(30 days)
Huvitz Imaging system (HIS-5000U) is intended for controlling digital imaging devices and for acceptance, transfer, display, storage and digital processing of documentation ophthalmic images and videos, acquired from a slit lamp camera through a direct connection to a PC or to multiple PCs via a local network.
Huvitz Imaging System (HIS-5000U) consists of slit lamp camera (HIS-5000U(10.0M), HIS-5000U(5.0M), HIS-5000U(1.4M)), Communication Cable and Imaging Software (HIS-5000N). It is a digital imaging system with a high resolution digital camera and PC based patient diagnostic data management software intended for controlling digital imaging devices, acceptance, transfer, display, storage and digital processing of ophthalmic images including videos, acquired from a of a slit lamp camera through direct connection or network. The imaging software (HIS-5000N) supports networking function to share patient information and examination images between multiple PCs existing on the local network or internet via TCP/IP protocol. Also, this version uses MS-SQL server solution as more reliable database, and includes additional HIS Server Management software to support to back up or restore patient and imaging data. HIS-5000N imaging system software is not able and intended to provide any diagnosis but help the user to view the visible structures of the eye and store the findings.
The provided text is a 510(k) summary for the Huvitz Imaging System (HIS-5000U). It details the device's technical characteristics and compares it to a predicate device, focusing on non-clinical performance tests.
Based on the provided text, an AI device is not being described. The Huvitz Imaging System is a digital imaging system for ophthalmology, primarily consisting of a slit lamp camera and PC-based patient diagnostic data management software. It is intended for controlling digital imaging devices, and for the acceptance, transfer, display, storage, and digital processing of ophthalmic images and videos. The document explicitly states: "HIS-5000N imaging system software is not able and intended to provide any diagnosis but help the user to view the visible structures of the eye and store the findings." Additionally, "the device is not a treatment device or a diagnostic device."
Therefore, it is not possible to provide the requested information regarding acceptance criteria and a study proving an AI device meets those criteria, as no AI device or AI-driven study is described in this document.
The document discusses non-clinical performance tests conducted on the Huvitz Imaging System (HIS-5000U) to validate its performance and demonstrate substantial equivalence to its predicate device. These tests relate to the camera and software's basic functionalities, not AI performance.
For completeness, here's what was reported about the non-clinical tests:
1. A table of acceptance criteria and the reported device performance:
The document doesn't present a formal table of acceptance criteria with specific thresholds. Instead, it lists the types of performance tests conducted and generally states that the device "performed as intended and is deemed substantially equivalent to and comparable to the predicate device."
| Characteristic Tested | Reported Performance |
|---|---|
| Camera Resolution | Performed as per manufacturer's performance report |
| Camera Time machine Function | Performed as per manufacturer's performance report |
| Camera Flicker | Performed as per manufacturer's performance report |
| Camera Image Capture | Performed as per manufacturer's performance report |
| Saving image file | Performed as per manufacturer's performance report |
| Adjust Color | Performed as per manufacturer's performance report |
2. Sample size used for the test set and the data provenance:
The document does not specify a "test set" in terms of patient data or images. The performance tests appear to be related to the device's functional operation. No sample size for test data is mentioned, nor is the provenance of any data (country of origin, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable, as this was a non-clinical performance test of a medical device's technical functions, not an AI model requiring expert ground truth for diagnostic imaging.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable, as this was a non-clinical performance test.
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 MRMC study was done, as this device does not involve AI assistance for human readers in diagnosis. The document explicitly states: "Huvitz Imaging system (HIS-5000U) does not require clinical testing, given the precedent of predicate equipment. No clinical test has been conducted."
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Not applicable, as no AI algorithm is described.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
Not applicable. The "ground truth" for these performance tests would be the device's technical specifications and intended functionality.
8. The sample size for the training set:
Not applicable, as this device does not involve AI or machine learning algorithms that require 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).