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Diagnostic feasibility study of stereoscopic optical palpation for breast tumour margin assessment

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Optical elastography has been developed for intraoperative tumour margin assessment during breast-conserving surgery (BCS), based on the elevated stiffness of tumour. It aims to assist the surgeon in removing all cancerous tissue in a single operation, reducing re-excision surgeries and potentially lowering recurrence rate. In this study, we investigate the use of a new, cost‑effective method called stereoscopic optical palpation (SOP), a camera‑based optical elastography technique, for breast cancer detection. We tested its diagnostic feasibility on tissue samples from 48 patients. Experimental design: SOP was performed on the margins of freshly excised breast tissue from 48 patients. For each specimen, pairs of photographs were taken, and within two minutes, detailed stress maps were generated to show areas of mechanical pressure on the tissue surface. To evaluate SOP’s accuracy, selected regions of interest were analysed and co‑registered with standard histopathology results. These regions were randomly divided into 10 groups, and an automatic classifier was trained and tested using 10‑fold cross‑validation. Results: Histopathology showed that 11.3% of the analysed regions had cancer within 1 mm of the margin. Based on the stress maps acquired using SOP and the automatic classifier, the sensitivity of cancer detection near the margin is 82.1% and the specificity of identifying benign tissue is 83.6%. The mean stress threshold determined to identify positive margins is 10.1 kPa. Conclusion: This diagnostic feasibility study shows that SOP can achieve accurate cancer assessment within 1 mm of the tissue boundary. Its simplicity and low cost make SOP a promising tool for real-time tumour margin assessment during BCS.

Original languageEnglish
Article number1793
Number of pages11
JournalBMC Cancer
Volume25
Issue number1
Early online date19 Nov 2025
DOIs
Publication statusPublished - Dec 2025

Funding

FundersFunder number
ARC Australian Research Council IC210100056

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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