Publication: Automatic detection of DNA double strand breaks after irradiation using an γH2AX assay
Authors
Hohmann, Tim ; Kessler, Jacqueline ; Grabiec, Urszula ; Bache, Matthias ; Dehghani, Faramarz
item.page.secondaryauthor
item.page.director
Publisher
Universidad de Murcia. Departamento de Biología Celular e Histología
publication.page.editor
publication.page.department
DOI
DOI: 10.14670/HH-11-945
item.page.type
info:eu-repo/semantics/article
Description
Abstract
Radiation therapy belongs to the most
common approaches for cancer therapy leading amongst
others to DNA damage like double strand breaks (DSB).
DSB can be used as a marker for the effect of radiation
on cells. For visualization and assessing the extent of
DNA damage the γH2AX foci assay is frequently used.
The analysis of the γH2AX foci assay remains
complicated as the number of γH2AX foci has to be
counted. The quantification is mostly done manually,
being time consuming and leading to person-dependent
variations. Therefore, we present a method to
automatically analyze the number of foci inside nuclei,
facilitating and quickening the analysis of DSBs with
high reliability in fluorescent images.
First nuclei were detected in fluorescent images.
Afterwards, the nuclei were analyzed independently
from each other with a local thresholding algorithm.
This approach allowed accounting for different levels of
noise and detection of the foci inside the respective
nucleus, using Hough transformation searching for
circles.
The presented algorithm was able to correctly
classify most foci in cases of “high” and “average”
image quality (sensitivity>0.8) with a low rate of false
positive detections (positive predictive value (PPV)
>0.98). In cases of “low” image quality the approach had
a decreased sensitivity (0.7-0.9), depending on the
manual control counter. The PPV remained high (PPV
>0.91). Compared to other automatic approaches the
presented algorithm had a higher sensitivity and PPV.
The used automatic foci detection algorithm was
capable of detecting foci with high sensitivity and PPV.
Thus it can be used for automatic analysis of images of
varying quality
publication.page.subject
Citation
Histology and Histopathology, Vol.33, nº5, (2018)
item.page.embargo
Ir a Estadísticas
Este ítem está sujeto a una licencia Creative Commons. http://creativecommons.org/licenses/by-nc-nd/4.0/