Test set of proximal CBCT acquisitions from the USA and France.
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Indications for Use
FlightPlan for Liver is a post processing software package that helps the analysis of 3D X-ray angiography images of the liver. Its output is intended to be used by physicians as an adjunct means to help visualize vasculature and identify arteries leading to the vicinity of hypervascular regions of interest in the liver.
Device Story
FlightPlan for Liver is a software-only post-processing application for 3D X-ray angiography (CBCT) images. Used by interventional radiologists in clinical settings during the planning phase of liver embolization, it assists in visualizing hepatic arterial anatomy and identifying hypervascular lesions. The device processes CBCT inputs to perform semi-automatic segmentation of the liver arterial tree and vicinity vessels. New features include a deep learning-based liver segmentation algorithm and a non-deep learning Virtual Parenchyma Visualization (VPV) algorithm. VPV estimates and displays distal liver regions adjacent to distal vessels based on user-defined reference points. The software operates on GE Advantage Workstation and AW Server platforms. Output is visualized by the physician to aid in selecting embolization injection points and planning treatment. It provides an adjunct visualization tool to improve anatomical understanding, potentially increasing the precision of embolization procedures.
Clinical Evidence
Clinical assessment involved interventional radiologists evaluating 3D X-ray angiography image pairs (non-selective vs. selective CBCT) from France and the USA. Using a 5-point Likert scale, clinicians confirmed the device aids in visualizing/analyzing images, estimating distal liver regions, and planning embolization procedures. Bench testing of the two new algorithms used a database of contrast-injected CBCT acquisitions for training/testing (DL algorithm) and a test set of proximal CBCT acquisitions compared against selective contrast-injected CBCT ground truth (VPV algorithm). All results met predefined acceptance criteria.
Technological Characteristics
Software-only post-processing application. Operates on GE Advantage Workstation and AW Server platforms. Features: multi-modality 3D review, semi-automatic arterial tree segmentation, and interactive vessel/parenchyma visualization. Algorithms: deep learning-based liver segmentation and non-deep learning Virtual Parenchyma Visualization. Connectivity: DICOM (NEMA PS 3.1-3.20) compliant. Developed under ISO 13485 and 21 CFR 820 quality systems.
Indications for Use
Indicated for physicians to aid in the evaluation of hepatic arterial anatomy during the planning phase of embolization procedures by visualizing vasculature and identifying arteries leading to hypervascular lesions in the liver using 3D X-ray angiography images.
Regulatory Classification
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.
Special Controls
*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).
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October 22, 2021
Image /page/0/Picture/1 description: The image contains two logos. The logo on the left is the Department of Health & Human Services - USA logo. The logo on the right is the FDA U.S. Food & Drug Administration logo. The FDA logo is in blue.
GE Medical Systems SCS % Ning Wen Regulatory Affairs Leader 283, rue de la Miniere Buc. 78530 FRANCE
Re: K210807
Trade/Device Name: FlightPlan for Liver Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: LLZ Dated: September 29, 2021 Received: September 30, 2021
Dear Ning Wen:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part
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801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4. Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
, for
Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known) K210807
Device Name
FlightPlan for Liver
Indications for Use (Describe)
FlightPlan for Liver is a post processing software package that helps the analysis of 3D X-ray angiography images of the liver. Its output is intended as an adjunct means to help visualize vasculature and identify of hypervascular lesions in the liver. This adjunct information may be used by physicians to aid them in their evaluation of hepatic arterial anatomy during the planning phase of embolization procedures.
| Type of Use (Select one or both, as applicable) | |
|----------------------------------------------------------------------------------|---------------------------------------------------------------------------------|
| <div> <span> Prescription Use (Part 21 CFR 801 Subpart D) </span> </div> | <div> <span> Over-The-Counter Use (21 CFR 801 Subpart C) </span> </div> |
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Image /page/3/Picture/1 description: The image shows the logo for General Electric (GE). The logo consists of the letters "GE" in a stylized script, enclosed within a blue circle. The circle is surrounded by a swirling, decorative border, also in blue. The logo is simple, recognizable, and represents the brand identity of General Electric.
