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OCS 3000® is intended to be used by qualified health-care providers to enhance the identification and visualization of oral mucosal abnormalities that may not be apparent or visible to the naked eye, such as oral cancer or premalignant dysplasia.

OCS 3000® allows for conventional oral mucosal examination and excites the tissue with multispectral lights for direct visualization of the resulting natural tissue fluorescence and reflectance, and vasculature.

OCS 3000® is also intended to be used by a surgeon to help identify diseased tissue around a clinically apparent lesion to aid in determining the appropriate margin for surgical excision. OCS 3000 eyewear is reusable polarized filtered eyewear that is worn by a health care professional to enhance the visual effects of violet light during oral exam. OCS 3000 eyewear has been designed to allow transmission of 430-580 nm light.

The TRIMIRA™ OCS 3000® is a "AA" battery operated, hand-held, multispectral oral examination light used in conventional and specialized oral examination. Accessories include safety glasses and disposable mirrors.

OCS 3000® eyewear is reusable polarized filtered eyewear that is worn by a health care professional to enhance the visual effects of violet light during oral exam. OCS 3000® eyewear has been designed to allow transmission of 430-580 nm light.

The OCS 3000 with multispectral identifi™ technology (Patent No. 7,365,844 and patents pending) uses "AA" batteries to operated high-intensity LEDs to produce white, violet and amber light. These safe, visible lights allow health professional to perform Conventional Oral Examination (COE) using white light, and specialized or enhanced visual examinations of tissue using violet and amber lights.

The OCS 3000 violet light enhances normal tissue's natural fluorescence. Visual examination under violet light shows healthy tissues in fluorescing green (when using filtered glasses) while suspicious tissue appears dark because of its loss of fluorescence. Amber light enhances the tissue's natural reflectance and makes visualization of the vasculature possible.

The direct visualization of fluorescent and reflective tissues is using the body's natural system to identify suspicious tissue quickly that may require further investigation. The loss of natural tissue fluorescence and reflectance can identify subclinical high-risk fields with cancerous and precancerous changes Clinical Cancer Research Vol. 12, 6716-6722. November 15, 2006.

The provided text is a 510(k) summary for the TRIMIRA™ OCS 3000® device, which is an oral examination light. It primarily focuses on demonstrating substantial equivalence to predicate devices and describes the device's technological characteristics and intended use. However, it does not contain information about specific acceptance criteria, a study proving the device meets these criteria, or any performance metrics from such a study.

Therefore, I cannot extract the requested information to populate the table or answer the specific questions about sample sizes, ground truth establishment, expert qualifications, or MRMC studies. The document states that the device is "substantially equivalent" to predicate devices based on its intended use and technological characteristics (fluorescence and reflectance for enhanced visualization). This generally implies that the performance is expected to be similar to the already approved predicate devices, but specific performance data or acceptance criteria are not detailed in this summary.

Based on the provided text, the following information is missing:

• A table of acceptance criteria and reported device performance.
• Sample size used for the test set and data provenance.
• Number of experts used to establish ground truth for the test set and their qualifications.
• Adjudication method for the test set.
• Whether a multi-reader multi-case (MRMC) comparative effectiveness study was done, or an effect size.
• Whether a standalone (algorithm only) performance study was done.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.) for any performance evaluation.
• Sample size for the training set.
• How the ground truth for the training set was established.

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