Computationally Enabled Polychromatic Polarized Imaging Enables Mapping of Matrix Architectures that Promote...

Pancreatic ductal adenocarcinoma (PDA) is a highly metastatic and lethal disease. In PDA, extracellular matrix (ECM) architectures, known as tumor-associated collagen signatures (TACSs), regulate invasion and metastatic spread in both early dissemination and late-stage disease. As such, TACS has been suggested as a biomarker to aid in pathologic assessment. However, despite its significance, approaches to quantitatively capture these ECM patterns currently require advanced optical systems with signaling processing analysis. Herein, an expansion of polychromatic polarized microscopy (PPM) with inherent angular information coupled with machine learning and computational pixel-wise analysis of TACS was used to accurately capture TACS architectures in hematoxylin and eosin-stained histology sections directly through PPM contrast. Moreover, PPM facilitated identification of transitions to dissemination architectures (ie, transitions from sequestration through expansion to dissemination from both pancreatic intraepithelial neoplasias and throughout PDA). Lastly, PPM evaluation of architectures in liver metastases, the most common metastatic site for PDA, demonstrated TACS-mediated focal and local invasion as well as identification of unique patterns anchoring aligned fibers into normal-adjacent tumor, suggesting that these patterns may be precursors to metastasis expansion and local spread from micrometastatic lesions. Combined, these findings demonstrate that PPM coupled to computational platforms is a powerful tool for analyzing ECM architecture that can be used to advance cancer microenvironment studies and provide clinically relevant diagnostic information.