Improving the diagnosis of ductal carcinoma in situ with microinvasion without immunohistochemistry: An innovative method with H&E‐stained and multiphoton microscopy images

肌上皮细胞 病理 H&E染色 免疫组织化学 导管癌 染色 基质 细胞角蛋白 原位癌 医学 乳腺癌 癌症 原位 导管细胞 化学 内科学 有机化学
作者
Xiahui Han,Yulan Liu,Shouxin Zhang,Lianhuang Li,Liqin Zheng,Lida Qiu,Jianhua Chen,Zhenlin Zhan,Shu Wang,Wei Ma,Deyong Kang,Jianxin Chen
出处
期刊:International Journal of Cancer [Wiley]
卷期号:154 (10): 1802-1813 被引量:2
标识
DOI:10.1002/ijc.34855
摘要

Abstract Ductal carcinoma in situ with microinvasion (DCISM) is a challenging subtype of breast cancer with controversial invasiveness and prognosis. Accurate diagnosis of DCISM from ductal carcinoma in situ (DCIS) is crucial for optimal treatment and improved clinical outcomes. However, there are often some suspicious small cancer nests in DCIS, and it is difficult to diagnose the presence of intact myoepithelium by conventional hematoxylin and eosin (H&E) stained images. Although a variety of biomarkers are available for immunohistochemical (IHC) staining of myoepithelial cells, no single biomarker is consistently sensitive to all tumor lesions. Here, we introduced a new diagnostic method that provides rapid and accurate diagnosis of DCISM using multiphoton microscopy (MPM). Suspicious foci in H&E‐stained images were labeled as regions of interest (ROIs), and the nuclei within these ROIs were segmented using a deep learning model. MPM was used to capture images of the ROIs in H&E‐stained sections. The intensity of two‐photon excitation fluorescence (TPEF) in the myoepithelium was significantly different from that in tumor parenchyma and tumor stroma. Through the use of MPM, the myoepithelium and basement membrane can be easily observed via TPEF and second‐harmonic generation (SHG), respectively. By fusing the nuclei in H&E‐stained images with MPM images, DCISM can be differentiated from suspicious small cancer clusters in DCIS. The proposed method demonstrated good consistency with the cytokeratin 5/6 (CK5/6) myoepithelial staining method (kappa coefficient = 0.818).
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