Honors Theses

Evaluation of Irreversibly Sickled Cells with Imaging Flow Cytometry and Machine Learning: A Faster and More Consistent Alternative


Katie Seu, Ph.D.


Chemical and Materials Engineering

Publication Date


Document Type

Honors Thesis


Sickle cell disease is an inherited blood disease where a mutation causes hemoglobin S (HbS) to be produced instead of normal adult hemoglobin (HbA). In low oxygen content, HbS polymerizes which causes the red blood cells (RBCs) to deform into a rigid, sickled shape. The RBCs can usually return to their normal biconcave shape after reoxygenation, but after repeated cycles of this process, some of them become stuck as sickled cells and are then referred to as irreversibly sickled cells (ISCs). The percentage of these ISCs is a valuable biomarker used to indicate long-term damage to cells and can be used to evaluate the effectiveness of anti-sickling therapeutic agents. In addition, it can help doctors better understand how patients are managing their disease. The current methodology to determine the percent ISCs is to manually count cells in a wet slide with a microscope which is time-consuming, subjective, and not clinically approved. We developed and tested a high-throughput ISC assay that is quicker and less subjective than the current methods. This novel assay utilizes imaging flow cytometry (ImageStreamTM) and machine learning analysis software (IDEASTM) to produce a high-throughput and accurate method for determining the ISC percentage. We then tested the assay using patient samples and compared the results to the current method of wet slides as well as to a previous method developed using imaging flow cytometry called the sickle imaging flow cytometry assay (SIFCA). The new machine learning assay correlates more strongly with the current manual counting of cells than the SIFCA. In addition, it doesn’t require training operators to recognize sickle cells or manually count them. We hope this new assay can be used to better monitor the health of patients and test for the effectiveness of new anti-sickling agents.

Permission Statement

This item is protected by copyright law (Title 17, U.S. Code) and may only be used for noncommercial, educational, and scholarly purposes.


Undergraduate research

This document is currently not available here.