FDA 510(k) Search - By Innolitics (SaMD and AI Experts)

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 / Criterion	Reported Device Performance (Olea Sphere v2.3 vs. Predicate)
Image Analysis: Volume of Interest (VOI) Segmentation	Enhanced 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 & Comparison	Enhanced visualization and comparison: New features include "Histogram normalization" and "Image subtraction."
Perfusion Deconvolution Algorithm	New 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 Modeling	T1-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 Imaging	Motion 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 Execution	Enhanced 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.

§ 892.2050 Medical image management and processing system.