Differences in vertebral bone density between African apes.

OBJECTIVES: Low-energy vertebral fractures are a common health concern, especially in elderly people. Interestingly, African apes do not seem to experience as many vertebral fractures and the low-energy ones are even rarer. One potential explanation for this difference is the lower bone density in humans. Yet, only limited research has been done on the vertebral bone density of the great apes and these have mainly included only single vertebrae. Hence the study aim is to expand our understanding of the vertebral microstructure of African apes in multiple spinal segments. MATERIALS: Bone density in the vertebral body of C7, T12, and L3 was measured from 32 Pan troglodytes and 26 Gorilla gorilla using peripheral quantitative computed tomography (pQCT). RESULTS: There was a clear difference between the three individual vertebrae and consequently the spinal segments in terms of trabecular density and cortical density and thickness. The variation of these bone parameters between the vertebrae differed between the apes but was also different from those reported for humans. The chimpanzees were observed to have overall higher trabecular density, but gorillas had higher cortical density and thickness. Cortical thickness had a relatively strong association with the vertebral size. DISCUSSION: Despite the similarity in locomotion and posture, the results show slight differences in the bone parameters and their variation between spinal segments in African apes. This variation also differs from humans and appears to indicate a complex influence of locomotion, posture, and body size on the different spinal segments.

Deep learning in sex estimation from a peripheral quantitative computed tomography scan of the fourth lumbar vertebra-a proof-of-concept study.

Sex estimation is a key element in the analysis of unknown skeletal remains. The vertebrae display clear sex discrepancy and have proven accurate in conventional morphometric sex estimation. This proof-of-concept study aimed to investigate the possibility to develop a deep learning algorithm for sex estimation even from a single peripheral quantitative computed tomography (pQCT) slice of the fourth lumbar vertebra (L4). The study utilized a total of 117 vertebrae from the Terry Anatomical Collection. There were 58 male and 59 female cadavers, all of the white ethnicity, with the average age at death 49 years and a range of 24 to 77 years. A coronal pQCT scan was taken from the midway of the L4 corpus. Sex estimation was performed in a total of 19 neural network architectures implemented in the AIDeveloper software. Of the explored architectures, a LeNet5-based algorithm reached the highest accuracy of 86.4% in the test set. Sex-specific classification rates were 90.9% among males and 81.8% among females. This preliminary finding advances the field by encouraging and directing future research on artificial intelligence-based methods in sex estimation from individual skeletal traits such as the vertebrae. Combining quickly obtained imaging data with automated deep learning algorithms may establish a valuable pipeline for forensic anthropology and provide aid when combined with traditional methods.

Sex- and site-specific, age-related changes in bone density - a Terry collection study.

As modern populations are living longer, age-related health issues have become more common. One growing concern is the age-related bone density loss that increases the individual's risk for fractures, which unfortunately seems to disproportionately afflict women. These fractures are not only detrimental to the individuals' lives but also come with a great economic burden to the societies. Although age-related bone loss is a normal phenomenon, studies on archaeological individuals have demonstrated that the pattern how this occurs has experienced changes due to our changing lifestyles. Hence, to add to our understanding of secular trends in age-related bone loss, we studied age- and sex-related differences in vertebral and femoral bone densities of a recent past population of late 19th and early 20th century Americans. We used a sample of 114 individuals (55 males, 59 females) from the Robert J. Terry Anatomical Skeletal Collection. Peripheral quantitative computed tomography (pQCT) was used to scan the dry bones. We took one scan from the 4th lumbar vertebra and three scans from the femur. The associations between the age, sex and bone density were analyzed. We were able to detect age-related bone loss in both vertebra and femur. It was observed that men tended to lose more bone density on the vertebra, whereas bone loss in women was more pronounced in the femur. We speculate that differences to modern and earlier archaeological populations are related to the major lifestyle differences between the periods.

Comparison of bone density patterns of the subaxial spine between chimpanzees and gorillas - A case study.

Case study on the bone density pattern of subaxial vertebral column in African apes. INTRODUCTION: African apes have been noted to experience fewer back ailments than humans and to have higher vertebral bone density. Yet, research on the subject is quite limited and has usually included only one or few vertebrae. However, to understand vertebral column as whole and how posture and locomotion might have affected it, we need to know how bone density varies between adjacent vertebrae. MATERIALS AND METHODS: Bone density in the vertebral body was measured for all subaxial vertebrae of five specimens including two Pan troglodytes (1 male and 1 female) and three Gorilla gorilla (2 males and 1 female) using peripheral quantitative computed tomography (pQCT). RESULTS: The results tentatively indicated differences between species, especially in the trabecular density of the cervical segment and support the need for further studies on this subject.

