Handheld Autofluorescence Imaging System for Intraoperative Parathyroid Detection.

ABSTRACT

Introduction: Hypoparathyroidism and hypocalcemia are common complications after thyroid surgery. Parathyroids may be incidentally damaged or removed because they are difficult to distinguish from surrounding tissue. Intraoperative optical technologies such as near infrared autofluorescence (NIRAF) are becoming increasingly popular to help identify parathyroids during thyroid surgery. The objective of this video is to introduce a developing NIRAF device called hANDY-i and compare the device with existing Food and Drug Administration approved technology. Materials and Methods: hANDY-i is developed by Optosurgical, LLC. The device consists of a coaxial 785 nm laser excitation module and coregistred red-green-blue and near-infrared cameras. Operation of the device and output from preliminary intraoperative use are shown. Results: hANDY-i performs well, producing intuitive side-by-side NIRAF and RGB images of the operating field. The device demonstrates high contrast between suspected parathyroid glands and surrounding tissue. Operating theater, overhead lamps, and surgical headlights can all be used with the device. The device is also shown to be effective in both in vivo and ex vivo applications. Conclusions: The prototype described advance NIRAF technology by reducing light sensitivity and improving output representation. In doing so, hANDY-i makes NIRAF more accessible and less obstructive to the surgical workflow. Sources of Funding: This study was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under Award Number R43EB030874. Disclaimer The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.Yoseph Kim is an employee of Optosurgical LLC. Jaepyeong Cha has ownership stake in Optosurgical LLC. For all other authors, no competing financial interests exist.Runtime of video 7 mins 14 secs.