(152 days)
Acorn 3D Software is a modular image processing software intended for use as an interface for visualization of medical images, segmentation, treatment planning, and production of an output file.
The Acorn 3D Segmentation module is intended for use as a software interface and image segmentation system for the transfer of CT or CTA medical images to an output file. Acorn 3D Segmentation is also intended for measuring and treatment planning. The Acorn 3D Segmentation output can also be used for the fabrication of physical replicas of the output file using additive manufacturing methods, Acorn 3DP Models. The physical replica can be used for diagnostic purposes in the field of musculoskeletal and craniomaxillofacial applications.
The Acorn 3D Alignment and Measurement module contains registration capabilities and measurement functionality based on anatomical reference geometry. It is intended to allow the user to align anatomical structures between datasets, perform spinopelvic measurements on 3D models of anatomy, and plan surgical procedures in pediatric and adult patients.
Acorn 3D Software and 3DP Models should be used in conjunction with expert clinical judgment.
Acorn 3D Software is an image processing software that allows the user to import, visualize and segment medical images, check and correct the segmentations, and create digital 3D models. The models can be used in Acorn 3D Software for measuring, treatment planning and producing an output file to be used for additive manufacturing (3D printing). Acorn 3D Software is structured as a modular package.
This includes the following functionality:
- Importing medical images in DICOM format
- Viewing images and DICOM data
- Selecting a region of interest using generic segmentation tools
- Segmenting specific anatomy using dedicated semi-automatic tools or fully automatic algorithms
- Verifying and editing a region of interest
- Calculating a digital 3D model and editing the model
- Measuring on images and 3D models
- Exporting 3D models to third-party packages
- Image registration
The Acorn 3D Segmentation module contains both machine learning based auto segmentation as well as semi-automatic and manual segmentation tools. The auto-segmentation tool is only intended to be used for thoracic and lumbar regions of the spine (T1-T12 and L1-L5) and the pelvis (sacrum). Semi-automatic and manual segmentation tools are intended to be used for all musculoskeletal anatomy.
Acorn 3DP Model is an additively manufactured physical replica of the virtual 3D model generated in Acorn 3D Segmentation. The output file from Acorn 3D Segmentation is used to additively manufacture the Acorn 3DP Model.
The Acorn 3D Alignment and Measurement module contains registration capabilities and spinopelvic measurement functionality. It is intended to align spinopelvic anatomical structures between datasets. The module allows the user to perform spinopelvic measurements on 3D models of anatomy, and to plan surgical procedures.
Here's a breakdown of the acceptance criteria and study details for the Acorn 3D Software, based on the provided FDA 510(k) clearance letter:
Acceptance Criteria and Reported Device Performance
| Acceptance Criteria Category | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Alignment Accuracy (Target Registration Error - TRE) for Slot Beam X-Ray Technique | Not explicitly stated (implied to be equivalent to predicate device) | Median TRE: 1.70 mm3rd Quartile TRE: 2.74 mm |
| Alignment Accuracy (Target Registration Error - TRE) for Cone Beam X-Ray Technique | Not explicitly stated (implied to be equivalent to predicate device) | Median TRE: 4.33 mm3rd Quartile TRE: 5.58 mm |
| Machine Learning Model Performance (DICE Similarity Coefficient - DSC) for Vertebral Model (T1-T12, L1-L5) | > 0.88375 | In-House (Mighty Oak Medical): 0.9331VERSE '20: 0.94451 |
| Machine Learning Model Performance (DICE Similarity Coefficient - DSC) for Sacral Model | > 0.96045 | In-House (Mighty Oak Medical): 0.96630 |
| General Performance | Device performance and substantial equivalence to the predicate device. | All performance testing conducted demonstrated device performance and substantial equivalence to the predicate device. |
Study Details
1. Sample Sizes and Data Provenance
Test Set:
- Vertebral Model (T1-T12, L1-L5):
- In-House (Mighty Oak Medical): 35 cases (450 segments - 139 lumbar / 311 thoracic).
- VERSE '20: 36 cases (401 segments - 144 lumbar / 257 thoracic).
- Total Test Set for Vertebral Model: 71 cases.
- Sacral Model:
- In-House (Mighty Oak Medical): 40 cases.
- Total Test Set for Sacral Model: 40 cases.
Data Provenance (Test Set):
- In-House (Mighty Oak Medical): Retrospective (implied, as it's an internal database). Country of origin not explicitly stated.
- VERSE '20: Publicly available dataset. Inclusion criteria: Patients > 30 years of age, no history of bone metastases. Specific country of origin not explicitly stated, but typically these are multi-institutional datasets from various countries. Retrospective.
- CTPelvic1K: Publicly available dataset used only for training and tuning the Sacral model. Country of origin not explicitly stated.
2. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
- Mighty Oak Medical (In-House): "Highly-trained experts" and "operators who have undergone extensive classroom training and tests for efficacy, with an established track record of creating accurate segmentations." Specific number not mentioned. Qualifications are described as having an "established track record of creating accurate segmentations in support of the FIREFLY Pedicle Screw Navigation Guide."
- VERSE '20: "Widely accepted as ground truth, with three levels of annotation and expert review (by medical and/or graduate students, radiology fellows, and finally a senior consultant)." Specific number not mentioned. The qualifications range from medical/graduate students to radiology fellows and senior consultants.
