(42 days)
iMagic v2.0™ device is software intended for viewing and diagnostic interpretation of images acquired from Ultrasound and other DICOM compliant medical imaging systems (CT, MR, CR, DR), when installed on suitable commercial standard hardware.
iMagic v2.0™ receives Ultrasound images and other modality imaging studies over a network from servers, directly from the imaging modality or from an archive (including media) utilizing both lossless (reversible) and lossy (irreversible) compression. iMagic v2.0™ does not use lossy (irreversible) compression during image handling, manipulation, or storage.
Only DICOM, for presentation, images will be captured for display and diagnosis.
Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretation. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 Mpixel resolution and meets other technical specifications reviewed and accepted by FDA.
iMagic, a software application for medical imaging centers, that allows to easily record patient details with study information along with their images and to prepare reports that can be distributed to the patient either in paper printout or through the Internet (email). Moreover, it allows the user to retrieve images easily and to compare the images of the patient between different visits or to distribute the patient records in CD's. It also allows generating statistical data from the available details. Overall features include:
- . Prevent unauthorized access of Patient Records
- Easy search of Patient details .
- . Flexibility to design auto patient ID
- Report transmission by mail .
- . Cropping of live images
- Editing of AVI/cine loops
- Distribution of Reports and Images in CD .
- . Comparison of images between different visits of patient
- . Tagging of significant images/cineloops for future references
- . Generation of statistical data from available details
The provided text is a 510(k) summary for the iMagic v2.0™ Picture Archiving Communications System. It primarily focuses on demonstrating substantial equivalence to a predicate device and does not contain detailed information regarding acceptance criteria, a specific study designed to prove device performance against those criteria, or the specific performance metrics typically found in such studies.
Therefore, I cannot fulfill all parts of your request with the provided input. However, I can extract information relevant to the device description and its intended use.
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1. A table of acceptance criteria and the reported device performance:
The document does not report specific quantitative acceptance criteria or detailed device performance metrics that would typically be found in a study demonstrating such criteria. The submission is a 510(k) for a PACS system, which focuses on functional equivalence rather than diagnostic performance metrics like sensitivity, specificity, or AUC as seen in AI/CADe submissions. The "performance" described is in terms of general PACS functionalities and adherence to standards.
| Acceptance Criteria Category (Derived from Device Description) | Reported Device "Performance" / Functionality |
|---|---|
| Data Handling & Viewing | - Records patient details with study information and images |
| - Prepares reports for distribution (printout, internet/email) | |
| - Retrieves images easily | |
| - Compares images between different visits | |
| - Distributes patient records in CDs | |
| - Captures DICOM for presentation, display, and diagnosis | |
| - Receives images from Ultrasound and other DICOM compliant systems (CT, MR, CR, DR) over network, direct from modality, or archive | |
| - Utilizes lossless and lossy (irreversible) compression, but does not use lossy during image handling, manipulation, or storage | |
| Security & Workflow | - Prevents unauthorized access of Patient Records |
| - Easy search of Patient details | |
| - Flexibility to design auto patient ID | |
| - Report transmission by mail | |
| - Cropping of live images | |
| - Editing of AVI/cine loops | |
| - Tagging of significant images/cineloops for future references | |
| - Generation of statistical data from available details | |
| Regulatory & Safety | - Does not contact the patient |
| - Does not control any life sustaining devices | |
| - Physician interprets images and information, providing opportunity for human intervention | |
| - Conforms to voluntary standards and hazard analysis (minor concern) |
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):
Not specified in the provided text. The document does not describe a clinical or performance study with a test set of patient 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):
Not specified. Since no clinical test set or ground truth establishment process is described, this information is not present.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
Not specified. No such adjudication method is mentioned as there is no described test set.
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:
Not applicable and not specified. This is a PACS system, not an AI/CADe device designed to assist human readers in diagnosis. Therefore, an MRMC study measuring an AI's effect on human reader performance would not be relevant or expected for this submission, and none is mentioned.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
Not applicable and not specified. This is a PACS system, which is an infrastructure for image management and viewing, not a standalone diagnostic algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
Not specified. No ground truth is mentioned as no study involving diagnostic accuracy is described.
8. The sample size for the training set:
Not applicable and not specified. This is a PACS system and would not typically have a "training set" in the context of machine learning algorithms for diagnostics.
9. How the ground truth for the training set was established:
Not applicable and not specified. As above, no training set or ground truth establishment for a training set is relevant to this PACS device or mentioned in the document.
Summary of what the document does describe as proof of meeting acceptance criteria (implicitly):
The document primarily relies on substantial equivalence to a predicate device (Voyager PACS System, K062062). The "study" proving the device meets its (implicit) acceptance criteria is the comparison of technological characteristics and indications for use between iMagic v2.0™ and the predicate device. The conclusion states that "The 510(k) Pre-Market Notification for iMagic v2.0™ contains adequate information and data to enable FDA - CDRH to determine substantial equivalence to the predicate device." This means the device's functionality, safety, and effectiveness are considered to be on par with a device already legally marketed. The submission also mentions adherence to voluntary standards and a hazard analysis classified as "minor."
§ 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).