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Towards in vivo preclinical monitoring of multiscale vascular structure-function relationships in resistant breast cancers with an integrated diffuse and nonlinear imaging system (Conference Presentation)
Author(s): Kavon Karrobi; Anahita Pilvar; Anup Tank; Kshama Doshi; David J. Waxman; Darren Roblyer

Paper Abstract

Alterations in tumor microvascular architecture are associated with resistance to several breast cancer therapies, and may be important markers for in vivo detection of resistance. Our goal is to map how micro-scale alterations in tumor vasculature manifest at the tissue level. To this end, we developed a multiscale preclinical imaging technique called Diffuse and Nonlinear Imaging (DNI) that integrates Spatial Frequency Domain Imaging (SFDI) for tissue-level mapping of tumor optical properties and hemodynamics, with Multiphoton Microscopy (MPM) to image tumor microvascular architecture with cellular resolution. Importantly, SFDI measures the same parameters as clinical Diffuse Optical Spectroscopy, providing a pathway to the clinic for microvascular imaging biomarkers. We demonstrated that the dual modality system can be spatially co-registered with high accuracy and precision (≤ 50 µm), and can be matched in optical sampling depth based on wavelength and spatial frequency selection. We also conducted an in vivo DNI study of untreated murine mammary tumors (Py230) in female C57BL/6 mice, and found strong multiscale relationships between tumor oxygen saturation and micro-vessel diameter, as well as deoxyhemoglobin concentrations and micro-vessel length (|Pearson’s ρ| > 0.5, p < 0.05). We carried out in vivo DNI monitoring in two mammary tumor xenograft models grown in BALB/c athymic nude female mice; one model was responsive to Trastuzumab (Herceptin®) (BT474) and the other was resistant (HR6). This presentation will report on characterizing the vascular structure-function relationships with DNI across length scales within each model, and differences in the multiscale vascular relationships between the models.

Paper Details

Date Published: 4 March 2019
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Proc. SPIE 10871, Multimodal Biomedical Imaging XIV, 108710E (4 March 2019); doi: 10.1117/12.2508872
Show Author Affiliations
Kavon Karrobi, Boston Univ. (United States)
Anahita Pilvar, Boston Univ. (United States)
Anup Tank, Boston Univ. (United States)
Kshama Doshi, Boston Univ. (United States)
David J. Waxman, Boston Univ. (United States)
Darren Roblyer, Boston Univ. (United States)


Published in SPIE Proceedings Vol. 10871:
Multimodal Biomedical Imaging XIV
Fred S. Azar; Xavier Intes; Qianqian Fang, Editor(s)

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