Ahn Sebastian W, Ferland Benjamin, Jonas Oliver H
Department of Radiology, Laboratory for Bio-Micro Devices, Brigham and Women's Hospital, Boston, MA, USA.
J Pathol Inform. 2021 Sep 16;12:34. doi: 10.4103/jpi.jpi_17_21. eCollection 2021.
Tumor heterogeneity is increasingly being recognized as a major source of variability in the histopathological assessment of drug responses. Quantitative analysis of immunohistochemistry (IHC) and immunofluorescence (IF) images using biomarkers that capture spatialpatterns of distinct tumor biology and drug concentration in tumors is of high interest to the field.
We have developed an image analysis pipeline to measure drug response using IF and IHC images along spatial gradients of local drug release from a tumor-implantable drug delivery microdevice. The pipeline utilizes a series of user-interactive python scripts and CellProfiler pipelines with custom modules to perform image and spatial analysis of regions of interest within whole-slide images.
Worked examples demonstrate that intratumor measurements such as apoptosis, cell proliferation, and immune cell population density can be quantitated in a spatially and drug concentration-dependent manner, establishing profiles of pharmacodynamics and pharmacokinetics in tumors.
Spatial image analysis of tumor response along gradients of local drug release is achievable in high throughput. The major advantage of this approach is the use of spatially aware annotation tools to correlate drug gradients with drug effects in tumors .
肿瘤异质性日益被认为是药物反应组织病理学评估中变异性的主要来源。利用能够捕捉肿瘤独特生物学空间模式和肿瘤内药物浓度的生物标志物对免疫组织化学（IHC）和免疫荧光（IF）图像进行定量分析，是该领域高度关注的内容。
我们开发了一种图像分析流程，用于沿着可植入肿瘤的药物递送微装置局部药物释放的空间梯度，使用IF和IHC图像测量药物反应。该流程利用一系列用户交互式Python脚本和带有自定义模块的CellProfiler流程，对全切片图像内的感兴趣区域进行图像和空间分析。
实例表明，肿瘤内测量指标如细胞凋亡、细胞增殖和免疫细胞群体密度可在空间和药物浓度依赖的方式下进行定量，从而建立肿瘤内的药效学和药代动力学图谱。
沿着局部药物释放梯度对肿瘤反应进行空间图像分析可实现高通量。这种方法的主要优点是使用空间感知注释工具将药物梯度与肿瘤内的药物效应相关联。
