(115 days)
These products are intended to be used in displaying radiological images for review, analysis and diagnosis by trained medical practitioners. They do not support the display of mammography images for diagnosis.
The Hisense LCD monitors are intended for trained medical practitioners and provides the image viewing and medical diagnostic functions. HMD2C21A, HMD4C27S, HMD6C30D are developed with different resolution:1600 x 1200, 2560 x 1440, 3280 × 2080. So the LCD monitors can be used in different environment according to different resolution requirement. The three models also developed with same features such as energy saving, ambient light induction, front-facing sensor calibration, etc. In particular, HMD4C27S, HMD6C30D have body-inductive energy-saving and auto awake function.
The provided text describes the acceptance criteria and the study conducted for the Hisense LCD monitors (HMD2C21A, HMD4C27S, HMD6C30D) to demonstrate substantial equivalence to predicate devices.
1. A table of acceptance criteria and the reported device performance
The acceptance criteria for the Hisense LCD monitors are based on demonstrating compliance with performance standards and being substantially equivalent to legally marketed predicate devices. The performance is reported through bench testing in accordance with AAPM Task Group 18 (TG18) guidelines.
Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Measured Guidance) | Reported Device Performance (HMD2C21A, HMD4C27S, HMD6C30D Measurements) |
|---|---|
| a. Spatial resolution | Measure Spatial resolution with TG18 Resolution |
| b. Pixel defects (maximum counts, allowed defect types, and locations) | Measure Pixel defects with TG18 |
| c. Artifacts | Measure Artifacts with TG18 |
| d. Temporal response | Measure Temporal response with TG18 |
| e. Luminance (maximum, minimum, achievable, and recommended) | Measure Luminance with TG18 |
| f. Conformance to a grayscale-to-luminance function (e.g., DICOM GSDF) | Measure Conformance to a grayscale-to-luminance function with TG18 |
| m. Color tracking (primary colors and color gamut) | Measure Color tracking with TG18 |
| Electrical Safety | Compliance with IEC 60601-1 |
| Electromagnetic Compatibility (EMC) | Compliance with IEC 60601-1-2 |
Note: The document explicitly states "No" for several other TG18 measurements (g. Luminance at 30° and 45° in diagonal, horizontal, and vertical directions at center and four corners; h. Luminance uniformity or Mura test; i. Stability of luminance and chromaticity response with temperature and time of operation or on-time; j. Spatial noise; k. Reflection coefficient; l. Veiling glare or small-spot contrast; n. Gray tracking (gray shades and white point)), indicating these were not considered part of the acceptance criteria for this submission.
2. Sample size used for the test set and the data provenance
The document does not specify a separate "test set" in the context of clinical images or patient data. The performance evaluation was primarily through bench testing of the devices themselves. Therefore, the "sample size" refers to the number of device models tested, which are HMD2C21A, HMD4C27S, and HMD6C30D.
- Sample size: 3 device models (HMD2C21A, HMD4C27S, HMD6C30D).
- Data provenance: Not applicable in the context of patient data. The data originates from physical measurements and tests conducted on the manufactured medical display devices. The study is prospective in the sense that the tests were performed on the devices to support the 510(k) submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. The study involved bench testing of display performance against established technical standards (AAPM TG18 guidelines, IEC 60601-1, IEC 60601-1-2), not the establishment of ground truth for medical images by human experts. The "ground truth" for the device's technical specifications is the physical characteristics and performance measurements of the monitors in comparison to the predefined standards and predicate devices.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. There was no test set involving human interpretation of medical images that would require an adjudication method. The evaluation was based on objective physical and electrical measurements of the display devices.
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
No, an MRMC comparative effectiveness study was not done. The device is a medical LCD monitor, not an AI-powered diagnostic tool. The submission focuses on the display capabilities of the monitor itself, not on its assistance to human readers or AI performance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
No, a standalone algorithm-only performance study was not done. The device is a monitor, which by its nature requires a human-in-the-loop (a medical practitioner) to interpret the displayed images. There is no algorithm for diagnostic purposes operating independently on the monitor itself.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The "ground truth" for this device's performance is objective technical specifications and performance metrics defined by international standards and guidelines, such as:
- AAPM Task Group 18 (TG18) guidelines: For display performance characteristics like spatial resolution, pixel defects, artifacts, temporal response, luminance, conformance to DICOM GSDF, and color tracking.
- IEC 60601-1: For electrical safety.
- IEC 60601-1-2: For electromagnetic compatibility (EMC).
- Comparison to predicate devices: The "ground truth" for substantial equivalence is that the proposed device's characteristics and performance are comparable to (or better than, without raising new questions of safety or effectiveness) those of legally marketed predicate devices.
8. The sample size for the training set
Not applicable. The device is a medical display monitor, not a machine learning or AI algorithm. Therefore, there is no "training set" in the context of machine learning.
9. How the ground truth for the training set was established
Not applicable, as there is no training set for this type of 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).