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The Scenium display and analysis software has been developed to aid the Clinician in the assessment and quantification of pathologies taken from PET and SPECT scans.

The software is deployed via medical imaging workplaces and is organized as a series of workflows which are specific to use with particular drug and disease combinations.

The software aids in the assessment of human brain scans enabling automated analysis through quantification of mean pixel values located within standard regions of interest. It facilitates comparison with existing scans derived from FDG-PET, amyloid-PET, and SPECT studies, calculation of uptake ratios between regions of interest, and subtraction between two functional scans.

Scenium VD10 display and analysis software enables visualization and appropriate rendering of multimodality data, providing a number of features which enable the user to process acquired image data.

Scenium VD10 consists of three workflows:

• Database Comparison
• Ratio Analysis
• Subtraction

These workflows are used to assist the clinician with the visual evaluation, assessment and quantification of pathologies with different imaging agents, such as using Amyloid imaging agents for dementia and Alzheimer's Disease, DaTSCAN(1-123) for Parkinson's Disease and FDG-PET for epileptic seizures.

The modifications made to the Scenium VD10 software (K133654) to create the Scenium VD20 software include:

• Customized databases can now be imported and exported in the Database Comparison workflow.
• Three new FDG databases normalized to the region of the cerebellum, in addition to whole brain, were added to the Database Comparison workflow.
• Deformable Registration for Amyloid PET has been integrated in the Ratio Analysis workflow with a different algorithm.
• Launch performance decreased the time taken to display patient data in the Ratio Analysis workflow.

This change is based on current commercially available software features and does not change the technological characteristics of the device.

Scenium VD20 Analysis software is intended to be run on commercially available software platforms such as the Siemens syngo.MI Workflow software platform (K133644) or commercially available Siemens scanners (e.g. symbia Intevo (K142006), Biograph mCT (K123737).

This document is a 510(k) premarket notification for the Scenium VD20 software. It claims substantial equivalence to the previously cleared Scenium VD10 software (K133654). The provided text does not include a detailed study proving the device meets specific acceptance criteria with reported performance metrics, expert qualifications, or detailed study methodologies. Instead, it focuses on demonstrating that the modifications introduced in Scenium VD20 do not alter the fundamental technological characteristics or indications for use compared to the predicate device, and thus do not raise new safety and effectiveness concerns.

Therefore, many of the requested details about acceptance criteria and a specific study are not present in this regulatory document.

However, based on the information provided, we can infer some aspects and highlight what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states: "All testing has met the predetermined acceptance values." This is a general statement and does not provide specific quantitative acceptance criteria or reported performance values.

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

• Sample Size for Test Set: Not specified. The document mentions "Verification and Validation activities" and "All testing," but does not detail the size of the dataset used for these tests.
• Data Provenance: Not specified. There is no mention of the country of origin of the data or whether it was retrospective or prospective.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The document focuses on software changes and their implications, not on clinical validation involving human readers or expert consensus on a test set.

4. Adjudication Method:

• Not specified. Since details about expert review or test sets are missing, an adjudication method is also not mentioned.

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

• No, an MRMC comparative effectiveness study is not mentioned or described. The documentation focuses on demonstrating substantial equivalence based on technical modifications and internal verification/validation, not on comparing human reader performance with and without AI assistance for the new features.

6. Standalone (Algorithm Only) Performance Study:

• No specific standalone performance study with detailed metrics (e.g., sensitivity, specificity, accuracy) is presented in this document. The verification and validation activities likely included internal testing of the algorithms, but explicit results demonstrating standalone performance are absent. The device itself is described as "display and analysis software" intended to "aid the Clinician," implying it is a tool for human-in-the-loop use rather than a fully autonomous diagnostic algorithm.

7. Type of Ground Truth Used:

• Not specified. Given the focus on software modifications and features, the "ground truth" for the verification and validation tests would likely relate to the expected outputs of the algorithms, internal consistency, and comparison with previous versions, rather than a clinical ground truth like pathology or long-term outcomes data.

8. Sample Size for the Training Set:

• Not applicable / Not specified. This device is described as "display and analysis software" and the modifications are primarily related to database functionalities, workflow integration, and an algorithmic change for deformable registration. There is no indication that this update involved a machine learning model that required a specific "training set" in the conventional sense of deep learning or AI model development. The "new FDG databases" are likely pre-computed reference datasets, not training data for a learning algorithm within Scenium VD20 itself.

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

• Not applicable / Not specified. As there's no mention of a traditional training set for a new machine learning algorithm, there's no information on how a ground truth for such a set would have been established.

Summary of what the document focuses on instead:

The document primarily provides evidence for substantial equivalence to a predicate device (Scenium VD10, K133654) by stating that:

• The modifications (customized database import/export, new FDG databases, deformable registration algorithm change, improved launch performance) do not change the technological characteristics of the device.
• There are no differences in the Indications for Use.
• No new issues of safety and effectiveness are raised by the modifications.
• Risk Management (ISO 14971:2012) and adherence to industry standards (ISO 13485, IEC 62304) were followed.
• Verification and Validation activities were successfully performed, and "All testing has met the predetermined acceptance values." This last point is the closest to an "acceptance criterion" statement, though it lacks specificity.

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