Axial3D Cloud Segmentation Service is intended for use as a cloud based service and image segmentation system for the transfer of DICOM imaging information from a medical scanner to an output file.

The Axial3D Cloud Segmentation Service output file can be used for the fabrication of physical replicas of the output file using additive manufacturing methods.

The output file or physical replica can be used for treatment planning.

The physical replica can be used for diagnostic purposes in the field of orthopedic, maxillofacial and cardiovascular applications.

Axial3D Cloud Segmentation Service should be used in conjunction with other diagnostic tools and expert clinical judgment.

Device Description

Axial3D Cloud Segmentation Service is a secure, highly available cloud based image processing, segmentation and 3D modeling framework for the transfer of imaging information to either a digital file or as a 3D printed physical model.

Axial3D Cloud Segmentation Service is made up of a number of component parts, which allow the production of patient-specific 1:1 scale replica models, either as a digital file or as a 3D printed physical model.

AI/ML Overview

Here's a breakdown of the acceptance criteria and study information for the Axial3D Cloud Segmentation Service, based on the provided text:

1. Acceptance Criteria and Reported Device Performance

The provided document describes a substantial equivalence submission to the FDA. In this context, the "acceptance criteria" are implied by the claim of substantial equivalence to the predicate device, Mimics InPrint (K173619). The primary performance metric is the accuracy of the segmentation against a defined ground truth, demonstrating that the subject device performs at least as well as the predicate and within acceptable specifications.

Performance Metric	Acceptance Criteria (Implied)	Reported Device Performance
Measurement Accuracy of Segmentation	"within specification" and "performs at least as well as the legally marketed predicate device."	"Measurement accuracy and comparisons were performed and confirmed to be within specification." "The validation highlighted that the subject device performed to a higher standard, than the predicate device." "minimal variances were visible between the Mesh generated from subject device and the predicate device"
Accuracy of Physical Replica Printing	Demonstrated to be accurate when using compatible 3D printers.	"Validation of printing of physical replica models was performed and demonstrated to be accurate when using any of the compatible 3D printers."
Equivalence in Design & Functionality	Similar to predicate device in intended use, design, functionality, operating principles, and performance characteristics.	"Comparison shows the Axial3D Cloud Segmentation Service is substantially equivalent in intended use, design, functionality, operating principles and performance characteristics of the predicate device." "Both devices use the same segmentation functionality and generate the same output files."
Safety & Effectiveness	As safe and effective as the legally marketed predicate device.	"The conclusions drawn from the nonclinical tests demonstrate that the proposed subject device is as safe, as effective, and performs as well as the legally marketed predicate device."
Minimal Variance from Original DICOM (Mesh)	Minimal variance from original DICOM images after smoothing.	"Axial3D apply minimal smoothing to the STL file generated from the labeled images to retain a higher level of accuracy to the original DICOM images."

2. Sample Size and Data Provenance

Test Set Sample Size: Not explicitly stated in the provided text. The document mentions "measurement accuracy and comparisons were performed" and "validation of printing of physical replica models was performed," but does not detail the number of cases or images used for these tests.
Data Provenance: Not explicitly stated. The document does not mention the country of origin of the data or whether it was retrospective or prospective.

3. Number of Experts and Qualifications for Ground Truth

Number of Experts: Not explicitly stated.
Qualifications of Experts: Not explicitly stated. The document refers to "expert clinical judgment" in the Indications for Use, which suggests clinical experts are involved in the overall use of the device, but it doesn't specify their role or qualifications in establishing the ground truth for the validation study.

4. Adjudication Method

Adjudication Method: Not explicitly stated.

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

MRMC Study: No, a multi-reader multi-case (MRMC) comparative effectiveness study was not mentioned or described in the provided text. The study focuses on the comparison of the device's output (segmentation accuracy) against a predicate device, not on the improvement of human readers' performance with AI assistance.

6. Standalone (Algorithm Only) Performance

Standalone Performance: Yes, a standalone performance study was seemingly conducted. The description states "Measurement accuracy and comparisons were performed" for the device's segmentation output, and "The validation highlighted that the subject device performed to a higher standard, than the predicate device." This indicates an assessment of the algorithm's performance independent of human-in-the-loop interaction for the specific tasks evaluated.

