(62 days)
Axial3D Insight 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 Insight output file can be used for the fabrication of the output file using additive manufacturing methods.
The output file or physical replica can be used for treatment planning.
The output file or physical replica can be used for diagnostic purposes in the field of trauma, orthopedic, maxillofacial, and cardiovascular applications.
Axial3D Insight should be used with other diagnostic tools and expert clinical judgment.
Axial3D Insight is a secure, highly available cloud-based image processing, segmentation, and 3D modelling framework for the transfer of imaging information either as a 3D printed physical model.
Here's a breakdown of the acceptance criteria and study information for the Axial3D Insight device, based on the provided text:
Acceptance Criteria and Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Clinical Segmentation Performance (RADPEER score) | All cases scored within the acceptance criteria of 1 or 2a. |
| Intended Use Validation Study | 3D models produced by Axial3D demonstrated satisfaction of end-user needs and indications for use. |
| Phantom Testing (Origin One printer) | Reproduce required geometry to an acceptance criterion of ± 0.3mm. |
| Standalone performance of AI models | No direct acceptance criteria are stated, as AI outputs are not used in isolation. |
Note: The document states that the update to the product does not affect the current software validation, and the software portion is not being updated. Therefore, the existing validation testing from the predicate device (K222745) is considered applicable.
Study Details
Clinical Segmentation Performance Study
- Sample Size for Test Set: 12 cases.
- Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective).
- Number of Experts and Qualifications: 3 radiologists. No specific years of experience or subspecialty are provided, beyond being "radiologists."
- Adjudication Method: Not explicitly stated as 2+1 or 3+1. The study adopted a "peer-reviewed medical imaging review framework of RADPEER" to capture assessment and feedback.
- Multi Reader Multi Case (MRMC) Comparative Effectiveness Study: Not mentioned. This study focused on the performance of the device's segmentation, not human reader improvement with AI assistance.
- Standalone Performance Study: The output of the machine learning models is not used in isolation. The segmentations are further refined and validated by Axial3D trained staff. Therefore, a standalone performance study for the AI component (without human oversight) is not presented as the final product.
- Type of Ground Truth: Not explicitly stated, though implicitly refers to the standard of radiologists reviewing the segmentation.
- Sample Size for Training Set: Not specified for the Clinical Segmentation Performance Study.
- How Ground Truth for Training Set was Established: Not specified for the Clinical Segmentation Performance Study.
Intended Use Validation Study
- Sample Size for Test Set: 12 cases.
- Data Provenance: Not explicitly stated.
- Number of Experts and Qualifications: 9 physicians. No specific qualifications are provided beyond "physicians."
- Adjudication Method: Not explicitly stated.
- Multi Reader Multi Case (MRMC) Comparative Effectiveness Study: Not mentioned.
- Standalone Performance Study: Not applicable; this study validated the 3D models with physician review.
- Type of Ground Truth: Implicitly based on "end user needs and indications for use" as assessed by physicians.
- Sample Size for Training Set: Not specified.
- How Ground Truth for Training Set was Established: Not specified.
Axial™- Machine Learning Validation
This section describes the validation of the underlying machine learning models, which are used to generate initial segmentations, but their output is not used in isolation.
- Sample Size for Test Set (Validation Data):
- Cardiac CT/CTa: 4,838 images
- Neuro CT/CTa: 4,041 images
- Ortho CT: 10,857 images
- Trauma CT: 19,134 images
- Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). However, a list of various CT scanner manufacturers and models (GE Medical Systems, Siemens, Phillips, Toshiba) indicates a diversity of acquisition sources.
- Number of Experts and Qualifications: Not mentioned for this specific validation as it focuses on model output.
- Adjudication Method: Not mentioned.
- Multi Reader Multi Case (MRMC) Comparative Effectiveness Study: Not mentioned.
- Standalone Performance Study: The document explicitly states that the "output of these models is not used in isolation to produce the final 3D patient specific model." The segmentations are "used by Axial3D trained staff who complete the final segmentation and validation." Therefore, this is not a standalone performance of the AI in a clinical workflow, but an internal validation of the AI component before human refinement.
- Type of Ground Truth: Not explicitly stated for this machine learning validation. Implicitly, it would be expertly generated ground truth for segmentation.
- Sample Size for Training Set: Not specified in the provided text, but it states that the "training data used during the algorithm development was explicitly kept separate and independent from the validation data used."
