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Vista Scientific Barium Sulfate™ is intended for use as an additive to Codman Cranioplastic™ (Type 1-Slow set) to provide radiopacity for imaging purposes.

Vista Scientific Barium Sulfate is a dry powder supplied sterile and non-pyrogenic for use as a radiopacifying additive to Codman Cranioplastic™ (Type 1-Slow set) bone cement. The Barium Sulfate is supplied in a quantity of 6 grams, packaged in a closed 120 mL polymer container, and sealed within a double sterile peel pouch package configuration.

The provided document (K024359 for Vista Scientific Barium Sulfate) is a 510(k) summary and FDA clearance letter, which describes the device and its intended use, and states that it is substantially equivalent to a predicate device. This type of document typically does not contain the detailed performance study results you are asking for (acceptance criteria, sample sizes, ground truth establishment, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance).

The purpose of a 510(k) submission for a device like this (an additive to a bone cement to provide radiopacity) is to demonstrate substantial equivalence to a legally marketed predicate device, primarily through performance, biocompatibility, and microbiological testing. It focuses on showing the new device performs as designed and is suitable for its intended use, similar to its predicate.

Therefore, many of the specific details you requested are not available within the provided text.

However, I can extract the information that is present:

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

The document does not provide a specific table of acceptance criteria nor detailed quantitative performance metrics for the device itself (e.g., specific radiopacity values or thresholds). It broadly states:

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

This information is not provided in the document. The document mentions "Performance, biocompatibility and microbiological testing," but does not detail the sample sizes, study design (retrospective/prospective), or data provenance for these tests.

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 provided in the document. Given the nature of a radiopacifying additive, "ground truth" would likely relate to objective measurements of radiopacity rather than expert interpretation of images.

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

This information is not provided in the document.

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

An MRMC study is not applicable and was not done for this device. This device is an additive to bone cement, not an AI or imaging diagnostic tool. The concept of "human readers improve with AI" does not apply here.

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

A standalone algorithm performance study is not applicable and was not done for this device. This device is an additive to bone cement, not an algorithm.

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

The "ground truth" for a radiopacifying agent would likely be objective physical or chemical measurements of its ability to absorb X-rays and provide contrast, compared to a standard. The document does not explicitly state the specific type of ground truth, but it would not be expert consensus, pathology, or outcomes data in the traditional sense for an imaging diagnosis. The evaluation would focus on the material properties.

8. The sample size for the training set

This information is not applicable and not provided. As this is not an AI/machine learning device, there is no "training set."

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

This information is not applicable and not provided. As this is not an AI/machine learning device, there is no "training set."

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