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The Diatron Abacus 3CP System is a quantitative multi-parameter automated hematology analyzer designed for in-vitro-diagnostic use in clinical laboratories for enumeration of the following parameters: WBC, LYM%, LYM#, MID%, MID#, GRA%, GRA#, RBC, HGB, HCT, MCV, MCH, MCHC, RDW, PLT, MPV in K3EDTA anti-coagulated venous whole blood samples. The Diatron Abacus 3CP is indicated for use to identify patients with hematologic parameters within and outside of established reference ranges.

The 'Abacus 3CP' is a fully automated, bench top hematology cell counter with a cap piercing function. It uses the impedance-method for counting cells passing through a small aperture, and measures the hemoglobin content of red blood cells using a photometric method. The analyzer features a color graphical LCD display module and a foil keypad of 29 keys including 6 software buttons, 6 function keys and a START button. The instrument allows printing reports to an external printer (USB port), or can have an optional built-in printer module. Its internal memory is capable of storing 1000 records with full histograms, and individual patient data. The QC measurements are stored in a separate database. The software operating the instrument can be updated by using a USB flash memory device. The instrument can be connected to a host computer for uploading records in its memory through a USB SLAVE port (USB B) or serial link (RS232). Archiving records to an USB flash memory device is also possible.

The provided text describes the 510(k) summary for the Diatron Abacus 3CP Automated Hematology Analyzer (K111534). It compares its performance to a predicate device, the Abbott CELL-DYN® 1800 (K030513), to demonstrate substantial equivalence.

Here's an analysis of the acceptance criteria and study information based on the provided document:

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

The document does not explicitly state quantitative acceptance criteria in a table format. Instead, it relies on demonstrating equivalence to the predicate device. The performance section states:

"All performance and accuracy data and data analysis in this submission support and substantiate equivalence to the selected predicate device (Abbott CELL-DYN® 1800 (K030513))."

This implies that the acceptance criteria are met if the device's performance is comparable to that of the legally marketed predicate device. The detailed performance data, which would show the "reported device performance" and how it compares to the predicate, is not included in this summary. It would likely be in the full submission. The key performance metrics mentioned are the ability to accurately enumerate the specified hematology parameters.

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

The document does not specify the sample size used for the test set or the data provenance (country of origin, retrospective/prospective). It generally states that "a representative sample of the device underwent software and system verification and validation testing."

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)

The document does not provide any information regarding the number or qualifications of experts used to establish the ground truth for the test set. For hematology analyzers, the ground truth is typically established through reference methods or manual microscopy performed by trained laboratory professionals (medical technologists, hematologists).

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

The document does not describe any specific adjudication method for the test set.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not done. This device is an automated hematology analyzer, directly measuring parameters, and does not involve human readers interpreting images with or without AI assistance. It's a standalone diagnostic device.

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

Yes, a standalone study was implicitly done. The "Abacus 3CP, Automated Hematology Analyzer" is designed for "in-vitro-diagnostic use in clinical laboratories for enumeration of the following parameters". This indicates that the device operates automatically without human intervention in the primary measurement and calculation of parameters. Its performance is assessed as a standalone system.

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

While not explicitly stated, for hematology analyzers, the ground truth is typically established by:

• Reference methods: Highly accurate and precise laboratory methods (e.g., manual cell counts, flow cytometry for cell differentials) are used as the gold standard to which the automated analyzer's results are compared.
• Manual microscopy (expert review): For certain parameters, especially cell differentials or identification of abnormal cells, expert microscopic review by trained medical technologists or hematologists serves as the ground truth.

8. The sample size for the training set

The document does not mention a "training set" or its sample size. This is typical for a device like an automated hematology analyzer, where the algorithms (methodologies for calculating parameters like impedance counting and photometric measurement) are based on established scientific principles rather than being "trained" on a dataset in the modern machine learning sense. The device's performance is validated through verification and validation testing, not through training data.

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

As there's no mention of a "training set" in the context of machine learning, there's no information on how its ground truth would have been established. The core methodologies of the device (impedance, photometry, calculations) are deterministic and based on physical principles, not a learned model.

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The Diatron Abacus 5 System is a quantitative multi-parameter automated hematology analyzer designed for in-vitro-diagnostic use in clinical laboratories for enumeration of the following parameters in K3EDTA anti-coagulated venous whole blood samples: WBC, LYM%, LYM#, MON%, MON#, NEU%, NEU#, EOS%, EOS#, BAS%, BAS#, RBC, HGB, HCT, MCV, MCH, MCHC, RDWcv, RDWsd, PLT and MPV. The Diatron Abacus 5 is indicated for use to identify patients with hematologic parameters within and outside of established reference ranges.

