Children with cerebral palsy (CP) often present femoral bone deformities not accounted for in generic musculoskeletal models [1,2]. MRI-based models can be used to include subject-specific muscle paths [3,4], although this is a time-demanding process. Recently, non-rigid deformation techniques have been used to transform generic bone geometry, including muscle points, onto personalized bones [5]. However, it is still unknown to what extent such an approximation of subject-specific detail affects calculated hip contact forces (HCFs) during gait in CP children.

Seven children diagnosed with diplegic CP walked independently at self-selected speed. 3D marker trajectories were captured using Vicon (Oxford Metrics, UK) and force data was measured using two AMTI force platforms (Watertown, MA). MR-images were acquired (Philips Ingenia 1.5T) of all subjects lying supine. Firstly, a generic model [6] was scaled using the marker positions of a static pose. Secondly, a MRI-model containing the subject-specific bone structures and muscle paths of all hip and upper leg muscles was created [3]. Thirdly, the generic femur and pelvis geometries and muscle points were transformed onto the image-based femur and pelvis using an advanced non-rigid deformation procedure (Materialise N.V.). For all models, further analyses were performed in OpenSim 3.1 [7]. A kalman smoother procedure was used to calculate joint angles [8]. Muscle forces were calculated using a static optimization minimizing the sum of squared muscle activities. Next, HCFs were calculated and normalized to body weight (BW). First and second peak HCFs were determined and used for a Kruskal-Wallis test to determine differences between models. In case of a significant difference, a post-hoc rank-based multiple comparison test with Bonferonni adjustment was used. Further, average absolute differences in muscle points between the models was calculated, as well as average differences in moment arm lengths (MALs), reflecting muscle function.

Where the scaled generic muscle points differed on average 2.49cm from the MRI points, the non-rigidly deformed points differed 1.54cm from the MRI muscle points. Specifically, the tensor fascia latae differed most between the deformed and MRI models (11.7cm). When considering MALs, the gluteii muscles present an altered function for the generic and deformed models compared to the MRI model for all degrees of freedom of the hip at the time of both HCF peaks. The differences between models resulted in a significantly increased second peak HCF for the MRI models compared to the generic models (first peak average HCF: 3.88BW, 3.95BW and 4.90BW; second peak average HCF: 3.03BW, 4.89BW and 5.32BW for the generic, MRI and non-rigidly deformed models respectively). Although not significantly different, the deformed models calculated slightly increased HCFs compare to the MRI models.

The generic models underestimated HCFs compared to the MRI models, while the non-rigidly deformed models slightly overestimated HCFs. However, differences between the deformed and MRI models in terms of muscle points and MALs remain, specifically for the gluteii muscles. Therefore, further user-guided modification of the model based on MR-images will be necessary.

Four-dimensional computed tomography (4DCT: three dimensional + time) allows to measure individual bone position over a period of time usually during motion. This method has been found useful in studying the joints around the wrist as dynamic instabilities are difficult to detect during static CT scans while they can be diagnosed using a 4DCT scan [1]–[3]. For the foot, the PedCAT system (Curvebeam, Warrington, USA) has been developed to study the foot bones under full weight bearing, however its use is limited to static images. On the contrary, dynamic measurements of the foot kinematics using skin markers can only describe motion of foot segments and not of individual bones. However, the ability to measure individual bone kinematics during gait is of paramount importance as such detailed information could be used to detect instabilities, to evaluate the effect of joint degeneration, to help in pre-operative planning as well as in post-operative evaluation.

The overall gait kinematics of two healthy volunteers were measured in a gait analysis lab (Movement Analysis Lab Leuven, Belgium) using a detailed foot-model (Oxford foot model, [4]). The measured plantar-dorsiflexion and in-eversion were used to manipulate their foot during a 4D CT acquisition. The manipulation was performed through a custom made foot manipulator that controls the position and orientation of the foot bed according to input kinematics. The manipulator was compatible with the 4D CT Scanner (Aquilion One, Toshiba, JP), and a sequence of CT scans (37 CT scans over 10 seconds with 320 slices for each scan and a slice thickness of 0.5 mm) was generated over the duration of the simulation. The position of the individual bones was determined using an automatic segmentation routine after which the kinematics of individual foot bones were calculated. To do so, three landmarks were tracked on each bone over time allowing to construct bone-specific coordinate frames. The motion of the foot bed was compared against the calculated kinematics of the tibia-calcaneus as the angles between these two bones are captured with skin markers.

There is high repeatability between the imposed plantar/dorsiflexion and inversion/eversion and the calculated. Although the internal/external rotation was not imposed, the calculated kinematics follow the same pattern as the measured in the gait-analysis lab. Based on the validation of the tibia-calcaneus, the kinematics were also calculated between four other joints: tibia-talar, talar-calcaneus, calcaneus-cuboid and talar-navicular. Repeatable measurements of individual foot bone motion were obtained for both volunteers.

The use of 4D CT-scanning in combination with a foot manipulator can provide more detailed information than skin marker-based gait-analysis e.g. for the study of the the tibia-talar joint. In the future, the foot manipulator will be tested for its sensitivity for specific pathologies (e.g. metatarsal coalition) and will be further developed to better resemble a real-life stance phase of gait (i.e. to include isolated heel contact and toe off).