- How Ground Truth for Training Set was Established: Not specified in the provided text.
Phantom Testing (for 3D Printer Verification)
- Sample Size for Test Set: Not explicitly stated as a number of phantoms, but involves "3D test phantoms provided by the National Institute of Standards and technology (NIST)."
- Data Provenance: NIST test phantoms.
- Number of Experts and Qualifications: Not applicable, as this is a technical verification of printer accuracy.
- Adjudication Method: Not applicable.
- Multi Reader Multi Case (MRMC) Comparative Effectiveness Study: Not applicable.
- Standalone Performance Study: Not applicable.
- Type of Ground Truth: Accuracy measurements against a known NIST test phantom.
- Sample Size for Training Set: Not applicable.
- How Ground Truth for Training Set was Established: Not applicable.
{0}------------------------------------------------
Image /page/0/Picture/0 description: The image contains 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 is 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.
Axial Medical Printing Limited % Sujith Shetty Executive Vice President Maxis Medical LLC 3031 Tisch Way, Suite 1010 San Jose, California 95128
Re: K232841
Trade/Device Name: Axial3D Insight Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH Dated: October 19, 2023 Received: October 20, 2023
Dear Sujith Shetty:
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
{1}------------------------------------------------
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).
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-regulatory
{2}------------------------------------------------
assistance/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
Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT 8B: Division of Radiological Imaging Devices and Electronic Products OHT 8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
{3}------------------------------------------------
Indications for Use
510(k) Number (if known) K232841
Device Name Axial3D Insight
Indications for Use (Describe)
Axial3D Insight 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 Insight output file can be used for the fabrication of the output file using additive manufacturing methods.
The output file or physical replica can be used for treatment planning.
The output file or physical replica can be used for diagnostic purposes in the field of trauma, orthopedic, maxillofacial, and cardiovascular applications.
Axial3D Insight should be used with other diagnostic tools and expert clinical judgment.
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."
{4}------------------------------------------------
Image /page/4/Picture/1 description: The image contains the logo for Axial3D. The logo consists of the word "axial" in a dark blue sans-serif font, with a small teal diamond shape above the "i". To the right of "axial" is the number "3D" in a smaller font size and slightly raised as a superscript. Below the main logo is the tagline "Patient data made real" in a teal sans-serif font.
510(k) Summary 5
{5}------------------------------------------------
Image /page/5/Picture/0 description: The image shows the logo for Axial3D. The logo is in a dark blue color, with the word "axial" in a bold, sans-serif font. Above the "i" in axial is a teal diamond. To the right of "axial" is the number "3D" in a smaller font. Below the logo is the tagline "Patient data made real" in a teal color.
510(k) Summary
This summary of 510(k) safety and effectiveness information is being submitted in accordance with the requirements of SMDA 1990 and 21 CRF 807.92.
510 (k) number: K232841
5.1 Applicant Information
| Axial Medical Printing Limited |
|---|
| 17A Ormeau Avenue |
| Belfast |
| BT2 8HD |
| United Kingdom |
| Tel: +44 (0)28 90183590 |
5.1.1 Contact Person
Joanne Flatley, QA/RA Lead
5.2 Device Information
| Trade Name | Axial3D Insight |
|---|---|
| Common Name | Automated Radiological Image Processing Software |
| Classification number: | 892.2050 |
| Regulatory Class | II |
| Product Code | QIH |
5.3 Predicate Device
Table 5-1 - Predicate Device
| Name | Manufacturer | 510(k)# |
|---|---|---|
| Axial3D Insight | Axial Medical Printing Limited | K222745 |
This predicate has not been subject to a design-related recall. No reference devices were used in this submission.
5.4 Device Description
Axial3D Insight is a secure, highly available cloud-based image processing, segmentation, and 3D modelling framework for the transfer of imaging information either as a 3D printed physical model.
{6}------------------------------------------------
Image /page/6/Picture/1 description: The image shows the logo for Axial3D. The word "axial" is in a dark gray color, with a teal diamond shape above the "i". To the right of "axial" is the number "3" in superscript, followed by the letter "D", also in dark gray. Below the logo is the text "Patient data made real" in teal.
5.4.1 Indications for Use
Axial3D Insight 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 Insight 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 output file or the physical replica can be used for diagnostic purposes in the field of trauma, orthopedic, maxillofacial, and cardiovascular applications.
