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Multi Modality Viewer is an option within Vitrea that allows the examination of a series of medical images obtained from MRI, CT, CR, DX, RG, RF, US, XA, PET, and PET/CT scanners. The option also enables clinicians to compare multiple series for the same patient, side-by-side, and switch to other integrated applications to further examine the data.

Multi Modality Viewer is an option within Vitrea that allows the examination and manipulation of a series of medical images obtained from MRI, CT, CR, DX, RG, RF, US, XA, PET, and PET/CT scanners. The option also enables clinicians to compare multiple series for the same patient, side-by-side, and switch to other integrated applications to further examine the data.

The Multi Modality Viewer provides an overview of the study, facilitates side-by-side comparison including priors, allows reformatting of image data, enables clinicians to record evidence and return to previous evidence, and provides easy access to other Vitrea applications for further analysis.

Here's a breakdown of the acceptance criteria and study information for the Multi Modality Viewer, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of numerical "acceptance criteria" for performance metrics in the typical sense (e.g., sensitivity, specificity, accuracy thresholds). Instead, it focuses on functional capabilities and states that verification and validation testing confirmed the software functions according to requirements and that "no negative feedback was received," and "Multi Modality Viewer was rated as equal to or better than the reference devices."

The acceptance is primarily based on establishing substantial equivalence to predicate and reference devices, demonstrating that the new features function as intended and do not raise new questions of safety or effectiveness.

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

• Test Set Sample Size: The document repeatedly mentions "anonymized datasets" but does not specify the number of cases or images used in the external validation studies.
• Data Provenance: The data used for the external validation studies were "anonymized datasets." The country of origin is not explicitly stated, but the evaluators were from "three different clinical locations." Given Vital Images, Inc. is located in Minnetonka, MN, USA, it's highly probable the data and clinical locations are from the United States. The studies were likely retrospective as they involved reviewing "anonymized datasets" rather than ongoing patient enrollment.

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

• Number of Experts: Three evaluators.
• Qualifications of Experts: The evaluators were "from three different clinical locations" and are described as "experienced professionals" in the context of simulated usability testing and clinical review. Their specific medical qualifications (e.g., radiologist, specific years of experience) are not explicitly detailed in the provided text.

4. Adjudication Method for the Test Set

The document does not describe an explicit "adjudication method" for establishing ground truth or resolving discrepancies between experts in the traditional sense. The phrase "no negative feedback received from the evaluators" and "Multi Modality Viewer was rated as equal to or better than the reference devices" suggests a consensus or individual evaluation model, but not a specific adjudication protocol like 2+1 or 3+1. It appears the evaluations focused on confirming functionality and subjective quality rather than comparing against a pre-established ground truth for a diagnostic task.

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

• No, an MRMC comparative effectiveness study was not explicitly stated to have been done in the context of measuring improvement with AI vs. without AI assistance.
• The "Substantial Equivalence Validation" involved three evaluators comparing the subject device against its predicate and reference devices. However, this comparison focused on functionality and image quality and aimed to show the equivalence or non-inferiority of the new device and its features, rather than quantifying performance gains due to AI assistance in human readers. The new features mentioned (like automatic segmentation or rigid registration) are components that might assist, but the study design wasn't an MRMC to measure the effect size of this assistance on human performance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

• The document describes "software verification testing" which confirms "the software functions according to its requirements." This implies a form of standalone testing for the algorithms and features. For example, "Automatic table segmentation" and "Automatic bone segmentation" are algorithms, and their functionality would have been tested independently.
• However, no specific performance metrics (e.g., accuracy, precision) for these algorithms in a standalone capacity are provided from these tests. The external validation was a human-in-the-loop setting where evaluators used the software.

7. The Type of Ground Truth Used

The external validation involved "clinical review of anonymized datasets" where evaluators assessed "functionality and image quality." For new features like segmentation or registration, the "ground truth" would likely be based on the expert consensus or judgment of the evaluators during their review of the anonymized datasets, confirming if the segmentation was accurate or if the registration was correct and useful. There is no mention of pathology, direct clinical outcomes data, or a separate "ground truth" panel.

8. The Sample Size for the Training Set

The document does not specify the sample size for the training set. It details verification and validation steps for the software but does not provide information about the development or training of any AI/ML components within the software. While features like "Automatic table segmentation" and "Automatic bone segmentation" likely involve machine learning, the document does not elaborate on their training data.