#### K210807 510(k) Summary of Safety and Effectiveness
In accordance with 21 CFR 807.92 the following summary of information is provided.
| Date: | October 20, 2021 |
|--------------------|----------------------------------------------------------------|
| Submitter: | GE Medical Systems SCS |
| | Establishment Registration Number - 9611343 |
| | 283, rue de la Minière |
| | 78530 Buc, France |
| Primary Contact: | Ning WEN |
| | Regulatory Affairs Leader |
| | GE Healthcare, (GE Medical Systems SCS) |
| | Tel: +33 6 4637 3852 |
| | Email: ning.wen@ge.com |
| Secondary Contact | John Jaeckle |
| | Chief Regulatory Affairs Strategist |
| | Tel: +1 262 424 9547 |
| | Email: john.jaeckle@ge.com |
| Device Trade Name: | FlightPlan for Liver |
| Common/Usual Name: | FlightPlan for Liver, with Parenchyma Analysis option |
| Regulation Number: | 21CFR 892.2050, Medical image management and processing system |
| Product Code: | LLZ |
| Regulatory Class: | Class II |
| Predicate Device: | |
| | Device Name: |
| | Manufacturer: |
| | 510(k) number: |
| | Regulation Number: |
| | Product Code: |
| Regulatory Class: | Class II |
| Reference Device: | |
| | Device Name: |
| | Manufacturer: |
| | 510(k) number: |
| | Regulation Number: |
| | Product Code: |
| Regulatory Class: | Class II |
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Image /page/4/Picture/1 description: The image shows the logo for General Electric (GE). The logo is a blue circle with the letters "GE" in white inside. The letters are stylized and connected, and the circle is surrounded by a swirling pattern. The logo is simple and recognizable, and it is associated with a well-known company.
# Device Description and Marketed Devices:
FlightPlan for Liver with the Parenchyma Analysis option is a post-processing, software-only application using 3D X-ray angiography images (CBCT) as input. It helps physicians visualize and analyze vasculature to aid in the planning of endovascular embolization procedures in the liver. It was developed from modifications to the predicate device, GE's FlightPlan for Liver [K121200], including the addition of 2 new algorithms supporting the Parenchyma Analysis option. The Parenchyma Analysis option is what triggered this 510k.
The subject device also includes a feature, Live Tracking, that was cleared in the reference device, GE's FlightPlan for Embolization. The software operates on GE's Advantage Workstation [K110834] platform and AW Server [K081985] platform and is an extension to the GE's Volume Viewer application [K041521].
The primary features of the software are:
- Multi-modality 3D review to load and compare CBCT, CT, MR, PET, NM dataset side by side with a CBCT dataset.
- Semi-automatic segmentation of the liver arterial tree from an operator-defined starting point in the CBCT images.
- Definition by operator of target(s).
- Semi-automatic segmentation (displayed using color highlights) of vessels from the operatordefined starting point to the vicinity of each target. The vessels are semi-automatically highlighted and are called "vicinity vessels".
- Ability to manually add and remove vessels in the vicinity of the targets.
- Selective display (Live Tracking) of both proximal vessels interactively from a reference point determined by the user's cursor on the vessel, used also in the reference device FlightPlan for Embolization.
- Ability to mark points of interest (POI) to store a cursor position.
- The Parenchyma Analysis option which includes the two new algorithms which triggered this 510k:
- The deep learning-based Liver Segmentation algorithm that performs an automated segmentation of the entire liver on injected CBCT acquisitions. The outputted liver segmentation is an intermediate result that is used as a boundary for the second algorithm, Virtual Parenchyma Visualization (VPV).
- o The non-deep learning Virtual Parenchyma Visualization algorithm that selectively displays, for visualization purposes, the estimated distal liver region adjacent to the distal parts of the computed skeleton of the vessel segmentation (Virtual Parenchyma) interactively from a userdetermined reference point(s).