3. Adjudication Method for the Test Set
- Mighty Oak Medical (In-House): "Verified by feedback loops of expert review and manual editing and correction."
- VERSE '20: "Three levels of annotation and expert review (by medical and/or graduate students, radiology fellows, and finally a senior consultant)." This implies a multi-level consensus approach, but a specific method like "2+1" or "3+1" is not explicitly stated.
4. MRMC Comparative Effectiveness Study
No Multi-Reader Multi-Case (MRMC) comparative effectiveness study was mentioned where human readers' improvement with AI vs. without AI assistance was evaluated. The performance data focuses on the standalone algorithm's accuracy, and the device is intended to be used "in conjunction with expert clinical judgment."
5. Standalone Performance Study
Yes, standalone (algorithm only) performance was done. The "Machine-Learning Model Performance Testing" section directly compares the model's output (segmentations) with ground truth segmentations using the DICE Similarity Coefficient (DSC). The "Alignment Accuracy" evaluation also assesses the algorithm's performance directly against ground truth.
6. Type of Ground Truth Used
- Expert Consensus: For both In-House (Mighty Oak Medical) and VERSE '20 datasets, the ground truth was established through expert review and refinement of segmentations.
- Pathology/Outcomes Data: Not explicitly mentioned as being used for ground truth for the segmentation or alignment accuracy.
7. Sample Size for the Training Set
- Vertebral Model (T1-T12, L1-L5): 147 cases (from Mighty Oak Medical In-House dataset).
- Sacral Model: 204 cases (104 from Mighty Oak Medical In-House dataset, 100 from CTPelvic1K dataset).
8. How the Ground Truth for the Training Set Was Established
- Mighty Oak Medical (In-House): Similar to the test set, segmentations are "produced on clinical cases by operators who have undergone extensive classroom training and tests for efficacy, with an established track record of creating accurate segmentations." These were "verified by feedback loops of expert review and manual editing and correction."
- CTPelvic1K: "Widely accepted as ground truth, with three levels of annotation and expert review (by medical and/or graduate students, radiology fellows, and finally a senior consultant), and being used in support of public machine-learning segmentation research."
FDA 510(k) Clearance Letter - Acorn 3D Software
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U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
Doc ID # 04017.08.02
Mighty Oak Medical
Mark Wylie
VP Quality and Regulatory
750 W. Hampden Ave
Suite 120
Englewood, Colorado 80110
Re: K252103
Trade/Device Name: Acorn 3D Software (AC-SEG-4009); Acorn 3DP Model (AC-101-XX)
Regulation Number: 21 CFR 892.2050
Regulation Name: Medical Image Management And Processing System
Regulatory Class: Class II
Product Code: QIH, LLZ
Dated: October 30, 2025
Received: October 30, 2025
Dear Mark Wylie:
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.
December 2, 2025
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Mighty Oak Medical
Mark Wylie
VP Quality and Regulatory
750 W. Hampden Ave
Suite 120
Englewood, Colorado 80110
December 2, 2025
Re: K252103
Trade/Device Name: Acorn 3D Software (AC-SEG-4009); Acorn 3DP Model (AC-101-XX)
Regulation Number: 21 CFR 892.2050
Regulation Name: Medical Image Management And Processing System
Regulatory Class: Class II
Product Code: QIH, LLZ
Dated: October 30, 2025
Received: October 30, 2025
Dear Mark Wylie:
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.
U.S. Food and Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
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 (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-reporting-combination-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.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
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-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/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
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the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-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, Ph.D.
Assistant Director
DHT8B: Division of Radiological 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
Please type in the marketing application/submission number, if it is known. This textbox will be left blank for original applications/submissions.
K252103
Please provide the device trade name(s).
Acorn 3D Software (AC-SEG-4009);
Acorn 3DP Model (AC-101-XX)
Please provide your Indications for Use below.
Acorn 3D Software is a modular image processing software intended for use as an interface for visualization of medical images, segmentation, treatment planning, and production of an output file.
The Acorn 3D Segmentation module is intended for use as a software interface and image segmentation system for the transfer of CT or CTA medical images to an output file. Acorn 3D Segmentation is also intended for measuring and treatment planning. The Acorn 3D Segmentation output can also be used for the fabrication of physical replicas of the output file using additive manufacturing methods, Acorn 3DP Models. The physical replica can be used for diagnostic purposes in the field of musculoskeletal and craniomaxillofacial applications.
The Acorn 3D Alignment and Measurement module contains registration capabilities and measurement functionality based on anatomical reference geometry. It is intended to allow the user to align anatomical structures between datasets, perform spinopelvic measurements on 3D models of anatomy, and plan surgical procedures in pediatric and adult patients.
Acorn 3D Software and 3DP Models should be used in conjunction with expert clinical judgment.
Please select the types of uses (select one or both, as applicable).
☑ Prescription Use (21 CFR 801 Subpart D)
☐ Over-The-Counter Use (21 CFR 801 Subpart C)
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510(K) SUMMARY
Acorn 3D Alignment & Measurement
Submitter:
Mighty Oak Medical
750 W. Hampden Ave., Suite 120
Englewood, CO 80110
(720) 398-9703
Contact: Mark A. Wylie, VP of Quality and Regulatory
Date Prepared: 29OCT2025
Device
Trade Name: Acorn 3D Software (AC-SEG-4009), Acorn 3DP Model (AC-101-XX)
Common Name: Image processing system
Device Classification: Class II
Regulation, Name: 21 CFR 892.2050, Medical image management and processing system
Device Product Code: QIH, LLZ
Type of 510(k)
Original Submission: Traditional.
