# Feasibility of an MR-based digital specimen for tongue cancer resection specimens: a novel approach for margin evaluation

## TL;DR

This study introduces a new MR-based digital specimen method to help surgeons evaluate resection margins in tongue cancer surgery.

## Contribution

The novel use of high-field MR imaging to create 3D digital specimens for real-time margin evaluation during cancer surgery.

## Key findings

- MR-based digital specimens showed higher sensitivity than specificity for detecting inadequate margins.
- Radiologists tended to overestimate tumor size, affecting diagnostic accuracy.
- The method demonstrated potential for improving surgical margin assessment in tongue cancer.

## Abstract

This study explores the feasibility of ex-vivo high-field magnetic resonance (MR) imaging to create digital a three-dimensional (3D) representations of tongue cancer specimens, referred to as the “MR-based digital specimen” (MR-DS). The aim was to create a method to assist surgeons in identifying and localizing inadequate resection margins during surgery, a critical factor in achieving locoregional control.

Fresh resection specimens of nine tongue cancer patients were imaged in a 7 Tesla small-bore MR, using a high-resolution multislice and 3D T2-weighted Turbo Spin Echo. Two independent radiologists (R1 and R2) outlined the tumor and mucosa on the MR-images whereafter the outlines were configured to an MR-DS. A color map was projected on the MR-DS, mapping the inadequate margins according to R1 and R2. We compared the hematoxylin-eosin-based digital specimen (HE-DS), which is a histopathological 3D representation derived from HE stained sections, with its corresponding MR-images. In line with conventional histopathological assessment, all digital specimens were divided into five anatomical regions (anterior, posterior, craniomedial, caudolateral and deep central). Over- and underestimation 95th-percentile Hausdorff-distances were calculated between the radiologist- and histopathologist-determined tumor outlines. The MR-DS’ diagnostic accuracy for inadequate margin detection (i.e. sensitivity and specificity) was determined in two ways: with conventional histopathology and HE-DS as reference.

Using conventional histopathology as a reference, R1 achieved 77% sensitivity and 50% specificity, while R2 achieved 65% sensitivity and 57% specificity. When referencing to the HE-DS, R1 achieved 94% sensitivity and 61% specificity, while R2 achieved 88% sensitivity and 71% specificity. Range of over- and underestimation 95HD was 0.9 mm - 11.8 mm and 0.0 mm - 5.3 mm, respectively.

This proof of concept for volumetric assessment of resection margins using MR-DSs, demonstrates promising potential for further development. Overall, sensitivity is higher than specificity for inadequate margin detection, because of the radiologist’s tendency to overestimate tumor size.