Background

The knee joint morphology varies according to gender and morphotype of the patients.

Introduction & aims. Different racial groups show variations in femoral morphometry. Femoral anteroposterior measurement and mediolateral measurement are key variables in designing femoral implant for TKR. Their aspect ratio determines the shape and mediolateral sizing for the proper patellofemoral tracking and uniform stress distribution over the resected distal femoral surface. Method. We reviewed the current literature in December 2013 in common medical databases including the Cochrane Library, PubMed and Medline. Keywords included combinations of: Anthropometry, Knee, Arthroplasty, Femur, Morphometry, Geometry. We selected papers including femoral morphometric data collected from populations of different ethnic origins. Papers covered populations in the USA, China, Germany, Thailand, Korea, India, Japan and Malaysia. Results. We have analysed femoral morphometry variables among different ethnic groups from the available data. Gross size of the resected femur can be defined in terms of antero-posterior (AP) and medio-lateral (ML) dimensions, an in the aspect ratio of femoral medio-lateral to femoral antero-posterior dimensions (fML/fAP). The Korean population showed the least value of fAP among all the groups, followed by Thai, Japanese, Indian, Malaysian and Chinese showing the increasing order among the sub-groups of Asian Population. American population shows the next higher fAP measurements from Asian population. German follows, and Arab quantify the largest value of this femoral anthropometric variable. fML varies by huge difference among male and female data in all populations. Thai, Indian, Malaysian, Arab, Japanese, Korean, German, Chinese and American; this sequence is the increasing order of fML. More trapezoid-shaped and narrower ML, this variation in female group leads to over-hang the implant for a given fAP. Generally, the aspect ratios are measured higher in these smaller female knees, and lower in larger male knees. Conclusions. Anthropometric data measuring distal femoral segment in different ethnic groups shows that the Asian population requires custom-fit implant design based on the morphological data. It would be more appropriate to introduce several medio-lateral options in sizing the implant for given antero-posterior dimensions

Introduction. Maximizing efficiency in total knee replacement surgery is desirable and one of the key aspects is optimum utilization of available theatre time allocation. The level of complexity of the pathology is often one of the determinants of the length of operative time. Body mass index (BMI) has also been positively correlated with operative time. However, two patients with the same BMI but different body habitus (central obesity vs generalized obesity) may present different challenges during surgery. An index focusing on the anthropometry of the lower limb (supra-patella index SPI) has been proposed and we hypothesize that it correlates more closely with operative time than BMI. Method. BMI and SPI were determined in all patients recruited into a prospective trial of a specific knee implant. All patients were operated on by one of two surgeons in a standardized manner. Data including operative time and tourniquet time were determined. Results. Data for BMI was available on 50 patients and 46 patients had SPI values. The mean BMI was 34, 3 (sd 7.6) and 74% of patients were obese. The mean SPI was 2, 3 (sd 3.2). Both the BMI and SPI correlated with operative time and tourniquet time using the Spearman rank-order correlation coefficient. The BMI correlated marginally better with the operative time and the SPI correlated marginally better with the tourniquet time. Conclusion. Both BMI and SPI correlated with operative time. Both indices can be used as predictors of operative time. ONE DISCLOSURE

Introduction. In a previous study of subjects with no history of lower extremity injury or disease we found a linear relationship between body weight and peak hip, knee, and ankle joint forces during the stance phase of gait. To investigate the effect of total knee arthroplasty (TKA) on forces in the operated joints as well as the other joints of the lower extremities, we tested TKA subjects during gait and performed inverse dynamics analyses of the results. Materials and Methods. TKA subjects (3 M, 1 F; 58 ± 5 years; body mass index range (BMI): 26–36 kg/m. 2. ) participated in this investigation following institutional review board approval and informed consent. One subject had bilateral knee replacement. Each patient received the same implant design (4 PS, 1 CR). Data from previously tested control subjects (8 M, 4 F; 26 ± 4 years; BMI: 20–36 kg/m. 2. ) were used for comparison. Retro-reflective markers were placed over bony landmarks of each subject. A nine-camera video-based opto-electronic system was used for 3D motion capture as subjects walked barefoot at a self-selected speed on a 10 meter walkway instrumented with three force plates. Data were imported into a 12-body segment multibody dynamics model (AnyBody Technology) to calculate joint forces. Each leg contained 56 muscles whose mechanical effect was modeled by 159 simple muscle slips, each consisting of a contractile element. The models were scaled to match each subject's anthropometry and BMI. For the control subjects, only one limb was used in determining the relationship between body mass and peak joint force at the hip, knee, and ankle. For the TKA subjects, the peak joint forces were calculated for both the TKA limb and the contralateral limb. Results. Figure 1 shows the knee joint forces for the TKA subjects’ operated (red triangles) and contralateral knees (diamonds) along with the values for the control subjects (circles). Knee joint forces for the TKA subjects fell within or near the upper and lower 95% confidence intervals (dashed lines) of the mean regression lines (solid lines) for the control subjects. Three patients had other lower limb complications (osteoarthritis, ankle surgery). One subject favored the operated limb and another the non-operated limb, as ascertained from the corresponding hip (Figure 2) and ankle joint forces (Figure 3). Discussion. Modeling and simulation can be used to indirectly estimate joint forces in the implanted and non-operated joints. Our gait-lab derived inverse dynamics simulations suggest that joint forces following TKA fall within or near the normal range over a wide range of body weights and that the linear dependence between joint force and body weight applies to the implanted as well as non-implanted joints