(30 days)
RadiForce GX220 and RadiForce GS220 are intended to be used in displaying for diagnosis in CT, DSA or MRI etc., except for a digital mammography system.
RadiForce GX220 and Radiforce GS220 are a 54cm (21,3") Monochrome LCD display for medical image viewing, RadiForce GX220 and RadiForce GS220 display high-definition medical imaging. The model difference between GX220 and GS220 are the built-in swing calibration sensor and the protection panel equipped with GX220 as standard feature.
This document is a 510(k) summary for the EIZO NANAO Monochrome LCD Monitors, RadiForce GX220 and RadiForce GS220, from 2007. It outlines the device's classification, intended use, and technological characteristics compared to a predicate device. However, it does not include detailed information regarding acceptance criteria or a study proving the device meets specific performance metrics in the way a modern AI/ML medical device submission would.
This document describes a medical imaging display monitor, not an AI/ML device. Therefore, the questions related to AI/ML specific criteria (such as ground truth, training sets, MRMC studies, standalone performance with AI, etc.) are not applicable here.
Here's the information that can be extracted from the provided text, primarily regarding the device itself and its comparison to a predicate device for substantial equivalence:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state "acceptance criteria" in a quantitative performance metric sense for image display quality. Instead, it focuses on substantial equivalence to a predicate device (RadiForce G22, K041597). The "performance" is implicitly tied to meeting the functional requirements expected of a medical display for diagnosis in CT, DSA, or MRI.
| Feature/Characteristic | Predicate Device (RadiForce G22) | New Devices (RadiForce GX220 / GS220) |
|---|---|---|
| Intended Use | Displaying for diagnosis in CT, DSA, or MRI, etc., except for a digital mammography system. | Displaying for diagnosis in CT, DSA, or MRI, etc., except for a digital mammography system. |
| Grayscale Tones | (Not specified, but implies larger) | Smaller |
| Panel Size | 19.6" | 54cm (21.3") |
| Digital Uniformity Equalizer (DUE) | (Not specified, implies not present) | Included (compensates for luminance non-uniformity) |
| Built-in Swing Calibration Sensor | (Not specified, implies not present) | GX220: Standard feature; GS220: Optional photo sensor |
| Protection Panel | (Not specified, implies not present) | GX220: Standard feature |
| Patient Contact | No | No |
| Control Life-Sustaining Device | No | No |
The statement: "Any difference between both devices not affects safety or efficacy" is the primary "acceptance criterion" met through comparison to the predicate device. The changes (smaller grayscale tones, larger panel, DUE, sensor, protection panel) are presented as not negatively impacting safety or efficacy, thus demonstrating substantial equivalence.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
Not applicable. This is a display monitor, not a data-driven diagnostic device. There is no "test set" of medical images or patient data to evaluate its diagnostic performance in the way an AI/ML algorithm would be tested. The evaluation is on display characteristics and functionality.
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)
Not applicable. See point 2.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. See point 2.
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
Not applicable. This is not an AI-assisted device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a display monitor, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable. See point 2.
8. The sample size for the training set
Not applicable. This is not an AI/ML device.
9. How the ground truth for the training set was established
Not applicable. This is not an AI/ML device.
§ 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).