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Synapse 3D Brain Perfusion is medical imaging software used with Synapse 3D Base Tools that is intended to provide trained medical professionals with tools to aid them in reading, interpreting, reporting, and treatment planning. Synapse 3D Brain Perfusion accepts DICOM compliant medical images acquired from CT and MR.

This product is not intended for use with or for the primary diagnostic interpretation of Mammography images.

Addition to Synapse 3D Base Tools, Synapse 3D Brain Perfusion provides the parameter images by post-processing with dynamic scanned CT cerebral arteriography images and magnetic resonance images (MR) with contrast agent to aid the assessment of cerebral blood flow. The parameter images are Cerebral Blood Volume (CBV), Cerebral Blood Flow (CBF), Mean Transit Time (MTT), and Time To Peak (TTP).

Synapse 3D Brain Perfusion (V3.0) is the updated version of previously-cleared Synapse 3D Cerebral Analysis software (cleared by CDRH via K103687 on 03/04/2011).

Synapse 3D Brain Perfusion is used in addition to Synapse 3D Base Tools (K120361, cleared on April 6, 2012) to analyze the images acquired from CT and MR. Synapse 3D Brain Perfusion is intended to provide trained medical professionals with tools to aid them in reading, interpreting, reporting, and treatment planning of DICOM compliant medical images. This product is not intended for use with or for the primary diagnostic interpretation of mammography images.

Synapse 3D Cerebral Analysis (V3.0) is an application that analyzes the changes of the cerebral blood flow on the dynamic scanned CT cerebral arteriography and the MR images.

• Brain Perfusion (CT): Unchanged from the cleared version K103687 . Brain Perfusion is an application analyzing the changes of the cerebral blood flow on the dynamic scanned CT cerebral arteriography images. CBV (Cerebral Blood Volume), CBF (Cerebral Blood Flow), MTT (Mean Transit Time), and TTP (Time To Peak) are calculated and mapped on images.
  · Brain Perfusion (MR):

Brain Perfusion is an application analyzing the changes of the cerebral blood flow on the magnetic resonance images (MR) with contrast agent. CBV (Cerebral Blood Volume), CBF (Cerebral Blood Flow), MTT (Mean Transit Time), and TTP (Time To Peak) are calculated and mapped on images.

Common image processing functions (such as window width and window level, zooming, panning, flip, rotate, adding annotations on an image, measurement of lengths, areas, etc.),are available to support the cerebral analysis of the CT and MR images. These functions belong to and are provided by Synapse 3D Base Tools (K120361) that is used with Synapse 3D Brain Perfusion (V3.0) (this submission).

The Brain Perfusion (CT) application is unchanged from the cleared version (K103465) and the Brain Perfusion (MR) is the added application.

Synapse 3D Brain Perfusion with Synapse 3D Basic/Base Tools can be integrated with our cleared Fujifilm's Synapse Workstation, version 3.2.1 and above, and can be used as a part of a Synapse system. Synapse 3D Brain Perfusion also can be integrated with Fujifilm's Synapse Cardiovascular for cardiology purposes.

The provided text does not contain detailed information about specific acceptance criteria or the study that definitively proves the device meets those criteria in a quantitative, performance-based manner (e.g., sensitivity, specificity, accuracy).

Instead, the submission focuses on substantial equivalence to predicate devices. The "Testing" section mentions the device was "tested successfully with reference to its Software Requirements Specification, as well as design verification and validation documents and Traceability Matrix document." It concludes that "Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the Synapse 3D Brain Perfusion software, which is found to be safe and effective and substantially equivalent to the currently-cleared predicate device."

This implies that the acceptance criteria are likely related to:

• Functional correctness: The software performs the calculations (CBV, CBF, MTT, TTP) as designed and produces parameter maps.
• Reliability: The software consistently produces these results.
• Performance: The output is comparable to, or within acceptable limits of, the predicate devices.
• Compatibility: It integrates correctly with Synapse 3D Base Tools and other Fujifilm systems.
• Safety: No new safety or efficacy issues compared to predicates.

However, the specific quantitative metrics for these criteria (e.g., "CBV values must be within X% of a reference standard") are not provided in this document.

