Condylus Occipitalis’in Morfometrik-Topografik Özelliklerinin ve Klinik Öneminin Değerlendirilmesi

Serdar Babacan, Rohat Bayat, Mustafa Deniz
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Abstract

Aim: To reduce morbidity and mortality in surgical operations to be applied to the craniovertebral junction, it is important to know the anatomical structures in the skull base and the topographical relationship between these structures. Lateral suboccipital craniotomy and occipital condyle resection are among the preferred methods. Surrounding neurovascular structures may be damaged during occipital condyle resection. The aim of study was to develop regression formulas that will determine the precise location of the occipital condyle and estimate the distances to the surrounding anatomical structures, based on the skull morphometry of the person. Material and Methods: The study was carried out on 22 condylus occipitalis (11 skulls) at Harran University, Medical Faculty Anatomy Laboratory. The determined 27 parameters were measured via the Image J program on the skulls’ inferior, anterior, lateral and posterior aspect photographs. Multiple linear regression analysis was performed. Results: To determine the morphometric and topographic features of the occipital condyle, the equations have been developed such as; The occipital condyle length= -2.142 + (0.330 x P15) – (0.468 x P19) – (0.748 x P20) + (0.807 x P21); Adjusted R2= 0.911, Standard Error of the Estimation= 0.938. Conclusion: Considering the difference between the minimum and the maximum values observed in descriptive statistics, the distribution between these values, the different findings in the studies in the literature, there may be erroneous applications in the attempts to be made over the mean values. We believe that the formulas we have developed will be beneficial in personal-specific approaches.
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目的:了解颅底解剖结构及各解剖结构之间的地形关系,对降低颅椎交界处外科手术的发病率和死亡率具有重要意义。枕下外侧开颅和枕髁切除术是首选的方法。在枕髁切除术中,周围的神经血管结构可能受损。研究的目的是开发回归公式,以确定枕髁的精确位置,并根据人的头骨形态测定法估计与周围解剖结构的距离。材料与方法:在哈兰大学医学院解剖实验室对22例枕髁(11例颅骨)进行研究。通过Image J程序对颅骨的下、前、侧、后侧面进行测量。进行多元线性回归分析。结果:为了确定枕髁的形态和地形特征,建立了如下方程;枕髁长度= -2.142 + (0.330 × P15) - (0.468 × P19) - (0.748 × P20) + (0.807 × P21);校正后R2= 0.911,估计标准误差= 0.938。结论:考虑到描述性统计中观察到的最小值与最大值之间的差异,这些值之间的分布,文献中研究结果的不同,在试图对平均值进行修正时可能存在错误的应用。我们认为,我们制定的公式将有利于采取针对个人的办法。
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