The current practice of surgical pathology relies on external contrast agents to reveal tissue architecture, which is then qualitatively examined by a trained pathologist. The diagnosis is based on the comparison with standardized empirical, qualitative assessments of limited objectivity. We propose an approach to pathology based on interferometric imaging of “unstained” biopsies, which provides unique capabilities for quantitative diagnosis and automation. We developed a label-free tissue scanner based on “quantitative phase imaging,” which maps out optical path length at each point in the field of view and, thus, yields images that are sensitive to the “nanoscale” tissue architecture. Unlike analysis of stained tissue, which is qualitative in nature and affected by color balance, staining strength and imaging conditions, optical path length measurements are intrinsically quantitative, i.e., images can be compared across different instruments and clinical sites. These critical features allow us to automate the diagnosis process. We paired our interferometric optical system with highly parallelized, dedicated software algorithms for data acquisition, allowing us to image at a throughput comparable to that of commercial tissue scanners while maintaining the nanoscale sensitivity to morphology. Based on the measured phase information, we implemented software tools for autofocusing during imaging, as well as image archiving and data access. To illustrate the potential of our technology for large volume pathology screening, we established an “intrinsic marker” for colorectal disease that detects tissue with dysplasia or colorectal cancer and flags specific areas for further examination, potentially improving the efficiency of existing pathology workflows.
Recent studies have revealed the importance of outlier cells in complex cellular systems. Quantifying heterogeneity in such systems may lead to a better understanding of organ engineering, microtumor growth, and disease models, as well as more precise drug design. We used the ability of quantitative phase imaging to perform long-term imaging of cell growth to estimate the "influence" of cellular clusters on their neighbors. We validated our approach by analyzing epithelial and fibroblast cultures imaged over the course of several days. Interestingly, we found that there is a significant number of cells characterized by a medium correlation between their growth rate and distance (modulus of the Pearson coefficient between 0.25-.5). Furthermore, we found a small percentage of cells exhibiting strong such correlations, which we label as "influencer" cellular clusters. Our approach might find important applications in studying dynamic phenomena, such as organogenesis and metastasis.
Samoyed hereditary glomerulopathy (SHG) is an X-linked dominant disease characterized by proteinuria and renal failure in affected male dogs. Electron microscopic examination of glomerular capillary basement membranes (GCBM) shows widespread multilaminar splitting of the lamina densa, identical to that in Alport's syndrome. Anionic sites in GCBM of three affected males and five unaffected dogs were labeled using polyethyleneimine to determine whether proteinuria was associated with an alteration in their number. No significant differences were noted in the number of anionic sites in the lamina rara externa, whereas small but statistically significant increases were seen in the number of sites in the lamina rara interna of affected males. In the lamina densa, affected males showed a striking increase in anionic sites, particularly in regions of GCBM which were split. Thus, although proteinuria in some glomerular diseases has been attributed to a reduction in anionic sites in GCBM, this was not so in SHG.
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