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510(k) Data Aggregation

    K Number
    K152602
    Device Name
    Olea Sphere V3.0
    Manufacturer
    Date Cleared
    2016-03-03

    (174 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Olea Sphere V3.0

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

    Olea Sphere V3.0 is an image processing software package to be used by trained professionals including but not limited to physicians and medical technicians. The software runs on a standard "off-the-shelf" workstation and can be used to perform image viewing, processing, image collage and analysis of medical images are acquired through DICOM compliant imaging devices and modalities.

    Olea Sphere V3.0 provides both viewing and analysis capabilities of functional and dynamic imaging datasets acquired with MRI or other relevant modalities, including a Diffusion Weighted MRI (DWI) / Fiber Tracking Module and a Dynamic Analysis Module (e.g. dynamic exogenous or endogenous contrast enhanced imaging data for MRI and CT). The DWI Module is used to visualize local water diffusion properties from the analysis of diffusion-weighted MRI data. The Fiber Tracking feature utilizes the directional dependency of the white matter structure in the brain or more generally the central nervous system.

    The Dynamic Analysis Module is used for visualization and analysis of dynamic imaging data, showing properties of changes in contrast while repeating acquisitions (e.g. over time without variable acquisition parameters) where such techniques are useful or necessary. This functionality is referred to as:

    Perfusion Module - the calculation of parameters related to tissue flow (perfusion) and tissue blood volume.

    Permeability Module - the calculation of parameters related to leakage of injected contrass material from intravascular to extracellular space.

    Arterial Spin Labeling (ASL) Module - the calculation of parameters related to tissue flow based on a MR technique using the water in arterial blood as endogenous tracer to evaluate the perfusion.

    Relaxometry Module - the calculation of parameters related to the MR longitudinal and transversal relaxation time and rate.

    Metabolic Module - the calculation of parameters related to the fat fraction based on a MR technique using opposedphase imaging.

    Device Description

    Olea Sphere V3.0 is a medical viewing, analysis and processing, Picture Archiving Communications System (PACS) software, compliant with the DICOM standard and running on Windows or Linux operating systems.

    Olea Sphere V3.0 allows the display, analysis and post-processing of medical images. These images, when interpreted by a trained physician, may yield clinically useful information.

    The software provides a wide range of basic image processing and manipulation functions, in addition to comprehensive dynamic image processing and display. The main features of the software are:

    • Image Loading & Saving
    • Image Viewing
    • Image Manipulation
    • Image Analysis
    • Imaging Processing
    • Perfusion post-processing
    • Permeability post-processing
    • Arterial Spin Labeling (ASL)
    • Diffusion-Weighted Imaging (DWI) / Tensor Imaging post-processing (DTI) / Intra-Voxel Incoherent Motion (IVIM)
    • Fiber Tracking post-processing
    • Collage
    • Relaxometry post-processing
    • Metabolic post-processing

    Depending on the purpose of the imaging, the following optional plug-in are used by the software:

    • DWI (for MR imaging)
    • DTI (for MR imaging)
    • Perfusion (for MR and CT imaging)
    • Permeability (for MR and CT imaging)
    • Kinetics (for MR imaging)
    • ASL (for MR imaging)
    • Analysis (for MR and CT imaging)
    • Olea Vision (for MR imaging)
    • IVIM (for MR imaging)
    • Collage (for MR imaging)
    • Metabolic (for MR imaging)
    • Relaxometry (for MR imaging)

    The main users of the program are medical imaging professionals who need to visualize and analyze images acquired primarily with MRI or CT systems. Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations

    AI/ML Overview

    The provided text describes Olea Sphere V3.0, an image processing software package, and its substantial equivalence to predicate devices, but it does not contain the detailed acceptance criteria or a specific study proving the device meets acceptance criteria in the format requested.

    The document is a 510(k) summary for FDA clearance, which focuses on demonstrating substantial equivalence to previously cleared devices rather than a standalone clinical study with detailed performance metrics against specific acceptance criteria.

    Therefore, the following information is not available in the provided text:

    • A table of acceptance criteria and reported device performance.
    • Sample sizes used for the test set and data provenance (country of origin, retrospective/prospective).
    • Number of experts used to establish ground truth and their qualifications.
    • Adjudication method for the test set.
    • Multi-reader multi-case (MRMC) comparative effectiveness study results or effect size of AI assistance.
    • The type of ground truth used (e.g., pathology, outcomes data).
    • Sample size for the training set.
    • How ground truth for the training set was established.

