Digital image analysis in pathology: Benefits and obligation
Digital image analysis in pathology: Benefits and obligation
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DOI：
10.1155/2012/243416
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发表时间：
2012-01-01
影响因子：
3.2
通讯作者：
Herlin, Paulette
中科院分区：
文献类型：
--
作者：
Laurinavicius, Arvydas;Laurinaviciene, Aida;Herlin, Paulette
病理学最近进入了个性化医学时代。这对基于组织的诊断的准确性和精确度带来了新的期望，特别是当需要量化组织学特征和生物标记物表达时。虽然多年来，传统的病理诊断一直被认为是基本事实，但在当代基于组织的生物标记物研究和临床应用中，这一概念已不再充分。病理学上的另一个重大变化是虚拟显微镜技术的进步，使显微镜载玻片数字化，并为数字图像分析提供了新的机会。计算机化的视觉提供了容量(自动化)和精确度(重复性)增加的直接好处，但不一定是分析的准确性。为了达到准确的效果，病理学家必须承担起对图像分析算法进行验证和质量保证的义务。需要参考值来测量和控制精度。虽然病理学家的共识值通常被用来验证这些工具，但我们认为，通过体视学方法估计相同的变量，就像算法打算做的那样，可以最好地获得基本事实。新技术的正确采用将需要病理学上一种新的量化思维。为了看到一种疾病的完整和清晰的图像，病理学家需要学会同时使用他们的模拟眼睛和数字眼睛。
Pathology has recently entered the era of personalized medicine. This brings new expectations for the accuracy and precision of tissue-based diagnosis, in particular, when quantification of histologic features and biomarker expression is required. While for many years traditional pathologic diagnosis has been regarded as ground truth, this concept is no longer sufficient in contemporary tissue-based biomarker research and clinical use. Another major change in pathology is brought by the advancement of virtual microscopy technology enabling digitization of microscopy slides and presenting new opportunities for digital image analysis. Computerized vision provides an immediate benefit of increased capacity (automation) and precision (reproducibility), but not necessarily the accuracy of the analysis. To achieve the benefit of accuracy, pathologists will have to assume an obligation of validation and quality assurance of the image analysis algorithms. Reference values are needed to measure and control the accuracy. Although pathologists' consensus values are commonly used to validate these tools, we argue that the ground truth can be best achieved by stereology methods, estimating the same variable as an algorithm is intended to do. Proper adoption of the new technology will require a new quantitative mentality in pathology. In order to see a complete and sharp picture of a disease, pathologists will need to learn to use both their analogue and digital eyes.