Automatic Registration is a software device for image guided surgery intended to be used in combination with compatible Brainlab navigation systems such as the Brainlab Spine & Trauma Navigation System. Automatic Registration provides an image registration for intraoperatively acquired 3D CT/CBCT or fluoroscopic images.

Device Description

The Subject Device Automatic Registration is an accessory to the Brainlab Spine & Trauma Navigation System. It correlates intraoperatively acquired patient data (3D CT/CBCT or fluoroscopic images) to the surgical environment in order to provide a patient registration for subsequent use by the Brainlab Spine & Trauma Navigation. The device includes the following software modules:

Automatic Registration 2.6
Universal Atlas Performer 6.0
Universal Atlas Transfer Performer 6.0 .
And uses as well several hardware devices, mainly registration matrices, adhesive flat markers and a calibration phantom, for performing the registration. The software is installed on an Image Guided Surgery (IGS) platform. The registration matrices are reusable devices, delivered nonsterile and having patient contact.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study details for the Automatic Registration device, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

Performance Metric	Acceptance Criteria	Reported Device Performance
Accuracy (New Registration Method)	Registration accuracy of ≤ 2.5 mm (P95) with a mean navigation accuracy with 3D deviation ≤ 1.5 mm	Registration accuracy of ≤ 2.5 mm (P95) with a mean navigation accuracy with 3D deviation ≤ 1.5 mm
Software Verification	Successful implementation of product specifications, incremental testing, risk control, compatibility, cybersecurity	Successfully conducted as recommended by FDA guidance.
AI/ML Landmark Detection	Quantifying object detection, quality of vertebra level assignment, quality of landmark predictions, performance of observer view direction.	Assessed by quantifying the above aspects for AI/ML detected landmarks on X-rays.
Usability	No critical use-related problems identified.	No critical use-related problems identified after summative usability testing.

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

Accuracy Testing (New Registration Method): The testing was performed on human cadavers. The exact number of cadavers or cases within them is not specified.
AI/ML Assessment: The summary states the algorithm was developed using a "controlled internal process that defines activities from the inspection of input data to the training and verification of the algorithm." No specific sample size for the test set is provided, nor is the data provenance (e.g., country of origin, retrospective/prospective) explicitly mentioned for the AI/ML assessment tests.
Usability Testing: 15 representative users were used for summative usability testing.

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

For the accuracy testing on human cadavers, the method for establishing ground truth and the number/qualifications of experts are not explicitly stated. It can be inferred that ground truth for navigation accuracy would involve precise measurements by trained personnel, likely using specialized equipment, but no details are provided.
For the AI/ML algorithm assessment, the criteria for "quantifying object detection, quality of vertebra level assignment, quality of landmark predictions, and the performance of the observer view direction" would imply expert review. However, the number of experts and their qualifications for establishing this ground truth are not specified.

4. Adjudication Method for the Test Set

The document does not specify any adjudication methods (e.g., 2+1, 3+1) for the test sets described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done or at least not reported in this summary. The summary focuses on the standalone performance of the device and its components, particularly the new AI/ML registration update method, against predefined accuracy criteria and usability.

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

Yes, a standalone performance evaluation was done for the new registration method, specifically the AI/ML algorithm component. The "Machine Learning" section describes the assessment of the AI/ML detected landmarks on X-rays, evaluating aspects like object detection, vertebra level assignment, and landmark predictions. The accuracy bench testing also evaluates the "overall system registration accuracy" of the new method, implying its standalone performance in achieving the specified accuracy.

7. The Type of Ground Truth Used

For accuracy testing (bench test on cadavers): The ground truth would likely be established through highly precise physical measurements on the cadavers, probably using a gold-standard measurement system (e.g., CMM, anatomical landmarks verified with high-precision tools). The document doesn't explicitly state the methodology, but this is typical for navigation accuracy.
For AI/ML assessment: The ground truth for "object detection, quality of vertebra level assignment, quality of landmark predictions, and the performance of the observer view direction for 2D X-rays" would have been established by human experts, likely radiologists or orthopedic surgeons with expertise in spinal anatomy and imaging. The document doesn't explicitly detail the methodology or the experts involved.

8. The Sample Size for the Training Set

The sample size for the training set of the Convolutional Neural Network (CNN) is not specified in the provided document. It only mentions that the algorithm was "developed using a controlled internal process that defines activities from the inspection of input data to the training and verification of the algorithm."

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

The document states that the AI/ML algorithm was developed using a "Supervised Learning approach." This implies that the training data was labeled by human experts. However, the specific method (e.g., single expert, consensus, specific qualifications of experts) for establishing this ground truth for the training set is not detailed in the provided text.

