(36 days)
Digital Dental Intra Oral Sensor is intended to collect dental x-ray photons and convert them into electronic impulses that may be stored, viewed and manipulated for diagnostic use by dentists.
Digital Dental Intra Oral Sensor is a device which acquires digital intra-oral images. Direct digital systems acquire images with a sensor that is connected to a computer to produce an image almost instantaneously following exposure. The primary advantage of direct sensor systems is the speed with which images are acquired. For patient comfort, the ergonomic design is based on human intraoral anatomy.
Here's a breakdown of the acceptance criteria and study information for the "Digital Dental Intra Oral Sensor, EzSensor Smart" device, based on the provided text:
Important Note: The provided text is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than a comprehensive standalone performance study with detailed acceptance criteria and ground truth validation as one might find for a novel AI device. Therefore, some information, particularly regarding specific numerical acceptance criteria and a detailed multi-reader multi-case (MRMC) study, is not present.
1. Table of Acceptance Criteria and Reported Device Performance
The document doesn't explicitly state numerical acceptance criteria in a pass/fail format for diagnostic performance. Instead, it focuses on demonstrating superiority or substantial equivalence to a predicate device (EzSensor) through various technical characteristics and a comparative image review.
| Characteristic | Acceptance Criteria (Implied) | Reported Device Performance (Proposed Device) |
|---|---|---|
| Diagnostic Image Quality | Produce images allowing for correct diagnosis of a range of anatomic structures while minimizing radiation exposure to patients. Ideally, equivalent or superior to the predicate device. | Images produced by the proposed device (IOS-U15VF AND 11MODELS, both Binning Mode and Full Resolution Mode) were consistently better than the predicate device (EzSensor) in terms of diagnostic quality in most cases. Negligible difference between Binning Mode and Full Resolution Mode. All images from both devices presented no significant difficulty in evaluating a range of anatomic structures necessary for a correct diagnosis. |
| Pixel Pitch ($\mu$m) | Improved (smaller) pixel pitch compared to predicate for better resolution. | Full Resolution: 14.8 $\mu$m; Binning mode: 29.6 $\mu$m (Predicate: 35 $\mu$m) |
| DQE (6 lp/mm) | Improved DQE compared to predicate for better dose efficiency. | Full Resolution: 0.38; Binning mode: 0.34 (Predicate: 0.123) - Consistently performed better. |
| MTF (6 lp/mm) | Improved MTF compared to predicate for better resolution. | Full Resolution: 0.642; Binning mode: 0.630 (Predicate: 0.382) - Consistently performed better. |
| Linear Response to X-ray Exposure | Improved linearity (closer to 1) compared to predicate. | Very linear response, closer to 1, than the predicate device in the same dynamic range. |
| Electrical, Mechanical, Environmental Safety | Compliance with IEC/EN 60601-1 and IEC 60601-1-2 EMC standards. | Electrical, mechanical, environmental safety and performance testing according to IEC 60601-1: 2005 + CORR.1(2006) + CORR(2007) and EMC testing according to IEC 60601-1-2:2007 were performed. (Implied compliance, as the conclusion states the device is safe and effective). |
| Risk Mitigation | All identified risks successfully mitigated and accepted. | Risks analyzed with FMEA method; specific risk control measures implemented. Overall assessment concluded all risks from design change successfully mitigated and accepted. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: "Total 30 sets of radiographic image samples" were reviewed for diagnostic image quality.
- Data Provenance: The document does not specify the country of origin. It also does not explicitly state whether the data was retrospective or prospective, but given it's an evaluation of image samples, it's most likely retrospective image data captured using the devices.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
- Number of Experts: "a licensed dentist." (Singular)
- Qualifications: "licensed dentist." (No specific years of experience or subspecialty beyond general dentistry is mentioned).
4. Adjudication Method for the Test Set
- Adjudication Method: "Based on the reviewer's conclusion..." The use of a single licensed dentist for review indicates none in terms of formal adjudication (e.g., 2+1 or 3+1 consensus). The assessment relies on a single expert opinion.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done
- MRMC Study: No, a formal MRMC comparative effectiveness study was not done. The evaluation of diagnostic image quality was conducted by a single licensed dentist reviewing 30 image sets.
- Effect Size: Not applicable, as no MRMC study was performed. The comparison was qualitative by a single reviewer ("superior to EzSensor in terms of diagnostic quality in most cases").
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was Done
- This device is a digital intra-oral sensor, a hardware device that captures X-ray images, not an AI algorithm. Therefore, the concept of a "standalone (algorithm only)" performance study is not applicable. The performance tests described relate to the sensor's physical and technical image acquisition capabilities (e.g., DQE, MTF, pixel pitch) and how the images are perceived by a human reader.
7. The Type of Ground Truth Used
- Type of Ground Truth: For the diagnostic image quality assessment, the ground truth was expert opinion/consensus by a single "licensed dentist." It's an assessment of whether the images facilitate correct diagnosis, rather than being linked to independent pathology or patient outcomes data.
- For technical characteristics (pixel pitch, DQE, MTF, linearity), the "ground truth" is derived from laboratory measurements using standardized testing methods.
8. The Sample Size for the Training Set
- The document describes a hardware device (intra-oral sensor) and its associated viewing software. It does not mention any machine learning or AI components that would require a "training set." Therefore, this question is not applicable to this device submission.
9. How the Ground Truth for the Training Set was Established
- As there is no mention of a training set for an AI algorithm, this question is not applicable.
§ 872.1800 Extraoral source x-ray system.
(a)
Identification. An extraoral source x-ray system is an AC-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 outside the mouth. This generic type of device may include patient and equipment supports and component parts.(b)
Classification. Class II.