(441 days)
20.1-inch (51cm) Color LCD Monitor CCL208 (CDL2013A) is intended to be used in displaying and viewing medical images for diagnosis by trained medical practitioners. It is not meant to be used in digital mammography.
CCL208 (CDL2013A) is a 20.1-inch (51 cm) Color LCD monitor whose display resolution is 1200 x 1600 (landscape), 1600 x 1200 (portrait) supporting DVI (digital visual interface).
This document is a 510(k) summary for the TOTOKU 20.1-inch (51 cm) Color LCD Monitor CCL208 (CDL2013A), a medical display device. The primary purpose of the submission is to demonstrate substantial equivalence to a predicate device.
The document does not describe any study that proves the device meets specific acceptance criteria in terms of performance for image interpretation or diagnostic accuracy. This is because the device is a monitor, and its "performance" is primarily related to display characteristics and technical specifications rather than diagnostic performance.
Therefore, many of the requested elements for a study proving device performance are not applicable to this submission. I will provide the information that is available in the document.
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state "acceptance criteria" in the context of diagnostic performance that would typically be described with metrics like sensitivity, specificity, accuracy, etc. Instead, the substantial equivalence argument relies on meeting technical specifications comparable to the predicate device.
The "performance" of this device is implicitly its ability to display medical images. The acceptance criteria would be that it functions as a display comparable to its predicate. The document states:
"CCL208 (CDL2013A) shares the same characteristics with our predicate devices, CCL202 (CDL2005A) (K063198) except for power supply, LCD panel, main board (driver board and sub board), tilt-stand, I/O position and inverter PWB for LCD backlight."
This implies that despite these component changes, the performance (i.e., its function as a display) is considered equivalent. The common elements like intended use for "displaying and viewing medical images for diagnosis" are the basis for 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 not a study assessing diagnostic performance on a dataset of medical images. The "test set" would refer to the monitor itself undergoing technical evaluation.
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, as this is not a diagnostic performance study where ground truth needs to be established by experts.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable.
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 device is a monitor, not an AI or a diagnostic aid that would participate in an MRMC study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a hardware device (monitor), not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable. The ground truth for a monitor would be its technical specifications meeting design requirements, not a diagnostic ground truth.
8. The sample size for the training set
Not applicable. This is not a machine learning device that requires a training set.
9. How the ground truth for the training set was established
Not applicable.
§ 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).