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The Disposable Brain Biopsy Needle 2.0 for brain biopsy is a single-use device intended for use in stereotactic and other guided biopsy of brain tissue, for example brain tumors. The Disposable Brain Biopsy Needle 2.0 is provided in a set.

Biopsy needles are used to perform a biopsy of brain tissue. In the area of the blunt tip, they have a lateral biopsy window (Sedan Type) on which the biopsy is obtained.

Through navigation systems or a stereotactic frame, the biopsy window is brought to the place of interest.

Brainlab cranial navigation allows the tracking and calculation of the position of instruments with attached reflective tracking marker. It is one possible method of navigation.

There are different versions of the Biopsy Needle for following use-cases:

Guide: In the use case "Guide" the Biopsy Needle shall be used with Brainlab optical cranial navigation system with Brainlab VarioGuide, Brainlab Frameless Biopsy System or Brainlab VarioGuide Robotics. Therefore, a tracking marker array attached to Biopsy Needle shall allow the depth tracking of the instrument and calculation of the cutting window position.

Frame: In the use case "Frame" the Biopsy Needle shall be used with the Elekta Leksell stereotactic frame. A defined length and exact stop shall allow the precise inserting of the Biopsy Needle in the stereotactic frame.

The provided text describes a 510(k) premarket notification for a medical device, the Disposable Brain Biopsy Needle 2.0. The core of a 510(k) submission is to demonstrate "substantial equivalence" to a legally marketed predicate device, rather than proving that the device meets specific acceptance criteria through a clinical study.

Therefore, the document does not contain the detailed information typically found in a study designed to prove a device meets acceptance criteria, especially not for an AI/ML powered device. This submission focuses on comparing the new device's design and performance characteristics to a previously cleared predicate device (K060808, BrainPro/BrainPro ACCESS).

Here's why the requested information cannot be fully provided based on the given text:

• No new clinical study details: The 510(k) process for this type of device (a modified existing device with unchanged intended use) often relies on design verification and validation testing to show that the modifications do not negatively impact safety or effectiveness, and that the new device performs comparably to the predicate. It does not typically involve human subject clinical trials with AI/ML-specific acceptance criteria.
• Focus on Substantial Equivalence: The document explicitly states, "Performance of the subject device is verified and validated through testing with the predicate device as well as by additional testing." This implies bench testing and non-clinical performance comparisons, not a clinical trial with human readers or AI algorithms.
• No AI/ML Component: The device described is a physical biopsy needle, not an AI/ML software device. Therefore, acceptance criteria related to AI/ML performance (e.g., sensitivity, specificity, reader improvement, standalone performance) are not applicable.

However, I can extract information related to the device's comparison to its predicate, which serves a similar function to demonstrating "acceptance" within the 510(k) framework for this type of device.

Based on the provided document, here's an attempt to address your questions, highlighting where the requested information is not applicable or not present:

The information provided describes a 510(k) premarket notification for a physical medical device (a brain biopsy needle), not an AI/ML-powered software. Therefore, many of the questions related to AI/ML specific performance studies (e.g., MRMC studies, standalone algorithm performance, expert consensus for AI ground truth) are not applicable to this submission. The "acceptance criteria" here are framed within the context of demonstrating substantial equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

For a 510(k) for a physical device where the intended use is identical and modifications are primarily design updates, "acceptance criteria" revolve around ensuring the new device performs as safely and effectively as the predicate. The document states:

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not specified in the provided summary. Performance testing for this type of device (bench testing) would typically involve a sample size sufficient to demonstrate consistency and equivalence, but it's not a "test set" in the context of clinical AI/ML validation data.
• Data Provenance: The testing is likely retrospective (on manufactured devices/materials) and conducted by the manufacturer (PAJUNK® GmbH Medizintechnologie) in Germany. It refers to "Design verification process" and "testing with the predicate device," implying lab-based, non-clinical tests.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• Not Applicable. This is a physical device, and the "ground truth" for its performance is established through engineering design verification and validation (bench testing, material testing, functional testing), not through expert clinical interpretation of data as it would be for an AI/ML algorithm.

4. Adjudication Method for the Test Set

• Not Applicable. As above, this isn't a study involving human readers or AI requiring adjudication of results. "Adjudication" for this device would refer to internal design control processes and quality assurance.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and effect size

• No. An MRMC study is a clinical study design used to evaluate the diagnostic accuracy of imaging interpretations, especially with AI assistance. This device is a biopsy needle, not an imaging interpretation tool.

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

• Not Applicable. This is a physical device, not an algorithm.

7. The Type of Ground Truth Used

• The "ground truth" for this device's acceptance is based on adherence to engineering specifications, functional performance requirements (e.g., ability to acquire tissue, cut precisely), material properties, and sterility assurance, as demonstrated through a rigorous design verification and validation process (bench testing, mechanical testing, material compatibility, sterilization validation). This is typically compared directly to the predicate device during testing.

8. The Sample Size for the Training Set

• Not Applicable. This is a physical device, not an AI/ML algorithm that requires a "training set." The development process involves design and manufacturing, not model training.

9. How the Ground Truth for the Training Set was Established

• Not Applicable. As above.

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