7. Type of Ground Truth Used

Type of Ground Truth: The document implies comparison against the output of the predicate device ("Mimics InPrint") as a reference for accuracy, and also refers to "original DICOM images" for mesh accuracy. It doesn't explicitly state whether expert consensus or pathology was used to establish the gold standard for the initial segmentation accuracy comparison. Given the nature of segmentation, it is highly probable that expert-annotated segmentations were used as ground truth, or a method accepted as gold standard in the field for anatomical model creation.

8. Sample Size for Training Set

Training Set Sample Size: Not explicitly stated. The document focuses on the validation and verification of the device, not its development or training data.

9. How Ground Truth for Training Set Was Established

Ground Truth for Training Set: Not explicitly stated. As with the test set, it's not detailed how ground truth was established for any potential training data used to develop the segmentation algorithms.

Summary

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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA logo on the right. The FDA logo is in blue and includes the letters "FDA" in a square and the words "U.S. FOOD & DRUG ADMINISTRATION".

Axial Medical Printing Limited % Prithul Bom Most Responsible Person Regulatory Technology Services, LLC 1000 Westgate Drive, Suite 510k Saint Paul, Minnesota 55114

June 23, 2022

Re: K221511

Trade/Device Name: Axial3D Cloud Segmentation Service Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: Mav 23, 2022 Received: May 24, 2022

Dear Prithul Bom:

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,

Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Imaging Devices and Electronic Products OHT8: Office of 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) K221511

Device Name Axial3D Cloud Segmentation Service

Indications for Use (Describe)

Axial3D Cloud Segmentation Service is intended for use as a cloud based service and image segmentation system for the transfer of DICOM imaging information from a medical scanner to an output file.

The Axial3D Cloud Segmentation Service output file can be used for the fabrication of physical replicas of the output file using additive manufacturing methods.

The output file or physical replica can be used for treatment planning.

The physical replica can be used for diagnostic purposes in the field of orthopedic, maxillofacial and cardiovascular applications.

Axial3D Cloud Segmentation Service should be used in conjunction with other diagnostic tools and expert clinical judgment.

Type of Use (Select one or both, as applicable)X Prescription Use (Part 21 CFR 801 Subpart D)

Over-The-Counter Use (21 CFR 801 Subpart C)

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510(k) Summary

K221511

Image /page/3/Picture/3 description: The image shows the logo for Axial3D. The word "axial" is written in a dark blue color, with a teal diamond shape above the "i". To the right of "axial" is the number "3D" in a smaller font size. Below the logo is the tagline "Patient data made real" in teal.

Submitters Contact Information

Submitter's Name: Axial Medical Printing Limited 17A Ormeau Avenue Belfast BT2 8HD United Kingdom Tel: +44 (0)28 90183590

Name of Contact Person

Jenna McGarry, QA/RA Manager

Date of submission

25th February 2022

Subject Device Name

Device Trade Name: Axial3D Cloud Segmentation Service

Device Common Name: Axial3D Cloud Segmentation Service

Classification Name: System, Image Processing, Radiological (21CFR 892.2050, Product Code LLZ)

Identification of Legally Marketed Predicate Device

The Axial Medical Printing Limited Axial3D Cloud Segmentation Service is substantially equivalent to the following:

Predicate Device

Manufacturer: Materialse NV

Trade Name: Mimics InPrint

Common Name: Mimics InPrint

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Classification Name: System, Image Processing, Radiological (21CFR 892.2050,

Product Code LLZ)

510(k) Number: K173619

Device Description

Intended Use/Indications for Use

Axial3D Cloud Segmentation Service is intended for use as a cloud based service and image segmentation framework for the transfer of DICOM imaging information from a medical scanner to an output file.

The Axial3D Cloud Segmentation Service output file can be used for the fabrication of physical replicas of the output file using additive manufacturing methods.

The output file or physical replica can be used for treatment planning.

The physical replica can be used for diagnostic purposes in the field of orthopedic, maxillofacial and cardiovascular applications.

Axial3D Cloud Segmentation Service should be used in conjunction with other diagnostic tools and expert clinical judgment.

