NIR autofluorescence allows for pituitary gland detection during surgery: the first evidence from microscopic studies and in vivo measurements

Abstract

A critical challenge in endocrine neurosurgery is intraoperative discrimination between normal pituitary tissue and pituitary neuroendocrine tumors (PitNETs). Suggesting the universal persistence of near-infrared autofluorescence (NIRAF) in endocrine organs and inspired by routine clinical use of NIRAF for parathyroid gland identification, we discovered that pituitary NIRAF can be employed for label-free transsphenoidal surgery guidance. Ex vivo confocal spectral imaging of 33 specimens identified secretory granules as the dominant long-wavelength fluorescence source and showed that normal pituitary had higher granule content than PitNETs. For the first time, we made use of the pituitary NIRAF during surgery and assessed its performance for pituitary/adenoma separation in vivo for 27 surgeries and showed near-perfect separability between pituitary and non-pituitary measurement sites with ROC-AUC of 0.98. The obtained results clearly demonstrate that the suggested method, based on the solid microscopic background, has the potential for clinical translation and paves the way for enhanced gland preservation during resection.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This work was supported by Russian Science Foundation (Grant no. 25-75-10082).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Local Ethics Committee of the Federal State Budgetary Institution National Medical Research Center for Endocrinology named after Academician I.I. Dedov of the Ministry of Health of the Russian Federation gave ethical approval for this work. Approval was granted under Protocol No. 17 dated 10 September 2025.

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Yes

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Data Availability

The datasets generated and analyzed during the current study are not publicly available due to ethical and legal restrictions related to patient confidentiality. All summary data necessary to evaluate the conclusions are presented in the manuscript.

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