(27 days)
The Sectra IDS device is intended for the manipulation and displaying of x-ray images, including mammograms. It can show images from different modalities and interfaces to various image storage and printing devices using DICOM or similar interface standards.
Device options make possible mammography reading, telecommunications; fast demonstration; prosthesis CAD; 3-D and angiography, etc .; and teleconferencing.
Typical users of this system are trained professionals, including but not limited to physicians, radiologists, nurses, medical technicians, and assistants.
The IDS5 Radiology Workstation with IDS5/mx.net is mainly a software product. It is used for visualization and processing of digital radiology images. The system runs under the Window 2000 and Windows XP operating system. The requirements on hardware are quite ordinary for a system used for displaying images. Most notably up to four monitors can be used.
Here's a breakdown of the acceptance criteria and study information for the Sectra IDS5 Radiology Workstation, based on the provided text:
Important Note: The provided document is a 510(k) Summary and the FDA's clearance letter. It focuses on demonstrating substantial equivalence to a predicate device, not on specific performance studies with detailed acceptance criteria and results in the way a clinical trial might be presented. Therefore, many of the requested details (like sample size for test sets, ground truth methodology, expert qualifications, effect size for MRMC studies, etc.) are not present in this type of document, as they are not typically required for a 510(k) for an image processing system like this. The "Performance Data" section primarily refers to compliance with standards.
Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Safety: Device does not pose undue risk to patients or users. | |
| Does not contact the patient. | Does not contact the patient. |
| Does not control life-sustaining devices. | Does not control life-sustaining devices. |
| Competent human intervention is always present. | Images and information are interpreted by a physician or trained medical personnel, providing ample opportunity for competent human intervention. |
| Protection against unauthorized use. | Passwords are required for operation and to protect against unauthorized use. |
| Recovery from failures (partial or failed transmissions, images, data). | Device failures may be recovered from storage or re-transmission after correcting the problem(s). |
| Effectiveness/Functionality: Device performs its intended functions. | |
| Visualization and processing of digital radiology images (including mammograms). | Used for visualization and processing of digital radiology images, including mammograms. |
| Runs on specified operating systems (Windows 2000, XP). | Runs under Windows 2000 and Windows XP operating system. |
| Supports up to four monitors. | Up to four monitors can be used. |
| Interfaces with various image storage and printing devices using DICOM or similar standards. | Interfaces to various image storage and printing devices using DICOM or similar interface standards. |
| Supports optional features like mammography reading, telecommunications, fast demonstration, prosthesis CAD, 3-D and angiography, teleconferencing. | Device options make possible mammography reading, telecommunications; fast demonstration; prosthesis CAD; 3-D and angiography, etc .; and teleconferencing. |
| Follows ISO 9001:2000 quality management standards. | Developed according to ISO 9001:2000. |
| Complies with ACR/NEMA Digital Imaging Communications in Medicine version 3.0. | Complies with ACR/NEMA Digital Imaging Communications in Medicine version 3.0. |
| Substantially equivalent to predicate device. | Concluded to be safe, effective, and substantially equivalent to the predicate device (Sectra IDS5 Radiology Workstation - Version 10.0, K0033088). |
Study Details:
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Sample size used for the test set and the data provenance:
- Not specified in this 510(k) summary. For image processing systems of this nature, performance testing often involves internal verification and validation against specified technical requirements rather than a formal clinical study with a "test set" of patient data in the sense of a diagnostic performance study. The focus is on functionality and safety equivalence.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not specified. Ground truth establishment is not detailed as this is not a diagnostic AI device requiring such a process for its 510(k) clearance.
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Adjudication method for the test set:
- Not specified. Adjudication is not applicable in the context of the information 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 study was done or reported. This device is a workstation for viewing and processing images, not an AI-assisted diagnostic tool designed to directly improve human reader performance in a quantifiable clinical output metric (like sensitivity or specificity).
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- No standalone performance study of an algorithm was done or reported. This device is not an algorithm that provides a diagnostic output independently; it's a tool for human interaction with images.
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The type of ground truth used:
- Not applicable/Not specified. The "ground truth" here would relate to the correct display and manipulation of images according to DICOM standards and user specifications, not a clinical diagnosis.
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The sample size for the training set:
- Not applicable/Not specified. This is not a machine learning/AI device that requires a "training set" in the conventional sense for developing a diagnostic algorithm. Its development is based on software engineering principles and compliance with standards.
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How the ground truth for the training set was established:
- Not applicable/Not specified. As mentioned above, this device does not utilize a training set in the way an AI algorithm does.
§ 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).