(105 days)
CAAS A-Valve has been developed to support the interventionalist during or in preparation of treatment of the aortic root. Based on a set of angiographic X-ray images an analysis is performed:
- To assist in C-arm projection selection to optimize visualization during treatment;
- To calculate dimensions of the aortic root corrected for out-of-plane magnification and foreshortening errors.
The CAAS A-Valve is a stand-alone software application intended to run on a PC with a Windows operating system. The CAAS A-Valve is designed for objective, accurate and reproducible assessment of the aortic root geometry from a set of angiographic X-ray images from different projections.
On each of the 2D images the aortic root is segmented. The segmented 2D aortic root contours in each image are used to generate a 3D reconstruction of the aortic root. A number of analysis results can be calculated:
- Optimal C-arm projection to optimize visualization during treatment;
- Dimensions of the aortic root.
Results are corrected for out-of-plane magnification and foreshortening errors.
Here's a breakdown of the acceptance criteria and study information for the CAAS A-Valve, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance:
The provided text does not explicitly state acceptance criteria in a quantitative table format. However, it does state the device's purpose and performance claims, which can be inferred as the basis for its perceived efficacy.
| Acceptance Criteria (Inferred from Intended Use/Description) | Reported Device Performance |
|---|---|
| Objective, accurate, and reproducible assessment of the aortic root geometry from angiographic X-ray images. | The CAAS A-Valve is designed for objective, accurate, and reproducible assessment of the aortic root geometry from a set of angiographic X-ray images. |
| Generation of 3D reconstruction of the aortic root from segmented 2D contours. | The segmented 2D aortic root contours in each image are used to generate a 3D reconstruction of the aortic root. |
| Calculation of optimal C-arm projection for visualization during treatment. | A number of analysis results can be calculated: Optimal C-arm projection to optimize visualization during treatment. |
| Calculation of aortic root dimensions, corrected for out-of-plane magnification and foreshortening errors. | A number of analysis results can be calculated: Dimensions of the aortic root. Results are corrected for out-of-plane magnification and foreshortening errors. |
| Support for interventionalists during or in preparation for aortic root treatment, including C-arm positioning assistance. | CAAS A-Valve has been developed to support the interventionalist during or in preparation of treatment of the aortic root. CAAS A-Valve quantifies dimensions of the aortic root and assists in C-arm positioning based on a set of angiographic images. |
| Indications for use: To assist in C-arm projection selection to optimize visualization during treatment; To calculate dimensions of the aortic root corrected for out-of-plane magnification and foreshortening errors. | |
| Substantial equivalence to predicate devices (CAAS QxA 3D and IC-Pro). | "The testing reported in this 510(k) establishes that CAAS A-Valve is [substantially equivalent] to a combination of predicate devices and is safe and effective for its intended use." |
| "The intended use and technological characteristics of CAAS A-Valve are [substantially equivalent...]" (The full phrase is cut off, but the intent is clear from the title "Substantial Equivalence"). |
2. Sample Size Used for the Test Set and Data Provenance:
The provided text does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective). It simply states: "Performance Data: CAAS A-Valve is developed, tested, validated and produced under the same Quality Assurance system applicable to the development and production of products currently marketed by Pie Medical Imaging." This is a general statement about their development process, not specific study details.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications:
The provided text does not specify the number of experts used or their qualifications for establishing ground truth for the test set.
4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set:
The provided text does not specify any adjudication method for the test set.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of Improvement:
The provided text does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it provide an effect size for human reader improvement with AI assistance. The focus of the 510(k) summary is on the device's standalone capabilities and its equivalence to predicate devices.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Study Was Done:
Yes, the information suggests that a standalone performance evaluation was done. The device is described as a "stand-alone software application" that performs "objective, accurate and reproducible assessment." The "Performance Data" section implies that the device itself was "tested" and "validated" to meet its intended functions, which primarily involve automated analysis without explicit mention of human input affecting the core measurements. The stated intended uses ("To assist in C-arm projection selection," "To calculate dimensions") are outputs of the algorithm.
7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.):
The provided text does not explicitly state the type of ground truth used for validation. Given the nature of aortic root geometry and dimensions derived from angiographic images, it is highly probable that the ground truth would have been established through expert consensus or measurements performed by highly experienced cardiologists or radiologists using established manual or semi-automated techniques on the same angiographic images. However, this is an inference, not a direct statement.
8. The Sample Size for the Training Set:
The provided text does not specify the sample size for the training set.
9. How the Ground Truth for the Training Set Was Established:
The provided text does not specify how the ground truth for the training set was established.
§ 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).