Summary

{0}------------------------------------------------

March 20, 2024

Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which consists of a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.

Brainlab AG Esther Moreno Garcia QM Consultant Olof-Palme-Str.9 Munich, 81829 Germany

Re: K234047

Trade/Device Name: Automatic Registration Regulation Number: 21 CFR 882.4560 Regulation Name: Stereotaxic Instrument Regulatory Class: Class II Product Code: OLO Dated: December 21, 2023 Received: December 21, 2023

Dear Esther Moreno Garcia:

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 (the 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 available 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.

Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).

{1}------------------------------------------------

Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).

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 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 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 Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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,

Tejen D. Soni -S

For

Shumaya Ali, M.P.H. Assistant Director DHT6C: Division of Restorative, Repair and Trauma Devices OHT6: Office of Orthopedic Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health

{2}------------------------------------------------

Indications for Use

510(k) Number (if known) K234047

Device Name Automatic Registration

Indications for Use (Describe)

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)

CONTINUE ON A SEPARATE PAGE IF NEEDED.

This section applies only to requirements of the Paperwork Reduction Act of 1995.

DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.

The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:

Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov

"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."

{3}------------------------------------------------

Image /page/3/Picture/0 description: The image shows the Brainlab logo. The logo consists of a stylized pink brain icon on the left, followed by the word "BRAINLAB" in pink, uppercase letters. The brain icon appears to be made up of several curved lines, giving it a modern and abstract look.

510(k) Summary K234047

March 20, 2024

General Information
Manufacturer	Brainlab AG; Olof-Palme-Str.9, 81829, Munich, Germany
Establishment Registration	8043933
Trade Name	Automatic Registration
Classification Name	Orthopedic Stereotaxic Instrument
Product Code	OLO
Regulation Number	882.4560
Regulatory Class	II
Panel	Orthopedic
Predicate Device(s)	K203679 - Automatic Registration
Contact Information
Primary Contact	Alternate Contact
Esther Moreno Garcia	Chiara Cunico
QM Consultant - Regulatory Affairs	Phone: +49 89 99 15 68 0
Phone: +49 89 99 15 68 0	Fax: +49 89 99 15 68 5033
Email: regulatory.affairs@brainlab.com	Email: chiara.cunico@brainlab.com

1. Indications for Use

2. Device Description

Automatic Registration 2.6 ●
Universal Atlas Performer 6.0 ●
Universal Atlas Transfer Performer 6.0 .

And uses as well several hardware devices, mainly registration matrices, adhesive flat markers and a calibration phantom, for performing the registration. The software is installed on an Image

{4}------------------------------------------------

Image /page/4/Picture/0 description: The image shows the Brainlab logo. The logo consists of a stylized brain icon on the left and the word "BRAINLAB" in capital letters on the right. The color of the logo is pink.

Guided Surgery (IGS) platform. The registration matrices are reusable devices, delivered nonsterile and having patient contact.

The image registration can be provided using different methods, depending on the compatible CT or Cone-Beam CT scanner used. There is a specific workflow integration with the 3ª party scanners Airo and LoopX, as well as a universal workflow that can be used with any CT scanner using Dicom data. As a new feature, Automatic Registration 2.6 implements the possibility to update an automatic registration generated with LoopX by using also a static (locked) Al/ ML algorithm provided by the Universal Atlas for detection of vertebrae in 2D X-Ray images. This vertebra detection is then used for a rough pre-positioning of 2D X-Rays in relation to the 3D dataset and reduces user interaction for outlining 2D images and manual pre-positioning of images.

3. Substantial Equivalence

For the Substantial Equivalence determination, comparison of the Subject Device features with the following predicate device(s) was carried out:

K203679 - Automatic Registration 2.5 (product code: OLO)

The predicate was chosen since it's the predecessor device and therefore very similar to the subject device w.r.t the indications for use, technological characteristics and use cases.

The main difference compared to the predicate device is the new Registration Update method using AI/ ML. The two already existing registration methods have been reimplemented in a new GUI, without significant changes.

Indications foruse	Automatic Registration is asurgical device for image guidedsurgery intended to be used incombination with compatibleBrainlab navigation systems.Automatic Registration providesan image registration forintraoperatively acquired 3D CT/CBCT or fluoroscopic images. Itconsists of the software moduleAutomatic Registration andhardware accessories.	Automatic Registration is asoftware device for image guidedsurgery intended to be used incombination with compatibleBrainlab navigation systems suchas the Brainlab Spine & TraumaNavigation System. AutomaticRegistration provides an imageregistration for intraoperativelyacquired 3D CT/CBCT orfluoroscopic images.


