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The syngo.CT Lung CAD device is a computer-aided detection (CAD) tool designed to assist radiologists in the detection of solid pulmonary nodules during review of multi-detector computed tomography (MDCT) examinations of the chest. The software is an adjunctive tool to alert the radiologist to regions of interest (ROI) that may have been initially overlooked. The syngo. CT Lung CAD device is intended to be used as a second reader after the radiologist has completed his/her initial read.

syngo.CT Lung CAD is a medical device that is designed to perform CAD processing in thoracic CT examinations for the detection of solid pulmonary nodules ≥ 3 mm in size. The device processes images acquired with Siemens multi-detector CT scanners with 4 or more detector rows.

The syngo.CT Lung CAD device supports the full range of nodule locations (central, peripheral) and contours (round, irregular). The detection performance of the syngo.CT Lung CAD device is optimized for nodules between 3 mm and 10 mm in size. Additionally, the syngo.CT Lung CAD device can be used in scans with or without contrast enhancement.

The device receives images via an input data interface, performs CAD processing and provides locations of suspected nodules as an output. Specific visualizations, such as the syngo PET&CT Oncology application (K093621) or equivalent Siemens products, should be used (but are not part of this clearance) to display the CAD marks. The syngo.CT Lung CAD device is intended to be used as a second reader only after the initial read is completed.

The provided document, K143196 for syngo.CT Lung CAD, largely focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study proving performance against explicit acceptance criteria with specific metrics. The document states that "Non-clinical tests were conducted... The modifications described in this Premarket Notification were supported with verification and validation testing." However, it does not explicitly outline a table of acceptance criteria nor the corresponding reported device performance.

Nonetheless, based on the information provided, we can infer some aspects of the performance and the nature of the testing:

1. Table of Acceptance Criteria and the Reported Device Performance

The document does not provide a quantitative table of acceptance criteria or reported device performance metrics like sensitivity, specificity, or false positive rates. It generally states that "The results of these tests support the substantial equivalence of this device" and that "Testing, including standalone performance testing, were conducted to assess the new syngo.CT Lung CAD device and compare it to the predicate device with respect to false positives, sensitivity, and the dismissibility of false positives." This implies that these metrics were assessed and found acceptable for substantial equivalence, but the actual numbers and predefined thresholds are not disclosed.

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

The document does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). It simply refers to "non-clinical tests" and "testing."

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

This information is not provided in the document.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

The document mentions that the device is intended to be used as a "second reader after the radiologist has completed his/her initial read." It also states, "Testing, including standalone performance testing, were conducted to assess the new syngo.CT Lung CAD device and compare it to the predicate device with respect to false positives, sensitivity, and the dismissibility of false positives." However, it does not explicitly describe an MRMC comparative effectiveness study that quantitatively assesses how much human readers improve with AI assistance versus without. The focus seems to be on the performance of the CAD system itself and its equivalence to a prior version.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, a standalone performance test was done. The document explicitly states: "Testing, including standalone performance testing, were conducted to assess the new syngo.CT Lung CAD device and compare it to the predicate device with respect to false positives, sensitivity, and the dismissibility of false positives." This indicates that the algorithm's performance without direct human intervention was evaluated.

7. The 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 context of detecting "solid pulmonary nodules," it is highly likely that the ground truth would have been established by a consensus of expert radiologists or possibly through follow-up imaging or pathology reports where available, but this is not explicitly detailed.

8. The 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 was established.

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syngo.via is a software solution intended to be used for viewing, manipulation, and storage of medical images.

It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options.

syngo via supports interpretation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments.

The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.

Siemens AG intends to market the Picture Archiving and Communications System, syngo.via, software version VB10A. This 510(k) submission describes several modifications to the previously cleared predicate device, syngo.via, software version VA20A.

syngo.via is a software only medical device, which is delivered on DVD to be installed on common IT hardware. This hardware has to fulfil the defined requirements. Any hardware platform that complies to the specified minimum hardware and software requirements and with successful installation verification and validation activities can be supported. The hardware itself is not seen as part of the medical device syngo.via and therefore not in the scope of this 510(k) submission.

syngo.via provides tools and features to cover the radiological tasks reading images and reporting. syngo.via supports DICOM formatted images and objects. syngo.via also supports storage of Structured DICOM Reports. In a comprehensive imaging suite, syngo. via interoperates with a Radiology Information System (RIS) to enable customer specific workflows.

syngo.via is based on a client-server architecture. The server processes and renders the data from the connected modalities. The server provides central services including image processing and temporary storage, and incorporates the local database. The client provides the user interface for interactive image viewing and processing and can be installed and started on each workplace that has a network connection to the server.

The server's backend communication and storage solution is based on Microsoft Windows server operating systems. The client machines are based on Microsoft Windows operating systems.

syngo.via supports various monitor setups and can be adapted to a range of image types by connecting different monitor types.

The subject device and the predicate device share the same fundamental scientific technology. This device description holds true for the subject device, syngo.via, software version VB10A; as well as the predicate device, syngo.via, software version VA20A.

The provided text describes a 510(k) submission for "syngo.via (version VB10A)", a Picture Archiving and Communications System, and its substantial equivalence to a predicate device. However, the document does not contain specific acceptance criteria, reported device performance data, details of a specific study proving it meets acceptance criteria, or information on sample sizes, ground truth establishment, or expert involvement in the way a clinical performance study report would.

