(25 days)
The display, processing, archiving, and communication of data acquired by Emission Tomography cameras used in diagnostic radiology, including procedures for planar imaging, whole body imaging, tomographic (SPECT) imaging, positron imaging by coincidence, attenuation correction, and anatomical image registration.
XELERIS 2 PROCESSING AND REVIEW WORKSTATION (Xeleris 2) is a modification of the Xeleris (initially submitted under the name JUPITER PROCESSING AND REVIEW WORKSTATION, K024137), which was first introduced and marketed in 2003. Xeleris 2, is a computer workstation software used for the display, processing, filming, and communication of Emission Tomography and planar images (data) and hybrid imaging. As in Xeleris, it too includes capabilities to perform image corrections based on Attenuation Tomography and motion and to provide registration of anatomical and physiological images. It runs on Microsoft Windows XP based PC workstation (high resolution color monitor, keyboard, mouse, and CD-RW for archiving), an Ethernet network connection and system software. Optional DVD and optical disk archive devices are also available.
The provided document is a 510(k) summary for the GE Medical Systems XELERIS 2 PROCESSING AND REVIEW WORKSTATION. It primarily focuses on demonstrating substantial equivalence to a predicate device (the original XELERIS) rather than presenting a detailed study with specific acceptance criteria and performance metrics for a novel AI-powered diagnostic device.
Therefore, many of the requested elements (acceptance criteria table, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, and detailed ground truth information for training sets) are not present in the provided text, as this type of information is typically required for AI/ML-driven diagnostic devices, not for a software modification of an existing image processing workstation.
However, I can extract the available information related to the device's assessment:
1. Table of Acceptance Criteria and Reported Device Performance:
The document does not provide a table with specific acceptance criteria related to diagnostic performance (e.g., sensitivity, specificity, accuracy) or quantitative device performance metrics (e.g., processing speed, image quality scores) against those criteria. The evaluation is focused on safety and equivalence to the predicate device.
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size: Not specified. The document states "Results of the testing and standards conformance described above demonstrate...", but does not provide details on the specific data or cases used for this testing.
- Data Provenance: Not specified.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications:
Not applicable/Not specified. The evaluation is not based on diagnostic agreement with expert ground truth in the way an AI diagnostic algorithm would be.
4. Adjudication Method:
Not applicable/Not specified.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:
No. An MRMC comparative effectiveness study was not performed or referenced. The device is a workstation for display and processing, not a diagnostic algorithm intended to assist human readers in a comparative effectiveness study.
6. If a Standalone Performance Study was done:
No. The device is a "PROCESSING AND REVIEW WORKSTATION," implying it's a tool for human review, not a standalone diagnostic algorithm. The substantial equivalence argument is based on its functional similarity and adherence to safety standards.
7. The Type of Ground Truth Used:
Not applicable. The "ground truth" here is compliance with safety standards and functional equivalence to the predicate device, rather than a clinical diagnostic ground truth. The summary states: "The device has been evaluated for electrical, mechanical, and radiation safety, and conforms to applicable medical device safety and performance standards."
8. Sample Size for the Training Set:
Not applicable. This device is a software workstation, not an AI/ML algorithm that undergoes a "training" phase with a dataset in the typical sense.
9. How the Ground Truth for the Training Set was Established:
Not applicable.
Summary of Device Acceptance Information from the Document:
The acceptance of the XELERIS 2 PROCESSING AND REVIEW WORKSTATION is based on demonstrating substantial equivalence to its predicate device (GE Medical System's XELERIS PROCESSING AND REVIEW WORKSTATION, K024137). This equivalence is asserted through:
- Technological Characteristics: Stated as having "the same technological characteristics."
- Safety and Effectiveness Features: Stated as "comparable in key safety and effectiveness features."
- Basic Design, Construction, and Materials: Stated as using "the same basic design, construction, and materials."
- Intended Use: Stated as having "the same intended use."
- Compliance with Standards:
- 21 CFR Subchapter J Radiation Standards for Monitors
- IEC 60950 Safety of information technology equipment
- IEC 60601-1-1 Safety requirements for medical electrical systems
- IEC 60601-1-2 Requirements for safety; Electromagnetic Compatibility
- IEC 60601-1-4-Medical Electrical Equipment Part 1-4: General Requirements
- NEMA PS3, DICOM
- Quality Systems Conformance: The design and development process conforms to 21 CFR 820, and ISO 9001/EN 46001 and ISO 13485 quality systems.
The "study" referenced is a general evaluation for electrical, mechanical, and radiation safety and conformance to applicable medical device safety and performance standards. No specific clinical trial data or performance metrics are provided in this 510(k) summary, as it relies on the predicate device's established safety and effectiveness.
§ 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).