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The CELLTRACKS® AUTOPREP® System is a laboratory instrument used with immunomagnetic reagents that capture and enrich target cells, and labeling reagents that differentiate cells in whole blood. The CELLTRACKS ANALYZER II® may be used for cell identification and enumeration. The system is for in vitro diagnostic use.

The CELLTRACKS® AUTOPREP® System is a general purpose laboratory instrument used with immunomagnetic reagents that capture and enrich target cells, and labeling reagents that differentiate cells in whole blood. The CELLTRACKS® AUTOPREP® System processes up to 8 samples in a batch, performing all required process steps, including red cell detection, plasma aspiration and final transfer to the analysis cartridge. The user is prompted to perform various pre-processing operations such as dilution and centrifugation. Cell analyzers such as the CELLTRACKS ANALYZER II® may be used for cell identification and enumeration following processing. The CELLTRACKS® AUTOPREP® system uses a series of immunomagnetic separation procedures to isolate the cells of interest and to stain the cells with fluorescence-labeled monoclonal antibodies.

This is a 510(k) summary for the CELLTRACKS® AUTOPREP® System, a medical device for in vitro diagnostic use. The purpose of this submission is to demonstrate substantial equivalence to a predicate device (CELLTRACKS® AUTOPREP® System (current - K110406)). The only change is a modification to the pipetting probe to reduce potential carryover and a corresponding label change.

Here's a breakdown of the requested information based on the provided text:

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

The provided 510(k) summary does not explicitly state numerical acceptance criteria for carryover. Instead, it focuses on demonstrating equivalence to the predicate device and characterization of the new probe's performance regarding carryover.

2. Sample size used for the test set and the data provenance

The document does not explicitly state the sample size used for the test set in terms of the number of patient samples. It mentions "up to 8 samples in a batch" for processing but this refers to the operational capacity of the instrument, not the sample size of the study for performance validation.

• Test Set Sample Size: Not explicitly stated for each test, but "up to 8 samples in a batch" is mentioned for processing.
• Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). The testing is described as "Non-clinical functional testing," implying laboratory-based testing rather than patient data collection in a clinical setting.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. This device is an automated instrument for processing and enriching cells. The evaluation appears to be based on analytical performance metrics (e.g., carryover levels, assay performance equivalence) rather than expert interpretation of images or patient data. Therefore, there's no mention of experts establishing ground truth for the test set in this context.

4. Adjudication method for the test set

Not applicable, as there are no human interpretations or classifications that would require adjudication. The testing is focused on the device's functional performance.

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

Not applicable. This is not an AI-assisted diagnostic device that involves human readers. It's an automated sample preparation system.

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

This refers to a standalone product. The CELLTRACKS® AUTOPREP® System is a standalone instrument for sample preparation. The performance evaluation described is of the instrument's functional characteristics (e.g., pipetting, carryover), which is inherently "standalone" in its operation relative to the manual methods it automates. The "algorithm" in this context would be the automated processing steps of the instrument.

7. The type of ground truth used

The "ground truth" for this device would be defined by the expected analytical performance. For example:

• Known Cell Spikes: For CTC spike level characterization, a known number of tumor cells would be "spiked" into samples, and the device's ability to recover them, and the level of carryover from these known spikes, would be measured.
• Control Cells: For control cell carryover, known control cells would be used.
• Reference Methods: The "new reagent probe versus current reagent probe assay performance equivalence" would imply comparison to assays run with the predicate device's probe, where the "truth" is the established performance of the predicate.
• Engineering Specifications: Reliability/Life testing would be against pre-defined engineering specifications for durability and performance over time.

Therefore, the ground truth is based on analytical standards, known input concentrations (e.g., spiked cells), and comparison to a well-characterized predicate device's performance.

8. The sample size for the training set

Not applicable. This device is not an AI/ML algorithm that requires a "training set." It's an automated instrument where the "learning" is incorporated during its design and engineering phases, not through a data-driven training process.

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

Not applicable, as there is no training set for this type of device.

