(15 days)
Aegis is a software application that is intended for use in analyzing magnetic resonance imaging (MRI) medical images as well as other multi-modality images. Its primary goal is to identify where and how deep a biopsy or localization needle should be inserted into an imaged breast in order to strike a targeted lesion or region of interest, as chosen by a trained medical professional. Aeris receives images and data from various sources (including but not linited to CT, MR, US, computed and direct radiographic devices, secondary capture devices, scanners, imaging gateways or imaging sources). Aegis can be used to communicate, process, and display medical images. Users have access to various image processing and measurement tools to assist them in viewing images. These user-defined post-processing functions include image subtractions, multiplanar reformats, maximum intensity projections, and segmenting of regions based on enhancement characteristics.
The digitized mammographic images and/or ultrasound images displayed by Aegis on the laptop display (or on any display not approved by the FDA for such purposes) must not be used for primary diagnostic interpretation.
Typical users of Aegis are trained medical professionals, including but not limited, to radiologists, technologists and clinicians. When interpreted by a skilled user, this device provides information that may be useful in screening and diagnosis. Patient management decisions shoulding be made solely on the results of Aegis analysis.
Aegis is one of the components of a PACS (Picture Archiving and Communications System), Aegis is visualization software designed for breast imaging and intervention procedures. Aegis receives DICOM 3.0 images over a medical imaging network where its primary goal is to identify where and how deep a biopsy needle should be inserted into an imaged breast in order to strike a targeted lesion or region of interest, as chosen by a trained medical professional.
This 510(k) submission (K070244) for Aegis does not contain specific acceptance criteria or details of a study proving the device meets acceptance criteria in the provided document. The submission focuses on device description, indications for use, and comparison to a predicate device to demonstrate substantial equivalence, which is typical for 510(k) submissions.
Therefore, I cannot populate the table or provide details for the requested points based solely on the provided text.
The document states: "The potential hazards have been studied and controlled as part of the product development validation houring risk analysis, test and design considerations, and planned verification and validation testing processes. Aegis provides images and functionality comparable to the breadicate device." This indicates that some validation and verification testing was performed, but the specifics of these tests, acceptance criteria, and results are not included in this summary.
Information not available in the provided document:
- A specific table of acceptance criteria and reported device performance.
- Sample sizes used for any test sets.
- Data provenance (country of origin, retrospective/prospective).
- Number and qualifications of experts for ground truth.
- Adjudication method for test sets.
- Results of a multi-reader multi-case (MRMC) comparative effectiveness study.
- Results of a standalone (algorithm only) performance study.
- Type of ground truth used (pathology, expert consensus, outcomes data).
- Sample size for the training set.
- How ground truth for the training set was established.
§ 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).