(13 days)
RapidiaColon ™ is a software application for the display and 3D visualization of medical data derived from digital modalities (CT and MRI scanners). It is intended for use by radiologists, clinicians and referring physicians to acquire, process, render, review, store, print, and distribute DICOM compliant image studies using standard PC hardware.
RapidiaColon™ is a software device for 3D (three dimensional) and 2D (two dimensional) viewing and manipulation of digital DICOM compliant images using graphics rendering technology. The software device provides 3D volume rendering (VR), multi-planar reconstruction (MPR), virtual endoscopy, and issues reports.
Here's an analysis of the provided text regarding the RapidiaColon™ device, focusing on the acceptance criteria and study information:
Unfortunately, the provided 510(k) summary for the INFINITT RapidiaColon™ System does not contain the detailed information necessary to fully answer all aspects of your request. This document focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed performance study with acceptance criteria and results.
Specifically, it lacks information on:
- Specific acceptance criteria.
- A dedicated study proving the device meets these criteria.
- Sample sizes for test or training sets.
- Data provenance.
- Details on expert consensus for ground truth.
- Adjudication methods.
- MRMC study results.
- Standalone performance.
- The type of ground truth used for performance evaluation.
- How ground truth was established for "training" data (though the device appears to be a viewing/processing tool, not one that uses machine learning in the modern sense of training data).
Based on the provided text, here's what can be extracted and what remains unknown:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not specified | Not specified |
Explanation: The 510(k) summary for RapidiaColon™ System does not provide explicit acceptance criteria or measured performance metrics for the device. The document's primary purpose is to establish substantial equivalence to a predicate device (Voxar Limited's plug 'n view 3d, version 1.0) based on technological characteristics and intended use, rather than presenting a detailed performance study with defined criteria and results. It primarily states that "Validation testing was provided that confirms that RapidiaColon performs all input functions, output functions, and all required actions according to the functional requirements specified in the Software Requirements Specification (SRS)." However, the specifics of these functional requirements, the tests performed, and the quantitative results are not included in this summary.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size for Test Set: Not specified.
- Data Provenance: Not specified (country of origin, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified.
- Role of Experts: Given the nature of the device (viewing and processing), "ground truth" as typically understood in AI/CAD performance studies (e.g., presence/absence of a lesion) is not directly applicable in the same way. The validation would likely involve functional testing to ensure accurate display and manipulation of images, not diagnostic accuracy against a ground truth.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Adjudication Method: Not specified.
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
- MRMC Study: Not mentioned or implied. The device is described as a "Picture Archiving Communications System" and a "software application for the display and 3D visualization of medical data." It does not appear to incorporate AI for diagnostic assistance, so an MRMC study comparing human readers with and without "AI assistance" would not be relevant in this context. It's a tool for visualization and manipulation, not an interpretation aid.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone Performance: The concept of "standalone performance" as it relates to AI algorithms is not applicable here. RapidiaColon™ is a software tool for image viewing and manipulation, not an independent algorithm making diagnostic determinations. Its "performance" would be related to its functionality (e.g., speed of rendering, accuracy of MPR reconstruction, stability) rather than a diagnostic output. The validation would have focused on its ability to perform its specified functions: acquiring, processing, rendering, reviewing, storing, printing, and distributing DICOM-compliant image studies.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Type of Ground Truth: Not specified in the context of diagnostic accuracy. For a viewing and processing system, "ground truth" would more likely refer to the correctness of the displayed medical data against the original DICOM data or the accuracy of its reconstruction algorithms, verifiable through technical specifications and controlled test cases rather than clinical outcomes or pathology.
8. The sample size for the training set
- Sample Size for Training Set: Not applicable/Not specified. This device is described as a viewing and manipulation tool, not a machine learning model that requires a "training set" in the conventional sense.
9. How the ground truth for the training set was established
- How Ground Truth for Training Set was Established: Not applicable. As noted above, the device does not appear to be an AI/ML model requiring a training set. Its functionality is based on established rendering and image processing algorithms.
§ 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).