Intended useenvironment	Automatic Registration isintended to be used in an ORenvironment. The device is notintended to be used in the MRenvironment..	Automatic Registration isintended to be used in an ORenvironment. The device is notintended to be used in the MRenvironment.
Software version	Automatic Registration 2.5	Automatic Registration 2.6Universal Atlas Performer 6.0Universal Atlas TransferPerformer 6.0
Hardwaredevices	Registration Matrix CT –Open Surgery (Spine) Registration Matrix CT –Small Incision (Spine) Registration Matrix CT –Minimally Invasive (Cranialand Spine) Adhesive flat markers Calibration Phantom iCT	Registration Matrix CT -Open Surgery (Spine) Registration Matrix CT -Small Incision (Spine) Registration Matrix CT -Minimally Invasive (Cranialand Spine) Adhesive flat markers Calibration Phantom iCT
Localizationtechnique	Optical tracking	Optical tracking
Registrationmethods	Universal AIR Pre-Calibrated AutomaticRegistration	Universal AIR Pre-Calibrated AutomaticRegistration Registration Update
Imageregistrationaccuracy	Registration accuracy of ≤ 2.5mm (P95, i.e. within the 95thpercentile) with a meannavigation accuracy with 3Ddeviation ≤ 1.5 mm.	Registration accuracy of ≤ 2.5mm (P95, i.e. within the 95thpercentile) with a meannavigation accuracy with 3Ddeviation ≤ 1.5 mm.
UI technology	WPF	HTML5
Compatible 3rdparty CTscanners	CT and Cone Beam CT Imagingdevices with DICOMConformance Statement arecompatible (Universal AIR).	CT and Cone Beam CT Imagingdevices with DICOMConformance Statement arecompatible (Universal AIR).
	Airo and LoopX	Airo and LoopX

{5}------------------------------------------------

Image /page/5/Picture/0 description: The image shows the word "BRAINLAB" in pink font. To the left of the word is a pink symbol that looks like three stylized brains stacked on top of each other. The symbol is slightly smaller than the word "BRAINLAB".

{6}------------------------------------------------

Image /page/6/Picture/0 description: The image shows the word "BRAINLAB" in pink, with a stylized pink symbol to the left of the word. The symbol appears to be three curved lines stacked on top of each other. The word "BRAINLAB" is written in a sans-serif font, with each letter capitalized. The overall image has a clean and modern look.

4. Performance Data

The following testing was conducted on the Subject Device to establish substantial equivalence with the predicate device:

Software Verification and Validation Testing

Software verification and validation testing has been conducted and documentation is provided as recommended by FDA's Guidance for Industry and FDA Staff, "Content of Premarket Submissions for Device Software Functions". These include successful implementation of product specifications, incremental testing for different release candidates, testing of risk control measures, compatibility testing or cybersecurity tests. The documentation submitted is for Enhanced Documentation level.

Bench Tests

. Accuracy: For the new reqistration method "Registration Update" the overall system registration accuracy was verified in human cadavers under a representative worst case scenario. The following acceptance criteria has been fulfilled: Registration accuracy of ≤ 2.5 mm (P95, i.e. within the 95th percentile) with a mean navigation accuracy with 3D deviation ≤ 1.5 mm. Therefore the subject device achieves the same accuracy values as the registration methods available in the predicate device.
Machine Learning: The AI/ML algorithm used in the new registration method is a Convolutional Neural network (CNN) developed using a Supervised Learning approach. The algorithm was developed using a controlled internal process that defines activities from the inspection of input data to the training and verification of the algorithm. This is a static algorithm (locked). The assessment of the AI/ML detected landmarks on X-rays has been done by quantifying the object detection, the quality of vertebra level assignment, the quality of landmark predictions, and the performance of the observer view direction for 2D X-rays from the Universal Atlas Transfer Performer 6.0.
. Usability: Summative usability testing was performed in order to validate the new user interface and workflow guidance for the Registration Update method. The evaluation was conducted with 15 representative users which had to use the Registration Update under different circumstances. The summative usability testing identified no critical use related problems.

No clinical testing was required for the subject device.

5. Conclusion

The comparison of the Subject Device with the predicate device shows that Automatic Registration (2.6) has similar functionality, intended use and technological characteristics as the predicate device. Based on the comparison to the predicate and the performance testing conducted, the Subject Device is considered substantially equivalent to the predicate device.

Regulation Number and Section

§ 882.4560 Stereotaxic instrument.

(a)
Identification. A stereotaxic instrument is a device consisting of a rigid frame with a calibrated guide mechanism for precisely positioning probes or other devices within a patient's brain, spinal cord, or other part of the nervous system.(b)
Classification. Class II (performance standards).