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The SIENET Cosmos is a Picture Archiving and Communication System (PACS) intended to enhance the complete imaging workflow, i.e.

• Manipulating .
• Reading .
• . Reporting
• Viewing .
• Communicating / distributing .
• Storing / archiving .
• of radiological softcopy images and
• . Storing / archiving of structured (DICOM) reports.

The system is a "software only" solution and is intended to assist the physician in diagnosis or treatment planning,

Therefore SIENET Cosmos supports the following generic imaging workflow:

• . Receive scheduled exams from IS at the SIENET Cosmos archiving component SDM
• Provide relevant prior exams and reports (Structured Reports only) to the Modalities and Workplaces .
• . Receive and store new exams from the Modalities at the SDM
• Prepare images for reading .
• . Report new images, if required by comparing them with prior exams and reports
• Demonstrate exams at Radiological Demos .
• View exams and reports at Workplaces outside Radiology (e.g. Surgery, Intensive Case Unit, wards, external referring physicians).

Note:
The workstation deployment syngo® Viewing Studio is not intended for primary diagnosis.

This premarket notification covers Siemens enhanced PACS system SIENET Cosmos, version V15A.

SIENET Cosmos is a "software only"- solution, including a backend communication and storage component and three different workplace deployments for medical imaging tasks and applications. It can be distributed as software only as well as preinstalled on hardware which meets the defined minimum requirements.

SIENET Cosmos is the integrated radiology suite for large radiological practices and community hospitals. Important factors are the centralized server structure, the wide ranging data distribution and the overall integrated concept, ranging from scheduling the examination to reporting and archiving as well as image and report distribution. The version V15A contains improvements for workplace functionality, such as layout enhancements and display improvements (user interface) and amended service functionality.

The three SIENET Cosmos workplace deployments ...
a) syngo® Viewing Studio - for image distribution (web-based viewing application not intended for primary diagnosis!)
b) syngo® Reporting Studio - for basic reporting, inside as well as outside of the radiology (standalone workstation)
c) syngo® Reporting Studio - Advanced Application Bundle - for use inside the radiology with advanced reporting functionality
... are medical diagnostic and viewing workstations intended for manipulating, reading, reporting, viewing and communicating / distributing of radiological softcopy images and so allows radiologists and radiological technicians to receive and process all data needed.

SIENET Cosmos Image Data Management ... ensures all authorized personnel fast and continuous access to radiological data. It's main functionality ranges from availability of images having regard to data security, open interfaces, storage media, central system administration, back-up, software distribution to providing a flexible storage hierarchy.

The main purpose is storing and archiving of radiological softcopy images and structured (DICOM) reports.

The Workflow Management enables by integration of any HL7- / DICOM-compatible RIS (IHE Year 5) to the SIENET Cosmos PACS a consistent workflow - from patient registration to requirement scheduling to a personal worklist and supports therefore reporting, documentation or administrative tasks.

SIENET Cosmos (version V15A) is a "software only"-system, which will be delivered on CD-ROM / DVD or as a complete radiology solution consisting of hardware and preinstalled software. SIENET Cosmos will be installed by Siemens service engineers.

Defined Hardware requirements are to be met.

The backend communication and storage solution (SDM) is based on the Solaris 8 operating system. The workplaces are based on Windows 2000 / Windows XP operating system.

The herewith described SIENET Cosmos supports DICOM formatted images and objects.

The version V15A contains an extended range of compression mode in comparison to version V10A.

The provided text is a 510(k) summary for the SIENET Cosmos, version V15A, a Picture Archiving and Communications System (PACS). This document focuses on demonstrating substantial equivalence to a predicate device, rather than proving the device meets specific performance acceptance criteria through clinical studies. Therefore, much of the requested information regarding detailed acceptance criteria, study methodologies, and performance metrics is not present in this type of regulatory document.

However, I can extract the available information and state which points are not covered.

1. Table of Acceptance Criteria and Reported Device Performance

Explanation: In a 510(k) process for a PACS, the "acceptance criteria" are generally tied to the demonstration of substantial equivalence to a legally marketed predicate device. This means the new device must perform as well as, or be no less safe or effective than, the predicate. The document doesn't provide quantifiable, specific acceptance thresholds (e.g., "DICOM conformance rate must be >99%"). Instead, it asserts that the new version is substantially equivalent, implying it meets the current standards for such systems.

