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The CELL-DYN Emerald 22 AL System is a quantitative multi-parameter automated hematology analyzer designed for in-vitro diagnostic use in clinical laboratories for enumeration of the following parameters: WBC, LYM%, LYM #, MON %, MON #, NEU%, NEU #, EOS%, EOS #, BAS%, BAS #, RBC, HCT, MCV, RDW, HGB, MCH, MCHC, PLT, MPV in K2EDTA anti-coagulated whole blood.

The CELL-DYN Emerald 22 AL is indicated for use to identify patients with hematologic parameters within and outside of established reference ranges.

The CELL-DYN Emerald 22 AL analyzer is a bench top analyzer, consisting of the main analyzer, autoloader module, and touch screen display. Sample analysis may be performed in open or closed mode. The CELL-DYN Emerald 22 AL is equipped with a sample loader that provides continuous automated closed mode sampling for up to 50 closed tube samples, one at a time. The analyzer is also equipped with a tube holder assembly that allows the use of open tube sampling.

The CELL-DYN Emerald 22 AL is designed to automatically perform the following:

• a) Aspirate and dilute whole blood
• b) Count, size and classify cells present in a whole blood specimen
• c) Measure the hemoglobin concentration of a whole blood specimen
• d) Analyze the raw data that is collected
• e) Output results to the display, printer and laboratory information system

Three types of measurements are used to count, size and classify blood cells and to measure hemoglobin. The three types of measurements are:

• a) Electrical Impedance Counting
• b) Absorption Spectrophotometry
• c) Optical Flow Cytometry

The electrical impedance counting is used for WBC, RBC and PLT measurements. The absorption spectrophotometry is used for HGB measurement. The optical flow cytometry is used for WBC differential. HCT is derived from the volume of the RBCs that are counted during the measurement cycle.

The provided text discusses the CELL-DYN Emerald 22 AL System, an automated hematology analyzer, and its substantial equivalence to the predicate device, CELL-DYN Emerald 22 (K110381).

Here's an analysis of the acceptance criteria and study that proves the device meets them, based on the provided information:

1. A table of acceptance criteria and the reported device performance

The document states that a variety of non-clinical design verification analyses were performed to demonstrate substantial equivalence and that "all predetermined acceptance criteria were met." However, the specific numerical acceptance criteria for each performance metric (e.g., specific ranges for background noise, percentages for carryover, R-squared values or other correlation coefficients for linearity, CV% for imprecision) are not explicitly detailed in a table format within the provided text.

The reported device performance is broadly stated as: "Results of this testing demonstrated substantial equivalence between the CELL-DYN Emerald 22 AL System and the CELL-DYN Emerald 22 System with respect to analytical performance and that the addition of the sample loader module does not impact functional performance."

The types of studies performed, for which acceptance criteria were met, include:

• Background
• Carryover
• Linearity
• Short-Term Imprecision
• Long-Term Imprecision
• Method Comparison
• Blood Tube Type Study
• Mode-to-Mode Equivalency
• Data Invalidation Clogging Rate

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not explicitly state the sample sizes used for each of the non-clinical design verification analyses. It also does not explicitly state the country of origin of the data or whether the studies were retrospective or prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This device is an automated hematology analyzer, and the studies described are analytical performance studies. These types of studies typically involve comparisons against reference methods or established standards rather than expert-established ground truth in the way a diagnostic imaging AI might. Therefore, the concept of "experts used to establish ground truth" with specific qualifications like radiologists is not applicable in this context. The ground truth for analytical performance studies would be based on the accuracy of the reference method used for comparison.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Given that the studies are analytical performance comparisons against reference methods (e.g., comparing measurements from the new device against those from the predicate device or a gold standard method), an adjudication method (like 2+1, 3+1) is not applicable. Adjudication is typically used in clinical studies where expert consensus is needed to resolve discrepancies in interpretation, which is not the nature of these analytical studies.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

This document describes a hematology analyzer, not an AI-assisted diagnostic imaging device for human readers. Therefore, an MRMC comparative effectiveness study involving human readers with/without AI assistance and associated effect sizes is not applicable.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Yes, the studies described are essentially "standalone" in the context of device performance. The non-clinical design verification analyses (Background, Carryover, Linearity, Imprecision, Method Comparison, etc.) evaluate the automated analyzer's performance directly, independent of human interaction for result generation. The device itself is an automated system providing quantitative measurements.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

For the analytical performance studies, the ground truth for parameters like cell counts (WBC, RBC, PLT), hemoglobin, and differential percentages would likely be established by:

• Reference methods: Highly accurate and precise laboratory methods, often considered "gold standards" for specific hematology parameters (e.g., manual cell counts, specialized spectrophotometry for HGB).
• Predicate Device Comparison: A significant part of the evaluation is demonstrating substantial equivalence to the predicate device (CELL-DYN Emerald 22), implying the predicate's performance serves as a comparative "ground truth" standard.

8. The sample size for the training set

The document describes non-clinical validation studies for an automated hematology analyzer, not an AI model that requires a "training set" in the machine learning sense. The device is based on established technologies (Electrical Impedance Counting, Absorption Spectrophotometry, Optical Flow Cytometry). Therefore, the concept of a "training set" for an algorithm is not directly applicable as it would be for a deep learning model.

9. How the ground truth for the training set was established

As explained above, the device's operational principles are physical and chemical measurements rather than a machine learning algorithm requiring a "training set" with ground truth established through annotation or clinical outcomes. Therefore, this question is not applicable.

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