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一种基于肱骨近端三维模型的头状骨容积-形态学评估的新分类方法,用于评估肱骨近端骨折。

A new classification of impacted proximal humerus fractures based on the morpho-volumetric evaluation of humeral head bone loss with a 3D model.

机构信息

Department of Orthopedic Surgery, Pineta Grande Hospital, Caserta, Italy.

Department of Orthopedic Surgery, Pineta Grande Hospital, Caserta, Italy.

出版信息

J Shoulder Elbow Surg. 2020 Oct;29(10):e374-e385. doi: 10.1016/j.jse.2020.02.022. Epub 2020 Jun 9.

Abstract

BACKGROUND

This study aimed to classify the pathomorphology of impacted proximal humeral fractures according to the control volume theory, with the intention to introduce a severity index to support surgeons in decision making.

METHODS

In total, 50 proximal humeral fractures were randomly selected from 200 medical records of adult patients treated from 2009 to 2016. Four nonindependent observers used 2 different imaging modalities (computed tomography scans plus volume rendering; 3D model) to test the classification reliability. A fracture classification system was created according to the control volume theory to provide simple and understandable patterns that would help surgeons make quick assessments. The impacted fractures table was generated based on an evaluation of the calcar condition, determined by the impairment of a defined volumetric area under the cephalic cup and the humeral head malposition. In addition to the main fracture pattern, the comminution degree (low, medium, high), providing important information on fracture severity, could also be evaluated.

RESULTS

From 3D imaging, the inter- and intraobserver reliability revealed a k value (95% confidence interval) of 0.55 (0.50-0.60) and 0.91 (0.79-1.00), respectively, for the pattern code, and 0.52 (0.43-0.76) and 0.91 (0.56-0.96), respectively, for the comminution degree.

CONCLUSIONS

The new classification provides a useful synoptic framework for identifying complex fracture patterns. It can provide the surgeon with useful information for fracture analysis and may represent a good starting point for an automated system.

摘要

背景

本研究旨在根据控制容积理论对肱骨近端嵌插骨折的病理形态进行分类,目的是引入一种严重程度指数以辅助外科医生进行决策。

方法

从 2009 年至 2016 年治疗的 200 例成年患者的病历中随机选择了 50 例肱骨近端骨折。4 名非独立观察者使用 2 种不同的成像方式(计算机断层扫描加容积再现;3D 模型)对分类可靠性进行了测试。根据控制容积理论创建了一种骨折分类系统,提供了简单易懂的模式,有助于外科医生快速评估。嵌插骨折表是根据对骺板状况的评估生成的,由头杯下和肱骨头错位定义的体积区域的损伤来确定。除了主要的骨折模式外,还可以评估粉碎程度(低、中、高),这为骨折的严重程度提供了重要信息。

结果

从 3D 成像来看,模式代码的观察者间和观察者内可靠性分别为 0.55(0.50-0.60)和 0.91(0.79-1.00),而粉碎程度的观察者间和观察者内可靠性分别为 0.52(0.43-0.76)和 0.91(0.56-0.96)。

结论

新的分类为识别复杂的骨折模式提供了有用的综合框架。它可以为外科医生提供有用的骨折分析信息,并可能成为自动系统的良好起点。

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