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Cervical MD™ is a digital colposcope designed to acquire images of the vagina, cervix and external genitalia. It is used to diagnose abnormalities and select areas for biopsy.

Cervical MD is a digital colposcope designed to acquire images of the vagina, cervix and external genitalia. It is used to diagnose abnormalities and select areas for hiopsy. The illumination and optical design of the device allow the user to carture ligh resolution quality images. The optical subsystem is augmented by integrated image quality assessment algorithms ensuring that focused, centered and balanced-contrast images are acquired. A liquid crystal display (LCD) provides a video display and user interface information. The acquired images can be transferred to a computer and viewed on a monitor.

The provided text describes the Cervical MD device, a digital colposcope, and its substantial equivalence to a predicate device. However, it does not include detailed acceptance criteria or a specific study proving the device meets quantitative performance criteria. The document focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than a detailed performance study with defined acceptance criteria.

Therefore, I cannot provide a table of acceptance criteria and reported performance, nor can I answer questions related to sample sizes, ground truth establishment, expert involvement, adjudication methods, or MRMC studies, as this information is not present in the provided text.

Based on the available information:

1. A table of acceptance criteria and the reported device performance: This information is not explicitly provided in the document. The document states that "Design verification testing has been conducted to verify that the device satisfies the performance requirements of the device specification and that the device performance is equivalent to the predicate device in relevant areas of comparison." However, the specific acceptance criteria and the results are not detailed.

2. Sample size used for the test set and the data provenance: This information is not provided.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: This information is not provided.

4. Adjudication method for the test set: This information is not provided.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: No, a multi-reader multi-case comparative effectiveness study is not mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The document mentions "integrated image quality assessment algorithms ensuring that focused, centered and balanced-contrast images are acquired" and "software that indicates when quality (focused, centered and balanced contrast) imagery has been acquired." This suggests some level of algorithmic performance. However, there is no standalone performance study detailing its metrics. The focus is on the device as a whole for image acquisition rather than an AI-driven diagnostic algorithm.

7. The type of ground truth used: This information is not provided. The device is intended to "diagnose abnormalities and select areas for biopsy," implying clinical assessment or pathology as potential ground truth, but this is not confirmed or detailed in the document.

8. The sample size for the training set: This information is not provided as there is no mention of a machine learning model requiring a training set in the context of a performance study.

9. How the ground truth for the training set was established: This information is not provided.

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