Presentation
12 August 2023 High-resolution imaging and modeling of collagen architecture alterations in high-grade serous ovarian cancer
Paul J. Campagnola, Farid Atry, Samuel Alkmin, Vikas Singh, Bruce L. Wen, Kirby R. Campbell, Manish Patankar, Melissa Champer, Chi-Hsiang Lien
Author Affiliations +
Abstract
We have developed SHG microscope tools to probe all levels of collagen architecture organization in human high grade serous ovarian cancer (HSOC). We have found pronounced differences using machine learning classification of the fiber morphology as well as alterations in macro/supramolecular structural aspects through polarization analysis. We have used multiphoton excited fabrication to create SHG image-based orthogonal models that represent both the collagen morphology and stiffness of normal ovarian stroma and HGSOC. We found the fiber morphology of HGSOC promotes motility through a contact guidance mechanism and that stiffer matrix further promotes these same processes through a mechanosensitive mechanism. We have also developed a machine learning approach using generative adversarial networks (GANs) to optimize the scaffold design. Collectively, this data provides insight into disease etiology and suggests future diagnostic approaches.
Conference Presentation
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paul J. Campagnola, Farid Atry, Samuel Alkmin, Vikas Singh, Bruce L. Wen, Kirby R. Campbell, Manish Patankar, Melissa Champer, and Chi-Hsiang Lien "High-resolution imaging and modeling of collagen architecture alterations in high-grade serous ovarian cancer", Proc. SPIE PC12622, Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VI, PC126220O (12 August 2023); https://doi.org/10.1117/12.2678187
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KEYWORDS
Collagen

Ovarian cancer

Image resolution

Modeling

Second harmonic generation

Cancer

Diseases and disorders

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