TMA-Mate: An open-source modular toolkit for constructing tissue microarrays of arbitrary layouts

被引:2
作者
Pazaitis, Nikolaos [1 ]
Kaiser, Alexandra [1 ]
机构
[1] Municipal Hosp Dresden, Inst Pathol Georg Schmorl, Campus Friedrichstadt,Friedrichstr 41, D-01067 Dresden, Germany
关键词
Tissue microarray (TMA); Histopathology; Histology; Biomarkers; 3D printing; Open-source hardware; HIGH-THROUGHPUT; HIGH-DENSITY; CORE BIOPSIES; CELL; PERFORMANCE; TECHNOLOGY; VALIDATION; HER2;
D O I
10.1016/j.ohx.2023.e00419
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Biomedical research and quality control procedures often demand a variety of microscopic analysis of numerous formalin-fixed and paraffin-embedded (FFPE) tissue samples from different individuals of both healthy and diseased regions of interest. Depending on the number of samples to be analyzed, conventional processing of each FFPE block separately can be laborious or impracticable. This effort can be drastically reduced by using tissue microarrays (TMAs). TMAs have a wide range of applications and can be considered as a high-throughput method to process up to hundreds of miniaturized tissue samples simultaneously on a single microscopy slide, in order to reduce labor, costs and sample consumption, and to increase results comparability. Several commercial and self-made solutions to fabricate TMAs with varying degrees of automation are available. However, these solutions may not be suitable for every situation, either due to high costs, high complexity, lack of precision or lack of flexibility, especially when diagnostically oriented pathology institutes or laboratories with constrained resources are considered. This article introduces the TMA-Mate, an open-source 3D printable modular toolkit for constructing high-density TMAs of arbitrary layouts, providing an affordable, lightweight, and accessible procedure to implement TMAs into existing histology processing pipelines. Step-by-step demonstrations for replicating the hardware and constructing TMAs are included.& COPY; 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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页数:20
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