Determination of stature from skeletal and skull measurements by CT scan evaluation

被引:62
作者
Giurazza, Francesco [1 ]
Del Vescovo, Riccardo [1 ]
Schena, Emiliano [1 ]
Battisti, Sofia [1 ]
Cazzato, Roberto Luigi [1 ]
Grasso, Francesco Rosario [1 ]
Silvestri, Sergio [1 ]
Denaro, Vincenzo [1 ]
Zobel, Bruno Beomonte [1 ]
机构
[1] Univ Campus Biomed Roma, I-00100 Rome, Italy
关键词
Stature estimation; Skull; Femur; CT scan; Caucasian; Forensic Anthropology Population Data; LONG BONES; REGRESSION-ANALYSIS; CEPHALOFACIAL DIMENSIONS; POPULATION; LENGTH; HEIGHT; RECONSTRUCTION;
D O I
10.1016/j.forsciint.2012.06.008
中图分类号
DF [法律]; D9 [法律]; R [医药、卫生];
学科分类号
0301 ; 10 ;
摘要
The aim of this article is to find a correlation between height and femur/skull measurements through Computed Tomography (CT) scans and derive regression equations for total skeletal height estimation in the Caucasian population. We selected 200 Caucasian patients from March 2010 to July 2011 who had to perform a CT scan for cancer restaging. The mean age is 64.5 years. Both sexes are represented by the same number of persons. Patients have executed a total body CT scan with contrast; once scan accomplished, we measured height through a digital scales. We analyzed CT scans of each patient, obtaining multiplanar reconstruction in sagittal and coronal planes with 1 mm of thickness, and we measured 10 diameters of skull and femur. Then we performed a single and a multiple regression analysis considering the three diameters that better correlated with height. The skeletal diameters with the highest correlation coefficients with stature were femur lengths, length of cranial base (Ba-N), and distance from the posterior extremity of the cranial base to the inferior point of the nasal bone (Ba-NB). Although both femur and skull are skeletal segments used for stature estimation, in our sample femur gave stronger correlation with height than skull. h = 35.7 + 1.48.BaN + 2.32.BaNB + 2.53.FEM and h = 3.06.FEM + 72.6 are the formulae that provided the most accurate stature assessment using multiple and single regression analysis respectively. (C) 2012 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:398.e1 / 398.e9
页数:9
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