Assisting Clinical Decision-Making for Paediatric Movement Disorders - Towards assessing the effectiveness of therapy in cerebral palsy through mapping of gait maturation

Cerebral Palsy (CP), caused by a lesion to or abnormality of the developing brain, is the most common movement disability in childhood within western countries. The central lesion affects motor control and leads to abnormal development of muscles and bones. Treatment targets the musculoskeletal deformities and focuses on optimizing quality of life by bringing walking patterns of affected individuals closer to those of typically developing children (TDC). Clinical gait analysis (CGA) is used to objectively assess walking patterns and determine the causes of gait deviations. While CGA provides added value to clinical decision making and has shown to improve treatment outcomes, it did not lead to the expected improvement in patient satisfaction. One-third of patients remain unsatisfied with outcomes after intervention, but this could be due to unrealistic expectations. Additionally, some useful information could be hidden in the high dimensional CGA data, which are difficult to interpret. Until now, mainly kinematic features and overall summary scores for gait and motor function are extracted from CGA to assist clinical decision making. However, it is questionable whether this practice can capture the complexity of walking and motor development. Therefore, there is a need for more in-depth evaluation of the possible approaches to translate CGA outcomes into clinically relevant and easily interpretable outcomes. By providing relevant information from CGA to clinicians, unnecessary treatments can be prevented, patients can receive the optimal treatment for their condition in a timelier fashion, and more realistic expectations can be set. This can help reduce healthcare costs, optimize treatment outcomes, and improve patient satisfaction. Therefore, this doctoral thesis aimed to identify CGA parameters capable of capturing gait development with age and the effects of treatment. As fluctuations in walking behaviour have shown promise in capturing development and skill acquisition, this work focussed on the ability of gait variability and asymmetry to differentiate age and different levels of motor impairment. First, methods for estimating gait events, such as touch-down (initial contact) and lift-off (toe-off), were evaluated for their efficacy on paediatric pathological gait. The optimal methodology identified was afterwards applied in a retrospective cohort study to extract spatiotemporal parameters and quantify their variability in a (semi-)automatic manner from kinematic data. This data was then used to present the concept of motor-developmental trajectories in movement variability and assess the ability of gait asymmetry and variability to capture development and motor function in children and adolescents with CP and those with typical development. It was then investigated whether these motor-developmental trajectories could be interrupted by surgical interventions. From all the evaluated methods to estimate timing of gait events, the sagittal velocity approach applied to markers located on the mid-foot (where the peaks from the marker velocity in the sagittal plane are used to estimate timing of gait events), was found to preform best across various paediatric pathological gait patterns. With this sagittal velocity method, gait variability and asymmetry parameters were extracted from a retrospective clinical dataset. Through childhood, significant differences in movement variability were present between TDC and children with CP. Walking patterns tended to become less variable and more symmetrical with increasing age in both TDC and children with CP. However, the change with age was greater in individuals with CP who underwent the standard care in Switzerland, compared to TDC, leading to less profound differences at greater age. The difference in severity levels of CP remained stable during child development. Following a multilevel surgery (i.e., operations on both hips, knees, and feet in one surgical session), gait variability and asymmetry reduced with time in individuals with CP, indicating that invasive musculoskeletal intervention does not disrupt motor maturation. While routinely reported parameters, such as gait profile score, improved short-term after surgery and were afterwards maintained, gait variability and asymmetry parameters further improved into adulthood. The motor-developmental trajectories in movement variability, that were developed as part of this thesis, enable the prognosis of gait function in children and adolescents with typical development and CP. Like growth charts commonly used for height and weight, these trajectories capture age-related changes for multiple gait domains. Motor-developmental trajectories in movement variability can be used for identification and detection of motor characteristics of CP and allow for expectations of development and functional discrepancies to be managed effectively. Additionally, motor-developmental trajectories elucidate underlying deficits and could therefore be used as functional biomarkers to support clinical decisionmaking for targeted treatment programmes. In the rapidly changing field of CGA, the concept of motor-developmental trajectories in movement variability is one of many new tools being developed. Each of these new tools contribute in their own unique way. Musculoskeletal modelling, in combination with measures for motor control, can be an asset to test hypotheses regarding the causes of motor deficits at the population level; machine learning can be used to provide patient-specific predictions and thereby support patient-centred care. The strength of the presented motor-developmental trajectories lies within monitoring of gait function over time and can be used to visualize progress and support management of CP