Comparison between Proposed Device and Predicate Device

Product Details	New Device:	ProposedPredicateDevice:	Comment:
DeviceManufacturer	Axial MedicalPrinting Limited	Materialise N.V.	N/A
Device Name	Axial3D CloudSegmentationService	Mimics inPrint	N/A
Device Trade orProprietaryName	Axial3D CloudSegmentationService	Mimics inPrint	N/A
510(k) Number	TBC	K173619	N/A

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Axial Medical Printing Limited

DeviceRegulationName:	Medical ImageManagement andProcessingSystem	Picture archivingandcommunicationssystem	The proposed device and predicate devices areidentical
DeviceRegulationNumber:	21 CFR 892.2050	21 CFR892.2050	The proposed device and predicate devices areidentical
Device ProductCode:	LLZ	LLZ	The proposed device and predicate devices areidentical
DeviceClassificationFDA:	Class II	Class II	The proposed device and predicate devices areidentical
Intended Use/Indication forUse	Axial3D CloudSegmentationService isintended for useas a cloud basedservice andimagesegmentationframework for thetransfer ofDICOM imaginginformation froma medicalscanner to anoutput file.The Axial3DCloudSegmentationService output filecan be used forthe fabrication ofphysical replicasof the output fileusing additivemanufacturingmethods.The output file orphysical replicacan be used fortreatmentplanning.The physicalreplica can beused fordiagnosticpurposes in thefield oforthopedic,maxillofacial and	Mimics inPrint isintended for useas a softwareinterface andimagesegmentationsystem for thetransfer ofDICOM imaginginformation froma medicalscanner to anoutput file. It isalso used aspre-operativesoftware fortreatmentplanning. Forthis purpose, theMimics inPrintoutput file canbe used for thefabrication ofphysical replicasof the output fileusing traditionalor additivemanufacturingmethods. Thephysical replicacan be used fordiagnosticpurposes in thefield oforthopedic,maxillofacial andcardiovascularapplications.Mimics inPrintshould be usedin conjunctionwith otherdiagnostic tools	The proposed device and primary predicate haveequivalent indications.
		cardiovascularapplications.Axial3D CloudSegmentationService should beused inconjunction withother diagnostictools and expertclinical judgment.	and expertclinicaljudgment.
TargetPopulation		Adult	Adult	Same
Method of Use		Used inconjunction withother diagnostictools and expertclinical judgment.	Used inconjunction withother diagnostictools and expertclinicaljudgment.	The proposed device has an identical method of useto the predicate.
ImagingModality		Computedtomograghy (CT),CT Angiography(CTA)	DICOMcompliant typesof imaginginformation	DICOM compliant types of imaging information
Environment		Hospital	Hospital	The proposed device and predicates have identicaltarget environments
OTC orPrescriptionDevice		Prescription Use	Prescription Use	The proposed device and predicate devices areidentical
	Level ofConcern	Moderate	Moderate
Software	Verification &Validation	Complies withFDA GuidanceRequirement	Complies withFDA GuidanceRequirement	The proposed device and predicate devices areidentical

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Comparison of Technological Characteristics

Comparison shows the Axial3D Cloud Segmentation Service is substantially equivalent in intended use, design, functionality, operating principles and performance characteristics of the predicate device.

Both the predicate and subject device are intended for use as a software interface and image segmentation process to facilitate the transfer of imaging information from a medical scanner to an output file. Both devices use the same segmentation functionality and generate the same output files. Both devices have functionalities to assist pre-surgical planning.

Verification and validation of both the subject and predicate devices have been performed in the same way.

It was found that minimal variances were visible between the Mesh generated from subject device and the predicate device, these variances are a result of mesh smoothing, Axial3D apply minimal smoothing to the STL file generated from the labeled images to retain a higher level of accuracy to

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the original DICOM images. The validation highlighted that the subject device performed to a higher standard, than the predicate device.

The printer selection is also based on 3D printer manufacturers' guidance on the most commonly used printing technologies for the production of medical 3D printed anatomical models.

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

. The subject device is a cloud based software platform rather than a standalone software package like the predicate

Performance Data

Non-clinical Testing

The Axial3D Cloud Segmentation Service device has been validated for its intended use to determine substantial equivalence to the predicate device. Measurement accuracy and comparisons were performed and confirmed to be within specification.

Validation of printing of physical replica models was performed and demonstrated to be accurate when using any of the compatible 3D printers.

Conclusion

The characteristics that determine functionality and performance of the subject device, Axial3D Cloud Segmentation Service are similar to the device cleared under K173619.

The conclusions drawn from the nonclinical tests demonstrate that the proposed subject device is as safe, as effective, and performs as well as the legally marketed predicate device.

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).