(19 days)
Agfa's Computed Radiography Systems with NX1.0 workstations are intended for use in the identification, generation, acquisition, processing and filing of computed radiography images in order to make them ready for interpretation by the physician.
Agfa's Computed Radiography Systems with NX1.0 workstations are indicated to provide diagnostic quality images to aid the physician with diagnosis.
The predicate and newly modified devices are computed radiography imaging systems. Instead of traditional screens and photographic film for producing the diagnostic image, these systems system utilize an "imaging plate," a plate coated with photo-stimulable storage phosphors that are sensitive to X-rays and capable of retaining a latent image. After exposure, this imaging plate is inserted into a digitizer that scans it with a laser and releases the latent image in the form of light that is converted into a digital image file. The image can then be previewed on a computer workstation, adjusted if necessary then stored locally, sent to an archive, printed or sent to a softcopy capable display such as a PACS system.
The NX1.0 and QS 3.0 (predicate) workstations are similar. The NX1.0 workstation includes a number of improvements including:
- . A more intuitive user interface.
- Enhanced image processing. .
- Easier installation and updates, .
- Enhanced image manipulation, display and export capabilities, .
The basic principles of operation are unchanged.
The provided document is a 510(k) summary for a Computed Radiography System with NX1.0 Workstation. It describes device modifications and asserts substantial equivalence to a predicate device. However, it explicitly states that performance data was not included in the submission because it is a Special 510(k) for Device Modification. It instead refers to "declarations in Exhibits I and H" which certify that data demonstrates equivalence, but these exhibits are not provided in the input.
Therefore, many of the requested details about acceptance criteria, specific performance metrics, and the study design are not available in the provided text.
Here's a breakdown of what can be extracted and what is missing:
1. Table of Acceptance Criteria and Reported Device Performance
Not available in the provided document. The document states that performance data was collected to demonstrate substantial equivalence but was not included in the submission. It only generally asserts "proper performance to specifications" through in-house tests.
2. Sample size used for the test set and the data provenance
Not available in the provided document. No specific sample sizes for test sets are mentioned. The provenance of any data is also not stated.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not available in the provided document. No information regarding ground truth establishment or expert involvement in any test sets is provided.
4. Adjudication method for the test set
Not available in the provided document. No information about any adjudication methods is provided.
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
No. The device is a "Computed Radiography System with NX1.0 Workstation," which is an imaging system, not an AI-powered diagnostic tool for human readers. Its purpose is to generate, process, and file CR images for interpretation by a physician. Therefore, an MRMC comparative effectiveness study regarding "human readers improve with AI vs without AI assistance" is not relevant to this device's function or the information provided.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
Not applicable. This device is an imaging system that produces diagnostic images for human interpretation, not a standalone diagnostic algorithm. Its performance is related to image quality and system functionality, not algorithmic diagnostic accuracy.
7. The type of ground truth used
Not available in the provided document. No details on ground truth for any testing are provided.
8. The sample size for the training set
Not applicable. This is an imaging acquisition and processing system, not an AI/ML algorithm that requires a training set in the conventional sense. The "training" of such a system would involve engineering and calibration, not machine learning model training with a labeled dataset.
9. How the ground truth for the training set was established
Not applicable. As the device is not an AI/ML algorithm with a training set, this question is not relevant.
Summary of available information:
The document describes software modifications to an existing Computed Radiography system. It asserts "substantial equivalence" to a predicate device based on similar intended use and technological characteristics. Testing was conducted "for proper performance to specifications through various in-house reliability and imaging performance demonstration tests," and the device meets EN 60601-1-1 and EN 60601-1-2. However, the specific details of these "specifications," the performance metrics, the test methodology, and the results are explicitly stated as not included in the submission as it's a Special 510(k). The document relies on declarations (Exhibits I and H) that certify data demonstrates equivalence, but these exhibits are not provided.
§ 892.1680 Stationary x-ray system.
(a)
Identification. A stationary x-ray system is a permanently installed diagnostic system intended to generate and control x-rays for examination of various anatomical regions. 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). A radiographic contrast tray or radiology diagnostic kit intended for use with a stationary 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.