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The design of the nD Vision-220, Medical Adaptive Image Processor for Medical Applications is virtually identical to the comparative device manufactured and sold by Digivision.

The provided document is a 510(k) summary for the nD VISION-220, a Medical Adaptive Image Processor. It primarily focuses on demonstrating substantial equivalence to a previously marketed device (DigiVision's device) rather than detailing specific performance criteria or a study designed to prove those criteria.

Therefore, most of the requested information regarding acceptance criteria, study design, expert involvement, and ground truth is not available in the provided text.

Here's a breakdown of what can be gathered and what is missing:

1. A table of acceptance criteria and the reported device performance

• Acceptance Criteria: Not explicitly stated in the document. The general acceptance criterion seems to be "substantially equivalent" to the predicate device in terms of design, technology, specifications, and intended use, with minor differences having no impact on safety or effectiveness.
• Reported Device Performance: No specific performance metrics (e.g., sensitivity, specificity, accuracy, image quality scores) are reported for the nD VISION-220. The document states that the "specifications [are] similar" to the predicate device, implying similar performance, but no actual data is provided.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• This information is not available in the provided summary. No test set or specific data is mentioned.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• This information is not available in the provided summary. There is no mention of experts or ground truth establishment for a test set.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• This information is not available in the provided summary. No test set or adjudication method is described.

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

• This information is not available in the provided summary. The document does not describe any MRMC study or the use of AI assistance for human readers. This device is described as an "Adaptive Image Processor," which would likely enhance images before human interpretation, rather than an AI assisting human interpretation directly in a comparative effectiveness study.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• This information is not available in the provided summary. No standalone performance study details are provided.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)

• This information is not available in the provided summary.

8. The sample size for the training set

• This information is not available in the provided summary. No training data or training set size is mentioned.

9. How the ground truth for the training set was established

• This information is not available in the provided summary.

In summary, the provided 510(k) summary focuses solely on demonstrating substantial equivalence based on design, technology, specifications, and intended use, rather than detailing a performance study with specific acceptance criteria, test sets, or ground truth establishment. This type of summary often relies on the predicate device's existing clearance and performance, assuming similar performance for the new device due to its comparable nature.

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