KEYWORDS: RGB color model, Data modeling, Performance modeling, Surgery, Near infrared, Computer-aided diagnosis, Computer aided diagnosis and therapy, Imaging systems, Visual process modeling
Parathyroid glands (PGs), small endocrine glands in the neck, control calcium levels in the body and are crucial to maintaining homeostasis. Accidental removal of or direct damage to healthy parathyroid glands during thyroid surgery may occur due to its small size and similar appearance to surrounding anatomical structures, potentially leading to postoperative hypocalcemia. Thus precise and quick detection of normal parathyroid glands in real-time during surgery can improve the surgical outcome. In this study, we introduce a deep learning system (YOLOv5) based on dual RGB/NIR imaging for Computer-aided detection (CADe) of PG with high accuracy. This model can effectively detect parathyroid glands in real-time as it also includes the confidence level, which can help surgeons make decisions. We tested a computer-aided detection (CADe) using the co-registered RGB/NIR camera and ex-vivo thyroid tissue specimen. The average precisions of models were significantly higher when trained by the dual-RGB/NIR (0.99) data than NIR (0.94) and RGB (0.96) data alone at a high confidence threshold (0.7). The proposed CADe may increase the parathyroid detection rates clinically.
In thyroid surgeries, it is often difficult to visually distinguish parathyroid glands (PTGs) from their surrounding anatomical structures such as lymph nodes, fat, and thyroid tissues. There is a clear need to provide head and neck surgeons with intraoperative surgical guidance to safely distinguish PTGs and assess its viability to prevent the risk of hypocalcemia. This study aims to develop a portable hand-held imager that eliminates the need for complex set up for intraoperative imaging to increase the efficiency and performance for surgeons during thyroid surgeries. The performance of the device prototype was evaluated via in-vivo testing throughout preclinical studies.
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