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Updated: Jun 9, 2026

A Time-lapse, Label-free, Quantitative Phase Imaging Study of Dormant and Active Human Cancer Cells
Published on: February 16, 2018
Spatial-domain low-coherence quantitative phase microscopy for cancer diagnosis
Pin Wang1, Rajan Bista, Rohit Bhargava
1Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania 15232, USA.
Spatial-domain low-coherence quantitative phase microscopy (SL-QPM) offers speckle-free imaging of subcellular structures. This novel method accurately measures cell nucleus refractive index, aiding early cancer detection in clinical settings.
Area of Science:
- Biomedical Optics
- Cell Biology
- Cancer Diagnostics
Background:
- Quantitative phase microscopy (QPM) enables label-free imaging of biological samples.
- Subcellular structures and their optical properties are crucial for understanding cell function and disease.
- Current methods for refractive index measurement often require complex sample preparation.
Purpose of the Study:
- To introduce spatial-domain low-coherence quantitative phase microscopy (SL-QPM) for high-sensitivity imaging.
- To quantify the refractive index of cell nuclei in native histology specimens.
- To evaluate the potential of refractive index measurements for early cancer detection.
Main Methods:
- Development and application of SL-QPM for speckle-free imaging.
- Measurement of refractive index of cell nuclei in unmodified histology samples.
- Correlation of refractive index changes with cancer presence.
Main Results:
- SL-QPM achieved subnanometer sensitivity for imaging subcellular structures.
- The refractive index of cell nuclei was successfully quantified in original histology specimens.
- Cell nucleus refractive index demonstrated high sensitivity in detecting cancer, including in normal-appearing cells from patients.
Conclusions:
- SL-QPM is a powerful tool for label-free, high-sensitivity imaging of subcellular structures.
- Quantifying cell nucleus refractive index offers a promising biomarker for early cancer detection.
- The technique's simplicity and lack of special sample processing facilitate clinical translation.
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