Axial3D Insight should be used with other diagnostic tools and expert clinical judgment.
5.5 Comparison of Intended Use to Predicate and Reference Devices
| Attribute | Axial3D Insight(Proposed Device) | Axial3D Insight(Predicate Device K222745) | Comparison |
|---|---|---|---|
| DeviceManufacturer | Axial Medical Printing Limited | Axial Medical Printing Limited | N/A |
| Device Name | Axial3D Insight | Axial3D Insight | N/A |
| Device Trade orProprietaryName | Axial3D Insight | Axial3D Insight | N/A |
| 510(k) Number | K232841 | K222745 | N/A |
| DeviceRegulationName: | Automated Radiological ImageProcessing Software | Automated Radiological imageProcessing Software | Equivalent |
| DeviceRegulationNumber: | 21 CFR 892.2050 | 21 CFR 892.2050 | Equivalent |
| Device ProductCode: | QIH | QIH | Equivalent |
| DeviceClassificationFDA: | Class II | Class II | Equivalent |
| Indication forUse | Axial3DInsight is intended for useas a cloud-based service andimage segmentation frameworkfor the transfer of DICOM imaginginformation from a medicalscanner to an output file. | Axial3DInsight is intended for useas a cloud-based service andimage segmentation frameworkfor the transfer of DICOM imaginginformation from a medicalscanner to an output file. | Equivalent |
| Attribute | Axial3D Insight(Proposed Device) | Axial3D Insight(Predicate Device K222745) | Comparison |
| The Axial3DInsight output file canbe used for the fabrication ofphysical replicas of the output fileusing additive manufacturingmethods. | The Axial3DInsight output file canbe used for the fabrication ofphysical replicas of the output fileusing additive manufacturingmethods. | ||
| The output file or physical replicacan be used for treatmentplanning. | The output file or physical replicacan be used for treatmentplanning. | ||
| The output file or physical replicacan be used for diagnosticpurposes in the field of orthopedictrauma, orthopedic, maxillofacial,and cardiovascular applications. | The output file or physical replicacan be used for diagnosticpurposes in the field of orthopedictrauma, orthopedic, maxillofacial,and cardiovascular applications. | ||
| Axial3DInsight should be usedwith other diagnostic tools andexpert clinical judgment. | Axial3DInsight should be usedwith other diagnostic tools andexpert clinical judgment. | ||
| Axial Medical Printing Limited's,Axial3D Insight provides patientspecific 1:1 scale replica models,either as a digital file or as a 3Dprinted physical model. | Axial Medical Printing Limited's,Axial3D Insight provides patientspecific 1:1 scale replica models,either as a digital file or as a 3Dprinted physical model. | ||
| The digital file or 3D printedphysical model is intended to beused in conjunction with theDICOM images and expertclinical judgement. Theapplications for using the physical3D printed physical model as apresurgical planning tool are asfollows: | The digital file or 3D printedphysical model is intended to beused in conjunction with theDICOM images and expertclinical judgement. Theapplications for using the physical3D printed physical model as apresurgical planning tool are asfollows: | ||
| Intended Use | Preoperative planning of surgicaltreatment options includingplanning for surgical instruments,aiding decisions on implants, andaiding the surgical treatmentplan., All planning using the 3Dreplica model should be carriedout with the assistance of theDICOM imagesCommunication with the surgicalteam to discuss the surgicaltreatment plan in conjunction withDICOM images.Communication with the patientto discuss the surgical treatment | Preoperative planning of surgicaltreatment options includingplanning for surgical instruments,aiding decisions on implants, andaiding the surgical treatmentplan., All planning using the 3Dreplica model should be carriedout with the assistance of theDICOM imagesCommunication with the surgicalteam to discuss the surgicaltreatment plan in conjunction withDICOM images.Communication with the patientto discuss the surgical treatment | Equivalent |
| Attribute | Axial3D Insight (Proposed Device) | Axial3D Insight (Predicate Device K222745) | Comparison |
| plan in conjunction with DICOM imagesEducation tool for surgical planning. The 3D printed physical model can be used for surgical planning in the following applications: orthopedics and trauma, maxillofacial, and cardiovascular surgery. | plan in conjunction with DICOM images.Education tool for surgical planning. The 3D printed physical model can be used for surgical planning in the following applications: orthopedics and trauma, maxillofacial, and cardiovascular surgery. | ||
| Method of Use | Used in conjunction with other diagnostic tools and expert clinical judgement. | Used in conjunction with other diagnostic tools and expert clinical judgement. | Equivalent |
| Environment | Hospital | Hospital | Equivalent |
| OTC orPrescriptionDevice | Prescription Use | Prescription Use | Equivalent |
| Level ofConcern / | Moderate | Moderate | Equivalent: |
| V&V | Complies with FDA Guidance Requirement | Complies with FDA Guidance Requirement | Equivalent |
Table 5-2 – Predicate Device Comparison: Intended Use
{7}------------------------------------------------
Image /page/7/Picture/1 description: The image shows the logo for Axial3D. The logo consists of the word "axial" in a dark gray color, with a small teal diamond above the "i". To the right of "axial" is the superscript "3D". Below the word "axial" is the phrase "Patient data made real" in a teal color.
