(60 days)
The indication for use of the Fuji Medical Laser Imager MF-PS667 is to connect imaging modalities on a network to a hard copy system for hard copy output.
The device consists of a computer (console, display, kevboard, and software. The device connects a DICOM or Toshiba medical image data network to Fuji hard copy printing systems.
The network typically carries images from modalities (e.g. CT, MR, NM, or US) or other image sources being transported under DICOM or Toshiba network protocol. The print server accepts the image data, performs protocol conversion to Fuji's protocol, and passes it to Fuji's hard copy print system.
This device is a print server (Fuji Medical Laser Imager MF-PS667) that connects medical imaging modalities to hard copy printing systems. As such, the performance data provided in the 510(k) summary focuses on its electrical safety and data transmission reliability rather than diagnostic accuracy. Therefore, many of the typical acceptance criteria and study design elements for AI/machine learning devices, such as reader studies or ground truth methodologies, are not applicable here.
Here's an analysis based on the provided document:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Electrical Safety | Complies with UL 1950 Standard for Safety of Information Technology Equipment, Including Electrical Business Equipment. |
| Data Transmission Reliability | Employs IEEE802.3 standard transceiver for Ethernet connection. Uses standard data communications controls to detect and correct errors. Device failures resulting in failed transmission can be recovered from by retransmission. |
| Data Security | Operation is password protected to prevent unauthorized use. |
| Protocol Conversion Functionality | Functions as a DICOM standard communications protocol converter. |
| Image Processing Capabilities | May perform simple image processing: image rotation, reversal, and decompression of reversibly compressed (ratio: ½) image data. |
| Data Loss Prevention | Not explicitly a criterion, but acknowledges potential for data loss due to hardware failure or operator error; however, transmission can be completed after correcting the cause of failure. |
| Patient Safety/Human Intervention | Images crossing the print server are interpreted by a physician, providing ample opportunity for competent human intervention. Device has no patient contact and does not control, monitor, or affect devices directly connected to a patient. |
| Technological Equivalence to Predicate | Both subject and predicate devices are based on Sun SPARC Station with 64-bit micro-SPARC II microprocessor, 64MB RAM, and 1.5 GB fixed magnetic disk storage. Both use a CRT for character display. |
2. Sample Size Used for the Test Set and Data Provenance
This is not applicable to the type of device and study presented. The device is a print server; its performance is assessed through compliance with technical standards and functional descriptions, not through a diagnostic test set with patient data.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications
Not applicable. There is no diagnostic ground truth established for this device.
4. Adjudication Method
Not applicable. There is no diagnostic ground truth established for this device.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No. This is not an AI/diagnostic device, so an MRMC study is not relevant.
6. Standalone Performance Study
No formal standalone "study" in the sense of a diagnostic performance evaluation was conducted. The performance described is inherent to the device's design, its adherence to industry standards (IEEE802.3, UL 1950, DICOM), and its functional capabilities (protocol conversion, basic image manipulation). The "performance data" section primarily lists technical specifications and compliance.
7. Type of Ground Truth Used
Not applicable. There is no diagnostic ground truth for this device. Its "truth" is its functional performance according to technical specifications and safety standards.
8. Sample Size for the Training Set
Not applicable. This device is not an AI/machine learning device that requires a training set.
9. How the Ground Truth for the Training Set Was Established
Not applicable. This device is not an AI/machine learning device that requires a training set.
§ 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).