Label-free automated neutropenia detection and grading using deep-ultraviolet microscopy

Area of Science:

• Biomedical Engineering
• Hematology
• Optical Microscopy

Background:

• Neutropenia, characterized by low neutrophil counts, increases infection risk, especially in cancer patients.
• Current diagnostic methods like complete blood count (CBC) are costly, complex, and time-consuming.
• Accessible and rapid monitoring of neutrophil levels is crucial for managing cancer patient care.

Purpose of the Study:

• To develop a simple, low-cost, and rapid method for detecting and grading neutropenia.
• To utilize label-free multi-spectral deep-UV microscopy for automated blood cell analysis.
• To provide a point-of-care solution for monitoring neutrophil counts in at-risk patients.

Main Methods:

• Employed label-free multi-spectral deep-UV microscopy for imaging unstained blood cells.
• Developed an automated framework for cell segmentation and classification.
• Validated the system's ability to differentiate neutropenia severity from healthy samples.

Main Results:

• The developed technique accurately detects and grades neutropenia using live, unstained blood cells.
• Automated analysis successfully differentiates moderate and severe neutropenia from healthy controls.
• The method provides critical hematological information within minutes.

Conclusions:

• This novel microscopy technique offers a robust and efficient alternative for neutropenia assessment.
• The findings support the development of a low-cost, point-of-care device for neutrophil monitoring.
• This technology has the potential to significantly improve patient outcomes and save lives.