(24 days)
2D Quantitative Analysis is a post processing software medical device intended to assist physicians through providing quantitative information as additional input for their comprehensive diagnosis decision making process and planning during cardiovascular procedures and for post procedural evaluation. 2D Quantitative Analysis consists of six applications:
The 2D Quantitative Coronary Analysis application is intended to be used for quantification of coronary artery dimensions (approximately 1 to 6 mm) from 2D angiographic images.
The 2D Quantitative Vascular Analysis application is intended to be used for quantification of aortic and peripheral artery dimensions (approximately 5 to 50 mm) from 2D angiographic images.
The 2D Left Ventricle Analysis and the Biplane 2D Left Ventricle Analysis applications are intended to be used for quantification of left ventricular volumes and local wall motion from biplane angiographic series. respectively.
The 2D Right Ventricle Analysis and the Biplane 2D Right Ventricle Analysis applications are intended to be used for quantification of right ventricular volumes and local wall motion from biplane angiographic series, respectively.
2D Quantitative Analysis is a software application that assists the user with quantification of
- · vessels and vessel obstructions,
- · ventricular volumes and
- ventricular wall motion
from angiographic X-ray images. The software provides semi-automatic contour detection of vessels, catheters and the left ventricle in angiographic X-ray images, where the end-user is able to edit the contours. 2D Quantitative Analysis implements computational models for the quantification of vessels, obstructions in vessels, ventricular volumes and ventricular local wall motion from 2D contours.
The proposed 2D Quantitative Analysis will be offered as an optional accessory to the Philips Interventional X-ray systems.
This looks like a 510(k) premarket notification for a medical device called "2D Quantitative Analysis" from Philips Medical Systems. Let's break down the information to answer your request.
It's important to note that this document is a 510(k) summary, which often focuses on demonstrating substantial equivalence to a predicate device rather than presenting extensive de novo clinical studies with detailed acceptance criteria and performance tables as might be expected for novel devices or PMAs.
Here's an analysis based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly present a table of numerical acceptance criteria (e.g., sensitivity, specificity, accuracy thresholds) for the device's performance, nor does it provide a direct quantifiable "reported device performance" against such criteria in the context of human-level tasks. Instead, the "acceptance criteria" appear to be met through demonstration of compliance with standards and successful completion of verification and validation testing, confirming it "conforms to its specifications" and "intended use and user needs."
The primary performance claim for the 2D Quantitative Analysis device is its ability to quantify:
- Vessel and vessel obstructions
- Ventricular volumes
- Ventricular wall motion
From angiographic X-ray images, with semi-automatic contour detection and user editing capabilities.
The document states:
- "Dedicated phantom based algorithm validation testing has been performed to ensure sufficient accuracy and agreement with the predicate device. Results demonstrated that the algorithm confirms to its specifications."
- "Non-clinical software validation testing covered the intended use and commercial claims as well as usability testing with representative intended users. Results demonstrated that the 2D Quantitative Analysis conforms to its intended use and user needs."
Therefore, the acceptance criteria are implicitly satisfied by the successful completion of these tests and demonstrating substantial equivalence. Specific numerical performance metrics against defined thresholds are not provided in this summary.
2. Sample Size Used for the Test Set and the Data Provenance
The document mentions "Dedicated phantom based algorithm validation testing" and "Non-clinical software validation testing." However, it does not specify the sample size (number of cases/patients or phantoms) used for these test sets.
The data provenance is also not explicitly stated as retrospective or prospective clinical data from specific countries. The testing appears to be primarily phantom-based and non-clinical software validation, rather than clinical studies using patient data.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
The document does not specify the number of experts or their qualifications used to establish ground truth for any test set. The validation appears to be against "specifications" and "predicate device agreement," which for phantom studies would likely involve known measurements or highly controlled scenarios rather than expert consensus on clinical images in the traditional sense.
4. Adjudication Method for the Test Set
Since the document does not describe the use of human experts to establish ground truth on clinical images, an "adjudication method" for a test set (like 2+1 or 3+1) is not applicable or mentioned.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size
The document explicitly states: "2D Quantitative Analysis, did not require clinical data since substantial equivalence to the currently marketed Allura Xper FD series and Allura Xper OR Table series was demonstrated..."
Therefore, an MRMC comparative effectiveness study, particularly one measuring the effect size of human readers with vs. without AI assistance, was not performed or, at least, not presented in this 510(k) summary. The device is a "post processing software medical device intended to assist physicians through providing quantitative information," implying it's a tool for physicians, but its impact on human reader performance was not quantified in a comparative study here.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done
The document states: "Dedicated phantom based algorithm validation testing has been performed to ensure sufficient accuracy and agreement with the predicate device. Results demonstrated that the algorithm confirms to its specifications."
This "phantom based algorithm validation testing" could be considered a form of standalone performance assessment, as it would evaluate the algorithm's output against known phantom measurements or the predicate's performance, without direct human interaction during the measurement process. However, the device is described as having "semi-automatic contour detection... where the end-user is able to edit the contours," indicating a human-in-the-loop design in its intended clinical use. The "standalone" testing here would likely refer to the algorithm's ability to generate measurements from specific inputs accurately.
7. The Type of Ground Truth Used
For the "dedicated phantom based algorithm validation testing," the ground truth was likely derived from known physical dimensions or precisely measured values from the phantoms. For "non-clinical software validation testing," ground truth would be based on the established "intended use and user needs" and the device's functional specifications. Pathology or outcomes data are not mentioned.
8. The Sample Size for the Training Set
The document does not provide any information about the sample size used for a training set. This is typical for 510(k) submissions focusing on substantial equivalence, especially for devices that may not rely on machine learning models trained on large datasets in the way that some modern AI devices do. The description of the device's functionality (semi-automatic contour detection, computational models) suggests a more rule-based or traditional image processing approach rather than deep learning, though the exact methodologies are not detailed.
9. How the Ground Truth for the Training Set Was Established
Since no training set information is provided, how its ground truth was established is also not discussed.
§ 892.1650 Image-intensified fluoroscopic x-ray system.
(a)
Identification. An image-intensified fluoroscopic x-ray system is a device intended to visualize anatomical structures by converting a pattern of x-radiation into a visible image through electronic amplification. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II (special controls). An anthrogram tray or radiology dental tray intended for use with an image-intensified fluoroscopic x-ray system only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9. In addition, when intended as an accessory to the device described in paragraph (a) of this section, the fluoroscopic compression device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.