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

Since the document does not specify the training set or imply explicit AI/ML development in the detail often seen for deep learning algorithms, it does not describe how the ground truth for the training set was established.

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Multi Modality Viewer is an option within Vitrea that allows the examination and manipulation of a series of medical images obtained from MRI, CT, CR, DX, RG, RF, XA, PET, and PET/CT scanners. The option also enables clinicians to compare multiple series for the same patient, side-by-side, and switch to other integrated applications to further examine the data.

Multi Modality Viewer is a medical image viewer software application, available on the Vitrea software platform cleared by K150258. The application allows qualified clinicians, including physicians, radiologists and technologists, to display, navigate, manipulate and quantify medical images obtained from MRI, CT, CR, DX, RG, RF, XA, PET, and PET/CT modalities.

The Multi-Modality Viewer provides an overview of the study, facilitates side-by-side comparison including priors, allows clinicians to record evidence and return to previous evidence, and provides easy access to other Vitrea applications for further analysis.

The provided document, a 510(k) summary for the "Multi Modality Viewer" software, primarily focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific acceptance criteria and a study proving those criteria are met for new features that would typically involve a performance study.

The device is an update to an existing medical image viewer, and the clearance is based on the argument that new features (support for additional modalities like PET, PET/CT, CR, DX, RG, RF, XA) do not raise new questions of safety and effectiveness because similar functionalities exist in previously cleared reference devices.

Therefore, the document explicitly states: "The subject of this 510(k) notification, Multi Modality Viewer software, did not require clinical studies to support safety and effectiveness of the software."

However, it does mention "Verification and Validation" activities and "Performance Standards" in a general sense. Based on the provided text, I can extract the following information about general testing and the device's performance, as much as is available:

1. Table of Acceptance Criteria and Reported Device Performance:

Since no specific quantitative acceptance criteria or detailed performance metrics are provided for the new features in the context of a dedicated performance study, the "acceptance criteria" here are inferred from the general statements about software development and verification. The device's "performance" is reported as meeting these general standards.

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

The document does not specify a distinct "test set" with a particular sample size for a performance study related to the new features. The testing mentioned is "internal verification and external validation" which included "simulated usability testing by experienced professionals." No details about the number of cases or data provenance (country of origin, retrospective/prospective) for these tests are provided.

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

No specific number of experts or their detailed qualifications are provided for establishing ground truth for a test set. The document refers to "experienced professionals" for "simulated usability testing."

4. Adjudication Method for the Test Set:

No adjudication method (e.g., 2+1, 3+1, none) is mentioned as no specific performance study test set is described.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done:

No MRMC comparative effectiveness study is mentioned. The document explicitly states: "The subject of this 510(k) notification, Multi Modality Viewer software, did not require clinical studies to support safety and effectiveness of the software."

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

The device is a medical image viewer software. Its function is to display, navigate, manipulate, and quantify medical images for clinicians. It is not an algorithm that performs automated detection or diagnosis. Therefore, a standalone (algorithm only) performance study as typically understood for AI algorithms would not be applicable and is not mentioned. Its performance is intrinsically tied to human interaction.

7. The Type of Ground Truth Used:

As no specific performance study with a dedicated test set is described, there is no mention of the type of ground truth used (e.g., expert consensus, pathology, outcomes data). The validation focuses on the software's ability to function as intended and display data from new modalities accurately, which relies on adherence to standards and internal software verification.

8. The Sample Size for the Training Set:

This device is image viewer software, not a machine learning or AI algorithm that requires a "training set" in the conventional sense. Therefore, no training set size is mentioned.

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

As there is no training set for this type of device, this information is not applicable.

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Multi Modality Viewer is a software application within Vitrea® that allows the examination and manipulation of a series of medical images obtained from MRI and CT scanners.

The option also enables clinicians to compare multiple series for the same patient, side-by-side, and switch to other integrated applications to further examine the data.

Multi Modality Viewer is a software application which functions on the Vitrea Platform, cleared by K150258. This application allows intuitive navigation, and manipulation of medical images obtained from MRI and CT scanners. This application enables clinicians to compare multiple series of the same patient, side-by-side, and switch to other integrated applications to further examine the data.

lt provides clinical tools to review images to help qualified physicians provide efficient and effective patient care.

