Presentation
24 April 2017 Improved cancer risk stratification and diagnosis via quantitative phase microscopy (Conference Presentation)
Author Affiliations +
Proceedings Volume 10074, Quantitative Phase Imaging III; 1007416 (2017) https://doi.org/10.1117/12.2252276
Event: SPIE BiOS, 2017, San Francisco, California, United States
Abstract
Pathology remains the gold standard for cancer diagnosis and in some cases prognosis, in which trained pathologists examine abnormality in tissue architecture and cell morphology characteristic of cancer cells with a bright-field microscope. The limited resolution of conventional microscope can result in intra-observer variation, missed early-stage cancers, and indeterminate cases that often result in unnecessary invasive procedures in the absence of cancer. Assessment of nanoscale structural characteristics via quantitative phase represents a promising strategy for identifying pre-cancerous or cancerous cells, due to its nanoscale sensitivity to optical path length, simple sample preparation (i.e., label-free) and low cost. I will present the development of quantitative phase microscopy system in transmission and reflection configuration to detect the structural changes in nuclear architecture, not be easily identifiable by conventional pathology. Specifically, we will present the use of transmission-mode quantitative phase imaging to improve diagnostic accuracy of urine cytology and the nuclear dry mass is progressively correlate with negative, atypical, suspicious and positive cytological diagnosis. In a second application, we will present the use of reflection-mode quantitative phase microscopy for depth-resolved nanoscale nuclear architecture mapping (nanoNAM) of clinically prepared formalin-fixed, paraffin-embedded tissue sections. We demonstrated that the quantitative phase microscopy system detects a gradual increase in the density alteration of nuclear architecture during malignant transformation in animal models of colon carcinogenesis and in human patients with ulcerative colitis, even in tissue that appears histologically normal according to pathologists. We evaluated the ability of nanoNAM to predict "future" cancer progression in patients with ulcerative colitis.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yang Liu, Shikhar Uttam, Hoa V. Pham, and Douglas J. Hartman M.D. "Improved cancer risk stratification and diagnosis via quantitative phase microscopy (Conference Presentation)", Proc. SPIE 10074, Quantitative Phase Imaging III, 1007416 (24 April 2017); https://doi.org/10.1117/12.2252276
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KEYWORDS
Cancer

Microscopy

Tissues

Microscopes

Pathology

Phase imaging

Animal model studies

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