CometQ: An automated tool for the detection and quantification of DNA damage using comet assay image analysis. Issue 133 (September 2016)

• Record Type: Journal Article
• Authors: Ganapathy, Sreelatha; Muraleedharan, Aparna; Sathidevi, Puthumangalathu Savithri; Chand, Parkash; Rajkumar, Ravi Philip
• Is Part Of: Computer methods and programs in biomedicine. Issue 133(2016)
• Page Start: 143
• Page End: 154
• Publication Date: 2016-09
• Subjects: Comet assay image analysis -- CometQ -- Comet segmentation -- Comet quantification -- Image enhancement; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2016.05.020
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: CometQ is a novel, fully automated tool for the detection and quantification of DNA damage by analysing comet assay images. CometQ is capable of analysing both types of comet assay images (Silver stained and fluorescent stained images). The comet parameters required for DNA damage analysis will be automatically saved in an excel file. CometQ gave 90.26% positive predictive value and 93.34% sensitivity, which is much higher than the recent related works. The performance of CometQ is analysed by clinical experts and found to be very useful for DNA damage analysis and repair. Abstract: Background and objective: DNA damage analysis plays an important role in determining the approaches for treatment and prevention of various diseases like cancer, schizophrenia and other heritable diseases. Comet assay is a sensitive and versatile method for DNA damage analysis. The main objective of this work is to implement a fully automated tool for the detection and quantification of DNA damage by analysing comet assay images. Methods: The comet assay image analysis consists of four stages: (1) classifier (2) comet segmentation (3) comet partitioning and (4) comet quantification. Main features of the proposed software are the design and development of four comet segmentation methods, and the automatic routing of the input comet assay image to the most suitable one among these methods depending on the type of the image (silver stained or fluorescent stained) as well as the level of DNA damage (heavily damaged or lightly/moderately damaged). A classifier stage, based on support vector machine (SVM) is designed and implemented at the front end, to categorise the input image into one of the above four groups to ensure proper routing. Comet segmentation is followed by comet partitioning which is implemented using a novel technique coined as modified fuzzy clustering. Comet parameters are calculated in the comet quantification stage and are saved in an excel file. Results: Our dataset consists of 600 silver stained images obtained from 40 Schizophrenia patients with different levels of severity, admitted to a tertiary hospital in South India and 56 fluorescent stained images obtained from different internet sources. The performance of "CometQ", the proposed standalone application for automated analysis of comet assay images, is evaluated by a clinical expert and is also compared with that of a most recent and related software—OpenComet. CometQ gave 90.26% positive predictive value (PPV) and 93.34% sensitivity which are much higher than those of OpenComet, especially in the case of silver stained images. The results are validated using confusion matrix and Jaccard index (JI). Comet assay images obtained after DNA damage repair by incubation in the nutrient medium were also analysed, and CometQ showed a significant change in all the comet parameters in most of the cases. Conclusions: Results show that CometQ is an accurate and efficient tool with good sensitivity and PPV for DNA damage analysis using comet assay images.