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Updated: Dec 13, 2025
A Precision Medicine Tool for Measurement and Monitoring of Hemoglobin S in Sickle Cell Disease Patients Receiving Transfusion Therapy
Smartphone-based sickle cell disease detection and monitoring for point-of-care settings
Shazia Ilyas1, Mazhar Sher1, E Du2
1Department of Computer & Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA; Asghar-Lab, Micro and Nanotechnology in Medicine, College of Engineering and Computer Science, Boca Raton, FL, 33431, USA.
Insights
A new smartphone-based method accurately detects sickle cell disease (SCD) by analyzing red blood cells (RBCs). This low-cost, point-of-care test is ideal for resource-limited settings, improving SCD diagnosis and management.
Area of Science:
- Hematology
- Biomedical Engineering
- Point-of-Care Diagnostics
Background:
- Sickle cell disease (SCD) is a global health issue, prevalent in resource-limited areas, causing severe complications and mortality.
- Current diagnostic methods are lab-based, time-consuming, costly, and unsuitable for point-of-care (POC) or home use.
- There is a critical need for accessible, rapid diagnostic tools for early SCD detection and management, especially in underserved regions.
Purpose of the Study:
- To develop and validate a smartphone-based imaging technique for diagnosing and monitoring sickle cell disease (SCD).
- To create a cost-effective and user-friendly POC diagnostic tool for SCD, suitable for low-resource settings.
- To demonstrate the feasibility of using smartphone technology for red blood cell (RBC) analysis in both normoxia and hypoxia.
Main Methods:
- Smartphone-based image acquisition of red blood cells (RBCs) from SCD patients under varying oxygen conditions (normoxia and hypoxia).
- Development of a computer algorithm to differentiate normal RBCs from sickled RBCs before and after induced sickling.
- Comparison of results obtained from the smartphone technique with conventional microscopy-based analysis.
Main Results:
- The smartphone-based method achieved comparable accuracy to standard microscopy in quantifying the percentage of sickle cells.
- The developed technique successfully differentiated RBCs based on sickling status.
- The system demonstrated potential for cost reduction in SCD screening and management.
Conclusions:
- Smartphone-based imaging offers a practical and accessible solution for SCD diagnosis and monitoring in resource-limited settings.
- The technique's simplicity and lack of special storage requirements make it advantageous over existing hemoglobin-based POC tests.
- This innovation holds promise for improving global health outcomes for individuals with sickle cell disease.
Abstract:
Sickle cell disease (SCD) is a worldwide hematological disorder causing painful episodes, anemia, organ damage, stroke, and even deaths. It is more common in sub-Saharan Africa and other resource-limited countries. Conventional laboratory-based diagnostic methods for SCD are time-consuming, complex, and cannot be performed at point-of-care (POC) and home settings. Optical microscope-based classification and counting demands a significant amount of time, extensive setup, and cost along with the skilled human labor to distinguish the normal red blood cells (RBCs) from sickled cells. There is an unmet need to develop a POC and home-based test to diagnose and monitor SCD and reduce mortality in resource-limited settings. An early-stage and timely diagnosis of SCD can help in the effective management of the disease. In this article, we utilized a smartphone-based image acquisition method for capturing RBC images from the SCD patients in normoxia and hypoxia conditions. A computer algorithm is developed to differentiate RBCs from the patient's blood before and after cell sickling. Using the developed smartphone-based technique, we obtained similar percentage of sickle cells in blood samples as analyzed by conventional method (standard microscope). The developed method of testing demonstrates the potential utility of the smartphone-based test for reducing the overall cost of screening and management for SCD, thus increasing the practicality of smartphone-based screening technique for SCD in low-resource settings. Our setup does not require any special storage requirements. This is the characteristic advantage of our technique as compared to other hemoglobin-based POC diagnostic techniques.
