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Sickle cell detection using a smartphone.

S M Knowlton¹, I Sencan², Y Aytar³

¹Department of Biomedical Engineering, University of Connecticut, 260 Glenbrook Road, Storrs, CT 06269.

Scientific Reports

|October 23, 2015

Summary

This summary is machine-generated.

A new smartphone-based test accurately detects sickle cell disease using red blood cell density differences. This rapid, low-cost platform offers a vital diagnostic tool for regions with high sickle cell disease prevalence.

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A Precision Medicine Tool for Measurement and Monitoring of Hemoglobin S in Sickle Cell Disease Patients Receiving Transfusion Therapy

A Precision Medicine Tool for Measurement and Monitoring of Hemoglobin S in Sickle Cell Disease Patients Receiving Transfusion Therapy

Area of Science:

Biomedical Engineering
Hematology
Point-of-Care Diagnostics

Background:

Sickle cell disease (SCD) is prevalent in Central and West Africa, causing severe health issues like silent strokes.
Current diagnostic methods are not widely accessible in affected regions.
A simple, rapid, and accurate diagnostic tool is urgently needed for SCD screening.

Purpose of the Study:

To develop and validate a novel, label-free diagnostic platform for sickle cell disease.
To enable rapid and accurate SCD diagnosis using a portable, smartphone-based device.

Main Methods:

A 3D-printed smartphone attachment was designed, incorporating an LED, lens, and magnets.
Red blood cells were levitated in a paramagnetic medium under deoxygenated conditions using magnetic forces.
Differences in red blood cell levitation patterns between sickle and normal cells were analyzed.

Main Results:

The platform demonstrated high sensitivity and specificity in distinguishing sickle red blood cells from normal cells.
The method relies on the increased density of deoxygenated sickle red blood cells.
Levitation patterns varied based on the degree of red blood cell confinement.

Conclusions:

This smartphone-based magnetic levitation assay provides a promising, low-cost method for SCD diagnosis.
The technology has the potential to significantly improve SCD screening in resource-limited settings.
Further implementation could lead to earlier diagnosis and improved patient outcomes for sickle cell disease.