Search Results

IMPAX® Workstations with MPR, Digital Subtraction and 3D options are intended for use in the acquisition, display, digital processing, review, transfer, storage, archiving and printing of medical images and patient demographic information.

They are indicated for use by the physician to aid in diagnosis, and by medical professionals whenever they would require or desire access to medical images and patient demographic information.

MPR and 3D functions allow the user to view 3D image data from perspectives different from that in which it was acquired. Digital subtraction allows a user viewing time series studies to remove densities not enhanced by a contrast medium, highlighting vascular structures.

The predicate devices and IMPAX® Workstations with MPR, Digital Subtraction and 3D options are medical image management devices.

Workstation configurations include a general purpose diagnostic workstation (DS3000) and analogous versions for cardiologists (Cardio3000) and orthopedists (OT3000). A review workstation (CS5000) is available for use by persons other than the interpreting physicians; and a quality control workstation (QC3000) provides administrative functions and the ability to view and correct improper operator entries.

The multi-planar reconstruction, digital subtraction and 3D features described in this notification will be offered as options, either separately or combined on multiple workstation configurations.

This 510(k) summary (K022292) is for Agfa Corporation's IMPAX® Workstations with MPR, Digital Subtraction and 3D options. This device is a Picture Archiving and Communications System (PACS) and the submission details its substantial equivalence to predicate devices, but it does not contain specific acceptance criteria or an analytical study proving that the device meets those criteria.

Here's an analysis based on the provided text, highlighting what is present and what is missing based on your request:

1. Table of acceptance criteria and the reported device performance:

This information is not provided in the document. The 510(k) summary focuses on establishing substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria.

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 provided. The document mentions various types of testing (Unit, System, Integration, Field, Beta tests) but does not detail sample sizes for any test sets or the origin/type of data used.

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. As detailed above, there's no mention of a test set with an established ground truth in the context of human expert review.

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

This information is not provided. No adjudication method is mentioned.

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:

This information is not provided. The document describes workstations that aid in diagnosis, but it does not describe an AI system or an MRMC study to compare human readers with and without AI assistance. The device is a PACS workstation with advanced visualization features (MPR, 3D, Digital Subtraction), not an AI-powered diagnostic tool in the modern sense.

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

This information is not provided. This device is described as a "Workstation" intended for "use by the physician to aid in diagnosis" and by "medical professionals." This clearly indicates a human-in-the-loop system, not a standalone algorithm.

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

This information is not provided. The document does not describe the use of any specific ground truth for performance evaluation.

8. The sample size for the training set:

This information is not provided. The device is not described as an AI/ML device that would typically involve a "training set" in the context of algorithm development for diagnostic performance.

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

This information is not provided. As above, there's no mention of a training set for an AI/ML algorithm.

Summary of Device and Testing Mentioned in the Document:

• Device Name: IMPAX® Workstations with MPR, Digital Subtraction and 3D options
• Intended Use: Acquisition, display, digital processing, review, transfer, storage, archiving, and printing of medical images and patient demographic information. Indicated for use by physicians to aid in diagnosis and by medical professionals for access to medical images and patient demographic information.
• Key Features: Multi-planar reconstruction (MPR), Digital Subtraction, and 3D visualization.
• Substantial Equivalence: Claimed based on having the same intended use and comparable image manipulation tools as predicate devices (Philips EasyVision workstations with Endo-3D option K973983 and Quantitative Analysis option K971965).
• Testing Mentioned:
  • Unit tests (single component/module, by development personnel)
  • System tests (multiple components/modules, entire system, by independent personnel)
  • Integration tests (Agfa performance under simulated use)
  • Field tests (complete system in user setting, direct control of Agfa)
  • Beta tests (system in user setting, without immediate/direct control of Agfa)

Conclusion regarding your request:

The provided 510(k) summary for K022292 details the device's intended use, technological characteristics, and a general overview of testing procedures to ensure functionality and safety. However, it does not include any of the specific information requested regarding acceptance criteria, quantitative device performance against those criteria, details about test or training sets, ground truth establishment, expert involvement, or MRMC studies. This is typical for 510(k) submissions of this era for PACS workstations, which focused on demonstrating substantial equivalence in function and safety, rather than providing detailed diagnostic performance metrics as might be expected for AI-powered diagnostic devices today.

Ask a specific question about this device