Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Label-free deep-UV microscopy detection and grading of neutropenia using a passive microfluidic device

Abstract

Neutropenia is a condition comprising an abnormally low number of neutrophils, a type of white blood cell, which puts patients at an increased risk of severe infections. Neutropenia is especially common among cancer patients and can disrupt their treatment or even be life-threatening in severe cases. Therefore, routine monitoring of neutrophil counts is crucial. However, the current standard of care to assess neutropenia, the complete blood count (CBC), is resource-intensive, time-consuming, and expensive, thereby limiting easy or timely access to critical hematological information such as neutrophil counts. Here, we present a simple technique for fast, label-free neutropenia detection and grading via deep-ultraviolet (deep-UV) microscopy of blood cells in polydimethylsiloxane (PDMS)-based passive microfluidic devices. The devices can potentially be manufactured in large quantities at a low cost, requiring only 1 μL of whole blood for operation. We show that the absolute neutrophil counts (ANC) obtained from our proposed microfluidic device-enabled deep-UV microscopy system are highly correlated with those from CBCs using commercial hematology analyzers in patients with moderate and severe neutropenia, as well as healthy donors. This work lays the foundation for the development of a compact, easy-to-use UV microscope system to track neutrophil counts that is suitable for low-resource, at-home, or point-of-care settings.

© 2022 Optica Publishing Group

Full Article  |  PDF Article
More Like This
Label-free automated neutropenia detection and grading using deep-ultraviolet microscopy

Ashkan Ojaghi, Paloma Casteleiro Costa, Christina Caruso, Wilbur A. Lam, and Francisco E. Robles
Biomed. Opt. Express 12(10) 6115-6128 (2021)

Compact and low-cost deep-ultraviolet microscope system for label-free molecular imaging and point-of-care hematological analysis

Viswanath Gorti, Nischita Kaza, Evelyn Kendall Williams, Wilbur A. Lam, and Francisco E. Robles
Biomed. Opt. Express 14(3) 1245-1255 (2023)

Deep learning-assisted smartphone-based quantitative microscopy for label-free peripheral blood smear analysis

Bingxin Huang, Lei Kang, Victor T. C. Tsang, Claudia T. K. Lo, and Terence T. W. Wong
Biomed. Opt. Express 15(4) 2636-2651 (2024)

Data availability

Data underlying the results presented in this paper are not publicly available at this time, but may be obtained from the authors upon reasonable request.

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (2)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.