PRAQA: Protein Relative Abundance Quantification Algorithm for 3D Fluorescent Images

Corrado Ameli, Corrado Ameli, Sonja Fixemer, Sonja Fixemer, David S. Bouvier, David S. Bouvier, David S. Bouvier, Alexander Skupin, Alexander Skupin

2021

Abstract

In confocal fluorescent microscopy, the quality of the acquisition strongly depends on diverse factors including the microscope parameterization, the light exposure time, the type and concentration of the antibodies used, the thickness of the sample and the degradation of the biological tissue itself. All these factors critically influence the final result and render tissue protein quantification challenging due to intra- and inter-sample variability. Therefore, image processing techniques need to address the acquisitions variability to minimize the risk of bias coming from changes in signal intensity, noise and parameterization. Here, we introduce Protein Relative Abundance Quantification Algorithm (PRAQA), a 1-parameter based, fast and adaptive approach for quantifying protein abundance in 3D fluorescent-immunohistochemistry stained tissues that requires no image preprocessing. Our method is based on the assessment of the global pixel intensity neighborhood dispersion that allows to statistically infer whether each small region of an image can be considered as positive signal or background noise. We benchmark our method with alternative approaches from literature and validate its applicability and efficiency based on synthetic scenarios and a real-world application to post-mortem human brain samples of Alzheimer’s Disease and Lewy Body Dementia patients. PRAQA is implemented in Matlab and freely available at https://doi.org/10.17881/j20h-pa27.

Paper Citation

in Harvard Style

Ameli C., Fixemer S., Bouvier D. and Skupin A. (2021). PRAQA: Protein Relative Abundance Quantification Algorithm for 3D Fluorescent Images. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 2: BIOIMAGING; ISBN 978-989-758-490-9, SciTePress, pages 21-30. DOI: 10.5220/0010187400002865

in Bibtex Style

@conference{bioimaging21,
author={Corrado Ameli and Sonja Fixemer and David S. Bouvier and Alexander Skupin},
title={PRAQA: Protein Relative Abundance Quantification Algorithm for 3D Fluorescent Images},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 2: BIOIMAGING},
year={2021},
pages={21-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010187400002865},
isbn={978-989-758-490-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 2: BIOIMAGING
TI - PRAQA: Protein Relative Abundance Quantification Algorithm for 3D Fluorescent Images
SN - 978-989-758-490-9
AU - Ameli C.
AU - Fixemer S.
AU - Bouvier D.
AU - Skupin A.
PY - 2021
SP - 21
EP - 30
DO - 10.5220/0010187400002865
PB - SciTePress