The 'Abacus 5' is a fully automated high quality hematology analyzer for in vitro diagnostic use in clinical laboratories. It provides precise and accurate 5-part differential measurement using a laser based optical measurement technology. The 'Abacus 5' analyzer uses the impedance method for measurement of leukocytes (WBC), erythrocytes (RBC) and platelet (PLT) concentrations. Measurement of the hemoglobin (HGB) content of red blood cells is accomplished by photometric measurement technology. Five part leukocyte differential (LYM%, MON%, NEU%, EOS%, BAS%) is accomplished using optical laser-based flow cytometric technology. A vivid color touch screen display is featured with an intuitive, informative, and attractive user interface. A START button allows one-touch operation for ease of use. The 'Abacus 5' analyzer's unique software system supports the use of many commonly used external printers with its USB connections. The 'Abacus 5' internal database is capable of storing 100,000 patient, QC, and calibration result records including flags and graphical scatter diagrams and histograms. The system software is field-upgradeable to ensure up-to-date operation. An automatic optional Autosampler is available (sold separately) for automated processing of up to 100 sample tubes for increased laboratory efficiency. The 'Abacus 5' features advanced Ethernet LIS connectivity using the HL7 protocol in addition to standard serial interfaces, providing the clinical laboratory with flexible connectivity options.

Here's an analysis of the acceptance criteria and study information for the Diatron Abacus 5, Automated Hematology Analyzer, based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly state specific quantitative acceptance criteria or detailed reported device performance in a table format. Instead, it makes a general statement about meeting requirements and substantiating equivalence to the predicate device.

What is present:
The "Substantial Equivalence: Similarities" and "Substantial Equivalence: Differences" sections compare the Abacus 5 against the predicate device (Abbott CELL-DYN® 3700) across various technical and functional aspects. This comparison indirectly implies that the Abacus 5's performance across these characteristics is considered equivalent or acceptable relative to the predicate.

What is missing (typical for a detailed acceptance criteria table):

• Specific numerical ranges or thresholds for accuracy, precision, linearity, carryover, etc., for each of the measured parameters (WBC, LYM%, RBC, HGB, etc.).
• The actual measured values or statistical correlations observed in the study for these parameters.

Given the information, a table of acceptance criteria and reported performance cannot be fully constructed with quantitative values. The document states:

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

The provided 510(k) summary does not specify the exact sample size used for the test set or provide details on data provenance (e.g., country of origin, retrospective/prospective). It generally refers to "performance and accuracy summary data" in an internal document, "Validation Report of Abacus 5 Hematology Instrument, Revision 2."

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

The 510(k) summary does not provide information on the number of experts used, their qualifications, or how ground truth was established for the "test set." For devices like automated hematology analyzers, ground truth often involves comparison to highly accurate reference methods or manual microscopy performed by skilled technicians or pathologists. This information is absent from the summary.

4. Adjudication Method for the Test Set

The document does not mention any adjudication method (e.g., 2+1, 3+1) for establishing ground truth for a test set.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study typically assesses how human readers' performance changes with and without AI assistance, which is not applicable to a standalone automated hematology analyzer like the Abacus 5. The device's purpose is to automate cell counting, not augment human interpretation in the same way an AI imaging tool might.

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

Yes, a standalone performance study was implicitly done. The "Performance" section explicitly states: "All performance and accuracy summary data and conclusions can be referenced in document # A5-05-0020-02, Validation Report of Abacus 5 Hematology Instrument, Revision 2...All performance and accuracy data and data analysis in this submission support and substantiate equivalence to the selected predicate device."

This indicates that the device's performance, as an automated analyzer, was tested and evaluated on its own (i.e., "algorithm only") to demonstrate its accuracy against the predicate device. The device itself is designed for automated measurement without human intervention in the primary measurement process, although human interpretation of results and flags is part of its intended use.

7. Type of Ground Truth Used

The type of ground truth used is not explicitly stated in the summary. For hematology analyzers, ground truth often involves:

• Reference Method Comparison: Comparing results to accepted reference methods (e.g., manual differential counts by trained technologists/pathologists, or flow cytometry for certain cell populations).
• Predicate Device Comparison: Due to the nature of a 510(k) submission, a significant aspect of "truth" establishing is demonstrating equivalence to a legally marketed predicate device (Abbott CELL-DYN® 3700 in this case). This means the predicate device's performance serves as a de facto benchmark for acceptable "truth."

The summary refers to "performance and accuracy data" that "substantiate equivalence to the selected predicate device," strongly suggesting that comparison to the predicate device's results formed a key part of establishing the device's validated "truth."

8. Sample Size for the Training Set

The 510(k) summary does not provide information on the sample size for a training set. Hematology analyzers, especially those from 2012, might not rely on "training sets" in the same way as modern AI/machine learning algorithms. Their operation is based on fixed algorithms derived from biophysical principles (impedance, light scatter/absorption). If any parameter tuning or algorithm development involved data, it's not detailed here.

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

Since the mechanism of "training" (in the machine learning sense) is not described, the summary does not specify how ground truth for a training set was established. Modern AI/ML-driven medical devices would typically provide this detail. For this device, "ground truth" during development would likely have referred to standard clinical samples analyzed by established reference methods to refine the physics-based algorithms and ensure accurate mapping of electrical impedance and optical scatter data to cell parameters.

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