一种新颖的深度多注意力通道网络管线，用于通过荧光显微镜自主检测转移细胞

A novel pipeline employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy

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COMPUTERS IN BIOLOGY AND MEDICINE

影响因子:6.3

分区:医学2区 / 数学与计算生物学1区生物学2区计算机：跨学科应用2区工程：生物医学2区

发表日期:2024 Oct

作者: Michail Mamalakis, Sarah C Macfarlane, Scott V Notley, Annica K B Gad, George Panoutsos

DOI: 10.1016/j.compbiomed.2024.109052

摘要

由癌细胞迁移驱动的转移是癌症相关死亡的主要原因。它涉及细胞骨架的显著变化，包括肌动蛋白微丝和波形蛋白间质纤维的重组。理解这些细胞骨架变化如何使细胞从正常状态变为侵袭性，提供了有助于改善癌症诊断和治疗的见解。我们开发了一种计算型、透明、大规模的成像管线，能够根据细胞质中肌动蛋白和波形蛋白的空间组织，区分正常人类细胞与其同源、癌变、侵袭性和转移性对应细胞。由于这些亚细胞结构的复杂性，手动标注难以实现自动化。我们采用了成熟的深度学习方法和我们新开发的多注意力通道架构。为了确保模型的高可解释性，这是应用中的关键，我们开发了一种可解释的全球性可解释方法，通过相关加权几何平均值与局部GradCam得分，提供详细、客观、可衡量的细胞骨架不同组成部分在转移中的作用理解。这些方法为未来开发新型诊断工具提供了基础，例如基于波形蛋白纤维的纳米级生物标志物，用于数字病理学，以及能显著提高患者存活率的新治疗策略。

Abstract

Metastasis driven by cancer cell migration is the leading cause of cancer-related deaths. It involves significant changes in the organization of the cytoskeleton, which includes the actin microfilaments and the vimentin intermediate filaments. Understanding how these filament change cells from normal to invasive offers insights that can be used to improve cancer diagnosis and therapy. We have developed a computational, transparent, large-scale and imaging-based pipeline, that can distinguish between normal human cells and their isogenically matched, oncogenically transformed, invasive and metastasizing counterparts, based on the spatial organization of actin and vimentin filaments in the cell cytoplasm. Due to the intricacy of these subcellular structures, manual annotation is not trivial to automate. We used established deep learning methods and our new multi-attention channel architecture. To ensure a high level of interpretability of the network, which is crucial for the application area, we developed an interpretable global explainable approach correlating the weighted geometric mean of the total cell images and their local GradCam scores. The methods offer detailed, objective and measurable understanding of how different components of the cytoskeleton contribute to metastasis, insights that can be used for future development of novel diagnostic tools, such as a nanometer level, vimentin filament-based biomarker for digital pathology, and for new treatments that significantly can increase patient survival.Crown