(94 days)
The Cell-Dyn® 3500R System is a multi-parameter, automated hematology analyzer designed for in vitro diagnostic use in clinical laboratories.
The Cell-Dyn 3500R System is a table-top analyzer consisting of the main analyzer, data station, and printer. The instrument has two sampling modes: Open Sample Aspiration Mode and Closed Sample Aspiration Mode. The Cell-Dyn 3500R System is available with a manual Closed Sampler (3500R, CS) or an automated Sample Loader (3500R, SL). The instrument has the capability of processing a whole-blood specimen to provide a CBC, including a 5-part WBC differential for a total of 22 parameters. The 22 reportable parameters are as follows:
White blood cells (WBC), red blood cells (RBC), platelets (PLT), percent of neutrophils (%N), number of neutrophils (NEU), percent of lymphocytes (%L), number of lymphocytes (LYM), percent of monocytes (%M), number of monocytes (MONO), percent of eosinophils (%E), number of eosinophils (EOS), percent of basophils (%B), number of basophils (BASO), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW) mean platelet volume (MPV).
In addition, the Reticulocyte software allows the instrument to process stained, diluted specimens in the Open Mode to provide a Reticulocyte percent (RETIC %), and number of Reticulocytes Absolute Number (Retic Abs). A Retic Scatter Index is provided for Laboratory Use Only and is not reportable.
The provided text details the Cell-Dyn® 3500R System, a hematology analyzer, and its reticulocyte enumeration capabilities. The document focuses on establishing substantial equivalence to the Becton Dickinson FACScan™ Flow Cytometer RetiCOUNT™ Reticulocyte Enumeration Kit, rather than presenting a study to prove the device meets specific acceptance criteria with defined metrics.
Therefore, many of the requested elements for a study proving device performance against acceptance criteria cannot be directly extracted from the provided text. The document primarily describes the device's intended use, operation, and a comparison with a predicate device.
Here's an attempt to address your request based on the available information:
1. Table of Acceptance Criteria and Reported Device Performance
The document states that the "accuracy, precision and linearity data shows performance to manufacturer's specifications." However, the specific manufacturer's specifications (i.e., the acceptance criteria) and the quantitative reported performance values are not provided in the text. The document mainly claims substantial equivalence based on the data supporting these aspects.
| Acceptance Criteria (e.g., Accuracy, Precision, Linearity Targets) | Reported Device Performance (Quantified Results) |
|---|---|
| Not explicitly stated in the provided text. The text only refers to "manufacturer's specifications" without detailing them. | Not explicitly stated in the provided text. The text only claims that performance "shows performance to manufacturer's specifications." |
2. Sample Size Used for the Test Set and Data Provenance
This information is not provided in the document. The text mentions "equivalence data" for accuracy, precision, linearity, and carryover, but does not specify the sample size of the test set used for these evaluations or the provenance (e.g., country of origin, retrospective/prospective).
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
This information is not provided. Hematology analyzers for cell counts typically rely on a reference method or a gold standard instrument for comparison, rather than human experts establishing "ground truth" in the same way as, for example, image interpretation. The comparison here is against the Becton Dickinson FACScan for reticulocyte enumeration.
4. Adjudication Method for the Test Set
This information is not provided. Given the nature of a hematology analyzer, an adjudication method like "2+1" or "3+1" (common in image-based diagnostic studies) is generally not applicable. Performance is usually assessed by direct comparison of numerical outputs to a reference method.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, a multi-reader multi-case (MRMC) comparative effectiveness study was not described. Such studies are typically for evaluating human reader performance with and without AI assistance in tasks like interpreting medical images. This document describes a standalone hematology analyzer.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
Yes, the evaluation described is for a standalone device. The Cell-Dyn 3500R System is an automated hematology analyzer designed to process samples and provide results without direct human interpretation of individual cell events in the same way an AI algorithm might augment a human. Its performance is assessed independently.
7. The Type of Ground Truth Used
The "ground truth" used for comparison appears to be the results obtained from the Becton Dickinson FACScan™ Flow Cytometer RetiCOUNT™ Reticulocyte Enumeration Kit, which is the predicate device. The document explicitly states: "Substantial equivalence has been demonstrated between the Cell-Dyn 3500R System and the Becton Dickinson FACScan™ Flow Cytometer RetiCOUNT™ Reticulocyte Enumeration Software..." and "The data compiled to support the claim that the Cell-Dyn 3500R System is substantially equivalent to the Becton Dickinson FACScan includes accuracy, precision, linearity, and carryover." This implies that the FACScan's results served as the reference for evaluating the Cell-Dyn 3500R.
8. The Sample Size for the Training Set
This information is not provided. The Cell-Dyn 3500R System is a hardware-based analyzer with embedded software for signal processing and parameter calculation based on established biological principles and optical scatter measurements. It is not an AI/ML system that undergoes "training" in the conventional sense with a distinct training set. Its development would involve calibration and validation processes, but not a "training set" like a deep learning model.
9. How the Ground Truth for the Training Set Was Established
As noted in point 8, the concept of a "training set" and "ground truth for a training set" in the context of an AI/ML model does not directly apply to the description of the Cell-Dyn 3500R System in this document. Its operational principles are based on light scatter measurements and established algorithms, not adaptive learning from a labeled training dataset.
§ 864.5220 Automated differential cell counter.
(a)
Identification. An automated differential cell counter is a device used to identify one or more of the formed elements of the blood. The device may also have the capability to flag, count, or classify immature or abnormal hematopoietic cells of the blood, bone marrow, or other body fluids. These devices may combine an electronic particle counting method, optical method, or a flow cytometric method utilizing monoclonal CD (cluster designation) markers. The device includes accessory CD markers.(b)
Classification. Class II (special controls). The special control for this device is the FDA document entitled “Class II Special Controls Guidance Document: Premarket Notifications for Automated Differential Cell Counters for Immature or Abnormal Blood Cells; Final Guidance for Industry and FDA.”