Epicardial fat is a relatively neglected component of the heart and could be an important risk factor of cardiac disease. The objective of our study was to assess the relationship between epicardial adipose tissue (EAT) extent, fat distribution, and coronaropathy in a group of adult victims of accidental or suspicious sudden death. In 56 cadavers, we performed 34 measurements of EAT from five computerized photographs of the heart (anterior and posterior faces, and three ventricle transversal slices) and analyzed their relationship with anthropometric markers of adiposity (BMI, waist and leg circumference, thickness of abdominal and thigh subcutaneous adipose tissue (SAT)), with the presence and staging of coronary artery disease (CAD), and with markers of myocardial hypertrophy. Simple linear regressions showed that EAT measurements are highly intercorrelated (r from 0.4 to 0.6, P < 0.001), and correlate with age, waist circumference, and heart weight, and to a lesser extent, with BMI, abdominal SAT thickness, and leg SAT thickness. Multiple regression showed that age, waist circumference, and heart weight significantly and independently correlate with EAT (P < 0.0001). No other anthropometric measurement was found independently correlated with EAT. The EAT/myocardium ratios correlated positively with age and waist circumference. Anterior and posterior areas of EAT were found significantly increased in patients with CAD and correlated positively with CAD staging (P = 0.0034, r = 0.38). Anterior EAT surface was found positively associated with CAD (P = 0.01), independently of age and other adiposity measurements. Prospective studies are needed to assess the risk of occurrence/progression of CAD that relate to EAT excess.
Canines are usually used in anthropological and forensic sciences for sex and age determination. The best methods to estimate age are based on secondary dentine apposition, evaluated from periapical X-rays. The aim of this study was to propose a new method of sex and age estimation using 3D models to obtain more precise predictions using tooth volumes. Fifty-eight dental CT scans of patients aged 14-74 with a well-balanced sex ratio composed the sample. One hundred and thirty-three healthy canines were modeled (Mimics 12.0). The sample was divided into a training sample and a validation sample. An age formula was determined using the "pulp volume/tooth volume" ratio. Sex prediction was adjusted with total volumes. Applying the equations to the validation sample, no significant difference was found between the real and predicted ages, and 100% of the sex predictions were correct. This preliminary study gives interesting results, and this method is worth being tested on a larger data sample.
Frontal sinuses (FSs) have been studied in radiology, anthropology, and forensic anthropology. This study aimed to determine whether it was possible to predict the age and sex of an individual using FS volume. Sixty-nine anonymized CT scans were imported to MIMICS 10.01(®) software (Materialise N.V.), and each FS volume was calculated in mm(3) . There was an absence of significant difference between right and left FS volume (p = 0.173) and an absence of correlation between age and FS volume (Pearson's test; p = 0.705). Sexual dimorphism was significantly different (p = 0.001). However, the most discriminant datum for determining sex was found to be the total FS volume (sum of an individual's right and left FS volumes) with linear discriminant Fisher's function coefficients of -2.759 for the male group and -1.275 for the female group. With this model, 72.5% of our sample was correctly classified according to sex.
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