(251 days)
MRIMath i2contour is intended for the semi-automatic labeling, visualization, and volumetric quantification of WHO grade 4 glioblastoma (GBM) from a set of standard MRI images of male or female patients 18 years of age or older who are known to have pathologically proven glioblastoma. Volumetric measurements may be compared to past measurements if available. MRIMath i2contour is not to be used for primary diagnosis and is not intended to be the sole diagnostic metric.
The MRIMath i2Contour is a web-based software platform designed for the contouring and segmentation of the T1c and FLAIR sequences of the MRIs of patients already diagnosed with GBM. It combines AI with a user interface (UI) for review, manual contouring, and approval. The software is intended to be used by trained medical professionals as an aid in the tumor contouring process. Review by a trained professional is a requirement for completion.
The AI algorithm within MRIMath i2Contour generates an initial tumor contour, which serves as a starting point for medical professionals to complete the contouring process manually. It is important to note that the software does not alter the original MRI images and is not intended for turnor detection or diagnostic purposes. MRIMath i2Contour is specifically designed to generate turnor volume contours for GBM. It is not intended for use with images of other brain tumor types.
Here's a breakdown of the acceptance criteria and the study proving the device's performance, based on the provided text:
Device: i2Contour
1. Table of Acceptance Criteria and Reported Device Performance
The acceptance criteria are implicitly set by comparing the device's performance to the predicate device's best mean DICE score (DSC) and demonstrating statistically significant improvement over a 50% chance of exceeding this threshold.
| Acceptance Criteria / Performance Metric | Target Value / Threshold | Reported Device Performance and Confidence Interval (CI) or P-value |
|---|---|---|
| Proportion of FLAIR AI DSC measurements exceeding predicate's best mean DSC (0.88) | Significantly different from 50% (P |
§ 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).