(86 days)
Synapse 3D Tensor Analysis is medical imaging software used with Synapse 3D Base Tools to accept, display, and process DICOM compliant 2D and 3D medical images acquired from MR for the purpose of viewing of local water diffusion properties and directional dependence of the diffusion in the white matter. It is intended to be used by trained medical professionals in reading, interpreting, reporting, screening and treatment planning.
Addition to the general 2D and 3D image processing and measurement tools available in Synapse 3D Base Tools, Synapse 3D Tensor Analysis provides custom workflows, UI, and reporting functions for tensor analysis with neck and head MR images. It includes display of diffusion and FA color map images, white matter tractography, dynamic review in MR, vessel and body visualization with registration of MR, CT, XA, PET and NM.
Synapse 3D Tensor Analysis is an optional software module that works with Synapse 3D Base Tools, cleared by CDRH via K120361 on 04/06/2012. Synapse 3D Tensor Analysis, Synapse 3D Base Tools and other optional software modules consist of the Synapse 3D product family.
Synapse 3D is medical application software running on a Standalone PC or Windows server/client configuration installed on a commercial general-purpose Windows-compatible computer. It offers provides custom workflows, UI, and reporting functions for trained medical professionals to aid them in reading, interpreting, reporting, screening and treatment planning.
Synapse 3D Tensor Analysis supports the display of diffusion and Fractional anisotropy (FA) colormap images, white matter tractography, dynamic review, vessel and body visualization with registration of MR, CT, XA, PET and NM. Tensor Analysis tool enables tensor analysis from diffusion-weighted MR images and tractography-based extraction and observation of local water diffusion properties and directional dependence of the diffusion in the white matter. Additional images (mainly CT images) can be loaded, and skin, bone, brain parenchyma, tumor, and cerebral vessels can be extracted in craniotomy simulations.
The main functions are shown below.
- Display FA and diffusion colormap images
- Extract and observe white matter
- Calculate FA value, number of fibers, area, and volume in the specified ROI
- Simultaneous display of white matter and skin, bone, brain parenchyma, tumor, artery, vein, and other reqions
- Craniotomy simulations involving cutting of skin and bone regions, brain surface clipping by depth, and tumor plane clipping
The provided text is a 510(k) summary for the FUJIFILM Medical Systems U.S.A., Inc.'s Synapse 3D Tensor Analysis device. It details the device's intended use and claims substantial equivalence to predicate devices. However, the document does not include quantitative acceptance criteria or detailed study results that prove the device meets specific performance thresholds.
Here's a breakdown of what is and is not present, based on your requested information:
1. Table of Acceptance Criteria and Reported Device Performance:
This information is not provided in the document. The document states:
- "Pass/Fail criteria were based on the requirements and intended use of the product."
- "Test results showed that all tests successfully passed."
- "a comparative performance testing was conducted between the Synapse 3D Tensor Analysis and the predicate device, and the comparison test result supported the substantial equivalence of the devices' performance characteristics."
However, no specific numerical acceptance criteria (e.g., minimum accuracy, sensitivity, specificity, or error rates) are listed, nor are the actual performance metrics (e.g., specific accuracy percentages, mean differences) from the tests.
2. Sample Size Used for the Test Set and Data Provenance:
This information is not explicitly provided in the document. The text mentions "actual clinical images" were used for bench performance testing but does not specify the number of images, cases, or their origin (country, retrospective/prospective).
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 general statement about testing implies that the results were evaluated against some standard, but it doesn't specify if expert consensus was used to establish ground truth for the test set or the qualifications of such experts if they were involved.
4. Adjudication Method:
This information is not provided.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size:
This information is not provided. The document mentions "comparative performance testing was conducted between the Synapse 3D Tensor Analysis and the predicate device," but it does not specify if this was an MRMC study or if it involved human readers. Therefore, an effect size of human improvement with AI assistance cannot be determined from this document.
6. If a Standalone Study Was Done:
Yes, a standalone performance assessment was conducted for the Synapse 3D Tensor Analysis software. The document states:
- "Testing involved system level functionality test, segmentation accuracy test, measurement accuracy test, interfacing test, usability test, serviceability test, labeling test, as well as the test for risk mitigation method analyzed and implemented in the risk management process."
- "In addition, we conducted the bench performance testing using actual clinical images to help demonstrate that the proposed device achieved the expected accuracy performance."
This indicates that the software's performance was evaluated on its own.
7. The Type of Ground Truth Used:
The type of ground truth used is not explicitly stated. However, given the nature of the device (medical imaging software for viewing water diffusion properties and tractography), potential ground truth sources could include expert consensus, follow-up imaging, or correlation with clinical outcomes, but the document does not confirm this. The phrase "expected accuracy performance" suggests a comparison to some established accurate output, but the source of that accuracy (ground truth) is not specified.
8. The Sample Size for the Training Set:
This information is not provided. The document describes testing and validation activities but does not mention the training of an algorithm or the size of a training set. This is consistent with a device that provides visualization and processing tools rather than an AI/ML algorithm that requires a training set.
9. How the Ground Truth for the Training Set Was Established:
As no training set is mentioned for an AI/ML algorithm, this information is not applicable/provided. The device is described as "medical imaging software used with Synapse 3D Base Tools to accept, display, and process DICOM compliant 2D and 3D medical images," implying a tool for visualization and analysis rather than an autonomous diagnostic AI.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).