Therefore, many of the requested details about the study that proves the device meets acceptance criteria cannot be extracted directly from this 510(k) summary.

Here's a breakdown of what can be inferred or explicitly stated based on the provided text, with "N/A" where information is not available:

1. Table of Acceptance Criteria and Reported Device Performance

• Calculates and maps CBV, CBF, MTT, and TTP from MR images with contrast agent (new addition).
• Common image processing functions (window/level, zoom, pan, etc.) are available via Synapse 3D Base Tools. |
  | Reliability | - "Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics..." |
  | Compatibility/Integration | - Works with Synapse 3D Base Tools (K120361).
• Integrates with Fujifilm's Synapse Workstation, version 3.2.1 and above.
• Can integrate with Fujifilm's Synapse Cardiovascular. |
  | Safety and Efficacy (Substantial Equivalence) | - "Introduces no new safety or efficacy issues other than those already identified with the predicate devices."
• "Found to be safe and effective and substantially equivalent to the currently-cleared predicate device." |
  | Software Requirements Conformance | - "Tested successfully with reference to its Software Requirements Specification, as well as design verification and validation documents and Traceability Matrix document." |
  | Quantitative Performance Metrics (e.g., accuracy of CBF, CBV) | N/A (Specific quantitative metrics for acceptance and results are not detailed in this document. The focus is on demonstrating substantial equivalence to predicates for these types of calculations, which implies similar performance.) |

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

• Sample Size: N/A (Not specified in the document).
• Data Provenance: N/A (Not specified in the document if clinical data was used for testing beyond internal software validation. It mentions "dynamic scanned CT cerebral arteriography images" and "MR images with contrast agent" but not their source or specifics).

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)

• Number of Experts: N/A (Not specified. The document primarily describes software testing and comparison to predicate functionality, not a clinical study involving experts for ground truth establishment).
• Qualifications of Experts: N/A (Not specified).

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

• Adjudication Method: N/A (Not applicable, as no external expert review or adjudication process for establishing ground truth on a test set is mentioned).

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

• MRMC Study: No, an MRMC comparative effectiveness study is not mentioned. This submission is for a medical image processing and analysis software that provides diagnostic aids, not an AI-assisted diagnostic tool in the sense of directly improving human reader performance quantified by an effect size. The device calculates parameters (CBV, CBF, MTT, TTP); it doesn't offer AI assistance in interpretation.
• Effect Size: N/A (Not applicable, as no such study was performed or reported).

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

• Standalone Performance: Yes, in essence, the "performance, functionality, and reliability characteristics" of the software itself (Synapse 3D Brain Perfusion) were established through "design verification and validation documents and Traceability Matrix document." The results of its calculations (CBV, CBF, MTT, TTP) are its standalone performance. The document states it was "tested successfully with reference to its Software Requirements Specification," indicating that the algorithm's output was verified against its design. However, specific metrics (like accuracy against a gold standard) for these calculations are not provided in this summary.

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

• Type of Ground Truth: The document implies that the ground truth for validating the software's calculations would be based on engineering specifications and established algorithms for calculating cerebral perfusion parameters. For the new MR functionality, it would likely have been validated against:
  • Mathematical/Computational correctness: Ensuring the algorithms correctly implement the physical models for perfusion.
  • Comparison to existing methods/software: For the new MR capabilities, it would likely have been compared against outputs from similar, already validated algorithms or systems (potentially the predicate IB Neuro v1.0, though the text states IB Neuro is a predicate generally, not specifically for MR perfusion calculations).
  • No mention of expert consensus, pathology, or outcomes data as direct ground truth for algorithm validation.

8. The sample size for the training set

• Sample Size for Training Set: N/A (Not applicable, as this is not an AI/machine learning device that requires a "training set" in the typical sense. It's an algorithm-based image processing software. The development of the algorithms would be based on scientific and medical principles, not machine learning training data.)

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

• Ground Truth for Training Set: N/A (Not applicable for the same reasons as #8. The algorithms are based on established biophysical models for cerebral perfusion, not learned from a training set with established ground truth labels.)

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