Predicate Device(s):
Acorn 3D Software & 3DP Model
| 510(k) | Product Code | Trade Name | Manufacturer |
|---|---|---|---|
| Primary Predicate Device | |||
| K234009 | QIH, LLZ | Acorn 3D Software & 3DP Model | Mighty Oak Medical |
| Subsequent Predicate Device | |||
| K240582 | QIH, LLZ | VEA Align; spineEOS | EOS Imaging |
Introduction
This 510(k) filing seeks to expand the indications for use of the previously cleared Acorn 3D Software (K234009) to include registration capabilities and measurement functionality based on anatomical reference geometry. This submission includes the Acorn 3D Alignment & Measurement module as a new extension of the Acorn 3D Software.
Acorn 3D Software is a modular and multi-functional software suite. The subject device, Acorn 3D Alignment & Measurement module, builds on the functions and capabilities of the Acorn 3D Software (predicate), specifically image segmentation and the transfer of imaging information from a medical scanner to an output file. Acorn 3D Alignment & Measurement module allows the user to align anatomical structures between datasets, perform spinopelvic measurements on 3D models of anatomy, and plan surgical procedures.
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Description
Acorn 3D Software is an image processing software that allows the user to import, visualize and segment medical images, check and correct the segmentations, and create digital 3D models. The models can be used in Acorn 3D Software for measuring, treatment planning and producing an output file to be used for additive manufacturing (3D printing). Acorn 3D Software is structured as a modular package.
This includes the following functionality:
- Importing medical images in DICOM format
- Viewing images and DICOM data
- Selecting a region of interest using generic segmentation tools
- Segmenting specific anatomy using dedicated semi-automatic tools or fully automatic algorithms
- Verifying and editing a region of interest
- Calculating a digital 3D model and editing the model
- Measuring on images and 3D models
- Exporting 3D models to third-party packages
- Image registration
The Acorn 3D Segmentation module contains both machine learning based auto segmentation as well as semi-automatic and manual segmentation tools. The auto-segmentation tool is only intended to be used for thoracic and lumbar regions of the spine (T1-T12 and L1-L5) and the pelvis (sacrum). Semi-automatic and manual segmentation tools are intended to be used for all musculoskeletal anatomy.
| Automatic | Semi-Automatic | Manual | |
|---|---|---|---|
| Definition | Algorithmic with little or no direct human control | A combination of algorithmic and direct human control | Directly controlled by a human |
| Tool Type | Machine Learning algorithm used to automatically segment individual vertebrae and the pelvis | Algorithmic based tools that do not incorporate machine learning. | Manual tools requiring user input. |
| Anatomical Location(s) | Spinal anatomy:• Thoracic (T1-T12)• Lumbar (L1-L5)• Sacrum | Musculoskeletal & craniomaxillofacial bone:• Short• Long• Flat• Sesamoid• Irregular | Musculoskeletal & craniomaxillofacial bone:• Short• Long• Flat• Sesamoid• Irregular |
Acorn 3DP Model is an additively manufactured physical replica of the virtual 3D model generated in Acorn 3D Segmentation. The output file from Acorn 3D Segmentation is used to additively manufacture the Acorn 3DP Model.
The Acorn 3D Alignment and Measurement module contains registration capabilities and spinopelvic measurement functionality. It is intended to align spinopelvic anatomical structures between datasets. The module allows the user to perform spinopelvic measurements on 3D models of anatomy, and to plan surgical procedures.
Indications for Use
Acorn 3D Software is a modular image processing software intended for use as an interface for visualization of medical images, segmentation, treatment planning, and production of an output file.
The Acorn 3D Segmentation module is intended for use as a software interface and image segmentation system for the transfer of CT or CTA medical images to an output file. Acorn 3D
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Segmentation is also intended for measuring and treatment planning. The Acorn 3D Segmentation output can also be used for the fabrication of physical replicas of the output file using additive manufacturing methods, Acorn 3DP Models. The physical replica can be used for diagnostic purposes in the field of musculoskeletal and craniomaxillofacial applications.
The Acorn 3D Alignment and Measurement module contains registration capabilities and measurement functionality based on anatomical reference geometry. It is intended to allow the user to align anatomical structures between datasets, perform spinopelvic measurements on 3D models of anatomy, and plan surgical procedures in pediatric and adult patients.
Acorn 3D Software and 3DP Models should be used in conjunction with expert clinical judgment.
Materials
The manufactured components of the Acorn 3DP Model are manufactured from a polymer powder for use in additive manufacturing (HP 3D High Reusability PA12).
Performance Data
Software verification and validation were performed and documentation was provided following the "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices". This includes verification against defined requirements and validation against user needs. Both end-user validation and bench testing were performed.
The accuracy of alignments and measurements completed within the subject device, Acorn 3D Alignment & Measurement module, was assessed via bench testing. Accuracy of anatomical structure alignment and resulting spinopelvic measurements were evaluated both qualitatively and quantitatively. Quantitative measurement results demonstrate registration accuracy equivalent to the predicate device.