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The CellTracks® AutoPrep® System is a general purpose laboratory instrument used with immunomagnetic reagents that capture and enrich target cells, and labeling reagents that differentiate cells in whole blood. Cell analyzers such as the CellTracks Analyzer II®, flow cytometers or microscopes may be used for cell identification and enumeration. The system is for in vitro diagnostic use.

The CellTracks® AutoPrep® System is a general purpose laboratory instrument used with immunomagnetic reagents that capture and enrich target cells, and labeling reagents that differentiate cells in whole blood.

This document is a FDA 510(k) clearance letter and does not contain the detailed information required to answer the prompt. Specifically, it does not describe the acceptance criteria, the study details, sample sizes, expert qualifications, or ground truth establishment. It merely states that the device, CellTracks® AutoPrep® System, is substantially equivalent to a legally marketed predicate device for its indicated use.

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The CellTracks® AutoPrep® System is a general purpose laboratory instrument used with immunomagnetic reagents that capture and enrich target cells, and labeling reagents that differentiate cells in whole blood. Cell analyzers such as the CellTracks Analyzer II®, CellSpotter® System, flow cytometers or microscopes may be used for cell identification and enumeration. The system is for in vitro diagnostic use.

The CellTracks® AutoPrep® System is a general purpose laboratory instrument used with immunomagnetic reagents that capture and enrich target cells, and labeling reagents that differentiate cells in whole blood. The CellTracks® AutoPrep® System processes up to 8 samples in a batch, performing all required process steps, including red cell detection, plasma aspiration and final transfer to the analysis cartridge. The user is prompted to perform various pre-processing operations such as dilution and centrifugation. Cell analyzers such as the CellTracks Analyzer II®, CellSpotter® System, flow cytometers or microscopes may be used for cell identification and enumeration following processing.

The AutoPrep® system uses a series of immunomagnetic separation procedures to isolate the cells of interest and to stain the cells with fluorescence-labeled monoclonal antibodies.

The provided text describes a 510(k) premarket notification for the CellTracks® AutoPrep® System. This is a general purpose laboratory instrument for automated blood cell preparation, not an AI/ML powered diagnostic device. Therefore, much of the requested information (such as AI performance metrics, expert adjudication, MRMC studies, and training/test set details) is not applicable or cannot be extracted from this document.

However, I can extract the acceptance criteria related to its substantial equivalence to the predicate device and the study that demonstrates this.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

The document does not specify a distinct "test set" in the context of AI/ML. The evaluation was based on "functional testing of the bulk fluid module" and "performance testing using quality control samples." The specifics of these samples (e.g., number, type, origin) are not detailed.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. Ground truth as typically defined for AI/ML validation (e.g., expert consensus on images or pathology) is not relevant for this device's evaluation as it is a laboratory instrument, not an interpretive diagnostic.

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

Not applicable. This concept is typically associated with expert review of diagnostic outputs, which is not described for this device.

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

Not applicable. This device is a pre-analytic instrument, not an AI-powered diagnostic that assists human readers.

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

This refers to the performance of the instrument itself. The study mentioned "functional testing of the bulk fluid module" and "performance testing using quality control samples," which represents the standalone performance of the modified device.

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

The "ground truth" for this device would be the expected functional output and performance metrics based on established laboratory standards and comparisons to the predicate device. This is indicated by "functional testing" and "performance testing using quality control samples." The specific methodology for establishing these performance benchmarks is not detailed beyond these general terms.

8. The sample size for the training set

Not applicable. This device is an instrument, not an AI/ML model that requires a training set.

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

Not applicable.

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The intended use for the Immunicon CellTracks™ AutoPrep System is as a generalpurpose laboratory instrument used with immunomagnetic reagents that capture and enrich target cells, and labeling reagents that differentiate cells in whole blood. Cell analyzers such as the CellTracks™ Analyzer, CellSpotter™ System, flow cytometers or microscopes may be used for cell identification and enumeration. The system is for in vitro diagnostic use.

