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510(k) Data Aggregation

    K Number
    K231833
    Date Cleared
    2023-07-13

    (21 days)

    Product Code
    Regulation Number
    892.1200
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Biograph Vision.X and Biograph Vision.X Edge

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Siemens Biograph systems are combined x-ray Computed Tomography (CT) and Positron Emission Tomography (PET) scanners that provide registration and fusion of physiologic and anatomic information.

    The CT component produces cross-sectional images of the body by computer reconstruction of x-ray transmission data from either the same axial plane taken at different angles or spiral planes taken at different angles. The PET subsystem images and measures the distribution of PET radiopharmaceuticals in humans for the purpose of determining various metabolic (molecular) and physiologic functions within the human body and utilizes the CT for fast attenuation correction maps for PET studies and precise anatomical reference for the fused PET and CT images.

    The system maintains independent functionality of the CT and PET devices, allowing for single modality CT and/or PET diagnostic imaging.

    These systems are intended to be utilized by appropriately trained healthcare professionals to aid in detecting, localizing, diagnosing, staging and restaging of lesions, tumors, disease, and organ function for the evaluation of diseases and disorders such as, but not limited to, cardiovascular disease, neurological disorders, and cancer. The images produced by the system can also be used by the physician to aid in radiotherapy treatment planning and interventional radiology procedures.

    This CT system can be used for low dose lung cancer screening in high risk populations*. * As defined by professional medical societies. Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

    Device Description

    The Biograph Vision.X and Biograph Vision.X Edge PET/CT systems are combined multi-slice X-Ray Computed Tomography and Positron Emission Tomography scanners. This system is designed for whole body oncology, neurology and cardiology examinations. The Biograph Vision.X and Biograph Vision.X Edge PET/CT systems provide registration and fusion of highresolution metabolic and anatomic information from the two major components of each system (PET and CT). Additional components of the system include a patient handling system and acquisition and processing workstations with associated software.

    Biograph Vision.X and Biograph Vision.X Edge software is a command-based program used for patient management, data management, scan control, image reconstruction and image archival and evaluation. All images conform to DICOM imaging format requirements.

    The Biograph Vision.X and Biograph Vision.X Edge scanners are based on the Biograph Vision 600 and Biograph Vision 600 Edge scanners. The primary difference between the Bigoraph Vision 600 / Vision 600 Edge and Biograph Vision.X / Vision.X Edge scanners is an update to the PET detector electronics assembly (DEA) to provide for better NEMA Time of Flight Resolution.

    The software for the Biograph Vision.X and Biograph Vision.X Edge PET/CT system, which is the subject of this application, is substantially equivalent to the commercially available Biograph Vision 600 / Vision 600 Edge software (K193248). Modifications have been made to the commercially available Biograph Vision software to provide for the additional two Biograph Vision configurations. All features and functionality of the Biograph Vision.X and Biograph Vision.X Edge scanners are the commercially available Biograph Vision 600 and Biograph Vision 600 Edge PET/CT scanners (K193248).

    AI/ML Overview

    The provided text describes the regulatory submission for the Siemens Biograph Vision.X and Biograph Vision.X Edge PET/CT systems. The primary focus is on demonstrating substantial equivalence to a predicate device and outlining performance testing for the PET subsystem.

    Here's an analysis of the provided information concerning acceptance criteria and supporting studies:

    1. A table of acceptance criteria and the reported device performance:

    Performance Criteria (Acceptance)Reported Performance (Results)
    Resolution - Full Size:
    Transverse Resolution FWHM @ 1 cm (≤ 4.0 mm)Pass
    Transverse Resolution FWHM @ 10 cm (≤ 4.8 mm)Pass
    Transverse Resolution FWHM @ 20 cm (≤ 5.2 mm)Pass
    Axial Resolution FWHM @ 1 cm (≤ 4.3 mm)Pass
    Axial Resolution FWHM @ 10 cm (≤ 5.4 mm)Pass
    Axial Resolution FWHM @ 20 cm (≤ 5.4 mm)Pass
    Sensitivity @ 435 keV LLD (≥ 15 cps/kBq)Pass
    Count Rate peak NECR (≥ 250 kcps @ ≤ 36 kBq/cc)Pass
    Count Rate peak trues (≥ 1100 kcps @ ≤ 36 kBq/cc)Pass
    Scatter Fraction at peak NECR (≤ 43%)Pass
    Co-Registration Accuracy (≤ 5 mm)Pass
    Time of Flight Resolution at 5.3kBq/cc (≤ 214 ps)Pass
    10mm sphere (Contrast / Background Variability):≥ 55.0% / ≤ 10.0%
    13mm sphere (Contrast / Background Variability):≥ 60.0% / ≤ 9.0%
    17mm sphere (Contrast / Background Variability):≥ 65.0% / ≤ 8.0%
    22mm sphere (Contrast / Background Variability):≥ 70.0% / ≤ 7.0%
    28mm sphere (Contrast / Background Variability):≥ 75.0% / ≤ 6.0%
    37mm sphere (Contrast / Background Variability):≥ 80.0% / ≤ 5.0%
    Lung Residual Error (≤ 5.0%)Pass

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

    The document states that "PET Testing in accordance with NEMA NU2-2018 was conducted on the Biograph Vision Quadra system." NEMA NU2-2018 is a standard for performance measurements of PET systems, which typically involves phantom studies rather than human patient data. Therefore, there is no sample size of patients mentioned, nor is there any information about data provenance (country of origin, retrospective/prospective) because the testing described is primarily physical performance testing using standardized phantoms.

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

    Since the testing is physical performance testing using phantoms (per NEMA NU2-2018), there were no human experts involved in establishing ground truth in the way medical image interpretation would require. The ground truth for these measurements is typically defined by the physical characteristics of the phantom and the known properties of the radioactive source used, measured by precise physical instruments.

    4. Adjudication method for the test set:

    Not applicable, as the testing involves physical measurements against defined engineering specifications, not expert consensus on medical images.

    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 MRMC study was performed or reported in this document. The submission focuses on the technical performance of the PET/CT system itself, not on AI-assisted interpretation or its impact on human readers. The provided text indicates that the device itself is a PET/CT scanner, not an AI interpretation device.

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

    The device described is a PET/CT system, which acquires imaging data. It is not an algorithm for image interpretation in the sense of a standalone AI system. The performance testing outlined (NEMA NU2-2018) evaluates the physical characteristics and image quality of the scanner, not the performance of an interpretive algorithm. Therefore, this question is not applicable in the context of the provided information.

    7. The type of ground truth used:

    The ground truth for the performance testing cited (NEMA NU2-2018) is based on physical phantom measurements and engineering specifications. These are objective, quantitative measurements of the scanner's performance using standardized phantoms.

    8. The sample size for the training set:

    Not applicable. The document describes a PET/CT imaging device, not a machine learning model that requires a training set of data.

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

    Not applicable, as this is not a device based on machine learning that requires a training set with established ground truth.

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