Keywords:
Musculoskeletal system, Radiographers, Ultrasound, Experimental, Computer Applications-Detection, diagnosis, Tissue characterisation
Authors:
P. Conde1, A. Silva1, M. Santos2, A. Silva1; 1Aveiro/PT, 2 Aveiro/PT
DOI:
10.1594/ecr2018/C-2061
Aims and objectives
Several studies have been conducted using ultrasonography to characterise how peripheral nerves respond and adapt to body movement (nerve biomechanics),
both in terms of quantity and direction as well as which factors affect nerve movement.
A systematic review showed that body movement might induce up to 12.
5 mm of nerve gliding,
which seem to vary according to range of motion for the moving joint,
position of adjacent joints,
number of moving joints and whether joint movement stretches or shortens nerve bed [1].
In addition,
the nerve cross-sectional area also seem to depend on the weight,
body mass index,
height and gender of the subjects [2].
Of potential clinical relevance is the fact that nerve movement seems to be affected by disease.
Changes in normal nerve biomechanics have been shown for several pathologies such as carpal tunnel syndrome,
cervical radiculopathy or epicondylitis,
suggesting a compromise of the adaptive mechanisms of the nervous system in these conditions.
For example,
individuals with type two diabetes seem to have a reduction of nerve elasticity,
which increases with the severity of the neuropathy and affects nerve conduction [3].
Furthermore,
the mean cross-sectional area of the tibial nerve in diabetic patients is larger than in controls (patients with diabetes: 6.1 ± 0.1 mm2; controls: 4.8 ± 0.2 mm2),
and seems to increase with increased severity of the neuropathy.
Furthermore,
it has already been shown that the pattern of nerve movement is different in older people with diabetes when compared with young and asymptomatic controls: participants with diabetes show a significant decrease in the quantity of longitudinal (0.8 ± 0.5 mm) and superficial nerve movement (1.0 ± 0.6 mm) when compared to healthy controls (2.2 ± 0.5 mm and 3.7 ± 1.5 mm,
respectively) [4].
Therefore,
ultrasonography shows promise as a potential diagnostic tool for pathology of the peripheral nervous system.
As a result,
the purpose of this work was to assess algorithms for the quantification of the displacement of peripheral nerve structures in response to joint movement using algorithms based on the Lucas-Kanade [5] optical flow method.