The LungVision System is intended to enable users to segment previously acquired 3D CT datasets and overlay and register these 3D segmented data sets with fluoroscopic live X-ray images of the same anatomy in order to support catheter/device navigation during pulmonary procedures.

Device Description

The Lung Vision System (K163622) is designed to enable users to segment previously acquired 3D CT datasets and overlay and register these 3D segmented data sets with live X-ray images of the same anatomy in order to support catheter/device navigation during pulmonary procedures.

The Lung Vision System is designed to assist the physician in guiding endobronchial tools towards the target area of interest inside the patient lungs. Prior to the endoscopic procedure the system allows planning the target location and the path to the target area on the CT scan. During the endoscopic procedure the system overlays planned data over fluoroscopic images to support endobronchial tool navigation towards the area of interest. The system does not include the Fluoroscope, Bronchoscope or the external monitor. Lung Vision system includes a main unit and a tablet vs. the previous PC based hardware platform. Image processing algorithms are executed on the main unit and the tablet is used as a primary method of interacting with the system. The Tablet is for planning but is not for diagnostic purposes. Both can perform the following functions: segment previously acquired DICOM 3D CT image data, register DICOM 3D CT image data with live fluoroscopic X-ray image, overlay the segmented 3D CT dataset over a live fluoroscopic X-ray image of the same anatomy, obtained on a Fluoroscopic system.

AI/ML Overview

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

Important Note: The provided text is a 510(k) Summary, which is a premarket notification for new medical devices. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed clinical trial results for efficacy or a comprehensive standalone AI performance study. Therefore, some information typically found in a clinical study report (like detailed MRMC results, specific effect sizes, or a large, prospectively collected, expert-adjudicated dataset for de novo AI training) is not present here. The performance testing described is primarily focused on demonstrating that the device functions as intended and safely, matching the predicate.

Acceptance Criteria and Reported Device Performance

The provided text doesn't explicitly state quantitative acceptance criteria in a table format with specific performance metrics (e.g., "accuracy > X%", "sensitivity > Y%"). Instead, the acceptance criteria are implicitly defined by demonstrating substantial equivalence to a predicate device and successful completion of bench testing to ensure the device meets its own "requirement specifications" and "hazards mitigations."

The performance is reported in terms of functional equivalence and safety:

Acceptance Criteria Category	Reported Device Performance (Summary of Findings)
Functional Equivalence	The Lung Vision System performs the same functions as the predicate device (LungVision - K163622).
	It includes new features (Virtual Bronchoscopy, C-Arm based Tomography, Multi-view set-up, Real-time compensation, 3D Guidance, Tablet use) which are similar in functionality or technological characteristics to either the predicate or reference devices (Covidien - superDimension™ Navigation System V7.2 - K173244).
Performance & Accuracy	"met all requirements specifications"
	"was found to be equivalent in comparison to the predicate"
	Accuracy testing in "deformable tissue" was performed using pig lungs. (No specific quantitative metric provided)
Safety	Complies with ANSI/AAMI/ES 60601-1:2005(2012) and IEC 60601-1-2:2014 standards (electrical and electromagnetic compatibility).
	No patient-contacting parts (no biocompatibility testing needed).
Clinical Efficacy	Not directly assessed; presumed equivalent based on substantial equivalence to predicate.

Study Details

Sample Size Used for the Test Set and Data Provenance:
- Test Set Sample Size: Not explicitly stated as a separate "test set" in the context of typical AI model validation. The "bench tests" included "verification testing of the requirements, testing of hazards mitigations and performance testing of the system." This suggests internal testing against pre-defined specifications rather than a distinct, large, clinical test dataset.
- Data Provenance: Not specified. The document mentions "pig lungs" were used for some accuracy testing in "deformable tissue." This implies animal (in vitro/ex vivo) testing. There is no mention of human clinical data for the performance testing cited.
- Retrospective or Prospective: Not explicitly stated for performance testing. Given the "bench tests" and no clinical testing, it's likely internal, controlled testing rather than a large-scale retrospective or prospective patient study.
Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:
- Not applicable/Not stated. The "ground truth" for the performance testing described here (bench tests, pig lungs) relates to the system's technical specifications and physical performance (e.g., registration accuracy on deformable tissue) rather than diagnostic interpretations by human experts.
Adjudication Method for the Test Set:
- Not applicable/Not stated. Since the "test set" described is for bench performance, there's no mention of human expert adjudication.
Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- No. The document explicitly states: "Clinical: No clinical testing was performed." Therefore, no MRMC study comparing human readers with and without AI assistance was conducted or reported.
Standalone (Algorithm Only Without Human-in-the-Loop) Performance Study:
- A standalone performance study for the algorithm itself in terms of diagnostic accuracy (e.g., detecting lesions) was not the focus or purpose of this 510(k) submission. The device is a "system, image processing, radiological" intended to support catheter/device navigation by overlaying pre-acquired CT data onto live X-ray. Its performance is evaluated on its ability to accurately segment, register, and overlay images, and perform real-time compensation, not on its ability to autonomously diagnose.
- The "Performance Testing" section states, "We have performed bench tests and found that the Lung Vision met all requirements specifications and was found to be equivalent in comparison to the predicate. Testing includes verification testing of the requirements, testing of hazards mitigations) and performance testing of the system." This implies internal measurements of system performance (e.g., accuracy of registration or compensation) but not a standalone diagnostic outcome.
Type of Ground Truth Used:
- For the bench testing, the ground truth would have been the engineering specifications of the device's functions (e.g., the expected accuracy of C-Arm based Tomography or real-time compensation).
- For testing in "deformable tissue (pig lungs)," the ground truth would likely be physical measurements or imaging references to assess the system's ability to maintain accuracy in a dynamic environment, rather than a clinical diagnosis or pathology.
Sample Size for the Training Set:
- Not stated. The document doesn't discuss the details of the training data used for any algorithms (e.g., segmentation, registration, real-time compensation). As this is primarily a system modification and not a de novo AI diagnostic device, the specifics of algorithm training or AI model validation datasets are not a required part of this 510(k) summary. The "software upgrades" are described as "an algorithm improvement" or "a standard technology," implying refinements rather than entirely new AI models requiring extensive separate training data disclosure for this type of submission.
How the Ground Truth for the Training Set Was Established:
- Not applicable/Not stated. As the training set details are not provided, the method for establishing its ground truth is also not mentioned.

