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首页> 外文会议>IEEE International Symposium on Biomedical Imaging: From Nano to Macro >Improved automated localization and quantification of protein multiplexes via multispectral fluorescence imaging in heterogenous biopsy samples
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Improved automated localization and quantification of protein multiplexes via multispectral fluorescence imaging in heterogenous biopsy samples

机译：通过多光谱荧光成像在异质活检样品中改进的蛋白质多路复用的自动定位和定量

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摘要

We present a novel improvement of our previously published image analysis system for the automated localization and quantification of protein biomarker expression in immunofluorescence (IF) microscopic images. The improvement has been developed primarily for biopsy based images which are by nature of variable quality and heterogeneous. The innovative method is employed for discriminating the biomarker signal from background, where signal may be the expression of multiple biomarkers or counterstains used in IF. The method is dynamic and it derives a threshold for a true biomarker signal based on the relationship between disease and non-disease tissue components. In addition, a new dynamic range feature construction is presented that is less affected by processing and other variations in tissue. The utility of the approach is demonstrated in predicting, based on the diagnostic biopsy tissue, prostate cancer disease progression within eight years after a radical prostatectomy. For this purpose, androgen receptor (AR) and Ki67 biomarker expression in prostate biopsy samples was quantified and features from the proposed approach were shown to be associated with disease progression in a univariate analysis and manifested improved performance over prior systems. Furthermore, AR and Ki67 features were selected in a multivariate model integrating clinical, histological, and biomarker features, proving their independent prognostic value.
机译：我们提出了我们以前发布的图像分析系统的一种新型改进，用于自动定位和定量免疫荧光（IF）显微镜图像中蛋白质生物标志物的表达。改进主要针对基于活检的图像而开发，这些图像本质上质量可变且异质。该创新方法用于将生物标志物信号与背景区分开，其中信号可能是IF中使用的多个生物标志物或复染色的表达。该方法是动态的，并且它基于疾病和非疾病组织成分之间的关​​系得出真实生物标记信号的阈值。此外，提出了一种新的动态范围特征构造，该构造受组织处理和其他变化的影响较小。该方法的实用性在基于诊断性活检组织预测前列腺癌根治术后八年内的前列腺癌疾病进展中得到了证明。为此，对前列腺活检样本中的雄激素受体（AR）和Ki67生物标志物表达进行了定量，单因素分析显示，所提出方法的特征与疾病进展相关，并且表现出比现有系统更高的性能。此外，在综合了临床，组织学和生物标志物特征的多元模型中选择了AR和Ki67特征，证明了其独立的预后价值。

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