(85 days)
Synapse 3D Lung and Abdomen Analysis is medical imaging software used with Synapse 3D Basic 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 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 Basic Tools, Synapse 3D Lung and Abdomen Analysis is intended to;
- use non-contrasted and contrast enhanced computed tomographic images of the lung, perform boundary detection and volume calculation for pulmonary nodes in the lung based on the location specified by the user and display low absorption areas.
- use non-contrasted CT images and calculate subcutaneous fat and visceral fat areas in 2D and both volumes in 3D.
Synapse 3D Lung and Abdomen Analysis is an application that can perform volume calculation for pulmonary nodes, display of low absorption areas, and other analysis for Lung contrasted and non-contrasted CT volume date. In addition, the application can calculate the area and volume (3D) of subcutaneous fat and visceral fat using abdomen CT images. The result can be displayed as a graph, and the fat quantity at each slice position can be presented.
Synapse 3D Lung and Abdomen Analysis is used in addition to the previously-cleared features available from Synapse 3D Basic Tools (K101662) to analyze the images acquired from CT. Synapse 3D Lung and Abdomen Analysis is intended to provide trained medical imaging professionals, including Physicians and Radiologists, with tools to aid them in reading, interpreting, reporting, and treatment planning and accepts DICOM compliant medical images.
Synapse 3D Lung and Abdomen Analysis with Synapse 3D Basic 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 Lung and Abdomen Analysis also can be integrated with Fujifilm's Synapse Cardiovascular for cardiology purposes.
This product is not intended for use with or for the primary diagnostic interpretation of Mammography images.
Here's an analysis of the provided text regarding the acceptance criteria and study for the Synapse 3D Lung and Abdomen Analysis device:
Acceptance Criteria and Reported Device Performance
The provided 510(k) summary does not explicitly state specific quantitative acceptance criteria or numerical reported device performance in a table format. It focuses on the general statement that "All planned verification and validation tests for Synapse 3D Lung and Abdomen Analysis have passed and the design validation has been successfully completed."
However, based on the device's intended use, we can infer the functional performance aspects that would have been tested:
| Acceptance Criteria (Inferred) | Reported Device Performance (General) |
|---|---|
| Accurate boundary detection of pulmonary nodes. | All planned verification and validation tests passed. |
| Accurate volume calculation for pulmonary nodes. | All planned verification and validation tests passed. |
| Correct display of low absorption areas in the lung. | All planned verification and validation tests passed. |
| Accurate calculation of subcutaneous fat area (2D). | All planned verification and validation tests passed. |
| Accurate calculation of visceral fat area (2D). | All planned verification and validation tests passed. |
| Accurate calculation of subcutaneous fat volume (3D). | All planned verification and validation tests passed. |
| Accurate calculation of visceral fat volume (3D). | All planned verification and validation tests passed. |
| Proper display of fat quantity at each slice position. | All planned verification and validation tests passed. |
| Compatibility with DICOM-compliant CT images. | Verification and validation tests indicate compatibility. |
| Integration with Synapse 3D Basic Tools, Synapse Workstation, and Synapse Cardiovascular. | Verification and validation tests confirm integration. |
| No new safety or efficacy issues compared to predicate devices. | Hazard Analysis combined with preventive measures indicates moderate concern, device is substantially equivalent to predicates. |
Study Information:
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Sample size used for the test set and the data provenance:
- Sample Size: The document does not specify the sample size used for the test set (verification and validation testing).
- Data Provenance: The document does not specify the country of origin or whether the data was retrospective or prospective.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- The document does not provide information on the number of experts or their qualifications used to establish ground truth for the test set.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- The document does not describe any adjudication method used for the test set.
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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:
- The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study or any effect size related to human reader improvement with AI assistance. The device is described as "tools to aid them in reading, interpreting, reporting, and treatment planning," implying an assistative role rather than a standalone AI for primary diagnosis that would typically necessitate such a study.
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- The document does not explicitly state that a standalone (algorithm only) performance study was conducted. The description emphasizes the device providing "tools to aid" medical professionals, suggesting it's intended for use with human interpretation rather than as a fully autonomous diagnostic tool.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- The document does not specify the type of ground truth used for its verification and validation testing. Given the functions (volume calculation, boundary detection, fat measurement), it's highly likely that a form of expert consensus or highly accurate manual measurements by trained professionals on the CT images themselves would have served as ground truth.
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The sample size for the training set:
- The document does not provide information on the sample size used for the training set. This is a 510(k) for a medical image processing and analysis software, not typically a machine learning-based device where a training set is a central component of the submission. While such software may use algorithms developed with training data, the 510(k) summary focuses on the validation of the final product.
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How the ground truth for the training set was established:
- Since information about a training set or its sample size is not provided, the method for establishing its ground truth is also not described.
§ 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).