Abstract:Variations in the infrahyoid muscle were identified as early as 19 th century. During regular dissection of cadaver in anatomy department in Kota an unilateral anomalous infrahyoid muscle was noted on right side with the absence of omohyoid muscle on same side. It was a flat, strap muscle 12 cm long and 2 cm wide. On one end it was attached to antero-lateral aspect of body of hyoid bone and on the other end to the clavicle. Its nerve supply was noted to be from the ansa cervicalis. Apart from this other infrahyoid muscles were normal. This muscle is best described as a cleidohyoid rather than the omohyoid. Hence in our case cleidohyoid appears to be variation of omohyoid muscle whereas some other workers have reported cleidohyoid as a variation of sternohyoid muscle. Surgeons and radiologists should be aware of such variations as it might interfere with the invasive techniques and knowledge of such variations should be kept in mind while interpreting MRI images of cervical region.

Background and aims: Surgeries involving the femur are quite common. The clinical importance of femur in sports biomechanics and rehabilitation is well known. Therefore, its morphometries has orthopedic implications. The present study aims at establishing interrelationship among various external parameters in adult dried femora including femoral offset (FO), neck shaft angle [NSA], femoral anteversion angle [FNA], Neck width [NW], Anterior Neck length [ANL], Posterior Neck length [PNL], Oblique length [OL] and trochanteric oblique length [TOL], Materials and Methods: A total of 100 [50 right and 50 left] intact, dried adult human femora from department of Anatomy, Government Medical College, Kota were included in this study. The FO, NSA and FNA were measured by digital image analysis in ‘IMAGEJ’ software. OL and TOL were measured using osteometric board. ANL, PNL and NW were recorded using sliding caliper. Statistical analysis was done using SPSS and Microsoft Excel software. The mean values were calculated, relationship between parameters was measured by Pearson's correlation coefficient ‘r’. Multiple regression equations were derived in order to calculate FO by other variables. Results: FO showed strong negative correlation with NSA; strong positive correlation with ANL, PNL, NW; moderate positive correlation with OL, TOL; but no relationship with FNA. NSA had moderate negative correlation with NW and weak negative correlation with PNL. NW & ANL had positive correlation with OL, TOL. Conclusion: In our method we used dried, intact bone and digital photographs with standardised method. Therefore it should provide accurate results; in addition it is cost effective. However studies on larger scale are warranted to design implants for Indian population.