Restoration of Heel–Toe Gait Patterns for the Prevention of Asymmetrical Hip Internal Rotation in Patients with Unilateral Spastic Cerebral Palsy

Forward modelling has indicated hip internal rotation as a secondary physical effect to plantar flexion under load. It could therefore be of interest to focus the treatment for patients with unilateral spastic cerebral palsy on achieving a heel–toe gait pattern, to prevent development of asymmetrical hip internal rotation. The aim of this preliminary retrospective cohort investigation was to evaluate the effect of restoring heel–toe gait, through use of functional orthoses, on passive hip internal rotation. In this study, the affected foot was kept in an anatomically correct position, aligned to the leg and the gait direction. In case of gastrosoleus shortness, a heel raise was attached to compensate for the equinus and yet to provide heel–floor contact (mean equinus = −2.6 degrees of dorsiflexion). Differences in passive hip internal rotation between the two sides were clinically assessed while the hip was extended. Two groups were formed according to the achieved correction of their gait patterns through orthotic care: patients with a heel-toe gait (with anterograde rocking) who wore the orthosis typically for at least eight hours per day for at least a year, or patients with toe-walking (with retrograde rocking) in spite of wearing the orthosis who used the orthosis less in most cases. A Student’s t-test was used to compare the values of clinically assessed passive hip rotation (p < 0.05) between the groups and the effect size (Hedges’ g) was estimated. Of the 70 study participants, 56 (mean age 11.5 y, majority GMFCS 1, similar severity of pathology) achieved a heel-toe gait, while 14 remained as toe-walkers. While patients with heel–toe gait patterns showed an almost symmetrical passive hip internal rotation (difference +1.5 degrees, standard deviation 9.6 degrees), patients who kept toe-walking had an increased asymmetrical passive hip internal rotation (difference +10.4 degrees, standard deviation 7.5 degrees; p = 0.001, Hedges’s g = 0.931). Our clinical findings are in line with the indications from forward modelling that treating the biomechanical problem might prevent development of a secondary deformity. Further prospective studies are needed to verify the presented hypothesis.ISSN:2227-906

Influence of TAL-TATS surgery on energy production of Triceps Surea – a musculoskeletal modeling evaluation

Introduction Cerebral palsy is the most common paediatric motor disability in Europe [1]. It is known to cause structural and functional gait deformities, such as equinus foot and toewalking. A common surgical option to rehabilitate toewalking is Tendo Achilles Lengthening (TAL) surgery. However, this procedure can lead to plantar flexor weakening, which can develop into a drop-foot or even crouch gait post-surgery [2]. To prevent these complications, a previous study recommended adding Tibialis Anterior Tendon Shortening (TATS) to the surgical procedure [3]. The combined TAL-TATS procedure has shown improvement towards typically developing gait patterns after surgery during early and midterm evaluations regarding clinical and overall gait scores [3,4], but it remains unknown how the procedure affects muscle function of the triceps surae. As conventional gait analysis does not provide detailed information on single muscles, this study proposes a musculoskeletal modelling approach, which will allow more in-depth investigation of muscle function before and after TAL-TATS intervention. Research Question Does the TAL-TATS procedure lead to weakening of the triceps surae (as shown by a reduction in energy production) during gait? Methods 3D gait analysis outcomes of 10 patients who underwent a combined TAL-TATS procedure (5 years 6 months ± 1 year 1 month post-surgery [mean±SD]) were analysed using the Twente Lower Extremity Model v1.1 from the AnyBody repository (5 segments; 5 degrees of freedom; 159 muscle fibers in 37 muscle groups; simple muscles; polynomial recruitment solver power 3). Resulting joint moments of every muscle fiber with respect to a certain joint were determined in order to compute the power of a muscle. This enabled computation of muscle moments of biarticular muscles at both joints separately. Muscle power was computed by multiplying these moments with the corresponding joint velocity. Integration of this power over the time of interest revealed the produced or absorbed energy of a muscle per joint [5]. Pre-operative muscle power over the ankle join of the gastrocnemius and soleus were compared against postoperative findings, using paired t-tests and statistical parametric mapping. Results Outcomes showed no significant reduction in produced energy during push off over the ankle joint for both Gastrocnemius (p=0.81) and Soleus (p=0.32), while there was a significant reduction in absorbed energy by the triceps surae during the load-response phase (p<0.001), when comparing pre- to postoperative gait (Figure 1). Discussion In conclusion, no indicators for reduced energy production of the triceps surae during gait after TAL-TATS procedure were found. The common fear of weakening plantar flexors after lengthening is not supported by the current findings. This outcome supports previous statements that the combined TAL-TATS procedure could prevent plantar flexor weakening after surgery. Further validation of the proposed method and further investigation of the TAL-TATS procedure are needed to establish added value of TAL-TATS to TAL

