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Quantification of patient-derived 3D cancer spheroids in high content screening images

Title
Quantification of patient-derived 3D cancer spheroids in high content screening images
Authors
Kang M.-S.Rhee S.-M.Seo J.-H.Kim M.-H.
Ewha Authors
김명희
SCOPUS Author ID
김명희scopus
Issue Date
2017
Journal Title
Progress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN
1605-7422JCR Link
Citation
Progress in Biomedical Optics and Imaging - Proceedings of SPIE vol. 10068
Keywords
3D spheroidsCancer cellHigh content screeningImage quantificationPatient-derived
Publisher
SPIE
Indexed
SCOPUS scopus
Document Type
Conference Paper
Abstract
We present a cell image quantification method for image-based drug response prediction from patient-derived glioblastoma cells. Drug response of each person differs at the cellular level. Therefore, quantification of a patientderived cell phenotype is important in drug response prediction. We performed fluorescence microscopy to understand the features of patient-derived 3D cancer spheroids. A 3D cell culture simulates the in-vivo environment more closely than 2D adherence culture, and thus, allows more accurate cell analysis. Furthermore, it allows assessment of cellular aggregates. Cohesion is an important feature of cancer cells. In this paper, we demonstrate image-based quantification of cellular area, fluorescence intensity, and cohesion. To this end, we first performed image stitching to create an image of each well of the plate with the same environment. This image shows colonies of various sizes and shapes. To automatically detect the colonies, we used an intensity based classification algorithm. The morphological features of each cancer cell colony were measured. Next, we calculated the location correlation of each colony that is appeal of the cell density in the same well environment. Finally, we compared the features for drug-treated and untreated cells. This technique could potentially be applied for drug screening and quantification of the effects of the drugs. © 2017 SPIE.
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DOI
10.1117/12.2250594
ISBN
9781510605770
Appears in Collections:
엘텍공과대학 > 컴퓨터공학과 > Journal papers
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