Quantitative bench testing was performed for alignment of 3D models to planar x-rays separately for two different x-ray techniques: slot beam and cone beam. For each sample (individual aligned vertebra), a Target Registration Error (TRE) was generated for a series of anatomical landmark points as the distance in mm between test alignments and ground truth. Alignment accuracy was assessed as the Median and 3rd Quartile TRE among all landmark points for each x-ray technique, as summarized below:
| X-Ray Technique | Median TRE (mm) | 3rd Quartile TRE (mm) |
|---|---|---|
| Slot Beam | 1.70 | 2.74 |
| Cone Beam | 4.33 | 5.58 |
In conclusion, all performance testing conducted demonstrated device performance and substantial equivalence to the predicate device.
Technological Characteristics
Acorn 3D Software is a standalone modular software package. This software package includes, but is not limited to, the following functions:
Image import
- Importing medical images in DICOM format (e.g., CT and CTA)
Image Processing
- Processing of images with common noise-reduction filters
- Editing of spatial arrangement of images
Visualization
- Viewing images and DICOM data
Segmentation
- Selecting a region of interest using generic segmentation tools
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- Segmenting specific anatomy using dedicated semi-automatic tools
- Segmenting specific vertebral anatomy using machine-learning-based fully automatic algorithms
- Verifying and editing a region of interest
Data Export
- Output information is exported in a machine-readable format (e.g., JSON and STL)
3D Models
- Calculating a digital 3D model and editing the model
- Smoothing a 3D model
- Importing 3D models
Treatment Planning
- Importing of third-party STLs to visualize planned interactions with anatomy as represented in DICOM images
Other features
- Using a collection of images and masks as a training dataset for machine-learning segmentation algorithm
- Pedicle Screw Placement
Registration
- Alignment of anatomical structures between datasets
Measurement
- Measuring on images and 3D models
- Standard and generic 3D measurements of spinopelvic anatomy based on user-defined reference geometry
Substantial Equivalence Comparison Table
| Device→Features↓ | Acorn 3D Software(K252103) | Acorn 3D Software(K234009) | spineEOS / VEA Align(K240582) |
|---|---|---|---|
| Trade Name | Acorn 3D Software (AC-SEG-4009);Acorn 3DP Model (AC-101-XX) | Acorn 3D Software (AC-SEG-4009);Acorn 3DP Model (AC-101-XX) | VEA Align; spineEOS |
| Common Name | Image processing system | Image processing system | Automated RadiologicalImage Processing Software |
| Premarket notification | K252103 | K234009 | K240582 |
| Manufacturer | Mighty Oak Medical | Mighty Oak Medical | EOS Imaging |
| Indications for Use Statement | Acorn 3D Software is a modular image processing software intended for use as an interface for visualization of medical images, segmentation, treatment planning, and production of an output file.The Acorn 3D Segmentation module is intended for use as a software interface and image segmentation system for the transfer of CT or CTA medical images to an output file. Acorn 3D Software is also intended for measuring and treatment planning. The Acorn 3D Segmentation output can also be used for the fabrication of physical replicas of the output file using additive manufacturing methods, Acorn 3DP Models. The physical replica can be used for | Acorn Segmentation is intended for use as a software interface and image segmentation system for the transfer of CT or CTA medical images to an output file. Acorn Segmentation is also intended for measuring and treatment planning. The Acorn Segmentation output can also be used for the fabrication of physical replicas of the output file using additive manufacturing methods, Acorn 3DP Models. The physical replica can be used for diagnostic purposes in the | VEA Align:This cloud-based software is intended for orthopedic applications in both pediatric and adult populations.2D X-ray images acquired in EOS imaging's imaging systems is the foundation and resource to display the interactive landmarks overlayed on the frontal and lateral images. These landmarks are available for users to assess patient-specific global alignment.For additional assessment, alignment parameters compared to published |
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| Device→Features↓ | Acorn 3D Software(K252103) | Acorn 3D Software(K234009) | spineEOS / VEA Align(K240582) |
|---|---|---|---|
| diagnostic purposes in the field of musculoskeletal and craniomaxillofacial applications.The Acorn 3D Alignment and Measurement module contains registration capabilities and measurement functionality based on anatomical reference geometry. It is intended to allow the user to align anatomical structures between datasets, perform spinopelvic measurements on 3D models of anatomy, and plan surgical procedures in pediatric and adult patients.Acorn 3D Software and 3DP Models should be used in conjunction with expert clinical judgment. | field of musculoskeletal and craniomaxillofacial applications.Acorn Segmentation and 3DP Models should be used in conjunction with expert clinical judgment. | normative values may be available.This product serves as a tool to aid in the analysis of spinal deformities and degenerative diseases, and lower limb alignment disorders and deformities through precise angle and length measurements. It is suitable for use with adult and pediatric patients aged 7 years and older.Clinical judgment and experience are required to properly use the software.spineEOS:spineEOS is indicated for assisting healthcare professionals with preoperative planning of spine surgeries. The product provides access to EOS images with associated 3D datasets and measurements. spineEOS includes surgical planning tools that enable users to define a patient specific surgical strategy. | |