The document focuses on:

• Regulatory Clearance: FDA's clearance of the device (K150843) as substantially equivalent to a predicate device (K123920).
• Device Description: General features, software architecture, operating systems, and some high-level feature differences from the predicate.
• Non-clinical Performance Testing: Stating that tests were conducted for verification and validation and that the device conforms to certain standards and cybersecurity requirements.
• Software Verification and Validation: Asserts that software documentation for a "Moderate Level of Concern" software was included, and testing results support that "all the software specifications have met the acceptance criteria."

Therefore, I cannot populate the table or answer most of the questions as the specific details are not present in the provided text.

Here's what can be inferred or explicitly stated based only on the provided text:

1. A table of acceptance criteria and the reported device performance

• Acceptance Criteria/Performance: The document states that "all the software specifications have met the acceptance criteria" through non-clinical verification and validation testing. However, the specific acceptance criteria (e.g., minimum accuracy rates, latency thresholds) and the numerical results for these criteria are not provided.
  The focus is on comparing features and ensuring the new version doesn't introduce new safety risks.

2. Sample size used for the test set and the data provenance

• Sample Size: Not provided. The document refers to "non-clinical tests" and "verification and validation testing" but does not specify sample sizes for any test sets.
• Data Provenance: Not provided. As it's non-clinical testing, it likely refers to internal testing data. No information on country of origin or retrospective/prospective nature is given.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of Experts: Not provided.
• Qualifications of Experts: Not provided.
  Since the document describes non-clinical software verification and validation, it's unlikely external medical experts were used to establish "ground truth" in the clinical sense. The "ground truth" here would likely be defined by internal software requirements and specifications.

4. Adjudication method for the test set

• Adjudication Method: Not provided.

5. 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

• MRMC Study: No. The document describes a "Picture Archiving and Communications System," which is a viewing and manipulation software, not an AI-powered diagnostic aide in the traditional sense that would warrant an MRMC study comparing human reader performance with and without AI assistance. This submission focuses on software updates and substantial equivalence, not a clinical efficacy claim for a new AI algorithm.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Standalone Performance: The device itself is a "software only medical device" which is intended for "viewing, manipulation, communication, and storage of medical images" and "supports interpretation and evaluation of examinations within healthcare institutions." While the software performs functions independently, the context of "standalone performance" often refers to the diagnostic accuracy of an AI algorithm without human intervention for making diagnoses. This document does not claim diagnostic capabilities for the software itself, but rather tools to aid human interpretation. Thus, a standalone diagnostic performance study (in the context of an AI algorithm making a diagnosis) was not done/relevant given the stated intended use.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• Type of Ground Truth: The document refers to "software specifications" and "hazard analysis." For non-clinical software testing, the "ground truth" would be the expected behavior and output defined by the software's functional and performance requirements. This is not clinical ground truth like pathology or expert consensus on patient cases.

8. The sample size for the training set

• Training Set Sample Size: Not applicable/Not provided. This document describes a traditional software system, not a machine learning or AI algorithm that requires a "training set" in the common sense.

9. How the ground truth for the training set was established

• Training Set Ground Truth Establishment: Not applicable/Not provided. As above, this is not a machine learning model requiring a training set with establish ground truth.

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syngo.via WebViewer is a software-only device indicated for reviewing medical images from syngo via. It supports interpretation and evaluations within healtheare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments (supported Image types: CT, MR, CR, DR, DX, PET). It is not intended for storage or distribution of medical images.

syngo.via WebViewer is an option for the syngo.via system and cannot be run without it. It is client server architecture and the client is intended to run on web clients which are connected to the healtheare institution IT infrastructure where the customer will insure HIPAA compliance. The communication of syngo.via WebViewer with connected medical IT systems will be done via standard interfaces such as but not limited to DICOM.

The system is not intended for the display of digital mammography images for diagnosis.

The syngo.via WebViewer is a software-based Picture Archiving and Communications System (PACS) used with the syngo.via system. The syngo.via WebViewer provides secure access to rendered medical image data and basic image manipulation through web browsers and mobile devices within the reach of the hospital network.

It extends the syngo.via WebViewer software application previous cleared under K111079. New image types supported are PET and X-Ray images. It also provides functionality for displaying images via a mobile application on an iPad.

The Siemens syngo.via WebViewer (K130998) is a PACS viewing software. The provided document does not contain acceptance criteria or a study that directly proves the device meets specific performance criteria through metrics like sensitivity, specificity, or accuracy for diagnostic tasks. Instead, the submission focuses on establishing substantial equivalence to a predicate device (syngo.via WebViewer K111079) based on its intended use, technical characteristics, and the results of non-clinical software verification and validation.

1. Table of Acceptance Criteria and Reported Device Performance:

As the device is a PACS viewing software, the acceptance criteria are not typically expressed in terms of diagnostic performance metrics (e.g., sensitivity, specificity) but rather in terms of functional performance, adherence to standards, and safety. The document states that "software verification and validation (Unit Test Level, Integration Test Level and System Test Level) was performed for all newly developed components and the complete system according to the following standards." The table below summarizes the implied acceptance criteria from the non-clinical tests and the device's adherence:

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

The document does not describe a clinical study or a test set of medical images with a specific sample size used to evaluate diagnostic performance. The validation mentioned is "software verification and validation (Unit Test Level, Integration Test Level and System Test Level)", which refers to engineering and software quality assurance testing rather than a clinical performance study using patient data. Therefore, there is no information on sample size or data provenance (e.g., country of origin, retrospective/prospective).

