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Automatic Identification and Validation of Planar Collagen Organization in the Aorta Wall with Application to Abdominal Aortic Aneurysm

Published online by Cambridge University Press:  09 September 2013

Stanislav Polzer ,
T. Christian Gasser ,
Caroline Forsell ,
Hana Druckmüllerova ,
Michal Tichy ,
Robert Staffa ,
Robert Vlachovsky  and
Jiri Bursa
Stanislav Polzer*
Affiliation:
Institute of Solid Mechanics, Mechatronics and Biomechanics, Brno University of Technology, Czech Republic
T. Christian Gasser
Affiliation:
Department of Solid Mechanics, Royal Institute of Technology, Stockholm, Sweden
Caroline Forsell
Affiliation:
Department of Solid Mechanics, Royal Institute of Technology, Stockholm, Sweden
Hana Druckmüllerova
Affiliation:
Institute of Mathematics, Faculty of Mechanical Engineering, Brno University of Technology, Czech Republic
Michal Tichy
Affiliation:
1st Department of Pathology and Anatomy, St. Anne's University Hospital, Brno, Czech Republic
Robert Staffa
Affiliation:
2nd Department of Surgery, St. Anne's University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
Robert Vlachovsky
Affiliation:
2nd Department of Surgery, St. Anne's University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic
Jiri Bursa
Affiliation:
Institute of Solid Mechanics, Mechatronics and Biomechanics, Brno University of Technology, Czech Republic
*
*Corresponding author. E-mail: [email protected]
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Abstract

Arterial physiology relies on a delicate three-dimensional (3D) organization of cells and extracellular matrix, which is remarkably altered by vascular diseases like abdominal aortic aneurysms (AAA). The ability to explore the micro-histology of the aorta wall is important in the study of vascular pathologies and in the development of vascular constitutive models, i.e., mathematical descriptions of biomechanical properties of the wall. The present study reports and validates a fast image processing sequence capable of quantifying collagen fiber organization from histological stains. Powering and re-normalizing the histogram of the classical fast Fourier transformation (FFT) is a key step in the proposed analysis sequence. This modification introduces a powering parameter w, which was calibrated to best fit the reference data obtained using classical FFT and polarized light microscopy (PLM) of stained histological slices of AAA wall samples. The values of w = 3 and 7 give the best correlation (Pearson's correlation coefficient larger than 0.7, R2 about 0.7) with the classical FFT approach and PLM measurements. A fast and operator independent method to identify collagen organization in the arterial wall was developed and validated. This overcomes severe limitations of currently applied methods like PLM to identify collagen organization in the arterial wall.

Keywords

fast Fourier transformcollagen organizationcollagen dispersionpolarized light microscopy
Type
Biomedical and Biological Applications
Information
Microscopy and Microanalysis , Volume 19 , Issue 6 , December 2013 , pp. 1395 - 1404
Copyright
Copyright © Microscopy Society of America 2013 

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