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Myrian® is a software medical device aimed at reviewing images produced by all standard medical imaging devices. It also includes DICOM communication, media interchange (printing, CD burning, storing) and reporting features. Myrian® can be run from any standard client platform (such as PC) that might be purchased independently by the end user.

Common Users are trained medical professionals, including surgeons, radiologist clinicians and technicians.

This device is not indicated for mammography use. Lossy compressed mammography images and digitized film screen images must not be used for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 mega pixel resolution and meets other technical specifications approved by the FDA.

Myrian® is a multi modality medical device for the review and analysis of anatomy and pathology in multi-dimensional images acquired from a variety of imaging devices. Myrian provides users with several visualization modes and includes DICOM communication, media interchange (printing, CD burning, storing).

Myrian includes toolsets which enable the reviewing physician to provide any selected relevant information for diagnosis, surgery and treatment planning to the referring physician. These toolsets are categorized as follow: Imaging tools, Manual or interactive Objects Of Interest (OOI), Reporting tools, Manual or assisted image alignment tools for multiphase or time-based image comparison, Virtual ROI Cutting Surface tool for preoperative evaluation of surgery strategies, Longitudinal Follow-up tools for oncology workflow.

Myrian® functionalities can be packaged, licensed and marketed as individual modules: XP Lung, XP Lungnodule, XP Liver, XP Vessel, XL Onco.

Here's an analysis of the provided text, focusing on the acceptance criteria and the study methodologies:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state specific quantitative acceptance criteria or corresponding reported device performance metrics for diagnostic accuracy or clinical effectiveness. The submission focuses on internal verification and validation, as well as substantiating equivalence to predicate devices based on functional and technological characteristics.

Instead of a table of numerical acceptance criteria, the document describes a series of internal tests and a literature review to ensure the software fulfills its intended aim with complete safety for the patient and demonstrates Myrian's capability to be used in a clinical environment as intended by the manufacturer. The "Performance data" section outlines the types of internal testing performed.

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

The document does not specify a sample size for a "test set" in the context of a clinical performance study. The stated testing refers to internal software validation.

• Test Set (Clinical): Not applicable, as detailed clinical performance testing with a 'test set' of patient data for diagnostic accuracy is not described.
• Data Provenance: Not applicable.

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

The document does not mention the use of experts to establish ground truth for a clinical test set. The information provided discusses internal software testing, not external validation against expert-derived ground truth.

• Number of Experts: Not applicable.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method for establishing ground truth, as no clinical test set with corresponding ground truth establishment is detailed.

• Adjudication Method: Not applicable.

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

The document does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was performed. There is no mention of comparing human readers' performance with and without AI assistance, nor any effect size reported.

• MRMC Study Performed: No.
• Effect Size: Not applicable.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The document does not specify a standalone performance study where the algorithm's performance is measured without human intervention for diagnostic tasks. The "Performance data" section refers to software testing and internal evaluations, not a standalone clinical performance study.

• Standalone Study Performed: Not explicitly detailed as a clinical performance study.

7. Type of Ground Truth Used

Based on the provided information, the primary "ground truth" used for evaluating the device's performance is its adherence to specified software requirements and functionalities through various internal testing phases (pre-integration, functional, integration, regression, build testing). For "clinical features" (e.g., segmentation engines), the document states that a "statistical analysis to apply is defined" and "sample size and relevant inclusion criteria are specified to select the appropriate exams," but it does not explicitly describe the type of clinical ground truth used for these internal evaluations (e.g., pathology, expert consensus, outcomes data).

• Ground Truth Type: Primarily software specification adherence. For certain "clinical features," it refers to "appropriate exams" and "statistical analysis" but lacks specifics on the nature of the clinical ground truth.

8. Sample Size for the Training Set

The document does not provide any information regarding a training set or its sample size. The software mentioned is a medical image review and aided diagnosis software, but the document does not describe it as a machine learning or AI algorithm that would typically require a distinct training set. The descriptions of modules like XP LungNodule mention "Automatic segmentation engine" and "Automatic measurement and characterization," which could imply machine learning, but the document doesn't detail their development or training.

• Training Set Sample Size: Not provided.

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

Since no training set is described, the method for establishing its ground truth is not mentioned.

• Ground Truth Establishment for Training Set: Not provided.

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