Automatic Identification of Ultrasound Images of the Tibial Nerve in Different Ankle Positions Using Deep Learning.

Peripheral nerve tension is known to be related to the pathophysiology of neuropathy; however, assessing this tension is difficult in a clinical setting. In this study, we aimed to develop a deep learning algorithm for the automatic assessment of tibial nerve tension using B-mode ultrasound imaging. To develop the algorithm, we used 204 ultrasound images of the tibial nerve in three positions: the maximum dorsiflexion position and -10° and -20° plantar flexion from maximum dorsiflexion.

Tibial nerve dynamics during ankle dorsiflexion: The relationship between stiffness and excursion of the tibial nerve.

Peripheral nerves extend with a gradual increase in stiffness and also with excursion, namely reduction of fiber bundle waviness, to adapt to joint movements. Although the close relationships between the tibial nerve (TN) excursion and stiffness during ankle dorsiflexion in cadaver studies, the precise in vivo their relationships remain unclear. We hypothesized that the excursion of the TN can be estimated from its stiffness in vivo using shear-wave elastography.

Changes in tibial nerve stiffness during ankle dorsiflexion according to in-vivo analysis with shear wave elastography.

A more detailed assessment of pathological changes in the tibial nerve (TN) is needed to better assess how physical therapy influences TN pathologies. The cross-sectional nerve area can be used for TN assessment but may be influenced by individual differences in parameters, such as body height, body weight, and foot length. Therefore, there are no known reliable noninvasive quantitative methods for assessing TN neuropathy.