Influence of software parameters on measurements in automatized image-based analysis of fat tissue histology

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.