(84 days)
Synapse 3D Liver and Kidney Analysis is medical imaging software used with Synapse 3D Base Tools that is intended to provide trained medical imaging professionals, including Physicians and Radiologists, with tools to aid them in reading, interpreting, reporting, and treatment planning. Synapse 3D Liver and Kidney Analysis accepts DICOM compliant medical images. 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 Liver and Kidney Analysis uses contrast enhanced images of the body and provides custom workflows and UI, and reporting functions for liver and kidney analysis including, liver and peripheral organ segmentation, and tumor segmentation of intrahepatic and peripheral vessels as well as the approximation of vascular territories is provided using contrast enhanced computed tomographic images.
Synapse 3D Liver and Kidney Analysis (V4.0) (this submission) is updated software of previously-cleared Synapse 3D Liver Analysis (cleared by CDRH via K110186 on 04/07, 2011) with expanded IFU and revised device name. The new feature in Synapse 3D Liver and Kidney Analysis (V4.0) are Kidney Analysis (CT) function and Liver Analysis (MR).
Synapse 3D Liver and Kidney Analysis is medical application software running on Windows standalone and server/client configuration installed on a commercial general-purpose Windowscompatible computer. It offers software tools which can be used by trained professionals, such as radiologists, clinicians or general practitioners to interpret medical images obtained from various medical devices, to create reports, or to develop treatment plans.
Synapse 3D Liver and Kidney Analysis is an optional software module that works with Synapse 3D Base Tools (cleared by CDRH via K120361 on 04/06/2012) which is connected through DICOM standard to medical devices such as CT, MR. CR, US, NM, PT, XA, etc. and to a PACS system storing data generated by these medial devices, and it retrieves image data via network communication based on the DICOM standard. The retrieved image data are stored on the local disk managed by Synapse 3D Base Tools, and the associated information of the image data is registered in the database and is used for display, image processing, analysis, etc. Synapse 3D Liver and Kidney Analysis can handle images of CT and MR. The software can display the images on a display monitor, or printed them on a hardcopy using a DICOM printer or a Windows printer.
The liver and kidney analysis tools both segment the organs, peripheral organs and vessels using similar body part recognition algorithms already available in the FDA-cleared Base Tools (K120361) and the Liver Analysis (CT) (K110186). The technical characteristics and principles of operations are described in details in the Device Description section, which includes the Liver Analysis (CT and MR) and Kidney Analysis (CT). Based on the cleared functions, Synapse 3D Liver and Kidney Analysis enhances the custom workflows and UI to improve the usability.
Synapse 3D Liver and Kidney Analysis with Synapse 3D Base Tools can be integrated with Fujifilm's Synapse PACS, and can be used as a part of a Synapse system. Synapse 3D Liver and Kidney Analysis also can be integrated with Fujifilm's Synapse Cardiovascular for cardiology purposes. In summary, this 510(k) submission introduces the Synapse 3D Liver and Kidney Analysis with the added capability of performing Liver (MR) and Kidney (CT) Analysis.
The provided text describes a 510(k) premarket notification for the "Synapse 3D Liver and Kidney Analysis" software. While it states that "Pass/Fail criteria were based on the requirements and intended use of the product. Test results showed that all tests successfully passed," it does not provide specific acceptance criteria values or detailed performance metrics for the device. Therefore, a table of reported device performance against acceptance criteria cannot be generated as the specific criteria and performance values are not given.
However, based on the provided text, here's what can be inferred and stated regarding the study:
1. Table of Acceptance Criteria and Reported Device Performance:
As noted above, the document does not provide specific numerical acceptance criteria or quantitative reported device performance values for metrics like accuracy, sensitivity, or specificity. It broadly states that "Pass/Fail criteria were based on the requirements and intended use of the product. Test results showed that all tests successfully passed."
The testing included:
- System level functionality test
- Segmentation accuracy test
- Measurement accuracy test
- Interfacing test
- Usability test
- Serviceability test
- Labeling test
- Test for risk mitigation method analyzed and implemented in the risk management process
- Bench performance testing using actual clinical images
Without specific numerical cut-offs or reported results for each of these tests, a table with quantitative data cannot be created.
2. Sample Size Used for the Test Set and Data Provenance:
The document mentions "bench performance testing using actual clinical images." However, it does not specify the sample size used for the test set or the provenance of the data (e.g., country of origin, retrospective or prospective nature).
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:
The document does not specify the number of experts used to establish ground truth or their qualifications. It generally states the software is "intended to provide trained medical imaging professionals, including Physicians and Radiologists, with tools to aid them."
4. Adjudication Method for the Test Set:
The document does not describe any adjudication method (e.g., 2+1, 3+1, none) for the test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
The document does not mention or describe a multi-reader multi-case (MRMC) comparative effectiveness study. Therefore, no effect size of human readers improving with AI vs. without AI assistance is provided.
6. Standalone (Algorithm Only) Performance Study:
The document describes the device as "medical imaging software used with Synapse 3D Base Tools that is intended to provide trained medical imaging professionals... with tools to aid them." It implies standalone performance as it is a software that provides segmentation and analysis tools. "Segmentation accuracy test" and "measurement accuracy test" would inherently evaluate the algorithm's performance without direct human interaction for generating the output, although the results are ultimately used by humans. However, it does not explicitly use the term "standalone study" or present results distinctly as such.
7. Type of Ground Truth Used:
The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). Given the nature of "segmentation accuracy test" and "measurement accuracy test," it is highly probable that expert consensus or expert-derived segmentations/measurements were used as ground truth on the clinical images, but this is not explicitly stated.
8. Sample Size for the Training Set:
The document does not provide information on the sample size used for the training set.
9. How the Ground Truth for the Training Set Was Established:
The document does not provide information on how the ground truth for the training set was established.
§ 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).