Summary

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	510(k) SummaryApril 18, 2019
Official Contact:	Dorian AverbuchBody Vision Medical Ltd.34 Sokolov St.Ramat Hasharon IsraelTel: 646- 863-7848 (US)
Submission Correspondent:	Paul DrydenProMedic, LLC131 Bay Point Dr. NESt. Petersburg, FL 33704
Proprietary or Trade Name:	LungVision System
Common/Usual Name:	System, image processing, radiological
Classification Name:	Picture archiving and communications systemLLZ, Class II, CFR 892.2050
Predicate Device:	BodyVision – LungVision – K163622
Reference Device:	Covidien - superDimension™ Navigation System V7.2K173244

Device Modification

1. Virtual Bronchoscopy
- a. A standard technology in the field of pulmonology. This is a visualization technique showing the same information already available in the CT scan.
1. Software upgrades
- a. C-Arm based Tomography - visual aid. Collecting a number of successive images produced by a standard C-Arm which are digitally "stacked" together to form an additional alternative visualization of imaging information sourcing from standard C-Arm.
- b. Multi view Setup - an algorithm improvement. Same airway based registration algorithm, extended to multiple C-Arm angles. previous was limited to one angle (AP, LAO, RAO or other C-Arm position)
1. Real time compensation
- Predicate displays a static target overlay on the fluoroscopic image, whereas the proposed a. modification performs small adjustments related to the tool movement on the fluoroscopic screen to the target overlay.
1. 3D Guidance
- Predicate calculates the tool position with respect to pre-operative CT. The proposed a. modification provides 3D visualization for those calculations in addition to the existing screen.
1. Use of a Tablet in addition to PC
- The Tablet image displayed is not for diagnostic purposes. a.

None of these modifications changes the indications for use, environment of use or patient population.

Description:

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510(k) Summary April 18, 2019

functions: segment previously acquired DICOM 3D CT image data, .
- . register DICOM 3D CT image data with live fluoroscopic X-ray image
- . overlay the segmented 3D CT dataset over a live fluoroscopic X-ray image of the same anatomy, obtained on a Fluoroscopic system.

System Components Overview

The following is a list of the LungVision System's main components: LungVision Main Unit LungVision Tablet LungVision Router LungVision Board (passive device) LungVision Software

Tablet is off-the-shelf information technology equipment powered from the medical grade power supply. The system has been evaluated to AAIM ANSI ES 60601-1 2005+ A1:2012 and IEC 60601-1-2: 2014.

Indications for Use:

The Lung Vision System is intended to enable users to segment previously acquired 3D CT datasets and overlay and register these 3D segmented data sets with fluoroscopic live X-ray images of the same anatomy in order to support catheter/device navigation during pulmonary procedures.

Contraindications:

