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.

Addition of decellularized extracellular matrix of porcine nasal cartilage improves cartilage regenerative capacities of PCL-based scaffolds in vitro.

Composite scaffolds can improve regenerative capacities of scaffolds in various tissue-engineering approaches. In order to generate a 3D printable scaffold that is capable of cartilage regeneration, decellularized extracellular matrix (DECM) of porcine nasal cartilage was added to 3D printed polycaprolactone (PCL) scaffolds. Subsequently, scaffolds (PCL, PCL/DECM and DECM) were seeded with human primary nasoseptal chondrocytes and differentiated with cartilage inductive medium for up to 42 days in vitro. Afterwards samples were analyzed with scanning electron microscopy, histology, biochemical assays and gene expression analysis. In short, results showed cell attachment and proliferation on all scaffolds. There was a trend towards ossification on pure PCL scaffolds, whereas we found evidence for cartilage tissue formation on DECM scaffolds as well as on PCL/DECM scaffolds. Moreover, biochemical analysis indicated an enhanced differentiation on novel PCL/DECM scaffolds. In conclusion, the addition of DECM to 3D printable PCL scaffolds may yield a new composite material for regenerative approaches in cartilage for facial reconstructive surgery. Further research will be necessary to evaluate these findings in vivo.