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AneurysmFlow assists during endovascular procedures for treating of saccular cerebral aneurysms, by:

· Visualization of blood flow patterns in the aneurysm and parent vessel, based on digital subtraction angiography.

· Quantification of the blood flow in the aneurysm parent vessel, based on digital subtraction angiography and 3D rotational angiography.

· Comparison of blood flow, both visual and quantified between two acquisitions.

AneurysmFlow is a software tool intended to provide relevant information on the blood flow in a cerebral aneurysm and its parent artery based on angiography. AneurysmFlow is a software medical device and is intended to be used in combination with the currently marketed Philips interventional X-ray system and 3D volume data from 3D Rotational Angiography. AneurysmFlow is a software product (Interventional Tool) that provides color coded and vector field representation of a digital subtraction angiography (DSA). It can quantify blood flow rates in the artery based on DSA and 3D-RA data. It can visualize blood flow patterns in an aneurysm based on DSA data. It can also provide a side by side visual and quantitative comparison between two acquisitions.

The provided document, a 510(k) summary for the AneurysmFlow device, states that clinical studies were not required to demonstrate substantial equivalence. Instead, it relies on non-clinical performance data and a comparison to a predicate device.

Therefore, many of the requested details about a study proving acceptance criteria (like sample size for test set, number of experts, adjudication method, MRMC study, ground truth for test set, etc.) are not available in this document because a dedicated clinical study for these metrics was not performed or submitted.

However, I can extract information related to the acceptance criteria as described for the non-clinical tests and the approach to demonstrating safety and effectiveness.

Here's a summary of the available information based on your request:

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

The document does not provide a specific table of acceptance criteria with numerical performance targets and reported results. Instead, it refers to general compliance and successful completion of various tests.

• IEC 62304 (Medical device software - Software life cycle processes)
• IEC 62366-1 (Medical devices - Application of usability engineering to medical devices)
• ISO 14971 (Medical devices - Application of risk management to medical devices)
• NEMA PS 3.1-3.20 (DICOM Set)
• FDA Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" |
  | Consistency with Raw Data (Limited "Clinical" Review) | Sample clinical images of one case accompanied by signed statements from three board-certified neuroradiologists were provided to demonstrate that after completing all worksteps, the presented data are consistent with the raw data (X-ray angiogram). (This is a very limited "validation" step rather than a full clinical study). |

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

• Sample Size for Test Set: Not applicable as a formal clinical "test set" to evaluate diagnostic performance against ground truth was not described in this document for the purpose of a clinical study.
  • For the limited "clinical" review, one case with sample clinical images was used.
• Data Provenance: Not specified for the software/algorithm verification and validation. For the one case of clinical images, the country of origin is not mentioned, and it is implied to be retrospective as it's presented as "sample clinical images."

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

• Number of Experts: Three
• Qualifications of Experts: Board-certified neuroradiologists.

4. Adjudication method for the test set

• Adjudication Method: Not explicitly stated as a formal adjudication method. The document mentions "signed statements from three board certified neuroradiologists were provided to demonstrate that... the presented data are consistent with the raw data." This suggests an expert consensus or agreement on consistency, but not a specific method for resolving discrepancies (e.g., 2+1, 3+1).

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, an MRMC comparative effectiveness study was NOT done. The document explicitly states that "AneurysmFlow did not require clinical studies." These types of studies are typically part of clinical trials.

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

• Yes, in spirit. The "Algorithm verification testing" falls under this category, as it verifies the algorithm's accuracy against its specifications, independent of human interaction. The non-clinical software validation also covers aspects of the device's performance in isolation from a clinical setting, ensuring it meets its intended use and user needs.

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

• For algorithm verification: "accuracy of the algorithm" against its "specifications" – this implies a computational or engineering ground truth based on defined parameters and expected outputs.
• For the limited "clinical" review: The ground truth was based on the "raw data (X-ray angiogram)" as assessed by the expert consensus of three board-certified neuroradiologists for consistency with the presented data.

8. The sample size for the training set

• Not provided. This document is a 510(k) summary, which focuses on demonstrating substantial equivalence, not the details of algorithm development (like training set size).

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

• Not provided. As the training set size is not mentioned, neither is the method for establishing its ground truth.

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