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Veuron-Brain-pAb3 is software for the registration, fusion, display, and analysis of medical images from multiple modalities including MRI and PET. The software aids clinicians in the assessment and quantification of pathologies from PET Amyloid scans of the human brain. It enables anatomic analysis and visualization of amyloid protein concentration through the calculation of standard uptake volume ratio (SUVR) within target reqions of interest and comparison to those within the reference regions. The software is deployed via medical imaging workplaces and is organized as a series of workflows which are specific to use with radio-tracer and disease combinations.

The Veuron-Brain-pAb3 is a standalone software for quantitative analysis of the PET amyloid by automatically calculating the "Standardized Uptake Value Ratio (SUVR)". The calculated result is only used as a reference to support the accuracy of the medical professional's diagnosis of dementia in patients. It also helps with accurate visual interpretation through visualization functions. Various PET amyloid images can be processed by using diverse options provided for users to choose in the image process.

The provided text describes the acceptance criteria and the study that proves the device meets those criteria for the Veuron-Brain-pAb3, a medical imaging software.

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

The document doesn't provide explicit acceptance criteria in a quantitative format (e.g., minimum accuracy percentages, SUVR ranges) for the Veuron-Brain-pAb3. Instead, it states that "Software verification and validation was performed to demonstrate the new functions perform as intended." and "The testing results support that all the system requirements have met their acceptance criteria and are adequate for its intended use."

However, the key functions that define the device's performance, as outlined in the "Summary of Technological Characteristics" and "Device Description," are:

• Automatic calculation of Standardized Uptake Value Ratio (SUVR) within target regions of interest and comparison to reference regions.
• Anatomic analysis and visualization of amyloid protein concentration.
• Registration, fusion, and display of medical images (MRI and PET).
• Accurate visual interpretation through visualization functions.

The document implicitly states that these functions perform as intended, which serves as the "reported device performance" meeting the unspecified acceptance criteria.

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. However, it mentions under 'Segmentation Algorithm' that the CNN model was "trained [on] 3D brain MR images were collected from one domestic institution." This suggests the data used for testing (and training) was from a single domestic institution. It doesn't specify if the data was retrospective or prospective, but given it's part of a model training and validation process, it's highly likely to be retrospective.

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

The document does not specify the number or qualifications of experts used to establish the ground truth for the test set. The ground truth for the segmentation algorithm appears to be implicitly derived from the "3D brain MR images collected from one domestic institution" used for training the CNN model, meaning the "truths" would be the labeled segmentations used to train the model. Given the device's function is quantitative analysis (SUVR calculation), the ground truth for the SUVR calculation itself would be based on the established methodology of SUVR calculation rather than expert annotation for each case.

4. Adjudication method for the test set:

The document does not describe any 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:

No. The document explicitly states: "No clinical testing was conducted." Therefore, an MRMC comparative effectiveness study was not performed.

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

Yes, implicitly. The device is described as "standalone software for quantitative analysis of the PET amyloid by automatically calculating the 'Standardized Uptake Value Ratio (SUVR)'." The "Non-Clinical Performance Testing" section mentions "Software verification and validation was performed to demonstrate the new functions perform as intended," which would involve evaluating the algorithm's performance in isolation. While the results are not quantitatively detailed, the device's core function is an automated calculation, suggesting standalone performance was assessed.

7. The type of ground truth used:

The type of ground truth for the core SUVR calculation is methodology-based (the calculation itself is a defined process). For the segmentation algorithm, the ground truth would be expert-annotated segmentations of brain MR images, used for training the CNN model.

8. The sample size for the training set:

The document does not specify the exact sample size for the training set, only stating that the CNN model for segmentation was "trained [on] 3D brain MR images were collected from one domestic institution."

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

The ground truth for the CNN model used for segmentation was established through the collection of "3D brain MR images were collected from one domestic institution" that were used to train the model. This implies that these images likely came with pre-existing or expert-derived segmentations necessary for supervised learning. For the SUVR calculation itself, the ground truth is inherently defined by the mathematical formula and anatomical regions used in its computation.

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The Veuron-Brain-pAb2 is a software for the registration, fusion, display and analysis of medical images from multiple modalities including MRI and PET. The software aids clinician in the assessment and quantification of pathologies from PET Amyloid scans of the human brain. It enables automatic analysis and visualization of amyloid protein concentration through the calculation of standard uptake volume ratios (SUVR) within target regions of interest and comparison to those within the reference regions. The software is deployed via medical imaging workplaces and is organized as a series of workflows which are specific to use with radiotracer and disease combinations.

The Veuron-Brain-pAb2 is stand-alone software to automatically calculate the "Standardized Uptake Value Ratio (SUVR)" for quantitative analysis of amyloid PET. The calculated result is just used as a reference supporting the accuracy of the diagnosis of patients' dementia for the medical professional. It also helps with accurate visual interpretation through visualization functions. Various amyloid PET images can be processed by providing a variety of options for users to choose in the image process.

The provided text describes the Veuron-Brain-pAb2 device, a software for the registration, fusion, display, and analysis of medical images (MRI and PET) to aid clinicians in assessing and quantifying pathologies from PET Amyloid scans of the human brain. It enables automatic analysis and visualization of amyloid protein concentration through the calculation of standard uptake volume ratios (SUVR).

