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The Revogene® instrument is intended for in vitro diagnostic (IVD) use in performing nucleic acid testing of specific IVD assays in clinical laboratories. Revogene is capable of automated lysis and dilution of samples originating from various clinical specimen types. Revogene performs automated amplification and detection of target nucleic acid sequences by fluorescence-based real-time PCR.

The Revogene is a PCR instrument that automates lysis and dilution of samples, followed by nucleic acid amplification, and detection of target sequences by fluorescence-based real-time PCR. Revogene runs are orchestrated by a combination of software, firmware and instrument control protocol that ensures the adequate combination times and temperatures for sample homogenization and PCR analysis. The Revogene instrument acquires fluorescence signals generated during amplification. The signals are then interpreted by the system using embedded calculation algorithms.

The Revogene requires the use of a 'PIE', i.e., an assay-specific cartridge to which a patient sample is added. The PIE contains the reagents needed to process a sample and to perform a PCR amplification. When the number of assay PIEs to be run is lower than eight, the user fills empty spaces with "MOCK PIE", which are cartridges that simulate the presence of an assay PIE to confer thermal and rotational balance.

The Revogene instrument subject of this Premarket Notification is substantially equivalent to the Revogene instrument cleared under K222779. Meridian is submitting this 510(k) Premarket Notification to implement a photomultiplier tube (PMT) cooling system. This cooling system keeps the PMT environment at a temperature that prevents the appearance of fluorescence glitches, which may stop the Revogene instrument

The provided document is a 510(k) Premarket Notification for a modified medical device, the Revogene instrument. It focuses on the changes made to an existing device (K222779) and its substantial equivalence to the predicate device.

The document does not contain information about acceptance criteria or a detailed study proving the device meets specific acceptance criteria, as one might find in a clinical trial report for an initial device clearance.

Instead, it describes the performance characteristics of functional testing conducted to demonstrate that the modifications (PMT cooling system and Windows 10 upgrade) do not adversely affect the device's performance compared to the predicate. The goal of this submission is to show substantial equivalence, not to establish new performance acceptance criteria.

Therefore, I cannot provide a table of acceptance criteria and reported device performance in the traditional sense, nor can I answer many of your specific questions about study design, sample sizes, ground truth establishment, or expert adjudication, as this information is not present in the provided text.

However, I can extract the available information regarding the functional testing that was performed to support the substantial equivalence claim.

Summary of Available Information on Device Performance and Testing:

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

The document does not explicitly state quantitative acceptance criteria. Instead, it describes general observations and conclusions from functional testing. The implicit acceptance criterion is "no statistically significant differences" and "operates as expected and yields expected assay results."

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

• Sample Size for Test Set: The document states "contrived and negative samples in relevant clinical matrix using the following assays...". However, it does not specify the number of samples or runs used for this functional testing.
• Data Provenance: Not explicitly stated, but given it's a regulatory submission by a US company, the testing would typically be conducted according to established protocols within their R&D or QA departments. It is retrospective relative to the design changes, but the testing itself is performed to support the new device version. No information on country of origin of data beyond the manufacturer's location.

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 as the testing described is functional performance testing of the instrument, not typically involving expert interpretation of patient samples for ground truth establishment. The "ground truth" here is the expected performance of control samples within the assays.

4. Adjudication method for the test set

• This is not applicable/provided. The testing focuses on the instrument's functional output (e.g., Ct values, glitch occurrence) rather than interpretation of results that would require adjudication.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done

• No, this was not done. The device is an instrumentation for clinical multiplex test systems, meaning it processes samples and detects nucleic acids. It does not output images or data that require human readers for interpretation in the way an AI diagnostic imaging device would. Therefore, an MRMC study is not relevant to this type of device or its modifications.

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

• The device itself is a standalone instrument that performs automated lysis, dilution, amplification, and detection. The "algorithm" here refers to the embedded calculation algorithms within the system that interpret fluorescence signals to determine results. The functional testing described is a form of standalone performance evaluation for the modified instrument. There is no human-in-the-loop component mentioned for the actual nucleic acid detection and interpretation process of the instrument.

