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STAGE is a post-processing software medical device intended for use in the visualization of the brain. STAGE analyzes input data from MR imaging systems. STAGE utilizes magnitude and phase data acquired with specific parameters to generate enhanced T1 weighted images, susceptibility weighted imaging (SWI) images, susceptibility weighted image map (SWIM) images, pseudo-SWIM (pSWIM) images, modified pSWIM ) images, true SWI (tSWI) images, MR angiography (MRA) images, simulated dual-inversion recovery (DIR) images, and maps of T1, R2*, and proton density (PD).

When interpreted by a trained physician, STAGE images may provide information useful in determining diagnosis.

STAGE is indicated for brain imaging only and should always be used in combination with at least one other conventional MR acquisition (e.g., T2 FLAIR).

STAGE works as a comprehensive brain imaging post-processing solution. The STAGE system consists of a dedicated medical grade computer (STAGE Module) connected to the user's local area network. The computer receives DICOM data from a specific MRI 3D GRE scan protocol (i.e., the STAGE protocol) and then outputs back numerous DICOM datasets with different types of contrast to the PACS server. The data transfer is initiated by the user's current DICOM viewing software.

Here's a breakdown of the acceptance criteria and study information for the STAGE device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly list specific quantitative acceptance criteria in a table format, nor does it provide a numerical "reported device performance" against those criteria. Instead, it makes general statements about meeting predefined acceptance criteria for image quality and clinical user needs.

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

The document states: "A reader study was conducted to demonstrate acceptable diagnostic image quality and equivalent radiologic finding classes compared to the predicate device."

• Test Set Sample Size: The exact number of cases or images in the test set for the reader study is not specified in the provided text.
• Data Provenance: The document does not specify the country of origin of the data or whether it was retrospective or prospective.

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

The document does not specify the number of experts used to establish ground truth or their qualifications. It mentions that "When interpreted by a trained physician, STAGE images may provide information useful in determining diagnosis." but this does not directly address the ground truth establishment for the reader study.

4. Adjudication Method for the Test Set

The document does not specify the adjudication method used for the test set in the reader study.

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

The document states: "A reader study was conducted to demonstrate acceptable diagnostic image quality and equivalent radiologic finding classes compared to the predicate device." This suggests a comparative study was performed, but it does not explicitly mention whether it was an MRMC study in the standard sense (comparing human readers with and without AI assistance).

• Effect Size of Human Readers with vs. without AI: This information is not provided in the document. The study aimed to show "equivalent radiologic finding classes compared to the predicate device," which implies a comparison between STAGE outputs and outputs from a predicate device, rather than a direct comparison of human reader performance with and without STAGE assistance on the same case.

6. Standalone (Algorithm Only) Performance Study

The document describes STAGE as "post-processing software medical device intended for use in the visualization of the brain" and states that "When interpreted by a trained physician, STAGE images may provide information useful in determining diagnosis." It clarifies that "STAGE is indicated for brain imaging only and should always be used in combination with at least one other conventional MR acquisition."

This suggests that STAGE is intended as a tool for a physician and not for standalone diagnostic use by the algorithm itself. Therefore, a standalone (algorithm-only) performance study, in the sense of the algorithm making a diagnosis without human input, was likely not performed or reported as part of this submission, given its described role as a "post-processing software."

7. Type of Ground Truth Used

The document does not explicitly state the type of ground truth used for the test set (e.g., expert consensus, pathology, outcome data). It only mentions demonstrating "acceptable diagnostic image quality and equivalent radiologic finding classes compared to the predicate device," implying comparison against established clinical understanding or predicate device outputs.

8. Sample Size for the Training Set

The document does not specify the sample size used for the training set. It only mentions the "Methodology" of STAGE and its use of input data.

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

The document does not specify how ground truth for the training set was established. It only describes the technical process of STAGE, stating it "analyzes input data from MR imaging systems" and uses "magnitude and phase data acquired with specific parameters to generate" various images and maps. This implies that the algorithms learn from MR imaging parameters and derived data, but the explicit method for establishing ground truth for training data is not detailed.

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