Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue using Deep Learning.
Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue using Deep Learning.
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DOI：
10.34133/2022/9786242
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Ozcan A
中科院分区：
文献类型：
--
作者：
Bai B;Wang H;Li Y;de Haan K;Colonnese F;Wan Y;Zuo J;Doan NB;Zhang X;Zhang Y;Li J;Yang X;Dong W;Darrow MA;Kamangar E;Lee HS;Rivenson Y;Ozcan A
人表皮生长因子受体2（HER 2）生物标志物的免疫组织化学（IHC）染色广泛应用于乳腺组织分析、临床前研究和诊断决策，指导癌症治疗和发病机制研究。HER 2染色需要由组织技术专家进行费力的组织处理和化学处理，这通常需要一天的时间在实验室中准备，增加了分析时间和相关成本。在这里，我们描述了一种基于深度学习的虚拟HER 2 IHC染色方法，该方法使用条件生成对抗网络，该网络经过训练，可将未标记/无标记乳腺组织切片的自发荧光显微图像快速转换为亮场等效显微图像，与在相同组织切片上进行的标准HER 2 IHC染色相匹配。通过定量分析证明了这种虚拟HER 2染色框架的有效性，其中三位委员会认证的乳腺病理学家对虚拟染色和化学染色的HER 2全载玻片图像（WSI）的HER 2评分进行盲分级，以揭示通过检查虚拟IHC图像确定的HER 2评分与化学染色的对应物一样准确。由相同诊断医师进行的第二项定量盲法研究进一步揭示，虚拟染色的HER 2图像在核细节水平、膜清晰度和不存在染色伪影方面与其化学染色的对应物表现出相当的染色质量。这种虚拟的HER 2染色框架绕过了实验室中昂贵、费力和耗时的IHC染色程序，并且可以扩展到其他类型的生物标志物，以加速生命科学和生物医学工作流程中使用的IHC组织染色。
The immunohistochemical (IHC) staining of the human epidermal growth factor receptor 2 (HER2) biomarker is widely practiced in breast tissue analysis, preclinical studies, and diagnostic decisions, guiding cancer treatment and investigation of pathogenesis. HER2 staining demands laborious tissue treatment and chemical processing performed by a histotechnologist, which typically takes one day to prepare in a laboratory, increasing analysis time and associated costs. Here, we describe a deep learning-based virtual HER2 IHC staining method using a conditional generative adversarial network that is trained to rapidly transform autofluorescence microscopic images of unlabeled/label-free breast tissue sections into bright-field equivalent microscopic images, matching the standard HER2 IHC staining that is chemically performed on the same tissue sections. The efficacy of this virtual HER2 staining framework was demonstrated by quantitative analysis, in which three board-certified breast pathologists blindly graded the HER2 scores of virtually stained and immunohistochemically stained HER2 whole slide images (WSIs) to reveal that the HER2 scores determined by inspecting virtual IHC images are as accurate as their immunohistochemically stained counterparts. A second quantitative blinded study performed by the same diagnosticians further revealed that the virtually stained HER2 images exhibit a comparable staining quality in the level of nuclear detail, membrane clearness, and absence of staining artifacts with respect to their immunohistochemically stained counterparts. This virtual HER2 staining framework bypasses the costly, laborious, and time-consuming IHC staining procedures in laboratory and can be extended to other types of biomarkers to accelerate the IHC tissue staining used in life sciences and biomedical workflow.
DOI：
10.1186/bcr3602
发表时间：
2014-01-23
期刊：
Breast cancer research : BCR
影响因子：
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作者：
De Giovanni C;Nicoletti G;Quaglino E;Landuzzi L;Palladini A;Ianzano ML;Dall'Ora M;Grosso V;Ranieri D;Laranga R;Croci S;Amici A;Penichet ML;Iezzi M;Cavallo F;Nanni P;Lollini PL
通讯作者：
Lollini PL