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The CELL-DYN® 1200 System is an automated multi-parameter hematology analyzer intended for in-vitro diagnostic use in the clinical hematology laboratory, medical clinic and/or Physicians Office Laboratory (POL) to classify the following formed elements of EDTA anti-coagulated blood:
White Blood Cell Parameters:
WBC - White Blood Cell or leukocyte count
GRAN -- Granulocyte absolute count
%GRAN -- Granulocyte percent
LYM - Lymphocyte absolute count
%L - Lymphocyte percent
MID – Mid-range absolute count
%M - Mid-range percent
Platelet Parameters:
PLT - Platelet Count
MPV - Mean Platelet Volume
PDW* - Platelet Distribution Width
CT* - Plateletcrit
Red Blood Cell Parameters:
RBC - Red Blood Cell or erythrocyte count
HCT - Hematocrit
MCV - Mean Corpuscular Volume
RDW - Red Cell Distribution Width
Hemoglobin Parameters:
HGB - Hemoglobin Concentration
MCH -- Mean Cell Hemoglobin
MCHC -- Mean Cell Hemoglobin Concentration
*Clinical significance has not been established for these parameters. Therefore, they are not reportable in the US.

The CELL-DYN 1200 System counts, sizes, and classifies blood cells by impedance and focused flow methods, which incorporates electrical resistance and electronic sizing principles. Each specimen is aspirated, diluted and mixed before the hematology parameters are measured. The CELL-DYN 1200 System utilizes a spectrophotometric method for hemoglobin concentration, which is measured optically by absorbance at 540nm +20nm. The system incorporates the coincidence loss principle for each cell that is counted.

The CELL-DYN® 1200 System is an automated multi-parameter hematology analyzer used for in-vitro diagnostic purposes in various clinical settings. The provided text outlines its intended use, principles of operation, and equivalency data to support its substantial equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state numerical acceptance criteria for the CELL-DYN® 1200 System. Instead, it indicates that "Equivalency Data" was compiled to support the claim of substantial equivalence when used in a Physician's Office Laboratory (POL) or Clinical Laboratory. This equivalency was demonstrated through studies on:

• Background
• Carryover
• Accuracy
• Precision
• Linearity
• Quality Control

Furthermore, "Correlation equivalence is demonstrated between the CELL-DYN 1200 System and the CELL-DYN 1700 System for the following measured parameters: White Blood Count (WBC), WBC differential sub populations, Red Blood Count (RBC), Hemoglobin concentration (HGB), Mean Corpuscular Volume (MCV), Platelet Count (PLT), Mean Platelet Volume (MPV), and Red Cell Distribution Width (RDW)."

Therefore, the acceptance criteria implicitly appear to be performance characteristics (accuracy, precision, linearity, etc.) that are comparable to the CELL-DYN 1700 predicate device, and the reported device performance is that it met these equivalence standards.

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

The provided text does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). It only mentions that "data compiled to support the claim" was gathered.

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

The provided text does not specify the number of experts used or their qualifications for establishing ground truth. As this is a hematology analyzer, the ground truth would typically be established by established laboratory methods and potentially expert review of blood smears, but this is not detailed in the given summary.

4. Adjudication Method for the Test Set

The provided text does not describe an adjudication method for the test set. Given the nature of a hematology analyzer, ground truth is typically established by reference methods or expert consensus on manual differential counts, rather than an adjudication process between multiple readers in the way an imaging study might.

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

The provided text does not mention a multi-reader, multi-case (MRMC) comparative effectiveness study. This type of study is more common for diagnostic imaging AI systems where human readers interpret images. For a hematology analyzer, the comparison is typically between the device's measurements and established reference methods or a predicate device.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The provided text describes a standalone performance evaluation implicitly. The "Equivalency Data" and "Correlation equivalence" studies evaluate the CELL-DYN 1200 System's performance (WBC, RBC, HGB, etc.) against a predicate device (CELL-DYN 1700) and established performance parameters (accuracy, precision, linearity). This is a direct measure of the device's output without human intervention during the measurement process.

7. Type of Ground Truth Used

The ground truth used for this device would likely be established through:

• Reference methods: Established laboratory techniques for measuring blood parameters (e.g., manual differential counts, spectrophotometry for hemoglobin, flow cytometry).
• Predicate device (CELL-DYN 1700 System): The performance of the predicate device serves as a benchmark for "correlation equivalence."

The text explicitly states "Correlation equivalence is demonstrated between the CELL-DYN 1200 System and the CELL-DYN 1700 System," indicating that the predicate device's performance was a key component of establishing the "truth" for comparison.

8. Sample Size for the Training Set

The provided text does not specify the sample size for a training set. Hematology analyzers of this type are typically "trained" during their development and calibration phase using a wide range of blood samples with known characteristics. However, the 510(k) summary focuses on the equivalency testing rather than the initial development and training.

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

The provided text does not describe how the ground truth for any training set was established. As with the test set, any "training" (calibration, algorithm development) would have relied on highly characterized samples with ground truth established through established reference laboratory methods.

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