- Saving of results and export optionally to GE's Vision application [K092639] for 3D road-mapping.
FlightPlan for Liver is intended to be used during the planning phase of liver embolization procedures. These procedures workflows are split in 5 main phases:
- (1) Planning, using 2D DSA and CBCT to characterize the anatomy and identify injection point candidates.
- (2) Navigation, to position catheters under fluoroscopic guidance.
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- (3) Decision, to confirm treatment points using 2D DSA and Selective CBCT.
- (4) Treatment, phase which consists into injection of drug to the confirmed treatment points.
- (5) Control, to assess the embolization procedure end-point.
The proposed device is only used as part of (1) Planning.
## Intended Use:
FlightPlan for Liver is a post processing software package that helps the analysis of 3D X-ray angiography images of the liver. Its output is intended to be used by physicians as an adjunct means to help visualize vasculature and identify arteries leading to the vicinity of hypervascular regions of interest in the liver.
#### Indication for Use:
FlightPlan for Liver is a post processing software package that helps the analysis of 3D X-ray angiography images of the liver. Its output is intended as an adjunct means to help visualize vasculature and identify arteries leading to the vicinity of hypervascular lesions in the liver. This adjunct information may be used by physicians to aid them in their evaluation of hepatic arterial anatomy during the planning phase of embolization procedures.
## Technology:
The proposed device, FlightPlan for Liver, employs the same fundamental scientific technology as its predicate device (FlightPlan for Liver) and its reference device (FlightPlan for Embolization).
In addition, the proposed device FlightPlan for Liver includes selective display tools helping user's visualization of vascular structures as well as estimated distal liver regions adjacent to distal vessels. The selective display of vessels (Live Tracking) and the selective display of estimated distal liver regions (Virtual Parenchyma) are interactive with user's cursor, based on the computed skeleton of the vessel tree segmentation for Live Tracking and on two new algorithms: deep learning-based Liver Segmentation algorithm; and non-deep learning Virtual Parenchyma Visualization algorithm for Virtual Parenchyma.
## Device Modification Overview
The table below summarizes the substantive feature/technological differences and similarities between the predicate device and the proposed device:
| Specification | Predicate Device:<br>FlightPlan for Liver<br>[K121200] | Proposed Device:<br>FlightPlan for Liver |
|-------------------------------------------------------------------------------|--------------------------------------------------------|------------------------------------------|
| Multi-modality 3D review &<br>comparison of CBCT, CT, MR,<br>PET, NM datasets | Identical | Identical |
| Semi-automatic segmentation<br>of the liver arterial tree | Yes | Yes |
| Definition by operator of<br>target(s) | Yes | Yes |
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Image /page/6/Picture/1 description: The image shows the General Electric (GE) logo. The logo consists of the letters 'GE' in a stylized, cursive font, enclosed within a circular frame. The frame has a design that resembles water droplets or swirling lines, giving it a dynamic and fluid appearance. The color of the logo is a light blue.
| Specification | Predicate Device:<br>FlightPlan for Liver<br>[K121200] | Proposed Device:<br>FlightPlan for Liver |
|-----------------------------------------------------------------------------------|--------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Semi-automatic segmentation<br>of "vicinity vessels" | Yes | Yes |
| Ability to manually add and<br>remove "vicinity vessels" | Identical | Identical |
| Segmentation and selective<br>display of parts of the<br>vasculature | Yes, using target<br>defined by user. | Yes, using tool for Live Tracking of vessels. |
| Ability to mark POIs | Yes | Yes |
| Deep learning-based full Liver<br>Segmentation | No, full liver<br>segmentation can only<br>be done manually. | Yes, DL based automated segmentation of<br>the full liver. |
| Selective display of the<br>estimated distal liver region<br>(Virtual Parenchyma) | No | Yes, the non-deep learning Virtual<br>Parenchyma Visualization algorithm<br>selectively displays, for visualization<br>purposes, the estimated distal liver region<br>adjacent to the distal parts of the<br>computed skeleton of the vessel<br>segmentation (Virtual Parenchyma). |
| Save and export | Identical | Identical |
| Platform | Advantage<br>Workstation | Advantage Workstation, AW Server |
## Determination of Substantial Equivalence:
#### Summary of Non-Clinical, Design Control Testing
FlightPlan for Liver has successfully completed the design control testing per GE's quality system. No additional hazards were identified, and no unexpected test results were observed. The proposed device complies with NEMA PS 3.1 - 3.20 (2016) Digital Imaging and Communications in Medicine (DICOM) Set (Radiology) standard.