Temporal Trends in Vertebral Dimensions - a case study from Finland.

Vertebral fractures and other back problems represent a major, increasing worldwide health problem. This has increased the need to better understand the reasons behind this phenomenon. In addition to a reduction in bone mineral density and overall size of the vertebral body, research has indicated a possible association between the shape of the endplate and spinal disorders. As one previous study has shown changes in vertebral body dimensions between contemporary people and their medieval counterparts, we wanted to examine the potential temporal trends in vertebral size and dimensions in Finnish samples of archaeological and contemporary individuals. To conduct this study, we utilized three archaeological populations from the 16th-19th century and clinical materials from two population-based Finnish birth cohorts. As the average height of people has increased greatly since the first time period, we also height-adjusted the dimensions to provide a clearer picture of the dimensional changes that have occurred in the later temporal group. Our results were in agreement with those of the earlier study. The archaeological samples had a larger vertebral size than the contemporary population when height was adjusted for. Vertebral mediolateral width in particular had decreased, and the shape of the vertebral body had changed.

Body mass estimation from dimensions of the fourth lumbar vertebra in middle-aged Finns.

Although body mass is not a stable trait over the lifespan, information regarding body size assists the forensic identification of unknown individuals. In this study, we aimed to study the potential of using the fourth lumbar vertebra (L4) for body mass estimation among contemporary Finns. Our sample comprised 1158 individuals from the Northern Finland Birth Cohort 1966 who had undergone measurements of body mass at age 31 and 46 and lumbar magnetic resonance imaging (MRI) at age 46. MRI scans were used to measure the maximum and minimum widths, depths, and heights of the L4 body. Their means and sum were calculated together with vertebral cross-sectional area (CSA) and volume. Ordinary least squares (OLS) and reduced major axis (RMA) regression was used to produce equations for body mass among the full sample (n = 1158) and among normal-weight individuals (n = 420). In our data, body mass was associated with all the L4 size parameters (R = 0.093-0.582, p ≤ 0.019 among the full sample; R = 0.243-0.696, p ≤ 0.002 among the normal-weight sample). RMA regression models seemed to fit the data better than OLS, with vertebral CSA having the highest predictive value in body mass estimation. In the full sample, the lowest standard errors were 6.1% (95% prediction interval ±9.6 kg) and 7.1% (±9.1 kg) among men and women, respectively. In the normal-weight sample, the lowest errors were 4.9% (±6.9 kg) and 4.7% (±5.7 kg) among men and women, respectively. Our results indicate that L4 dimensions are potentially useful in body mass estimation, especially in cases with only the axial skeleton available.

Estimation of stature from dimensions of the fourth lumbar vertebra in contemporary middle-aged Finns.

BACKGROUND: Accurate stature estimation plays an essential role in the identification of unknown deceased individuals. For cases in which conventional methods of stature estimation are not applicable, we studied the stature estimation potential of the fourth lumbar vertebra (L4) among a large living sample of representative contemporary Finns. We also generated stature estimation equations for the middle-aged Finnish population. MATERIAL AND METHODS: Our study population comprised the Northern Finland Birth Cohort 1966 for which lumbar magnetic resonance imaging (MRI) scans and objective measurements of stature were available from midlife (n=1358). After screening the MRI scans for vertebral pathologies, we measured the maximum and minimum widths, depths and heights of the L4 body with high precision and reliability. We then calculated their sums and means together with approximations of vertebral cross-sectional area and volume. By constructing simple and multiple linear regression models around the L4 parameters, we generated equations for stature prediction, and investigated their accuracy on the basis of the adjusted R squared (R2) and standard error of the estimate (SEE) values of the models. RESULTS: The multiple linear regression models of the mean width, depth and height of L4 yielded the highest prediction accuracies with the lowest prediction errors (for the entire sample, R2=0.621 and SEE=5.635cm; for men, R2=0.306 and SEE=5.125cm; for women, R2=0.367 and SEE=4.640cm). CONCLUSION: When conventional methods for estimating stature are not applicable, the lumbar vertebrae may be utilized for this purpose. Relatively accurate stature estimates can be given on the basis of only L4 dimensions.