Brainlab Elements Contouring provides an interface with tools and views to outline, refine, combine and manipulate structures in patient image data. The generated 3D structures are not intended to create physical replicas used for diagnostic purposes. The device itself does not have clinical indications.

Brainlab Elements Fibertracking is an application for the processing and visualization of cranial white matter tracts based on Diffusion Tensor Imaging (DTI) data for use in treatment planning procedures. The device itself does not have clinical indications.

Brainlab Elements Image Fusion is an application for the co-registration of image data within medical procedures by using rigid and deformable registration methods. It is intended to align anatomical structures between data sets. The device itself does not have clinical indications.

Brainlab Elements Image Fusion Angio is a software application that is intended to be used for the co-registration of cerebrovascular image data. The device itself does not have clinical indications.

Device Description

Brainlab Elements is a medical device for processing of medical images, that is used to support treatment planning of surgical or radio-therapeutical procedures.

The Brainlab Elements applications transfer DICOM data to and from picture archiving and communication systems (PACS) and other storage media devices. They include modules for 2D & 3D image viewing, image processing, image co-registration, image segmentation and 3D visualization of medical image data for treatment planning procedures.

Brainlab Elements main software functionalities include:

Visualization of medical image data in DICOM format -
Co-registration of different imaging modalities by using both rigid and deformable registration methods
Processing of co-registered data to highlight differences between distinct scanning sequences or to assess the response to a treatment
Contouring and delineation of objects and anatomical structures -
-Automatic segmentation of anatomical structures
Manipulation of objects and seqmented structures (e.g. splitting, mirroring, etc.) -
-Measuring tools
Co-reqistration of cerebrovascular image data -
Visualization of Diffusion Tensor Imaging (DTI) based data and processing of such data to visualize e.g. cranial white matter tracts

AI/ML Overview

The provided text describes a 510(k) premarket notification for "Brainlab Elements," a medical image processing system. The document outlines the device's intended use, its technological characteristics, and comparison to predicate devices, along with performance data.

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

Acceptance Criteria and Reported Device Performance

The document states that "In all cases, acceptance criteria for the validation tests were derived from scientific literature." However, the specific quantitative acceptance criteria are not explicitly detailed in the provided text. Instead, it broadly mentions the parameters that were evaluated for accuracy.

Acceptance Criteria Category	Reported Device Performance (as stated in the document)
Accuracy of Co-registrations	Tested for devices Elements Image Fusion and Elements Image Fusion Angio. Result: "Validation tests were performed to demonstrate that the products fulfill critical state of the art requirements." (Specific quantitative accuracy values or thresholds are not provided.)
Accuracy of Automatically Segmented Objects	Tested for device Elements Contouring. Result: "Validation tests were performed to demonstrate that the products fulfill critical state of the art requirements." (Specific quantitative accuracy values or thresholds are not provided, e.g., Dice Similarity Coefficient, Hausdorff Distance, etc.)
Accuracy of Fiber Tracts	Tested for device Elements Fibertracking. Result: "Validation tests were performed to demonstrate that the products fulfill critical state of the art requirements." (Specific quantitative accuracy values or thresholds are not provided.)
General Product Specifications	"Product specifications and the implementation of risk control measures have been tested in verification tests for the device according to IEC 62304 and ISO 14971." (No specific performance metrics are listed beyond conformity to standards.)
Usability Requirements	"Usability tests were performed to demonstrate the devices meet usability requirements as defined in IEC 62366." (No specific usability metrics or thresholds, such as task completion rates or error rates, are provided. It generally states that the new/modified user interface and modified interactions were subject to formative and summative usability tests.)
Safety and Effectiveness	"Verification and validation activities ensured that the design specifications are met and that Brainlab Elements does not introduce new issues concerning safety and effectiveness. Hence, Brainlab Elements is substantially equivalent to the predicate device(s)." (This is a summary conclusion rather than a specific performance metric.)

Study Details:

