# Detecting Anatomical Leg Length Discrepancy Using the Plug-in-Gait Model
## 4 Discussion  
Herein, we compared femur and tibia segmental length measurements using the PGM to detect anatomical discrepancy compared to X-ray measurements. Our results revealed that the PGM is highly valid and reliable in detecting anatomical difference in segmental length. Minimal differences in segmental discrepancy between sides were found when comparing both methods, with a mean difference of 3.6 mm in the femur and the tibia segmental length. Participants' measurements were found symmetrical with no significant difference in all lower limb measurements. A high correlation was found between methods, however, a significant difference in absolute values of the two measurements was found. Femoral length as calculated by the PGM was shorter by 18-21 mm; the tibial segmental length was shorter by 52-53 mm when X-rayed. The difference in segmental length of the femur was attributed to the measuring method. Femur segmental length as measured by the PGM was based on the joint center location as opposed to the X-ray where measurement started from the proximal edge of the femur head to the distal end of the femoral condyle. However, the tibias segments were relatively similarly measured in both methods, and despite difference that might be attributed to measuring methods, it cannot explain the large discrepancy found, and thus should be further investigated. Radiographic evaluations either by standing X-ray or CT scanogram are considered the gold standard for measuring images. Computed radiography used for measuring segmental length has been found to be valid and reliable [20]. Radiographs calibrated using a 1-inch reference metal ball supported by a designated software program (TraumaCad(r)) have been found to have high intra and inter-observer reliability (Intraclass correlation coefficient (ICC) 0.91-0.95, respectively) and a standard deviation of 3.61 to 4.65 mm when measuring femoral and tibial length, respectively [20]. [PERSON] et al. reported a high inter and intra-observer reliability for scanogram (ICC 0.975-0.995, respectively) as well as standing teleorentgenogram (ICC 0.939-0.996) [21]. The mean absolute difference for intra-observer and inter-observer reliability was 1.5 to 2.6 mm and 2.6 mm, respectively for scanograms and 1.5 to 4.6 mm and 3 mm, respectively for standing radiographs. In summary, imaging is a highly reliable measurement tool, with a minimum estimated margin of error. The PGM divides the body into seven segments (pelvis, two femurs, tibias and feet) [15]. The segments are defined from the measured positions of the markers, subjects' measurements and model calculation. Its accuracy is limited, relying on the examiner's ability to formulate an accurate anthropometric measurement such as the distance from the ASIS to MM, the distance between the right and left ASIS, knee and ankle width and tibial torsion, as well as accurate marker placement. In this study,  
Figure 3: Differences in the median, quartiles, extreme values and outlier subjects for segmental and leg length measured by PGM and X-ray. all measurements and marker placements were performed by the same examiner experienced in gait analysis which has been shown to improve reliability [22; 23]. Moreover, anthropometric measurements assessed by experienced examiners have found no considerable effect on joint kinematics [24], thus, the likelihood that most differences found in the tibia segmental length were due to model calculation. In the PGM, body segment parameters are based on a simple relationship described by [PERSON] et al. [25]. The location of the hip, knee, and ankle joint centers are calculated relative to the associated embedded coordinate system origin of the segments. Hip joint centering algorithm is based on a model developed at Newington Children's Hospital in 1981 analyzing radiographic studies of 25 hip studies [15]. The HJC was defined in the pelvis segment, using the pelvis width (right ASIS to left ASIS) and leg length (ASIS to MM) as scaling factors [15].