7. The type of ground truth used

• The ground truth for the functional testing appears to be based on the expected outcomes from known contrived and negative samples when run with specific IVD assays (Revogene® Strep A, Revogene® Carba C and Revogene® SARS-CoV-2). Essentially, the "ground truth" is the established performance of the assays themselves on control materials, and the instrument must correctly process these, showing no statistical degradation from the predicate.

8. The sample size for the training set

• This information is not provided and is generally not applicable in the context of hardware modifications to an existing IVD instrument as described. The "training set" concept is typically relevant for machine learning algorithms, which are not detailed here beyond "embedded calculation algorithms" that likely leverage established PCR physics and signal processing rather than iterative machine learning training.

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

• This information is not provided as there is no mention of a traditional "training set" in the machine learning sense. The established performance of the assays with known control materials serves as the reference for evaluating the modified instrument.

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The Revogene® instrument is intended for in vitro diagnostic (IVD) use in performing nucleic acid testing of specific IVD assays in clinical laboratories. Revogene is capable of automated lysis and dilution of samples originating from various clinical specimen types. Revogene performs automated amplification and detection of target nucleic acid sequences by fluorescence-based real-time PCR.

The Revogene® instrument is intended for in vitro diagnostic (IVD) use in performing nucleic acid testing of specific IVD assays in clinical laboratories. Revogene is capable of automated lysis and dilution of samples originating from various clinical specimen types. Revogene performs automated amplification and detection of target nucleic acid sequences by fluorescence-based real-time PCR.

The provided document is an FDA 510(k) Substantial Equivalence Determination Decision Summary for the Revogene instrument.
Crucially, this submission (K222779) is a "Special 510(k)" for a firmware modification only, specifically to add a cooling sequence before lid opening in the event of a run interruption.

Therefore, the document does not contain information about a study to prove the device's diagnostic performance against acceptance criteria in the typical sense of analytical or clinical performance (e.g., sensitivity, specificity for detecting a disease). Instead, the performance demonstrated here relates to the safety feature implemented by the firmware update.

Based on the provided text, here's an analysis of the acceptance criteria and study that address the firmware modification:

1. Table of Acceptance Criteria and Reported Device Performance:

The document implicitly defines the acceptance criteria for this specific modification: the firmware update must successfully implement a cooling sequence before lid opening when a run is interrupted, to prevent access to hot parts.

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

The document does not detail specific sample sizes or data provenance (e.g., country of origin, retrospective/prospective) for testing this firmware modification. This is expected given the nature of a Special 510(k) for a safety-related firmware update. The FDA's decision to clear the device implies they were satisfied with the internal validation conducted by the manufacturer to demonstrate the successful implementation of this safety feature. No clinical data or large-scale analytical testing is typically required for such minor safety updates.

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

Not applicable for this type of firmware modification. The ground truth here is a functional safety requirement (i.e., "are hot parts accessible when a run is aborted after the update?"). This would be verified through engineering testing and safety assessments, not typically by expert consensus of clinical or radiological images.

4. Adjudication method for the test set:

Not applicable. This is not a study assessing diagnostic performance where adjudication of ambiguous results would be necessary.

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 an instrument for molecular diagnostics (nucleic acid testing), not an AI-assisted diagnostic imaging device.

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

Not directly applicable in the typical sense (e.g., for an AI algorithm). The device itself operates "standalone" in its function of automated lysis, amplification, and detection, but the "performance" discussed here is a safety feature of its firmware, not its diagnostic accuracy.

7. The type of ground truth used:

The ground truth for this specific firmware modification is a functional safety performance objective. The "truth" is whether the cooling sequence activates as intended upon run interruption and whether it effectively prevents access to hot parts, thereby improving user safety. This would be established through engineering functional testing and safety verification protocols.

8. The sample size for the training set:

Not applicable. This is a firmware modification for a safety feature, not a machine learning algorithm that requires a "training set."

