(72 days)
The ImageChecker-CT is indicated for use as a general imaging workstation, and is intended to be used to acquire, store, transmit and display images from medical scanning devices.
Specific indications for use for the ImageChecker-CT Workstation are the display of a composite view of 2D cross-sections, and 3D volumes of chest CT images, including findings or regions of interest ("ROI") identified by the radiologist or Computer Assisted Detection ("CAD") findings.
The general indications for use of the ImageChecker-CT Workstation are as a general imaging workstation to assist radiologists in reviewing digital computed Tomography (CT) images of the chest.
Specific indications for use for the ImageChecker-CT Workstation are the display of a composite view of 2D cross-sections, and 3D volumes of chest CT images, including findings or regions of interest ("ROI") identified by the radiologist or Computer Assisted Detection ("CAD") findings.
The ImageChecker-CT System is a combination of dedicated computer software and hardware. The System uses an off-the-shelf personal computer with Windows and Linux-based CPUs, a hard drive, and a single monitor.
The provided document, K023003 for the ImageChecker-CT Workstation, does not contain information about acceptance criteria or a study proving the device meets specific performance criteria.
Instead, the document primarily focuses on establishing substantial equivalence to predicate devices. This means that instead of presenting a stand-alone performance study with acceptance criteria, the manufacturer is arguing that their device is as safe and effective as other legally marketed devices with similar intended use and technological characteristics.
Therefore, many of the requested details cannot be extracted from this specific 510(k) summary. I can only provide information directly mentioned or inferable from the document regarding the type of evaluation conducted.
Here's a breakdown of the requested information based on the provided text:
1. Table of acceptance criteria and the reported device performance
The document does not specify performance acceptance criteria or report device performance metrics in the way a clinical performance study would for a new device. The "Studies" section states, "The ImageChecker-CT Workstation will undergo design verification tests for conformance with specifications." This implies internal testing against design specifications, not necessarily clinical performance metrics.
2. Sample size used for the test set and the data provenance
Not applicable. The document describes a comparison to predicate devices for substantial equivalence, not a performance study with a distinct test set.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. The document does not describe a performance study involving ground truth establishment by experts.
4. Adjudication method for the test set
Not applicable. No test set or expert adjudication is described for a performance study.
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. The document makes no mention of an MRMC study or any assessment of human reader improvement with AI assistance. The device is described as a "general imaging workstation" that can display CAD findings, but its effectiveness with CAD is not studied here.
6. If a standalone (i.e. algorithm only, without human-in-the-loop performance) was done
No. The document describes a workstation for displaying images and CAD findings, but it does not report on the standalone performance of any algorithm. The 510(k) focuses on the workstation itself, not the performance of a specific CAD algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable. No performance study with ground truth is described.
8. The sample size for the training set
Not applicable. The document does not describe the development or training of an algorithm.
9. How the ground truth for the training set was established
Not applicable. The document does not describe the development or training of an algorithm.
§ 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).