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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

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.

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Vision 2, EVARVision, TrackVision 2 and HeartVision 2 software applications are intended to enable users to load 3D datasets and overlay and register in real time these 3D datasets with radioscopic or radiographic images of the same anatomy in order to support catheter/device guidance during interventional procedures.

Structures of interest and estimated dimensions can be overlaid on the radioscopic or radiographic images. Image processing can be applied to enhance the display of such images. This information is intended to assist the physician during interventional procedures.

The Stereo 3D option enables physicians to visualize and localize needles, points, and segments on a 3D model/space using a stereotactic reconstruction of radioscopic or radiographic images at a significantly lower dose than use of a full cone beam CT acquisition. This information is intended to assist the physician during interventional procedures.

Vision Applications are a group of software applications called Vision 2, EVARVision, TrackVision 2 and HeartVision 2 that share the same core functionalities to target different clinical procedures.

Vision Applications load 3D datasets previously acquired from an acquisition modality (CT, MR or CBCT) and prepared with Volume Viewer application [K041521]. They overlay and register in real-time these 3D datasets with the 2D X-ray live images acquired from the GE Interventional X-ray system [K181403] (called IGS X-ray system in the rest of the document) to help support localization and guidance of catheters / devices during interventional procedures, in conjunction with primary images, native live 2D X-ray images.

Vision Applications help physicians to perform interventional procedures by providing enhanced image quality and additional 3D information instead of 2D X-ray live images alone.

Vision Applications operate on GE's Advantage Workstation (AW) [K110834] platform and communicates with the IGS X-ray system [K181403] for receiving the live X-ray images.

The subject device, Vision Applications were developed from modifications to the primary predicate device Innova Vision Applications [K092639], including the addition of new optional feature "Digital Pen". The Digital Pen option is what triggered this 510k and was modified from the reference device, GE's IGS X-ray systems [K181403] under the name Stenosis Analysis. The Vision Applications include also Stereo 3D option feature [K152352, secondary predicate].

The primary features/functionalities of the Vision Applications are:

• . Digital Pen.
• Overlay of 2D/3D images.
• Reception and display of live 2D images and related information. ●
• Loading of 3D datasets.
• Review mode.
• Film/Sequence/photo store.
• . Display controls for Visualization of images: including Zoom/Roam, Rendering, Planning data display, Annotation display, Virtual Collimation, ECG Display, Calcification Visualization Enhancement, display adjustment tools.
• Automatic Registration: including A priori registration and Registration based on Augmented Calibration.
• Manual Registration.
• Bi-view registration.
• User Interface: control from AW and from Tableside.
• . 2D Modes.
• Send Angles: including EVAR Angles, Progress View/Bull's eye.
• . Stereo 3D.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on your provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for Test Set and Data Provenance

• Sample Size: The text states "a phantom with series of known dimension." It does not provide a specific numerical sample size for the test set.
• Data Provenance: The data was generated through "Engineering bench testing" using a "phantom." This indicates the data is prospective and simulated in a controlled environment, rather than from actual patient clinical data. The country of origin is not explicitly stated for this specific test, but the submitter is GE Medical Systems SCS, located in Buc, France.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: The document does not mention the use of experts to establish ground truth for this engineering bench testing. The ground truth for the dimension estimation was based on a "phantom with series of known dimension," implying a pre-defined, objective standard rather than expert consensus on images.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. The ground truth was based on a phantom with known dimensions, not on human interpretation requiring adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• MRMC Study: No, an MRMC comparative effectiveness study was not performed. The text explicitly states, "The subject of this premarket submission, Vision Applications, did not require clinical studies to support substantial equivalence."

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: Yes, the testing described appears to be a standalone performance study of the "Digital Pen option" specifically focusing on its "dimension estimation accuracy." This was performed using "engineering bench testing" with a "phantom," meaning the algorithm's performance was evaluated against known physical dimensions without human-in-the-loop assistance during the measurement evaluation. The overall device, however, is intended to assist human operators.

7. Type of Ground Truth Used

• Type of Ground Truth: For the "Digital Pen option" dimension estimation testing, the ground truth was objective, pre-defined physical dimensions of a phantom ("a phantom with series of known dimension").

8. Sample Size for Training Set

• Sample Size: The document does not provide information about the sample size used for the training set. This is common for submissions if the device is a modification of a predicate and primarily relies on engineering changes and validation rather than a completely new AI model.

9. How Ground Truth for Training Set was Established

• How Ground Truth was Established: The document does not provide information on how ground truth was established for a training set. This suggests that the development likely leveraged existing algorithms or established principles from the predicate devices and the reference device's "Stenosis Analysis" functionality, rather than requiring a new, extensive labeled training dataset for novel AI model development.

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The OEC 3D mobile fluoroscopy system is designed to provide fluoroscopic and digital spot images of adult and pediativ populations during diagnostic, interventional, and surgical procedures. Examples of a clinical application may include: orthopedic, gastrointestinal, endoscopic, neurologic, vascular, cardiac, citical care and emergency procedures.

