Microfluidic Adhesion Measurement Using Digital Holography
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Solution Overview
Problem
Current methods for monitoring the severity of sickle cell disease lack objective measures, relying heavily on subjective patient-reported symptoms, which poses challenges in early diagnosis and effective treatment, especially in resource-limited settings.
Innovation Solution
A diagnostic system utilizing microfluidic channels coated with Laminin or p-selectin to selectively adhere diseased red blood cells, combined with an inline digital holography technique and AI/ML analysis to quantify adhesion and determine disease severity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If microfluidic channels with specific coatings are used to selectively adhere diseased RBCs, then measurement precision of adhesion is improved, but device complexity increases
Solution Approach 1:
The microfluidic channel interior surface is coated with specific proteins (laminin, p-selectin, or fibronectin) to create localized adhesion sites that selectively bind diseased RBCs. This local modification enables precise measurement of adhesion properties without requiring complex overall device architecture.
Solution Approach 2:
Protein coatings serve as intermediaries between the microfluidic channel surface and diseased RBCs, facilitating selective adhesion. The coatings act as mediators that enable the measurement of adhesion forces without direct contact between the channel surface and cells, simplifying the measurement process.
2Measurement precision
If digital holography imaging is used to visualize and count adhered RBCs, then measurement precision is improved, but use of energy increases
Solution Approach 1:
Digital holography replaces traditional mechanical counting methods with optical field-based imaging and computational analysis. The system uses light fields to capture three-dimensional information about adhered RBCs, enabling precise counting without mechanical manipulation or staining procedures.
Solution Approach 2:
The system changes the imaging parameters by using digital holography instead of conventional microscopy. This allows for label-free visualization and counting of RBCs based on their intrinsic optical properties, reducing the need for additional energy-consuming staining or fluorescent labeling procedures.
3Measurement precision
If AI/ML algorithms are applied to analyze holography images, then measurement precision of disease severity assessment is improved, but device complexity increases
Solution Approach 1:
The system creates digital copies of the holography images and uses AI/ML algorithms to analyze these copies. By working with digital representations rather than physical samples, the system enables complex pattern recognition and disease severity assessment without requiring additional physical processing steps.
Solution Approach 2:
AI/ML algorithms serve as intermediaries between the raw holography images and the final disease severity assessment. The algorithms process and interpret the imaging data, translating visual information into quantitative disease severity scores without requiring direct human analysis.
4Ease of operation
If unstained, untagged, and unmodified RBCs are used, then ease of operation is improved, but measurement precision may worsen
Solution Approach 1:
The system uses the intrinsic optical properties of unstained, untagged, and unmodified RBCs for visualization and analysis. The cells themselves provide the necessary contrast and structural information for adhesion detection, eliminating the need for external staining or tagging procedures while maintaining measurement capability.
Solution Approach 2:
The system exploits natural optical contrast and refractive index differences of unstained RBCs against the background to achieve visualization. By utilizing the inherent optical properties of the cells rather than external dyes, the system maintains ease of operation while achieving sufficient measurement precision through advanced image processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system provides an objective and quantitative assessment of sickle cell disease severity, enabling more effective monitoring and treatment, while being cost-effective and not requiring labeling of cells.
Implementation Method 1
one or more microfluidic channels configured to selectively adhere a plurality of diseased red blood cells (RBCs) of a blood sample on an interior surface of the one or more microfluidic channels
Implementation Method 2
at least one imager configured to generate one or more digital holography images or videos of the plurality of diseased RBCs adhered to the interior surface of the one or more microfluidic channels
Data Source
AI summary
A system and a method for measuring adhesion of blood cells in microfluidic channels are disclosed. The system includes a device having one or more microfluidic channels configured to adhere a plurality of diseased red blood cells (RBCs) of a blood sample on an interior surface of the one or more microfluidic channels. Further, the system includes at least one imager configured to generate one or more digital holography images or videos of the plurality of diseased RBCs adhered to the interior surface of the one or more microfluidic channels. Further, at least one processor is operationally coupled to the at least one imager and configured to receive the one or more digital holography images or videos and analyze the generated one or more digital holography images or videos to quantify adhesion of the plurality of diseased RBCs to the interior surface of the one or more microfluidic channels.