| General intended use | Acorn 3D Software is an image processing software that allows the user to import, visualize and segment medical images, check and correct the segmentations, conduct surgical planning, and create and manipulate digital 3D models. | Acorn Segmentation is image processing software that allows the user to import, visualize and segment medical images, check and correct the segmentations, and create digital 3D models. | spineEOS is indicated for assisting healthcare professionals with preoperative planning of spine surgeries. The product provides access to EOS images with associated 3D datasets and measurements. spineEOS includes surgical planning tools that enable users to define a patient specific surgical strategy. |
| Product Classification | System, Image processing, Radiological | System, Image processing, Radiological | System, Image processing, Radiological |
| Regulatory Class | Class II | Class II | Class II |
| Regulation Number | 892.2050 | 892.2050 | 892.2050 |
| Product Code | QIH and LLZ | QIH and LLZ | QIH and LLZ |
| Device Description | Acorn 3D Software is an image processing software that allows the user to import, visualize and segment medical images, check and correct the segmentations, and create digital 3D models. The models can be used in Acorn 3D for measuring, treatment planning and producing an output file | Acorn Segmentation is an image processing software that allows the user to import, visualize and segment medical images, check and correct the segmentations, and create digital 3D models. The models can be used in Acorn Segmentation for measuring, treatment planning and producing an | VEA Align is a software indicated for assisting healthcare professionals with global alignment assessment through clinical parameters computation. |
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| Device→Features↓ | Acorn 3D Software(K252103) | Acorn 3D Software(K234009) | spineEOS / VEA Align(K240582) |
|---|---|---|---|
| to be used for additive manufacturing (3D printing). Acorn 3D Software is structured as a modular package.This includes the following functionality:• Importing medical images in DICOM format• Viewing images and DICOM data• Selecting a region of interest using generic segmentation tools• Segmenting specific anatomy using dedicated semi-automatic tools or fully automatic algorithms• Verifying and editing a region of interest• Calculating a digital 3D model and editing the model• Measuring on images and 3D models• Exporting 3D models to third-party packages• Image registrationThe Acorn 3D Segmentation module contains both machine learning based auto segmentation as well as semi-automatic and manual segmentation tools. The auto-segmentation tool is only intended to be used for thoracic and lumbar regions of the spine (T1-T12 and L1-L5). Semi-automatic and manual segmentation tools are intended to be used for all musculoskeletal anatomy.Acorn 3DP Model is an additively manufactured physical replica of the virtual 3D model generated in Acorn 3D Segmentation. The output file from Acorn 3D Segmentation is used to additively manufacture the Acorn 3DP Model.The Acorn 3D Alignment and Measurement module contains registration capabilities and spinopelvic measurement functionality. It is intended to align spinopelvic anatomical structures between datasets. The module allows the user to perform spinopelvic measurements on 3D models of anatomy, and to plan surgical procedures. | output file to be used for additive manufacturing (3D printing). Acorn Segmentation is structured as a modular package.This includes the following functionality:• Importing medical images in DICOM format• Viewing images and DICOM data• Selecting a region of interest using generic segmentation tools• Segmenting specific anatomy using dedicated semi-automatic tools or fully automatic algorithms• Verifying and editing a region of interest• Calculating a digital 3D model and editing the model• Measuring on images and 3D models• Exporting 3D models to third-party packagesAcorn Segmentation contains both machine learning based auto segmentation as well as semi-automatic and manual segmentation tools. The auto-segmentation tool is only intended to be used for thoracic and lumbar regions of the spine (T1-T12 and L1-L5). Semi-automatic and manual segmentation tools are intended to be used for all musculoskeletal anatomy.Acorn 3DP Model is an additively manufactured physical replica of the virtual 3D model generated in Acorn Segmentation. The output file from Acorn Segmentation is used to additively manufacture the Acorn 3DP Model. | The product uses biplanar 2D X-ray images, exclusively generated by EOS imaging's EOS (K152788) and EOSedge (K202394) systems and generates an initial placement of the patient anatomic landmarks on the images using a machine learning-based algorithm. The user may adjust the landmarks to align with the patient's anatomy.Landmark locations require user validation. The clinical parameters communicated to the user are inferred from the landmarks and are recalculated as the user adjusts the landmarks. 3D datasets may be exported for use in spineEOS for surgical planning.The product is hosted on a cloud infrastructure and relies on VEA Portal for support capabilities, such as user access control and data access. 2D X-ray image transmissions from healthcare institutions to the cloud are managed by VEA Portal. VEA Portal is a Class I 510(k)-exempt device (LMD).spineEOS is a software indicated for assisting healthcare professionals with preoperative planning of spine surgeries. EOS images (generated from EOS imaging's acquisition system) and associated 3D datasets are used as inputs of the software. The product manages clinical measurements and allows user to access surgical planning tools to define a patient specific surgical strategy. The product is indicated for adolescent and adult patients. | |
| Intended User | The Acorn 3D Segmentation module can be used by biomedical engineers or personnel equivalent by training or experience. Their results should be used in conjunction with expert clinical judgement.The Acorn 3D Alignment & Measurement module is intended for | Acorn Segmentation can be used by biomedical engineers or personnel equivalent by training or experience. Their results should be used in conjunction with expert clinical judgement. | spineEOS is a software indicated for assisting healthcare professionals with preoperative planning of spine surgeries. |
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| Device→Features↓ | Acorn 3D Software(K252103) | Acorn 3D Software(K234009) | spineEOS / VEA Align(K240582) |
