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Ezra Plexo Software is a medical diagnostic application for viewing, manipulation, 3D- visualization, and comparison of MR medical images. The images can be viewed in a number of output formats including volume rendering.

Ezra Plexo Software enables visualization of information that would otherwise have to be visually compared disjointedly.

Ezra Plexo Software is designed to support the oncological workflow by helping the user to confirm the absence or presence of lesions, including evaluation, quantification, and documentation of any such lesions.

Note: The clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard practices and visual comparison of the separate unregistered images. Ezra Plexo Software is a complement to these standard procedures.

Ezra Plexo is a medical image application for 2D and 3D visualization, comparison, and manipulation of medical images. Plexo can be accessed through a web browser. It provides radiologists the ability to view and manipulate volumetric data such as MRI. The product allows volumetric segmentation of regions of interest, while enabling users to edit such segmentations and to take quantitative measurements.

Plexo does not interface directly with the MR scanner or any other data collection equipment. Instead, it uploads data files previously generated by such equipment. Its functionality is independent of the acquisition equipment vendor. Its analysis results are available on screen and can be saved for review.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA 510(k) summary for Ezra Plexo Software:

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

The document does not explicitly present a table of acceptance criteria with numerical performance metrics. Instead, it states that "The test results demonstrated that the Ezra Plexo Software performs to its intended use, is deemed acceptable for clinical use, and does not introduce new questions of safety or efficacy."

This suggests the acceptance criteria were likely qualitative and based on the software successfully performing its intended functions (viewing, manipulation, 3D-visualization, and comparison of MR medical images; visualization of information; and supporting oncological workflow by helping confirm absence/presence of lesions, evaluation, quantification, and documentation) without errors or safety/efficacy concerns in the validation setting.

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

• Sample Size for Test Set: 150 patient exams
• Data Provenance: Not explicitly stated, but it was reviewed by five U.S. board-certified expert radiologists. It's not specified if this data was retrospective or prospective.

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

• Number of Experts: Five (5)
• Qualifications of Experts: U.S. board-certified expert radiologists. Specific years of experience are not mentioned.

4. Adjudication method for the test set

• Adjudication Method: "Consensus ground truth created by five U.S. board certified expert radiologists." This implies a form of consensus process, where the five radiologists collectively reviewed the 150 patient exams to establish the definitive ground truth for the study. The exact method of achieving consensus (e.g., majority vote, discussion until agreement) is not detailed.

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

• MRMC Study: No, a multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not conducted or reported in this document. The study was a "nonclinical software validation" focused on the software's performance against expert consensus ground truth, not on human reader improvement.

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

• Standalone Performance: The description of the validation test, which involved "performing nonclinical software validation tests on 150 patient exams utilizing consensus ground truth," strongly suggests a standalone (algorithm only) performance evaluation. The device is for "viewing, manipulation, 3D-visualization, and comparison," and it "enables visualization of information that would otherwise have to be visually compared disjointedly." The focus on "performs to its intended use" suggests the algorithm's output was compared to the ground truth. However, the exact metrics (e.g., sensitivity, specificity for lesion detection/quantification) are not provided.

7. The type of ground truth used

• Type of Ground Truth: Expert consensus. Specifically, "consensus ground truth created by five U.S. board certified expert radiologists."

8. The sample size for the training set

• Training Set Sample Size: The document does not specify the sample size for the training set. It only describes the "nonclinical software validation tests" on a test set of 150 patient exams.

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

• Ground Truth for Training Set: The document does not provide information on how ground truth was established for the training set, as it only details the validation (test) set.

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