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The Biopsy Digit-AM is intended to be used for mammographic procedures requiring stereotactic guidance, such as fine needle aspiration, needle biopsy, and guide wire placement.

The BIOPSY DIGIT-AM device uses two stereo images taken by a digital solid state camera to determine the location of a lesion in three dimensions. Once the coordinates of the lesion are determined by the BIOPSY DIGIT-AM they are used to position a needle holder such that when the physician inserts the needle or guide-wire, the tip will be precisely positioned at the pre-determined coordinates.

The provided text describes a medical device called BIOPSY DIGIT-AM, which is a mammographic system intended for stereotactic guidance in breast biopsy procedures. However, the document is a 510(k) summary for regulatory clearance and focuses on demonstrating substantial equivalence to a predicate device (BIOPSY DIGIT).

It does not contain information about specific acceptance criteria, a detailed study proving performance against those criteria, or the typical elements of an AI/algorithm-focused performance study. The document primarily asserts equivalence based on "materials used, technology applied, and functional methodology" and states that "Differences of note do not affect safety and effectiveness of the device, intended use, or application methods."

Therefore, I cannot populate the requested table and answer many of the questions directly from the provided text. The document is about a mechanical/imaging system rather than an AI or algorithm-driven diagnostic tool that would typically have the kind of performance metrics you've asked for.

Here's an attempt to address your request based on the absence of information and the nature of the device described:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance:
Not provided. The document describes a physical medical device, not an AI/algorithm trained on a dataset. Substantial equivalence for such devices often relies on engineering specifications and preclinical testing, rather than large clinical test sets with ground truth labels in the way AI algorithms do.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable. No ground truth establishment by experts for a test set is described, as this is not an AI/algorithm performance study.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable. No expert adjudication for a test set 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:
Not applicable. This device is a stereotactic guidance system, not an AI assistant for human readers. No MRMC study is mentioned.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
Not applicable. The device is a "System Mammographic" and "uses two stereo images... to determine the location of a lesion." While it uses a calculated determination, it's a physical system for guidance, not a standalone diagnostic algorithm. Its function is to determine coordinates for physical needle placement, which is then performed by a physician.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
Not applicable in the context of an AI/algorithm performance study. For a stereotactic biopsy device, the "ground truth" would implicitly be the actual pathological confirmation of the lesion's presence and type, and the device's accuracy would be measured by how closely the needle tip reaches the target. However, no such specific study or ground truth methodology for performance validation is described in this document.

8. The sample size for the training set:
Not applicable. This is not an AI/algorithm that undergoes a training phase with a dataset.

9. How the ground truth for the training set was established:
Not applicable.

Summary of what the document does indicate regarding "performance":

• Principle of Operation: It works like human binocular vision to determine 3D coordinates from two stereo X-ray images.
• Intended Use: Identical to the predicate device (BIOPSY DIGIT, K990192) for mammographic stereotactic guidance (fine needle aspiration, needle biopsy, guide wire placement).
• Substantial Equivalence: The BIOPSY DIGIT-AM is described as substantially equivalent to the predicate BIOPSY DIGIT in "materials used, technology applied, and functional methodology." The submission asserts that "differences of note do not affect safety and effectiveness of the device, intended use, or application methods."
• Performance Claim: The device "performs as well as the predicate BIOPSY DIGIT." The predicate itself was implicitly deemed safe and effective for its intended use through its prior clearance.

In essence, this 510(k) submission is a declaration of equivalence to an already cleared device, arguing that the new device has no new questions of safety or effectiveness. It does not present novel performance data against specific, defined acceptance criteria in the way a new AI algorithm might.

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