背景:上颌窦(MS)的基础疾病,包括鼻窦手术史,慢性鼻窦炎,或先天性异常可能会影响鼻窦功能和结构,需要仔细的评估和管理。此外,完整的鼻窦在法医人类学的性别确定中至关重要。本研究旨在使用形态参数检查MS在性别确定中的准确性和可靠性。
方法:这项回顾性研究是对北印度人口中年龄在18至50岁之间的74例侧位头颅图(男性37例,女性37例)进行的。使用NewTomCBCT机(NewTom,伊莫拉,意大利)带有切片机软件。确定了鼻窦的解剖标志,面积以平方毫米(mm2)计算。
结果:就表面积而言,女性的平均值为13,210.40mm2,标准误差为713.46。男性,然而,表现出更高的平均表面积为18,713.82mm2,但标准误差为3,371.70。男性和女性的MS面积差异有统计学意义(p<0.01)。在接收器工作特性(ROC)曲线中,曲线下面积(AUC)为0.77,提示良好的判别能力。
结论:侧脑图上的MS区域显示出明显的性二态性。总的来说,研究结果表明,MS表面积可以成为区分北印度男性和女性受试者的有用解剖学特征,鉴于ROC曲线分析表明有统计学意义的差异和良好的判别性能。
BACKGROUND: Underlying disorders of the maxillary sinus (MS), including a history of sinus surgeries, chronic sinusitis, or congenital anomalies can potentially impact sinus function and structure, necessitating careful evaluation and management. Moreover, intact sinuses are crucial in gender determination in forensic anthropology. The present study was undertaken to check the accuracy and reliability of MS in gender determination using morphometric parameters.
METHODS: This retrospective study was carried out on 74 lateral cephalograms (37 males and 37 females) aged between 18 to 50 years from the North Indian population. The MS area was measured using a NewTom CBCT machine (NewTom, Imola, Italy) with slicer software. The anatomical landmarks for the sinus were identified, and the area was calculated in square millimeters (mm2).
RESULTS: In terms of surface area, females had a mean of 13,210.40 mm2 with a standard error of 713.46. Males, however, exhibited a higher mean surface area of 18,713.82 mm2, but with a significantly larger standard error of 3,371.70. The difference in MS area between males and females was statistically significant (p<0.01). In the receiver operating characteristic (ROC) curve, the area under the curve (AUC) was 0.77, suggesting good discriminative ability.
CONCLUSIONS: The MS area on lateral cephalograms shows significant sexual dimorphism. Overall, the findings suggest that the MS surface area can be a useful anatomical feature for distinguishing between male and female North Indian subjects, given the statistically significant difference and the good discriminative performance indicated by the ROC curve analysis.