(191 days)
The InSight™ Diagnostic Imaging Workstation must be used by or on the order of a physician. The system receives digital information from scanning devices and manipulates image data for the purpose of image characterization, enhancement, communication, archiving, and real-time 3D visualization. The system is designed as an aide to trained medical practitioners in the diagnostic process. Only qualified personnel should service system hardware and software.
The InSight™ Diagnostic Imaging Workstation provides real-time 3-D visualization, communication, archiving, characterization, and image enhancement with digital information received from medical scanning devices. System utilizes IBM compatible PC with Intel "X"86 family microprocessors and Microsoft Windows NT™ operating system for ease of maintenance and cost.
The provided text is a 510(k) Summary for the InSight™ Diagnostic Imaging Workstation (K965179). It focuses heavily on describing the device and establishing its substantial equivalence to predicate devices, rather than presenting a performance study with acceptance criteria.
Based on the provided text, there is NO acceptance criteria or study that proves device performance against specific metrics.
The document explicitly states:
- "Although there are no performance standards established by the Special Controls: FDA on image processing workstations, Neo Imagery Technologies, Inc. has developed the InSight™ Diagnostic Imaging Workstation in compliance with the guidance issued by the FDA, CDRH, ODE such as the August 29, 1991 Reviewer Guidance for Computer Controlled Medical Devices Undergoing 510(k) Review."
This indicates that the device was cleared based on its substantial equivalence to predicate devices and adherence to general guidance, not on a specific performance study against defined acceptance criteria.
Therefore, most of the requested information cannot be extracted from this document.
Here's what can be stated based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criterion | Reported Device Performance |
|---|---|
| No specific performance criteria or metrics are mentioned in the provided document. | No performance data is reported against specific criteria. The document states the device "has no significant changes in technological characteristics from the predicate devices that will alter its safety or effectiveness" and "does not raise new questions of safety and effectiveness." |
2. Sample size used for the test set and the data provenance
- Sample Size for Test Set: Not applicable. No performance study involving a test set is described.
- Data Provenance: Not applicable. No performance study is described.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable. No performance study involving ground truth establishment is described.
4. Adjudication method for the test set
- Not applicable. No performance study involving a test set is described.
5. Multi-reader multi-case (MRMC) comparative effectiveness study
- Was an MRMC study done? No. The document does not describe any MRMC comparative effectiveness study. The clearance is based on substantial equivalence to predicate devices, not on a study demonstrating improved human reader performance with AI assistance.
- Effect size of human readers improve with AI vs without AI assistance: Not applicable. No such study was described.
6. Standalone (i.e. algorithm only without human-in-the loop performance) study
- No. The document does not describe any standalone performance study of the algorithm. The device is referred to as a "workstation" for medical practitioners, implying human-in-the-loop operation.
7. Type of ground truth used
- Not applicable. No performance study requiring ground truth is described.
8. Sample size for the training set
- Not applicable. No machine learning training process is described, nor is a training set referenced.
9. How the ground truth for the training set was established
- Not applicable. No machine learning training process or training set ground truth establishment is described.
§ 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).