Abstract

Primary hyperparathyroidism, often caused by a single adenoma (80-85%) or four-gland hyperplasia (10-15%), can lead to elevated parathyroid hormone (PTH) levels and resultant hypercalcemia. Surgical excision of offending lesions is the standard of care, as the removal of pathologic adenomas reduces PTH and calcium values to baseline. The small size, variable location, and indistinct external features of parathyroid glands can make their identification quite challenging intraoperatively. Our group has developed the dynamic optical contrast imaging (DOCI) technique, a novel realization of dynamic temporally dependent measurements of tissue autofluorescence. In this study, we evaluated the efficacy of using the DOCI technique and normalized steady-state fluorescence intensity data for differentiating types of human parathyroid and thyroid tissues. We demonstrate that the DOCI technique has the capability to distinguish normal parathyroid tissue from diseased parathyroid glands as well as from adjacent healthy thyroid and adipose tissue across 8 different spectral channels between 405nm-600nm (p<0.05). Patient tissue DOCI data was further analyzed with a logistic regression classifier trained across the 8 spectral channels. After computer training, the computer-aided identification was able to accurately locate hypercellular parathyroid tissue with 100% sensitivity and 98.8% specificity within the captured DOCI image.

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