Needle-I – “seeing” what tissue types surround a needle tip

Business opportunity

Nerve injuries related to peripheral nerve blocks can be caused by toxicity of the injected solution or by mechanical nerve damage. In the worst cases, nerve damage can lead to persistent motor or sensory impairment and debilitating neuropathic pain. Thus, it is highly important to avoid such iatrogenic injuries. Ultrasound guidance, electrical nerve stimulation, and injection pressure measurements are used to reduce the risk of intraneural needle placement and injection and a combination of these methods is recommended in peripheral nerve blocks. However, the reliability of these methods to reduce the incidence of nerve injuries has not been demonstrated. We propose to supplement ultrasound guidance with a novel method based on electrical bioimpedance to reliably identify and discriminate nerve tissue from other tissue types in peripheral nerve blocks. The method is proven in animal studies.

Inven2 seeks development partners and/or licensees for the technology.

Technology description

Impedance is a measure of the opposition of the flow of alternating current (similar to the resistance of a conductor to direct current) and is given as a complex number that can be described as a vector defined by the modulus and the phase angle. Based on various impedance variables and multiple frequency measurements, researchers at Oslo University Hospital have developed a method to discriminate nerve tissue from other tissue types and detect intraneural needle placement in peripherial nerve blocks with very high sensitivity and specificity (ROC=97% in animal model). Clinical studies in humans are needed to confirm the results.

Advantages

Non-invasive guidance reducing risk of nerve injuries in peripheral nerve blocks.

Publications

H. Kalvøy, A. Sauter, Detection of intraneural needle-placement with multiple frequency bioimpedance monitoring: a novel method, J Clin Monit Comput DOI 10.1007/s10877-015-9698-3

H. Kalvøy et al., Detection of needle to nerve contact based on electric bioimpedance and machine learning methods, https://pubmed.ncbi.nlm.nih.gov/29059798/

Pending patent application WO2016055666A1

Elin Melby Ph.D

Elin Melby Ph.D

Technology Strategy Manager

Innovation

+47 95 20 70 71

elin.melby@inven2.com