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

Not applicable. As above, no training set for a machine learning model is involved.

Summary of the document's relevance to your request:

The provided document is an FDA clearance letter for a firmware upgrade to an existing medical device, the Revogene instrument. This is a very specific type of submission (Special 510(k)) that focuses on demonstrating that a minor change does not adversely affect the device's safety or effectiveness, or alter its fundamental scientific technology.

Therefore, the typical metrics and study designs used for evaluating the diagnostic performance of new AI/ML-based devices (e.g., sensitivity, specificity, MRMC studies, ground truth established by expert consensus or pathology) are not present or applicable here. The "acceptance criteria" and "study" are focused solely on verifying the successful and safe implementation of the firmware's added cooling sequence upon run interruption.

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The Revogene® instrument is intended for in vitro diagnostic (IVD) use in performing nucleic acid testing of specific IVD assays in clinical laboratories. Revogene is capable of automated lysis and dilution of samples originating from various clinical specimen types. Revogene performs automated amplification and detection of target nucleic acid sequences by fluorescence-based real-time PCR.

The Revogene was previously cleared under K170558. Meridian Biosciences, Inc. is submitting this 510(k) to implement a software modification to the Revogene that updates the current software with a PMT surveillance algorithm. The software monitors raw data fluorescence signal during assay testing and identifies issues due to a malfunction of the photomultiplier tube (the "PMT"), a key component in the Revogene instrument's optics system used in the management of fluorescence signals. Upon detection of a PMT malfunction, the PMT surveillance algorithm software produces a specific error code to the user labeled "Detection Error" and will lock the instrument thereby preventing further use.

The provided text describes a 510(k) submission for a software modification to the Revogene instrument, specifically the addition of a PMT (photomultiplier tube) surveillance algorithm. This modification is intended to monitor raw data fluorescence signals and identify issues due to a malfunction of the PMT, a key component in the instrument's optics system. Upon detection of a PMT malfunction, the algorithm produces an error code and locks the instrument, preventing further use.

The document states that this change does not affect the device's intended use nor alter the device's fundamental scientific technology. Therefore, the acceptance criteria and performance study details are focused on validating the new PMT surveillance algorithm's functionality and ensuring it does not negatively impact the previously cleared performance of the Revogene instrument.

Based on the provided text, a formal table of acceptance criteria and reported device performance, akin to what would be provided for a diagnostic or AI algorithm's clinical performance, is not explicitly present for the PMT surveillance algorithm itself. The document emphasizes that the modification is minor and focuses on the software's ability to detect and report PMT malfunctions.

However, we can infer the acceptance criteria and study proving the device meets them from the description of the software modification and the context of a 510(k) submission for a software update.

Here's a breakdown based on the provided information, addressing each point as much as possible:

Acceptance Criteria and Reported Device Performance

The core acceptance criterion for this software modification is that the PMT surveillance algorithm successfully detects and reports PMT malfunctions. The reported performance would be the successful implementation of this functionality.

Inferred Acceptance Criteria Table:

Study Proving Acceptance Criteria:

The document implicitly indicates that a validation study was performed to demonstrate the functionality of the PMT surveillance algorithm. While details are scarce, the submission implies that the testing confirmed the algorithm's ability to detect PMT issues and trigger the appropriate error and lock-out mechanisms.

Detailed Study Information (Based on Inferences and General 510(k) Practices for Software Updates)

1. A table of acceptance criteria and the reported device performance:
   (See above table for inferred criteria and performance, as direct explicit table is not provided in the document for the new software feature). The document stresses that the overall performance characteristics of the Revogene instrument remain as previously cleared (K170558, K170557, etc.), and this software update doesn't change those.

