title: Rapid 3-D delineation of cell nuclei for high-content screening platforms.
abstract: High-resolution three-dimensional (3-D) microscopy combined with multiplexing of fluorescent labels allows high-content analysis of large numbers of cell nuclei. The full automation of 3-D screening platforms necessitates image processing algorithms that can accurately and robustly delineate nuclei in images with little to no human intervention. Imaging-based high-content screening was originally developed as a powerful tool for drug discovery. However, cell confluency, complexity of nuclear staining as well as poor contrast between nuclei and background result in slow and unreliable 3-D image processing and therefore negatively affect the performance of studying a drug response. Here, we propose a new method, 3D-RSD, to delineate nuclei by means of 3-D radial symmetries and test it on high-resolution image data of human cancer cells treated by drugs. The nuclei detection performance was evaluated by means of manually generated ground truth from 2351 nuclei (27 confocal stacks). When compared to three other nuclei segmentation methods, 3D-RSD possessed a better true positive rate of 83.3% and F-score of 0.895±0.045 (p-value=0.047). Altogether, 3D-RSD is a method with a very good overall segmentation performance. Furthermore, implementation of radial symmetries offers good processing speed, and makes 3D-RSD less sensitive to staining patterns. In particular, the 3D-RSD method performs well in cell lines, which are often used in imaging-based HCS platforms and are afflicted by nuclear crowding and overlaps that hinder feature extraction.
authors.affiliation: Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Electronic address: arkadiusz.gertych@cshs.org.
authors.forename: Arkadiusz
authors.initials: A
authors.lastname: Gertych
authors.affiliation: Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
authors.forename: Zhaoxuan
authors.initials: Z
authors.lastname: Ma
authors.affiliation: Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
authors.forename: Jian
authors.initials: J
authors.lastname: Tajbakhsh
authors.affiliation: Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
authors.forename: Adriana
authors.initials: A
authors.lastname: Velásquez-Vacca
authors.affiliation: Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
authors.forename: Beatrice S
authors.initials: BS
authors.lastname: Knudsen
mesh_terms: D045744:Cell Line, Tumor; D002467:Cell Nucleus / Q000378:metabolism / Q000473:pathology*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D018613:Microscopy, Confocal / Q000379:methods; D009369:Neoplasms / Q000378:metabolism / Q000473:pathology*
keywords: 3-D segmentation of nuclei; Bio-image informatics; High-content screening; Image processing