Home » homeblock » NEUROLOGICAL AND NEUROMUSCULAR DISEASES (NND)

The most common paediatric disorder within the NND disease area is Cerebral Palsy (CP) whose incidence ranges between 2 to 3.6 per 1,000 live births. The second important disorder is Spinal Muscular Atrophy (SMA). [...]

  Read the Clinical Application Scenario - Download the Clinical Gait Analysis Protocol 

Clinical Concept:

In Neurological and Neuromuscular Diseases (NND) as well as in certain chronic paediatric diseases of the musculoskeletal system, treatments are strongly guided by maximising the walking function of the human movement system, because walking is considered as clinically meaningful by patients. This generalises to most mobility‐related functions. The most common paediatric disorder within the NND disease area is Cerebral Palsy (CP) whose incidence ranges between 2 to 3.6 per 1,000 live births . CP includes a group of non‐progressive, often changing, motor impairment syndromes, secondary to lesions in the sensory-motor cortex and corticospinal tract, arising in the early stages of the child’s development. Conventional clinical gait analysis (CGA) is already an important tool in the treatment of children with CP that aims to improve or sustain walking performance, but its potential is under-utilised and recent developments need full exploration. The second important disorder is Spinal Muscular Atrophy (SMA), an autosomal recessive disease characterised by degeneration of motoneurons in the spinal cord. SMA is caused by mutations of the survival motor neuron 1 gene (SMN1). Estimated incidence is 1 in 8,000 live births. This disease is characterised by progressive generalised muscle weakness and atrophy predominating in proximal limb muscles. For ambulant SMA patients, new methods for functional motor evaluation based on gait modelling would allow to increase sensitivity to change in assessing weakness and fatigability. The third disorder, Duchenne Muscular Dystrophy (DMD) is the most common and severe form of muscular dystrophy, with anincidence around 1 in 3,600 juveniles. This disorder is caused by a mutation in the dystrophin gene, that codes for a protein which is a major structural component of the muscle. The absence of dystrophin results in muscle degeneration, difficulty in walking (resulting in wheelchair use from 14 years of age), followed by loss of arms and hands function. In the last few years, following a rapidly increasing number of potentially effective therapeutic approaches for DMD, the request for validated and sensitive outcome measures to be used in clinical trials has increased.

Although walking is a common task executed by a healthy individual in a seemingly effortless manner, it implies a complex involvement of inputs from several senses (visual, vestibular, proprioceptive, somatosensory), partly automated by the so called spinal central pattern generator (CPG). These inputs are known to interact with each other, but the way in which this is performed is not fully exploited at present. Nevertheless, the current insights are certainly at an advanced state that allows for meaningful application towards pathological walking, where decision support is needed. In the clinical practice of specialised centres, CGA is used to evaluate the joint and muscle functions in their functional context, i.e. during gait.

CGA is a special form of personalised computer-aided medicine that supports clinical decision making. Unfortunately, the output of CGA is not yet in a format that permits clear, unambiguous interpretation, because of the redundancy of the Neuro-Musculo-Skeletal System (NMSS) which obstructs distinguishing cause from compensation. Even though recent developments in modelling the NMS Physiome as a part of EU funded Virtual Physiological Human efforts are at an advanced state, their results have not yet been implemented in clinical practice, and the full potential of CGA still needs to be reaped.

MD-Paedigree Goals:

MD-Paedigree will develop and evaluate a scaling method for children, to be applied in existing NMS models used in clinical gait analysis (CGA), taking into account subject specific bony deformities. Also antropometric measures and DXA will be explored and pathology specific muscle parameters will be taken into account.

MD-Paedigree will  re-use the HBM Motek model for real time CGA, in order to assess the function and performance of the underlying muscle activation, muscle forces, and joint loads to unravel the aetiology of the pathological gait pattern of patients.

MD-Paedigree will also re-use NMS Physiome (derived from the VPHOP and the NIH funded SIMBIOS projects).

Finally, MD-Paedigree will integrate the pre‐processing of imaging and gait analysis data into a full musculoskeletal model through NMS Builder and the OpenSIM musculoskeletal modelling environment to attain 3 disease-specific predictive biomechanical models supporting:

  • Ethiopatological speculation
  • More effective scoring of disease severity
  • Treatment planning

 

md-paedigree twitter page
md-paedigree secure
md-paedigree call
MD-Paedigree Infostructure