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Quantifying collagen structure in breast biopsies using second-harmonic generation imaging

Quantitative second-harmonic generation imaging is employed to assess stromal collagen in normal, hyperplastic, dysplastic, and malignant breast tissues. The cellular scale organization is quantified using Fourier transform-second harmonic generation imaging (FT-SHG), while the molecular scale organ...

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Detalles Bibliográficos
Autores principales: Ambekar, Raghu, Lau, Tung-Yuen, Walsh, Michael, Bhargava, Rohit, Toussaint, Kimani C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Optical Society of America 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3447546/
https://www.ncbi.nlm.nih.gov/pubmed/23024898
http://dx.doi.org/10.1364/BOE.3.002021
Descripción
Sumario:Quantitative second-harmonic generation imaging is employed to assess stromal collagen in normal, hyperplastic, dysplastic, and malignant breast tissues. The cellular scale organization is quantified using Fourier transform-second harmonic generation imaging (FT-SHG), while the molecular scale organization is quantified using polarization-resolved second-harmonic generation measurements (P-SHG). In the case of FT-SHG, we apply a parameter that quantifies the regularity in collagen fiber orientation and find that malignant tissue contains locally aligned fibers compared to other tissue conditions. Alternatively, using P-SHG we calculate the ratio of tensor elements (d(15)/d(31), d(22)/d(31), and d(33)/d(31)) of the second-order susceptibility χ(2) for collagen fibers in breast biopsies. In particular, d(15)/d(31) shows potential differences across the tissue pathology. We also find that trigonal symmetry (3m) is a more appropriate model to describe collagen fibers in malignant tissues as opposed to the conventionally used hexagonal symmetry (C6). This novel method of targeting collagen fibers using a combination of two quantitative SHG techniques, FT-SHG and P-SHG, holds promise for breast tissue analysis and applications to characterizing cancer in a manner that is compatible with clinical practice.