(120 days)
FlightPlan for Embolization is a post processing software package that helps the analysis of 3D X-ray angiography images. Its output is intended to be used by physicians as an adjunct means to help visualize vasculature during the planning phase of embolization procedures. FlightPlan for Embolization is not intended to be used during therapy delivery.
The output includes segmented vasculature, and selective display of proximal vessels from a reference point determined by the user. User-defined data from the 3D X-ray angiography images may be exported for use during the guidance phase of the procedure. The injection points should be confirmed independently of FlightPlan for Embolization prior to therapy delivery.
FlightPlan for Embolization is a post-processing, software-only application using 3D X-ray angiography images (CBCT) as input. It helps clinicians visualize vasculature to aid in the planning of endovascular embolization procedures throughout the body.
A new option, called AI Segmentation, was developed from the modifications to the predicate device, GE HealthCare's FlightPlan for Embolization [K193261]. It includes two new algorithms. This Al Segmentation option is what triggered this 510(k) submission.
The software process 3D X-ray angiography images (CBCT) acquired from GE HealthCare's interventional X-ray system [K181403], operates on GEHC's Advantage Workstation (AW) [K110834] platform and AW Server (AWS) [K081985] platform, and is an extension to the GE HealthCare's Volume Viewer application [K041521].
FlightPlan for Embolization is intended to be used during the planning phase of embolization procedures.
The primary features/functions of the proposed software are:
- Semi-automatic segmentation of vasculature from a starting point determined by the user, when AI Segmentation option is not activated;
- Automatic segmentation of vasculature powered by a deep-learning algorithm, when Al Segmentation option is activated;
- Automatic definition of the root point powered by a deep-learning algorithm, when AI Segmentation option is activated;
- Selective display (Live Tracking) of proximal vessels from a point determined by the user's cursor;
- Ability to segment part of the selected vasculature;
- Ability to mark points of interest (POI) to store cursor position(s);
- Save results and optionally export them to other applications such as GEHC's Vision Applications ● [K092639] for 3D road-mapping.
Here's a breakdown of the acceptance criteria and the study details for the GE Medical Systems SCS's FlightPlan for Embolization device, based on the provided text:
Acceptance Criteria and Device Performance
| Feature / Algorithm | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Vessel Extraction | 90% success rate | 93.7% success rate |
| Root Definition | 90% success rate | 95.2% success rate |
Study Details
1. Sample Size Used for the Test Set and Data Provenance:
- Test Set Sample Size: 207 contrast-injected CBCT scans, each from a unique patient.
- Data Provenance: The scans were acquired during the planning of embolization procedures from GE HealthCare's interventional X-ray system. The text indicates that these were from "clinical sites" and were "representative of the intended population" but does not specify countries of origin. The study appears to be retrospective, using existing scans.
2. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications:
- Vessel Extraction: 3 board-certified radiologists.
- Root Definition: 1 GEHC advanced application specialist.
3. Adjudication Method for the Test Set:
- Vessel Extraction: Consensus of 3 board-certified radiologists. (Implies a qualitative agreement, not a specific quantitative method like 2+1).
- Root Definition: The acceptable area was manually defined by the annotator (the GEHC advanced application specialist).
4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:
- No, an MRMC comparative effectiveness study was not explicitly described in terms of human readers improving with AI vs. without AI assistance. The non-clinical testing focused on the algorithms' performance against ground truth and the clinical assessment used a Likert scale to evaluate the proposed device with the AI option, rather than a direct comparison of human reader performance with and without AI.
5. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:
- Yes, a standalone performance evaluation was conducted for both the vessel extraction and root definition algorithms. The reported success rates of 93.7% and 95.2% are measures of the algorithms' performance against established ground truth without a human in the loop for the primary performance metrics.
6. The Type of Ground Truth Used:
- Vessel Extraction: Expert consensus (3 board-certified radiologists).
- Root Definition: Manual definition by an expert (GEHC advanced application specialist), defining an "acceptable area."
7. The Sample Size for the Training Set:
- The document states that "contrast injected CBCT scans acquired from GE HealthCare's interventional X-ray system [K181403] were used for designing and qualifying the algorithms." However, it does not specify the sample size for the training set. It only mentions that a test set of 207 scans was "reserved, segregated, and used to evaluate both algorithms."
8. How the Ground Truth for the Training Set Was Established:
- The document does not explicitly state how the ground truth for the training set was established. It only details the ground truth establishment for the test 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).