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Clinical immunophenotyping using the CyAn DXD flow cytometer, a lyse wash sample preparation method, for identification and enumeration of CD3, CD4 and CD8 lymphocyte subsets using TC-660. For In-Vitro Diagnostic Use

The Dako CyAn™ DXD device is a bench-top flow cytometer system relying on multiple (up to three) laser stimulation of fluorescence tagged lymphocytes. It is used with the Dako MultiMix, a triple color reagent; one each to CD3, CD4 and CD8, conjugated to fluorochromes APC(allophycocyanin), r-phycoerythrin, and fluorescein isothiocynate, which are balanced to identify the dual positive T-cell populations (CD3+CD4+ and CD3+CD8+) in peripheral blood lymphocytes. The instrument requires daily set-up with Dako FluoroSpheres consisting of a set of 5 bead populations having different fluorescent intensities and one nonfluorescent bead population. The combination of fluorochromes enables excitation by light of any wavelength from 365-650 nm. The CyAn DXD utilizes anti-human CD3 conjugated with FITC, RPE and APC to perform autocompensation.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Dako CyAn™ DXD device:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state specific numerical acceptance criteria for performance metrics like precision, accuracy, specificity, or linearity. Instead, it makes a general statement about the study's findings:

Important Note: The document focuses on demonstrating substantial equivalence to predicate devices rather than meeting specific quantitative performance targets. This is a common approach in 510(k) submissions.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective nature of the data). It only mentions "Results of all testing conducted."

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

The document does not mention the use of experts or how ground truth was established for the test set. For a flow cytometer, the "ground truth" would typically be derived from the instrument's own measurements or comparison to a gold standard method.

4. Adjudication Method for the Test Set

Since the document does not mention the use of experts to establish a ground truth or subjective assessments, there is no adjudication method described.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. The document does not indicate that a multi-reader multi-case (MRMC) comparative effectiveness study was done. The device is an automated differential cell counter, which typically doesn't involve human readers in the same way an imaging AI would.

6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study

Yes, implicitly. The study evaluates the "Performance characteristics evaluated in support of the CVAn DXD and its associated components." This implies the performance of the device itself, including its automated algorithms for identification and enumeration of lymphocyte subsets, in a standalone manner. The device is a "bench-top flow cytometer system" with "Summit™ software" and "automated quality control algorithms."

7. Type of Ground Truth Used

The document does not explicitly state the type of ground truth used. However, given the nature of a flow cytometer that measures cell populations, the "ground truth" would likely be:

• Reference standard measurements: Comparison to established flow cytometry methods or other validated laboratory techniques for cell counting and phenotyping.
• Intra-device consistency: Demonstrating that the device consistently identifies and enumerates cell populations.

The claim of "substantial degree of equivalency to the predicate devices" suggests that the predicate devices themselves served as a de facto "ground truth" or a benchmark for comparison.

8. Sample Size for the Training Set

The document does not mention a training set sample size. This device is a flow cytometer for direct measurement and analysis, not an AI/machine learning model in the contemporary sense that typically requires a separate training set for model development. The software (Summit™) and algorithms are likely part of the device's inherent design and calibration, rather than being "trained" on a specific dataset in the modern ML context.

9. How the Ground Truth for the Training Set Was Established

Since no training set is mentioned in the context of an AI/ML model, the document does not describe how ground truth for a training set was established.

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