|---|---|---|---|
| use by medical professionals, such as clinicians and surgeons, who are trained in spinal procedures and the interpretation of diagnostic imaging. | The product uses biplanar 2D X-ray images, exclusively generated by EOS imaging's EOS (K152788) and EOSedge (K202394) systems and generates an initial placement of the patient anatomic landmarks on the images using a machine learning-based algorithm. The user may adjust the landmarks to align with the patient's anatomy.Landmark locations require user validation. The clinical parameters communicated to the user are inferred from the landmarks and are recalculated as the user adjusts the landmarks. 3D datasets may be exported for use in spineEOS for surgical planning.The product is hosted on a cloud infrastructure and relies on VEA Portal for support capabilities, such as user access control and data access. 2D X-ray image transmissions from healthcare institutions to the cloud are managed by VEA Portal. VEA Portal is a Class I 510(k)-exempt device (LMD).spineEOS is a software indicated for assisting healthcare professionals with preoperative planning of spine surgeries. EOS images (generated from EOS imaging's acquisition system) and associated 3D datasets are used as inputs of the software. The product manages clinical measurements and allows user to access surgical planning tools to define a patient specific surgical strategy. The product is indicated for adolescent and adult patients. | ||
| Intended User | The Acorn 3D Segmentation module can be used by biomedical engineers or personnel equivalent by training or experience. Their results should be used in conjunction with expert clinical judgement.The Acorn 3D Alignment & Measurement module is intended for | Acorn Segmentation can be used by biomedical engineers or personnel equivalent by training or experience. Their results should be used in conjunction with expert clinical judgement. | spineEOS is a software indicated for assisting healthcare professionals with preoperative planning of spine surgeries. |
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| Device→Features↓ | Acorn 3D Software(K252103) | Acorn 3D Software(K234009) | spineEOS / VEA Align(K240582) |
|---|---|---|---|
| Technological characteristics | Acorn 3D Software is a standalone modular software package. This software package includes, but is not limited to the following functions:Acorn 3D - SegmentationImage Import• Importing medical images in DICOM formatImage Processing• Processing of images with common noise-reduction filters• Editing of spatial arrangement of imagesVisualization• Viewing images and DICOM dataSegmentation• Selecting a region of interest using generic segmentation tools• Segmenting specific anatomy using dedicated semi-automatic tools• Segmenting specific vertebral anatomy using machine-learning-based fully automatic algorithms• Verifying and editing a region of interestMeasurement• Measuring on images and 3D modelsImage Export• Exporting images and 3D models to third-party packages3D Models• Calculating a digital 3D model and editing the model• Smoothing a 3D model• Importing 3D modelsTreatment Planning• Importing of third-party STLs to visualize planned interactions with anatomy as represented in DICOM imagesOther featuresUsing a collection of images and masks as a training dataset for machine-learning segmentation algorithmAcorn 3D – Alignment and MeasurementRegistration | Acorn Segmentation is a standalone modular software package. This module includes, but is not limited to the following functions:Image Import• Importing medical images in DICOM formatImage Processing• Processing of images with common noise-reduction filters• Editing of spatial arrangement of imagesVisualization• Viewing images and DICOM dataSegmentation• Selecting a region of interest using generic segmentation tools• Segmenting specific anatomy using dedicated semi-automatic tools• Segmenting specific vertebral anatomy using machine-learning-based fully automatic algorithms• Verifying and editing a region of interestMeasurement• Measuring on images and 3D modelsImage Export• Exporting images and 3D models to third-party packages3D Models• Calculating a digital 3D model and editing the model• Smoothing a 3D model• Importing 3D modelsTreatment Planning• Importing of third-party STLs to visualize planned interactions with anatomy as represented in DICOM imagesOther featuresUsing a collection of images and masks as a training dataset for machine-learning segmentation algorithm | spineEOS / VEA Align includes the following functionality:Image Import• Import of medical dataVisualization• Display of data• Switching of view orientation• Basic manipulation (zoom, panning, annotations)Measurement• Distance and angle measurements on 2D images and 3D models• Clinical Parameters: • Pelvic Tilt (PT) • Sacral Slope (SS) • Pelvic Incidence (PI) • Pelvic Obliquity (PO) • Sagittal Vertical Axis (SVA) • C7-CSL • PI-LL • T1 Pelvic Angle (TPA) • Cobb Angle • Kyphosis/Lordosis Angle • Knee Flexion/Extension Angle • Lordosis Percentage Distributions • Spondylolisthesis grade (i.e., Slippage percentage)Registration• Initial placement of anatomic landmarks on images using a machine-learning-based algorithm• 3D reconstruction model initialized by AI algorithm• Manual deformation of resulting 3D model through control points |
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| Device→Features↓ | Acorn 3D Software(K252103) | Acorn 3D Software(K234009) | spineEOS / VEA Align(K240582) |
|---|---|---|---|
| • Alignment of anatomical structures between datasetsMeasurement• Standard and generic 3D measurements of spinopelvic anatomy based on user-defined reference geometry | • Verification of deformation result by matching accurately the X-ray contoursData Export• Export of medical data | ||
