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510(k) Data Aggregation
(180 days)
uAngio AVIVA CX
The system is used to perform image guidance in diagnostic, intervention and surgical procedures. Procedures that can be performed with the system include cardiac angiography, neuro-angiography, vascular and non-vascular angiography, rotational angiography and whole body radiographic/fluoroscopic procedures.
The uAngio AVIVA CX is an angiographic X-ray system that generates X-rays through the X-ray tube, receives the signal through the flat panel detector and presents the image after D/A conversion and image post-processing.
The uAngio AVIVA CX is designed to provide intelligent, safe, and precise image guidance in cardiac, neuro, oncology, peripheral interventional, and surgical procedures.
The main components of the uAngio AVIVA CX include a C-arm stand, patient table, generator, X-ray tube, flat panel detector, collimator, grid, monitors, control module, control panel, foot switch, hand switch, V-box, and intercom.
The main software characteristics of the uAngio AVIVA CX include patient registration, patient administration, 2D&3D image viewing and post-processing, data import/archiving, filming, camera-assisted recognition function (uSpace), and voice control function (uLingo).
The provided FDA 510(k) clearance letter and summary for the uAngio AVIVA CX device do not contain detailed information about specific acceptance criteria for performance metrics (e.g., sensitivity, specificity, accuracy) typically associated with AI-driven diagnostic tools. Instead, the document focuses on non-clinical testing to ensure the device meets safety and operational specifications, as well as satisfactory image quality for clinical use.
However, based on the non-clinical testing section, we can infer some performance criteria and how the device reportedly meets them.
Here's an attempt to extract and synthesize the information provided, keeping in mind the limitations of the input regarding specific "acceptance criteria" as they would apply to an AI-driven image interpretation system:
1. Table of Acceptance Criteria and Reported Device Performance
Since this is a fluoroscopic X-ray system, the "acceptance criteria" are related to technical performance and image quality rather than diagnostic AI algorithm metrics like sensitivity or specificity.
| Feature/Metric | Acceptance Criterion (Implied/Stated) | Reported Device Performance |
|---|---|---|
| Cone Beam CT (CBCT) | ||
| C-arm positioning accuracy | Acceptable and repeatable position error. | "The position error of the C-arm is acceptable and the position is repeatable." |
| CBCT imaging performance | Fulfills requirements for in-plane uniformity, spatial resolution, reconstruction section thickness, noise, contrast to noise ratio, artifact analyses. | "The imaging performance of CBCT fulfills the requirements." |
| Radiation dose (CBCT) | CTDI of CBCT protocols fulfills the requirement. | "CTDI of CBCT protocols fulfills the requirement." |
| Fusion (Image Registration Algorithm) | ||
| Accuracy of Image Registration Algorithm (mTRE) | Mean target registration error (mTRE) less than the pixel diagonal distance. | "All the mTREs of the test cases are smaller than the voxel diagonal distance, which can achieve sub-pixel accuracy registration. Image Registration Algorithm is able to meet the verification criteria, the verification result is passed." |
| DSA (Digital Subtraction Angiography) | ||
| Dynamic range (submillimeter vessel visibility) | Submillimeter vessel simulation component is visible across all copper step wedges of the subtracted image. | "submillimeter sized blood vessels can be seen in all copper step wedges" (for four typical groups: Body, Head, Vascular, Pediatric). |
| Contrast sensitivity (low millimeter vessel visibility) | Low millimeter vascular simulation component should be visible in a copper step wedge of sufficient thickness in the subtraction image. | "the thickness of blood vessels visible in sufficiently thick copper step wedges meets the requirements." |
| 3D Roadmap (Neuro Registration Algorithm) | ||
| Accuracy of neuro registration (mTRE) | A precision of at least 1 mm (mTRE |
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