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

This level of detail is not provided as the submission focuses on software validation and substantial equivalence, not a clinical study involving ground truth establishment by experts for diagnostic performance.

4. Adjudication Method for the Test Set:

Not applicable, as no clinical test set for diagnostic performance requiring expert adjudication is described.

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

No MRMC comparative effectiveness study is mentioned or appears to have been performed for this 510(k) submission. The document focuses on showing substantial equivalence to a predicate device rather than demonstrating a performance improvement with or without AI assistance.

6. Standalone Performance Study:

No standalone (algorithm only without human-in-the-loop performance) study is described, as the device is a medical image viewing software, not an AI diagnostic algorithm. The "software-only device" refers to its deployment model, not its functionality as an autonomous diagnostic tool.

7. Type of Ground Truth Used:

Ground truth as understood in the context of diagnostic accuracy studies (e.g., pathology, expert consensus) is not mentioned. The "ground truth" for the software validation activities would be the expected functional behavior and adherence to standards, checked against specified requirements.

8. Sample Size for the Training Set:

Not applicable. The device is a viewing software, not an AI/ML algorithm that requires a training set of data.

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

Not applicable, as no training set is relevant for this type of device.

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syngo.plaza is a Picture Archiving and Communication System intended to display, process, read, report, communicate, distribute, store, and archive digital medical images, including mammographic images. It supports the physician in diagnosis and treatment planning. For primary image diagnosis in Mammography only uncompressed or non-lossy compressed images and only preprocessed DICOM "For Presentation" images must be used. Also monitors (displays) and printers which received FDA clearance for Mammography must be used. syngo.plaza also supports DICOM Structured Reports. In a comprehensive imaging suite, syngo.plaza integrates Hospital / Radiology Information Systems (HIS / RIS) to enable customer specific workflows. syngo.plaza optionally uses a variety of advanced postprocessing applications. Note: Web-based image distribution is not intended for reporting.

syngo.plaza is a Picture Archiving and Communication System intended to display, process, read, report, communicate, distribute, store, and archive digital medical images, including mammographic images. It supports the physician in diagnosis and treatment planning. For primary image diagnosis in Mammography only uncompressed or non-lossy compressed images and only preprocessed DICOM "For Presentation" images must be used. Also monitors (displays) and printers which received FDA clearance for Mammography must be used. syngo.plaza also supports DICOM Structured Reports. In a comprehensive imaging suite, syngo.plaza integrates Hospital / Radiology Information Systems (HIS / RIS) to enable customer specific workflows. syngo.plaza optionally uses a variety of advanced postprocessing applications. Note: Web-based image distribution is not intended for reporting. syngo.plaza is a "software only"-system. which will be delivered on DVD to be installed on common IT hardware, matching the syngo.plaza hardware requirements. syngo.plaza will be installed by Siemens implementation engineers. The integration into customer specific 17 environments is offered based on professional services. Updates / upgrades are offered based on service contracts and fulfilled by trained service technicians.

The provided text describes the Siemens syngo.plaza VB10A, a Picture Archiving and Communication System (PACS), and its substantial equivalence to a predicate device (syngo.plaza VA20A). It is a 510(k) summary, which focuses on demonstrating that a new device is as safe and effective as a legally marketed predicate device. This type of submission generally does not include extensive clinical studies or detailed performance metrics against specific acceptance criteria. Instead, it relies on demonstrating similar technical and functional characteristics to a previously cleared device.

Therefore, many of the requested details regarding acceptance criteria, specific performance metrics, and detailed study information are not present in the provided document, as they are not typically required for a 510(k) submission for a PACS device of this nature. The information below is extracted or inferred from the provided text where possible, and explicitly states where information is missing.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of a 510(k) submission for aPACS device, "acceptance criteria" are primarily related to functional equivalence, adherence to standards, and safety. There are no quantitative diagnostic performance metrics presented for the device itself in this document. The "performance" is largely described in terms of functional parity with the predicate device and adherence to listed standards.

Note: This document does not contain quantitative clinical performance metrics (e.g., sensitivity, specificity, accuracy) for image interpretation, as the device is a PACS for display and management, not a diagnostic algorithm that provides an output needing validation against clinical outcomes. The "study" here is primarily a series of verification and validation activities against engineering and regulatory standards, and a comparison against a predicate device.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document describes non-clinical testing including Unit Test Level, Integration Test Level, and System Test Level performed for newly developed components and the complete system. This implies testing against technical specifications and requirements, rather than a "test set" of patient data in the clinical sense for performance evaluation.

• Sample Size for Test Set: Not specified. The document does not refer to a "test set" in terms of patient cases or images for evaluating diagnostic performance. Testing was for software functionality, safety, and adherence to standards.
• Data Provenance: Not applicable/Not specified. As this is primarily software verification and validation, there is no mention of country of origin for clinical data or whether it was retrospective or prospective. The testing would have involved simulated data, test cases designed to check functionalities, and potentially a range of DICOM images to ensure compatibility and correct display/processing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Number of Experts: Not applicable/Not specified. Since this is a PACS system and the application is for functional equivalence, there is no mention of expert radiologists establishing ground truth for diagnostic purposes within this 510(k) summary. The "ground truth" for software functionality would be the defined specifications and expected behavior, tested by software engineers and quality assurance personnel.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Adjudication Method: Not applicable. Given that the testing is focused on software functionality, safety, and adherence to standards, the concept of "adjudication" for a clinical test set is not present in this document.