{8}------------------------------------------------
Image /page/8/Picture/1 description: The image shows the logo for Axial3D. The logo consists of the word "axial" 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 and also in dark blue. Below the word "axial" is the phrase "Patient data made real" in teal.
Comparison of Technological Characteristics to the Predicate Device 5.6
| Attribute | Axial3D Insight(Proposed Device) | Axial3D Insight(Predicate Device K222745) | Comparison |
|---|---|---|---|
| Method of Use | software interface | software interface | Equivalent |
| ComputerPlatform andOperatingSystem | Microsoft Edge (v104), Safari (v15) orChrome (v103) or equivalent | Microsoft Edge (v104), Safari (v15) orChrome (v103) or equivalent | Equivalent |
| SupportedModalities | CT and CTA | CT and CTA | Equivalent |
| Imageregistration | Yes | Yes | Equivalent |
| SegmentationFeatures | A combination of automated tools withsmart editing tools | A combination of automated tools withsmart editing tools | Equivalent |
| ViewManipulation and | Yes | Yes | Equivalent |
| Attribute | Axial3D Insight(Proposed Device) | Axial3D Insight(Predicate Device K222745) | Comparison |
| VolumeRendering | |||
| Regions andVolumes ofInterest (ROI) | Orthopedics / TraumaCardiovascularCranio- Maxillofacial | Orthopedics / TraumaCardiovascularCranio- Maxillofacial | Equivalent |
| Region/volumeof interestmeasurementsand sizemeasurements | Yes | Yes | Equivalent |
| Region/VolumeQuantification | Yes | Yes | Equivalent |
| ApprovedPrinters | Formlabs• Form 3BStratasys• J750• J5 Medijet• J850• Origin OneHP• HP580• HP540 | Formlabs• Form 3BStratasys• J750• J5 MedijetHP• HP580• HP540 | Similar |
| ApprovedMaterials | Formlabs• Form 3B◦ Standard White V4 FLGPWH04◦ Standard Draft V2 FLDRGR02◦ Standard Clear V4 FLGPCL04◦ Flexible 80A V1 FLFL8001Stratasys• J750◦ Agilus,◦ VeroBlackPlus,◦ VeroClear, | Formlabs• Form 3B◦ Standard White V4 FLGPWH04◦ Standard Draft V2 FLDRGR02◦ Standard Clear V4 FLGPCL04◦ Flexible 80A V1 FLFL8001Stratasys• J750◦ Agilus,◦ VeroBlackPlus,◦ VeroClear, | Similar |
| Attribute | Axial3D Insight(Proposed Device) | Axial3D Insight(Predicate Device K222745) | Comparison |
| VeroCyan, VeroGrey, VeroMagenta, VeroPureWhite, VeroYellow | VeroCyan, VeroGrey, VeroMagenta, VeroPureWhite, VeroYellow | ||
| J5 Medijet VeroVividTMCyan, VeroVividTMMagenta, VeroVividTMYellow, DraftWhite, MED610, MED615RGD, VeroUltraClearTM ElasticoTMClear | J5 Medijet VeroVividTMCyan, VeroVividTMMagenta, VeroVividTMYellow, DraftWhite, MED610, MED615RGD, VeroUltraClearTM ElasticoTMClear | ||
| J850 VeroVividTMCyan, VeroVividTMMagenta, VeroVividTMYellow, VeroPureWhite BoneMatrixTM GelMatrixTM TissueMatrixTM RadioMatrixTM Agilus30 VeroClear VeroMagenta BlackPlus | HP HP580 Nylon PA12 HP540 Nylon PA12 | ||
| Origin One ORIGIN DM100 by BASF ORIGIN DM200 by BASF LOCTITE 3D 3843 LOCTITE 3D IND405 | |||
| HP HP580 Nylon PA12 HP540 Nylon PA12 | |||
| Attribute | Axial3D Insight(Proposed Device) | Axial3D Insight(Predicate Device K222745) | Comparison |
| • Nylon PA12 |
{9}------------------------------------------------
Image /page/9/Picture/1 description: The image shows the logo for Axial3D. The word "axial" is in a dark gray color, with a teal diamond above the "i". The "3D" is in a smaller font and is located to the right and above the word "axial". Below the logo is the phrase "Patient data made real" in a teal color.
