(78 days)
ACCENT™ is a computerized tissue segmentation device intended for use in conjunction with magnetic resonance (MRI) imaging data to identify similar tissue types. When interpreted by a skilled physician, this device provides information that may be useful in screening and diagnosis. ACCENT can also be used to provide accurate and reproducible measurements of the longest diameter and volume of identified tissue. Patient management decisions should not be made based solely on the results of ACCENT analysis.
The ACCENT device relies on the assumption that pixels having similar MR signal intensities represent similar tissues. The ACCENT software simultaneously analyzes the pixel signal intensities from multiple MR sequences and applies multivariate pattern recognition methods to perform tissue segmentation and classification.
The ACCENT system consists of proprietary software developed by Confirma installed on an off-the-shelf personal computer and a monitor configured as an ACCENT display station.
This is a 510(k) premarket notification for the ACCENT device, which means the device is seeking substantial equivalence to existing predicate devices rather than proving de novo safety and effectiveness. As such, the submission primarily focuses on comparing the new device's intended use, design, function, and performance characteristics to those of predicate devices already on the market.
Therefore, the provided text does not contain information about a dedicated study proving that the device meets specific acceptance criteria. The document states that the software has been designed, developed, tested, and validated according to internal procedures, and a hazard analysis was performed. However, it does not explicitly detail a clinical or performance study with defined acceptance criteria and corresponding results.
Here's a breakdown of the information that is present, and what is missing, based on your request:
1. A table of acceptance criteria and the reported device performance
This information is not provided in the document. The submission is a 510(k) aiming for substantial equivalence to predicate devices, not a demonstration of meeting predefined performance acceptance criteria through a specific study in the detailed manner you've requested.
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
This information is not provided in the document. No specific test set or data provenance is mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)
This information is not provided in the document. Since no specific test set is detailed, there's no mention of experts establishing ground truth.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
This information is not provided in the document. No adjudication method is mentioned as there is no detailed test set described.
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
There is no mention of an MRMC comparative effectiveness study in the provided text. The device's intended use states it "provides information that may be useful in screening and diagnosis" and "Patient management decisions should not be made based solely on the results of ACCENT analysis," implying it's an assistive tool, but no study on human reader improvement is presented.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not explicitly stated as a formal standalone performance study with specific metrics. The device is described as "computerized tissue segmentation device" that "simultaneously analyzes the pixel signal intensities... and applies multivariate pattern recognition methods to perform tissue segmentation and classification." While this describes the algorithm's function, there's no dedicated study or reported performance metrics for its standalone accuracy without human intervention.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
This information is not provided in the document. No specific ground truth methodology is described.
8. The sample size for the training set
This information is not provided in the document.
9. How the ground truth for the training set was established
This information is not provided in the document.
In summary: The provided 510(k) submission for the ACCENT device focuses on establishing substantial equivalence to predicate devices rather than detailing a specific performance study with acceptance criteria, expert adjudication, or ground truth establishment. Therefore, most of the requested information regarding experimental design, sample sizes, and performance metrics is absent from this document.
§ 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).