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Chemotherapy drug potency assessment method of ovarian cancer cells by digital holography microscopy

  • Yakun Liu
  • , Wen Xiao
  • , Huanzhi Zhang
  • , Lu Xin
  • , Xiaoping Li
  • , Feng Pan*
  • *Corresponding author for this work
  • Beihang University
  • Peking University

Research output: Contribution to journalArticlepeer-review

Abstract

Drug potency assessment plays a crucial role in cancer chemotherapy. The selection of appropriate chemotherapy drugs can reduce the impact on the patient’s physical condition and achieve a better therapeutic effect. Various methods have been used to achieve in vitro drug susceptibility assays, but there are few studies on calculating morphology and texture parameters quantitatively based on phase imaging for drug potency assessment. In this study, digital holography microscopy was used to get phase imaging of ovarian cancer cells after adding three different drugs, namely, Cisplatin, Adriamycin, and 5-fluorouracil. Based on the reconstructed phase imaging, four parameters of ovarian cancer cells changed with time, such as the average height, projected area, cluster shade, and entropy, were calculated. And the half-inhibitory concentration of cells under the effect of different drugs was calculated according to these four parameters. The half-inhibitory concentration, which can directly reflect the drug potency, is associated with the morphological and texture features extracted from phase images by numerical fitting. So, a new method for calculating the half-inhibitory concentration was proposed. The result shows that the morphological and texture feature parameters can be used to evaluate the sensitivity of ovarian cancer cells to different drugs by fitting the half-inhibitory concentration numerically. And the result provides a new idea for drug potency assessment methods before chemotherapy for ovarian cancer.

Original languageEnglish
Pages (from-to)4370-4385
Number of pages16
JournalBiomedical Optics Express
Volume13
Issue number8
DOIs
StatePublished - 1 Aug 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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