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

• Sample Size: Not specified.
• Data Provenance: Not specified. This document does not detail any specific clinical performance testing with a "test set" of images or data; rather, it refers to internal "verification and validation testing" (a general quality assurance statement).

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

• Number of Experts: Not applicable, as detailed clinical testing with expert-established ground truth is not described.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable, as a test set with expert ground truth establishment is not described.

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

• Was an MRMC study done? No. The document does not mention any MRMC study.
• Effect Size of Human Readers with/without AI assistance: Not applicable, as this is a PACS system, not an AI-assisted diagnostic tool, and no MRMC study was conducted.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

• Was a standalone study done? Not applicable in the context of an algorithm's diagnostic performance. This device is a PACS (Picture Archiving and Communications System), which is a software system for managing, viewing, and distributing images, not an autonomous diagnostic algorithm. Its "performance" is related to its functionality, data integrity, and usability within the clinical workflow, rather than a diagnostic accuracy metric. The document mentions "verification and validation testing" which would cover the standalone functionality of the PACS itself (e.g., proper image storage, retrieval, display, and communication).

7. The Type of Ground Truth Used

• Type of Ground Truth: Not applicable for diagnostic performance metrics, as this document is about a PACS system's substantial equivalence, not a diagnostic algorithm's accuracy. For the PACS's own functionality, the "ground truth" would be its adherence to specified technical requirements (e.g., DICOM standards, data integrity, system uptime, and usability).

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This document does not pertain to an algorithm developed through machine learning, and therefore, there is no "training set" in that context.

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

• How Ground Truth Was Established: Not applicable, as there is no mention of a machine learning training set.

Summary of Document Focus:

This 510(k) summary (K042832) for SIENET Cosmos version V15A primarily focuses on asserting substantial equivalence to an existing legally marketed device (SIENET Cosmos, K033831). It describes the device's intended use (PACS functionality), technological characteristics (software-only, operating systems, DICOM support), and general safety and effectiveness considerations (risk management, adherence to standards). It does not provide details on specific clinical performance studies, such as those that would involve acceptance criteria for diagnostic accuracy, test sets, expert ground truth, or MRMC studies, because a PACS system's regulatory pathway typically emphasizes functionality, safety, and compatibility rather than clinical diagnostic outcome metrics in the same way an AI diagnostic algorithm would.

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The SIENET Cosmos is a Picture Archiving and Communication System (PACS) intended to enhance the complete imaging workflow, i.e.

• Manipulating
• Reading
• Reporting
• Vicwing
• Communicating / distributing
• Storing / archiving
  of radiological softcopy images and
• Storing / archiving of structured (DICOM) reports.
  The system is a "software only" solution and is intended to assist the physician in diagnosis or treatment planning.
  Therefore SIENET Cosmos supports the following generic imaging workflow:
• Receive scheduled exams from IS at the SIENET Cosmos archiving component SDM
• Provide relevant prior exams and reports (Structured Reports only) to the Modalities and Workplaces
• Receive and store new exams from the Modalities at the SDM
• Prepare images for reading
• Report new images, if required by comparing them with prior exams and reports
• Demonstrate exams at Radiological Demos
• Domonstante onations at Radiology (e.g. Surgery, Intensive Case Unit, wards, external referring physicians).
  Note:
  The workstation deployment syngo Viewing Studio is not intended for primary diagnosis.

