Shape decomposition algorithms for laser capture microdissection

Algorithms for Molecular Biology

Axel Mosig¹  Klaus Gerwert²  Tobias Kowalski²  Maike Buchin³  Leonie Selbach⁴ 

[1] Bioinformatics Group, Faculty of Biology and Biotechnology, Ruhr University Bochum, Bochum, Germany;Center for Protein Diagnostics, Ruhr University Bochum, Bochum, Germany;Department of Biophysics, Faculty of Biology and Biotechnology, Ruhr University Bochum, Bochum, Germany;Center for Protein Diagnostics, Ruhr University Bochum, Bochum, Germany;Department of Computer Science, Faculty of Mathematics, Ruhr University Bochum, Bochum, Germany;Department of Computer Science, Faculty of Mathematics, Ruhr University Bochum, Bochum, Germany;Center for Protein Diagnostics, Ruhr University Bochum, Bochum, Germany;

关键词: Laser capture microdissection;    Shape decomposition;    Skeletonization;   

DOI  :  10.1186/s13015-021-00193-6

来源: Springer

【 摘 要 】

BackgroundIn the context of biomarker discovery and molecular characterization of diseases, laser capture microdissection is a highly effective approach to extract disease-specific regions from complex, heterogeneous tissue samples. For the extraction to be successful, these regions have to satisfy certain constraints in size and shape and thus have to be decomposed into feasible fragments.ResultsWe model this problem of constrained shape decomposition as the computation of optimal feasible decompositions of simple polygons. We use a skeleton-based approach and present an algorithmic framework that allows the implementation of various feasibility criteria as well as optimization goals. Motivated by our application, we consider different constraints and examine the resulting fragmentations. We evaluate our algorithm on lung tissue samples in comparison to a heuristic decomposition approach. Our method achieved a success rate of over 95% in the microdissection and tissue yield was increased by 10–30%.ConclusionWe present a novel approach for constrained shape decomposition by demonstrating its advantages for the application in the microdissection of tissue samples. In comparison to the previous decomposition approach, the proposed method considerably increases the amount of successfully dissected tissue.

【 授权许可】

CC BY