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Simplifying the assessment of human breast cancer by mapping a micro‐scale heterogeneity index in optical coherence elastography
Authors:Lixin Chin  Bruce Latham  Christobel M Saunders  David D Sampson  Brendan F Kennedy
Affiliation:1. Optical+Biomedical Engineering Laboratory, School of Electrical, Electronic & Computer Engineering, The University of Western Australia, Perth, Australia;2. BRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands, Perth, Australia;3. PathWest, Fiona Stanley Hospital, Murdoch, Australia;4. School of Surgery, The University of Western Australia, Perth, Australia;5. Breast Clinic, Royal Perth Hospital, Perth, Australia;6. Centre for Microscopy, Characterisation & Analysis, The University of Western Australia, Perth, Australia
Abstract:Surgical treatment of breast cancer aims to identify and remove all malignant tissue. Intraoperative assessment of tumor margins is, however, not exact; thus, re‐excision is frequently needed, or excess normal tissue is removed. Imaging methods applicable intraoperatively could help to reduce re‐excision rates whilst minimizing removal of excess healthy tissue. Optical coherence elastography (OCE) has been proposed for use in breast‐conserving surgery; however, intraoperative interpretation of complex OCE images may prove challenging. Observations of breast cancer on multiple length scales, by OCE, ultrasound elastography, and atomic force microscopy, have shown an increase in the mechanical heterogeneity of malignant breast tumors compared to normal breast tissue. In this study, a micro‐scale mechanical heterogeneity index is introduced and used to form heterogeneity maps from OCE scans of 10 ex vivo human breast tissue samples. Through comparison of OCE, optical coherence tomography images, and corresponding histology, malignant tissue is shown to possess a higher heterogeneity index than benign tissue. The heterogeneity map simplifies the contrast between tumor and normal stroma in breast tissue, facilitating the rapid identification of possible areas of malignancy, which is an important step towards intraoperative margin assessment using OCE.

Keywords:optical coherence elastography  breast cancer  tumor margins  mechanical heterogeneity  signal processing  visualization  optical coherence tomography
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