Multiscale Imaging of collagen topology in cancer invasion and progression
Kevin Eliceiri
University of Wisconsin-Madison, USA
Abstract
The multi-level structure of tissue, from the arrangement of cells to the composition of organs, is a key factor in many major diseases. Differences in these micro-environments determine how likely a metastasis is to occur and thus how the disease will progress on the tissue-mesoscale and organ-macroscale. The converse can also be true, where macroscale composition affects the disease. A specific example with motivating interest to our lab is the role of collagen in breast cancer invasion and progression. The microscale alignment of collagen fibers around a tumor boundary increases the risk of metastasis, while the macroscale density of collagen is related to risk of developing breast cancer. Collagen thus plays a large role in the disease, but there are still many questions about its multiscale significance because there are not yet sufficient imaging tools to directly correlate the microscale to macroscale and because we still do not fully understand the mechanism of the macroscale density influencing risk. Many other cancers and diseases have analogous interactions across spatial scales.
To help address this need, we have developed an integrated multiscale-imaging system that can image tissue samples in the same condition for all component modalities: Ultrasound (US), Multiphoton Microscopy (MPM), Optical Coherence Tomography (OCT), and Enhanced Backscattering (EBS). These modalities were selected because they are all sensitive to changes in fibrillar collagen organization, which is the driving motivation for this instrument. The modalities are all inherently multiscale as they derive part of their contrast from scattering off of structures smaller than their resolution. In this work, the MPM modality can acquire Second Harmonic Generation (SHG) and Two Photon Excited Fluorescence (TPEF) signal. Based on our past published work, SHG can detect collagen fiber organization at sub-micron resolution, whereas US is clinically compatible and is sensitive to larger scale collagen architecture. Their combination then allows us to measure how differences in microscale composition and fiber arrangement change in clinical US images. This talk details the system design, computational approaches and preliminary data informing on the role of collagen topology in several cancer models.