Abstract
Abstract Purpose Optical coherence tomography (OCT) is an attractive technology for surgical imaging because it permits the real-time visualization of microscopic tissue morphology with a handheld probe without the need for exogeneous agents, tissue manipulation, ionizing radiation, or histological processing. While initial studies have shown that OCT is an effective margin-evaluation tool for breast conserving surgery (BCS), image interpretation and feature identification have not been directly studied. In this work, breast pathologies were assessed with a handheld OCT probe and the images were compared to histology. Methods Mastectomy and BCS specimens from 26 women were imaged with a handheld OCT probe, and histology slides from the same region were digitally photographed. OCT and histology images from the same region were paired by selecting the best structural matches. Because image characteristics in OCT are akin to those in ultrasound, descriptive OCT image feature terminology similar to that of ultrasound was developed. Each of these characteristics was used to select and describe OCT-histology image matches. Results In total, 2880 OCT images were acquired from 26 breast specimens, and 48 matching OCT-histology image pairs were identified. These matched image pairs illustrate tissue types including adipose tissue, dense fibrosis, fibroadipose tissue, blood vessels, regular and hyperplastic ducts and lobules, cysts, fibroadenoma, IDC, ILC, DCIS, calcifications, and biopsy cavities. Differentiation between pathologies was achieved by considering feature boundaries, interior appearance, posterior shadowing or enhancement, and overall morphologic patterns. Conclusions This is the first work to systematically catalog the features of breast OCT images. The results indicate that OCT can be used to identify important structures and distinguish between benign and malignant breast pathologies. Citation Format: Yemul KS, Zysk AM, Richardson AL, Tangella KV, Jacobs LK. Interpretation schema for optical coherence tomography images in breast tissue [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P6-02-03.
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