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PET VCAR (Volume Computer Assisted Reading) is a PET/CT software package which can be used by the clinician to assist in diagnosis, staging, treatment planning and monitoring treatment response. PET VCAR automatically highlights and bookmarks PET defined regions of interest based on user-defined settings. The software can be used for visualization and analytical monitoring of disease progression or response to treatment or therapy using multi exam comparison. The software is designed to measure Standard Uptake Value (SUV) and volume for any PET defined metabolic activity. The software automatically propagates bookmarks from one time point to another for the purpose of improving analysis and workflow, which is designed to allow clinicians to make informed follow-up decisions in an efficient manner. PET VCAR does not provide or claim any automatic detection or automatic diagnosis of abnormal anatomy, structure or function.

PET VCAR (Volume Computer Assisted Reading) is a PET/CT post processing software package which can be used by the trained clinician to assist in diagnosis, staging, treatment planning and monitoring treatment response. PET VCAR automatically highlights and bookmarks PET defined regions of interest based on user defined threshold settings. Bookmarks are any highlighted item including 2D or 3D region of interests and their associated measurements and annotations on the images. The software can be used for visualization and analytical monitoring of disease progression or response to treatment or therapy using multi exam comparison. It is designed to measure PET Standard Uptake Value (SUV) and volume for any PET defined metabolic activity. The software automatically propagates bookmarks from one time point to another for the purpose of improving analysis and workflow. Bookmark propagating is the feature that allows all bookmarks from the baseline exam of the patient to be automatically populated to subsequent exams of the same patient to facilitate the analysis of changes between the exams. PET VCAR offers a tool called Summary Table that compiles and manages all the analytical information in an organized and interactive design. The Summary Table is synchronized with the image display layouts offering quick measurement / image visual validation. PET VCAR's workflow is designed to allow clinicians to make informed follow-up decisions in an efficient manner. PET VCAR does not provide or claim any automatic detection or automatic diagnosis of abnormal anatomy, structure, or function.

Acceptance Criteria and Study for PET VCAR

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the sample size used for the test set. It mentions "bench testing" to evaluate the automatic reference region VOI placement algorithm and "verification on the AW VolumeShare workstation and AW Server platforms" for overall software performance. The data provenance (e.g., country of origin, retrospective/prospective) is not specified.

3. Number of Experts Used to Establish Ground Truth and Their Qualifications

The document does not specify the number of experts used or their qualifications for establishing ground truth for the test set.

4. Adjudication Method for the Test Set

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

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

No multi-reader multi-case (MRMC) comparative effectiveness study is mentioned in the provided text. The document focuses on demonstrating substantial equivalence to a predicate device through software verification and bench testing, rather than comparing human reader performance with and without AI assistance.

6. Standalone Performance Study

Yes, a standalone performance study was conducted in the form of "bench testing" to evaluate the "automatic reference region VOI placement algorithm." The document states that "the algorithm passed the defined acceptance criteria." Additionally, the overall software performance was verified on "AW VolumeShare workstation and AW Server platforms."

7. Type of Ground Truth Used

The type of ground truth used is not explicitly stated. Given the nature of the device (assistive software for image analysis) and the testing described (bench testing for an algorithm, software verification), it likely involved:

• Bench testing for the VOI algorithm: Comparison against a pre-defined "correct" placement based on established anatomical landmarks or manual expert placement.
• Overall software performance: Verification against expected output and functionality, implying internal reference data or pre-defined outcomes for various operations.

8. Sample Size for the Training Set

The document does not provide information about a training set since the study described is focused on verification and validation of the device's performance against pre-defined criteria, rather than training a new algorithm or AI model from scratch.

9. How Ground Truth for the Training Set Was Established

As no training set is mentioned or implied for the studies described, the method for establishing its ground truth is not applicable or provided in the document.

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