Sample Size Used for the Test Set and Data Provenance:
- The document states that "Validation tests using retrospective patient data and phantom data were performed" for the Fibertracking algorithm and for comparing results to the predicate device.
- Sample Size: The exact sample size (number of patients or phantom data sets) used for the test set is not specified in the provided text.
- Data Provenance: The text indicates "retrospective patient data" and "phantom data." The country of origin of this data is not mentioned. The data's nature is retrospective.
Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:
- The document does not provide any information regarding the number of experts or their qualifications used to establish ground truth for the test set.
Adjudication Method for the Test Set:
- The document does not provide any information on the adjudication method (e.g., 2+1, 3+1, none) used for the test set. Given the lack of mention of multiple experts, it's possible such a method was not explicitly described or applied in a consensus manner for ground truth creation.
Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
- The document does not mention an MRMC comparative effectiveness study involving human readers with and without AI assistance. The focus of the validation described is on the accuracy of the software's outputs (co-registration, segmentation, fiber tracts) and its substantial equivalence to predicate devices, rather than a human-in-the-loop performance improvement study.
Standalone (Algorithm-Only) Performance:
- Yes, the performance tests described (accuracy of co-registrations, segmented objects, and fiber tracts) appear to be evaluating the standalone performance of the algorithms. The results are compared against "scientific literature" derived acceptance criteria, implying an assessment of the algorithm's output directly.
Type of Ground Truth Used:
- The document states that for accuracy validation, "acceptance criteria for the validation tests were derived from scientific literature." While this suggests a scientific basis for evaluation, the specific type of ground truth (e.g., expert consensus, pathology, outcomes data, or a gold standard from imaging physics/phantoms) is not explicitly stated. For "retrospective patient data," it's often expert-derived or an existing clinical standard, but this is not confirmed. For "phantom data," the ground truth would be known by design.
Sample Size for the Training Set:
- The document does not provide any information regarding the sample size of the training set. It mentions "Contouring: Automatic segmentation of anatomical structures" and "Automatic DTI data processing", which typically implies machine learning models requiring training data, but the details are omitted.
How the Ground Truth for the Training Set Was Established:
- The document does not provide any information on how the ground truth for the training set (if any machine learning was used implicitly for "automatic segmentation" or "automatic DTI processing") was established.

In summary, while the document confirms that validation tests were performed to demonstrate substantial equivalence and adherence to "state of the art requirements" based on "scientific literature," it largely lacks the detailed quantitative acceptance criteria and the specifics of the study methodology (e.g., precise sample sizes, expert details, and ground truth establishment methods) that would typically be expected for a comprehensive understanding of the device's performance validation.

Summary

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Image /page/0/Picture/0 description: The image shows the logo for the U.S. Food & Drug Administration (FDA). The logo consists of two parts: on the left, there is a symbol representing the Department of Health & Human Services, and on the right, there is the text "FDA U.S. FOOD & DRUG ADMINISTRATION" in blue. The text is arranged in two lines, with "FDA" being larger and bolder than the rest of the text.

Brainlab AG % Chiara Cunico Manager Regulatory Affairs Olof-Palme-Str. 9 Munich, Bayern 80809 GERMANY

December 16, 2021

Re: K212420

Trade/Device Name: Brainlab Elements, Brainlab Elements Contouring, Brainlab Elements Fibertracking, Brainlab Elements Image Fusion, Brainlab Elements Image Fusion Angio Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ, JAK Dated: November 10, 2021 Received: November 15, 2021

Dear Chiara Cunico:

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/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); 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 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) K212420

Device Name

Brainlab Elements, Brainlab Elements Contouring (4.0), Brainlab Elements Fibertracking (2.0), Brainlab Elements Image Fusion (4.0), Brainlab Elements Image Fusion Angio (1.0)

Indications for Use (Describe)

Brainlab Elements Fibertracking is an application for the processing and visualization of cranial white matter tracts based on Diffusion Tensor Imaging (DTT) data for use in treatment planning procedures. The device itself does not have clinical indications.

Brainlab Elements Image Fusion Angio is a software application that is intended to be used for the co-registration of cerebrovascular image data. The device itself does not have clinical indications.

Type of Use (Select one or both, as applicable)
Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)

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RAINLAB

510(k) Summary

K212420

November 10, 2021

General Information
Manufacturer	Brainlab AG; Olof-Palme-Str.9, 81829, Munich, Germany
Establishment Registration	8043933
Trade Name	Brainlab Elements, Brainlab Elements Contouring, Brainlab ElementsFibertracking, Brainlab Elements Image Fusion, Brainlab ElementsImage Fusion Angio
Classification Name	System, image processing, radiological
Product Code	LLZ, JAK
Regulation Number	892.2050
Regulatory Class	Class II
Panel	Radiology
Predicate Device(s)	Mimics Medical (K183105) – Primary PredicateiPlan (K113732) – Second predicateImage Fusion (K170816) – Third predicate
Reference Device	Brainlab Elements Image Fusion Angio (K190042)
Contact Information
Primary Contact	Alternate Contact
Chiara Cunico	Regulatory Affairs Brainlab
Manager RA	Phone: +49 89 99 15 68 0
Phone: +49 89 99 15 68 0	Fax: +49 89 99 15 68 5033
Email: chiara.cunico@brainlab.com	Email: regulatory.affairs@brainlab.com

1. Indication for Use

Brainlab Elements Image Fusion Angio is a software application that is intended to be used for the co-registration of cerebrovascular image data. The device itself does not have clinical indications.

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2. Device Description

Brainlab Elements is a medical device for processing of medical images, that is used to support treatment planning of surgical or radio-therapeutical procedures.

