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Fast label-free multilayered histology-like imaging of human breast cancer by photoacoustic microscopy
Author(s) -
Terence T. W. Wong,
Ruiying Zhang,
Pengfei Hai,
Chi Zhang,
Miguel A. Pleitez,
Rebecca Aft,
Deborah V. Novack,
Lihong V. Wang
Publication year - 2017
Publication title -
science advances
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.928
H-Index - 146
ISSN - 2375-2548
DOI - 10.1126/sciadv.1602168
Subject(s) - lumpectomy , histology , photoacoustic imaging in biomedicine , microscopy , breast cancer , biomedical engineering , cancer , human breast , surgical margin , margin (machine learning) , medicine , materials science , mastectomy , pathology , computer science , optics , physics , machine learning
The goal of breast-conserving surgery is to completely remove all of the cancer. Currently, no intraoperative tools can microscopically analyze the entire lumpectomy specimen, which results in 20 to 60% of patients undergoing second surgeries to achieve clear margins. To address this critical need, we have laid the foundation for the development of a device that could allow accurate intraoperative margin assessment. We demonstrate that by taking advantage of the intrinsic optical contrast of breast tissue, photoacoustic microscopy (PAM) can achieve multilayered histology-like imaging of the tissue surface. The high correlation of the PAM images to the conventional histologic images allows rapid computations of diagnostic features such as nuclear size and packing density, potentially identifying small clusters of cancer cells. Because PAM does not require tissue processing or staining, it can be performed promptly and intraoperatively, enabling immediate directed re-excision and reducing the number of second surgeries.

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