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The digital mammography system MAMMOMAT B.brilliant is intended to be used for mammography exams, screening, diagnosis, biopsies and dual energy procedures under the supervision of medical professionals. Mammography images can be interpreted by either hard copy film or soft copy workstation.

With Biopsy Option: The InSpect feature for MAMMOMAT B.brilliant with HD Biopsy options is intended to provide digital X-ray images of core biopsy specimens in order to allow rapid verification that the correct tissue has been excised with the biopsy procedure.

MAMMOMAT B.brilliant is a floor-mounted, full field digital mammography system for screening, diagnostic, and biopsy procedures on standing, seated, or recumbent patients.

The system consists of an examination stand with x-ray generator, a gantry with tube housing assembly, and mammography support table, including detector and an acquisition workstation with a radiation shield. The MAMMOMAT B.brilliant comes with a variety of compression plates and a biopsy attachment for diagnostic adjunct procedures.

The MAMMOMAT B.brilliant features an updated detector, a new image acquisition chain (tube, filter, collimator) and improvements to the image acquisition workflow and biopsy workflow. Adaptations have been made to the image processing due to the new image acquisition hardware and the Soft- and hardware feature improvements. Patient positioning features like a head rest have been added.

Here's a breakdown of the acceptance criteria and study information for the MAMMOMAT B.brilliant device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Sizes Used for Test Set and Data Provenance

• Clinical Image Evaluation Test Set: 19 FFDM cases
  • 4 cases with biopsy
  • 2 cases with PRIME
  • 3 cases with contrast-enhanced mammography (TiCEM)
  • 3 of the above cases included magnification views.
• Data Provenance: Not explicitly stated regarding the origin (e.g., country) or whether it was retrospective or prospective. It is implied to be a Siemens-conducted study.

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

• Number of Experts: 3 expert readers.
• Qualifications: "Expert radiologists." No further specific qualifications (e.g., years of experience) are provided in the document.

4. Adjudication Method for the Test Set

• The document implies a consensus-based approach for the clinical image evaluation, stating, "The radiologists found all image sets to be of acceptable overall clinical image quality." However, a specific adjudication method like "2+1" or "3+1" is not detailed. It suggests independent review followed by a collective judgment of acceptability.

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

• No, a multi-reader multi-case (MRMC) comparative effectiveness study focusing on human readers' improvement with AI vs. without AI assistance was not reported. The clinical image evaluation was to determine if images from the new device (MAMMOMAT B.brilliant) were of acceptable quality and substantially equivalent to the predicate device, not to evaluate AI assistance for human readers.

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

• No, a standalone algorithm performance study was not explicitly reported as a primary clinical test for this submission. The clinical image evaluation focused on the overall image quality generated by the device for interpretation by human radiologists. The device itself (MAMMOMAT B.brilliant) is a mammography system, not primarily an AI-driven image analysis algorithm in the context of this submission.
  • Note: While the device utilizes "Image processing algorithms," the clinical evaluation was on the output images for human interpretation, not on the algorithm's standalone diagnostic performance.

7. The Type of Ground Truth Used

• Clinical Image Evaluation: Expert consensus (judgment of "acceptable overall clinical image quality" by 3 expert radiologists).
• Targeting Accuracy: Physical measurement against a phantom and calibration needle.

8. The Sample Size for the Training Set

• The document does not specify a training set size or provide details about a training set for any AI/software components within the device. The clinical evaluation focuses on comparing the new device's images to the predicate and determining acceptability, not on performance of a trained AI diagnostic algorithm.

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

• As no training set is described for an AI diagnostic algorithm, this information is not applicable and is not provided in the document. The document primarily concerns the hardware and basic image processing of a mammography system.

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