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The Cytomics FC 500 MPL is a system for the qualitative and quantitative measurement of biological and physical properties of cells and other particles. These properties are measured when the cells pass through one or two laser beams in single-file.

The tetraCXP SYSTEM for Cytomics FC 500 flow cytometry systems is an automated analysis method for simultaneous identification and enumeration of lymphocyte subpopulations (CD3+, CD19+ and CD56+) combining fourcolor fluorescent monoclonal antibody reagents, quality control reagents, optional absolute count reagent and CXP software. The systems with CYTO-STAT tetraCHROME CD45-FITC/CD4-PD/CD8-ECD/CD3-PC5 Monoclonal antibody reagent is intended "For In Vitro Diagnostic Use", allowing the identification and enumeration of Total CD3+ (T cells), Total CD4+, Total CD8+, Dual CD3+/CD4+, Dual CD3+/CD8+ lymphocyte percentages and absolute counts as well as the CD4/CD8 ratio in whole blood flow cytometry. The systems with CD45-FITC/CD56-PC/CD3-PC5, the total lymphocyte percentage can be obtained. CD45-FITC/CD56-PE/CD19-ECD/CD3-PC5 monoclonal antibody reagent is intended "For In Vitro Diagnostic Use", allowing the identification and enumeration of total CD19+ (B cells) and CD3-/CD56+ (NK cells) lymphocyte percentages and absolute counts in whole blood flow cytometry. The total lymphocyte percentage can obtained as well.

The FC 500 Flow Cytometer has two cleared configurations: MPL (Multi Plate Loader) and MCL (Multi Carousel Loader). Both devices use flow cytometric principles to determine qualitative and quantitative measurements of biological and physical properties of cells and other particles. These properties are measured when the cells pass through one or two laser beams in single file. The instrument can simultaneously measure forward scatter, and five fluorescent dyes using one or two lasers at 488 nm and either 635 nm (solid-state laser) or 633 nm (HeNe laser). Therefore, the instrument can perform correlated multi-parameter analyses of individual cells. The instrument uses hydrodynamic focusing in the flow cell to ensure cells move through the laser beam one at a time. Scattered laser light and fluorescent light are collected, separated and measured by seven sensors. The results of sample analysis appear on the workstation screen as graphs in which the user defines the parameters on the plot axes. To analyze the data, regions and gates are defined by the user to select the cells of interest, and then statistics are generated.

This modification to the FC 500 Flow Cytometers is a software update containing additional risk control measures to mitigate potential failure modes associated with reported signal loss and/or signal drift.

This document describes a software update for the Beckman Coulter Cytomics FC 500 Series Flow Cytometers (MPL and MCL) intended to mitigate signal loss and drift issues. The update introduces a Software Detection Tool (SDT) and updated user instructions for visual review of time plots.

Here's a breakdown of the acceptance criteria and study information:

1. Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of predetermined acceptance criteria with corresponding performance metrics like sensitivity, specificity, or accuracy. Instead, the "Summary of Performance Testing" section describes the studies conducted and their outcomes, which demonstrate the device's ability to detect signal loss/drift and the effectiveness of the added controls.

The reported device performance is qualitative, focusing on whether the SDT and visual review methods successfully identified signal loss failures.

2. Sample Size and Data Provenance

• Pre-acquisition, Post-acquisition, Real World Data: The document does not specify exact sample sizes (e.g., number of runs, number of files) for these studies. It mentions "a sample run," "2 test cases utilizing the SDT," "additional set of files," and "customer files sourced from the field and prospective testing performed with field returned boards."
• Reader Study: "10 files where 7 of these files contained signal loss undetectable by the SDT."
• Data Provenance:
  • Post-acquisition: "a combination of retrospective data imprinted with failure patterns characterized from field data and prospective sample runs processed through a modified instrument."
  • Real World Data: "customer files sourced from the field and prospective testing performed with field returned boards."
  • Reader Study: Not explicitly stated, but implies existing data files used for evaluation.

3. Number of Experts and Qualifications for Ground Truth

• Real World Data: Ground truth for real-world failures was "confirmed by visual review of the time plots." The number and qualifications of experts performing this visual review are not specified.
• Reader Study: "multiple readers" were used. Their specific qualifications (e.g., medical technologists, scientists) are not detailed, but they followed "user instructions in the IFU for visual review of time plots," implying they were trained users of the device.

4. Adjudication Method

The document does not explicitly describe an adjudication method like 2+1 or 3+1. For the "Real World Data" study, failures were "confirmed by visual review," suggesting a consensus or single expert review. In the "Reader Study," "multiple readers" were involved, but how discrepancies were resolved or if a consensus was formed is not stated.

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

There is no mention of an MRMC comparative effectiveness study that demonstrates how much human readers improve with AI (SDT) assistance versus without it. The "Reader Study" confirms that visual review itself identifies signal loss, and the overall conclusion states that "The use of the SDT, in addition to visual review of time plots provides a comprehensive solution." This suggests the SDT acts as an additional control or an aid to human review, rather than a system where humans improve with the SDT.

6. Standalone Performance Study

Yes, a standalone performance of the algorithm (SDT) was conducted. The "Pre-acquisition," "Post-acquisition," and "Real World Data" studies primarily describe the SDT's ability to detect failures independently or to flag files for user review without requiring a human to actively search for the anomaly first. For instance, the "Pre-acquisition" study verifies the SDT detects failures, aborts runs, and alerts the operator. The "Post-acquisition" study verified the SDT identified data files with signal loss.

7. Type of Ground Truth Used

• Pre-acquisition: Induced signal loss.
• Post-acquisition:
  • "retrospective data imprinted with failure patterns characterized from field data" (implies prior expert identification of failure patterns).
  • "prospectively induced random signal loss" (controlled experimental induction).
• Real World Data: "verifiable signal failure" on field-returned boards and "confirmed by visual review of the time plots." This indicates a form of expert consensus or established visual criteria.
• Reader Study: Signal loss was pre-determined in "7 of these files." How this ground truth was established for the 7 files (e.g., by experts, by other means) is not explicitly detailed but presumed to be based on an established method for classifying signal loss.

8. Sample Size for Training Set

The document does not provide details about a specific training set or its sample size. The description of the software update as "additional risk control measures" suggests it might be based on analysis of existing field data rather than a classically trained machine learning model with a distinct training phase. If the SDT uses machine learning or pattern recognition, the "failure patterns characterized from field data" mentioned in the post-acquisition study might represent a form of data used for setting detection thresholds or rules, but it's not explicitly called a "training set."

9. How Ground Truth for Training Set Was Established

Since a specific training set is not explicitly mentioned, the method for establishing its ground truth is also not detailed. However, the "failure patterns characterized from field data" (potentially used for developing the SDT) would likely have been established through expert analysis and root cause investigation of reported signal loss/drift incidents.

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