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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 Avanto® and MAGNETOM Skyra™ with software syngo MR XA61A, consist of new and modified software and hardware that is similar to what is currently offered on the predicate device, MAGNETOM Sola with syngo MR XA51A (K221733) and MAGNETOM Vida with syngo MR XA50A (K213693).

The provided text is a 510(k) summary for MRI devices (MAGNETOM Avanto fit; MAGNETOM Skyra fit) and does not contain detailed acceptance criteria or a study proving that a specific device meets those criteria in the typical sense for an AI/ML medical device.

This document describes hardware and software updates to existing MR systems, which are general Magnetic Resonance Diagnostic Devices (MRDD). The "acceptance criteria" here are mainly related to maintaining substantial equivalence to predicate devices and conforming to recognized standards for safety and performance (e.g., IEC 60601-1, ISO 14971, NEMA standards for SNR and uniformity, and software validation guidance).

Here's a breakdown based on the information provided, highlighting why it doesn't fit the typical AI/ML device study request:

1. Table of Acceptance Criteria and Reported Device Performance

Instead of specific quantitative performance metrics for a diagnostic task (like sensitivity/specificity for disease detection), the acceptance criteria for these MR systems are based on demonstrating that new and modified components maintain safety and performance comparable to their predicate devices and adhere to relevant standards.

2. Sample size used for the test set and the data provenance

The document mentions "sample clinical images" were used for image quality assessment. However, it does not specify the sample size, country of origin, or whether the data was retrospective or prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This information is not provided. The document states that the devices are intended for use by "healthcare professionals familiar with and responsible for the acquisition and post processing of magnetic resonance images," and the images are "interpreted by a trained physician" to assist in diagnosis, but it does not detail an expert ground truth establishment process for a specific test set.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not provided.

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

No such study was mentioned. This submission is for an MR system, not an AI/ML-assisted diagnostic device, so a comparative effectiveness study of human readers with/without AI assistance would not be applicable here.

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

This is not an AI/ML algorithm-only device; it's a general MR system. Therefore, a standalone algorithm performance study is not applicable or mentioned.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

Given the nature of the device (an MR system), the "ground truth" for image quality assessment would typically be visual comparison by trained MR physicists or radiologists, ensuring that the new sequences or hardware components produce images of diagnostic quality, comparable to, or better than, existing methods. However, the exact type of ground truth (e.g., specific metrics, qualitative expert assessment) is not explicitly stated beyond "image quality assessment by sample clinical images."

8. The sample size for the training set

This information is not applicable. The document describes updates to an MR system, not a machine learning model that requires a training set.

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 for a machine learning algorithm.

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The MAGNETOM systems are indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional 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 mages 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 systems may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room display and MR-Safe biopsy needles.

MAGNETOM Aera, MAGNETOM Skyra and MAGNETOM Prisma/Prisma" with syngo MR E11C software were cleared with K153343 and MAGNETOM Avanto" and MAGNETOM Skyrafff systems with syngo MR E11C software were cleared with K162102.

To address the new feature GOKnee3D and the modifications summarized in Section 3 and furthermore described in this Premarket Notification Siemens intends to make the software application package syngo MR E11C - AP04 available to the systems mentioned above.

The additional options for the synqo MR E11C software is being made available for the following MAGNETOM MR Systems:

• . MAGNETOM Aera,
• MAGNETOM Skyra / Skyraf" ●
• MAGNETOM Prisma / Prisma™ ●
• MAGNETOM Avantofit .

Those options include a new feature with a modified sequence and modified features for the above mentioned MR systems. A high level summary of sequences, features and improvements made available for the above systems is included below.

The provided text does not contain information about specific acceptance criteria, a study proving a device meets these criteria, or detailed performance metrics. The document is a 510(k) premarket notification summary for Siemens MAGNETOM MRI systems, explaining their substantial equivalence to previously cleared devices.

It discusses:

• Device Name: MAGNETOM Aera, MAGNETOM Skyra/Skyrafit, MAGNETOM Prisma/Prismafit, MAGNETOM Avantofit with syngo MR E11C - AP04 software.
• Intended Use: Magnetic resonance diagnostic device (MRDD) for imaging internal structures and functions of the head, body, or extremities, assisting in diagnosis.
• New Feature: GOKnee3D (fast, push-button knee examination with AutoAlign knee localizer and two CAIPIRINHA SPACE sequences).
• Modified Features: SPACE with CAIPIRINHA acquisition technique, Dual Monitor support, Compressed Sensing Cardiac Cine (BEAT_CS Sequence).
• Technological Characteristics: Similar to predicate devices, conforming to IEC 62304:2006 and other standards.
• Nonclinical Tests: Performance testing for modified sequence (CAIPIRINHA SPACE), image quality assessments of new sequences/algorithms, software verification and validation.
• Clinical Tests: "No clinical tests were conducted to support the subject devices and the substantial equivalence argument; however, clinical images and LV evaluation were provided to support the argumentation and documentation which demonstrate the clinical utility and technical capabilities of the method."
• Safety and Effectiveness: Risk management via ISO 14971:2007, adherence to IEC 60601-1 series, and compliance with FDA recognized standards.
• Substantial Equivalence: Concluded based on identical intended use and similar technological characteristics to predicate devices. The hardware is unchanged.

