A coaxial excitation, dual-red-green-blue/near-infrared paired imaging system toward computer-aided detection of parathyroid glands in situ and ex vivo

• Type of Material: Article
• Authors: Yoseph Kim, Johns Hopkins University; Hun Chan Lee, Boston University; Jongchan Kim, Children’s National Hospital; Eugene Oh, Johns Hopkins University; Jennifer Yoo, Children’s National Hospital; Bo Ning, Children’s National Hospital; Seung Lee, Emory University; Khalid Mohamed Ali, Johns Hopkins University; Ralph P. Tufano, Johns Hopkins University; Jonathon O. Russell, Johns Hopkins University; Jaepyeong Cha, Optosurgical LLC
• Language: English
• Date: 2022-04-20
• Publisher: WILEY-V C H VERLAG GMBH
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2022 Wiley-VCH GmbH.
• Final Published Version (URL): http://dx.doi.org/10.1002/jbio.202200008
• Title of Journal or Parent Work: JOURNAL OF BIOPHOTONICS
• Volume: 15
• Issue: 8
• Start Page: e202200008
• End Page: e202200008
• Grant/Funding Information: Research reported in this publication was supported by the National Institute of Biomedical Imaging and Bioengineering and National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under Award Number R43EB030874, R41EB032284, R41DK131650, Johns Hopkins University FastForward U 2021 Summer MedTech Award, and Children’s National Hospital SPF44215PID30005967. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
• Keywords: Physical Sciences; THYROIDECTOMY; near-infrared autofluorescence; COMPLICATIONS; Biophysics; hypocalcemia; IMPACT; VOLUME; Science & Technology; LOCALIZATION; OUTCOMES; thyroid surgery; deep learning; Life Sciences & Biomedicine; Biochemical Research Methods; parathyroid glands; Optics; Biochemistry & Molecular Biology; IDENTIFICATION
• Research Categories: Chemistry, Biochemistry; Biology, Molecular; Biophysics, Medical

Abstract

Early and precise detection of parathyroid glands (PGs) is a challenging problem in thyroidectomy due to their small size and similar appearance to surrounding tissues. Near-infrared autofluorescence (NIRAF) has stimulated interest as a method to localize PGs. However, high incidence of false positives for PGs has been reported with this technique. We introduce a prototype equipped with a coaxial excitation light (785 nm) and a dual-sensor to address the issue of false positives with the NIRAF technique. We test the clinical feasibility of our prototype in situ and ex vivo using sterile drapes on 10 human subjects. Video data (1287 images) of detected PGs were collected to train, validate and compare the performance for PG detection. We achieved a mean average precision of 94.7% and a 19.5-millisecond processing time/detection. This feasibility study supports the effectiveness of the optical design and may open new doors for a deep learning-based PG detection method.