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CAAS QxA 3D is used for:

• 3D Reconstruction of coronary arteries and peripheral vessels from a set of angiographic X-ray images;
• Calculation of dimensions of the vessel corrected for out-of-plane magnification and foreshortening errors;
• To determine acquisition parameters for optimal imaging of part of interest on a vessel tree;
• To assist in the positioning of implantable devices in the vessel segment of interest.

The CAAS QxA 3D software is designed for use in clinical practice to support diagnoses and interventional treatment of cardiovascular conditions. The software is used by or under supervision of a cardiologist or radiologist.

Indications for use: CAAS QCA 3D: coronary arteries CAAS QVA 3D: peripheral vessels

The CAAS QxA 3D covers the QCA 3D and QVA 3D software modules intended to run on the Cardiovascular Angiography Analysis System (CAAS). The CAAS QxA-3D is designed for objective, accurate and reproducible assessment of the vessel geometry from a set of angiographic X-ray images from different projections. The variant QCA 3D is intended for coronaries and the variant QVA 3D is intended for peripheral vessels.

On each of the 2D images an arterial segment is selected resulting in automatic contour detection. The detected 2D arterial contours in each image are used to generate a 3D reconstruction of the arterial segment. A number of analysis results can be calculated.

• Vessel dimensions such as area, diameter and length;
• Reconstruction of healthy vessel shape;
• User defined subsegments analysis.

Results are corrected for out-of-plane magnification and foreshortening errors. CAAS QxA 3D features a virtual display of an implantable device on the 2D images and assists to plan its position based on the 3D reconstruction.

The provided text does not contain information about specific acceptance criteria, study design details, or performance metrics from a study to prove the device meets acceptance criteria.

The 510(k) summary (K100292) for the CAAS QxA 3D device primarily focuses on:

• Device Description and Intended Use: Explaining what the device does (3D reconstruction, vessel dimension calculation, planning for implantable devices) and who uses it (cardiologists or radiologists).
• Substantial Equivalence: Stating that the device is substantially equivalent to predicate devices (CAAS, CAAS QCA 3D, IC-Pro) based on its intended use and technological characteristics.
• Performance Data: A single, vague statement: "CAAS QxA 3D 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."

There is no mention of:

1. Specific acceptance criteria (e.g., minimum accuracy percentages, error margins).
2. A study demonstrating the device's performance against such criteria.
3. Sample sizes for test sets or training sets.
4. Data provenance, ground truth establishment methods, or expert qualifications.
5. Comparative effectiveness studies (MRMC), standalone performance, or human-in-the-loop performance.

Therefore, I cannot populate the requested table or answer the specific questions about the study from the provided document. The document confirms that the FDA concluded the device is "safe and effective for its intended use" based on the substantial equivalence argument and the company's QA system, but it does not detail the underlying performance data or studies that would typically be used to demonstrate meeting acceptance criteria.

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Detect the contour of the coronary vessel from a set of angiographic X-ray images – Generate absolute measurements about the dimensions of the coronary arterial segment in 3D space to improve accuracy by elimination of out-of-plane and foreshortening errors.

The CAAS OCA 3D is one of the software modules intended to run on the Cardiovascular Angiography Analysis System mark. CAAS. It functions in the same manner as other vascular analysis software packages. The OCA-3D module allows accurate and reproducible quantification of the coronary arteries from a set of angiographic X-ray images. The analyst selects between 2 and 5 angiographic images obtained from different X-Ray projections. On each of the images a classic 2D arterial detection is performed, after which from all images a reconstruction of the arterial segment is obtained in 3D space. Indication of a common point in each of the images is used to obtain an exact spatial relationship between the images. After the selection of the arterial segment of interest the contour of this arterial segment is automatically detected. Based on the contour information a number of analysis results can be calculated. Three analysis methods are available: The first method is an automatic reconstruction of the diseased arterial vessel by means of computing the reference along the arterial vessel to reconstruct the healthy arterial vessel, calculation of main result the % of stenosis. The second method allows for manual definition of the reference along the arterial segment by means of selecting one or more reference positions in the arterial segment, calculation of main result the % of stenosis. The third analysis method enables the user to define one or more subsegments, within each user defined subsegment the minimum, maximum and mean area are calculated. Besides area information also diameter results for each image used to reconstruct the vessel into 3D space are calculated over the arterial positions of interest. These diameter results will be corrected for out of plane calibration and length measurements will be corrected for foreshortening errors.

I am sorry, but the provided text does not contain sufficiently detailed information to complete all sections of your request. The document is primarily a 510(k) summary for the CAAS QCA 3D software package, establishing its substantial equivalence to a predicate device. It describes the device's functionality and intended use but does not present a specific study with acceptance criteria and detailed performance metrics in the format you've requested.

Here's an attempt to answer the questions based on the available information:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria or report specific performance metrics for the CAAS QCA 3D device. It mentions that "The CAAS QCA 3D software produces similar results as the predicate device" (K052988), implying that its performance is implicitly accepted if it matches the predicate. The focus is on its ability to detect contours and generate measurements for coronary arterial segments, correcting for out-of-plane and foreshortening errors.

Since specific criteria and performance values are not provided, I cannot generate this table.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not explicitly stated in the provided text. The document refers to its functionality with "a set of angiographic X-ray images" but does not detail any specific test set used for performance evaluation or its provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not provided in the document.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not provided in the document.

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

A MRMC comparative effectiveness study is not mentioned. The document describes a software package for quantitative analysis, not an AI-assisted interpretation tool for human readers in the context of improving their performance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

The document describes the CAAS QCA 3D as "one of the software modules intended to run on the Cardiovascular Angiography Analysis System mark. CAAS." It performs "automatic detection" and "automatic reconstruction," implying standalone algorithmic processing. However, it also mentions the "analyst selects" images and arterial segments, suggesting a human-in-the-loop workflow where the software assists the user in quantification. No specific "standalone" performance study is detailed with metrics.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

This information is not provided. The document focuses on "automatic reconstruction of the diseased arterial vessel by means of computing the reference along the arterial vessel to reconstruct the healthy arterial vessel" and contour detection. The implicitly accepted ground truth would likely be established through validated methods for quantitative coronary analysis, potentially comparing against other established QCA systems or phantom studies, but this is not detailed.

8. The sample size for the training set

The document does not mention a training set, as it emphasizes that the device consists of "reused algorithms with the addition of several improvements that do not influence the indications for use." This suggests the algorithms were developed and validated prior to this submission, possibly without a distinct "training set" in the context of this specific 510(k).

9. How the ground truth for the training set was established

As no training set is mentioned for this specific submission, its ground truth establishment is not discussed.

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