Therefore, I cannot populate the requested table or answer the specific questions about acceptance criteria, study details, sample sizes, expert involvement, and ground truth establishment, as this information is not present in the provided text. The document explicitly states that no clinical tests were conducted, and the assessment relies on nonclinical tests and substantial equivalence to predicate devices.

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Your 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 that displays the internal structure and/or function of the head, body, or extremittes. 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 mages 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.

Your 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.

MAGNETOM Vida with software syngo MR XA10A is similar to the previous cleared predicate device MAGNETOM Skyra with syngo MR E11C (K153343) but includes new and modified hardware and software compared to MAGNETOM Skyra.

Here's a breakdown of the acceptance criteria and study information for the MAGNETOM Vida device, based on the provided text:

Preamble: It's important to note that this document is a 510(k) summary for a premarket notification for a Class II medical device (Magnetic Resonance Diagnostic Device). The primary goal of a 510(k) submission is to demonstrate "substantial equivalence" to a legally marketed predicate device, not necessarily to prove absolute efficacy in a clinical setting in the same way a PMA (Premarket Approval) might require. Therefore, the "acceptance criteria" and "device performance" are primarily focused on meeting established standards and showing that changes do not negatively impact safety or effectiveness compared to the predicate.

Acceptance Criteria and Reported Device Performance

The general acceptance criteria are that the device performs as intended and is "substantially equivalent" to the predicate device, especially regarding safety and effectiveness. The specific performance reported largely revolves around conformance to recognized standards and successful completion of verification and validation.

Table of Acceptance Criteria and Reported Device Performance:

Study Information

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

   • Clinical Study (PNS Threshold): 33 individuals. The document does not specify the country of origin or whether it was retrospective or prospective, but clinical studies for such thresholds are typically prospective.
   • Nonclinical Tests (Image Quality, Software V&V, Performance Tests): The document does not specify a numerical sample size but mentions "sample clinical images were taken" for new coils and software features. It does not provide provenance (country, retrospective/prospective) for these samples specifically, but they would likely be internal studies.

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

   • The document does not explicitly state the number or qualifications of experts used to establish ground truth for the image quality assessments, software V&V, or performance tests. However, it indicates that the interpretation of images and spectra is done "by a trained physician." For image quality assessments, it's implied that Siemens' internal experts or qualified personnel performed these.

3. Adjudication Method for the Test Set:

   • The document does not specify an adjudication method like 2+1 or 3+1 for any of the tests described.

4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

   • No MRMC comparative effectiveness study is mentioned for the entire device. The submission focuses on demonstrating substantial equivalence through compliance with standards, verification, and validation, rather than a direct comparison of reader performance with and without the new AI features (if any specific AI features are implied, they are integrated within the "new software" and not evaluated separately as AI-assisted reading).
   • There is no mention of an effect size for human readers with vs. without AI assistance.

5. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

   • No standalone performance study of an algorithm is explicitly described. The device is an MRI system, which always involves a human operator and physician interpretation. The "new software" features are part of the overall system performance, not presented as a discrete AI algorithm for standalone evaluation.

6. Type of Ground Truth Used:

   • PNS Threshold Study: The ground truth would be the observed physiological response (nerve stimulation) in the 33 individuals, used to set the safety threshold.
   • Image Quality Assessments: The ground truth would likely be internal Siemens expert assessment of expected image characteristics, clarity, and diagnostic interpretability against established quality metrics or comparisons to images from the predicate device.
   • Software V&V/Performance Tests: Ground truth would be derived from specifications, expected functional outputs, and adherence to regulatory standards.
   • General Diagnosis: The "Indications for Use" state that images and spectra, "when interpreted by a trained physician yield information that may assist in diagnosis." This implies physician interpretation is the ultimate ground truth for diagnostic purposes in clinical use, but not for the technical performance studies described in the 510(k).

7. Sample Size for the Training Set:

   • The document does not provide information on a specific training set size. This type of 510(k) submission generally does not detail the internal development and training data for software components, especially when the changes are primarily updates to an existing system, rather than a de novo AI algorithm approval.

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

   • Since no specific training set or study for algorithm training is described, the method for establishing its ground truth is not provided.

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