Goodheart Jacklyn R, Cleary Richard J, Damron Timothy A, Mann Kenneth A
Department of Orthopedic Surgery, SUNY Upstate Medical University, Syracuse, New York.
Mathematics & Science Division, Babson College, Babson Park, Massachusetts.
J Orthop Res. 2015 Aug;33(8):1226-34. doi: 10.1002/jor.22887. Epub 2015 May 21.
Predicting fracture risk for patients with metastatic femoral lesions remains an important clinical problem. Mirels' criterion remains the most formalized radiographic scoring system with good sensitivity (correctly identifying clinical fractures) but relatively poor specificity (correctly identify cases that do not fracture). A series of patients with metastatic femoral lesions had Computed Tomography (CT) scans, were followed prospectively for 4 months, and categorized into fracture (n = 5), non-fracture (n = 28), or stabilized (n = 11) groups. CT based-Finite Element (FE) modeling was used to predict fracture for these cases using axial compression (AC), level walking (LW), and aggressive stair ascent (ASA) loading conditions. The FE predicted fracture force was greater for the non-fracture compared to the fracture group for all loading cases. The ability of the FE models to predict fracture cases (sensitivity) was similar for the groups (Mirels, AC, LW: 80%, ASA: 100%). The ability of the models to correctly predict the non-fracture cases (specificity) was improved for AC (71%) and LW (86%) loading conditions, when compared to Mirels specificity (43%), but poorer for the ASA (21%) conditions. The results suggest that FE models that assess fracture risk using LW conditions can improve fracture prediction over Mirels scoring in a clinical population.
预测股骨转移瘤患者的骨折风险仍然是一个重要的临床问题。米雷尔斯标准仍然是最形式化的影像学评分系统,具有良好的敏感性(正确识别临床骨折),但特异性相对较差(正确识别未发生骨折的病例)。对一系列股骨转移瘤患者进行了计算机断层扫描(CT),并进行了为期4个月的前瞻性随访,将其分为骨折组(n = 5)、非骨折组(n = 28)或稳定组(n = 11)。基于CT的有限元(FE)建模用于在轴向压缩(AC)、平路行走(LW)和上楼梯(ASA)等加载条件下预测这些病例的骨折情况。在所有加载情况下,FE预测的非骨折组骨折力均高于骨折组。FE模型预测骨折病例的能力(敏感性)在各分组中相似(米雷尔斯标准、AC、LW:80%,ASA:100%)。与米雷尔斯标准的特异性(43%)相比,AC(71%)和平路行走(LW,86%)加载条件下模型正确预测非骨折病例的能力(特异性)有所提高,但在上楼梯(ASA,21%)条件下则较差。结果表明,在临床人群中,使用平路行走条件评估骨折风险的FE模型比米雷尔斯评分能更好地预测骨折。