Brainlab Elements main software functionalities include:

Visualization of medical image data in DICOM format -
Co-registration of different imaging modalities by using both rigid and deformable registration methods
Processing of co-registered data to highlight differences between distinct scanning sequences or to assess the response to a treatment
Contouring and delineation of objects and anatomical structures -
-Automatic segmentation of anatomical structures
Manipulation of objects and seqmented structures (e.g. splitting, mirroring, etc.) -
-Measuring tools
Co-reqistration of cerebrovascular image data -
Visualization of Diffusion Tensor Imaging (DTI) based data and processing of such data to visualize e.g. cranial white matter tracts

The intended users are medical professionals. Typical users as defined in the use case descriptions are:

-Image Guided Surgery: Neurosurgeons, Ear-Nose-Throat (ENT) surgeons and Cranio-Maxillofacial (CMF) surgeons including their assistants
Radiotherapy: medical professionals who perform radiation treatment planning (medical physicists, radiation oncologists, dosimetrists, physicians, etc.)

The device shall be used in a hospital office environment or rooms appropriate for surgical interventions or radiotherapy planning.

3. Substantial Equivalence

ltem	Information	510 (k)	Product Code;SubsequentProduct Code(s)	Subject Device
PrimaryPredicatedevice	Mimics Medical	K183105	LLZ	Brainlab Elements Contouring 4.0

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BRAINLAB

Item	Information	510 (k)	Product Code;SubsequentProduct Code(s)	Subject Device
SecondPredicatedevice	iPlan (iPlan Cranial, iPlanStereotaxy, iPlan ENT,iPlan CMF, iPlan View,iPlan Spine)	K113732	JAK; LLZ	Brainlab Elements Fibertracking2.0; Brainlab ElementsCountouring 4.0
ThirdPredicatedevice	Image Fusion 3.0	K170816	LLZ; JAK	Brainlab Elements Image Fusion4.0
ReferenceDevice	Image Fusion Angio 1.0	K190042	LLZ; JAK	Brainlab Elements Image FusionAngio 1.0.1

COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH THE PREDICATE DEVICE

At a high level, the subject and predicate devices are based on the following same technological elements:

Image Fusion and Image Fusion Angio:

-Principle of image co-registration (rigid and deformable)
-Verification tools
Viewing of images and DICOM data -

Contouring:

Object segmentation using manual, semi-automatic or fully automatic algorithms -
3D model calculation
-Measuring functionalities
Verification tools -
Viewing of images and DICOM data -

Fibertracking:

-Automatic DTI data processing
Region-of-interest (ROI) definition -
3D visualization -

In addition, the subject device indications for use are equivalent to that of the predicate device.

The following technological differences exist between the subject and predicate device(s):

New/modified user interface -
Fibertracking algorithm improvements (compared to predicate device iPlan) -
-Contouring: support of 2D-DSA images (compared to predicate device iPlan)
-Functionality: The device shares the main functionalities of the predicate devices, but is organized in a different way and tools and views are slightly different.

Validation of differences compared to predicate devices:

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INLAB
The new/modified user interface and views as well as the modified interactions with tools were subject of several formative and summative usability tests.
-Validation tests using retrospective patient data and phantom data were performed to compare the results of the modified algorithm to the results of the algorithm which was present in the predicate device.

4. Performance Data

Product specifications and the implementation of risk control measures have been tested in verification tests for the device according to IEC 62304 and ISO 14971.

Validation tests were performed to demonstrate that the products fulfill critical state of the art requirements:

-Accuracy of co-registrations, generated by the devices Elements Image Fusion and Elements Image Fusion Angio
-Accuracy of automatically segmented objects, generated by the device Elements Contouring
Accuracy of fiber tracts, generated by the device Elements Fibertracking -

In all cases, acceptance criteria for the validation tests were derived from scientific literature.

Usability tests were performed to demonstrate the devices meet usability requirements as defined in IEC 62366.

Software Verification and Validation Testing

Software verification and validation testing were conducted and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." The software for this device was considered as a major level of concern, since:

Prior to mitigation of hazards, a failure of the Software could result in death or serious injury of the patient, because the software provides information that directly drives a decision regarding treatment or therapy
A malfunction of, or a latent design flaw in, the software could lead to an erroneous diagnosis or delay in delivery of appropriate medical care that would likely lead to Minor Injury.

5. Conclusion

The comparison of Brainlab Elements with the predicate devices shows that the Brainlab Elements have similar functionality, intended use, technological characteristics and users like the predicate device(s). Verification and validation activities ensured that the design specifications are met and that Brainlab Elements does not introduce new issues concerning safety and effectiveness. Hence, Brainlab Elements is substantially equivalent to the predicate device(s).

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).