In vitro analysis of exfoliated cells plays an important role in disease screening and clinical diagnosis. An accurate cytological diagnosis depends largely on the ability to detect changes in cellular and nuclear structural characteristics of individual single cells. The diffraction-limited resolution of a conventional light microscope limis the detection of mostly micron-scale features of cancer cells, which result in intra-observer variation, missed early-stage cancers (false negatives), and indeterminate cases that often result in unnecessary invasive procedures in the absence of cancer (false positives). Technologies that perform high-speed, accurate, quantitative and cost-effective cytological analysis and are suitable for routine clinic use are urgently needed. Cellular nanoscale structural changes represent a promising strategy for identifying pre-cancerous or cancerous cells. We have recently developed two complementary techniques, both of which can assess nanoscale structural characteristics at the single-cell level: quantitative phase microscopy and spectral-encoding of spatial frequency (SESF). We demonstrated their ability to detect structural changes in pre-cancerous cells missed by conventional light microscopy. We propose to develop a new advanced microscopy that integrates the complementary attributes of these two techniques to perform real-time quantitative structural imaging and high-speed and comprehensive nanoscale structural analysis of label-free single cells in their natural state for use in both research and clinical applications. The technical performance of this microscopy system will be characterized and their ability to analyze nanoscale structures will be rigorously validated. It will be optimized for routine clinical use to analyze unstained exfoliative cytology specimens by developing cell segmentation algorithm and multi-metric structural analysis. We will focus on two large-volume and clinically challenging cytology specimens as our disease models: cervical and urine cytology. The accuracy of the system will be tested using a relatively large scale of cervical and urine cytology specimens via a training and a validation set. If successful, this technique could be used to support conventional cytology for accurate, quantitative, high-speed, comprehensive and cost-effective cytological analysis to improve the diagnostic accuracy and prevent costly unnecessary procedures.

Public Health Relevance

This project aims to develop an advanced imaging microscopy system for high-speed and comprehensive nanoscale structural analysis of unlabeled single cells for use in research and clinical applications. It will be optimized for routne clinical use to analyze exfoliative cytology, which plays a significant role in disease screening and diagnosis. If successful, the technique will significantly improve the diagnostic accuracy of cancer screening and reduce number of false positives and false negatives.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB016657-03
Application #
8826115
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Conroy, Richard
Project Start
2013-04-01
Project End
2016-03-31
Budget Start
2015-04-01
Budget End
2016-03-31
Support Year
3
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Uttam, Shikhar; Liu, Yang (2018) Fourier phase based depth-resolved nanoscale nuclear architecture mapping for cancer detection. Methods 136:134-151
Xu, Jianquan; Ma, Hongqiang; Jin, Jingyi et al. (2018) Super-Resolution Imaging of Higher-Order Chromatin Structures at Different Epigenomic States in Single Mammalian Cells. Cell Rep 24:873-882
Xu, Jianquan; Ma, Hongqiang; Liu, Yang (2017) Stochastic Optical Reconstruction Microscopy (STORM). Curr Protoc Cytom 81:12.46.1-12.46.27
Ma, Hongqiang; Fu, Rao; Xu, Jianquan et al. (2017) A simple and cost-effective setup for super-resolution localization microscopy. Sci Rep 7:1542
Ma, Hongqiang; Xu, Jianquan; Jin, Jingyi et al. (2017) A Simple Marker-Assisted 3D Nanometer Drift Correction Method for Superresolution Microscopy. Biophys J 112:2196-2208
Pham, Hoa V; Pantanowitz, Liron; Liu, Yang (2016) Quantitative phase imaging to improve the diagnostic accuracy of urine cytology. Cancer Cytopathol 124:641-50
Sun, Luxi; Tan, Rong; Xu, Jianquan et al. (2015) Targeted DNA damage at individual telomeres disrupts their integrity and triggers cell death. Nucleic Acids Res 43:6334-47
Del Portillo, Armando; Lagana, Stephen M; Yao, Yuan et al. (2015) Evaluation of Mutational Testing of Preneoplastic Barrett's Mucosa by Next-Generation Sequencing of Formalin-Fixed, Paraffin-Embedded Endoscopic Samples for Detection of Concurrent Dysplasia and Adenocarcinoma in Barrett's Esophagus. J Mol Diagn 17:412-9
Ma, Hongqiang; Xu, Jianquan; Jin, Jingyi et al. (2015) Fast and Precise 3D Fluorophore Localization based on Gradient Fitting. Sci Rep 5:14335
Uttam, Shikhar; Pham, Hoa V; LaFace, Justin et al. (2015) Early Prediction of Cancer Progression by Depth-Resolved Nanoscale Mapping of Nuclear Architecture from Unstained Tissue Specimens. Cancer Res 75:4718-27

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