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首页> 外文期刊>Computer methods in biomechanics and biomedical engineering >Osteocyte-based Image Analysis for Quantitation of Histologically Apparent Femoral Head Osteonecrosis: Application to an Emu Model
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Osteocyte-based Image Analysis for Quantitation of Histologically Apparent Femoral Head Osteonecrosis: Application to an Emu Model

机译：基于骨细胞的图像分析在组织学上明显的股骨头坏死的定量：mu模型的应用

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Femoral head osteonecrosis is often characterized histologically by the presence of empty lacunae in the affected bony regions. The shape, size and location of a necrotic lesion influences prognosis, and can, in principle, be quantified by mapping the distribution of empty lacunae within a femoral head. An algorithm is here described that automatically identifies the locations of osteocyte-filled vs. empty lacunae. The algorithm is applied to necrotic lesions surgically induced in the emu, a large bipedal animal model in which osteonecrosis progresses to collapse, as occurs in humans. The animals' femoral heads were harvested at sacrifice, and hematoxylin and eosin-stained histological preparations of the coronal midsections were digitized and image-analyzed. The algorithm's performance in detecting empty lacunae was validated by comparing its results to corresponding assessments by six trained histologists. The percentage of osteocyte-filled lacunae identified by the algorithm vs. by the human readers was statistically indistinguishable.
机译：股骨头坏死的组织学特征通常是在受影响的骨区域中存在空洞。坏死病变的形状，大小和位置会影响预后，并且原则上可以通过绘制股骨头内空腔的分布来量化。这里描述了一种算法，该算法自动识别骨细胞填充与空腔的位置。该算法适用于在mu中外科手术诱发的坏死病变，e是一种大型两足动物模型，在该模型中，骨坏死逐渐崩溃，就像在人类中一样。处死时收集动物的股骨头，并对苏木精和伊红染色的冠状动脉中段染色的组织学制剂进行数字化和图像分析。通过将其结果与六位训练有素的组织学家的相应评估进行比较，验证了该算法在检测空腔方面的性能。通过算法与人类读者确定的填充骨细胞腔的百分比在统计学上是无法区分的。

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