Automated detection of dual p16/Ki67 nuclear immunoreactivity in liquid-based Pap tests for improved cervical cancer risk stratification.
Automated detection of dual p16/Ki67 nuclear immunoreactivity in liquid-based Pap tests for improved cervical cancer risk stratification.
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DOI：
10.1007/s10439-011-0498-8
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发表时间：
2012-05
影响因子：
3.8
通讯作者：
Bose, Shikha
中科院分区：
文献类型：
--
作者：
Gertych, Arkadiusz;Joseph, Anika O.;Walts, Ann E.;Bose, Shikha
关键词：
巴氏试验（Pap）是一种常规的细胞学检查程序，用于早期发现宫颈上皮的发育异常病变。一个可靠的筛查方法是至关重要的分流妇女的风险;然而，人工筛查和解释与相对较低的灵敏度和大量的观察者间的诊断变异性。P16和Ki 67生物标志物最近已被提出作为诊断高危人乳头瘤病毒（hrHPV）相关发育不良的辅助工具，以通过额外的比色特征来补充细胞的形态特征。在这项研究中，介绍了一种自动化技术，用于评价双重p16/Ki 67在宫颈细胞核中的免疫反应性。用p16和Ki 67抗体染色的涂片被数字化，并通过我们开发的算法进行分析。采用基于自适应的径向对称算子和对称图像的自适应处理来获得核掩模。该步骤之后是提取特征，包括来自每个细胞核的像素数据和免疫反应性签名。用两个支持向量机分类器对这些特征进行分析，将细胞核分为四种免疫反应性类型之一：p16阳性（p16+/Ki 67-），Ki 67阳性（p16-/Ki 67+），p16/Ki 67双重阳性（p16+/Ki 67+）和阴性（p16-/Ki 67-）。通过我们的方法获得的结果相关性以及由两个细胞病理学家（n=18068细胞）的读数; p16+/Ki 67+细胞核分别为77.1%和82.6%的精度进行分类。对p16-/Ki 67-核的特异性优于99.5%，对所有免疫阳性核的敏感性分别为86.3%和89.4%。我们发现，由分类核的额外突出显示提供的免疫反应性的定量表征可以积极影响巴氏试验的功效和筛选结果。
The Papanicolau (Pap) test is a routine cytological procedure for early detection of dysplastic lesions in cervical epithelium. A reliable screening method is crucial for triage of women at risk; however manual screening and interpretation are associated with relatively low sensitivity and substantial interobserver diagnostic variability. P16 and Ki67 biomarkers have been recently proposed as adjunctive tools in the diagnosis of high-risk human papillomavirus (hrHPV) associated dysplasias to supplement the morphological characteristics of cells by additional colorimetric features. In this study, an automated technique for the evaluation of dual p16/Ki67 immunoreactivity in cervical cell nuclei is introduced. Smears stained with p16 and Ki67 antibodies were digitized, and analyzed by algorithms we developed. Gradient-based radial symmetry operator and adaptive processing of symmetry image were employed to obtain the nuclear mask. This step was followed by the extraction of features including pixel data and immunoreactivity signature from each nucleus. The features were analyzed by two support vector machine classifiers to assign a nucleus into one of four types of immunoreactivity: p16 positive (p16+/Ki67-), Ki67 positive (p16-/Ki67+), dual p16/Ki67 positive (p16+/Ki67+) and negative (p16-/Ki67-) respectively. Results obtained by our method correlated well with readings by two cytopathologists (n=18068 cells); p16+/Ki67+ nuclei were classified with respective precisions of 77.1% and 82.6%. Specificity in identification of p16-/Ki67- nuclei was better than 99.5%, and the sensitivity in detection of all immunopositive nuclei was 86.3% and 89.4% respectively. We found that the quantitative characterization of immunoreactivity provided by the additional highlighting of classified nuclei can positively impact the efficacy and screening outcome of the Pap test.
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