(35 days)
Syngo Neuro-PBV IR is an extended software application to the InSpace 3D software option which allows the reconstruction of two-dimentional images acquired with a standard angiographic C-arm device into a three-dimentional image format.
Syngo Neuro-PBV-IR is intended for imaging primarily soft tissue for diagnosis, surgical planning, interventional procedures and treatment follow-up. It is design for the visualization of contrast enhanced blood distribution in the arterial and venous vessels in the head using color coded relative values for diagnosis.
This software is designed to visually assist physicians in the diagnosis and treatment of vessel malformations (i.e. Aneurysms, AVM's and Stenoses)
syngo Neuro-PBV IR is a post-processing software application designed to provide the physician with images similar to CT cerebral perfusion in the Interventional Radiography suite. The physician can use these images to visualize blood volume in the vasculature and blood-brain barrier without moving the patient to a CT system. A contrast agent is used to enhance the visualization of the blood flow. As with CT perfusion, the image is further enhanced using color as a reference of the amount of contrast filled blood in an area of the brain.
Here's an analysis of the provided text regarding the acceptance criteria and study for the syngo Neuro PBV IR device:
1. Table of Acceptance Criteria and Reported Device Performance
The provided text does not contain explicit acceptance criteria in a quantitative or qualitative form. It describes the device as an extension of a legally marketed predicate device (InSpace 3D) and asserts substantial equivalence based on functionality and intended use. There are no performance metrics (e.g., sensitivity, specificity, accuracy, or other benchmark values) stated as acceptance criteria, nor are there reported performance results against such criteria.
The document primarily focuses on establishing substantial equivalence by stating that:
- "Most of the functionality remains the same as used with the predicate device Inspace 3D (K011447)."
- "The functionality is the same or similar to the predicate device with enhanced algorithm to display syngo Neuro PBV IR images."
- "syngo Neuro PBV IR is intended for the same indications for use as the predicate Inspace 3D."
2. Sample Size Used for the Test Set and Data Provenance
The provided text does not mention any specific test set, sample size, or data provenance (e.g., country of origin, retrospective/prospective). The submission relies on a comparison to a predicate device rather than a new clinical performance study with a test set.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts
As no specific test set or clinical performance study is described, there is no information provided regarding experts or ground truth establishment for a test set. The document implies that healthcare professionals familiar with X-ray images would be the users, but this is not about ground truth for a study.
4. Adjudication Method for the Test Set
Since no test set or clinical study is described, there is no information on adjudication methods.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
The document does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. There is no discussion of human reader improvement with or without AI assistance.
6. Standalone Performance Study (Algorithm Only Without Human-in-the-Loop Performance)
The text does not describe a standalone performance study for the algorithm. The focus is on the software as an "accessory" and "extended software application" to an existing system, implying its use with human operators.
7. Type of Ground Truth Used
Given the absence of a performance study, the document does not specify the type of ground truth used. The method of demonstrating substantial equivalence relies on functional similarity and intended use alignment with the predicate device, rather than a direct comparison against a clinical ground truth.
8. Sample Size for the Training Set
The provided text does not mention any training set or its sample size. The device is presented as an "enhanced algorithm" extension, but details of its development or any machine learning training are not included.
9. How the Ground Truth for the Training Set Was Established
As no training set is discussed, there is naturally no information on how ground truth for a training set was established.
Summary of the Document's Approach to Demonstrating Safety and Effectiveness:
The 510(k) submission for syngo Neuro PBV IR primarily relies on demonstrating substantial equivalence to a previously cleared predicate device, InSpace 3D (K011447). The core argument is that syngo Neuro PBV IR is an extension of InSpace 3D, sharing the same hardware, software components, and essential functionality, with enhanced algorithms primarily for visualization.
Instead of presenting new performance data against specific acceptance criteria, the submission asserts equivalence in intended use and technological characteristics. This approach is common in 510(k) submissions where a new device is a minor modification or extension of an existing, cleared device. The "study" proving the device meets criteria is implicitly the demonstration of its functional similarity and an enhanced display algorithm compared to the predicate, implying that if the predicate was safe and effective, this extension also is, given its similar technological characteristics and same intended use.
§ 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).