This premarket notification covers Siemens' cnhanced PACS system SIENET Cosmos.
SIENET Cosmos is a "software only"- solution, including a backend communication and storage component and three different workplace deployments for medical imaging tasks and applications.
SIENET Cosmos is the integrated radiology suite for large radiological practices and community hospitals. Important factors are the centralized server structure, the wideranging data distribution and the overall integrated concept, ranging from scheduling the examination to reporting and archiving as well as image and report distribution.
The three SIENET Cosmos workplace deployments ...
a) syngo® Viewing Studio - for image distribution (web-based viewing application not intended for primary diagnosis!)
b) syngo® Reporting Studio - for basic reporting, inside as well as outside of the radiology (standalone workstation)
c) syngo® Reporting Studio - Advanced Application Bundle - for use inside the radiology with advanced reporting functionality
... are medical diagnostic and viewing workstations intended for manipulating, reading, reporting, viewing and communicating / distributing of radiological softcopy images and so allows radiologists and radiological technicians to receive and process all data needed.
SIENET Cosmos Image Data Management ensures all authorized personnel fast and continuous access to radiological data. It's main functionality ranges from availability of images having regard to data security, open interfaces, storage media, central system administration, back-up, software distribution to providing a flexible storage hierarchy.
The main purpose is storing and archiving of radiological softcopy images and structured (DICOM) reports.
The Workflow Management enables by integration of any HL7- / DICOM-compatible RIS (IHF Year 5) to the SIENET Cosmos PACS a consistent workflow – from patient registration to requirement scheduling to a personal worklist and supports therefore reporting, documentation or administrative tasks.
SIENET Cosmos is a "software only"-system, which will be delivered on CD-ROM / DVD and installed by Siemens service engineers. Hardware-Requirements to be met arc therefore defined.
The backend communication and storage solution (SDM) is based on the Solaris 8 operating system. The workplaces are based on Windows 2000 / Windows XP operating system.
The herewith described SIENET Cosmos supports DICOM formatted images and objects.

The provided 510(k) summary for K033831, SIENET Cosmos, does not contain explicit acceptance criteria or a detailed study proving the device meets those criteria in the traditional sense of a performance study for an AI-powered diagnostic device.

Instead, this submission is for a Picture Archiving and Communication System (PACS), which is a software-only solution for managing, viewing, reporting, and archiving medical images. For such devices, the "proof" often involves demonstrating substantial equivalence to predicate devices, adherence to recognized standards, and thorough verification and validation (V&V) testing as part of a risk management process, rather than a clinical trial with specific performance metrics like sensitivity and specificity.

Therefore, many of the requested fields cannot be directly answered from the provided text as they pertain to performance studies that are not typically required or included for PACS systems.

Here's an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

   • Acceptance Criteria: The document implies that the acceptance criteria are met by demonstrating substantial equivalence to predicate devices, adhering to general safety and effectiveness concerns, and fulfilling the intended uses as a PACS system. Specific quantitative performance metrics (e.g., accuracy, sensitivity, specificity) for image analysis are not provided, as this is a PACS system, not an AI diagnostic algorithm. The "performance" is implicitly tied to its ability to manipulate, read, report, view, communicate/distribute, and store/archive radiological softcopy images and structured reports.
   • Reported Device Performance:
     • Functional Performance: The device performs the functions of a PACS system, including image data management (storage, archiving, availability, data security, interfaces), workflow management (integration with HL7/DICOM RIS), and various workplace deployments for viewing, reporting, and advanced reporting.
     • Safety and Effectiveness: "The device labeling contains instructions for use and any necessary cautions and warning, to provide for safe and effective use of the device. Risk management is ensured via a risk analysis, which is used to identify potential hazards. These potential hazards are controlled via software development, verification and validation testing."

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

   • Not applicable/Not provided. The submission focuses on software validation and substantial equivalence, not a clinical performance study with a specific test set of patient cases.

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

   • Not applicable/Not provided. Ground truth establishment by experts is not described, as this is not a diagnostic AI algorithm study.

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

   • Not applicable/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:

   • No MRMC comparative effectiveness study was done or mentioned. This device is a PACS system, not an AI-assisted diagnostic tool in the typical sense for which such studies are conducted.

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

   • Not applicable/Not provided. The device is a system that supports human radiologists, not a standalone diagnostic algorithm.

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

   • Not applicable/Not provided. The concept of "ground truth" for diagnostic accuracy is not relevant to a PACS system's validation as presented here. The validation likely focused on functional correctness, data integrity, and compliance with standards.

8. The sample size for the training set:

   • Not applicable/Not provided. This is not an AI/machine learning model where a "training set" would be used to develop an algorithm.

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

   • Not applicable/Not provided.

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