    The document states that "Internal verification and validation testing confirms that the product specifications are met, in support of the substantial equivalence of the intended use and technological characteristic as the predicate devices." It also lists the main groups of tests performed as: Product Risk Assessment, Software modules verification tests, and Software validation test. However, it does not provide the specifics of these tests or their results in terms of acceptance criteria.

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    K Number
    K132095
    Device Name
    OLEA SPHERE
    Manufacturer
    Date Cleared
    2013-12-26

    (171 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    OLEA SPHERE

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

    Olea Sphere is an image processing software package to be used by trained professionals including but not limited to physicians and medical technicians. The software runs on a standard "off-the-shelf" workstation and can be used to perform image viewing, processing and analysis of medical images. Data and images are acquired through DICOM compliant imaging devices and modalities.

    Olea Sphere provides both viewing and analysis capabilities of functional and dynamic imaging datasets acquired with MRI or other relevant modalities. including a Diffusion Weighted MRI (DWI) / Fiber Tracking Module and a Dynamic Analysis Module (dynamic contrast enhanced imaging data for MRI and CT).

    The DWI Module is used to visualize local water diffusion properties from the analysis of diffusion-weighted MRI data. The Fiber Tracking feature utilizes the directional dependency of the diffusion to display the white matter structure in the brain or more generally the central nervous system.

    The Dynamic Analysis Module is used for visualization and analysis of dynamic imaging data, showing properties of changes in contrast over time where such techniques are useful or necessary. This functionality is referred to as:

    Perfusion Module - the calculation of parameters related to tissue flow (perfusion) and tissue blood volume.

    Permeability Module - the calculation of parameters related to leakage of injected contrast material from intravascular to extracellular space.

    Device Description

    Olea Sphere is a medical viewing, analysis and processing software package (PACS) compliant with the DICOM standard and running on Windows, Macintosh or Linux operating systems.

    Olea Sphere allows the display, analysis and post-processing of medical images.

    These images, when interpreted by a trained physician, may vield clinically useful information.

    AI/ML Overview

    The provided text describes a submission for 510(k) clearance for the Olea Sphere v2.3, a Picture Archiving Communications System (PACS) with advanced imaging analysis capabilities. However, it explicitly states that no clinical testing was conducted in support of this version. Instead, the substantial equivalence to its predicate device (Olea Sphere) is based on non-clinical performance data and the proven safety and efficacy of similar devices already on the market.

    Therefore, many of the requested details about acceptance criteria, study design, ground truth, experts, and sample sizes for clinical validation are not applicable to this submission as no such studies were performed for the Olea Sphere v2.3 itself.

    Here's a breakdown of the available information based on your request:

    1. Table of Acceptance Criteria and Reported Device Performance:

    Since no clinical studies were performed for Olea Sphere v2.3 to establish new clinical acceptance criteria, the "performance" described is largely a comparison to its predicate device and adherence to general PACS standards. The submission highlights technological updates rather than new clinical outcome performance metrics.

    Feature / CriterionReported Device Performance (Olea Sphere v2.3 vs. Predicate)
    Image Analysis: Volume of Interest (VOI) SegmentationEnhanced automatic volume segmentation: The new version includes a "Region-based volume segmentation" method equivalent to region growing. However, the segmentation remains "always supervised by the user" who "can always adjust the segmentation with the existing manual delineation tools."
    Image Analysis: Visualization & ComparisonEnhanced visualization and comparison: New features include "Histogram normalization" and "Image subtraction."
    Perfusion Deconvolution AlgorithmNew probabilistic, Bayesian method added: The fundamental scientific technology remains the same (perfusion model and deconvolution process). Bayesian probability is cited as a standard methodology known to outperform SVD in terms of accuracy. References [1, 2, 3] are provided for the SVD and Bayesian methods.
    Permeability ModelingT1-mapping for signal conversion & new output parameters: The fundamental scientific technology (kinetic modeling and compartmental models) is the same. The addition of T1-mapping allows loading additional MR sequences for converting transient signal response into concentration values, which are "more and more commonly acquired in clinical settings." New output maps include PEAK_ENHANCEMENT, CURVE_WASHOUT, SER, and T10. This also enables permeability parameter estimation "in case of acquisitions with a lower temporal resolution."
    Diffusion Weighted Imaging/Tensor ImagingMotion Correction: The existing motion correction algorithm (from perfusion and permeability modules) is now available in the DWI and DTI module. 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    Software Configuration and Module ExecutionEnhanced configuration and workflow: The software now allows user-defined settings and workflow-driven use, where a workflow is a sequence of modules executed in a wizard mode. Factory pre-defined settings are now editable through the user interface, not just property files.
    General Acceptance (Implicit for PACs Device)Complies with applicable voluntary standards related to PACS systems. Passed all testing in accordance with national and international standards. Provides reliable post-processing and display of images for instantaneous multi-parametric analysis. Provides all capabilities necessary to operate safely and effectively through stress testing of all components. 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    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

