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This SW modification does not affect the intended use statements of the previously reviewed HP imaging platforms.

This 510(k)submittal is for a SW modification to Hewlett-Packard ultrasound imaging systems that have been previously reviewed by the FDA and found to be substantially equivalent. This SW modification provides the capability to: 1) define a region of interest (ROI) in an image; 2) quantify the average brightness level in the ROI: 3) track the brightness level versus time for the ROI.

The provided text does not contain information about acceptance criteria and a study to prove the device meets these criteria in the typical sense of a detailed clinical study with specific performance metrics and statistical analyses.

Instead, the document is a 510(k) summary for a software modification, primarily focusing on demonstrating substantial equivalence to a predicate device. The "performance" described is about functionality and characteristics, not diagnostic accuracy or effectiveness in a clinical context.

Here's an interpretation based on the provided text, addressing your points where possible, and noting when information is absent:

Acceptance Criteria and Study for Acoustic Densitometry Software Modification

The focus of this 510(k) submission is to demonstrate that a software modification to Hewlett-Packard ultrasound imaging systems, which provides the capability to define a region of interest, quantify average brightness levels, and track brightness over time, is substantially equivalent to a predicate device and does not raise new questions of safety or effectiveness.

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

The "acceptance criteria" in this context are primarily the functional and characteristic similarities to the predicate device. The table below presents the comparison provided in the document:

Interpretation of "Acceptance Criteria" and "Performance": For this 510(k), the primary "acceptance criterion" is proving substantial equivalence, meaning the new device's features are either identical, similar, or functionally superior without introducing new risks compared to the predicate device. The "reported device performance" is the functionality described for the HP Acoustic Densitometry system.

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 provided in the document. The submission focuses on a software modification's functionality and comparison to a predicate, not clinical performance data from a specific test set of images or patients. There is no mention of a "test set" in the context of clinical evaluation.

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 applicable/not provided. There is no mention of a test set requiring expert ground truth establishment for diagnostic performance.

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

This information is not applicable/not provided. There is no described test set that would require 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

An MRMC comparative effectiveness study was not performed or mentioned. This device is a measurement tool (quantifying brightness), not an AI-assisted diagnostic device, and the submission does not involve an evaluation of human reader performance.

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

A standalone performance evaluation in the context of diagnostic accuracy was not performed. The device's standalone performance is simply its ability to perform the stated functions: define ROI, quantify brightness, and track brightness over time. These are assumed to be directly testable through engineering validation, not a clinical study.

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

"Ground truth" in the diagnostic sense is not applicable here, as the device is a measurement tool, not a diagnostic one. The "truth" lies in the accuracy of its mathematical computations (e.g., correctly calculating average brightness from raw digital scan converter data), which would be verified through software validation and testing against known inputs and expected outputs.

8. The sample size for the training set

This information is not applicable/not provided. The software modification describes basic image processing functionalities, not a machine learning or AI model that requires a "training set."

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

This information is not applicable/not provided. As there's no training set, there's no ground truth establishment for one.

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