| Technological characteristics | Acorn 3D Software is a standalone modular software package. This software package includes, but is not limited to the following functions:Acorn 3D - SegmentationImage Import• Importing medical images in DICOM formatImage Processing• Processing of images with common noise-reduction filters• Editing of spatial arrangement of imagesVisualization• Viewing images and DICOM dataSegmentation• Selecting a region of interest using generic segmentation tools• Segmenting specific anatomy using dedicated semi-automatic tools• Segmenting specific vertebral anatomy using machine-learning-based fully automatic algorithms• Verifying and editing a region of interestMeasurement• Measuring on images and 3D modelsImage Export• Exporting images and 3D models to third-party packages3D Models• Calculating a digital 3D model and editing the model• Smoothing a 3D model• Importing 3D modelsTreatment Planning• Importing of third-party STLs to visualize planned interactions with anatomy as represented in DICOM imagesOther featuresUsing a collection of images and masks as a training dataset for machine-learning segmentation algorithmAcorn 3D – Alignment and MeasurementRegistration | Acorn Segmentation is a standalone modular software package. This module includes, but is not limited to the following functions:Image Import• Importing medical images in DICOM formatImage Processing• Processing of images with common noise-reduction filters• Editing of spatial arrangement of imagesVisualization• Viewing images and DICOM dataSegmentation• Selecting a region of interest using generic segmentation tools• Segmenting specific anatomy using dedicated semi-automatic tools• Segmenting specific vertebral anatomy using machine-learning-based fully automatic algorithms• Verifying and editing a region of interestMeasurement• Measuring on images and 3D modelsImage Export• Exporting images and 3D models to third-party packages3D Models• Calculating a digital 3D model and editing the model• Smoothing a 3D model• Importing 3D modelsTreatment Planning• Importing of third-party STLs to visualize planned interactions with anatomy as represented in DICOM imagesOther featuresUsing a collection of images and masks as a training dataset for machine-learning segmentation algorithm | spineEOS / VEA Align includes the following functionality:Image Import• Import of medical dataVisualization• Display of data• Switching of view orientation• Basic manipulation (zoom, panning, annotations)Measurement• Distance and angle measurements on 2D images and 3D models• Clinical Parameters: • Pelvic Tilt (PT) • Sacral Slope (SS) • Pelvic Incidence (PI) • Pelvic Obliquity (PO) • Sagittal Vertical Axis (SVA) • C7-CSL • PI-LL • T1 Pelvic Angle (TPA) • Cobb Angle • Kyphosis/Lordosis Angle • Knee Flexion/Extension Angle • Lordosis Percentage Distributions • Spondylolisthesis grade (i.e., Slippage percentage)Registration• Initial placement of anatomic landmarks on images using a machine-learning-based algorithm• 3D reconstruction model initialized by AI algorithm• Manual deformation of resulting 3D model through control points• Verification of deformation result by matching accurately the X-ray contoursData Export• Export of medical data |
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| Device→Features↓ | Acorn 3D Software(K252103) | Acorn 3D Software(K234009) | spineEOS / VEA Align(K240582) |
|---|---|---|---|
| Machine-Learning Algorithms | The Acorn 3D Segmentation module automates the segmentation of particular anatomy (listed in IFU) by implementing a 3D U-Net machine learning model. Segmentation of the images is completed by generating an input image that is preprocessed (image processing methods) and then is run through an analysis (encoder) path and a synthesis (decoder) path. When the image is going through the analysis path, the model is learning by focusing on new information presented and by dynamically learning which information from the image is the most useful. The image then goes through the synthesis path in which the model recovers spatial resolution and focus on salient features that the analysis path coded. The parameters of the model were obtained through an algorithm development pipeline. | The Acorn 3D Segmentation module automates the segmentation of particular anatomy (listed in IFU) by implementing a 3D U-Net machine learning model. Segmentation of the images is completed by generating an input image that is preprocessed (image processing methods) and then is run through an analysis (encoder) path and a synthesis (decoder) path. When the image is going through the analysis path, the model is learning by focusing on new information presented and by dynamically learning which information from the image is the most useful. The image then goes through the synthesis path in which the model recovers spatial resolution and focus on salient features that the analysis path coded. The parameters of the model were obtained through an algorithm development pipeline. | N/A |
| Machine-Learning Models | Acorn 3D – Segmentation• Vertebral model (T1-T12, L1-L5)• Sacral model | Acorn Segmentation• Vertebral model (T1-T12, L1-L5) | N/A |
| Bone Model | The Acorn 3D Segmentation output can be used for the fabrication of physical replicas of the output file using additive manufacturing methods. The physical replica can be used for diagnostic purposes and/or intraoperative reference of anatomy in the field of orthopedic and musculoskeletal applications. | The Acorn Segmentation output can be used for the fabrication of physical replicas of the output file using additive manufacturing methods. The physical replica can be used for diagnostic purposes and/or intraoperative reference of anatomy in the field of orthopedic and musculoskeletal applications. | N/A |
Predetermined Change Control Plan (cleared as part of K234009)
The Acorn 3D Software uses an algorithm derived from machine learning (ML) to segment bony anatomy from CT or CTA images. Mighty Oak Medical will make future algorithm improvements under a Predetermined Change Control Plan (PCCP; cleared as part of K234009 – no changes made to the PCCP as part of K252103). In that plan, a protocol is provided to mitigate the risks of the algorithm changes leading to changes in the device's technical specifications or negatively affecting performance specifications directly associated with the indications for use of the device. Changes made under this PCCP are detailed in the table below. In accordance with the PCCP, all algorithm modifications will be trained, tuned, and locked prior to release of the software.
