| Literature DB >> 33583122 |
Emmanuel A Mannoh1,2, Logan B Parker1,2, Giju Thomas1,2, Carmen C Solórzano3, Anita Mahadevan-Jansen1,2.
Abstract
During thyroid surgeries, it is important for surgeons to accurately identify healthy parathyroid glands and assess their vascularity to preserve their function postoperatively, thus preventing hypoparathyroidism and hypocalcemia. Near infrared autofluorescence detection enables parathyroid identification, while laser speckle contrast imaging allows assessment of parathyroid vascularity. Here, we present an imaging system combining the two techniques to perform both functions, simultaneously and label-free. An algorithm to automate the segmentation of a parathyroid gland in the fluorescence image to determine its average speckle contrast is also presented, reducing a barrier to clinical translation. Results from imaging ex vivo tissue samples show that the algorithm is equivalent to manual segmentation. Intraoperative images from representative procedures are presented showing successful implementation of the device to identify and assess vascularity of healthy and diseased parathyroid glands.Entities:
Keywords: clinical translation; laser speckle contrast imaging; near-infrared autofluorescence; parathyroid; parathyroidectomy; surgical guidance; thyroidectomy
Mesh:
Year: 2021 PMID: 33583122 PMCID: PMC8556476 DOI: 10.1002/jbio.202100008
Source DB: PubMed Journal: J Biophotonics ISSN: 1864-063X Impact factor: 3.207