However, the document is a 510(k) summary and primarily focuses on demonstrating substantial equivalence to a predicate device (Veuron-Brain-pAb). While it mentions "bench testing" and that the "measurement tool performance meets its pre-defined requirements," it does not provide explicit details about specific acceptance criteria, reported device performance metrics against those criteria, or the study design (including sample size, ground truth establishment, expert qualifications, or adjudication methods) that would typically prove such acceptance.

Therefore, many of your requested details cannot be extracted from this document.

Here's a breakdown of what can and cannot be answered from the provided text:

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

• Cannot be fully provided. The document states, "Bench testing is done to show that the system is suitable for its intended use and that the measurement tool performance meets its pre-defined requirements. This did not reveal any issues with the system, demonstrating that the performance of Veuron-Brain-pAb2 is as safe and effective as its predicate device."
  • This implies that there were pre-defined requirements (acceptance criteria) and that the device met them. However, the document does not list these specific acceptance criteria (e.g., accuracy thresholds for SUVR calculation, registration precision limits) or the quantitative results of the device's performance against them.

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

• Cannot be provided. The document mentions "bench testing" but does not describe the test set size, its provenance, or whether it was retrospective or prospective.

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)

• Cannot be provided. The document does not describe the method for establishing ground truth for any test set or the involvement or qualifications of experts in such a process.

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

• Cannot be provided. No adjudication method is described.

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

• Cannot be provided. The document does not mention an MRMC study or any assessment of human reader improvement with AI assistance. The device is described as aiding clinicians and providing automatic analysis but not specifically as an AI assistance tool in an MRMC context within this summary.

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

• Partially addressed, but not with specific performance metrics. The device is described as "stand-alone software to automatically calculate the 'Standardized Uptake Value Ratio (SUVR)' for quantitative analysis of amyloid PET." This indicates that the core SUVR calculation is standalone. However, the document does not present specific standalone performance metrics (e.g., sensitivity, specificity, accuracy) for this calculation. It merely states that its performance "is as safe and effective as its predicate device."

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

• Cannot be provided. The document does not specify the type of ground truth used for performance evaluation.

8. The sample size for the training set

• Cannot be provided. The document does not mention a training set or its size.

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

• Cannot be provided. No information about a training set or its ground truth establishment is present.

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The Veuron-Brain-pAb is a software for the registration, fusion, display and analysis of medical images from multiple modalities including MRI and PET. The software aids clinician in the assessment and quantification of pathologies from PET Amyloid scans of the human brain. It enables automatic analysis and visualization of amyloid protein concentration through the calculation of standard uptake volume ratios (SUVR) within target regions of interest and comparison to those within the reference regions. The software is deployed via medical imaging workplaces and is organized as a series of workflows which are specific to use with radio-tracer and disease combinations.

The Veuron-Brain-pAb is stand-alone software to automatically calculate the "Standardized Uptake Value Ratio (SUVR)" for quantitative analysis of amyloid PET. The calculated result supports the accuracy of the diagnosis of patients' dementia for the medical professional. It also helps with accurate visual interpretation through visualization functions. Various amyloid PET images can be processed by providing a variety of options for users to choose in the image process.

The provided Presubmission document does not contain the detailed acceptance criteria and study results for the Veuron-Brain-pAb device's performance in the quantitative analysis of amyloid PET scans. The document primarily focuses on demonstrating substantial equivalence to predicate devices based on intended use, design features, and general technological characteristics.

However, based on the information provided, here's what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not provided in the document. The document states "Bench testing is done to show that the system is suitable for its intended use and that the measurement tool performance meets its pre-defined requirements," and that "This did not reveal any issues with the system, demonstrating that the performance of Veuron-Brain-pAb is as safe and effective as its predicate devices." However, specific quantitative acceptance criteria (e.g., accuracy, precision, correlation with ground truth for SUVR values) and the actual numerical performance results against these criteria are not reported.

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

This information is not provided in the document. The document mentions "non-clinical study performance" and "bench testing" but does not specify the sample size of the test set used or the provenance (country of origin, retrospective/prospective) of the data.

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

This information is not provided in the document. The document does not describe how ground truth was established for any performance testing.

4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set

This information is not provided in the document. There is no mention of expert adjudication for ground truth.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

This information is not provided in the document. The document focuses on standalone device performance and substantial equivalence to predicate devices, not on comparative effectiveness with human readers.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, the document implies that standalone performance testing was conducted. It states, "The Veuron-Brain-pAb is stand-alone software to automatically calculate the 'Standardized Uptake Value Ratio (SUVR)' for quantitative analysis of amyloid PET." The "non-clinical study performance" and "bench testing" described would likely refer to the evaluation of this standalone performance. However, specific results beyond the general statement of "no issues" are not presented.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

This information is not provided in the document. Given the device calculates SUVR for amyloid PET, the ground truth would typically involve either:

• Standardized quantitative methods using a reference region for SUVR calculation (which the device aims to automate).
• Correlation with definitive histopathological findings (e.g., brain biopsy/autopsy) or clinical outcomes for amyloid burden.
• Concordance with expert readings or a consensus panel on amyloid positivity/negativity.
  The document does not specify which, if any, of these were used as ground truth for testing.

8. The Sample Size for the Training Set

This information is not provided in the document. The document does not discuss the development or training of the algorithm.

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

This information is not provided in the document, as the training set and its ground truth establishment are not discussed.

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