5. 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

• MRMC Study: No. The document does not describe any MRMC comparative effectiveness study where human readers utilized AI. The device is a PACS system, not an AI-powered diagnostic aide.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done

• Standalone Performance Study: No. This device is a PACS and its function is to display, process, and manage medical images for human interpretation, not to provide standalone diagnostic outputs. Therefore, a standalone algorithm performance study is not applicable and not mentioned.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• Type of Ground Truth: Not applicable/Not specified for clinical outcomes. For the software verification and validation, the "ground truth" would be the documented functional requirements, design specifications, and expected outputs of the software features (e.g., correct image display, accurate measurements, proper storage, and retrieval). There is no mention of clinical ground truth (like pathology or outcomes data) being used to evaluate the device's performance in a diagnostic capacity.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable. As the device is a PACS system and not an AI/ML algorithm that requires training data in the diagnostic sense, there is no mention of a "training set."

9. How the ground truth for the training set was established

• Ground Truth for Training Set: Not applicable. See point 8.

Ask a specific question about this device

syngo.via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options. syngo.via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.

syngo.via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options. syngo.via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S. The system is a software only medical device. It defines minimum requirements to the hardware it runs on. The hardware itself is not seen as a medical device and not in the scope of this 510(k) submission. It supports the physician in diagnosis and treatment planning. syngo.via also supports storage of Structured DICOM Reports. In a comprehensive imaging suite syngo.via integrates Radiology Information Systems (RIS) to enable customer specific workflows. The predicate device, syngo.via allows for the use of a variety of advanced applications (clinical applications) These applications are medical devices on their own rights and filed separately. They are not part of this 510(k) submission and not part of the syngo.via medical device. syngo.via has a universal component called generic reader application which is part of this medical device and it allows no newly introduced imaging and post processing algorithms compared to the above mentioned predicate devices. syngo.via is based on Windows. Due to special customer requirements and the clinical focus syngo.via can be configured in the same way as the predicate device with different combinations of syngo- or Windows based software options and clinical applications which are intended to assist the physician in diagnosis and/or treatment planning. This includes commercially available post-processing software packages.

Here's an analysis of the provided 510(k) summary regarding acceptance criteria and supporting studies:

This 510(k) pertains to "syngo.via," a PACS system. Based on the document, this 510(k) is for enhanced functionalities of syngo.via, making it an update or extension of a previously cleared device (K123375). The key here is that it's not a new AI algorithm designed for a
specific diagnostic task with associated performance metrics. Instead, it seems to be primarily a software platform update that integrates functionalities already present in other cleared Siemens products.

Therefore, the typical structure for reporting AI/CADe/CADx device performance (sensitivity, specificity, AUROC, etc.) involving a test set, ground truth, and expert readers is not applicable in this submission. The "acceptance criteria" discussed are likely related to software verification and validation, adherence to standards, and demonstrating substantial equivalence to existing devices with similar functionalities.

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned above, this 510(k) is for an enhanced PACS system and does not present specific diagnostic performance metrics. The "performance" is primarily demonstrated through compliance with standards and equivalence to predicate devices. There are no explicit quantitative acceptance criteria for diagnostic performance in terms of sensitivity, specificity, etc., as it's not a new diagnostic algorithm.

The "performance" described is in terms of:

• Software Functionality: Viewing, manipulation, communication, and storage of medical images.
• Integration: HL7-/DICOM-compatible RIS workflow.
• Technological Characteristics: Runs on Windows OS, supports DICOM images, image data compression (lossless and lossy).
• Imaging Algorithms (inherited/similar to predicates): MPR, MIP, MinIP, VRT, SSD, Digitally Reconstructed Radiograph, Editor functionality, Registration, Region Growing, Quantitative measurements.
• Automatic Spine Labeling (inherited/similar to predicates): Anatomy Labeling of Vertebra bodies, automatically suggested labels with manual override.

2. Sample size used for the test set and the data provenance

The document does not describe a "test set" in the context of diagnostic performance evaluation (e.g., a set of medical images used to evaluate an algorithm's diagnostic accuracy). The testing performed was software verification and validation testing at Unit, Integration, and System levels, as per IEC 62304. This type of testing uses various software inputs and configurations to ensure functional correctness, rather than a diagnostic image dataset. No specific sample size of images or data provenance (country, retrospective/prospective) is provided because it's not relevant for this type of submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. There was no diagnostic "test set" requiring expert ground truth for diagnostic accuracy evaluation.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable. There was no diagnostic "test set" requiring expert ground truth or adjudication.

5. 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

Not applicable. This 510(k) does not present an MRMC study comparing human reader performance with and without AI assistance, as it is a PACS system enhancement, not a new AI-powered diagnostic tool.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Not applicable. This is not a standalone diagnostic algorithm. syngo.via is a platform for viewing, manipulation, communication, and storage of medical images, intended to "support the physician in diagnosis and treatment planning." The functionalities described (like automatic spine labeling) are features within this broader platform, and their performance is indicated as being similar to those from previously cleared predicate devices.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

Not applicable. As there was no diagnostic test set in the traditional sense, there was no ground truth for diagnostic accuracy established through expert consensus, pathology, or outcomes data. The "ground truth" for the software's functional performance would be defined by the software requirements and design specifications, verified through testing procedures.