The CellTracks™ AutoPrep System is an automated sample-handling instrument that starts with a tube of anticoagulated whole blood and delivers an enriched, processed sample that is ready to analyze by flow-cytometry, fluorescent microscopy, CellSpotter™ System or by the CellTracks™ Analyzer. The AutoPrep System performs several steps, including red cell detection, plasma aspiration and filling of a sample chamber or test tube. The principal of operation relates to the addition of a ferrofluid, which has been conjugated with monoclonal antibodies that act with the system to magnetically separate the cells of interest and in subsequent steps, within the system, to add fluorescencelabeled monoclonals to further differentiate the captured cells. The first reagent added is ferrofluid, which consists of a magnetic core surrounded by a protein layer coated with antibodies for attachment to cells. Ferrofluid particles are colloidal and when mixed with a sample containing the target cells, they interact and attach to the target cells. The ferrofluid/sample mixture is placed in a strong magnetic field, which causes the labeled target cells to move to the side of the tube. The blood is aspirated, the magnetic field is removed and the cells are resuspended in a small volume of buffer and fluorescent reagents are added for the identification and enumeration of the target cells. Another magnetic separation step and resuspension is performed and the sample is now ready for analysis. The immunomagnetic enrichment process is the new technology but does not raise any new issues of safety and effectiveness.

The provided document is a 510(k) summary for the Immunicon CellTracks™ AutoPrep System. It does not contain information about acceptance criteria or a study proving that a device meets specific performance criteria in the context of an AI/ML medical device, as the prompt's structure implies. This device is a sample-handling instrument for in vitro diagnostic use, not an AI-based system.

However, I can extract the relevant performance data that was collected as part of the 510(k submission.

Here's an analysis based on the information provided, framed to best fit the request, while acknowledging the limitations of the document's content for an AI/ML context:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a tabular format with predefined numerical targets. Instead, it describes performance characteristics observed during clinical and non-clinical testing. I will present the reported performance as if these were the metrics assessed.

The document discusses two main types of studies: a precision study and a method comparison study.

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

• Test Set Sample Size: The document states a "20 day precision study" was performed and a "method comparison was performed." It does not explicitly state the number of samples or patients used in these studies. The precision study implies repeated measurements over 20 days.
• Data Provenance: Clinical testing was performed at "three clinical sites." The document does not specify the country of origin, but given the FDA submission, it's highly likely to be within the United States. The studies are prospective in nature, as they involve performing tests with the device to evaluate its performance.

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

The document does not mention the use of experts to establish a "ground truth" for the test set in the context of diagnostic interpretation. The studies are technical performance evaluations of an automated sample preparation system. The "ground truth" for the precision study would be the known spike levels of control cells, and for the method comparison, it would be the results obtained by the predicate device. Therefore, no external experts were explicitly mentioned for ground truth establishment.

4. Adjudication Method for the Test Set

Not applicable. This is not a study requiring adjudication of diagnostic interpretations. The studies described are analytical performance evaluations.

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

No. This is not an AI/ML diagnostic device; it's an automated sample preparation system. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this submission and was not conducted.

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

Yes, in the sense that the performance evaluations (precision, sensitivity, linearity, method comparison) assess the device's technical capabilities as a standalone automated system. There's no "human-in-the-loop" component for the sample preparation itself, although subsequent analysis of the processed samples would involve human operators and/or other analytical instruments.

7. Type of Ground Truth Used

• Precision Study: The ground truth for the precision study was based on "control cells" at "spike levels" (38 cells and 264 cells). This implies a known, controlled input to assess reproducibility.
• Nonclinical Testing (Sensitivity, Linearity): The ground truth for sensitivity and linearity was derived from known cell counts introduced into the system to determine its ability to detect and accurately quantify them.
• Method Comparison: The ground truth for the method comparison was the results obtained from the "predicate device." This establishes a comparative baseline against an already legally marketed device for the same intended use.

8. Sample Size for the Training Set

Not applicable. This is not an AI/ML device that requires a training set. The device operates based on pre-programmed protocols and immunomagnetic separation principles, not on learned patterns from a training dataset.

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

Not applicable, as there is no training set for this type of device.

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