Dataset Information

Quantification of human upper extremity nerves and fascicular anatomy.

ABSTRACT: INTRODUCTION:In this study we provide detailed quantification of upper extremity nerve and fascicular anatomy. The purpose is to provide values and trends in neural features useful for clinical applications and neural interface device design. METHODS:Nerve cross-sections were taken from 4 ulnar, 4 median, and 3 radial nerves from 5 arms of 3 human cadavers. Quantified nerve features included cross-sectional area, minor diameter, and major diameter. Fascicular features analyzed included count, perimeter, area, and position. RESULTS:Mean fascicular diameters were 0.57?±?0.39, 0.6?±?0.3, 0.5?±?0.26?mm in the upper arm and 0.38?±?0.18, 0.47?±?0.18, 0.4?±?0.27?mm in the forearm of ulnar, median, and radial nerves, respectively. Mean fascicular diameters were inversely proportional to fascicle count. CONCLUSION:Detailed quantitative anatomy of upper extremity nerves is a resource for design of neural electrodes, guidance in extraneural procedures, and improved neurosurgical planning. Muscle Nerve 56: 463-471, 2017.

SUBMITTER: Brill NA

PROVIDER: S-EPMC5712902 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantification of human upper extremity nerves and fascicular anatomy.

Brill Natalie A NA Tyler Dustin J DJ

Muscle & nerve 20170401 3

<h4>Introduction</h4>In this study we provide detailed quantification of upper extremity nerve and fascicular anatomy. The purpose is to provide values and trends in neural features useful for clinical applications and neural interface device design.<h4>Methods</h4>Nerve cross-sections were taken from 4 ulnar, 4 median, and 3 radial nerves from 5 arms of 3 human cadavers. Quantified nerve features included cross-sectional area, minor diameter, and major diameter. Fascicular features analyzed inc ...[more]

PMID: 28006854

Similar Datasets

Project description:Background and objectivePrediction of voluntary upper extremity (UE) movement recovery is largely unknown in patients with little voluntary UE movement at admission. The present study aimed to investigate (1) the extent and variation of voluntary UE movement recovery, and (2) the best predictive model of the recovery of voluntary UE movement by clinical variables in patients with severe UE paresis.DesignProspective cohort study.Methods140 (out of 590) stroke patients with severe UE paresis completed all assessments. Voluntary UE movement was assessed using the UE subscale of the Stroke Rehabilitation Assessment of Movement (STREAM-UE). Two outcome measures, STREAM-UE scores at discharge (DC(STREAM-UE)) and changes between admission and discharge (?(STREAM-UE)), were investigated to represent the final states and improvement of the recovery of voluntary UE movement. Stepwise regression analyses were used to investigate 19 clinical variables and to find the best predictive models of the two outcome measures.ResultsThe participants showed wide variation in both DC(STREAM-UE) and ?(STREAM-UE). 3.6% of the participants almost fully recovered at discharge (DC(STREAM-UE) > 15). A large improvement (?(STREAM-UE) >= 10) occurred in 16.4% of the participants, while 32.9% of the participants did not have any improvement. The four predictors for the DC(STREAM-UE) (R(2) = 35.0%) were 'baseline STREAM-UE score', 'hemorrhagic stroke', 'baseline National Institutes of Health Stroke Scale (NIHSS) score', and 'cortical lesion excluding primary motor cortex'. The three predictors for the ?(STREAM-UE) (R(2) = 22.0%) were 'hemorrhagic stroke', 'baseline NIHSS score', and 'cortical lesion excluding primary motor cortex'.ConclusionsRecovery of voluntary UE movement varied widely in patients with severe UE paresis after stroke. The predictive power of clinical variables was poor. Both results indicate the complex nature of voluntary UE movement recovery in patients with severe UE paresis after stroke.

Dataset Information

Quantification of human upper extremity nerves and fascicular anatomy.

Publications

Quantification of human upper extremity nerves and fascicular anatomy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets