Estimation of stature and sex from sternal lengths: an autopsy study.

The aim of this study was to derive regression equations for estimating stature and further to estimate sex from four measured sternal lengths. This study included intact sterna from 65 males and 30 females, aged between 25 and 40 years, obtained during medico-legal autopsies. Stature and four sternal lengths, length of the manubrium (LM), length of the body (LB), length of the manubrium and body (LMB) and total sternal length, of each cadaver were measured. Stature and all measured sternal lengths were greater in males compared to females (p < 0.001). All sternal lengths were positively correlated with stature in sexes. LMB had the highest correlation coefficient in both males and females (correlation coefficient: 0.721 and 0.740, respectively). In both sexes, linear regression analysis for stature estimation revealed equations with the highest R (2) values when derived from LMB (R (2) = 0.521 for males and R (2) = 0.547 for females). On the other hand, only the multiple linear regression equation derived from the combination of the LB and LMB had the higher R (2) value (R (2) = 0.640) for stature estimation in females. Receiver-operating curve analysis for all measurements was statistically significant (p < 0.05 for all). These findings suggested that measured sternal lengths can be used for estimation of sex. However, LB and LMB measurements were found to be the most reliable sternal lengths for estimating sex with an accuracy rate of 90 %. Our results revealed that the sternum is a useful tool for estimating stature and sex when other skeletal bones are not available.

An automated method for analysis of microcirculation videos for accurate assessment of tissue perfusion.

BACKGROUND: Imaging of the human microcirculation in real-time has the potential to detect injuries and illnesses that disturb the microcirculation at earlier stages and may improve the efficacy of resuscitation. Despite advanced imaging techniques to monitor the microcirculation, there are currently no tools for the near real-time analysis of the videos produced by these imaging systems. An automated system tool that can extract microvasculature information and monitor changes in tissue perfusion quantitatively might be invaluable as a diagnostic and therapeutic endpoint for resuscitation. METHODS: The experimental algorithm automatically extracts microvascular network and quantitatively measures changes in the microcirculation. There are two main parts in the algorithm: video processing and vessel segmentation. Microcirculatory videos are first stabilized in a video processing step to remove motion artifacts. In the vessel segmentation process, the microvascular network is extracted using multiple level thresholding and pixel verification techniques. Threshold levels are selected using histogram information of a set of training video recordings. Pixel-by-pixel differences are calculated throughout the frames to identify active blood vessels and capillaries with flow. RESULTS: Sublingual microcirculatory videos are recorded from anesthetized swine at baseline and during hemorrhage using a hand-held Side-stream Dark Field (SDF) imaging device to track changes in the microvasculature during hemorrhage. Automatically segmented vessels in the recordings are analyzed visually and the functional capillary density (FCD) values calculated by the algorithm are compared for both health baseline and hemorrhagic conditions. These results were compared to independently made FCD measurements using a well-known semi-automated method. Results of the fully automated algorithm demonstrated a significant decrease of FCD values. Similar, but more variable FCD values were calculated using a commercially available software program requiring manual editing. CONCLUSIONS: An entirely automated system for analyzing microcirculation videos to reduce human interaction and computation time is developed. The algorithm successfully stabilizes video recordings, segments blood vessels, identifies vessels without flow and calculates FCD in a fully automated process. The automated process provides an equal or better separation between healthy and hemorrhagic FCD values compared to currently available semi-automatic techniques. The proposed method shows promise for the quantitative measurement of changes occurring in microcirculation during injury.