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Epithelial Ovarian Cancer Diagnosis of Second-Harmonic Generation Images: A Semiautomatic Collagen Fibers Quantification Protocol

View Article: PubMed Central - PubMed

ABSTRACT

A vast number of human pathologic conditions are directly or indirectly related to tissular collagen structure remodeling. The nonlinear optical microscopy second-harmonic generation has become a powerful tool for imaging biological tissues with anisotropic hyperpolarized structures, such as collagen. During the past years, several quantification methods to analyze and evaluate these images have been developed. However, automated or semiautomated solutions are necessary to ensure objectivity and reproducibility of such analysis. This work describes automation and improvement methods for calculating the anisotropy (using fast Fourier transform analysis and the gray-level co-occurrence matrix). These were applied to analyze biopsy samples of human ovarian epithelial cancer at different stages of malignancy (mucinous, serous, mixed, and endometrial subtypes). The semiautomation procedure enabled us to design a diagnostic protocol that recognizes between healthy and pathologic tissues, as well as between different tumor types.

No MeSH data available.


Related in: MedlinePlus

(A) Phantoms used to represent straight (normal) and wavy (pathologic) collagen fibers of stromal ovarian tumors—1: normal; 4: pathologic; 2 and 3: intermediate condition representations. (B) FFT outcomes of phantoms shown in (A) indicating AR. (C) GLCM-texture parameters (correlation, contrast, entropy, and energy) used to characterize phantoms, as a function of d (0–50) in the directions of 0°, 45°, 90°, and 135°. Black line: phantom 1 (straight fibers); red line: phantom 2 (tilted straight fiber); green line: phantom 3 (wavy fibers); and yellow line: phantom 4 (disorganized fibers). AR indicates aspect ratio; FFT, fast Fourier transform; GLCM; gray-level co-occurrence matrix.
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f3-10.1177_1176935117690162: (A) Phantoms used to represent straight (normal) and wavy (pathologic) collagen fibers of stromal ovarian tumors—1: normal; 4: pathologic; 2 and 3: intermediate condition representations. (B) FFT outcomes of phantoms shown in (A) indicating AR. (C) GLCM-texture parameters (correlation, contrast, entropy, and energy) used to characterize phantoms, as a function of d (0–50) in the directions of 0°, 45°, 90°, and 135°. Black line: phantom 1 (straight fibers); red line: phantom 2 (tilted straight fiber); green line: phantom 3 (wavy fibers); and yellow line: phantom 4 (disorganized fibers). AR indicates aspect ratio; FFT, fast Fourier transform; GLCM; gray-level co-occurrence matrix.

Mentions: Facing different fiber arrangements, to understand the meaning and behavior of the obtained variables, artificial images (phantoms) simulating those arrangements were made (Figure 3). Ovary collagen fiber package widths were measured using the line and the Scarbar plus commands of the ImageJ software (range, 1–3 µm). This operation allows us to determine that fibers have a width of approximately 2.5 µm. Because all ovarian stroma images used are 1024 × 1024 pixels (212.25 µm × 212.25 µm), fiber width would be around 12 pixels. The phantoms were generated with known thickness, spacing, and orientation fibers. Simulated fibers were built with a width and interspacing of 13 pixels, in agreement with the data of Hu et al.20 Two phantoms of straight fibers were built with 0° and 45° orientation angles, one with wavy fibers and the other having random fiber distribution (Figure 3A).


Epithelial Ovarian Cancer Diagnosis of Second-Harmonic Generation Images: A Semiautomatic Collagen Fibers Quantification Protocol
(A) Phantoms used to represent straight (normal) and wavy (pathologic) collagen fibers of stromal ovarian tumors—1: normal; 4: pathologic; 2 and 3: intermediate condition representations. (B) FFT outcomes of phantoms shown in (A) indicating AR. (C) GLCM-texture parameters (correlation, contrast, entropy, and energy) used to characterize phantoms, as a function of d (0–50) in the directions of 0°, 45°, 90°, and 135°. Black line: phantom 1 (straight fibers); red line: phantom 2 (tilted straight fiber); green line: phantom 3 (wavy fibers); and yellow line: phantom 4 (disorganized fibers). AR indicates aspect ratio; FFT, fast Fourier transform; GLCM; gray-level co-occurrence matrix.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5392028&req=5

f3-10.1177_1176935117690162: (A) Phantoms used to represent straight (normal) and wavy (pathologic) collagen fibers of stromal ovarian tumors—1: normal; 4: pathologic; 2 and 3: intermediate condition representations. (B) FFT outcomes of phantoms shown in (A) indicating AR. (C) GLCM-texture parameters (correlation, contrast, entropy, and energy) used to characterize phantoms, as a function of d (0–50) in the directions of 0°, 45°, 90°, and 135°. Black line: phantom 1 (straight fibers); red line: phantom 2 (tilted straight fiber); green line: phantom 3 (wavy fibers); and yellow line: phantom 4 (disorganized fibers). AR indicates aspect ratio; FFT, fast Fourier transform; GLCM; gray-level co-occurrence matrix.
Mentions: Facing different fiber arrangements, to understand the meaning and behavior of the obtained variables, artificial images (phantoms) simulating those arrangements were made (Figure 3). Ovary collagen fiber package widths were measured using the line and the Scarbar plus commands of the ImageJ software (range, 1–3 µm). This operation allows us to determine that fibers have a width of approximately 2.5 µm. Because all ovarian stroma images used are 1024 × 1024 pixels (212.25 µm × 212.25 µm), fiber width would be around 12 pixels. The phantoms were generated with known thickness, spacing, and orientation fibers. Simulated fibers were built with a width and interspacing of 13 pixels, in agreement with the data of Hu et al.20 Two phantoms of straight fibers were built with 0° and 45° orientation angles, one with wavy fibers and the other having random fiber distribution (Figure 3A).

View Article: PubMed Central - PubMed

ABSTRACT

A vast number of human pathologic conditions are directly or indirectly related to tissular collagen structure remodeling. The nonlinear optical microscopy second-harmonic generation has become a powerful tool for imaging biological tissues with anisotropic hyperpolarized structures, such as collagen. During the past years, several quantification methods to analyze and evaluate these images have been developed. However, automated or semiautomated solutions are necessary to ensure objectivity and reproducibility of such analysis. This work describes automation and improvement methods for calculating the anisotropy (using fast Fourier transform analysis and the gray-level co-occurrence matrix). These were applied to analyze biopsy samples of human ovarian epithelial cancer at different stages of malignancy (mucinous, serous, mixed, and endometrial subtypes). The semiautomation procedure enabled us to design a diagnostic protocol that recognizes between healthy and pathologic tissues, as well as between different tumor types.

No MeSH data available.


Related in: MedlinePlus