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The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.

The subject devices, MAGNETOM Sola, MAGNETOM Altea, MAGNETOM Sola Fit with software syngo MR XA51A, consist of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Vida with syngo MR XA50A (K213693).

This FDA 510(k) summary describes the Siemens Medical Solutions USA, Inc. MAGNETOM Sola, MAGNETOM Altea, MAGNETOM Sola Fit with syngo MR XA51A, a magnetic resonance diagnostic device (MRDD).

Here's an analysis of the provided text for acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state a specific "test set" in the context of clinical images or patient data for evaluating the performance of the new/modified features. The performance testing conducted was primarily focused on non-clinical tests (software, electrical, mechanical, EMC).

Therefore:

• Sample size for the test set: Not applicable and not specified for clinical performance evaluation.
• Data Provenance: Not applicable and not specified. The document only mentions "sample clinical images were provided" but doesn't detail their use in performance testing or their origin.

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

Not applicable. This document focuses on the technical safety and performance of the MR system itself (hardware and software functionalities) rather than the diagnostic accuracy of an AI algorithm on patient data. Therefore, there's no mention of experts establishing a "ground truth" for a test set of images.

4. Adjudication Method for the Test Set

Not applicable for the reasons mentioned above.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. The document explicitly states: "No additional clinical tests were conducted to support substantial equivalence for the subject devices..." and "no additional clinical publications were needed referenced to provide information on the use of the following features and functions, since this was sufficiently done for the predicate device."

Therefore, an MRMC study was not conducted or referenced for these new/modified features.

6. Standalone Performance Study (Algorithm Only)

No. The document's performance testing section focuses on the integrated system's safety and functionality (software V&V, electrical, mechanical, EMC). There is no mention of a standalone algorithm performance study for a diagnostic task.

7. Type of Ground Truth Used

Not applicable. The "ground truth" concept (e.g., expert consensus, pathology, outcome data) typically applies to the evaluation of diagnostic algorithms against a gold standard. The reported performance tests are for the safety and functionality of the MR system and its software, where the "ground truth" is adherence to engineering specifications and regulatory standards.

8. Sample Size for the Training Set

Not applicable. The document describes the device as a magnetic resonance diagnostic device, not an AI-powered diagnostic algorithm that requires a "training set" of data in the machine learning sense. The "training" implied in the context of "myExam Autopilot" is about simplifying human user interaction, not about training a diagnostic AI model.

9. How Ground Truth for the Training Set Was Established

Not applicable for the reasons mentioned above.

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