(84 days)
Image display of GE Ultrasound 3D/4D data sets for diagnostic purposes including measurements on displayed image.
Standalone software product with Primary Operating Functions:
• Display and editing of GE Ultrasound 3D/4D data sets
• Measurements on displayed image incl. derived calculations based on medical literature in the following applications: Abdominal, Obstetrics, Gynecology, Cardiology, Transrectal, Vascular, Cephalic, Small Parts, Pediatrics, Musko-Skeletal (MSK)
• Data storage (image, measurement and patient data)
• Data transfer to and from remote systems (e.g. via DICOM®1)
• Adding annotations to acquired image
This document describes the 510(k) premarket notification for GE Medical Systems Ultrasound and Primary Care Diagnostics' 4D View device. The 4D View is a software product intended for image display of GE Ultrasound 3D/4D datasets for diagnostic purposes, including measurements.
The submission claims substantial equivalence to its predicate device, 4D View (K131118), and references Voluson E10 (K172342). As the submission explicitly states, "The subject of this premarket submission, 4D View, did not require clinical studies to support substantial equivalence." Therefore, there is no study described that proves the device meets specific acceptance criteria based on clinical performance.
Based on the provided text, the following information can be extracted regarding the device and its assessment for substantial equivalence.
1. A table of acceptance criteria and the reported device performance:
Since no clinical studies were performed, there are no specific performance-based acceptance criteria or reported device performance metrics in terms of clinical accuracy (e.g., sensitivity, specificity, accuracy). The acceptance criteria for this submission are based on demonstrating substantial equivalence to the predicate device in terms of:
| Acceptance Criteria Category | Equivalence Claimed |
|---|---|
| Intended Use | Same |
| Capabilities | Same |
| Technological Characteristics | Same |
| Safety | Same |
| Effectiveness | Same |
The document states that the proposed 4D View adds workflow improvements and improvements to archive and DICOM functionality, implying performance enhancements in these areas compared to the predicate, but no quantitative metrics are given.
2. Sample size used for the test set and the data provenance:
Not applicable, as no clinical studies with a test set were conducted.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable, as no clinical studies with a test set were conducted.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
Not applicable, as no clinical studies with a test set were conducted.
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. The 4D View is described as a standalone software product primarily for displaying and measuring GE Ultrasound 3D/4D datasets. There is no mention of "AI" or a human-in-the-loop component that would require an MRMC study to assess reader improvement with AI assistance.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
While the device is a "standalone software product," the documentation does not describe a performance study for the algorithm without human-in-the-loop. The substantial equivalence is based on the device's functional and technological similarities to the predicate, not on a standalone performance study against a clinical ground truth.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
Not applicable, as no clinical studies were conducted that required establishing a clinical ground truth for performance evaluation.
8. The sample size for the training set:
Not applicable, as this device's submission does not describe an AI/machine learning model development process that would involve a training set.
9. How the ground truth for the training set was established:
Not applicable, as this device's submission does not describe an AI/machine learning model development process.
Summary of Non-Clinical Tests Used for Substantial Equivalence:
The primary evidence for substantial equivalence for the 4D View device came from non-clinical tests and a comparison to its predicate device. These included:
- Compliance with voluntary standards:
- ISO 14971:2007 (Risk Management)
- NEMA PS 3.1 -3.20 (DICOM standards)
- IEC 62304:2006 (Medical device software life cycle process)
- Quality assurance measures applied during development:
- Risk Analysis
- Requirements Reviews
- Design Reviews
- Testing on unit level (Module verification)
- Integration testing (System verification)
- Performance testing (Verification)
The manufacturer concluded that the proposed 4D View is as safe, as effective, and its performance is substantially equivalent to the predicate devices based on these non-clinical assessments and the functional comparison.
§ 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).