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

Authors

Yoseph Kim, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Hun Chan Lee, Department of Mechanical Engineering, Boston University, Boston, Massachusetts, USA.
Jongchan Kim, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC, USA.
Eugene Oh, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Jennifer Yoo, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC, USA.
Bo Ning, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC, USA.
Seung Yup Lee, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA.
Khalid Mohamed Ali, Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Ralph P. Tufano, Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Jonathon O. Russell, Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Jaepyeong Cha, R&D Division, Optosurgical, LLC, Laurel, Maryland, USA.

Document Type

Journal Article

Publication Date

3-27-2022

Journal

Journal of biophotonics

DOI

10.1002/jbio.202200008

Keywords

deep learning; hypocalcemia; near-infrared autofluorescence; parathyroid glands; thyroid surgery

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.

APA Citation

Kim, Yoseph; Lee, Hun Chan; Kim, Jongchan; Oh, Eugene; Yoo, Jennifer; Ning, Bo; Lee, Seung Yup; Ali, Khalid Mohamed; Tufano, Ralph P.; Russell, Jonathon O.; and Cha, Jaepyeong, "A coaxial excitation, dual-red-green-blue/near-infrared paired imaging system toward computer-aided detection of parathyroid glands in situ and ex vivo" (2022). GW Authored Works. Paper 536.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/536

Department

Pediatrics