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510(k) Data Aggregation
(21 days)
Smartxide Tetra Pro
Incision, excision, ablation, vaporization, and coagulation of body soft tissue including intraoral tissue, in medical specialities including aesthetic (dermatology and plastic surgery), otolaryngology (ENT), gynaecology, neurosurgery, dental and oral surgery and genitourinary surgery. The use with the scanning unit is indicated for ablative skin resurfacing.
The SMARTXIDE TETRA PRO DEVICE consists of a 10,600nm carbon dioxide laser (CO2) laser with 40W of maximum power. The laser energy is delivered to the treatment area via an articulated arm and a delivery accessory connected to its distal end. The articulated arm is an optical assembly that delivers free beam laser radiation. It is made up of seven mirrors placed on rotating knuckles: the mechanical accuracy of the articulated arm allows the CO2 laser beam to travel inside it and along its axis regardless of the arm orientation. The device may be used in combination with scanning units in order to achieve greater predictability and reproducibility. The use with the scanning units is indicated for layer-by-layer char-free ablation, enhancing the safety of the treatment with more uniform, accurate and controllable impact such as ablative skin resurfacing.
The overall weight is approximately 62 kg and the sizes are 42 x 122 x 54cm (W x H x D) with folded articulated arm.
Electrical requirements: 100-230V ~ 50/60Hz, 1200VA (max).
This document is a 510(k) summary for a medical device called SMARTXIDE TETRA PRO, a CO2 laser surgical instrument. As such, it does not describe acceptance criteria and a study that proves the AI/ML device meets the acceptance criteria. The document explicitly states "Clinical Performance Data: None".
Instead, it focuses on demonstrating substantial equivalence to a predicate device (DEKA Smartxide family) through non-clinical performance data, primarily electrical safety, electromagnetic compatibility, and software validation.
To directly answer your request based on the provided text, the relevant information regarding acceptance criteria and device performance is as follows:
1. Table of Acceptance Criteria and Reported Device Performance:
Acceptance Criteria (from standards) | Reported Device Performance (from testing) |
---|---|
Compliance with general requirements for basic safety and essential performance (ANSI AAMI ES60601-1) | Electrical safety testing conducted and device meets requirements |
Compliance with electromagnetic disturbances requirements (IEC 60601-1-2) | EMC testing conducted and device meets requirements |
Compliance with particular requirements for basic safety and essential performance of surgical, cosmetic, therapeutic and diagnostic laser equipment (IEC 60601-2-22) | Compliance testing conducted and device meets requirements |
Compliance with safety of laser products - Equipment classification and requirements (IEC 60825-1) | Compliance testing conducted and device meets requirements |
Software verification and validation (as per FDA Guidance for Industry and FDA Staff, "Content of Premarket Submissions for Device Software Functions") | Software verification and validation testing conducted and documented |
2. Sample size used for the test set and the data provenance: Not applicable. This document refers to non-clinical testing of the device hardware and software, not a study involving patient data or test sets in the context of an AI/ML device.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for an AI/ML device is not relevant for the type of non-clinical testing described.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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 device is not an AI-assisted device for human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable to this type of device and testing. The "ground truth" for the non-clinical tests would be the specifications and requirements defined by the relevant electrical safety, EMC, and laser safety standards.
8. The sample size for the training set: Not applicable. This is not an AI/ML device, so there is no training set in the context of machine learning.
9. How the ground truth for the training set was established: Not applicable.
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