K Number
K061029
Manufacturer
Date Cleared
2006-05-01

(17 days)

Product Code
Regulation Number
892.2050
Panel
RA
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

JETStream® Workspace is a nuclear medicine image display and processing workstation that provides software applications used to process, analyze, and display medical images/data. The results obtained may be used as a tool, by a nuclear physician, in determining the diagnosis of patient disease conditions in various organs, tissues, and other anatomical structures. The data processed may be derived from any nuclear medicine gamma camera. The JETStream® Workspace system should only be operated by qualified healthcare professionals trained in the use of nuclear medicine equipment.

Device Description

JETStream® Workspace is a Windows®-based Nuclear Medicine workstation for the Nuclear Medicine market segment. The computer system will consist of a Hewlett Packard XW4300 workstation or HP Compaq nc6230 Notebook or their equivalents. The comprehensive tools and features provided with this product, will allow the technologist and/or physician to perform image review, processing of source data, post processing, hardcopy production, interpretation, report generation and contains the utilities necessary to support the workflow and data management between those activities. The system will support connectivity aspects necessary to import and export data as required to accomplish daily work scenarios.

AI/ML Overview

The provided text is a 510(k) summary for the ADAC Laboratories JETStream® Workspace. It describes the device, its intended use, and states its substantial equivalence to predicate devices. However, it does not contain a detailed study report with acceptance criteria, reported device performance, sample sizes, ground truth establishment, or details about comparative effectiveness studies (MRMC or standalone).

The document primarily focuses on establishing substantial equivalence based on:

  • Similar intended use: Processing, analyzing, and displaying nuclear medicine images for diagnosis.
  • Technological comparison: Similar display, review, processing applications, data storage, and system utilities to predicate devices.
  • System performance: Implied to be similar to predicate devices based on the above, but no specific performance metrics or studies are reported.

Therefore, I cannot populate the requested table or provide detailed answers to most of your questions as the information is not present in the provided text.

Here's what can be extracted and what is missing:


1. Table of Acceptance Criteria and Reported Device Performance

Not available in the provided text. The document asserts "system performance" is similar to predicate devices but provides no specific quantitative acceptance criteria or reported performance metrics (e.g., sensitivity, specificity, accuracy, processing speed, image quality benchmarks).


2. Sample Size Used for the Test Set and Data Provenance

Not available in the provided text. There is no mention of a specific test set or clinical study data used to demonstrate performance. The submission relies on substantial equivalence to predicate devices.


3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

Not applicable/Not available. Since no specific test set or performance study is detailed, there's no mention of experts establishing ground truth for such a study.


4. Adjudication Method for the Test Set

Not applicable/Not available. No adjudication method is described as no test set data is presented.


5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, it appears no MRMC study was done or reported in this 510(k) summary. The document does not describe any studies involving human readers or comparative effectiveness of AI assistance.


6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

No, it appears no standalone performance study was done or reported in this 510(k) summary. The device is described as a workstation with software applications for a nuclear physician to use as a tool, implying human-in-the-loop operation, but no specific standalone algorithm performance is detailed.


7. The Type of Ground Truth Used

Not applicable/Not available. No ground truth type (e.g., pathology, expert consensus, outcomes data) is mentioned because the document does not describe a performance study requiring ground truth.


8. The Sample Size for the Training Set

Not available in the provided text. There is no mention of a training set for any algorithmic development, as the focus is on a workstation for image display and processing, not necessarily an AI diagnostic algorithm.


9. How the Ground Truth for the Training Set Was Established

Not applicable/Not available. As there's no mention of a training set, the method for establishing its ground truth is also not mentioned.


In summary, the provided 510(k) documentation focuses on the administrative and regulatory aspects of establishing substantial equivalence to existing devices, rather than presenting a detailed performance study with specific acceptance criteria and results. For a medical device like a workstation for image processing, the "performance" might refer more to its fidelity in displaying images, its processing capabilities (e.g., speed, accuracy of calculations on pixel data), and its adherence to standards, which are not explicitly quantified in this summary.

§ 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).