    • Not Applicable (N/A). No clinical testing was conducted for Olea Sphere v2.3. The submission focuses on non-clinical verification and validation.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

    • N/A. No clinical testing was conducted.

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

    • N/A. No clinical testing was conducted.

    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:

    • N/A. No clinical testing was conducted. The device is a PACS with analysis tools, not specifically an AI-assisted diagnostic tool in the sense of an MRMC study with human readers improving with AI.

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

    • While the document mentions "stress testing" and "verification and validation testing" of software components (non-clinical performance data), it does not detail any standalone performance studies in a clinical context. The device is explicitly stated to be "used by trained professionals" for image viewing, processing, and analysis, implying a human-in-the-loop use case.

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

    • N/A. For the non-clinical testing, the "ground truth" would likely refer to expected computational outputs or adherence to DICOM standards, rather than clinical ground truth derived from expert consensus or pathology. The document does not specify the ground truth methods for its non-clinical verification.

    8. The sample size for the training set:

    • N/A. No clinical testing or machine learning model training (in the modern AI sense requiring large labeled datasets) is described in the context of this 510(k) submission. The new features (like Bayesian deconvolution) are described as standard methodologies rather than novel machine learning models requiring extensive training data specific to this device.

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

    • N/A. As no dedicated training set for a clinical machine learning model is mentioned, this is not applicable.
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    K Number
    K120196
    Device Name
    OLEA SPHERE
    Manufacturer
    Date Cleared
    2012-04-19

    (87 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    OLEA SPHERE

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

    Olea Sphere is an image processing software package to be used by trained professionals including but not limited to physicians and medical technicians. The software runs on a standard "off-the-shelf" workstation and can be used to perform image viewing, processing and analysis of medical images. Data and images are acquired through DICOM compliant imaging devices and modalities.

    Olea Sphere provides both viewing and analysis capabilities of functional and dynamic imaging datasets acquired with MRI or other relevant modalities, including a Diffusion Weighted MRI (DWI) / Fiber Tracking Module and a Dynamic Analysis Module (dynamic contrast enhanced imaging data for MRI and CT).

    The DWI Module is used to visualize local water diffusion properties from the analysis of diffusion-weighted MRI data. The Fiber Tracking feature utilizes the directional dependency of the diffusion to display the white matter structure in the brain or more generally the central nervous system.

    The Dynamic Analysis Module is used for visualization and analysis of dynamic imaging data, showing properties of changes in contrast over time where such techniques are useful or necessary. This functionality is referred to as:

    Perfusion Module - the calculation of parameters related to tissue flow (perfusion) and tissue blood volume.

    Permeability Module - the calculation of parameters related to leakage of injected contrast material from intravascular to extracellular space.

    Device Description

    Olea Sphere is a medical viewing, analysis and processing software package (PACS) compliant with the DICOM standard and running on Windows, Macintosh or Linux operating systems.

    Olea Sphere allows the display, analysis and post-processing of medical images.

    These images, when interpreted by a trained physician, may yield clinically useful information.

    The software provides a wide range of basic image processing and manipulation functions, in addition to comprehensive dynamic image processing and display.

    The main features of the software are:

    • Image Loading & Saving
    • Image Viewing
    • Image Manipulation
    • Image Analysis
    • Imaging Processing
    • Perfusion Post-processing
    • Permeability Post-processing
    • Diffusion Weighted Image / Tensor Image Post-processing
    • Fiber Tracking Post-processing

    The main users of the program are medical imaging professionals who need to visualize and analyze images acquired primarily with MRI or CT systems. Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations.