Key features:
General Viewing:

• · Linked 2D, MPR and 4D viewers for single and multi-study comparison
• · Creation of retrievable evidence and snapshots
• · User defined flexible display protocols

Access to Advanced Applications and Workflows:

• In application access to MR Stitching application
• · Evidence creation and sharing across workflows

General Image Display, Manipulation, and Analysis Tools:

• · Maximum and Minimum Intensity Projection (MIP/MinIP)
• · Identification and Display of Regions of Interest (ROIs)
• · CINE image display
• · Multi-frame display
• · Color image display
• . Simultaneous multiple studies review
• · Cross-reference lines support
• Display of selected images, series, or entire study .
• · Comparison of multiple series or studies
• · Scroll
• Pan
• Zoom
• · Focus
• · Flip (Vertically, horizontally)
• Invert
• · Rotate (Clockwise, counter-clockwise)
• · Arrow
• · Adjust Registration
• · Auto window level/width setting
• · Text/Arrow annotation (Label)
• · Measurement of distance (Ruler), Angle, Cobb Angle, Ellipse ROI, and Freehand ROI

Specialized Tools:

• · Image subtraction of two series/datasets
• · Access to semi-automated image stitching
• Study and series linking .
• · Register two different series or groups that do not share a frame of reference to link them spatially

The Multi Modality Viewer is a software application for examining and manipulating medical images from MRI and CT scanners.

It is considered substantially equivalent to its predicate device, the MR Core Software (K151115), which only handled MRI images, and a reference device, Softread Software (K040305), which supports both CT and MRI.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not explicitly state quantitative acceptance criteria or a specific performance study comparison table for the Multi Modality Viewer beyond feature-by-feature comparison with predicate/reference devices. Instead, it focuses on demonstrating that the device has similar technological characteristics, intended use, and indications for use, and that verification and validation testing confirms its safety and effectiveness.

The document primarily performs a feature-by-feature comparison to establish substantial equivalence.

Overall Conclusion: The device is considered substantially equivalent because the added CT modality feature is similar to the reference device and does not raise different questions of safety and effectiveness. The verification and validation testing performed "demonstrate the subject device is as safe and effective as the predicate and reference devices."

2. Sample Size for Test Set and Data Provenance

The document mentions "Verification of the software that included performance and safety testing" and "Validation of the software that included simulated usability testing by experienced professionals." However, it does not specify the sample size used for any test set or the country of origin of the data, nor whether it was retrospective or prospective. The information provided is high-level about the testing processes.

3. Number of Experts Used to Establish Ground Truth and Qualifications

For the "External Validation" mentioned under the "Validation" section, "experienced medical professionals evaluated the application." However, the exact number of experts and their specific qualifications (e.g., radiologist with 10 years of experience) are not specified.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for establishing ground truth or evaluating the test set. It only states that "All validators confirmed that the Multi Modality Viewer software fulfills its intended use."

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

The document does not mention a Multi Reader Multi Case (MRMC) comparative effectiveness study and therefore, there is no information on the effect size of human readers improving with AI vs. without AI assistance. This device is a viewer, not an AI-assisted diagnostic tool in the sense of providing automated interpretations.

6. Standalone (Algorithm Only) Performance Study

The primary evaluation appears to be of the software's functionality as a viewer, not as an algorithm performing a specific diagnostic task in standalone mode. Verification and validation tests were conducted to confirm proper function of the device's features, but no standalone performance study measuring diagnostic accuracy or similar metrics for an algorithm without human-in-the-loop was reported.

7. Type of Ground Truth Used

The document indicates that "simulation usability testing by experienced professionals" and "workflow testing" were conducted, with "validators confirmed that the Multi Modality Viewer software fulfills its intended use." This suggests "expert consensus" on usability and fulfillment of intended use as the form of "ground truth" or validation outcome, rather than pathology, outcomes data, or a specific diagnostic ground truth, as the device is a viewing platform.

8. Sample Size for the Training Set

The document does not refer to a "training set" because the Multi Modality Viewer is described as a software application for viewing and manipulating images, not an AI/ML algorithm that requires a training set for model development.

9. How Ground Truth for Training Set Was Established

Since there is no mention of a training set, the method for establishing ground truth for a training set is not applicable or discussed.

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