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Comparison of an image cytometry somatic cell count analyzer to a flow cytometry analyzer
A Hubner1, N Taechachokevivat1, J M Grantz1
1Department of Veterinary Clinical Sciences, Purdue University, West Lafayette, IN 47907.
JDS Communications
|December 4, 2023
Summary
A new image cytometry somatic cell counter shows good performance for on-farm use, offering high concordance and acceptable sensitivity/specificity for detecting mammary infections. Precision is best when using the full image capacity.
Area of Science:
- Veterinary Diagnostics
- Dairy Science
- Biomedical Engineering
Background:
- Somatic cell count (SCC) is a key indicator of bovine mammary gland health.
- Accurate and accessible SCC testing is crucial for dairy herd management.
- Traditional flow cytometry methods are laboratory-based.
Purpose of the Study:
- To evaluate the performance of a benchtop image cytometer (LactiCyte HD) against a standard flow cytometer.
- To assess the accuracy, precision, and diagnostic capabilities of the image cytometer for somatic cell counting in milk.
- To determine the optimal image resolution for the image cytometer.
Main Methods:
- Milk samples from routine dairy herd improvement (DHI) testing were analyzed.
- Samples were split for analysis by flow cytometry (regional DHI lab) and image cytometry (16 and 8 images per slide).
- Concordance correlation coefficients, bias, sensitivity, specificity, and coefficients of variation (CV) were calculated.
Main Results:
- The image cytometer demonstrated high concordance (CCC > 0.95) with flow cytometry across both imaging resolutions.
- Sensitivity and specificity for detecting subclinical infection (≥200,000 cells/mL) were high, particularly at 16 images (92.0% and 91.7%).
- Method precision (CV) was generally better with 16 images compared to 8 images, especially at lower cell counts.
Conclusions:
- The LactiCyte HD image cytometer is a suitable analyzer for on-farm somatic cell counting.
- It can be effectively used for screening cows for potential mammary infections.
- Optimal precision and diagnostic accuracy are achieved when utilizing the full image analysis capacity (16 images).

