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510(k) Data Aggregation

    K Number
    K240571
    Device Name
    OASIS MRI System
    Date Cleared
    2024-04-12

    (43 days)

    Product Code
    Regulation Number
    892.1000
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The OASIS MRI System is an imaging device, and is intended to provide the physician with physiological and clinical information, obtained non-invasively and without the use of ionizing radiation. The MR system produces transverse, coronal, sagittal, oblique, and curved crosssectional images that display the internal structure of the head, body, or extremities. The images produced by the MR system reflect the spatial distribution of protons (hydrogen nuclei) exhibiting magnetic resonance. The NMR properties that determine the image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2), and flow. When interpreted by a trained physician. these images provide information that can be useful in diagnosis determination.

    Anatomical Region: Head, Body, Spine, Extremities
    Nucleus excited: Proton
    Diagnostic uses: T1, T2, proton density weighted imaging
    Diffusion weighted imaging
    MR Angiography
    Image processing
    Spectroscopy
    Whole Body

    Device Description

    The OASIS MRI System is a Magnetic Resonance Imaging System that utilizes a 1.2 Tesla superconducting magnet in a gantry design. Magnetic Resonance imaging (MRI) is based on the fact that certain atomic nuclei have electromagnetic properties that cause them to act as small spinning bar magnets. The most ubiquitous of these nuclei is hydrogen, which makes it the primary nuclei currently used in magnetic resonance imaging. When placed in a static magnetic field, these nuclei assume a net orientation or alignment with the magnetic field, referred to as a net magnetization vector. The introduction of a short burst of radiofrequency (RF) excitation of a wavelength specific to the magnetic field strength and to the atomic nuclei under consideration can cause a re-orientation of the net magnetization vector. When the RF excitation is removed, the protons relax and return to their original vector. The rate of relaxation is exponential and varies with the character of the proton and its adjacent molecular environment. This re-orientation process is characterized by two exponential relaxation times, called T1 and T2. A RF emission or echo that can be measured accompanies these relaxation events.

    The emissions are used to develop a representation of the relaxation events in a three dimensional matrix. Spatial localization is encoded into the RF excitation, applying appropriate magnetic field gradients in the x, y, and z directions, and changing the direction and strength of these gradients. Images depicting the spatial distribution of the NMR characteristics can be reconstructed by using image processing techniques similar to those used in computed tomography.

    AI/ML Overview

    The provided document, a 510(k) Summary for the OASIS MRI System (K240571), describes the device and its equivalence to a predicate device (OASIS MRI System K211406). The acceptance criteria and performance study details are primarily focused on a new feature, DLR Rise.

    Here's a breakdown of the requested information:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document does not explicitly state numerical acceptance criteria for DLR Rise. Instead, the acceptance is based on expert subjective evaluation of image quality metrics and clinical acceptability.

    Acceptance CriterionReported Device Performance (DLR Rise vs. Conventional)
    Image Quality Metrics:
    SNRSuperior (statistically significant, p<0.05)
    SharpnessSuperior (statistically significant, p<0.05)
    Lesion ConspicuitySuperior (statistically significant, p<0.05)
    Overall Image QualitySuperior (statistically significant, p<0.05)
    Clinical Acceptability:
    All images with DLR RiseRated as clinically acceptable
    Performance with Artifacts:
    Images with artifacts with DLR RiseRated as better or equivalent image quality

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

    • Sample Size: 71 unique subjects (patients and volunteers).
    • Data Provenance: Imaging data collected from the U.S. and Japan. The study was retrospective, using pre-existing data or data collected specifically for this evaluation. (The text states "scanned in the anatomical regions... to provide the test datasets separately from the training and validation datasets," implying these were fresh scans for testing purposes, but the retrospective/prospective nature isn't explicitly stated for the overall study design.)

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

    • Number of Experts: Three (3) US board-certified radiologists.
    • Qualifications: Each radiologist had at least 5 years' experience since residency.

    4. Adjudication Method for the Test Set

    • Adjudication Method: Majority decision. After each radiologist reviewed the images, the combination of the three radiologists' answers was obtained by majority decision, and the combined answers were used for the evaluation.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

    • Yes, a multi-reader, multi-case study was performed.
    • Effect Size of Human Readers Improvement with AI vs. Without AI Assistance: The study directly compared images reconstructed with DLR Rise (AI-assisted) against conventional images (without DLR Rise/AI-assisted). The results indicated that for SNR, sharpness, lesion conspicuity, and overall image quality, the images with DLR Rise were superior with a statistically significant difference (p<0.05). Furthermore, all images with DLR Rise were rated as "better or equivalent" compared to images without DLR Rise, and all were clinically acceptable. This indicates a significant positive effect on image quality, which directly aids human readers. The exact quantitative effect size (e.g., AUC difference, percentage improvement) is not provided beyond the statistical significance and qualitative superiority.

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

    • No, the study design explicitly involved human readers (radiologists) reviewing and comparing the images. It was not a standalone algorithm performance evaluation. The DLR Rise is an image processing feature, not a diagnostic AI algorithm that provides direct diagnostic outputs without human interpretation.

    7. The Type of Ground Truth Used

    • Ground Truth Type: Expert consensus based on subjective evaluation of image quality metrics and clinical acceptability by three board-certified radiologists using a majority decision. There is no mention of pathology or outcomes data being used as ground truth for this image quality assessment.

    8. The Sample Size for the Training Set

    • The document states that the test datasets were provided "separately from the training and validation datasets." However, the sample size for the training set is not explicitly provided in the excerpt. It mentions that "The AI algorithm and learning condition of DLR Rise in the subject device are the same as those of DLR Rise in the reference device (K223426)." This implies the training was done for the DLR Rise algorithm itself, but the sample size for that training is not detailed in this document.

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

    • The document does not provide details on how the ground truth for the training set was established. It only states that the AI algorithm and its learning conditions for DLR Rise are the same as those in the reference device (K223426). This suggests that the ground truth establishment for training would have been part of the development/validation for the DLR Rise feature that was included in the reference device, but the specifics are not included here.
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