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To be used when stereotactically localized, large diameter, breast biopsies, identified by the placement of a needle localization wire, are desired for diagnostic sampling of a mammographic abnormality that is suspicious for malignant diseasc (i.e. usually BIRADS class 4 or 5). The ABBI* device is intended to provide breast tissue for histologic examination with partial or complete removal of the imaged abnormality.

The extent of a histologic abnormality cannot be determined from its mammographic appearance. Therefore, the extent of removal of a mammographic abnormality does not predict the extent of removal of a histologic abnormality, e.g., malignancy. When the sampled mammographic abnormality or the sampled tissue is not histologically benign, it is essential that the tissue margins be examined for completeness of removal.

The device is available in 5, 10, 15 and 20mm diameters. Device diameter should be matched to desired diameter of tissue sample for diagnosis.

The Auto Suture* ABBI* System uses stereotactic mammography to target non-palpable breast abnormalitics for biopsy. The system includes a disposable biopsy device, which uses a circular scalpel and elcctrocautcry snare to excise a diagnostic sample for diagnosis.

Here's an analysis of the acceptance criteria and study details for the Auto Suture* ABBI* System based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: 106 patients.
• Data Provenance:
  • Country of Origin: Not explicitly stated, but the submission is to the U.S. FDA, suggesting the study likely took place in the USA or North America.
  • Retrospective or Prospective: Prospective study.

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

The document does not explicitly state the number of experts or their specific qualifications (e.g., "radiologist with 10 years of experience") used to establish the ground truth for the test set. However, the study focuses on "histological diagnosis" and "mammographically visible abnormality," implying the involvement of:

• Pathologists: For histological diagnosis.
• Radiologists: For identifying and confirming the removal of mammographically visible abnormalities.

4. Adjudication Method for the Test Set:

The document does not explicitly describe an adjudication method (e.g., 2+1, 3+1) for the test set. The outcomes appear to be derived from clinical practice and standard diagnostic procedures (histological examination, mammographic review).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance:

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The Auto Suture* ABBI* System is a device for tissue excision, not an AI-powered diagnostic tool. Therefore, the concept of human readers improving with AI assistance is not applicable here.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

No, a standalone (algorithm only) performance study was not done. The ABBI* System is a physical biopsy device used by a clinician, not an algorithm operating independently. The study evaluates the device's clinical performance in human-led procedures.

7. The Type of Ground Truth Used:

The ground truth used was based on:

• Histological Examination: For diagnosing benign or malignant lesions, and determining margin status.
• Radiographic Confirmation: Via specimen radiographs and post-operative mammograms to verify the removal of the mammographically visible abnormality.

8. The Sample Size for the Training Set:

This information is not provided in the document. As this is a medical device for biopsy, not a machine learning algorithm, the concept of a "training set" for an algorithm is not directly applicable. The study data represents an evaluation of the device's performance in a clinical setting.

9. How the Ground Truth for the Training Set Was Established:

This information is not applicable as there is no mention of a "training set" in the context of an AI/machine learning model for this medical device. The "ground truth" during the clinical study was established through standard medical diagnostic procedures (histology and radiology) as described in point 7.

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Like the Bard Biopsy Needle (K871390), the Auto Suture* ABBI* Breast Biopsy System is intended for obtaining biopsies from breast tissues for diagnostic purposes. The device is not intended for therapeutic excision of tissue.

Both the Auto Suture* ABBI* Breast Biopsy System, and Bard® Biopty® Instrument Biopty-Cut® Needle (K871390) are indicated for obtaining soft tissue samples under imaging control.

This 510(k) summary describes a manual surgical instrument and does not appear to involve an AI/ML device. Therefore, the requested information regarding acceptance criteria, study data, ground truth, and reader studies for an AI/ML device is not applicable to this submission.

The "PERFORMANCE" section in the provided document merely states that "Both the Auto Suture* ABBI* Breast Biopsy System and the Bard Biopsy Needle (K871390) are effective in removing a sample of tissue for biopsy." This is a general statement of intended function rather than a detailing of specific performance metrics or a study demonstrating their achievement.

For a medical device like this biopsy system, performance is typically demonstrated through:

• Bench testing: Verifying aspects like cutting efficiency, sample integrity, and mechanical function.
• Biocompatibility: Ensuring materials are safe for human contact (as noted with ISO Standard #109931).
• Sterility validation: Confirming the device can be sterilized effectively.
• Comparison to predicate device: Demonstrating substantial equivalence to a legally marketed device (the Bard Biopty instrument).

However, none of these are elaborated with specific acceptance criteria or study results in the provided summary as would be relevant for an AI/ML product.

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