Spine Planning (2.0)
Overview
Elements Spine Planning (2.0) is an advanced AI-powered software developed by Brainlab AG, designed for comprehensive pre- and intraoperative planning of open and minimally invasive spinal procedures. It leverages intelligent segmentation algorithms and a Convolutional Neural Network (CNN) to automate and enhance various aspects of surgical planning. The tool facilitates automatic identification, segmentation, and labeling of vertebrae from the cervical spine to the sacrum in 2D and 3D imaging datasets (CT, Cone Beam CT, MR, X-ray). Surgeons can benefit from automated sagittal balance analysis, real-time spinopelvic measurement updates, and personalized patient avatars for accurate alignment correction. The software also provides proposals for screw and rod implants, and allows for visualization of rods in life size to mitigate scaling issues during bending. Elements Spine Planning integrates seamlessly with PACS for immediate access to patient datasets and can be used in conjunction with spinal navigation software during surgery. It supports efficient alignment correction, screw placement, and accurate measurements, contributing to improved surgical outcomes across various complex spine cases.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI/ML-powered automated vertebral labeling (cervical to sacral)
- Automated sagittal balance analysis and spinopelvic measurements
- Patient-specific spine avatar for personalized planning and alignment correction
- Pre- and intraoperative planning for screw and rod implants
- Life-size rod visualization for pre-planning rod bending
- Compatibility with 2D (X-ray) and 3D (CT, Cone Beam CT, MR) imaging data
- Seamless PACS integration for patient dataset access
- Integration with spinal navigation systems for intraoperative use
- Support for deformity, degenerative, trauma, and tumor cases
- Mixed Reality Viewer compatibility for immersive 3D visualization and patient education
Use Cases
- Preoperative surgical planning for spinal procedures
- Intraoperative guidance and plan adjustments during spine surgery
- Planning for complex spinal deformity correction
- Preparation for degenerative, trauma, and tumor spine cases
- Spine Stereotactic Radiosurgery (SRS) and Stereotactic Body Radiation Therapy (SBRT) planning
- Patient education and informed consent using 3D visualizations
What Physicians Need to Know
Leverage the automated vertebral labeling and screw proposal features to streamline preoperative planning, but always review and manually refine as needed, especially in cases with altered anatomy. Utilize the multi-modality imaging support, including CT, MRI, X-ray, and BoneMRI, to gain comprehensive anatomical insights. Take advantage of the 3D patient-specific spine model and surgical simulation capabilities to visualize complex cases, optimize alignment, and enhance patient education and informed consent. The system's ability to account for spinal flexibility between supine pre-op and prone intra-op imaging is crucial for maintaining planning accuracy in the OR.
Brainlab Spine Planning (2.0) offers robust integration with existing hospital infrastructure through seamless DICOM and PACS support. It is part of an 'open platform' and 'data-driven ecosystem,' designed to integrate fluidly with Brainlab's navigation systems, robotics, mobile imaging solutions, and mixed reality viewers (e.g., Mixed Reality Viewer for 3D visualization). This interoperability extends to supporting various pre-calibrated and third-party instruments, fostering a comprehensive and efficient digital spine surgery workflow.
Details
| Category | Radiology & Imaging AI, Surgical AI |
| Pricing | Contact for pricing — Not specified; prices may vary by country. |
| Deployment | On-premise (integrated with hospital systems); Hybrid (software with cloud components for data transfer/reconstruction, e.g., BoneMRI integration). |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated Spine Planning 2.0 received FDA 510(k) clearance (K223553) on August 2, 2023. It is classified as a Class II Stereotaxic Instrument (21 CFR 882.4560, Product Code OLO, LLZ). The device is intended for pre- and intraoperative planning of open and minimally invasive spinal procedures, displaying digital patient images and allowing measurement and planning of spinal implants like screws and rods. |
| Integrations | |
| EHR | Not specified |
| Specialties | Neurosurgery, Orthopedics |
What the Web Says
Brainlab's Spine Planning (2.0) is an AI-powered software designed for comprehensive pre- and intraoperative planning of spinal procedures, including open and minimally invasive surgeries. It utilizes patient-specific avatars, automated vertebral labeling, and sagittal balance analysis to enhance precision and personalize surgical planning. The software integrates with spinal navigation systems and supports various imaging modalities, aiming to streamline workflows and improve surgical outcomes.
Overall: PositiveStrengths
- AI/ML for personalized pre- and intraoperative surgical planning, including patient-specific avatars and sagittal balance analysis.
- Seamless integration with spinal navigation systems and mixed reality systems for complex procedures.
- Automated vertebral labeling and spinopelvic measurements from cervical to sacral spine.
- Supports various imaging types including 2D X-ray, 3D CT, Cone Beam CT, and MR.
- Intuitive interface designed to reduce preparation time and facilitate efficient review.
- Comprehensive support and documentation ecosystem, including a dedicated Service & Support website, education and training programs, and online campus.
Limitations
- Lack of transparent pricing structure, requiring direct vendor engagement to assess value.
- May involve a more significant learning process for surgeons due to its comprehensive features.
- Specific performance metrics for AI capabilities are not detailed in initial descriptions.
- Atlas-based screw planning in a related Brainlab app showed significantly greater deviations from manual reference compared to deep-learning-based tools.
Based on reviews from: Vertex AI Search, accessdata.fda.gov, 510k Monitor, OUCI, Brainlab, Innolitics
Last updated: 2026-07-18
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