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Updated: Jun 29, 2025
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A Time-lapse, Label-free, Quantitative Phase Imaging Study of Dormant and Active Human Cancer Cells
Published on: February 16, 2018
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Perspective on quantitative phase imaging to improve precision cancer medicine
Yang Liu1,2, Shikhar Uttam3
1University of Illinois Urbana-Champaign, Beckman Institute for Advanced Science and Technology, Cancer Center at Illinois, Department of Bioengineering, Department of Electrical and Computer Engineering, Urbana, Illinois, United States.
Journal of Biomedical Optics
|April 8, 2024
Summary
Quantitative phase imaging (QPI) is a label-free technique that non-invasively characterizes cells and tissues. This method advances precision cancer medicine through enhanced diagnostics, risk assessment, and monitoring of treatment efficacy.
Area of Science:
- Biophysics
- Optical Imaging
- Cancer Research
Background:
- Quantitative Phase Imaging (QPI) is a label-free optical technique that quantifies cellular biophysical properties by measuring refractive index-based contrast.
- QPI translates phase shifts caused by refractive index variations into quantifiable intensity data with nanoscale precision.
- Its non-invasive nature and sensitivity make it ideal for studying cells and tissues in their native states.
Purpose of the Study:
- To explore the potential of QPI in understanding cancer development and response to therapy.
- To discuss advancements in QPI methodologies for personalized cancer treatment and early detection.
- To highlight QPI's role in precision cancer medicine.
Main Methods:
- Review of technical advancements in QPI, including transmission and reflection geometries.
- Examination of interferometric and non-interferometric phase retrieval techniques.
- Discussion of QPI applications such as dynamic cell mass imaging, cancer risk stratification, and in vivo tissue imaging.
Main Results:
- QPI provides crucial insights into tumor biology and treatment effectiveness.
- The technique's sensitivity to nanoscale changes aids in cancer diagnostics, risk assessment, and prognostication.
- Integration with AI, morpho-dynamics, and spatial biology is expanding QPI's impact in cancer research.
Conclusions:
- QPI holds significant potential to advance precision cancer medicine, improving diagnosis, monitoring, and treatment.
- Future directions include high-throughput dynamic imaging, 3D QPI, and AI-driven multi-omics integration.
- QPI is positioned as a key technology in cancer research and clinical applications.
