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Enhancing hip fracture risk prediction by statistical modeling and texture analysis on DXA images.
Medical Engineering & Physics ( IF 2.2 ) Pub Date : 2020-02-10 , DOI: 10.1016/j.medengphy.2020.01.015
Fatemeh Jazinizadeh 1 , Cheryl E Quenneville 2
Affiliation  

Each year in the US more than 300,000 older adults suffer from hip fractures. While protective measures exist, identification of those at greatest risk by DXA scanning has proved inadequate. This study proposed a new technique to enhance hip fracture risk prediction by accounting for many contributing factors to the strength of the proximal femur. Twenty-two isolated cadaveric femurs were DXA scanned, 16 of which had been mechanically tested to failure. A function consisting of the calculated modes from the statistical shape and appearance modeling (to consider the shape and BMD distribution), homogeneity index (representing trabecular quality), BMD, age and sex of the donor was created in a training set and used to predict the fracture load in a test group. To classify patients as "high risk" or "low risk", fracture load thresholds were investigated. Hip fracture load estimation was significantly enhanced using the new technique in comparison to using t-score or BMD alone (average R² of 0.68, 0.32, and 0.50, respectively) (P < 0.05). Using a fracture cut-off of 3400 N correctly predicted risk in 94% of specimens, a substantial improvement over t-score classification (38%). Ultimately, by identifying patients at high risk more accurately, devastating hip fractures can be prevented through applying protective measures.

中文翻译:

通过对DXA图像进行统计建模和纹理分析来增强髋部骨折风险的预测。

在美国,每年有30万以上的成年人患有髋部骨折。尽管存在保护措施,但通过DXA扫描识别风险最大的人已被证明是不充分的。这项研究提出了一种新技术,通过考虑许多影响股骨近端强度的因素来提高髋部骨折风险的预测。DXA扫描了22个孤立的尸体股骨,其中16个已经过机械测试,以检查失败。在训练集中创建了一个功能,该功能由统计形状和外观模型(考虑形状和BMD分布),均一性指标(代表骨小梁质量),BMD,年龄和性别的计算模式组成,并用于预测测试组的骨折负荷。要将患者分类为“高风险”或“低风险”,研究了断裂载荷阈值。与单独使用t评分或BMD相比,使用新技术可显着提高髋部骨折负荷估算(平均R²分别为0.68、0.32和0.50)(P <0.05)。使用3400 N的裂缝临界值可以正确预测94%的标本中的风险,与t评分分类(38%)相比有显着改善。最终,通过更准确地识别高危患者,可以通过采取防护措施来预防破坏性的髋部骨折。与t分数分类(38%)相比有实质性的改进。最终,通过更准确地识别高危患者,可以通过采取防护措施来预防破坏性的髋部骨折。与t分数分类(38%)相比有实质性的改进。最终,通过更准确地识别高危患者,可以通过采取保护性措施来预防破坏性的髋部骨折。
更新日期:2020-02-10
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