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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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The Immunicon CellPrep™ Sample Preparation 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, flow cytometers or microscopes may be used for cell identification and enumeration. The system is for in vitro diagnostic use.

The CellPrep System is a semi-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 or by the CellTracks™ Analyzer. The CellPrep™ System performs several steps, including red cell detection, plasma aspiration and filling of a sample chamber or test tube. The user is prompted to perform various operations such as reagent addition and mixing. 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 fluorescence-labeled 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 provided text describes the Immunicon CellPrep™ Sample Preparation System and summarizes the testing performed to demonstrate its safety and effectiveness. However, it does not explicitly present a table of acceptance criteria or a detailed, structured study report in the format requested. Instead, it provides a narrative summary of performance findings.

Based on the provided text, here's an attempt to extract and infer the requested information:

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

The document does not explicitly state "acceptance criteria" as a separate, defined list. However, we can infer the performance targets/criteria from the reported results.

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

• Sample Size for Test Set: The text states, "Clinical testing was performed at five clinical sites." It mentions the device was "capable of removing small numbers of cells (~950) from a 7.5 ml volume of blood" and that the CV range was for "duplicate samples." However, it does not explicitly state the total number of patient samples, runs, or analyses conducted within the clinical trial. It only refers to "small numbers of cells (~950)". For non-clinical testing, it mentions "very low levels of approximately 10 cells" and "range of 50 to 200 cells" in a 7.5ml sample, but again, no specific sample size (i.e., number of spiked samples or replicates) is provided.
• Data Provenance:
  • Country of Origin: Not specified.
  • Retrospective or Prospective: "Clinical testing was performed at five clinical sites" implies a prospective study, where samples were processed and analyzed as part of the trial. The term "nonclinical testing" typically refers to laboratory-based, controlled studies, which are also generally prospective in nature.

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

This information is not provided in the document. The text states, "Clinical testing was performed at five clinical sites by Medical technicians or degreed biologists." While these individuals performed the testing, the method and number of experts establishing the ground truth (e.g., the true cell count before processing, or an independent verification of captured cells) are not detailed.

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

This information is not provided in the document. The text does not describe any adjudication process for the results obtained.

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

The Immunicon CellPrep™ Sample Preparation System is described as a "semi-automated sample-handling instrument" designed to prepare samples for analysis by "flow cytometers or microscopes." It processes blood and delivers an enriched sample. It is not an AI-powered diagnostic tool for image interpretation or diagnosis that would typically be evaluated in an MRMC study involving human readers with and without AI assistance. Therefore, an MRMC study as described, and its effect size, are not applicable and were not performed for this device type based on the provided text.

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

The device is a "semi-automated sample-handling instrument." It performs physical steps to prepare blood samples. While it has automated components, it is not an "algorithm only" device in the sense of an AI model. The performance metrics (recovery, precision, sensitivity, linearity) are for the device's ability to process samples, which is inherently a "standalone" performance evaluation of the instrument itself in its intended function.

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

The document implies that the ground truth for cell recovery and linearity studies would have been established by:

• Known input concentrations: For nonclinical sensitivity and linearity testing, cells are typically spiked into samples at known concentrations.
• Baseline measurements or reference methods: For clinical recovery, it would involve knowing the initial cell count in the 7.5 ml blood volume before the CellPrep device processes it. This might be done using a highly accurate reference method or manual counting.
  The document does not explicitly state the exact method used, but for "recovery" and "sensitivity" of a sample preparation system, the ground truth is generally a quantified, validated initial cell count or concentration.

8. The sample size for the training set

The device is a sample preparation instrument. It does not use machine learning or AI models that require a "training set" in the typical sense of AI/ML software development. Therefore, this concept is not applicable to the Immunicon CellPrep™ Sample Preparation System as described.

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

As explained in point 8, the concept of a "training set" for an AI/ML model does not apply to this device.

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The COULTER® CellPrep is an automated system that processes human blood for preparation of leukocyte suspensions for quantitative immunofluorescence analysis by optical flow cytometers.

The use of data generated by this instrument depends on the regulatory status of the reagents you use. If the reagent is labeled by the manufacturer "For Research Use Only. Not for use in diagnostic procedures," federal law prohibits the use of the data for diagnosis.

This product is intended "For In Vitro Diagnostic Use" when using the "IVDImmunophenotype" protocol and processing whole blood samples with COULTER reagents and antibodies labeled for In Vitro Diagnostic Use.

The COULTER® CellPrep is a compact, fully automated sample processing workstation which can be programmed to perform a variety of cell wash, dilution, and concentration operations.

The provided text presents a 510(k) summary for the COULTER® CellPrep device. However, it does not contain the specific details required to answer all the questions about acceptance criteria and the study proving the device meets them. The document primarily focuses on establishing substantial equivalence to a predicate device and describing its intended use.

Here's what can be extracted and what is missing:

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

The document does not explicitly state acceptance criteria or provide a table of reported device performance metrics against such criteria. It only states: "The data in the Premarket Notification on safety and effectiveness supports a finding of substantial equivalence to products already in commercial distribution."

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

This information is not present in the provided text.

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 information is not present in the provided text.

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

This information is not present in the provided text.

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 information is not present in the provided text. The COULTER® CellPrep is an automated system for processing blood, not an AI-assisted diagnostic tool that would typically involve human readers.

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

The device itself is described as a "fully automated sample processing workstation." The entire device is designed to operate in a standalone manner for sample preparation. However, the document does not provide performance metrics for this standalone operation.

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

This information is not present in the provided text.

8. The sample size for the training set

This information is not present in the provided text.

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

This information is not present in the provided text.

In summary, the provided document is a 510(k) premarket notification summary, which primarily aims to demonstrate substantial equivalence to a predicate device based on its intended use and general performance. It does not delve into the detailed study methodology, acceptance criteria, or performance metrics in the way a more comprehensive clinical study report would.

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