| Modification | Rationale |
|---|---|
| Additional implementation of Sacral model | The sacrum is important to the spinopelvic pre-surgical planning workflow; auto-segmentation of the sacrum is intended to increase the speed and accuracy of the software. |
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Machine-Learning Model Performance Testing
Acorn 3D utilizes a machine learning algorithm to assist in the segmentation of regions of interest, with a primary focus on segmenting vertebrae from the spine in DICOM images. The algorithm produces segmentations using a convolutional neural network called U-Net, which is trained on qualified ground truth data. The software contains two models: a vertebral model, trained on vertebral levels T1-T12 and L1-L5, and a sacral model, trained on the sacrum alone.
Quantitative accuracy testing of machine-learning models was performed by direct comparison of model outputs with corresponding ground-truth segmentations by DICE similarity coefficient (DSC), a well-established metric for measuring the spatial overlap of two objects.
| Model | Testing Dataset | Cases | N(Lumbar /Thoracic) | Adult /Peds | M / F | AcceptanceCriteria(Threshold DSC) | MeanDSC |
|---|---|---|---|---|---|---|---|
| Vertebral(T1-T12, L1-L5) | In-House(Mighty Oak Medical) | 35 | 450(139 / 311) | 15 / 20 | 12 / 23 | > 0.88375 | 0.9331 |
| VERSE '20 | 36 | 401(144 / 257) | 36 / 0 | 22 / 14 | 0.94451 | ||
| Sacral | In-House(Mighty Oak Medical) | 40 | 40(N/A) | 20 / 20 | 13 / 27 | > 0.96045 | 0.96630 |
Machine-Learning Testing Data Image Acquisition
The equipment and protocol to collect images for the Mighty Oak Medical Database are as follows:
- Scan Type: Helical/Spiral
- Slice Thickness: Do not exceed 1.25 mm
- Slice Spacing: Do not exceed Slice Thickness
- DFOV: Do not exceed 500 mm
- Scan Matrix: 512x512
The equipment and protocol for publicly-available VERSE '20 dataset are as follows:
Inclusion criteria:
- Patients > 30 years of age
- No history of bone metastases
CT scanners:
- Philips Brilliance 64 iCT 256 and IQon
- Philips Medical Care
- Siemens Somatom Definition AS and AS+
- Siemens Healthineers
Imaging parameters:
- Scan Type: Helical/Spiral
- Peak Tube Voltage: 120 kVP
- Slice Thickness: 0.9 – 1.0 mm
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- Tube Load: Adaptive
Machine-Learning Clinical Subgroups and Confounders
The dataset is anonymized, so available patient demographics are limited to age and gender, which were adequately represented by the data. Major factors that could confound algorithm performance include morphology (abnormal anatomy), bone quality and density, imaging quality, and the presence of orthopedic hardware. To address these, cases were limited to those that met the imaging criteria given above, and cases with hardware in the region of interest and abnormal anatomies were excluded from testing. Testing included clinical subgroups such as degenerative spinal disease, scoliosis, and DiGeorge syndrome.
Machine-Learning Ground Truth and Data Independence
Both in-house (Mighty Oak Medical) and publicly-available (VERSE '20, CTPelvic1K) datasets are produced by highly-trained experts and verified by feedback loops of expert review and manual editing and correction. Mighty Oak Medical segmentations are produced on clinical cases by operators who have undergone extensive classroom training and tests for efficacy, with an established track record of creating accurate segmentations in support of the FIREFLY Pedicle Screw Navigation Guide (K181399, K162419, and K143222).
The VERSE '20 and CTPelvic1K datasets are widely accepted as ground truth, with three levels of annotation and expert review (by medical and/or graduate students, radiology fellows, and finally a senior consultant), and being used in support of public machine-learning segmentation research.
To ensure the independence of the test data from the training data, the full training data was collected first and a k-fold was applied during training to randomly generate tuning data. Once the training-tuning was completed, an entirely new random dataset was selected from the Mighty Oak Medical database that excluded cases that were used for the training/tuning dataset. The VERSE '20 dataset was used exclusively for testing, and was not included in the training/tuning dataset. Conversely, the CTPelvic1K dataset was used exclusively in training and tuning, and was not used for testing. A summary breakdown of datasets used for training, tuning, and testing for each model is provided in the table below.
| Model | Testing Dataset | Training | Tuning | Testing |
|---|---|---|---|---|
| Vertebral(T1-T12, L1-L5) | In-House(Mighty Oak Medical) | 147 | 55 | 35 |
| VERSE '20 | 0 | 0 | 36 | |
| Total | 147 | 55 | 71 | |
| Sacral | In-House(Mighty Oak Medical) | 104 | 47 | 40 |
| CTPelvic1K | 100 | 55 | 0 | |
| Total | 204 | 102 | 40 |
Conclusion
The Acorn 3D Software's Alignment & Measurement module possesses the same intended use and technological characteristics as the predicate devices. Therefore, the Acorn 3D Alignment & Measurement module is substantially equivalent for its intended use.
N/A