Standardization of biorepository best practices will enhance the quality of translational biomedical research utilizing patient-derived biobank specimens. Harmonization of pathology quality assurance procedures for biobank accessions has lagged behind other avenues of biospecimen research and biobank development. Comprehension of the cellular content of biorepository specimens is important for discovery of tissue-specific clinically relevant biomarkers for diagnosis and treatment. While rapidly emerging technologies in molecular analyses and data mining create focus on appropriate measures for minimizing pre-analytic artifact-inducing variables, less attention gets paid to annotating the constituent makeup of biospecimens for more effective specimen selection by biobank clients. Both pre-analytic tissue processing and specimen composition influence acquisition of relevant macromolecules for downstream assays. Pathologist review of biorepository submissions, particularly tissues as part of quality assurance procedures, helps to ensure that the intended target cells are present and in sufficient quantity in accessioned specimens. This manual procedure can be tedious and subjective. Incorporating digital pathology into biobank quality assurance procedures, using automated pattern recognition morphometric image analysis to quantify tissue feature areas in digital whole slide images of tissue sections, can minimize variability and subjectivity associated with routine pathologic evaluations in biorepositories. Whole-slide images and pathologist-reviewed morphometric analyses can be provided to researchers to guide specimen selection. Harmonization of pathology quality assurance methods that minimize subjectivity and improve reproducibility among collections would facilitate research-relevant specimen selection by investigators and could facilitate information sharing in an integrated network approach to biobanking.

中文翻译：

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数字病理学和图像分析增强了生物样本注释和生物样本库质量保证的协调性。

生物样本库最佳实践的标准化将利用患者来源的生物样本库提高转化生物医学研究的质量。生物样本库加入的病理学质量保证程序的协调落后于生物样本研究和生物样本库开发的其他途径。了解生物样本库标本的细胞含量对于发现用于诊断和治疗的组织特异性临床相关生物标志物非常重要。虽然分子分析和数据挖掘中迅速出现的技术专注于采取适当措施来最大限度地减少分析前的人工制品诱导变量，但对生物样本的组成成分进行注释以供生物银行客户更有效地选择样本的关注较少。分析前组织处理和样本组成都会影响下游检测相关大分子的获取。病理学家对生物样本库提交的材料进行审查，尤其是作为质量保证程序一部分的组织，有助于确保所收集的标本中存在预期的靶细胞并且数量充足。这个手动过程可能是乏味和主观的。将数字病理学纳入生物样本库质量保证程序，使用自动模式识别形态测量图像分析来量化组织切片数字全玻片图像中的组织特征区域，可以最大限度地减少与生物样本库中常规病理学评估相关的变异性和主观性。可以向研究人员提供全幻灯片图像和病理学家审查的形态测量分析，以指导标本选择。协调病理学质量保证方法，最大限度地减少主观性并提高集合之间的可重复性，将有助于研究人员选择与研究相关的标本，并可以促进生物样本库综合网络方法中的信息共享。