Objectives To develop individualized growth assessment (IGA) standards for upper (ThC(u)) and middle (ThC(m)) fetal thigh circumferences using threedimensional ultrasonography. ThC(u) , GPRI ThC(m) and GPRI ThC(o) ( 103.7 (95% range,. Corresponding mean ± SD m 3 NGAS 51 values, using GPRI ThC(u) , GPRI ThC(m) and GPRI ThC(o) , were 203 ± 11%, 201 ± 10% and 200 ± 9%, respectively. MethodsConclusions Fetal thigh circumference can be measured reliably and evaluated using standard IGA methods. Both ThC(u) and ThC(m) give similar results in the third trimester but neonatal thigh circumference predictions are improved by using ThC(m). Corresponding GPRI ThC(m) values are closer to the ideal value of 100% and can be used in m 3 NGAS 51 calculations for assessment of neonatal growth outcome.

Determination of sex is of crucial importance in forensic investigations, when only a part of the body or skeletal remains are available. The present study focussed on the sexual dimorphism of hyoid bone in Telangana population by using morphometric analysis.Materials and methods: The present study was carried out on a total of 60 hyoid bones in which 30 were of male and 30 were of female individuals. The bones were obtained from the department of Anatomy, Osmania Medical College and Deccan College of Medical Sciences, Hyderabad. Damaged and deformed bones were excluded, and only fully intact bones were included in the study. Lengths of greater horns, lengths of lesser horns, total hyoid length, and distance between distal ends of right and left greater horns, width of the body, length of the body and the thickness of the body of hyoid bone were measured by using sliding calipers.Results: All parameters showed significant difference between the male and female groups. The measurements of all the parameters were significantly higher in males than in females. Conclusion:All parameters used in the present study confirmed sexual dimorphism in hyoid bone. Hence, hyoid bone can be considered in forensic investigations or anthropological studies to determine the sex of an individual.

Oral communication abstracts variables could improve ultrasound prediction of fetal macrosomia over prediction which relies on the commonly used formulas for the sonographic estimation of fetal weight. Methods: The δ SVM algorithm was used for binary classification between two categories of weight estimation: > 4000 g and < 4000 g. Clinical and sononographic input variables of 100 pregnancies suspected of having LGA fetuses were tested. Results: Thirteen of 38 features were selected as contributing variables that distinguish birth weights of below 4000 g and of 4000 g and above. Considering 4000 g as a cutoff weight the pattern recognition algorithm predicted macrosomia with a sensitivity of 81%, specificity of 73%, positive predictive value of 81% and negative predictive value of 73%. The comparative figures according to the combined criteria based on two commonly used formulae generated from regression analysis were 88.1%, 34%, 65.8% and 66.7%. Conclusions: The δ SVM algorithm provides a prediction of LGA fetuses comparable to that of other commonly used formulae generated from regression analysis. The better specificity and better positive predictive value suggest potential value for this method and further accumulation of data may improve the reliability of this approach.

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Objectives: We studied the benefits of adding three-dimensional (3D) to two-dimensional (2D) ultrasound to diagnose malignant and benign breast disease. Methods: This prospective study included 121 patients with clinical or mammographic breast anomalies who underwent 2D and then 3D breast ultrasound centred on the 2D anomaly. Patients with cystic masses were excluded because they are well described with 2D ultrasound. 2D and 3D images were classified into three categories-benign, atypical, and malignant. A single operator performed all ultrasounds. All patients underwent breast biopsies; pathology results, classified into four types, were compared with ultrasound results. The sensitivity, specificity, and predictive values of both ultrasound techniques for diagnosing malignant diseases were calculated, as was the kappa coefficient of concordance between the ultrasound and pathology results. Fisher's exact test was used to compare 2D and 3D ultrasound assessment categories according to pathology results. Results: 3D ultrasound provided the same sensitivity as 2D ultrasound (0.96) and better specificity (1 versus 0.74) for diagnosis of malignant disease. The kappa coefficient of concordance between 2D ultrasound and pathology findings was 0.53 versus 0.97 between 3D and pathology findings. Three identifying criteria in the coronal plane (rim, type of convergences and architectural distortion) were especially helpful for image analysis. 3D ultrasound also provided significantly better diagnostic information for fibrocystic breast disease: 100% (25/25) of cases were characterized on 3D ultrasound, and only 40% (10/25) on 2D ultrasound (P < 0.001). Conclusion: 3D ultrasound, although not more accurate than 2D ultrasound for diagnosing breast cancer, improves accuracy of fibrocystic breast disease diagnosis by reducing false-positive results.