(83 days)
Intended for use to independently review and process anglographic images outside the exam room. These images are intended to assist the physician in diagnosis and treatment planning of vessel malformations and other diseases or injuries for which digital x-ray imaging is a suitable means for visualization. Image processing functions similar to currently commercially available Siemens digital angiography systems including filtering, gray scale windowing, zoom/roam, and subtraction will be provided to support diagnosis and treatment planning as well as quantification, report and archival functions. A multimodality viewer allows viewing of images previously acquired on computer tomographs and magnetic resonance scanners, providing viewing of different modalities for the same patient on the same workstation to further support diagnosis and treatment planning.
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The provided text is a summary of a 510(k) premarket notification for the "AX Workstation," an angiographic x-ray system. This document focuses on establishing substantial equivalence to previously marketed devices rather than presenting detailed acceptance criteria and a study proving performance against them in the way a clinical trial for a novel AI diagnostic might.
Therefore, much of the requested information regarding acceptance criteria, specific performance metrics, sample sizes, ground truth establishment, expert qualifications, and detailed study methodologies is not present in the provided text. The document is primarily concerned with regulatory clearance based on the device's functional similarity to existing and legally marketed devices.
Here's a breakdown of what can and cannot be extracted from the provided text:
1. Table of Acceptance Criteria and Reported Device Performance:
This information is not provided in the document. The 510(k) submission focuses on demonstrating "substantial equivalence" of the new device to existing predicate devices (Siemens TOP ACOM Station and Camtronics Analytical Review Station). Substantial equivalence means that the device is as safe and effective as a legally marketed device and does not raise different questions of safety and effectiveness. It does not typically involve presenting specific, quantitative acceptance criteria met through a performance study in the same way a de novo device or a novel AI algorithm might.
The "performance" described is functional similarity: "Image processing functions similar to currently commercially available Siemens digital angiography systems including filtering, gray scale windowing, zoom/roam, and subtraction will be provided to support diagnosis and treatment planning as well as quantification, report and archival functions." This is a statement of intended functionality, not a metric with an acceptance threshold.
2. Sample size used for the test set and the data provenance:
- Sample size for the test set: Not provided. No specific test set or associated sample size is mentioned.
- Data provenance: Not applicable/Not provided. Since no specific test set is detailed, there's no information on data provenance (e.g., country of origin, retrospective/prospective). The document implies the functionalities are derived from existing Siemens angiography systems.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Number of experts: Not provided.
- Qualifications of experts: Not provided.
This type of information is usually relevant for studies validating diagnostic accuracy, which is not the primary focus of this 510(k) for a review workstation.
4. Adjudication method for the test set:
- Adjudication method: Not provided. As no test set is detailed, no adjudication method is mentioned.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance:
- MRMC study: Not provided. The document describes a "review workstation" for angiographic images, which provides image processing and viewing functions. It does not describe an AI algorithm or a comparative effectiveness study involving human readers with and without AI assistance. The term "AI" is not present in the document.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Standalone performance study: Not provided. This device is a workstation designed for human interaction and review; it's not described as a standalone algorithm performing automated diagnosis.
7. The type of ground truth used:
- Type of ground truth: Not applicable/Not provided. As there's no described performance study requiring a ground truth (e.g., for diagnostic accuracy), no type of ground truth is mentioned. The device's purpose is to assist diagnosis, not to make a diagnosis itself, implying human experts will establish the final diagnostic ground truth in clinical practice.
8. The sample size for the training set:
- Sample size for the training set: Not provided. This document does not describe any machine learning or AI components that would require a "training set."
9. How the ground truth for the training set was established:
- Ground truth establishment for training set: Not applicable/Not provided. Since no training set is described, no method for establishing its ground truth is mentioned.
§ 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).