A framework of computer vision-enhanced microfluidic approach for automated assessment of the transient sickling kinetics in sickle red blood cells

Yuhao Qiang, Mengjia Xu, Mira Patel Pochron, Madhulika Jupelli, Ming Dao

Research output: Contribution to journalArticlepeer-review

Abstract

The occurrence of vaso-occlusive crisis greatly depends on the competition between the sickling delay time and the transit time of individual sickle cells, i.e., red blood cells from sickle cell disease (SCD) patients, while they are traversing the circulatory system. Many drugs for treating SCD work by inhibiting the polymerization of sickle hemoglobin (HbS), effectively delaying the sickling process in sickle cells (SS RBCs). Most previous studies on screening anti-sickling drugs, such as voxelotor, rely on in vitro testing of sickling characteristics, often conducted under prolonged deoxygenation for up to 1 hour. However, since the microcirculation of RBCs typically takes less than 1 minute, the results of these studies may be less accurate and less relevant for in vitro-in vivo correlation. In our current study, we introduce a computer vision-enhanced microfluidic framework designed to automatically capture the transient sickling kinetics of SS RBCs within a 1-min timeframe. Our study has successfully detected differences in the transient sickling kinetics between vehicle control and voxelotor-treated SS RBCs. This approach has the potential for broader applications in screening anti-sickling therapies.

Original languageEnglish (US)
Article number1331047
JournalFrontiers in Physics
Volume12
DOIs
StatePublished - 2024
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Materials Science (miscellaneous)
  • Mathematical Physics
  • General Physics and Astronomy
  • Physical and Theoretical Chemistry

Keywords

  • automated sickling kinetics assay
  • deep learning
  • drug testing
  • image segmentation and classification
  • microfluidics
  • sickle cell disease

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