The OEC 3D is a mobile fluoroscopic C-arm imaging system used to assist trained surgeons and other qualified physicians. The system is used to provide fluoroscopic X-ray images and volumetric reconstructions during diagnostic, interventional, and surgical procedures. These images help the physician visualize the patient's anatomy and interventional tools. This visualization helps to localize clinical regions of interest and pathology. The images provide real-time visualization and records of pre-procedure anatomy, in vivo-clinical activity and post-procedure outcomes.

The system is composed of two primary physical components. The first is referred to as the "C -Arm" because of its "C" shaped image gantry; the second is referred to as the "Workstation", and this is the primary user interface for the user to interact with the system. The C-arm has an interface tablet allowing a technician to interact with the system.

The C-arm is a stable mobile platform capable of performing linear motions (vertical, horizontal) and rotational motions (orbital, lateral) that allow the user to position the X-ray image chain at various angles and distances with respect to the patient anatomy to be imaged. The C-Arm is comprised of the high voltage generator, software, X-ray control, and a "C" shaped image gantry, which supports an X-ray tube and a Flat Panel Detector,

The workstation is a stable mobile platform with an articulating arm supporting a color image high resolution LCD display monitor. It also includes image processing equipment/software, recording devices, data input/output devices and power control systems.

On the C-Arm, the generator remains unchanged from the OEC Elite. This is also true for the 31 cm x 31 cm image receptor, consisting of a Thallium-doped Cesium Iodide [Cs] (TI)] solid state flat panel X-ray detector with Complementary Metal Oxide Semiconductor (CMOS) light imager. The X-ray tube housing and insert remains the same as on the predicate OEC Elite (K192819).

C-Arm functionality is managed by a digital flat tablet control panel mounted on the C-arm base. Motion is controlled by a joystick.

On the workstation, the main hardware includes a computer with integrated wireless capability and a dedicated computer for 3D reconstruction located within the storage bay. The OEC 3D employs the same software architecture and platform design that fully supports the flat panel detector as the OEC Elite and complies with IEC 60601-1. The OEC 3D includes the existing 2D imaging functionalities available on the OEC Elite including imaging and post processing applications.

The provided text does not contain specific acceptance criteria or a detailed study proving the device meets those criteria. Instead, it is a 510(k) premarket notification summary from the FDA, asserting substantial equivalence to predicate devices rather than demonstrating performance against explicit acceptance criteria with clinical data.

Here's an analysis of the information available in the document, and where details are explicitly not provided:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not provided in the document. The submission focuses on demonstrating substantial equivalence to predicate devices based on technological characteristics and non-clinical performance testing against general standards, rather than specific acceptance criteria for performance metrics.

2. Sample Size Used for the Test Set and Data Provenance

This information is not provided. The document states that "clinical data is not required to demonstrate substantial equivalence" and that the device was evaluated using "engineering bench testing" and "non-clinical performance testing." Therefore, there is no discrete "test set" of patient data in the clinical sense mentioned.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This information is not provided. Since clinical data was not used for the performance evaluation for substantial equivalence, no expert ground truth establishment for a test set is described.

4. Adjudication Method for the Test Set

This information is not provided. As no clinical test set with human assessments is described, no adjudication method is relevant or provided.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No, an MRMC comparative effectiveness study was not done. The document explicitly states: "The new performance claims did not require clinical data in order to establish safety or efficacy." Therefore, no effect size of human readers improving with AI vs. without AI assistance is reported.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The document describes non-clinical performance testing and engineering bench testing, which would broadly cover standalone algorithm performance in a technical sense (e.g., image quality metrics, reconstruction accuracy). However, it does not explicitly detail a "standalone performance study" in the context of clinical metrics like sensitivity, specificity, or reader performance. The focus is on demonstrating that the new 3D functionality is "substantially equivalent" to that of reference devices.

7. The Type of Ground Truth Used

The document does not describe the use of specific ground truth (expert consensus, pathology, outcomes data) in the context of clinical performance evaluation for substantial equivalence to the same extent as a traditional clinical study. The "ground truth" for the non-clinical performance testing would be derived from engineering specifications, phantom measurements, and compliance with standards (e.g., IEC 60601-1, NEMA XR-27). The 3D algorithm is stated to be "identical" to one of the reference devices (INNOVA IGS 5), implying its performance characteristics are assumed to be similar to that previously cleared device.

8. The Sample Size for the Training Set

This information is not provided. The document does not describe any machine learning or AI algorithm development that would involve a training set of data. The 3D algorithm is stated to be "identical" to one of the reference devices, suggesting it's an existing, proven algorithm rather than a newly trained one requiring a specific training set.

9. How the Ground Truth for the Training Set Was Established

This information is not provided, as no training set is mentioned.

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