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510(k) Data Aggregation
(39 days)
OPTIM, INC.
To provide illumination for examination, diagnostic, and therapeutic applications, particularly in endoscopy.
The PLS is a stand-alone, portable, detachable adaptation of the light source embedded into the ENTity NasoView Fiberscope. The PLS is an accessory to endoscopes and other devices that require an external light source.
The provided text describes a 510(k) premarket notification for a medical device called OPTIM's "PLS" Portable Light Source. This device is an LED light source intended to provide illumination for examination, diagnostic, and therapeutic applications, particularly in endoscopy.
Based on the information provided in the document, here's a breakdown of the requested criteria:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state quantitative acceptance criteria or specific performance metrics in the way one might expect for a diagnostic or AI-driven device (e.g., sensitivity, specificity, accuracy thresholds). Instead, the performance assessment is based on demonstrating compliance with recognized medical electrical equipment standards and substantial equivalence to predicate devices.
Acceptance Criterion | Reported Device Performance |
---|---|
Safety & Effectiveness | "Performance testing demonstrates that the PLS is as safe and as effective as the predicate device." |
Electrical Safety | Declaration of conformity to IEC Medical Electrical Equipment standards: |
- 60601-1:1998
- 60601-2-18:1996
- 60601-1-2:2001 |
| Intended Use | Same intended use as the predicate devices. |
| Fundamental Scientific Technology | Same fundamental scientific technology as the light engine embedded into the ENTity NasoView Fiberscope (a predicate device). |
2. Sample size used for the test set and the data provenance
The document does not describe a "test set" in the context of collected data (e.g., images, patient records). The performance evaluation here is based on engineering testing and confirmation of compliance with standards for the device itself, rather than a study involving patient data. Therefore, there is no information about sample size or data provenance in this context.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. This is not a study requiring expert-established ground truth for a test set of data. The ground truth for device performance revolves around adherence to engineering specifications and regulatory standards.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. As noted above, there is no "test set" in the context of data requiring expert 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
No. This document pertains to a medical device (a portable light source), not an AI-driven system or a diagnostic tool that would involve human reader performance with or without AI assistance. Therefore, an MRMC study was not performed.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
Not applicable. This is a hardware device (a light source), not an algorithm.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
The "ground truth" for this device's performance is established by its compliance with recognized industry standards for medical electrical equipment (IEC 60601 series) and demonstrating that its performance is equivalent to legally marketed predicate devices in terms of safety and effectiveness for its intended use. There is no biological or clinical ground truth like pathology or outcomes data mentioned for this specific device.
8. The sample size for the training set
Not applicable. This is a hardware device, not a machine learning model, so there is no training set mentioned.
9. How the ground truth for the training set was established
Not applicable. There is no training set for this hardware device.
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(28 days)
OPTIM, INC.
For oral or nasal introduction for the examination of the upper airway from the nasal passage to the vocal cords.
The ENTity NasoView is a modification of the OL-1 Airway Fiberscope. The device has been modified to include a battery-operated LED light source internal to the device control body. An accessory charger is provided for charging the battery outside the scope.
The provided text for the OPTIM's ENTity NasoView LED Nasopharyngoscope does not contain the information requested for a detailed study description with acceptance criteria and device performance.
The document is a 510(k) summary for a Special 510(k) notice, indicating a modification to an existing device (OL-1 Airway Fiberscope). The main modification is the inclusion of a battery-operated LED light source internal to the device control body.
Here's what can be extracted and what is missing:
1. Table of Acceptance Criteria and Reported Device Performance
- Acceptance Criteria: Not explicitly stated in terms of specific performance metrics (e.g., illumination intensity, battery life, image clarity standards). The document mentions "Verification and validation activities have been completed for the device modifications" and that the modifications "do not raise any new questions of safety or effectiveness." It also states that "Validation and verification testing demonstrates that the ENTity NasoView is as safe and effective as the predicate devices." This implies that the acceptance criteria are related to maintaining the safety and effectiveness profile of the predicate device with the new LED light source.
- Reported Device Performance: No specific performance data (e.g., illumination output, battery duration, resolution, field of view) of the ENTity NasoView is provided. The document only generally states that it meets design control requirements and is as safe and effective as the predicate.
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: Not mentioned. No specific test sets are described.
- Data Provenance: Not mentioned.
3. Number of Experts Used to Establish Ground Truth and Qualifications
- Not applicable/Not mentioned. No "ground truth" establishment by experts is described as this is not a diagnostic device relying on expert interpretation of results.
4. Adjudication Method
- Not applicable/Not mentioned.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- Not done. This device is a direct visualization tool (nasopharyngoscope), not a diagnostic algorithm that requires human-in-the-loop performance evaluation or comparison against human readers. The change is a light source modification.
6. Standalone Performance Study
- Not explicitly described. While "verification and validation activities" were completed for the device modifications, the document does not detail a specific "standalone" study in the context of an algorithm's performance without human input. The validation would have been on the physical device's functionality (e.g., light output, battery performance, mechanical integrity) but this is not detailed.
7. Type of Ground Truth Used
- Not applicable in the conventional sense of diagnostic algorithms. The "ground truth" for a medical device like a nasopharyngoscope would relate to its physical and optical specifications, safety standards, and functional performance, not diagnostic accuracy against a disease state.
8. Sample Size for the Training Set
- Not applicable/Not mentioned. This is a hardware device modification, not a machine learning algorithm that requires a training set.
9. How Ground Truth for the Training Set Was Established
- Not applicable/Not mentioned.
In summary, the provided 510(k) summary focuses on demonstrating substantial equivalence of a modified medical device to its predicates based on design control requirements and general verification/validation activities. It does not contain the detailed performance metrics, study designs, sample sizes, and expert ground truth establishment that would be associated with a new diagnostic algorithm or a study proving specific performance against acceptance criteria.
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