(105 days)
Synapse 3D Lung and Abdomen Analysis 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 Lung and Abdomen Analysis accepts DICOM compliant medical images acquired from CT.
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 Lung and Abdomen Analysis is intended to;
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use non-contrast and contrast enhanced computed tomographic images of the lung, provide custom workflows and UI, and reporting functions for lung analysis including boundary detection and volume calculation for pulmonary nodules in the lung based on the location specified by the user, segmentation of bronchial tubes in the lung, approximation of air supply region by the user specified bronchial tube, identifying, displaying and processing low absorption regions in the lung.
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use non-contrasted CT images and calculate subcutaneous fat and visceral fat areas in 2D and both volumes in 3D.
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analyze a bronchus path to reach a lung nodule using the volume data collected with CT, and simulate insertion of bronchoscope into the path.
Synapse 3D Lung and Abdomen Analysis is the updated version of previously - cleared Synapse 3D Lung and Abdomen Analysis software (cleared by CDRH via K120648 on 06/14/2012).
Synapse 3D Lung and Abdomen Analysis is used in addition to Synapse 3D Base Tools (K120361) to analyze the images acquired from CT. Synapse 3D Lung and Abdomen Analysis is intended to provide trained medical professionals with tools to aid them in reading, interpreting, reporting, and treatment planning of DICOM compliant medical images. Synapse 3D Lung and Abdomen Analysis is an application that performs the CT lung analysis/airway, lung analysis scope, and abdomen 2D and 3D fat analysis.
Here's an analysis of the provided text regarding the Synapse 3D Lung and Abdomen Analysis device, focusing on acceptance criteria and study details:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| System level functionality test pass | All tests successfully passed |
| Segmentation accuracy test pass | All tests successfully passed |
| Measurement accuracy test pass | All tests successfully passed |
| Interfacing test pass | All tests successfully passed |
| Usability test pass | All tests successfully passed |
| Serviceability test pass | All tests successfully passed |
| Labeling test pass | All tests successfully passed |
| Risk mitigation method test pass | All tests successfully passed |
| Bench performance using actual clinical images demonstrated expected accuracy | All tests successfully passed |
2. Sample Size Used for the Test Set and Data Provenance
The document states: "we conducted the bench performance testing using actual clinical images". However, it does not specify the sample size for the test set or the data provenance (e.g., country of origin, retrospective or prospective nature of the "clinical images").
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts
The document does not specify the number of experts used or their qualifications to establish ground truth for the test set.
4. Adjudication Method for the Test Set
The document does not specify any adjudication method for the test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
A multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or described in the provided text. The submission focuses on device performance studies against defined criteria rather than comparative effectiveness with human readers.
6. Standalone Performance Study
Yes, a standalone performance study was done. 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 device was tested on its own to meet set criteria.
7. Type of Ground Truth Used
The document implies that the ground truth for "segmentation accuracy" and "measurement accuracy" was based on some form of pre-established "requirements" and "expected accuracy performance" but does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data, etc.) for the clinical images. It only mentions that "Pass/Fail criteria were based on the requirements and intended use of the product."
8. Sample Size for the Training Set
The document does not provide any information regarding the sample size used for the training set.
9. How the Ground Truth for the Training Set Was Established
The document does not provide any information on how the ground truth for the training set (or if a training set was even used, though implied for such a device) 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).