BACKGROUND AND OBJECTIVE: The identification of parathyroid glands can be a major problem in parathyroid surgery. The purpose of this study was to evaluate the feasibility of optical coherence tomography (OCT) in distinguishing between parathyroid tissue, thyroid tissue, lymph nodes, and adipose tissue. METHODS: Ex vivo OCT images as well as histological sections were generated from parathyroid glands, thyroid tissue, lymph nodes and fat in order to define significant morphologic differences between these entities. As a second step all OCT images were separately evaluated by two blinded investigators and later compared to the corresponding histology. Sensitivity and specificity of OCT in distinguishing between the different tissues were determined. To assess the interobserver agreement, κ coefficients were calculated from the ratings of each investigator for each OCT image seen. RESULTS: A total of 320 OCT images from 32 patients undergoing thyroid surgery, parathyroidectomy or lymphadenectomy were compared with the corresponding histology. The sensitivity and specificity in distinguishing parathyroid tissue from the other entities was 84% (second investigator: 82%) and 94% (93%) respectively. Unweighted κ using four diagnostic categories was 0.97 (95% CI, 0.94-0.99) showing substantial agreement between both investigators. CONCLUSION: OCT is highly sensitive in distinguishing between parathyroid tissue, thyroid tissue, lymph nodes and adipose tissue. These ex vivo results should be confirmed by using OCT imaging intraoperatively.
BACKGROUND AND OBJECTIVE: The identification of parathyroid glands can be a major problem in parathyroid surgery. The purpose of this study was to evaluate the feasibility of optical coherence tomography (OCT) in distinguishing between parathyroid tissue, thyroid tissue, lymph nodes, and adipose tissue. METHODS: Ex vivo OCT images as well as histological sections were generated from parathyroid glands, thyroid tissue, lymph nodes and fat in order to define significant morphologic differences between these entities. As a second step all OCT images were separately evaluated by two blinded investigators and later compared to the corresponding histology. Sensitivity and specificity of OCT in distinguishing between the different tissues were determined. To assess the interobserver agreement, κ coefficients were calculated from the ratings of each investigator for each OCT image seen. RESULTS: A total of 320 OCT images from 32 patients undergoing thyroid surgery, parathyroidectomy or lymphadenectomy were compared with the corresponding histology. The sensitivity and specificity in distinguishing parathyroid tissue from the other entities was 84% (second investigator: 82%) and 94% (93%) respectively. Unweighted κ using four diagnostic categories was 0.97 (95% CI, 0.94-0.99) showing substantial agreement between both investigators. CONCLUSION: OCT is highly sensitive in distinguishing between parathyroid tissue, thyroid tissue, lymph nodes and adipose tissue. These ex vivo results should be confirmed by using OCT imaging intraoperatively.
Authors: Sandra Sommerey; Norah Al Arabi; Roland Ladurner; Constanza Chiapponi; Herbert Stepp; Klaus K J Hallfeldt; Julia K S Gallwas Journal: Surg Endosc Date: 2014-12-05 Impact factor: 4.584
Authors: Sarah J Erickson-Bhatt; Kelly J Mesa; Marina Marjanovic; Eric J Chaney; Adeel Ahmad; Pin-Chieh Huang; Z George Liu; Kelly Cunningham; Stephen A Boppart Journal: Transl Res Date: 2017-12-08 Impact factor: 7.012
Authors: Roland Ladurner; Sandra Sommerey; Nora Al Arabi; Klaus K J Hallfeldt; Herbert Stepp; Julia K S Gallwas Journal: Surg Endosc Date: 2016-11-14 Impact factor: 4.584
Authors: Giju Thomas; Melanie A McWade; Constantine Paras; Emmanuel A Mannoh; Melinda E Sanders; Lisa M White; James T Broome; John E Phay; Naira Baregamian; Carmen C Solórzano; Anita Mahadevan-Jansen Journal: Thyroid Date: 2018-09-11 Impact factor: 6.568
Authors: Marc Rubinstein; Allison C Hu; Phil-Sang Chung; Jason H Kim; Kathryn E Osann; Paul Schalch; William B Armstrong; Brian J F Wong Journal: Lasers Med Sci Date: 2020-04-27 Impact factor: 3.161