Advances in rapid parathyroid gland identification: clinical significance and emerging handheld imaging technologies

Abstract

Accurate intraoperative identification of parathyroid glands is essential to prevent postoperative hypocalcemia and persistent hyperparathyroidism. This review addressed the current challenges associated with parathyroid gland identification, evaluated traditional and emerging imaging techniques, and discussed innovative developments, including portable and smartphone-based near-infrared autofluorescence (NIRAF) technologies. Conventional methods, such as ultrasound, 99mTc-sestamibi scanning, computerized tomography (CT)/ magnetic resonance imaging (MRI), intraoperative parathyroid hormone (ioPTH) monitoring, and frozen-section pathology, have limitations including time delays, operator dependency, and varying accuracy. Recent advancements utilizing NIRAF have shown promising results, significantly reducing the rates of postoperative hypocalcemia, permanent gland dysfunction, and inadvertent gland removal, with reported sensitivities and specificities exceeding 95% in various clinical settings. Emerging portable and handheld autofluorescence devices, notably prototypes like the hANDY-I and costeffective smartphone-based solutions, demonstrate substantial potential for real-time, surgeon-operated gland identification. Integration with machine learning algorithms and augmented reality further enhances diagnostic accuracy and accessibility, particularly valuable in resource-limited environments and in surgical training. To facilitate widespread adoption, future developments must prioritize device optimization, rigorous clinical validation, regulatory approvals, and standardization. Continued interdisciplinary collaboration among surgeons, engineers, data scientists, and healthcare policymakers is critical for translating these technological advancements into improved patient outcomes and equitable surgical care globally.