(13 days)
The Computed Oral Radiology System is indicated for patients undergoing an intra-oral dental x-ray examination. It produces instant, digital, intra-oral x-ray images of a patient's mouth while reducing the necessary x-ray dosage.
The device and its predicate are small digital imaging receptors that may be used in place of dental x-ray film. The new control mechanism differs from the predicate in that image acquisition may additionally be triggered through a hardwire to an x-ray tube. This modification allows for a quicker x-ray response time and may improve ergonomics as it eliminates the need for a standalone remote module. The existing firmware has been altered to support the modified and additional hardware. The new remote module may be housed within a specified x-ray source. The modification in no way effects the fundamental technology governing image acquisition.
Based on the provided document, here's an analysis of the acceptance criteria and the study (or lack thereof) to prove the device meets them:
1. A table of acceptance criteria and the reported device performance
The document does not provide specific, quantifiable acceptance criteria or reported device performance in a table format. It states generally:
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Predetermined acceptance criteria were met. (General statement for risk analysis and validation) | Not explicitly detailed beyond the statement that criteria were met. The context implies that the device maintained its previously cleared performance characteristics despite the hardware/firmware modification. |
| Principal risk of unintended x-ray exposure evaluated; all validation activities demonstrated criteria were met. | "Bench, and third-party safety testing" was conducted. Specific results are not provided. |
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document does not specify the sample size used for any test set or the data 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)
The document does not provide information about any experts used to establish ground truth or their qualifications.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
The document does not describe any adjudication method for a test set.
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 multi-reader, multi-case (MRMC) comparative effectiveness study was not conducted. The device in question is a digital X-ray imager, not an AI-assisted diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This document describes a modification to a digital dental X-ray imaging system, which is a hardware and firmware update to improve image acquisition and ergonomics. It is not an algorithm-only or AI device, so a standalone performance study in that context is not applicable and was not performed. The "standalone" aspect in this context refers to the elimination of a "standalone remote module."
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
The document does not describe the type of ground truth used, as it doesn't detail specific performance studies where ground truth would be established for diagnostic accuracy. The focus of this 510(k) submission is on demonstrating that a modification to an existing system maintains its safety and effectiveness relative to its predicate, rather than establishing primary diagnostic efficacy with new clinical data. The "ground truth" implicitly would be that the modified system continues to produce images suitable for dental x-ray examination without increased risk of unintended x-ray exposure.
8. The sample size for the training set
The document does not discuss a training set. This is not an AI/machine learning device that would require such data.
9. How the ground truth for the training set was established
Not applicable, as there is no training set for an AI/machine learning model mentioned in the document.
Summary of the Document's Focus:
This 510(k) submission focuses on a device modification to an already cleared Computed Oral Radiology System. The modification involves a change in the control mechanism (allowing image acquisition to be triggered via a hardwire to an x-ray tube rather than a standalone remote module) and corresponding firmware alterations.
The document emphasizes demonstrating substantial equivalence to the predicate device. The "studies" mentioned are risk analysis, bench testing, and third-party safety testing, which focused on ensuring the modification did not introduce new risks (specifically unintended X-ray exposure) or alter the fundamental technology or indications for use. The acceptance criteria were therefore primarily related to safety and the maintenance of equivalence to the predicate, rather than new performance benchmarks for diagnostic accuracy.
§ 872.1810 Intraoral source x-ray system.
(a)
Identification. An intraoral source x-ray system is an electrically powered device that produces x-rays and is intended for dental radiographic examination and diagnosis of diseases of the teeth, jaw, and oral structures. The x-ray source (a tube) is located inside the mouth. This generic type of device may include patient and equipment supports and component parts.(b)
Classification. Class II.