(9 days)
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:
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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."
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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.
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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.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not applicable/Not provided.
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If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
- 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.
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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.
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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.
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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.
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How the ground truth for the training set was established:
- Not applicable/Not provided.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).