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510(k) Data Aggregation
(301 days)
Park Dental Research Aligners are indicated for the treatment of tooth malocclusion in patients with permanent dentition (i.e. all second molars). Park Dental Research Aligners positions teeth by way of continuous gentle force.
The Park Dental Research Aligners device is fabricated of clear thin thermoformed polyurethane plastic in a sequential series to progressively reposition the teeth. Corrective force to straighten the teeth is delivered via minor changes into a position in each subsequent aligner.
This document, K180648, is a 510(k) premarket notification for the "Park Dental Research Aligners." It appears to be a submission demonstrating substantial equivalence to a predicate device, rather than a submission for a novel artificial intelligence/machine learning (AI/ML) device that would typically involve extensive performance testing against acceptance criteria for AI algorithms.
Therefore, the provided text does not contain the information requested in points 1-9, as it describes a traditional medical device (clear aligners) and seeks clearance based on its similarity to an existing device, not based on AI/ML performance. The "Non-Clinical Performance Testing" section primarily discusses material biocompatibility and manufacturing validation related to software for fabrication, but this is not an AI/ML algorithm performance study.
Therefore, I cannot extract the requested information from the provided text.
To illustrate what a response would look like if the document contained AI/ML device performance data, here's a hypothetical structure and explanation of what each point would cover:
Hypothetical Acceptance Criteria and Study Proof (If this were an AI/ML device submission):
This section is not based on the provided document K180648, as the document does not describe the performance testing of an AI/ML algorithm for a medical device. It is a hypothetical example of what the requested information would look like if the submission were for an AI/ML device.
1. Table of Acceptance Criteria and Reported Device Performance:
| Performance Metric | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Primary Endpoints | ||
| Sensitivity (for Condition A Detection) | ≥ 90% | XX% |
| Specificity (for Condition A Detection) | ≥ 85% | YY% |
| Secondary Endpoints (if applicable) | ||
| AUC (for Classification) | ≥ 0.92 | ZZ |
| Agreement with expert readers (Kappa) | ≥ 0.80 | WW |
| Processing Time per case |
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