Search Results

QuickRad is a web-based PACS intended for use in radiology centers, diagnostic labs, and hospitals. It is designed to receive, store, transmit, process, and display medical images and associated data from various DICOM-compliant sources, including CT scanners, MRI systems, ultrasound machines, and X-ray devices. The system enhances communication and accessibility by allowing distributed access to images and data across computer networks. QuickRad also offers optional integration with FDA-cleared third-party Al models, enabling the visualization of Al-generated outputs. The system displays these outputs "as-is," with the safety and effectiveness of the Al models being covered under the original third-party manufacturer's regulatory clearance.Mammographic images may only be interpreted using a monitor that meets the technical specifications identified by the FDA. The system is designed for utilization by proficient and certified medical practitioners, including physicians, radiologists, and medical technicians.

QuickRad is a web-based PACS designed to optimize radiology workflows and enhance clinical efficiency. It allows seamless receipt, management, and processing of DICOM images from various modalities, including CT, MRI, ultrasound, X-ray, and more.

Key Features and Functions:

• Comprehensive Radiology Management: QuickRad provides end-to-end functionality for the storage, transmission, processing, and visualization of medical images, ensuring seamless collaboration across healthcare networks.
• Zero Footprint Viewer (ZFP): QuickRad's ZFP viewer offers cross-platform accessibility without the need for additional native software installation. It is compatible with macOS, Windows, Ubuntu and Chrome, Edge, Firefox browsers.
• . Enhanced Viewer Options: QuickRad ensures that all scans are displayed with true-to-source fidelity, offering optional FDA-cleared viewer integrations that enhance diagnostic accuracy.
• . Advanced 3D Viewer: QuickRad's 3D viewer empowers radiologists with cutting-edge image analysis tools, including:
  • o Smooth stack scrolling, zooming, panning, and reset options.
  • O Measurement tools for length, angles, and annotations.
  • Advanced visualization techniques such as Multiplanar Reconstruction (MPR) and Maximum Intensity O Projection (MIP).
  • O PET scan mode with customizable contrast settings, annotation capabilities, and snapshot tools for enhanced diagnostic insights.
• . Smart Reporting Editor: QuickRad includes a modality-specific report editor that simplifies report creation. Pre-built templates for various imaging studies ensure consistent report generation with voiceenabled editing features.
• . AI Integration: QuickRad offers optional integration with FDA-cleared third-party AI models, allowing radiologists to review AI-generated results directly within the platform. The AI output is displayed alongside original images for confirmation by qualified medical professionals.
• DICOM Compliance: Fully compliant with DICOM standards, QuickRad guarantees secure and interoperable ● image and data exchange across systems, ensuring compatibility with a wide range of imaging devices.
• . Secure Data Transmission: It adheres to strict security protocols, utilizing HTTPS, AES 256 encryption, and multi-factor authentication (MFA) for secure access.

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

Device Name: QuickRad
Regulation Number: 21 CFR 892.2050 (Medical Image Management And Processing System)
Product Code: LLZ

QuickRad is a web-based PACS designed to receive, store, transmit, process, and display medical images and associated data from DICOM-compliant sources. It also offers optional integration with FDA-cleared third-party AI models for visualization of AI-generated outputs.

1. Table of Acceptance Criteria and Reported Device Performance

The non-clinical performance data section outlines the studies performed and their objectives, which serve as the acceptance criteria. The reported device performance is consistently stated as meeting these criteria.

2. Sample size used for the test set and the data provenance

• Angle Measurement Study: 12 X-ray images (AP Pelvic, AP Knee, Lateral Ankle).
  • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). However, the context of a 510(k) submission for a PACS system suggests general medical imaging data.
• Other Measurement Studies (Length, Rectangle, Ellipse ROI, Probe, Reference Line): CT abdomen images for length, rectangle, ellipse ROI, and probe measurements; MR spine and brain images for reference line accuracy.
  • Data Provenance: Not explicitly stated.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Angle Measurement Study: "two experienced radiologists."
  • Qualifications: "experienced radiologists" (further details like years of experience or board certification are not provided).

For other testing types (software V&V, cybersecurity, usability, AI integration), the concept of "ground truth established by experts" in the same way as for clinical performance is not directly applicable. These studies validate the software's functionality, security, and usability against predefined requirements and standards.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

• Angle Measurement Study: "evaluated independently by two experienced radiologists." This suggests a comparison of their independent measurements against the device's measurements and the benchmark device. An explicit "adjudication" method (like a third reader resolving discrepancies) is not mentioned.

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, an MRMC comparative effectiveness study was not done for QuickRad itself for human reader improvement with AI assistance.
  • QuickRad offers "optional integration with FDA-cleared third-party AI models," and explicitly states: "The solution only supports the visualization of outputs of 3rd party AI models 'as-is'. The safety and effectiveness of the 3rd party model are covered under the original 3rd party manufacturer's regulatory clearance."
  • This means QuickRad does not claim to enhance human reader performance with its integrated AI. It merely displays the output of other cleared AI models. The effectiveness and safety of those AI models, including any human-AI collaboration benefits, would have been established in the separate regulatory clearances for those specific AI models (e.g., qXR, qCT LN Quant, qER, which are identified by their K-numbers).

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• No, a standalone algorithm-only performance study was not done for QuickRad itself.
  • QuickRad is a PACS/viewer, not a diagnostic AI algorithm. Its purpose is to manage and display images, and optionally display the output of other (standalone) FDA-cleared AI algorithms.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• For the measurement studies (angle, length, etc.): The ground truth was implicitly established by the measurements taken by the "two experienced radiologists" using a comparison against the FDA-cleared FlexView Diagnostic DICOM Viewer (K233226). This indicates a comparison to a cleared predicate device's performance as the benchmark/ground truth. It's not explicitly stated if a consensus was formed between the two radiologists or if their independent measurements were directly compared.

8. The sample size for the training set

• Not applicable. QuickRad is a PACS/viewer and not an AI algorithm itself. It does not have a "training set" in the machine learning sense. The individual third-party AI models that QuickRad integrates would have had their own training sets, but those are external to this submission.

9. How the ground truth for the training set was established

• Not applicable. (See point 8).

Ask a specific question about this device