None

Device Comparison

Table 1 compares the subject device to the predicate

Feature	Proposed DeviceLungVision	Primary PredicateK163622Body Vision-LungVision
Indications for Use	The LungVision System is intended toenable users to segment previouslyacquired 3D CT datasets and overlay andregister these 3D segmented data setswith fluoroscopic live X-ray images ofthe same anatomy in order to supportcatheter/device navigation duringpulmonary procedures.	The LungVision System is intended toenable users to segment previouslyacquired 3D CT datasets and overlay andregister these 3D segmented data setswith fluoroscopic live X-ray images ofthe same anatomy in order to supportcatheter/device navigation duringpulmonary procedures.
Classification	Picture archiving and communicationssystem21CFR 892.2050	Picture archiving and communicationssystem21CFR 892.2050
Feature	April 18, 2019Proposed DeviceLungVision	Primary PredicateK163622Body Vision-LungVision
	Product Code: LLZ	Product Code: LLZ
Target anatomy	Lungs	Lungs
Anatomy access	Bronchial airways	Bronchial airways
Windows OS	Windows 10	Windows 10
Medical imagingsoftware	Yes	Yes
General Image 2D/3Dreview	Yes	Yes
3D rendering view	Yes	Yes
Multi-modalitySupport	Yes	Yes
Image registration	Yes	Yes
Multi-planarreformatting (MPR)	Yes	Yes
DICOM import	Yes	Yes
Fluoroscopic video	Yes	Yes
Standard Imageviewing tools	Yes	Yes
Segmentation tool	Yes	Yes
Video capture	Yes	Yes
Live Image overlays	Yes	Yes
Import prior plans	Yes	Yes
Pointmarking/ tagging	Yes	Yes
Navigation type	Visual	Visual
Modifications
Virtual bronchoscopy	Yes	NoReference Covidien -superDimension™ NavigationSystem V7.2 - K173244
C-Arm based	Yes	No
Tomography
Multi-view set-up	Yes	No
Real-time	Yes - software upgrade	No
compensation

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0(k) Summar 000 0010

Substantial Equivalence Discussion

We will discuss the table above.

Indications for Use / Patient Population / Environment of Use: As in comparison of Indications For Use above, we can conclude that the indications for use for the LungVision and the predicate are substantially equivalent.

Discussion: The differences in proposed indications for use are minor. The minor differences do not raise new risk or safety concerns, and the subject device can be found substantially equivalent.

Prescriptive: Both the LungVision and predicate are prescription devices.

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510(k) Summary April 18, 2019

Discussion: There are no differences.

Design and Technology: The LungVision utilizes the same technological characteristics as the predicate and reference devices. Both include:

. software applications that provide 2D and 3D medical image acquisition including real-time video image acquisition and visualization of the anatomy
. allow co-registration of real-time images to previously created 3D image sets based on previously collected DICOM CT images
. include image enhancements such as contrast and brightness, zoom and pan capabilities
addition of a Tablet to the PC but not to be used for diagnostic purposes ●

For the Virtual Bronchoscopy feature the reference device - Covidien - superDimension™ Navigation System V7.2 - K173244 has the same feature and intended use.

Discussion: The software modifications including virtual bronchoscopy, C-arm based Tomography, 3D Guidance, and Real-time compensation are similar to the reference device.

Performance and Specifications:

The performance and specifications demonstrate that the Lung Vision and predicate devices perform the same functions using the same technologies thus can be found substantially equivalent. Discussion: There are no differences, thus the subject device can be found substantially equivalent.

Compliance with Standards:

LungVision includes hardware and complies with ANSI/AAMI/ES 60601-1:2005(2012) and IEC 60601-1-2:2014.

Discussion: The proposed device complies with the latest standards and thus can be found substantially equivalent.

Performance Testing:

Nonclinical / Bench: We have performed bench tests and found that the Lung Vision met all requirements specifications and was found to be equivalent in comparison to the predicate. Testing includes verification testing of the requirements, testing of hazards mitigations) and performance testing of the system.

Testing has also been performed with pig lungs to test accuracy in deformable tissue.

Biocompatibility: There are no patient contacting parts of the LungVision System

Animal: No animal testing was performed

Clinical: No clinical testing was performed

Substantial Equivalence Conclusion

Based upon the foregoing performance testing and comparison to the legally marketed predicate devices for indications for use, technology, and performance we believe we have demonstrated that the Lung Vision System is substantially equivalent in safety and effectiveness to the predicate device.

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DEPARTMENT OF HEALTH AND HUMAN SERVICESFood and Drug Administration	Form Approved: OMB No. 0910-0120Expiration Date: 06/30/2020See PRA Statement on last page.
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Indications for Use

510(k) Number ( if known )	K183593
Device Name	LungVision System
Indications for Use ( Describe )	The LungVision System is intended to enable users to segment previously acquired 3D CT datasets and overlay and register these 3D segmented data sets with fluoroscopic live X-ray images of the same anatomy in order to support catheter/device navigation during pulmonary procedures.
Type of Use ( Select one or both, as applicable )
XX Prescription Use (Part 21 CFR 801 Subpart D)	Over-The-Counter Use (21 CFR 801 Subpart C)

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April 18, 2019

Body Vision Medical Ltd. % Mr. Paul Dryden Consultant ProMedic, LLC 131 Bay Point Dr., NE ST. PETERSBURG FL 33704

Re: K183593

Trade/Device Name: LungVision System Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ Dated: April 1, 2019 Received: April 2, 2019

Dear Mr. Dryden:

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

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requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 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/CombinationProducts/GuidanceRegulatoryInformation/ucm597488.html; good manufacturing practice requirements as set forth in the quality systems (OS) 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 http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm.

For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/) and CDRH Learn (http://www.fda.gov/Training/CDRHLearn). 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 (http://www.fda.gov/DICE) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

Thalia T. Mills, Ph.D. Director Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological Health

Enclosure

Regulation Number and Section

§ 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).