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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;

• 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.

• use non-contrasted CT images and calculate subcutaneous fat and visceral fat areas in 2D and both volumes in 3D.

• 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

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.

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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;

• use non-contrast and contrast enhanced computed tomographic images of the lung, provide custom workflows and UI, and reporting 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.
• 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 (V3.0) is the updated version of previously-cleared Synapse 3D Lung and Abdomen Analysis software (cleared by CDRH via K103720 on 03/16/2011).

Synapse 3D Lung and Abdomen Analysis is used in addition to Synapse 3D Base Tools (K120361, cleared on April 6, 2012) 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. This product is not intended for use with or for the primary diagnostic interpretation of mammography images.

Synapse 3D Lung and Abdomen Analysis (V3.0) is an application that performs the CT Jung analysis/airway and abdomen 2D and 3D fat analysis.

• Lung analysis/Airway .
  Lung analysis/Airway is an application using non-contrast and contrast enhanced computed tomographic images of the lung which provides custom workflows and UI, and reporting functions 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,

• 2D Fat Analysis (Unchanged from the cleared version K103720) . 2D Fat Analysis is an application which can use single slice (2-dimensional) noncontrasted CT images to calculate subcutaneous fat and visceral fat areas.

• 3D Fat Analysis (Unchanged from the cleared version K103720) . 3D Fat Analysis is an application which can use volume (3-dimensional) non-contrasted CT images to calculate subcutaneous fat and visceral fat areas and volumes.

The following common image processing functions are available to support the analysis of the lung and abdomen CT images. These functions belong to and are provided by Synapse 3D Base Tools (K120361) that is used with Synapse 3D Lung and Abdomen Analysis (V3.0).

• Window width and window level. .
• Zooming, panning, flip, rotate. .
• Measurement of lengths, areas, etc. .
• Adding annotations on an image. .
• Extraction and Deletion of 3D objects: Editing of mask areas using the smart out feature. .
• 3D clipping: The display area can be specified for 3D display. .
• Creation of video files: Video files with 2D or 3D display can be created. .

The provided text describes the acceptance criteria and the study conducted for the Synapse 3D Lung and Abdomen Analysis (V3.0) device, specifically for its new lung volume analysis feature (approximation of air supply region).

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Simulated Test: "a simulated image data set for air supply region approximation with known air supply volume for each bronchus." (Specific number of cases or volumes not given, but implies a designed set.)
• Real Human Body CT Image Test: "five lung CT image data sets of real human body."
• Data Provenance: Not explicitly stated for either test in terms of country of origin or whether it was retrospective or prospective. The term "real human body" suggests clinical data.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

• Simulated Test: Ground truth was established by "known air supply volume for each bronchus," implying a computational or theoretical basis rather than expert consensus on images. Experts were not used to establish this ground truth.
• Real Human Body CT Image Test: The ground truth for the "reference volumes of five pulmonary lobes for each test data set" was established manually "using the validated segmentation tools." The number of experts is not specified, nor are their particular qualifications (e.g., radiologist with X years of experience). The phrasing "manually using the validated segmentation tools" suggests a skilled user performing the segmentation, rather than a multidisciplinary expert panel.

4. Adjudication Method for the Test Set

• The document implies that the "validated segmentation tools" were used to establish the reference volumes for the real human body CT images. No formal adjudication method like "2+1" or "3+1" is described. The simulated test had "known values," so no adjudication was needed.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No MRMC comparative effectiveness study is mentioned for the new lung volume analysis feature. The testing described focuses on the accuracy of the algorithm's measurements against defined ground truths.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• Yes, the studies described are essentially standalone performance evaluations of the algorithm for the new lung volume analysis feature. In the "Test using lung CT image data sets of real human body," the device's output (air supply region approximation) is compared against "reference volumes" established prior to or independently of the device's main function being tested. The user's role is primarily to specify the root of each bronchus, which is an input for the algorithm, but the calculation and approximation itself are done by the device.

7. Type of Ground Truth Used

• Simulated Test: "Known air supply volume" (presumably computationally derived or theoretically defined).
• Real Human Body CT Image Test: Expert consensus via "manual... segmentation and volume calculation using validated segmentation tools" for pulmonary lobes. This serves as a reference standard for comparison with the device's approximation of air supply regions.

8. Sample Size for the Training Set

• The document does not provide information on the sample size used for the training set for the lung volume analysis feature. The studies described are verification/validation tests, not details of model training.

9. How the Ground Truth for the Training Set Was Established

• Since the document does not provide information on the training set, it also does not describe how its ground truth was established.

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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:

Study Information:

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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.

7. 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.

8. 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.

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