(138 days)
Synaptive ImageDrive Pro is a device that displays medical images (including mammograms) and data from various imaging sources. Images and data can be viewed, communicated, processed and displayed within the system or across computer networks at distributed locations.
Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 Megapixel resolution and meet other technical specifications reviewed and accepted by the FDA.
Typical users of this system are trained professionals, including but not limited to radiologists, physicians, nurses, medical technicians, and assistants.
Synaptive ImageDrive Pro is a medical imaging informatics system that allows the storage, management, display and analysis of imaging and non-imaging data. The Synaptive ImageDrive Pro data repository can be populated either by manually uploading data through the user interface (UI) or in an unattended fashion by automatically receiving DICOM objects or HL7 messages from other information systems such as PACS and EMRs. Automatic data processing rules can be configured to process data when it arrives in the system. An example of this is when pre-operative MR scans are done and sent to ImageDrive to ensure that they were acquired using appropriate scan protocol before they are consumed downstream by other Synaptive applications, such as BrightMatter Plan (cleared as a Class-II device, K140337). Once in the system, the data is indexed so that it can be easily searched in the future. Imaging data can also be de-identified and securely shared with authorized persons. Further, the system provides an extensible architecture to enable local or distributed processing of the data. As data accumulates in the system, analytics can be generated to summarize, for example, intra- and inter-patient statistics and trends in surgical treatment planning based on surgical plan data that is output from external software that can generate data in compatible formats. An example of such external system is the surgical planning software manufactured by this applicant - - BrightMatter Plan. The subject device is composed of the following key features: A hierarchical folder system Three data storage areas Data processing functionality Analytics capability Image viewing capability
The provided text does not contain specific acceptance criteria or an explicit study describing the device's performance against those criteria in a quantitative manner. The document is a 510(k) summary for the Synaptive ImageDrive Pro, focusing on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance metrics from a dedicated clinical or non-clinical study to meet specific acceptance criteria.
However, based on the non-clinical testing and design validation sections, we can infer the intent of the acceptance criteria was to ensure the device performs as intended and is safe and effective.
Here's an attempt to answer your request based on the available information, with many points marked as "N/A" or "Not specified" due to the nature of the document:
1. Table of acceptance criteria and the reported device performance
Since specific quantitative acceptance criteria are not provided, I will infer general categories of performance based on the non-clinical testing performed.
| Acceptance Criteria Category (Inferred) | Reported Device Performance |
|---|---|
| Software Functionality | |
| (All requirements met) | "Software verification testing for each requirement specification" was conducted, implying that the software met its specified requirements. |
| System Reliability/Usability | |
| (System operates as intended by users) | "System validation testing using intended users" was performed, indicating the system's usability and functionality were validated in a simulated use setting. |
| Safety and Effectiveness | |
| (Equivalent to predicate device, no new questions of safety/effectiveness) | "The results support substantial equivalence to the predicate device and demonstrate that Synaptive ImageDrive Pro is safe for its intended use." The conclusion states that "the differences between the subject device and the predicate device do not raise any new questions regarding safety and effectiveness." |
| Quality Assurance Adherence | |
| (Software developed under quality management system) | Various quality assurance measures were applied: Software development life cycle, Software risk assessment, Risk assessment of OTS software, Risk assessment from Cyber and Information security perspective, Software configuration management and version control, Software issue tracking and resolution. (Performance implicitly means adherence to these processes). |
2. Sample size used for the test set and the data provenance
- Sample size for the test set: Not specified. The document mentions "System validation testing using intended users" but does not provide details on the number of users or the test cases/data used.
- Data provenance: Not specified. It's a medical imaging informatics system that displays images from "various imaging sources," but the origin of data used for testing is not detailed. The product description indicates it receives DICOM objects or HL7 messages from PACS and EMRs, implying it handles clinical data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not specified. The document mentions "System validation testing using intended users," which implies clinical professionals, but does not detail how ground truth was established for the validation tests or how many experts were involved.
4. Adjudication method for the test set
- 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
- No. The document explicitly states: "This technology is not new, therefore a clinical study was not considered necessary prior to release." The device is a Picture Archiving and Communication System (PACS) and generally, these systems are cleared based on substantial equivalence to existing technology, and not typically through MRMC studies that assess reader performance with and without AI. The device described does not appear to have an "AI" component that assists readers in interpretation in the way that would necessitate such a study.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
- The device itself is a PACS for viewing, communicating, processing, and displaying medical images. It's not an algorithm that performs a diagnostic task independently. Its "performance" is tied to its functional capabilities (storage, management, display, processing, communication). Software verification and system validation were done, which tests the algorithm/system's internal functionality.
7. The type of ground truth used
- Not explicitly stated for the "test set" in the context of diagnostic performance. For general software verification and system validation, the "ground truth" would be the expected behavior of the system as defined by its requirements and design specifications. For the "intended users" validation, it would be the successful execution of tasks by users in a simulated environment.
8. The sample size for the training set
- Not applicable. This device is a PACS, not a machine learning algorithm that requires a "training set" in the conventional sense. Its "training" is in its development and programming, rather than learning from data.
9. How the ground truth for the training set was established
- Not applicable, as there is no "training set."
§ 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).