{10}------------------------------------------------
Image /page/10/Picture/1 description: The image shows the logo for Axial3D. The logo consists of the word "axial" in a dark blue sans-serif font, with a small teal diamond above the "i". To the right of "axial" is the superscript "3D". Below the word "axial" is the tagline "Patient data made real" in a teal sans-serif font.
{11}------------------------------------------------
Image /page/11/Picture/1 description: The image shows the logo for Axial3D. The word "axial" is written in a bold, dark blue font, with a small teal diamond above the "i". To the right of "axial" is a superscript "3D", also in dark blue. Below the logo is the tagline "Patient data made real" in a teal font.
5.7 Performance Data
Axial3D Insight Device Validation 5.7.1
Axial3D performed software design verification and validation testing on all three software components of the device and the software documentation for a Moderate Level of Concern software, per FDA Guidance "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" issued in 2005. The update to the product that is the subject of this premarket notification does not affect the current software validation, as only new materials and printers are being added to the product. Axial3D is aware that the FDA software quidance was updated in 2023, but since the software portion of the Axial insight product is not being updated as a part of this submission, testing in accordance with the previous guidance remains applicable.
Axial3D has conducted software verification and validation, in accordance with the FDA guidance, General Principles of Software Validation; Final Guidance for Industry and FDA Staff, issued on January 11, 2002. All software requirements and risk analysis have been successfully verified and traced.
In addition to the human factors' validation of the Axial3D Insight device, Axial3D conducted two validation studies:
- Clinical Segmentation Performance Study .
- . Intended Use Validation Study
The Clinical Segmentation Performance study was conducted with 3 radiologists reviewing the segmentation of 12 cases across the fields of Orthopedics, Trauma, Maxillofacial and Cardiovascular. Axial3D adopted a peer reviewed medical imaging review framework of RADPEER* to capture the assessment and feedback from the radiologists involved - all cases were scored within the acceptance criteria of 1 or 2a.
- "ACR RADPEER committee white paper with 2016 updates: revised scoring system, new classifications, self-review, and subspecialized reports." Journal of the American College of Radiology 14.8 (2017): 1080-1086.
The Intended Use validation study of the device was conducted with 9 physicians reviewing 12 cases across the fields of Orthopedics, Trauma, Maxillofacial and Cardiovascular, as defined in the Intended Use statement of the device. This study concluded successful validation of the 3D models produced by Axial3D demonstrating the device outputs satisfied end user needs and indications for use.
Axial™- Machine Learning Validation 5.7.2
AxialM- machine learning models are used to generate an initial segmentation of cases, however
{12}------------------------------------------------
Image /page/12/Picture/1 description: The image shows the logo for Axial3D. The logo consists of the word "axial" in a dark gray color, with a small teal diamond above the "i". To the right of "axial" is the superscript "3D" in the same dark gray color. Below the word "axial" is the phrase "Patient data made real" in a teal color.
the output of these models is not used in isolation to produce the final 3D patient specific model. The segmentations produced by the Axial™ machine learning models are used by Axial3D trained staff who complete the final segmentation and validation of the quality of each 3D patient specific model produced.
AxialMI- machine learning models were independently verified and validated before inclusion in the Axial3D Insight device. Details of the data used in the validation of each machine learning model is provided below.
