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510(k) Data Aggregation
(251 days)
MEGA ISQ
The MEGA ISQ is indicated for use in measuring the stability of implants in the oral cavity and maxillofacial region.
The MEGA ISQ is an new generation of the Osstell ISQ, (K082523) the system is designed to measure dental implant stability in the oral cavity and maxillofacial region. Similar to K082523, the MEGA ISQ is a portable, handheld instrument that involves the use of the noninvasive technique, Resonance Frequency Analysis. The system involves the use of a Smartpeg (aluminum rod) attached to the dental implant by means of a screw. The Smartpeg is excited by a magnetic pulse from the measurement probe on the handheld instrument. The resonance frequency, which is the measure of implant stability, is calculated from the response signal. Results are displayed as the Implant Stability Quotient (ISQ). The ISQ is a measurement of the stability of the implant and is derived from the resonance frequency value obtained from the Smartpeg.
The provided text describes a 510(k) premarket notification for the "MEGA ISQ" device, which is an updated version of the "Osstell ISQ" predicate device (K082523). The submission focuses on demonstrating substantial equivalence to the predicate, rather than proving novel performance.
Here's an analysis of the acceptance criteria and study information provided:
1. A table of acceptance criteria and the reported device performance
The submission does not present a formal table of acceptance criteria with corresponding performance metrics in the typical sense of a clinical study. Instead, the acceptance criteria are based on demonstrating equivalence to the predicate device through several nonclinical tests.
Acceptance Criteria Category | Specific Acceptance Criteria (Implied) | Reported Device Performance |
---|---|---|
Safety and Performance Equivalence | The device does not introduce new safety concerns or degrade performance compared to the predicate device. | "These minor differences do not affect the safety or performance of the device and do not change the intended use of the MEGA ISQ." |
Electromagnetic Compatibility (EMC) | Conformance to EN IEC 60601-1-2 (Medical electrical equipment - Part 1-2: General requirements for basic safety and essential performance - Collateral Standard: Electromagnetic compatibility - Requirements and tests). | "The proposed device passed all applicable test per IEC 60601-1-2..." |
Comparative Performance (Display) | Performance of the new LED display is equivalent to the predicate's display. | "...comparative testing of the new LED display... demonstrated equivalent performance to the declared predicate." |
Comparative Performance (USB Interface) | Performance of the USB interface (now in a dock station) is equivalent to the predicate's USB interface. | "...performance of the USB interface... demonstrated equivalent performance to the declared predicate." |
Material Biocompatibility | New materials used for the instrument and docking station are biocompatible and do not pose new risks. | "Material biocompatibility" (listed as a test) and "...biocompatibility of the new material demonstrated equivalent performance to the declared predicate." |
Sterilization Parameters | Updated steam sterilization parameters conform to ANSI/AAMI/ST79:2010/A2:2011. | "Updated steam sterilization parameters in accordance with ANSI/AAMI/ST79:2010/A2:2011" (listed as a test). The text implies compliance. |
2. Sample size used for the test set and the data provenance
The document does not describe a clinical test set with human subjects. The testing described is primarily non-clinical, focused on demonstrating engineering and material equivalence. Therefore, there is no sample size for a "test set" in a clinical sense, nor a provenance (country of origin or retrospective/prospective) for such data. The comparative performance testing was likely conducted in a lab setting.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is not applicable as there was no clinical test set requiring expert ground truth establishment. The "ground truth" for the non-clinical tests would be defined by engineering standards and predicate device specifications.
4. Adjudication method for the test set
Not applicable, as there was no clinical 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
An MRMC study was not done. The device is a direct measurement instrument (dental implant stability analyzer), not an AI-assisted diagnostic tool that would involve human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This concept is not directly applicable to the MEGA ISQ as it's a measurement device, not an algorithm-based diagnostic tool. However, the core functionality of the device (Resonance Frequency Analysis) operates autonomously to generate an ISQ value. The "standalone" performance is implicitly covered by the "Comparative performance testing to predicate" and conformance to EMC standards. The device's mechanism for calculating ISQ is independent of human interpretation during the measurement process.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
For the non-clinical and comparative performance testing, the ground truth was based on:
- Engineering Standards: For EMC testing (EN IEC 60601-1-2).
- Predicate Device Specifications/Performance: For comparative performance of the display, USB interface, and material characteristics. The performance of the predicate device (Osstell ISQ, K082523) served as the benchmark.
- Industry Standards: For sterilization parameters (ANSI/AAMI/ST79:2010/A2:2011).
8. The sample size for the training set
This is not applicable. The MEGA ISQ is a hardware device for physical measurement and does not involve machine learning or a "training set" in the context of AI.
9. How the ground truth for the training set was established
Not applicable, as there is no training set for a machine learning algorithm.
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