(77 days)
The RadStar DDR Digital Imaging System is intended for use in generating radiographic images of human anatomy. This device is intended to replace film/screen systems in all general purpose diagnostic procedures. This device is intended for incorporation into a complete x-ray system by qualified x-ray service personnel. This device is not intended for mammography applications. This device is intended for use by qualified medical personnel and is contraindicated when, in the judgment of the physician, procedures would be contrary to the best interest of the patient.
The RadStar Digital Imaging System consists of two components, a solid state x-ray imager and software for viewing the captured images on a Windows-based computer. The device is intended for incorporation into a complete x-ray system by qualified x-ray service personnel. The RadStar Digital Imaging System will display high quality images in less than 5 seconds over a wide range of X-Ray dose settings.
This document is a 510(k) summary for the RadStar Digital Imaging System, describing its substantial equivalence to previously marketed devices. It does not contain the typical elements of a study proving a device meets specific acceptance criteria as it would for an algorithm or AI-powered device.
For medical devices that generate images, "acceptance criteria" are usually related to image quality metrics, safety, and performance against predicate devices. The study involved in such a submission primarily aims to demonstrate substantial equivalence to a predicate device, rather than proving performance against pre-defined quantitative acceptance criteria for a new and innovative function.
Based on the provided text, here's an analysis:
1. A table of acceptance criteria and the reported device performance
The provided text does not define specific quantitative "acceptance criteria" for performance metrics like sensitivity, specificity, accuracy, or image quality scores. This submission is for a conventional digital X-ray detector, and its performance demonstration focuses on substantial equivalence rather than novel algorithm performance.
The submission states:
- "The RadStar Digital Imaging System will display high quality images in less than 5 seconds over a wide range of X-Ray dose settings."
- "The technological characteristics between the predicate and proposed devices are identical. There is no difference in fundamental scientific technology."
- "There are no significant differences between the RadStar Digital Imaging System and the predicate devices and therefore, the RadStar Digital Imaging System does not raise any questions regarding safety and effectiveness."
- "The RadStar Digital Imaging System, as designed, is as safe and effective as the predicate device, and the device is determined to be substantially equivalent to the referenced predicate device currently on the market."
These statements serve as the "performance" claim, but they are qualitative and comparative to existing technology, not quantitative against specific, pre-defined acceptance criteria for diagnostic efficacy.
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
Not applicable. This is a submission for a digital X-ray imager, not an AI or algorithm-based diagnostic tool requiring a test set of patient data with ground truth. The "test" for this device would involve engineering and physical performance evaluations (e.g., image resolution, DQE, MTF, dose response) rather than a clinical study with patient images to evaluate diagnostic accuracy.
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)
Not applicable, as there is no mention of a "test set" of medical images requiring expert ground truth establishment.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
Not applicable, as there is no mention of a "test set" requiring adjudication.
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
Not applicable. This is not an AI-assisted device. The submission focuses on the digital imaging system itself replacing film/screen systems.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is not an algorithm, but a hardware imaging system with associated viewing software. Its performance is inherent to its image acquisition capabilities.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable. There is no "ground truth" in the clinical sense for this type of device submission. Performance is assessed through technical specifications and comparison to predicate devices.
8. The sample size for the training set
Not applicable. This device does not use machine learning or AI that requires a "training set."
9. How the ground truth for the training set was established
Not applicable, as there is no training set for this device.
§ 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.