    AI/ML Overview

    The provided document describes the Olea Sphere PACS software, which is intended for viewing, processing, and analyzing medical images, including functional and dynamic imaging datasets from MRI and CT.

    Please note: This document primarily focuses on establishing substantial equivalence to predicate devices and outlines the device's features and intended use. It does not contain a detailed study proving the device meets specific performance acceptance criteria through quantitative metrics. Instead, it relies on the established performance of its predicate devices and a general statement of internal validation.

    Here's an breakdown based on the information available:


    1. Acceptance Criteria and Reported Device Performance

    The document does not explicitly state quantitative acceptance criteria or detailed performance metrics like sensitivity, specificity, or AUC for specific tasks. Instead, it asserts that the Olea Sphere performs "substantially equivalent" to its predicate devices in terms of intended use, environment of use, limitations of use, principles of operation, and performance characteristics.

    The "performance characteristics" section in the comparison table (pages 11-12) lists the main software features expected and implies that the new device performs these features similarly to the predicates.

    Acceptance Criteria (Implied)Reported Device Performance
    Functional Equivalence: Ability to perform core PACS functionsOlea Sphere provides image loading & saving, viewing, manipulation,
    (Image Loading/Saving, Viewing, Manipulation, Processing).and processing, perfusion maps, and diffusion weighted imaging/tensor
    imaging maps (per pages 11-12).
    Dynamic Image Analysis: Visualization and analysis ofOlea Sphere performs dynamic analysis, including dedicated analysis
    dynamic imaging data, including perfusion and permeabilitymethods and visualization tools for dynamic contrast-enhanced imaging
    modules.data (MRI/CT), calculation of parameters related to tissue flow
    (perfusion) and tissue blood volume, and leakage (permeability) (per
    pages 10-11).
    DWI/Fiber Tracking: Visualization of water diffusionOlea Sphere's DWI Module visualizes local water diffusion properties
    properties and display of white matter structure.and the Fiber Tracking feature displays white matter structure in the
    brain or central nervous system (per pages 9-10).
    Substantial Equivalence to Predicates:Olea Sphere is substantially equivalent to Nordic Image Control and
    Demonstrated equivalence in intended use, environment of use,Evaluation (nordicICE) Software (K090546) and shares identical
    limitations, principles of operation, and performance characteristics.software architecture for many features with Perfscape V2.0 (K111161)
    (per page 13).

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

    The document does not provide details on the sample size of a test set (e.g., number of images or cases) used for performance validation. It states that "OLEA Medical has conducted extensive validation testing of the Olea Sphere system," but does not specify the dataset used for these tests. Therefore, data provenance (country of origin, retrospective/prospective) is also not indicated.


    3. Number of Experts and Qualifications for Ground Truth

    The document does not mention the use of experts to establish a ground truth for a test set. This type of information is typically provided for studies assessing diagnostic accuracy, which is not the focus of this submission, as it mainly aims to demonstrate functional equivalence for a PACS viewing and analysis software.


    4. Adjudication Method

    No adjudication method is described, as there is no mention of a study involving expert readers and ground truth establishment.


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

    No MRMC comparative effectiveness study is mentioned. The document aims to demonstrate substantial equivalence to existing PACS systems, not to quantify improvement with AI assistance. The device description suggests a tool for analysis, but there is no mention of it being an "AI" device in the context of improving human reader performance.


    6. Standalone (Algorithm Only) Performance Study

    No standalone performance study is mentioned with quantitative metrics. The validation described is likely functional (e.g., software testing, verification) rather than a clinical performance study measuring accuracy against a reference standard.


    7. Type of Ground Truth Used

    No specific type of ground truth (e.g., expert consensus, pathology, outcomes data) is mentioned as being used for performance validation in the context of diagnostic accuracy. Given the nature of the device (PACS for viewing and analysis), the "validation" described likely refers to software functionality and accuracy of calculations, rather than diagnostic accuracy against a clinical ground truth.


    8. Sample Size for the Training Set

    The document does not refer to a training set or machine learning algorithms in a way that would require specifying a sample size for training. The Olea Sphere is described as a "software package" for image viewing, processing, and analysis, and its features are compared to predicate devices with similar functionalities, implying a traditional software development and validation approach rather than an AI/ML model.


    9. How Ground Truth for the Training Set Was Established

    As no training set is mentioned in the context of machine learning, there is no information on how its ground truth would have been established.


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