schaeffer David J, Pijanowski Gerald J, Hsiao-Wecksler Elizabeth T
Small Animal Clinic, Department of Small Animal Surgery, College of Veterinary Medicine, University of Illinois, Urbana, IL 61802, USA.
Am J Vet Res. 2008 Sep;69(9):1188-96. doi: 10.2460/ajvr.69.9.1188.
To determine mass, center of mass (COM), and moment of inertia (ie, body segment parameters [BSPs]) of hind limb segments by use of a noninvasive method based on computerized tomography (CT) in Labrador Retrievers with and without cranial cruciate ligament (CCL) disease and to provide regression equations to estimate BSPs of normal, CCL-deficient, and contralateral hind limbs.
14 clinically normal and 10 CCL-deficient Labrador Retrievers.
Bone, muscle, and fat areas were identified via CT. Mass, COM, and moment of inertia were determined on the basis of tissue densities in the thigh, crus, and foot segments. Regression models were developed to determine predictive equations to estimate BSP on the basis of simple morphometric measurements.
The thigh and crus of CCL-deficient limbs weighed less than in contralateral segments. Thighs weighed less in CCL-deficient than in normal limbs. The thigh moment of inertia was less in CCL-deficient than in contralateral limbs. The crural COM was located more distally in normal limbs, compared with other limbs. Predictive equations to estimate BSP varied by parameter, body segment, and limb status.
BSPs of the thigh and crus varied with segment and status of the hind limb in Labrador Retrievers with or without CCL disease. Equations to estimate BSP on the basis of simple morphometric measurements were proposed, providing a basis for nonterminal studies of inverse dynamics of the hind limbs in Labrador Retrievers. This approach may offer new strategies to investigate the pathogenesis of nontraumatic joint diseases.
采用基于计算机断层扫描（CT）的非侵入性方法，测定患有和未患有颅交叉韧带（CCL）疾病的拉布拉多犬后肢各节段的质量、质心（COM）和转动惯量（即身体节段参数[BSPs]），并提供回归方程以估计正常、CCL缺陷和对侧后肢的BSPs。
14只临床正常的拉布拉多犬和10只患有CCL疾病的拉布拉多犬。
通过CT识别骨骼、肌肉和脂肪区域。根据大腿、小腿和足部节段的组织密度测定质量、质心和转动惯量。建立回归模型，以确定基于简单形态测量来估计BSP的预测方程。
CCL缺陷肢体的大腿和小腿重量比其对侧节段轻。CCL缺陷肢体的大腿重量比正常肢体轻。CCL缺陷肢体的大腿转动惯量比其对侧肢体小。与其他肢体相比，正常肢体的小腿质心位置更靠远端。估计BSP的预测方程因参数、身体节段和肢体状态而异。
在患有或未患有CCL疾病的拉布拉多犬中，大腿和小腿的BSPs因后肢节段和状态而异。提出了基于简单形态测量来估计BSP的方程，为拉布拉多犬后肢逆动力学的非终末研究提供了基础。这种方法可能为研究非创伤性关节疾病的发病机制提供新策略。
