(68 days)
The intended use of the SCEPTRE-VS is to review, process, film and store multi-modality images acquired from other diagnostic imaging systems or workstations.
The SCEPTRE-VS is a workstation/server consisting of a computer, keyboard, mouse, monitor, network interface ;optional storage device(s) such as magneto-optical disk ,compact disk amd magnetic tape; and optional film digitizer. The computer workstation is PC based utilizing the latest Intel Pentium technology. The operating system is Windows 2000/XP. The Sceptre-VS workstation is used to store, process, view and print diagnostic medical images from diagnostic imaging systems conforming to DICOM 3.0 including x-ray, MRI, CT, PET, Nuclear Medicine and Ultrasound. Several proprietary image formats can also be accomodated. The optional Fusion 7D fusion module can be used for fusion of 2 modalities such as CT/PET, MRI/PET to provide crossmodality comparison.
This 510(k) summary (K021314) describes the SCEPTRE-VS, a PACS workstation/server intended for reviewing, processing, filming, and storing multi-modality images. The provided document does not contain the detailed study information typically found in acceptance criteria and performance evaluation sections of a modern medical device submission.
Here's an analysis based on the provided text, highlighting the absence of crucial information:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not explicitly stated: No specific quantitative or qualitative performance criteria (e.g., accuracy, speed, image quality metrics) are provided in the document. | Not reported: The document states "The device operates in a manner substantially equivalent to other cleared devices in this category, and performs as well as the predicate Hermes." This is a general statement of equivalence and not a report of specific performance metrics against defined criteria. |
2. Sample Size for the Test Set and Data Provenance
- Sample Size: Not specified.
- Data Provenance: Not specified. The document mentions accommodating DICOM 3.0 images from various modalities (x-ray, MRI, CT, PET, Nuclear Medicine, Ultrasound) and "several proprietary image formats," implying a variety of sources but no specific origin or type of study (retrospective/prospective) for a test set.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified.
4. Adjudication Method
- Adjudication Method: Not specified.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- MRMC Study: No mention of an MRMC study. This type of study is typically used for AI-assisted diagnostic devices to quantify the improvement in human reader performance. The SCEPTRE-VS, being a PACS workstation, is focused on image management and display rather than AI-driven diagnosis.
- Effect Size of Human Reader Improvement: Not applicable, as no MRMC study is mentioned.
6. Standalone (Algorithm Only) Performance Study
- Standalone Study: No mention of a standalone performance study. The device is described as a "workstation/server" for image review and processing, not as a standalone diagnostic algorithm. While it has an "optional Fusion 7D fusion module," no performance study specific to this module or the overall system as an algorithm is detailed.
7. Type of Ground Truth Used
- Type of Ground Truth: Not specified. Given the device's function as a PACS, the "ground truth" would likely relate to the accurate display, storage, and manipulation of images, rather than a diagnostic 'truth' in the clinical sense. However, no specific method for verifying this is provided.
8. Sample Size for the Training Set
- Sample Size: Not applicable/Not specified. The SCEPTRE-VS, as described, is a PACS workstation, not a machine learning model that would require a "training set." Its function is to display, process, and store images.
9. How Ground Truth for the Training Set Was Established
- Method: Not applicable/Not specified, as no training set is relevant for this type of device.
Summary of Device and Context:
The SCEPTRE-VS, submitted in 2002, is a Picture Archiving and Communication System (PACS). At the time of this submission, the regulatory requirements and expectations for demonstrating "acceptance criteria" and "study results" were different from those applied to modern AI/ML medical devices. This document primarily focuses on establishing substantial equivalence to a predicate device (Nuclear-Diagnostics HERMES Workstation) by comparing technological characteristics, materials, and functional methodology, rather than providing detailed performance metrics from a specific study against a pre-defined ground truth. The FDA's letter confirms the determination of substantial equivalence based on the provided information, allowing the device to be marketed.
§ 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).