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Rapidia® is a software package intended for viewing and manipulating DICOM-compliant medical images from CT (computerized tomography) and MR (magnetic resonance) scanners. Rapidia can be used for real-time viewing, image manipulation, segmentation, 3D volume and surface rendering, virtual endoscopy, and reporting.

Rapidia® is a fast, practical and accurate tool for 3D (three dimensional) and 2D (two dimensional) viewing and manipulation of CT and MRI images using the most advanced graphics rendering technology. The proposed software provides volume rendering (VR), maximum/minimum intensity projection 3D (MIP/MinIP), surface shaded display (SSD), multi-planar reconstruction (MPR), virtual endoscopy, 2D image editing and segmentation (2D), and issues reports.

Here's an analysis of the provided text regarding the Rapidia® device, focusing on acceptance criteria and study details.

Executive Summary:

The provided 510(k) summary for the Rapidia® device offers very limited information regarding explicit acceptance criteria and a detailed study proving its performance. The primary focus of the document is on establishing substantial equivalence to a predicate device (Plug'n View 3D K993654) and demonstrating conformance to DICOM standards and internal functional requirements.

Acceptance Criteria and Device Performance:

Study Details:

The document describes a "Validation testing" but provides very few specifics about its methodology or results in terms of concrete performance metrics.

1. Sample size used for the test set and the data provenance: Not specified. The document only mentions "Validation testing was provided." We don't know the number of images, patient cases, or the origin (country, retrospective/prospective) of the data.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified. The document does not mention any expert involvement in establishing ground truth for testing.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not specified.
4. 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 is not mentioned. The device is purely an image processing and visualization tool, not an AI-assisted diagnostic aid in the context of this 2001 submission.
5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Yes, the "Validation testing" appears to be a standalone performance evaluation against the Software Requirements Specification (SRS), focusing on the software's functionality. It's an algorithm-only performance in the sense that it tests the software's ability to execute its programmed functions.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The "ground truth" for this device's validation appears to be its internal "Software Requirements Specification (SRS)." The testing confirmed the software performed "according to the functional requirements specified in the Software Requirements Specification (SRS)." This is essentially a black-box functional testing approach, not clinical ground truth.
7. The sample size for the training set: Not applicable/specified. This device, submitted in 2001, is described as an "Image processing and 3D visualization system." It does not appear to employ machine learning or AI that would require a "training set" in the modern sense. Its functionality is based on explicit programming for rendering and manipulation.
8. How the ground truth for the training set was established: Not applicable, as there's no mention of a training set or machine learning.

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