8. The sample size for the training set

Not applicable. This 510(k) does not describe a new AI algorithm that requires a training set. The enhanced functionalities are stated to have "similar technological characteristics as the predicate device" and incorporate "imaging and post processing algorithms compared to the above mentioned predicate devices." This implies that any underlying algorithms for features like "Automatic Spine Labeling" are either existing, well-established, or derived from components previously cleared, rather than newly developed and trained models.

9. How the ground truth for the training set was established

Not applicable, as there is no mention of a training set for a new algorithm in this 510(k) submission.

Ask a specific question about this device

syngo via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options. syngo via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.

syngo.via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a standalone device or together with a variety of cleared and unmodified syngo based software options. syngo via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S. The system is a software only medical device. It defines minimum requirements to the hardware it runs on. The hardware itself is not seen as a medical device and not in the scope of this 510(k) submission. It supports the physician in diagnosis and treatment planning. syngo.via also supports storage of Structured DICOM Reports. In a comprehensive imaging suite syngo. Via integrates Radiology Information Systems (RIS) to enable customer specific workflows. syngo.via allows to use a variety of advanced applications (clinical applications) designed for syngo.via just as the predicate device syngo.x (K0925519, cleared on August 27, 2009). These applications are medical devices on their own rights and filed separately. They are not part of this 510(k) submission and not part of the syngo. via medical device. syngo. via has a universal component called generic reader application which is part of this medical device and it allows no newly introduced imaging and post processing algorithms compared to the above mentioned predicate devices. syngo.via is based on Windows. Due to special customer requirements and the clinical focus syngo.via can be configured in the same way as the predicate device with different combinations of syngo- or Windows -based software options and clinical applications which are intended to assist the physician in diagnosis and/or treatment planning. This includes commercially available post-processing software packages.

The provided 510(k) summary for K123375, Siemens syngo.via, primarily describes a Picture Archiving and Communications System (PACS) software solution. It does not contain the specific details about acceptance criteria, device performance, or a standalone study that would be necessary to fully answer your request.

The document focuses on the general capabilities of syngo.via related to viewing, manipulation, communication, and storage of medical images, and its substantial equivalence to a predicate device (syngo.x). It explicitly states that advanced applications (clinical applications) designed for syngo.via are medical devices on their own rights and filed separately. They are not part of this 510(k) submission and not part of the syngo.via medical device.

This means that the information you are looking for regarding acceptance criteria, study details, sample sizes, expert qualifications, and ground truth would be found in the 510(k) submissions for those specific advanced clinical applications, not in this general PACS software submission.

Therefore, I cannot populate the requested tables and information based on the provided text.

Here's what I can extract and what is missing based on your template:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Test Set Sample Size: Not specified.
• Data Provenance: Not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication method for the test set

• Adjudication Method: Not specified.

5. 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

• MRMC Study Done? No. This 510(k) is for a PACS system, not an AI-powered diagnostic application that would typically use an MRMC study for comparative effectiveness with or without AI assistance. The document explicitly states that "advanced applications (clinical applications) designed for syngo.via... are not part of this 510(k) submission and not part of the syngo.via medical device".

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done

• Standalone Study Done? No. The syngo.via described here is a foundational PACS system, not a standalone diagnostic algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• Type of Ground Truth: Not applicable, as detailed performance studies for specific diagnostic tasks are not part of this 510(k) for the syngo.via PACS system.

8. The sample size for the training set

• Training Set Sample Size: Not applicable/Not specified. This document does not describe the development or training of a specific diagnostic algorithm.

9. How the ground truth for the training set was established

• Training Set Ground Truth Establishment: Not applicable/Not specified.

Conclusion:

The provided 510(k) is for the syngo.via PACS system itself, which provides viewing, manipulation, communication, and storage functionalities for medical images. It explicitly states that specific "advanced applications (clinical applications)" which would contain diagnostic algorithms with measurable performance metrics, acceptance criteria, and associated studies, are not part of this submission and are filed separately. Therefore, the detailed information requested in your template is not present within this particular 510(k) summary.

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The syngo.CT Dynamic Angio software package has been designed to evaluate CT data which has been continuously acquired with computed tomography (CT) imaging systems. Contrast enhanced CT images are used to visualize the flow of contrast from the arteries to the veins.

syngo.CT Dynamic Angio can be used to assist the physician in the diagnosis of blood vessels and it supports in the evaluation of regions of interest, the visual inspection of time attenuation curves, and the creation of specific CT volumes, for example, arterial or venous phase. It will aid in the inspection of diseases which affect the vessel system, for example, vessel stenosis, collateral or late filling of vessels, vascular malformations, control of stent graft extravasation, or in the evaluation of tumor vascularization.

syngo.CT Dynamic Angio is a software, which was developed to visualize dynamic CT datasets in a three and four dimensional view. Possible input data are Siemens CT Dynamic Sequence, Dynamic Multiscan, Adaptive 4D Spiral and Heart Perfusion Scanning datasets.

syngo.CT Dynamic Angio supports the overlay free visualization of the vessel enhancement with the help of motion correction and bone segmentation. The software can be used to run a movie of a time series or to create CT phase volumes (e.g. arterial phase or venous phase) by combining multiple neighboring time points from the dynamic CT data. It also supports the evaluation of regions of interest and the visual inspection of time attenuation curves.

syngo.CT Dynamic Angiois a post-processing software package which provides a combination of functionality similar to functionality provided by one or more of the predicate devices as listed above. It uses the same data for evaluation as the predicate devices and provides results in the same format as the predicate devices

All result volumes created by CT Dynamic Angio are stored in separate series and consist of a set of standard DICOM single frame CT images. All finding snapshot images are stored in a different series as DICOM secondary captures.

As basis for data viewing, syngo.CT Dynamic Angio uses basic reader and image display functionality as provided by syngo.via. Different visualization filters like multiplanar reformatting (MPR, MPR Thick), maximum intensity projection (MIP, MIP Thin) and volume rendering techniques (VRT, VRT Thin) can be applied. Windowing of the visualized data cao be done by mouse interaction and with predefined CT window presets. Zooming and panning of the CT volumes is supported.

In addition to basic viewing capabilities, syngo.CT Dynamic Angio provides tools for visualization, analysis and reporting of vascular conditions.

Standard syngo.via analysis tools are Distance Line, Pixel Lens, Marker, Arrow and ROI (Region of Interest).

The Siemens syngo.CT Dynamic Angio is a software designed to visualize dynamic CT datasets in three and four dimensions. It aids physicians in diagnosing blood vessel conditions by allowing for the evaluation of regions of interest, visual inspection of time attenuation curves, and creation of specific CT volumes (e.g., arterial or venous phase). It helps in inspecting diseases affecting the vessel system, such as vessel stenosis, vascular malformations, and tumor vascularization.

Here's an analysis of the acceptance criteria and the study provided:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide specific numerical acceptance criteria or performance metrics for the syngo.CT Dynamic Angio's diagnostic capabilities (e.g., sensitivity, specificity, accuracy). Instead, it focuses on general safety and effectiveness, and equivalence to predicate devices.

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

The document does not specify a sample size for a test set (e.g., a specific number of CT scans or patient cases). The non-clinical testing mentioned is "conducted for syngo.CT Dynamic Angio software package during product development" and includes "verification and validation testing." The data provenance (e.g., country of origin, retrospective or prospective) is also not mentioned.

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

This information is not provided in the document. No details about expert involvement in establishing ground truth are given for any testing.

4. Adjudication Method for the Test Set:

No adjudication method (e.g., 2+1, 3+1, none) is mentioned, as there is no specific test set or reader study described.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not conducted or reported in this summary. The document does not describe any study comparing human readers with and without AI assistance to determine an effect size.

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

A standalone performance study of the algorithm without human-in-the-loop performance is explicitly not described. The "testing results supports that all the software specifications have met the acceptance criteria," but these acceptance criteria appear to be related to internal software development and safety standards rather than a formal standalone clinical performance evaluation against a gold standard. The device's purpose is to "assist the physician," implying a human-in-the-loop scenario.

7. Type of Ground Truth Used:

The document does not specify the type of ground truth used for any testing. Given the nature of the software (post-processing and visualization tools), internal software specifications and functional verification likely served as the "ground truth" for the non-clinical tests mentioned. There is no indication of expert consensus, pathology, or outcomes data being used as ground truth.

8. Sample Size for the Training Set:

The document does not provide any information about a training set or its sample size. This is a post-processing visualization tool, and the summary focuses on its functionality and equivalence to predicate devices, not on a machine learning model that would require a distinct training set.

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

Since no training set is mentioned, the method for establishing its ground truth is also not provided.

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syngo.via WebViewer is intended to be a software-only solution for reviewing medical images from syngo.via. The system cannot be used as stand-alone device. It is intended to be an option for syngo.via system only. syngo.via WebViewer is not intended for storage or distribution of medical images from one medical device to another. syngo.via WebViewer is a client server architecture and the client is intended to run on web clients which are connected to the healthcare institution IT infrastructure where the customer has to ensure HIPPA compliance. syngo.via WebViewer supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The communication of syngo.via WebViewer with connected medical IT systems will be done via standard interfaces such as but not limited to DICOM. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.

This premarket notification covers Siemens ' PACS syngo.via WebViewer. syngo.via WebViewer is intended to be a software-only solution for reviewing medical images from syngo.via. The system cannot be used as stand-alone device. It is intended to be an option for syngo via system only. syngo. via Web Viewer is not intended for storage or distribution of medical images from one medical device to another. syngo.via WebViewer is a client server architecture and the client is intended to run on web clients which are connected to the healthcare institution IT infrastructure where the customer has to ensure HIPPA compliance. syngo. via Web Viewer supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The communication of syngo.via WebViewer with connected medical IT systems will be done via standard interfaces such as but not limited to DICOM. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S. The system is a software only medical device. It defines minimum requirements to the hardware it runs on. The hardware itself is not seen as a medical device and not in the scope of this 510(k) submission. It supports the physician in diagnosis and treatment planning.

The provided text is a 510(k) Summary for the Siemens syngo.via WebViewer. This document describes the device, its intended use, and its substantial equivalence to predicate devices. However, this document does not contain explicit acceptance criteria or a study demonstrating that the device meets such criteria.

The 510(k) submission process for a Picture Archiving and Communications System (PACS) like syngo.via WebViewer primarily focuses on establishing substantial equivalence to existing legally marketed devices, rather than conducting new clinical trials with specific statistical performance metrics and acceptance criteria as might be expected for an AI-powered diagnostic device.

Here's a breakdown of why the requested information is largely absent based solely on the provided text, and what could be inferred or is generally understood for this type of device:

1. A table of acceptance criteria and the reported device performance

• Acceptance Criteria: Not explicitly stated in the document. For a PACS viewer, acceptance criteria would typically revolve around functional performance (e.g., image display accuracy, speed, compliance with DICOM standards, user interface usability, data integrity, security).
• Reported Device Performance: Not quantitively reported in the document. The document affirms that the device "passed all necessary verification and validation steps to demonstrate safety and effectiveness" and "does not introduce any new significant potential safety risks and is substantially equivalent to and performs as well as the predicate devices." This is a qualitative statement of performance relative to predicates rather than a measured performance against specific criteria.

2. Sample sized used for the test set and the data provenance

• Test Set Sample Size: Not specified. Validation for a PACS viewer typically involves testing against various types of DICOM images and objects (CT, MR, SC, PDF) to ensure correct display and functionality. The "sample" here would be representative medical images, but the document doesn't quantify how many were used.
• Data Provenance: Not specified. It's implied that various types of DICOM images would be used for testing, but their origin (country, retrospective/prospective) is not detailed.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Ground Truth Experts: Not applicable or specified. For a PACS viewer, "ground truth" isn't generally established by experts in the same way it would be for a diagnostic AI algorithm. The viewer's "ground truth" is adherence to DICOM standards for image display and manipulation, and the successful execution of its functions. The verification and validation would be conducted by software testers and engineers, likely with medical domain knowledge.

4. Adjudication method for the test set

• Adjudication Method: Not applicable or specified. Again, for a PACS viewer, the "test set" isn't typically adjudicated like an AI diagnostic outcome. Functional and performance testing would involve objective checks against specifications and industry standards.

5. 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

• MRMC Study: No. The syngo.via WebViewer is a medical image viewing and management system, not an AI-assisted diagnostic tool designed to improve human reader performance. Therefore, an MRMC study and
  "effect size of how much human readers improve with AI vs without AI assistance" are not relevant to this device as described.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Standalone Performance: Not applicable as a diagnostic algorithm. The device itself is described as a "software-only solution for reviewing medical images" and "cannot be used as stand-alone device" meaning it requires the syngo.via system to function. It functions as a standalone software component (algorithm only in its specified role), but its "performance" is in displaying images and managing data, not making diagnoses without a human.

7. The type of ground truth used

• Type of Ground Truth: Not applicable in the traditional sense of a diagnostic device (e.g., pathology, outcomes data). The "ground truth" for a PACS viewer essentially refers to the correct and accurate display of DICOM images as per specifications and standards, and the proper functioning of its features (e.g., measurements, windowing). This is verified through comparison against known correct outputs or adherence to technical specifications.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. The syngo.via WebViewer is not described as an AI/ML device that requires a "training set" in the context of machine learning model development. It's a traditional software application.

9. How the ground truth for the training set was established

• Ground Truth for Training Set: Not applicable, as there is no "training set."

Summary based on the provided document:

The 510(k) summary focuses on demonstrating the substantial equivalence of the syngo.via WebViewer to previously cleared predicate devices (Siemens syngo.x and Siemens InSpace 4D). It highlights similarities in intended use, technological characteristics (image communication, processing, supported image types, user interface, hardware), and adherence to relevant industry standards (IEC 62304 for software lifecycle, ISO 14971 for risk management, IEC 60601-1-1-6 for usability, DICOM, HL7, JPEG, JPEG2000 for communication and compression).

The "study" referenced implicitly is the verification and validation activities performed during the device's development cycle, which are stated to be compliant with QSR design processes, IEC 62304, ISO 14971, and IEC 60601-1-1-6. These activities would have ensured that the software functions as intended and meets its specifications, including accurate rendering of medical images and adherence to interface standards. However, direct evidence of specific acceptance criteria met through a formal study with statistical outcomes is not part of this 510(k) summary.

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Syngo.CT Cardiac Function is an image analysis software package for evaluating cardiac CT angiography (CTA) volume data sets. Combining digital image processing and visualization tools (multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP) thin/thick, inverted MIP thin/thick, volume rendering technique (VRT)), evaluation tools (left and right ventricular (LV/RV) volume calculation, left ventricular myocardial wall calculation and visualization of myocardial enhancement by color coding of hypo-/hyperdense areas) and reporting tools (finding location, finding characteristics and key images), the software package is designed to support the physician in determining the functional parameters of the left and right ventricles, confirming the presence of physician-identified myocardial enhancement defects and evaluation, documentation and follow-up of any such finding.

These visualization/evaluation tools allow for quantification of functional parameters and characterization of myocardial enhancements defects over time, helping the physician to assess any changes. It is also designed to help the physician classify conspicuous regions of tissue.

Syngo.CT Cardiac Function is an image analysis software package for evaluating cardiac CT angiography (CTA) volume data sets. Combining digital image processing and visualization tools (multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP) thin/thick, inverted MIP thin/thick, volume rendering technique (VRT)), evaluation tools (left and right ventricular (LV/RV) volume calculation, left ventricular myocardial wall calculation and visualization of myocardial enhancement by color coding of hypo-/hyperdense areas) and reporting tools (finding location, finding characteristics and key images), the software package is designed to support the physician in determining the functional parameters of the left and right ventricles, confirming the presence or absence of physician-identified myocardial enhancement defects and evaluation, documentation and follow-up of any such finding.

These visualization/evaluation tools allow for quantification of functional parameters and characterization of myocardial enhancements defects over time, helping the physician to assess any changes. It is also designed to help the physician classify conspicuous regions of tissue.

I am sorry, but the provided text does not contain specific acceptance criteria or an explicit study proving the device meets those criteria. The document is a 510(k) summary for the Siemens syngo.CT Cardiac Function software, primarily focused on establishing substantial equivalence to previously cleared devices.

It mentions that "The testing results supports that all the software specifications have met the acceptance criteria" in section 10, but it does not detail:

• What those acceptance criteria are.
• The specifics of the study that demonstrates the device meets these criteria (e.g., sample size, data provenance, ground truth establishment, expert qualifications, adjudication methods, or specific performance metrics).
• Any multi-reader multi-case (MRMC) comparative effectiveness studies or standalone performance studies with quantitative results.

Therefore, I cannot provide the requested table and detailed information based on the given input.

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syngo.plaza is a Picture Archiving and Communication System intended to display, process, read, report, communicate, distribute, store, and archive digital medical images, including mammographic images. It supports the physician in diagnosis and treatment planning. For primary image diagnosis in Mammography only uncompressed or non-lossy compressed images and only preprocessed DICOM "For Presentation" images must be used. Also monitors (displays) and printers which received FDA clearance for Mammography must be used. syngo.plaza also supports DICOM Structured Reports. In a comprehensive imaging suite, syngo.plaza integrates Hospital / Radiology Information Systems (HIS/RIS) to enable customer specific workflows. syngo.plaza optionally uses a variety of advanced postprocessing applications. Note: Web-based image distribution is not intended for reporting.

syngo plaza is a "software only"-system, which will be delivered on CD-ROM / DVD to be installed on common IT hardware. syngo.plaza will be installed by Siemens service engineers. The backend communication and storage solution is based in Windows 2008 operating systems as described in the predicate devices syngo.plaza VA10A (093612) and syngo.x (K092519). The clients are based on Windows XP as also described in the predicate devices syngo.plaza VA10A (093612) and syngo.x (K092519) The syngo plaza will be marketed as a software only solution for the end-user (with recommended hardware requirements). It will be installed by trained service engineers only. Any special needs such as integration in a specific environment and updates / upgrades will be I any spond individual service contract and fulfilled by special trained service technicians. This is also applicable for the predicate devices syngo.plaza VA10A (093612) and syngo.x (K092519). The herewith described syngo plaza VA20A supports DICOM formatted images and This which is also described for the predicate devices syngo.plaza VA10A (093612), syngo.x (K092519) and syngo Imaging (K071114).

The provided text describes the syngo.plaza VA20A, a Picture Archiving and Communication System (PACS). However, it does not contain information about specific acceptance criteria or a study proving that the device meets those criteria, as typically found in performance studies for AI/CADe devices.

The document is a 510(k) summary for a PACS system, which primarily focuses on stating substantial equivalence to predicate devices based on intended use and technical characteristics, rather than detailed performance metrics of a novel algorithm or diagnostic aid.

Here's a breakdown of what is and is not present, based on your request:

1. A table of acceptance criteria and the reported device performance:

• Not provided. The document describes the system's functionalities (display, process, read, report, communicate, distribute, store, and archive digital medical images) and states that software verification and validation were performed according to various standards (DICOM, JPEG, ISO, IEC, HL7). It concludes that "Siemens is of the opinion, that syngo plaza is substantially equivalent to and performs as well as the predicate device." There are no quantitative performance metrics (e.g., sensitivity, specificity, AUC) or defined acceptance criteria for such metrics.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

• Not provided. No specific test set, sample size, or data provenance is mentioned as this is not a clinical performance study of an AI algorithm.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

• Not provided. Ground truth establishment is not relevant in this context, as there's no clinical performance study reported.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not provided. Not applicable.

5. 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:

• Not provided. No MRMC study is mentioned. The device is a PACS system, not an AI or CADe product designed to assist human readers in a diagnostic task in a comparative effectiveness study.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Not provided. Not applicable, as this is a PACS system and not a standalone AI algorithm with diagnostic output.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

• Not provided. Not applicable.

8. The sample size for the training set:

• Not provided. Not applicable, as this is a PACS system, not an AI algorithm that undergoes specific training on a dataset.

9. How the ground truth for the training set was established:

• Not provided. Not applicable.

In summary, the provided document is a regulatory submission (510(k) summary) for a PACS system (syngo.plaza VA20A) demonstrating its substantial equivalence to previously cleared predicate devices. It focuses on functional descriptions, compliance with technical standards, and risk management, rather than detailed performance studies of an AI diagnostic component as would be required for a device claiming to interpret images or assist in diagnosis via AI/CAD.

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