Research Papers: Imaging

Label-free tissue scanner for colorectal cancer screening

[+] Author Affiliations
Mikhail E. Kandel

University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United States

University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States

Shamira Sridharan

University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United States

University of Illinois at Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United States

University of California, Biomedical Engineering Department, Davis, California, United States

Jon Liang, Zelun Luo, Kevin Han

University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United States

Virgilia Macias, Anish Shah, Roshan Patel, Andre Kajdacsy-Balla, Grace Guzman

University of Illinois at Chicago, Department of Pathology, Chicago, Illinois, United States

Krishnarao Tangella

Christie Clinic, Department of Pathology, Urbana, Illinois, United States

Gabriel Popescu

University of Illinois at Urbana-Champaign, Beckman Institute of Advanced Science and Technology, Quantitative Light Imaging Laboratory, Urbana, Illinois, United States

University of Illinois at Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States

University of Illinois at Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United States

J. Biomed. Opt. 22(6), 066016 (Jun 24, 2017). doi:10.1117/1.JBO.22.6.066016
History: Received December 23, 2016; Accepted May 22, 2017
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Abstract.  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.

Figures in this Article
© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Mikhail E. Kandel ; Shamira Sridharan ; Jon Liang ; Zelun Luo ; Kevin Han, et al.
"Label-free tissue scanner for colorectal cancer screening", J. Biomed. Opt. 22(6), 066016 (Jun 24, 2017). ; http://dx.doi.org/10.1117/1.JBO.22.6.066016


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