{13}------------------------------------------------
Image /page/13/Picture/1 description: The image shows the logo for Axial3D. The word "axial" is in a dark blue color, and the "3D" is in black. Below the logo is the phrase "Patient data made real" in a light blue color.
| CardiacCT/CTa | Neuro CT/CTa | Ortho CT | Trauma CT | |
|---|---|---|---|---|
| Number ofImages Usedfor Validation | 4,838 | 4,041 | 10,857 | 19,134 |
| Slice SpacingRange(Min, Max inmm) | 0.4 - 0.8 | 0.44 - 1.0 | 0.3 - 2.0 | 0.2 - 2.0 |
| Slice SpacingAverage(in mm) | 0.54 | 0.63 | 0.79 | 0.76 |
| Pixel SizeRange (Min,Max in mm) | 0.23 - 0.78 | 0.34 - 0.70 | 0.18 - 0.98 | 0.22 - 0.98 |
| Pixel SizeAverage (mm) | 0.46 | 0.51 | 0.44 | 0.51 |
Table 5-3: Software Validation Data
*NeuroCT/CTa model is used for cardiology cases.
The variety of image scanner manufacturers and models used within the validation dataset are listed below.
Table 5-4 – Imaging scanner manufactures and models used for the validation datasets
| Manufacturer | Model |
|---|---|
| GE Medical Systems | Lightspeed Pro 16 |
| Lightspeed Pro 32 | |
| Revolution CT | |
| Optima CT660 | |
| Discovery CT750 HD | |
| Siemens | SOMATOM Definition Flash |
| SOMATOM Definition Edge | |
| SOMATOM Definition AS | |
| SOMATOM Definition AS+ |
{14}------------------------------------------------
Image /page/14/Picture/1 description: The image shows the logo for Axial3D. The logo consists of the word "axial" in a dark blue sans-serif font, with a small teal diamond above the "i". To the right of "axial" is the number "3D" in a smaller font, with the "3" raised as a superscript. Below the word "axial" is the tagline "Patient data made real" in a teal sans-serif font.
| SOMATOM Perspective | |
|---|---|
| SOMATOM Force | |
| Sensation 16 | |
| AXIOM-Artis | |
| Emotion 16 | |
| Phillips | IQON Spectral CT |
| iCT 128 | |
| iCT 256 | |
| Ingenuity Core 128 | |
| Brilliance 62 | |
| Toshiba | Aquillon PRIME |
| Aquillon PRIME SP |
The AxialM machine learning model training data used during the algorithm development was explicitly kept separate and independent from the validation data used.
5.7.3 Phantom Testing
Verification of the Stratasys Origin One Printer and materials 5.7.3.1
The verification testing of the Origin One printer involved printing 3D test phantoms provided by the National Institute of Standards and technology (NIST). This object provides a realistic challenge to the geometry the printer will need to replicate to print anatomical models. Similar features are present in anatomical structures such as thin walls, flat surfaces, holes, and overhangs. The NIST test phantom also makes possible a detailed evaluation of a range of small, medium, and large features, which also replicate anatomical features while allowing repeated measurements to determine accuracy and repeatability as outlined in Slide 12 FDA/CDRH-RSNA SIG Joint Meeting on 3D Printed Patient-Specific Anatomic Models.
This verification test establishes that the printer can reproduce the required geometry to an acceptance criterion of ± 0.3mm, the same acceptance criteria used to verify the predicate device (Axial 3D Insight, K222745)
Verification of the Stratasys J850 and materials 5.7.3.2
Axial Medical Printing verified the Stratasys J850 printer as part of the design control process. Testing was performed on the J850 by Stratasys, who provided a test report detailing the verification activity.
{15}------------------------------------------------
Image /page/15/Picture/0 description: The image shows the logo for Axial3D. The logo consists of the word "axial" in a dark blue color, with a small teal diamond shape above the "i". To the right of "axial" is the number "3D" in a smaller font size and also in dark blue. Below the word "axial" is the phrase "Patient data made real" in teal.
Verification testing for the J850 printer is appropriate to establish that the Axial3D Insight device can produce anatomical models with the required accuracy of the product, as established in K222745
5.8 Conclusions:
Based on the indications for use, product performance, and clinical information provided in this notification, the Axial3D Insight is considered substantially equivalent to the marketed predicate device, Axial3D Insight (K222745). Both the predicate device and the Axial3D Insight have similar DICOM segmentation and 3D model creation. This 510(k) notification contains the technological characteristics and validation and verification to demonstrate the Axial3D Insight does not raise any different questions regarding safety and effectiveness compared to the predicate, Axial3D Insight (K222745).
§ 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).