Statistical shape modeling describes variation in tibia and femur surface geometry between Control and Incidence groups from the osteoarthritis initiative database.
Statistical shape modeling describes variation in tibia and femur surface geometry between Control and Incidence groups from the osteoarthritis initiative database.
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DOI：
10.1016/j.jbiomech.2010.02.015
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发表时间：
2010-06-18
影响因子：
2.4
通讯作者：
Nicolella, Daniel P.
中科院分区：
文献类型：
--
作者：
Bredbenner, Todd L.;Eliason, Travis D.;Potter, Ryan S.;Mason, Robert L.;Havill, Lorena M.;Nicolella, Daniel P.
我们假设膝关节软骨下骨表面几何形状的变异性将区分有骨关节炎（OA）风险和无骨关节炎（OA）风险的患者，并建议统计形状模型（SSM）方法构成开发预测 OA 发病的诊断工具的基础。使用来自骨关节炎倡议 (OAI) 的临床膝关节 MRI 数据子集，本研究的目的是 (1) 利用 SSM 紧凑而有效地描述膝关节软骨下骨表面几何形状的变异性，以及 (2) 确定 SSM 和刚体变换的功效，以区分预计不会发展为骨关节炎的患者（即对照组）和临床骨关节炎患者 OA 的危险因素（即发病组）。尽管膝关节排列测量的差异并不具有统计学意义，但组间股骨和胫骨表面几何形状的定量差异得到了证实，这表明个体骨骼几何形状的变异性可能在确定关节空间几何形状和力学方面发挥更大的作用。 SSM 提供了一种明确描述完整关节表面几何形状的方法，并允许统计证明健康受试者和具有发展或现有 OA 体征临床风险的受试者之间关节表面几何形状和关节一致性的复杂空间变化。
We hypothesize that variability in knee subchondral bone surface geometry will differentiate between patients at risk and those not at risk for developing osteoarthritis (OA) and suggest that statistical shape modeling (SSM) methods form the basis for developing a diagnostic tool for predicting the onset of OA. Using a subset of clinical knee MRI data from the osteoarthritis initiative (OAI), the objectives of this study were to (1) utilize SSM to compactly and efficiently describe variability in knee subchondral bone surface geometry and (2) determine the efficacy of SSM and rigid body transformations to distinguish between patients who are not expected to develop osteoarthritis (i.e. Control group) and those with clinical risk factors for OA (i.e. Incidence group). Quantitative differences in femur and tibia surface geometry were demonstrated between groups, although differences in knee joint alignment measures were not statistically significant, suggesting that variability in individual bone geometry may play a greater role in determining joint space geometry and mechanics. SSM provides a means of explicitly describing complete articular surface geometry and allows the complex spatial variation in joint surface geometry and joint congruence between healthy subjects and those with clinical risk of developing or existing signs of OA to be statistically demonstrated.
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影响因子：
5.3
作者：
Hashemi, Javad;Chandrashekar, Naveen;Dabezies, Eugene
通讯作者：
Dabezies, Eugene
影响因子：
2.8
作者：
KADABA, MP;RAMAKRISHNAN, HK;COCHRAN, GVB
通讯作者：
COCHRAN, GVB
影响因子：
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作者：
Hunter, DJ;Zhang, YQ;Felson, DT
通讯作者：
Felson, DT
影响因子：
5.7
作者：
Ferrarini, Luca;Palm, Walter M.;Admiraal-Behloul, Faiza
通讯作者：
Admiraal-Behloul, Faiza
影响因子：
4.7
作者：
Dornaika, Fadi;Ahlberg, Jorgen
通讯作者：
Ahlberg, Jorgen