PublicationsDural Sac - Nerve Root



Nerve visualization and the identification of other neural tissues during surgery is crucial for numerous reasons, including the prevention of iatrogenic nerve and neural structure injury and facilitation of nerve repair. However, current methods of intra-operative nerve detection are generally expensive, unproven, and/or technically challenging. Recently, we have documented, in both in vivo animal models and ex vivo human tissue, that nerves autofluorescence when viewed in near-ultraviolet light (NUV). In this paper, we describe our use of nerve autofluorescence to facilitate the visualization of nerves and other neural tissues intra-operatively in 17 patients undergoing a range of surgical procedures.


Employing the same prototype axon imaging system previously documented to markedly enhance nerve visualization in both in vivo animal and ex vivo human models, surgical fields were observed in 17 patients under both white and NUV light during parotid tumor resection (n = 3), thyroid tumor resection (n = 7), and surgery for peripheral nerve and spinal tumors and injury (n = 7).


In all 17 patients, the intra-operative use of the imaging system both was feasible and markedly enhanced the localization of all neural tissues throughout their course within the surgical field. All 17 procedures were successful and devoid of any peri-operative complications or post-operative neurological deficits.


Intra-operatively visualizing auto-fluorescent peripheral nerves and other neural tissues under NUV light is feasible in human patients across a range of clinical scenarios and appears to appreciably enhance nerve and other neural tissue visualization. Controlled studies to explore this technology further are needed.


Dip F, Rosenthal D, Socolovsky M, Falco J, De la Fuente M, White KP, Rosenthal RJ. Nerve autofluorescence under near-ultraviolet light: cutting-edge technology for intra-operative neural tissue visualization in 17 patients. Surg Endosc. 2021 Oct 25. doi: 10.1007/s00464-021-08729-y. Epub ahead of print. PMID: 34694489.

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