Identifying treatment non-responders based on pre-treatment gait characteristics - A machine learning approach

Background: Paediatric movement disorders such as cerebral palsy often negatively impact walking behaviour. Although clinical gait analysis is usually performed to guide therapy decisions, not all respond positively to their assigned treatment. Identifying these individuals based on their pre-treatment characteristics could guide clinicians towards more appropriate and personalized interventions. Using routinely collected pre-treatment gait and anthropometric features, we aimed to assess whether standard machine learning approaches can be effective in identifying patients at risk of negative treatment outcomes. Methods: Observational data of 119 patients with movement disorders were retrospectively extracted from a local clinical database, comprising sagittal joint angles and spatiotemporal parameters, derived from motion capture data pre- and post-treatment (physiotherapy, orthosis, botulin toxin injections, or surgery). Participants were labelled based on their change in gait profile score (GPS, non-responders with a decline in GPS of <1.6° vs. responders). Their pre-treatment features (sagittal joint angles, spatiotemporal parameters, anthropometrics) were used to train a support vector machine classifier with 5-fold cross-validation and Bayesian optimization within a MATLAB-based Classification Learner App. Results: An average accuracy of 88.2 ± 0.5 % was achieved for identifying participants whose gait will not respond to treatment, with 64 % true negative rate and an area under the curve of 88 %. Conclusion: Overall, a classical machine learning model was able to identify patients at risk of not responding to treatment, based on gait features and anthropometrics collected prior to treatment. The output of such a model could function as a warning signal, notifying clinicians that a certain individual might not respond well to the standard of care and that a more personalized intervention might be needed.ISSN:2405-844

Towards validation and standardization of automatic gait event identification algorithms for use in paediatric pathological populations

Background: To analyse and interpret gait patterns in pathological paediatric populations, accurate determination of the timing of specific gait events (e.g. initial contract – IC, or toe-off – TO) is essential. As currently used clinical identification methods are generally subjective, time-consuming, or limited to steps with force platform data, several techniques have been proposed based on processing of marker kinematics. However, until now, validation and standardization of these methods for use in diverse gait patterns remains lacking. Research questions: 1) What is the accuracy of available kinematics-based identification algorithms in determining the timing of IC and TO for diverse gait signatures? 2) Does automatic identification affect interpretation of spatio-temporal parameters?. Methods: 3D kinematic and kinetic data of 90 children were retrospectively analysed from a clinical gait database. Participants were classified into 3 gait categories: group A (toe-walkers), B (flat IC) and C (heel IC). Five kinematic algorithms (one modified) were implemented for two different foot marker configurations for both IC and TO and compared with clinical (visual and force-plate) identification using Bland-Altman analysis. The best-performing algorithm-marker configuration was used to compute spatio-temporal parameters (STP) of all gait trials. To establish whether the error associated with this configuration would affect clinical interpretation, the bias and limits of agreement were determined and compared against inter-trial variability established using visual identification. Results: Sagittal velocity of the heel (Group C) or toe marker configurations (Group A and B) was the most reliable indicator of IC, while the sagittal velocity of the hallux marker configuration performed best for TO. Biases for walking speed, stride time and stride length were within the respective inter-trial variability values. Significance: Automatic identification of gait events was dependent on algorithm-marker configuration, and best results were obtained when optimized towards specific gait patterns. Our data suggest that correct selection of automatic gait event detection approach will ensure that misinterpretation of STPs is avoided

