3D Ultrasound and MRI in Assessing Resection Margins during Tongue Cancer Surgery: A Research Protocol for a Clinical Diagnostic Accuracy Study

Author:

Makouei Fatemeh12ORCID,Agander Tina Klitmøller3,Ewertsen Caroline24,Søndergaard Svendsen Morten Bo56,Norling Rikke4,Kaltoft Mikkel1ORCID,Hansen Adam Espe24ORCID,Rasmussen Jacob Høygaard12,Wessel Irene12,Todsen Tobias125

Affiliation:

1. Department of Otorhinolaryngology, Head and Neck Surgery and Audiology, Rigshospitalet, Copenhagen University Hospital, DK-2100 Copenhagen, Denmark

2. Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen, Denmark

3. Department of Pathology, Rigshospitalet, Copenhagen University Hospital, DK-2100 Copenhagen, Denmark

4. Department of Radiology, Rigshospitalet, Copenhagen University Hospital, DK-2100 Copenhagen, Denmark

5. Copenhagen Academy for Medical Education and Simulation, The Capital Region of Denmark, DK-2100 Copenhagen, Denmark

6. Department of Computer Science, University of Copenhagen, 2100 Copenhagen, Denmark

Abstract

Surgery is the primary treatment for tongue cancer. The goal is a complete resection of the tumor with an adequate margin of healthy tissue around the tumor.Inadequate margins lead to a high risk of local cancer recurrence and the need for adjuvant therapies. Ex vivo imaging of the resected surgical specimen has been suggested for margin assessment and improved surgical results. Therefore, we have developed a novel three-dimensional (3D) ultrasound imaging technique to improve the assessment of resection margins during surgery. In this research protocol, we describe a study comparing the accuracy of 3D ultrasound, magnetic resonance imaging (MRI), and clinical examination of the surgical specimen to assess the resection margins during cancer surgery. Tumor segmentation and margin measurement will be performed using 3D ultrasound and MRI of the ex vivo specimen. We will determine the accuracy of each method by comparing the margin measurements and the proportion of correctly classified margins (positive, close, and free) obtained by each technique with respect to the gold standard histopathology.

Funder

Innovation Fund Denmark—InnoExplorer

Novo Nordisk Foundation

BetaHealth

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging

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