Search Results

NEONA 1.5T MRI system is indicated for use as a magnetic resonance diagnostic device (MRDD) which produces transverse, sagittal, coronal and oblique cross-sectional images, and those display the internal structure and/or function of the head, body, or extremities. Depending on the region of interest, contrast agents may be used. These images when interpreted by trained physician yield information that may assist medical diagnosis.

The NEONA 1.5T MRI System is a 1.5T superconducting magnet MRI system which produces transverse, sagittal, coronal and oblique cross-sectional images, and those display the internal structure and/or function of the head, body, or extremities. It is composed of Magnet, Magnet Enclosure, Patient Table, Gradient Coil, Transmission Coil, Receiver Coil, Client PC, and Imaging Cabinet. The system software, Prodiva, a Windows-based software, is an interactive program with user friendly interface. The device is conformed to IEC and DICOM standards.

The sponsor, Time Medical Limited, has demonstrated the substantial equivalence of their NEONA 1.5T MRI System to a legally marketed predicate device (EMMA 1.5T MRI System, K183621) through non-clinical performance data and clinical images.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document doesn't explicitly state "acceptance criteria" in a quantified manner for comparison. Instead, it focuses on demonstrating that the NEONA 1.5T MRI System performs as well as the predicate device and complies with recognized standards, indicating that meeting these standards and achieving comparable image quality to the predicate serves as the de facto acceptance.

The "Performance Data" section in the comparative table (page 9) implicitly suggests the acceptance criteria are compliance with:

• NEMA MS standards
• IEC standards: IEC 60601-1, IEC60601-1-2, IEC60601-2-33

The reported device performance is demonstrated by the non-clinical testing results and the sample clinical images.

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

The document states: "Sample clinical images are provided to verify the claim of filing device's capability in generating images for diagnostic purposes." and "Sample clinical image sets from filing device and predicate device on same pulse sequences are provided to demonstrate the substantial equivalence of filing device to legally marketed predicate device."

• Sample Size: The exact number of clinical images or cases used in the test set is not specified in the provided document. It refers to "sample clinical images" and "sample clinical image sets."
• Data Provenance: The document does not specify the country of origin of the data nor 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

The document states that images are "interpreted by trained physician" to "assist medical diagnosis." However, it does not specify how many experts were involved in evaluating the sample clinical images for the substantial equivalence demonstration, nor does it detail their qualifications (e.g., years of experience, specific certifications).

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

The document does not specify any adjudication method used for establishing ground truth or evaluating the clinical image sets. The phrasing "interpreted by trained physician" suggests individual interpretation but doesn't detail a consensus process.

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, an MRMC comparative effectiveness study was not done.
• The device in question, NEONA 1.5T MRI System, is a Magnetic Resonance Diagnostic Device (MRDD), which is the hardware system that produces images. It is not an AI-powered diagnostic software designed to assist human readers. Therefore, the concept of "human readers improving with AI vs without AI assistance" is not applicable to this submission. The comparison is between the performance of the new MRI system and a predicate MRI system.

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

• Not applicable. The NEONA 1.5T MRI System is an imaging device, not an algorithm, and its output (images) is explicitly intended to be "interpreted by trained physician." Therefore, a standalone algorithm-only performance assessment is not relevant in this context.

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

For the evaluation of the clinical images, the implicit ground truth appears to be the diagnostic information derived from the images when interpreted by trained physicians. The comparison of images from the filing device and the predicate device on the same pulse sequences suggests a direct visual and interpretive comparison, implying that the diagnostic conclusions reached from both sets of images should be comparable. However, no specific method like "pathology" or "outcomes data" is mentioned to serve as an independent, definitive ground truth reference beyond physician interpretation of the images themselves.

8. The sample size for the training set

This information is not applicable to the submission for the NEONA 1.5T MRI System. This device is a hardware MRI system, not an AI or machine learning algorithm that requires a "training set" in the conventional sense. The "training" for such a device would relate to its manufacturing, calibration, and quality control processes to ensure image quality, not to a dataset for an AI model.

9. How the ground truth for the training set was established

This information is not applicable for the same reasons as point 8.

Ask a specific question about this device

The EMMA 1.5T MR System is a magnetic resonance diagnostic device (MRDD) which produces transverse, sagittal, coronal and oblique cross-sectional images, and those display the internal structure and/or function of the head, body, or extremities. Depending on the region of interest, contrast agents may be used. These images when interpreted by trained physician yield information that may assist medical diagnosis.

The EMMA 1.5T MRI System is a 1.5T superconducting magnet MRI system which produces transverse, sagittal, coronal and oblique cross-sectional images, and those display the internal structure and/or function of the head, body, or extremities. It is composed of Magnet, Magnet Enclosure, Patient Table, Gradient Coil, Transmission Coil, Receiver Coil, Client PC, and Imaging Cabinet. The system software, Prodiva, a Windows-based software, is an interactive program with user friendly interface. The device is conformed to IEC and DICOM standards.

The provided text is a 510(k) summary for the EMMA 1.5T MRI System. It details the device's characteristics and its substantial equivalence to a predicate device, focusing on non-clinical performance data and a comparison of clinical images.

Here's an analysis based on your request, highlighting the information available in the text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the EMMA 1.5T MRI System are largely based on compliance with various NEMA MS and IEC standards, demonstrating that its performance is equivalent to the predicate device. The text does not provide specific numerical acceptance criteria alongside numerical reported performance for each metric; instead, it states compliance with the standards.

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

The document mentions "Sample clinical images are provided to verify the claim of filing device's capability in generating images for diagnostic purposes." and "Sample clinical image sets from filing device and predicate device on same pulse sequences are provided to demonstrate the substantial equivalence."

• Sample size used for the test set: Not explicitly stated. The term "sample clinical images" suggests a limited set, but no number is given.
• Data provenance: Not explicitly stated. It is implied these are clinical images, but information on country of origin or whether they are retrospective or prospective is not provided.

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

This information is not provided in the document. The text states that the resulting images, "when interpreted by trained physician yield information that may assist medical diagnosis," but it does not detail an expert review process for a specific test set or the qualifications of any such experts.

4. Adjudication Method for the Test Set

This information is not provided in the document. There is no mention of an adjudication method like 2+1 or 3+1 for establishing ground truth on a test set.

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

A MRMC comparative effectiveness study is not mentioned in the document. The study performed focuses on demonstrating substantial equivalence through non-clinical performance and a visual comparison of sample clinical images, not on quantifying human reader improvement with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study

This is an MRI system, not an AI algorithm. Therefore, a standalone (algorithm only) performance study in the context of AI is not applicable/not performed as described for diagnostic algorithms. The performance studies are for the imaging system itself. The document mentions "Software Verification and Validation Testing," which is focused on the software's functionality and safety within the device, not its standalone diagnostic performance.

7. Type of Ground Truth Used

For the clinical image comparison, the ground truth is implicitly based on the visual interpretability of the images by a "trained physician" for diagnostic assistance. However, a formal "ground truth" (e.g., pathology, clinical follow-up) for a specific diagnostic outcome for these sample images is not explicitly stated or detailed. The comparison is about the quality and diagnostic utility of the images produced by the new device versus the predicate device.

8. Sample Size for the Training Set

This information is not applicable as the document describes an MRI system, not an AI algorithm that requires a training set in that conventional sense. The "software" in this context refers to the operating and image reconstruction software, which is traditionally developed and validated through engineering processes, not trained on radiological data like an AI model.

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

This information is not applicable for the same reason as point 8.

Ask a specific question about this device