Impact of the Marker Set Configuration on the Accuracy of Gait Event Detection in Healthy and Pathological Subjects

For interpreting outcomes of clinical gait analysis, an accurate estimation of gait events, such as initial contact (IC) and toe-off (TO), is essential. Numerous algorithms to automatically identify timing of gait events have been developed based on various marker set configurations as input. However, a systematic overview of the effect of the marker selection on the accuracy of estimating gait event timing is lacking. Therefore, we aim to evaluate (1) if the marker selection influences the accuracy of kinematic algorithms for estimating gait event timings and (2) what the best marker location is to ensure the highest event timing accuracy across various gait patterns. 104 individuals with cerebral palsy (16.0 ± 8.6 years) and 31 typically developing controls (age 20.6 ± 7.8) performed clinical gait analysis, and were divided into two out of eight groups based on the orientation of their foot, in sagittal and frontal plane at mid-stance. 3D marker trajectories of 11 foot/ankle markers were used to estimate the gait event timings (IC, TO) using five commonly used kinematic algorithms. Heatmaps, for IC and TO timing per group were created showing the median detection error, compared to detection using vertical ground reaction forces, for each marker. Our findings indicate that median detection errors can be kept within 7 ms for IC and 13 ms for TO when optimizing the choice of marker and detection algorithm toward foot orientation in midstance. Our results highlight that the use of markers located on the midfoot is robust for detecting gait events across different gait patterns.ISSN:1662-516

Towards validation and standardization of automatic gait event identification algorithms for use in paediatric pathological populations

Background: To analyse and interpret gait patterns in pathological paediatric populations, accurate determination of the timing of specific gait events (e.g. initial contract – IC, or toe-off – TO) is essential. As currently used clinical identification methods are generally subjective, time-consuming, or limited to steps with force platform data, several techniques have been proposed based on processing of marker kinematics. However, until now, validation and standardization of these methods for use in diverse gait patterns remains lacking. Research questions: 1) What is the accuracy of available kinematics-based identification algorithms in determining the timing of IC and TO for diverse gait signatures? 2) Does automatic identification affect interpretation of spatio-temporal parameters?. Methods: 3D kinematic and kinetic data of 90 children were retrospectively analysed from a clinical gait database. Participants were classified into 3 gait categories: group A (toe-walkers), B (flat IC) and C (heel IC). Five kinematic algorithms (one modified) were implemented for two different foot marker configurations for both IC and TO and compared with clinical (visual and force-plate) identification using Bland-Altman analysis. The best-performing algorithm-marker configuration was used to compute spatio-temporal parameters (STP) of all gait trials. To establish whether the error associated with this configuration would affect clinical interpretation, the bias and limits of agreement were determined and compared against inter-trial variability established using visual identification. Results: Sagittal velocity of the heel (Group C) or toe marker configurations (Group A and B) was the most reliable indicator of IC, while the sagittal velocity of the hallux marker configuration performed best for TO. Biases for walking speed, stride time and stride length were within the respective inter-trial variability values. Significance: Automatic identification of gait events was dependent on algorithm-marker configuration, and best results were obtained when optimized towards specific gait patterns. Our data suggest that correct selection of automatic gait event detection approach will ensure that misinterpretation of STPs is avoided.Biomechatronics & Human-Machine Contro

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P=1 × 10) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P=8.4 × 10). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies