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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 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.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.

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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.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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Syngo.CT Coronary 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), curved planar reformation (CPR)), evaluation tools (coronary vessel centerline calculation, stenosis calculation and plaque analysis) and reporting tools (lesion location, lesion characteristics and key images), the software package is designed to support the physician in confirming the presence or absence of physician-identified coronary lesions and evaluation, documentation and follow-up of any such lesion.

These visualization/evaluation tools allow for characterization of coronary lesions and lesion size over time, helping the physician to assess the changes in their growth. It is also designed to help the physician classify conspicuous regions of tissue.

Syngo.CT Coronary 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), curved planar reformation (CPR)), evaluation tools (coronary vessel centerline calculation, stenosis calculation and plaque analysis) and reporting tools (lesion location, lesion characteristics and key images), the software package is designed to support the physician in confirming the presence or absence of physician-identified coronary lesions and evaluation, documentation and follow-up of any such lesion. These visualization/evaluation tools allow for characterization of coronary lesions and lesion size over time, helping the physician to assess the changes in their growth. It is also designed to help the physician classify conspicuous regions of tissue.

Here's a breakdown of the acceptance criteria and study information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state acceptance criteria in a formal table or list quantifiable performance metrics with specific thresholds. Instead, it refers to general safety and effectiveness concerns and the device's intended use, which is to support physicians in confirming the presence or absence of coronary lesions, and evaluating and documenting them.

The document highlights the device's functionality and visualization tools, implying that these capabilities are what define its "performance." However, no numerical performance data (e.g., sensitivity, specificity, accuracy for lesion detection or quantification) is presented.

2. Sample Size for the Test Set and Data Provenance

The provided text does not include information about the sample size used for a test set, nor does it specify the data provenance (country of origin, retrospective or prospective nature).

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

The provided text does not include information about the number of experts used to establish ground truth or their qualifications.

4. Adjudication Method for the Test Set

The provided text does not include information about any adjudication method used for the test set.

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

The provided text does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it quantify any effect size of human reader improvement with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study

The provided text does not explicitly describe a standalone (algorithm-only) performance study with quantifiable results. The description of the device focuses on its role as an "image analysis software package" designed to "support the physician," implying a human-in-the-loop workflow rather than a fully autonomous application.

7. Type of Ground Truth Used

The provided text does not explicitly state the type of ground truth used for any evaluation. Given the context of coronary analysis, likely ground truth would involve either invasive coronary angiography (ICA) or expert consensus readings by cardiologists/radiologists. However, this is not confirmed in the document.

8. Sample Size for the Training Set

The provided text does not include any information about the sample size used for a training set. The document is a 510(k) summary, which often focuses on substantial equivalence to predicate devices and general safety/effectiveness, rather than detailed algorithmic training and validation specifics.

9. How Ground Truth for the Training Set Was Established

The provided text does not describe how ground truth for any training set was established.

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syngo plaza is a Picture Archiving and Communication System (PACS) intended to display, process, read, report, communicate, distribute, store and archive digital medical images. It supports the physician in diagnosis and treatment planning. syngo.plaza also supports storage and archiving of 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. In the U.S.A., syngo.plaza is not intended for the reporting of digital mammography images.

syngo. plaza is a Picture Archiving and Communication System (PACS) intended to display, process, read, report, communicate, distribute, store and archive digital medical images. It supports the physician in diagnosis and treatment planning. syngo.plaza also supports storage and archiving of 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 post processing applications. syngo.plaza is a "software only"-system, which will be delivered on CD-ROM / DVD or also preconfigured on hardware. syngo.plaza will be installed by Siemens service engineers. Defined Hardware requirements are to be met. The herewith described syngo.plaza supports DICOM formatted images and objects.

This 510(k) summary for syngo.plaza is quite brief and primarily focuses on establishing substantial equivalence to a predicate device rather than detailing specific performance studies with acceptance criteria for a new or significantly modified feature. It is a PACS system, and the submission emphasizes its functionality as a medical diagnostic and viewing workstation, along with its integration capabilities.

Therefore, much of the requested information regarding acceptance criteria and performance studies for a device meeting specific quantitative performance metrics is not explicitly stated in this document. The submission focuses on verification and validation (V&V) against established standards for software development and medical devices.

Here's an analysis of the provided text in relation to your request:

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

The document does not provide a table of acceptance criteria with reported device performance in the manner typically seen for devices that perform a specific diagnostic measurement or AI-driven analysis. The "acceptance criteria" here refer to the successful completion of software verification and validation (V&V) activities and the demonstration of substantial equivalence.

The closest statement to an acceptance criterion is:

• "After completion of the system test and comparison of the test results with the software release acceptance criteria, Siemens is of the opinion, that syngo.plaza is substantially equivalent to and performs as well as the predicate device."

This implies that the overall system performance as a PACS met internal "software release acceptance criteria" to demonstrate substantial equivalence to the predicate device. However, these criteria are not detailed in terms of specific quantitative metrics (e.g., sensitivity, specificity, processing time).

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

This information is not provided in the document. The non-clinical testing discussion focuses on software V&V against standards, not on clinical performance testing with a specific test set of medical images from patients.

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)

This information is not provided. As there's no mention of a clinical test set with ground truth, there's no information about experts.

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

This information is 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

There is no mention of an MRMC study or any study evaluating human reader improvement with or without AI assistance. This submission describes a PACS system, not an AI-assisted diagnostic tool in the sense of a standalone algorithm for interpretation.

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

There is no mention of a standalone algorithm performance study. The device is a PACS system, which is inherently a human-in-the-loop system for image display, processing, reading, and reporting.

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

This information is not provided. Given the nature of the device (PACS), the "ground truth" for V&V would likely involve ensuring accurate image display, processing functions, data integrity, and compliance with standards, rather than diagnostic accuracy against a clinical ground truth.

8. The sample size for the training set

This information is not provided. There is no mention of a "training set" as would be relevant for machine learning or AI models with learned parameters. The software V&V process for a PACS does not typically involve a training set.

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

This information is not provided.

Summary of what is present:

• Acceptance Criteria (Implicit): Substantial equivalence to the predicate device and successful completion of software V&V against specified standards (DICOM, JPEG, SMPTE, ISO 14971, IEC 60601-1-4, IEC 60601-1-6, HL7, IEC 62304). The "reported device performance" is that it "performs as well as the predicate device" and successfully passed these V&V activities.
• Study: The "study" referenced is the non-clinical testing which comprises "software verification and validation (Unit Test Level, Integration Test Level and System Test Level)." This is a demonstration of adherence to quality systems and regulatory standards, not a comparative clinical performance study.
• Key focus: The submission's primary goal is to demonstrate substantial equivalence to an existing PACS device (Siemens VO 1190). It is a "software only"-system delivered on CD-ROM/DVD or preconfigured hardware, meeting defined hardware requirements, and supporting DICOM formatted images and objects.

In conclusion, the provided document describes a PACS system and its regulatory submission focused on substantial equivalence based on software V&V. It does not contain the detailed quantitative performance metrics, test set characteristics, or AI-specific study designs that are typically requested when evaluating advanced diagnostic algorithms or AI-powered devices.

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The ABVS Workplace is intended to display ultrasound images of the breast acquired from B-mode imaging using an automatic or handheld scanning linear transducer. The images may be reviewed and analyzed by the physician. The ABVS Workplace is indicated for use as an adjunct to mammography. The ABVS Workplace is not Intended to be used as a replacement for screening mammography.

This premarket notification covers the Siemens ABVS Workplace, an offline image viewing workstation. The ABVS workplace consists of common IT hardware and preinstalled software to ensure that defined hardware requirements are met. The workplace is based on Windows XP.

The provided text describes the Siemens ABVS Workplace, an offline image viewing workstation for breast ultrasound images, and its substantial equivalence to a predicate device. However, it does not contain any information regarding specific acceptance criteria, a study proving device performance against those criteria, sample sizes for test or training sets, expert qualifications, or adjudication methods.

The document is a 510(k) summary for regulatory clearance, primarily focusing on establishing substantial equivalence to a legally marketed predicate device rather than detailing specific performance studies against pre-defined acceptance criteria for a novel device.

Therefore, I cannot extract the requested information from the provided text. The output will reflect the lack of this information.

Summary of Unavailable Information:

The provided document, a 510(k) summary for the Siemens ABVS Workplace, details the device's general information, intended use, and technological characteristics, and establishes its substantial equivalence to a predicate device for regulatory clearance. However, it does not contain any information regarding specific acceptance criteria for device performance, the results of a study demonstrating the device meets such criteria, the sample sizes used for testing or training, the provenance of data, expert qualifications, adjudication methods, or whether MRMC or standalone performance studies were conducted.

Therefore, I cannot complete the requested tables and sections with the information about acceptance criteria and performance studies.

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syngo.x 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.x based software options.

syngo.x 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.

This premarket notification covers Siemens enhanced PACS system syngo.x.

syngo.x 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 x based software options. syngo x 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.x also supports storage of Structured DICOM Reports.

In a comprehensive imaging suite syngo.x integrates Radiology Information Systems (RIS) to enable customer specific workflows.

syngo.x allows to use a variety of advanced applications (clinical applications) designed for syngo.x just as the predicate device syngo MultiModality Workplace (K072728, cleared on April 22, 2007). 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 x medical device. syngo.x has a universal component called generic reader application which is part of this medical device and it allows no newly introduced imaging and postprocessing algorithms compared to the above mentioned predicate devices.

syngo.x is based on Windows. Due to special customer requirements and the clinical focus syngo.x can be configured in the same way as the syngo MultiModality Workplace with different combinations of syngo.x- 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.

syngo.x is a "software only"-system, which will be delivered on CD-ROM / DVD to be installed on common IT hardware. This hardware has to fulfil the · defined requirements. The Software will be installed by Siemens service engineers only.

The herewith described syngo.x supports DICOM formatted images and objects.

The syngo.x 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 covered by individual service contract and fulfilled by special trained service technicians.

The provided text is a 510(k) summary for the syngo.x Picture Archiving and Communications System (PACS). This document focuses on demonstrating that the syngo.x device is substantially equivalent to previously cleared devices (syngo Imaging and syngo MultiModality Workplace), rather than presenting a study to prove meeting specific acceptance criteria for performance.

Therefore, much of the requested information (acceptance criteria, device performance, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, training data details) is not available in this specific 510(k) summary.

The document primarily states that "syngo.x does not introduce any new significant potential safety risks and is substantially equivalent to and performs as well as the predicate devices." This substantial equivalence argument is based on similar intended use and technical characteristics, not on a new clinical study with defined performance metrics.

Here's a breakdown of what can be extracted from the provided text, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: Not explicitly stated as quantifiable performance metrics for the syngo.x device itself. The acceptance criteria for this 510(k) submission are implicitly demonstrating substantial equivalence to predicate devices based on intended use and technological characteristics.
• Reported Device Performance: No specific numerical performance metrics (e.g., accuracy, sensitivity, specificity, processing speed targets) are reported for syngo.x. The claim is that it "performs as well as the predicate devices," but no data from a performance study is included to substantiate this in a measurable way.

Missing Information: Specific KPIs, thresholds, and performance results of syngo.x.

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

• Sample Size (Test Set): Not applicable or not specified. There is no mention of a test set being used for a performance study.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not applicable or not specified.

Missing Information: Any details about a performance test set.

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

• Number of Experts: Not applicable or not specified.
• Qualifications of Experts: Not applicable or not specified.

Missing Information: Details about experts for ground truth establishment.

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

• Adjudication Method: Not applicable or not specified.

Missing Information: Adjudication method.

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 Comparative Effectiveness Study: No, an MRMC study is not mentioned. The syngo.x is a PACS system for viewing, manipulation, communication, and storage of medical images, and its 510(k) is about demonstrating substantial equivalence to existing PACS systems, not about demonstrating improvement in human reader performance with AI assistance. The document explicitly states that "advanced applications (clinical applications) designed for syngo.x... 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 x medical device."

Missing Information: MRMC study details and effect size.

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

• Standalone Study: No, a standalone algorithm performance study is not mentioned. This device is a PACS system intended for human use and interaction, not a standalone diagnostic algorithm.

Missing Information: Standalone study details.

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

• Type of Ground Truth: Not applicable or not specified. No performance study data is presented.

Missing Information: Type of ground truth.

8. The sample size for the training set:

• Sample Size (Training Set): Not applicable or not specified. No machine learning or AI algorithm development details are provided for syngo.x itself in this submission.

Missing Information: Training set details.

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

• Ground Truth Establishment (Training Set): Not applicable or not specified.

Missing Information: Ground truth establishment for training set.

Summary of available information:

The 510(k) summary for syngo.x focuses on:

• Device Description and Intended Use: Viewing, manipulation, communication, and storage of medical images (excluding digital mammography for diagnosis in the U.S.).
• Regulatory Classification: Class II, Product Code LLZ, 21 CFR §892.2050 (Picture Archiving and Communications System).
• Substantial Equivalence: Claimed based on similar intended use and technical characteristics to predicate devices:
  • Siemens syngo Imaging (K081734)
  • Siemens syngo MultiModality Workplace (K072728)
• Safety and Effectiveness Concerns: Addressed through risk analysis, software development, verification and validation testing, and adherence to recognized industry practices and standards.
• Software Only: The device is a software-only medical device, with hardware requirements specified, and installation performed by Siemens service engineers.

In essence, this 510(k) submission is a declaration of equivalence to existing PACS systems based on the functionalities and technological aspects of the software, not a report of a new performance study with specific acceptance criteria that the device had to meet through experimental data.

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