(62 days)
The Philips Fresco release 1, add-on to Philips Integris systems, is intended for use in a cardiovascular and vascular x-ray interventional application, viz. stent placing.
The Philips Fresco release 1 will produce an enhanced image of a deployed stent in a coronary artery. To do so, it finds the area of the stent in every image of the Fresco run by finding the radiopaque bullets on the stent delivery catheter. These areas are processed such that the final result over all run images, produces an improved image of the stent area, whereas the distracting peripheral image parts have been blurred.
This 510(k) summary for the Philips Fresco release 1 device does not contain the detailed information necessary to fully address all aspects of your request regarding acceptance criteria and a study proving device performance. The document focuses on demonstrating substantial equivalence to predicate devices rather than providing a standalone clinical study report.
However, based on the provided text, here's what can be extracted and what information is missing:
1. Table of Acceptance Criteria and Reported Device Performance
This information is not explicitly stated in the provided 510(k) summary. The document mentions that the device "will produce an enhanced image of a deployed stent" and "will improve the visualization of the stent," but it does not specify quantitative acceptance criteria (e.g., specific metrics for image quality improvement, sensitivity, specificity, etc.) nor does it report the device's performance against such criteria.
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not specified | Not specified |
2. Sample size used for the test set and the data provenance
This information is not provided in the 510(k) summary. There is no mention of a specific test set, its size, or the country of origin/retrospective/prospective nature of any data used for performance evaluation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is not provided in the 510(k) summary. No details about experts for ground truth establishment are mentioned.
4. Adjudication method for the test set
This information is not provided in the 510(k) summary. No adjudication method is described.
5. 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
There is no indication of an MRMC comparative effectiveness study in the provided text. The document describes the device as an "add-on" that "will improve the visualization," implying a technical enhancement rather than a study on human reader performance with and without the aid.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
The document describes the device's function: "To do so, it finds the area of the stent in every image... These areas are processed such that the final result... produces an improved image of the stent area..." This description suggests that the device's core functionality is indeed standalone image processing. However, a formal "standalone performance study" with specific metrics (e.g., how well the algorithm identifies stent areas, how much contrast it adds, signal-to-noise ratio improvement) is not detailed or reported in this 510(k) summary. The claim is for "enhanced stent visibility," which is a qualitative improvement from the algorithm itself.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
This information is not provided in the 510(k) summary. Given the absence of a detailed study, there's no mention of how ground truth (e.g., true stent presence, accurate stent boundaries) might have been established.
8. The sample size for the training set
This information is not provided in the 510(k) summary. There is no mention of a training set as the device is described as an image processing system that finds and processes areas. While such systems are often developed using data, a formal training set size isn't specified in this document.
9. How the ground truth for the training set was established
This information is not provided in the 510(k) summary.
Summary of what is available from the document:
- Device Function: The Philips Fresco release 1 produces an enhanced image of a deployed stent by finding the stent area through radiopaque markers and processing these areas to improve stent visualization while blurring peripheral distractions.
- Purpose: To improve stent visualization ("enhanced stent visibility") compared to basic stent visibility.
- Regulatory Pathway: 510(k) substantial equivalence to predicate devices (Philips diagnostic X-ray systems Integris H5000, Integris Allura, and Integris Allura Flat Detector).
- Safety and Effectiveness Justification: Compliance with applicable 21CFR requirements (Subchapter J - Radiological Health), UL 60950, and ACR/NEMA DICOM standard. The document states it "does not introduce new indications for use, nor does the use of the device result in any new potential hazard."
Conclusion:
The provided 510(k) summary is a regulatory document focused on demonstrating substantial equivalence. It describes the device's intended function and general safety/effectiveness through compliance with standards and comparison to predicate devices. It does not include the detailed performance study, acceptance criteria, sample sizes, or ground truth establishment methods that would be found in a comprehensive clinical or technical performance report for a newly developed device requiring such evidence.
§ 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).