Chen Yongtai, Chu Jinkui, Lin Fanlu, Jiang Bing, Liu Yadong, Huang Bo, Zhang Ran, Xin Benda, Ding Xiaohan
School of Mechanical Engineering, Dalian University of Technology, Dalian, China.
Department of Urology, Linyi Central Hospital, Linyi, China.
J Biophotonics. 2023 Feb;16(2):e202200255. doi: 10.1002/jbio.202200255. Epub 2022 Nov 11.
Mueller matrix imaging polarimetry (MMIP) is a promising technique for the characterization of biological tissues, including the classification of microstructures in pathological diagnosis. To expand the parameter space of Mueller matrix parameters, we propose new vector parameters (VPs) according to the Mueller matrix polar decomposition method. We measure invasive bladder cancer (IBC) with extensive necrosis and high-grade ductal carcinoma in situ (DCIS) with MMIP, and the regions of cancer cells and fibrotic stroma are classified with the VPs. Then the proposed and existing VPs are mapped on the Poincaré sphere with 3D visualization, and an indicator of spatial feature is defined based on the minimum enclosing sphere to evaluate the classification capability of the VPs. For both IBC and DCIS, the results show that the proposed VPs exhibit evident contrast between the regions of cancer cells and fibrotic stroma. This study broadens the fundamental Mueller matrix parameters and helps to improve the characterization ability of the MMIP technique.
穆勒矩阵成像偏振测量法（MMIP）是一种用于生物组织表征的很有前景的技术，包括在病理诊断中对微观结构进行分类。为了扩展穆勒矩阵参数的参数空间，我们根据穆勒矩阵偏振分解方法提出了新的矢量参数（VPs）。我们用MMIP测量了伴有广泛坏死的浸润性膀胱癌（IBC）和高级别导管原位癌（DCIS），并用VPs对癌细胞和纤维化基质区域进行了分类。然后，将所提出的和现有的VPs映射到具有三维可视化的庞加莱球上，并基于最小包围球定义了一个空间特征指标，以评估VPs的分类能力。对于IBC和DCIS，结果表明，所提出的VPs在癌细胞区域和纤维化基质区域之间表现出明显的对比度。本研究拓宽了基本的穆勒矩阵参数，并有助于提高MMIP技术的表征能力。
