The understanding of fat tissue plays an eminent role in plastic surgery as well as in metabolic research. Histopathological analysis of tissue samples provides insight in free fat graft survival and culture experiments help to better understand fat tissue derived stem cells (ASCs). To facilitate such experiments, modern image-based histology could provide an automatized approach to a large amount of data to gain not only qualitative but also quantitative data. This study was designed to critically evaluate image-based analysis of fat tissue samples in cell culture or in tissue probes and to identify critical parameters to avoid bias in further studies. In the first part of the study, ASCs were harvested and differentiated into adipocytes in cell culture. Histology was performed with the fluorescent dye BODIPY and the obtained digital images were analyzed using Image J software. In the second part of the study, digitalized histology of a previous in vivo study was subjected to automatized fat vacuole quantification using Image J. Both approaches were critically reviewed, and different software parameter settings were tested. Results showed that automatized digital image analysis allows the quantification of fat tissue probes with enough precision giving significant results. But the testing of different software parameters revealed a significant influence of parameters themselves on calculated results. Therefore, we recommend the use of image-based analysis to quantify fat tissue probes to improve the comparability of studies. But we also emphasize to calibrate software using internal controls in every single experimental approach.

中文翻译：

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在基于脂肪组织组织学图像的自动化分析中，软件参数对测量的影响。

对脂肪组织的了解在整形外科以及新陈代谢研究中发挥着重要作用。组织样品的组织病理学分析为游离脂肪移植物的存活提供了见识，而培养实验有助于更好地了解脂肪组织衍生的干细胞（ASC）。为了促进此类实验，现代的基于图像的组织学可以为大量数据提供一种自动化的方法，以获取定性和定量数据。这项研究旨在严格评估细胞培养或组织探针中脂肪组织样品的基于图像的分析，并确定关键参数以避免在进一步研究中产生偏差。在研究的第一部分，ASCs被收获并在细胞培养中分化为脂肪细胞。用荧光染料BODIPY进行组织学，并使用Image J软件分析获得的数字图像。在研究的第二部分中，使用Image J对先前体内研究的数字化组织学进行了自动化脂肪液泡定量分析。对两种方法进行了严格审查，并测试了不同的软件参数设置。结果表明，自动化的数字图像分析可以对脂肪组织探针进行足够精确的定量，从而获得显着结果。但是，对不同软件参数的测试显示出参数本身对计算结果的重大影响。因此，我们建议使用基于图像的分析来量化脂肪组织探针，以提高研究的可比性。