The proposed device, FlightPlan for Liver, has successfully completed the required design control testing per GE Healthcare Quality Management System. It was designed and will be manufactured under the Quality System Regulations of 21CFR 820 and ISO 13485.
The following quality assurance measures were applied to the development of the device:
- Requirements Definition
- Risk Analysis
- Technical Design Reviews
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- Formal Design Reviews
- Software Development Lifecycle
- · Performance testing (Verification, Validation)
- System Testing (Verification, Validation)
The proposed FlightPlan for Liver has been successfully verified on the AW VolumeShare workstation and AW Server platforms. All the testing and results did not raise new or different questions of safety and effectiveness other than those already associated with predicate device.
Software documentation for a MODERATE level of concern.
# Additional Non-Clinical Testing
Engineering bench testing of the two new algorithms for the Parenchyma Analysis option demonstrated the new algorithms' capabilities to selectively display vascular structures and estimated distal liver region to support substantial equivalence and demonstrate performance.
A database of contrast injected CBCT liver acquisitions from clinical sites in the USA and France was used for the training and testing of the deep learning Liver Segmentation algorithm.
The non-DL Virtual Parenchyma Visualization algorithm's performance was evaluated using a test set of proximal CBCT acquisitions from the USA and France. This test set was used to evaluate the performance of the VPV algorithm compared to selective contrast injected CBCT exams from same patients used as the ground truth.
The variety of exams in the evaluations is representative of the clinical scenarios where FlightPlan for Liver with the Parenchyma Analysis option is intended to be used. The test results of both of the algorithms met their predefined acceptance criteria.
## Summary of Clinical Testing
A sample of 3D X-ray angiography image pairs, from France and the USA, of non-selective CBCT and selective CBCT images representative of clinical practice in liver embolization were assessed by interventional radiologists using a 5-point Likert scale. The clinical assessment demonstrated that the proposed device FlightPlan for Liver with the Parenchyma Analysis option met its predefined acceptance criteria and helps physicians visualize and analyze 3D X-ray angiography images, can be used to estimate distal liver regions from a reference point, and aids in the planning of embolization procedures in the liver, including the selection of embolization injection points.
## Substantial Equivalence Conclusion
The changes to FlightPlan for Liver cleared in 2012 do not create a new Intended Use. FlightPlan for Liver with the Parenchyma Analysis option has identical or equivalent technological characteristics as its predicate device and reference device.
GE's quality system's design, verification, and risk management processes did not identify any new questions of safety or effectiveness, hazards, unexpected results, or adverse effects stemming from the changes to the predicate.
Based on development under GE Healthcare's quality system, successful design verification, software documentation for a "Moderate" level of concern, along with the engineering bench testing and the
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Image /page/8/Picture/1 description: The image shows the General Electric (GE) logo. The logo consists of the letters 'GE' in a stylized, cursive font, enclosed within a circular shape. The circle has a swirling pattern around the letters, giving it a dynamic and recognizable appearance. The logo is presented in a blue color.
clinical evaluation demonstrate that the proposed FlightPlan for Liver with the Parenchyma Analysis option is substantially equivalent to, and hence as safe and as effective for its Intended Use as the legally marketed predicate device.
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Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
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Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
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Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
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Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
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Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
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Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
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Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
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Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.