Cap‐oPMN: Oral Inflammatory Load Quantification Using Capillary Microfluidics and Automated Image Processing

ABSTRACT Quantifying oral polymorphonuclear neutrophils (oPMNs) is a clinically validated approach for assessing periodontal inflammation. However, current methods, such as manual hemocytometry and flow cytometry, are time‐consuming (>3 h), require invasive sampling, and depend on staining and complex instrumentation, making them unsuitable for point‐of‐care applications. Here, we present Cap‐oPMN, a self‐powered capillary microfluidic platform that enables rapid (<30 s), label‐free quantification of oPMNs from an oral rinse, a non‐invasive and easily collected biofluid. The multilayer device integrates laser‐cut hydrophilic channels, stop valves, porous membrane filters, and flow stabilizers to remove debris and non‐cellular components while passively guiding neutrophils into an imaging zone via capillary action, without external pumps or power sources. Captured oPMNs are visualized by brightfield microscopy and automatically quantified using a YOLOv4‐based deep learning model, achieving 95% detection precision. Agreement with manual hemocytometry was evaluated using Deming regression and Bland–Altman analysis, demonstrating minimal bias and excellent concordance (CCC ≈ 0.999). In a clinical study of 21 subjects across five periodontal disease stages, Cap‐oPMN measurements showed significant differences between diagnostic groups (Welch’s ANOVA with Games–Howell post‐hoc testing) and large effect sizes between progressive disease stages, supporting reliable POC assessment of oral inflammatory burden and periodontal disease severity.

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Publication Details

Journal
Advanced Materials Technologies
Published
2026-03-26
DOI
https://doi.org/10.1002/admt.202502599
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
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article

Cap‐oPMN: Oral Inflammatory Load Quantification Using Capillary Microfluidics and Automated Image Processing

Ebrahim Ghafar‐Zadeh, Yasaman Tahernezhad, Mahdi Amrollahi Biouki, Chunxiang Sun et al.
Advanced Materials Technologies
Biosensors and Analytical Detection
article

Cap‐oPMN: Oral Inflammatory Load Quantification Using Capillary Microfluidics and Automated Image Processing

Ebrahim Ghafar‐Zadeh, Yasaman Tahernezhad, Mahdi Amrollahi Biouki, Chunxiang Sun, Mohsen Hassani, S. M. Mahdi H. Daneshvar, Azam Zare, Michael Glogauer, Fatemeh Soheili, Amir Sanati‐Nezhad
article en

Abstract

ABSTRACT Quantifying oral polymorphonuclear neutrophils (oPMNs) is a clinically validated approach for assessing periodontal inflammation. However, current methods, such as manual hemocytometry and flow cytometry, are time‐consuming (>3 h), require invasive sampling, and depend on staining and complex instrumentation, making them unsuitable for point‐of‐care applications. Here, we present Cap‐oPMN, a self‐powered capillary microfluidic platform that enables rapid (<30 s), label‐free quantification of oPMNs from an oral rinse, a non‐invasive and easily collected biofluid. The multilayer device integrates laser‐cut hydrophilic channels, stop valves, porous membrane filters, and flow stabilizers to remove debris and non‐cellular components while passively guiding neutrophils into an imaging zone via capillary action, without external pumps or power sources. Captured oPMNs are visualized by brightfield microscopy and automatically quantified using a YOLOv4‐based deep learning model, achieving 95% detection precision. Agreement with manual hemocytometry was evaluated using Deming regression and Bland–Altman analysis, demonstrating minimal bias and excellent concordance (CCC ≈ 0.999). In a clinical study of 21 subjects across five periodontal disease stages, Cap‐oPMN measurements showed significant differences between diagnostic groups (Welch’s ANOVA with Games–Howell post‐hoc testing) and large effect sizes between progressive disease stages, supporting reliable POC assessment of oral inflammatory burden and periodontal disease severity.

Advanced Materials Technologies
University of Calgary (CA), University of Toronto (CA), York University (CA)
Openalex Percentile: Top 8%
Biosensors and Analytical Detection
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Cap‐oPMN: Oral Inflammatory Load Quantification Using Capillary Microfluidics and Automated Image Processing — Ebrahim Ghafar‐Zadeh, Yasaman Tahernezhad, et al. · Advanced Materials Technologies (2026) | TGRS Research Map | TGRS