(79 days)
Vitrea® CT Myocardial Analysis is an image analysis software application for cardiac Computer Tomography (CT) studies to visualize cardiovascular anatomy and pathology and to highlight and color code the presence of hypo/hyper dense areas of myocardial tissue.
Vitrea CT Myocardial Analysis is a post-processing software option for the Vitrea® software platform. it leverages existing Vites functionality such as multiplanar reconstruction (MPR) images, maximum intensity projections (MIP), and volume rendering. Vitrea CT Myocardial Analysis enables the visualization and analysis of the myocardium. It assists in analyzing the hyperhypo dense areas of myocardial tissue. Its visualization tools include segmentation, color coding, and polar maps. Its analysis tools include measurements and companison ratios. It also includes reporting tools for formatting findings and user selected areas of interest.
The provided text does not contain detailed information regarding specific acceptance criteria, study methodologies, or performance metrics in a structured manner. The summary only mentions general verification and validation activities without quantifying results, sample sizes, or expert involvement.
Here's a breakdown of what can be extracted and what is missing:
The device under review is Vitrea® CT Myocardial Analysis.
1. A table of acceptance criteria and the reported device performance:
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Image display functionality (e.g., MPR, MIP, volume rendering) | Software confirmed to function according to requirements, without impacting existing functionality. Users could operate and perform desired functions. |
| Myocardial tissue visualization & analysis (hyper/hypo dense areas) | Software confirmed to function according to requirements, without impacting existing functionality. Users could operate and perform desired functions. |
| Software stability and reliability | No new hazards found during risk management and testing. |
| Compliance with NEMA PS 3.1 - 3.18 DICOM standards | Software designed to meet these standards. |
| Substantial equivalence to predicate devices (GE CardIQ Express 2.0, Siemens syngo.CT Cardiac Functions) | Testing supports a determination of substantial equivalence. |
2. Sample size used for the test set and the data provenance:
- Sample size: Not specified. The document only mentions "validating previously acquired diagnostic images."
- Data provenance: Not specified. It only states "previously acquired diagnostic images," which implies retrospective data, but the country of origin is not mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not specified. The document states that "users can operate the software and successfully perform the desired function," which suggests user testing but doesn't detail expert involvement for ground truth establishment.
4. Adjudication method for the test set:
- Not specified.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance:
- No, an MRMC comparative effectiveness study is not mentioned. The study described focuses on the device's functionality and its substantial equivalence to predicate devices, not on human reader improvement with AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- The summary describes the software's functionality and states that "users can operate the software and successfully perform the desired function," which implies human interaction. It doesn't explicitly state whether a standalone algorithm-only performance assessment was conducted. However, the nature of a "post-processing software option" generally suggests it's a tool for human users.
7. The type of ground truth used:
- Not explicitly stated. Given the context of "validating previously acquired diagnostic images" for visualizing and analyzing myocardial tissue, it imply comparison against established clinical interpretations or potentially consensus. However, it's not explicitly labeled as "expert consensus," "pathology," or "outcomes data."
8. The sample size for the training set:
- Not specified. The document does not discuss a training set, as it describes a software product that leverages existing functionality and performs post-processing analysis.
9. How the ground truth for the training set was established:
- Not applicable/Not specified, as no training set is mentioned.
In summary, the provided 510(k) summary is very high-level and lacks specific details regarding the methodology, quantitative results, and sample characteristics of the studies conducted. It focuses on declaring substantial equivalence based on general software verification and validation.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).