2. Sample sizes used for the test set and the data provenance:

   • Test Set Sample Size: Not explicitly stated for the PMT surveillance algorithm. For a software update of this nature (detecting a hardware malfunction), the "test set" would likely involve inducing PMT malfunctions (or simulating conditions that would lead to them) on multiple instruments to verify the algorithm's response. The general statement "The submitted information demonstrates that the modified Revogene instrument is safe, effective" implies a sufficient level of testing.
   • Data Provenance: Not specified. Given it's a software update for a commercialized instrument, the testing would typically be performed internally by the manufacturer (Meridian Bioscience, Inc.). It's likely retrospective in that it's testing a new feature on existing hardware, but the testing itself would be prospective for evaluating the new software. Country of origin not specified, but the manufacturer is based in Ohio, USA.

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

   • This is unlikely to involve a panel of "experts" in the same way an AI diagnostic algorithm's ground truth is established. The ground truth for a PMT malfunction would be a measurable hardware degradation or induced failure that clearly indicates the PMT is not functioning correctly. This would be established by engineers or instrument specialists, not clinical experts like radiologists.

4. Adjudication method for the test set:

   • Not applicable in the context of this software update. Adjudication methods like 2+1 or 3+1 are typically for establishing ground truth for subjective human interpretations (e.g., medical image reads). Here, the judgment is objective: either the PMT is malfunctioning or it's not, and the software either detects it or it doesn't.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

   • No. An MRMC study is not relevant for this type of software modification. MRMC studies are used to evaluate the impact of an AI algorithm on human reader performance for tasks involving perception and interpretation (e.g., diagnosing disease from medical images). This software is performing an automated internal diagnostic check on the instrument itself, not assisting human clinical interpretation.

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

   • Yes, implicitly. The PMT surveillance algorithm operates automatically as an internal check. Its performance is evaluated purely on its ability to detect PMT malfunctions and trigger the pre-defined error and lock-out, without human intervention in its real-time operation.

7. The type of ground truth used:

   • Instrumental/Hardware Ground Truth: The ground truth would be based on objective measurements and engineered conditions that reliably indicate a PMT malfunction within the Revogene instrument's optics system. This could involve simulating PMT degradation, intentionally causing component failures, or verifying against known hardware states.

8. The sample size for the training set:

   • Not specified. For a diagnostic algorithm like this, the "training set" would involve data collected from instrument operations, potentially including data from instruments with known good or failing PMT conditions, to develop and refine the detection algorithms. The complexity of the algorithm (e.g., rule-based vs. machine learning) would influence the need for and size of a specific "training set." Given the description, it sounds more like a rule-based or threshold-based detection system rather than a complex machine learning model that requires a large, annotated training set in the typical sense.

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

   • If a "training set" was used (e.g., for setting detection thresholds or developing rules), the ground truth would have been established by engineering teams through controlled experiments, measurements of PMT performance over time, and potentially by inducing known PMT issues on instruments. This would involve characterization of the instrument's optical signals under various conditions, including states indicative of PMT malfunction.

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The revogene™ instrument is intended for in vitro diagnostic (IVD) use in performing nucleic acid testing of specific IVD assays in clinical laboratories. The revogene™ is capable of automated lysis and dilution of samples originating from various clinical specimen types. revogene™ performs automated amplification and detection of target nucleic acid sequences by fluorescence-based real-time PCR.

Not Found

The provided text is a 510(k) premarket notification letter from the FDA to GENEPOC INC. regarding their Revogene device. It details the regulatory classification, general controls, and indications for use of the device.

However, the document does not contain the specific information required to answer your request about acceptance criteria and the study proving the device meets those criteria. Specifically, the document does not provide:

• A table of acceptance criteria and reported device performance.
• Details on the sample size used for the test set or its data provenance.
• The number or qualifications of experts used for ground truth establishment.
• Information on adjudication methods.
• Details on multi-reader multi-case (MRMC) comparative effectiveness studies.
• Standalone algorithm performance.
• The type of ground truth used.
• Sample size for the training set or how its ground truth was established.

The document is purely administrative, confirming the FDA's substantial equivalence determination and outlining regulatory obligations. It does not delve into the technical performance studies or the clinical trials typically associated with proving a device meets acceptance criteria.

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