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IQQA-Liver Multimodality is a PC-based, self-contained, non-invasive image analysis software application for reviewing multiphase images derived from CT scanners and MR scanners. Combining image viewing, processing and reporting tools, the software is designed to support the visualization, evaluation and reporting of liver and physician-identified lesions.

The software supports a workflow based on automated image registration for viewing and analyzing multiphase volume datasets. It includes tools for interactive segmentation and labeling of liver segments and vascular structures. The software provides functionalities for manual or interactive segmentation of physician-identified lesions, interactive definition of virtual resection plane, and allows for regional volumetric analysis of such lesions in terms of size, position, margin and enhancement pattern, providing information for physician's evaluation and treatment planning.

The software is designed for use by trained professionals, including physicians and technicians. Image source: DICOM.

The IQQA-Liver Multimodality Software is a self-contained, noninvasive radiographic image analysis application that is designed to run on standard PC hardware. The image data utilized is derived from sources including CT and MR scanners, and of DICOM format. Combining image processing, viewing and reporting tools, the software supports the visualization, evaluation and reporting of liver and physician identified liver lesions. Viewing tools include various standard visualization modes (e.g. original DICOM 2D image viewing, window level adjustment, svnchronized viewing of multi-phase sets, Multi-Planar Reformation (MPR) in any plane (orthogonal, oblique, curved), 3D views in rendering mode (MIP. MinIP, volume rendering), and their relationship to originally acquired images from modality). Analysis and evaluation tools include segmentation of structures utilizing user input of seeding points, user tracing and interactive editing, interactive labeling of segmented areas. quantitative measurement derived from segmentation and labeling results, and the measurement of distance between physician specified structures and landmarks. Reporting tools in the software automatically assemble information (including physician identified lesion focations, measurement information. physician-input lesion characterization. Iesion ROI images across multi-phases, information of liver lobes and vessels, and illustrative snapshots of the GUI taken by user) for physician's confirmation and for further diagnosis note input.

The IQQA-Liver Multimodality software supports a workflow based on automated registration for viewing and analyzing multi-phase volume datasets. The software automatically matches the spatial location of original DICOM images across multi-phases, and provides synchronized viewing of multi-phase dataset to aid visualization. The software further includes tools for interactive segmentation and interactive labeling of liver segments and vascular structures (such as liver lobes. vessels and ducts and major branches), thus facilitation of spatial relationship between suspicious liver lesions and specified anatomical structures/landmarks. The tools also allow for interactive segmentation of physician-identified lesions using user input of seed points and boundary editing, interactive definition of virtual resection plane, interactive ' adjustment of user specified margin size around the lesion, and regional analysis of such lesions with respect to size, shape, position, margin, enhancement pattern etc, thus providing information to support physician's assessment of lesion and treatment plans.

The software is designed for use by trained professionals, including physicians and technicians. Physicians make all final patient management decisions.

1. Acceptance Criteria and Device Performance:

The provided document does not explicitly list acceptance criteria in a table format with corresponding reported device performance values. It states that "Test results support the conclusion that actual device performance satisfies the design intent." However, it does not quantify what that "design intent" or "acceptance criteria" actually were.

What is provided is a general statement about the successful outcome of testing and the fulfillment of the intended use, and the FDA's concurrence that the device is substantially equivalent to predicate devices. More specific performance metrics and their comparison to acceptance thresholds are not detailed in this summary.

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

The document states: "EDDA Technology has conducted software testing at two clinical sites." However, it does not specify the sample size (number of cases or patients) used for this clinical testing.

The data provenance is implicitly retrospective as it mentions "physicians use the v2.0 software application to review multiphase CT and MR images of the liver". The document does not specify the country of origin of the data.

3. Number and Qualifications of Experts for Ground Truth:

The document states: "The purpose of the testing is to have physicians use the v2.0 software application to review multiphase CT and MR images of the liver... and provide feedback along the line of the intended use of the system."

It does not specify the number of physicians or their specific qualifications (e.g., years of experience, subspecialty in radiology) used to establish ground truth or provide feedback. It only refers to them as "physicians."

4. Adjudication Method for the Test Set:

The document does not describe any specific adjudication method used for the test set (e.g., 2+1, 3+1 consensus). It only mentions that physicians used the software, validated major functionalities, and provided feedback. This suggests a less formal "feedback" approach rather than a structured adjudication process for ground truth establishment.

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

A MRMC comparative effectiveness study was not explicitly described in the provided document. The study described was focused on physicians using the software to validate functionalities and provide feedback, not on comparing human reader performance with and without AI assistance to quantify an effect size.

6. Standalone (Algorithm Only) Performance Study:

The document does not describe a standalone performance study where the algorithm's performance was evaluated without human interaction. The clinical testing involved "physicians use the v2.0 software application," implying a human-in-the-loop scenario. The preceding software testing mentioned ("Software testing and validation were done according to written test protocols") likely refers to internal functional and verification testing rather than performance validation against a clinical ground truth in a standalone mode.

7. Type of Ground Truth Used:

The ground truth for the clinical testing appears to be based on physician-identified findings and evaluations. The document states that "physicians use the v2.0 software application to review multiphase CT and MR images... and provide feedback along the line of the intended use of the system." This suggests that the "ground truth" was established by the interpreting physicians and their clinical assessment/feedback, rather than a definitive, independent source like pathology or long-term outcomes data.

8. Sample Size for the Training Set:

The document does not specify the sample size used for the training set. The summary focuses on the validation/testing activities.

9. Ground Truth Establishment for the Training Set:

The document does not describe how the ground truth for the training set was established. This information is typically proprietary and often not included in 510(k) summaries.

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