(55 days)
i-Rapha Solution is intended for use as a primary diagnostic and analysis tool for diagnostic images for hospitals, imaging centers, radiologists and any user who requires and is granted access to patient image, demographic.
i-Rapha View, a component of i-Rapha Solution, displays and manages diagnostic quality DICOM images.
Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using cleared monitors intended for mammography display.
The i-Rapha solution is a professional DICOM web browser application that conforms HTML5 standards to receive, store, and view DICOM images; utilizable under any web browser that supports HTML 5 protocols (e.g. Chrome Browser). This web browser application supports various types of annotation for medical images interpretation.
The i-Rapha solution is a software device that does not contact the patient, nor does it control any life sustaining devices. The software does not provide any diagnostic assistance to the physician.
The i-Rapha solution allows displaying of image studies that may not in the location as the modality. With its Web features, it is possible to review and manipulate the images of the studies located in a remote server. The i-Rapha View, a component of i-Rapha Solution, is an HTML5-based DICOM Viewer. The i-Rapha View can be used in any operating system because it can be executed by using a web browsers and especially Google Chrome that supports HTML5 regardless of the type of operating system.
Any diagnostic determination or treatment is solely determined by a physician and not the software. A physician, providing ample opportunity for competent human intervention, interprets images and information being displayed and printed.
The i-Rapha solution allows users to take full advantage of the radiographic images from various modalities in order to obtain invaluable mission critical diagnostic data and images.
The users can access their own diagnostic environment anywhere, anytime on PC.
This document is a 510(k) Premarket Notification from IRM, Inc. to the FDA regarding their device, i-Rapha Solution. The primary purpose of this document is to demonstrate "substantial equivalence" of the i-Rapha Solution to a legally marketed predicate device (DG PACS, K152977).
A key takeaway from this document is that no clinical studies (which would typically involve patient data and human readers) were conducted for the i-Rapha Solution. The substantial equivalence claim is based entirely on non-clinical testing and a comparison of technological characteristics with the predicate device.
Therefore, many of the requested details about acceptance criteria, ground truth, sample sizes for test sets, expert qualifications, and MRMC studies, cannot be found in this document because they were not performed as part of this specific 510(k) submission. This device, being a "Picture archiving and communications system" (PACS) device, is primarily about displaying and managing diagnostic images, rather than providing AI-driven diagnostic assistance where such detailed clinical validation would be more commonly required.
Based on the provided document:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state quantitative performance acceptance criteria or report specific performance metrics from a clinical study for user performance. Instead, the acceptance is based on demonstrating substantial equivalence to a predicate device through:
- Similar Indications for Use.
- Similar Technological Characteristics.
- Passing Non-Clinical Test Summary (software verification and validation).
The "performance" demonstrated is that the device "was designed and developed according to a software development process and was verified and validated," as stated in the Non-Clinical Test Summary.
| Acceptance Criteria (Implied by Substantial Equivalence) | Reported Device Performance |
|---|---|
| Functional Equivalence: Device functions as intended for displaying and managing diagnostic images. | "i-Rapha solution contains MODERATE level of concern software was designed and developed according to a software development process and was verified and validated." |
| Safety and Effectiveness Equivalence: No new safety or effectiveness concerns compared to predicate. | "The differences in technological characteristics do not raise different questions of safety and effectiveness. In addition, performance testing conducted demonstrate that the subject devices are as safe and effective as the predicate." |
| Intended Use Equivalence: Matches predicate's intended use. | "i-Rapha Solution is intended for use as a primary diagnostic and analysis tool for diagnostic images for hospitals, imaging centers, radiologists and any user who requires and is granted access to patient image, demographic." (This exact text is shared with the predicate, with minor variations not impacting the core use). |
| Technological Equivalence: Similar underlying technology and standards. | The comprehensive table on page 5 compares various technological characteristics, showing many "Same" or "Similar" designations with explanations for differences (e.g., supported browsers, mobile viewer support). |
2. Sample size 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 applicable and not mentioned. No specific test set of medical images for clinical evaluation of diagnostic performance was used. The evaluation was based on software testing and feature comparison.
- Data provenance: Not applicable and not mentioned for clinical data.
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/Qualifications of Experts: Not applicable. No clinical ground truth was established by experts for a test set, as no clinical study was performed.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Adjudication Method: Not applicable. No test set requiring adjudication was used.
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: No. The document explicitly states: "No clinical studies were considered necessary and performed." This device is a PACS system, not an AI diagnostic assistance tool that would typically undergo such a study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone Performance: Not applicable. This device is a display and management system for diagnostic images, not an algorithm providing diagnostic outputs. Its function inherently involves a human user for diagnostic interpretation.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Type of Ground Truth: Not applicable. No clinical ground truth was established for the purpose of validating diagnostic performance.
8. The sample size for the training set
- Sample size for training set: Not applicable. This is not an AI/ML device that requires a training set of data.
9. How the ground truth for the training set was established
- Ground Truth for Training Set: Not applicable.
§ 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).