(Elements) Spine SRS

by Brainlab AG  · Based in Germany → — Medical technology just got a whole lot easier and innovation is within reach with pre-planning software apps by Brainlab.
Neurosurgery Oncology

Not publicly disclosed
Regulatory Status Disclosed

Overview

Brainlab Elements Spine SRS is an advanced software solution designed to optimize the treatment of spinal metastases through stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT). This treatment planning system (TPS) utilizes automated volumetric modulated arc radiotherapy to provide a highly conformal dose distribution to targets, ensuring superior sparing of the spinal cord. The workflow incorporates automation at every step, including anatomical mapping, spinal curvature correction, and target definition, to ensure submillimetric accuracy and consistency. A unique algorithm compensates for variations in spinal curvature, enhancing image fusion accuracy between MR and CT images. The software employs automatic segmentation of spinal anatomy using a patented synthetic tissue model to identify and label individual spine levels for precise dose calculations. It provides tools for Gross Tumor Volume (GTV) contouring and automatically generates the Clinical Target Volume (CTV) and cropped spinal canal object based on International Spine Consortium Guidelines. Elements Spine SRS also features VMAT optimization, user-defined protocol-based planning, and Monte Carlo-based dose calculation, which is critical for accurate dose delivery, especially in regions with bone inhomogeneity. The system is designed to streamline the treatment planning process, reduce planning time and effort, and achieve superior conformity and cord dose sparing compared to traditional methods.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Automated treatment planning for spine SRS/SBRT
  • Spinal curvature correction for accurate image fusion (MR/CT)
  • Automatic target delineation (GTV, CTV) based on ISRC guidelines
  • Spine VMAT optimization for highly conformal dose distribution
  • Monte Carlo dose calculation for precision in heterogeneous tissues
  • PTV splitting for enhanced spinal cord sparing
  • Steep dose gradient optimization at target-spinal cord interface
  • AI-driven contouring solutions for over 200 structures
  • User-defined protocol-based planning to expedite treatment
  • Advanced 3D viewer for treatment envisioning

Use Cases

  • Treatment planning for spine metastases
  • Spine stereotactic radiosurgery (SRS)
  • Spine stereotactic body radiation therapy (SBRT)
  • Optimizing dose delivery for complex spine target shapes
  • Minimizing radiation dose to the spinal cord and organs at risk
  • Streamlining and standardizing radiation oncology workflows

What Physicians Need to Know

Key Capabilities
Offers patient-tailored and highly automated radiosurgery planning for spine indications, ensuring precise radiation delivery while effectively sparing organs at risk. It features a patented integrated 4u03c0 algorithm for optimizing beam trajectories and includes a dedicated spine VMAT optimization with arc splitting to achieve steep dose gradients and superior spinal cord sparing. The system provides streamlined contouring with semiautomatic Clinical Target Volume (CTV) generation based on Gross Tumor Volume (GTV) and International Spine Consortium guidelines (Elements SmartBrush Spine module). It also incorporates a Monte Carlo based dose calculation engine for accuracy. AI-driven contouring solutions are available for rapid and reliable delineation of numerous structures, and it can generate automated, AI-driven 3D patient-specific spine models for surgical planning.
Clinical Utility
Facilitates quick and efficient treatment planning and delivery for spinal radiosurgery (SRS) and stereotactic body radiotherapy (SBRT) without compromising treatment quality. It significantly improves the accuracy of image fusion by accounting for spinal curvature variations and achieves superior conformity and spinal cord dose sparing compared to other planning systems. The software reduces planning time and planner involvement, particularly with newer versions.
Integration Options
Designed to bridge various clinical departments, including neurosurgery, spine surgery, orthopedics, and radiation oncology. It offers seamless integration with other Brainlab platforms like Curveu2122 Image Guided Surgery and Buzzu00ae Digital O.R. The system supports co-registration between MR and CT images in complex regions and promotes vendor-independent workflows for instruments and imaging modalities, enhancing flexibility in the operating room.
Compliance Status
Received FDA clearance in September 2017 and CE approval in May 2017, making it ready for clinical use in the United States and worldwide. It is also required to comply with the Unique Device Identification System (UDI) rule.
Pricing Model
Specific pricing details are not publicly available. Brainlab offers flexible business models to allow facilities to access Elements according to their needs.
User Experience
Features a highly automated planning process designed for consistency and efficiency, capable of generating radiosurgery plans rapidly. It offers intuitive administration of its feature-rich and scalable software, with multi-platform flexibility for planning and review, contributing to a positive customer experience.
Support Quality
Brainlab emphasizes timely access to Elements and corresponding technical support, scalable to the evolving needs of any department.
Implementation Complexity
Requires commissioning and clinical implementation, with institutions sharing their experiences regarding setup and evaluation. It involves evaluating dosimetric differences between calculation models and setting up user-predefined templates for arc configurations.
Evidence Base
Supported by clinical use worldwide following regulatory clearances. Treatment planning studies have demonstrated its dosimetric advantages, including superior conformity and spinal cord sparing, compared to other planning systems. Studies also validate the accuracy of its semiautomatic CTV generation against expert manual contouring. Brainlab engages in research agreements with clinical sites to improve outcomes and conducts studies to assure data validity.
Physician Tip

Leverage the automated contouring and planning features to significantly reduce planning time and enhance consistency, particularly for complex spine cases. Prioritize the tool's advanced spinal cord sparing capabilities and steep dose gradients, which are crucial for effective spine SRS. Utilize the co-registration of MR and CT images for a comprehensive anatomical understanding. Consider the robust evidence base supporting its dosimetric advantages and accuracy in CTV generation. Explore its integration with other Brainlab platforms for a streamlined workflow from initial planning to treatment delivery.

Brainlab Elements Spine SRS is designed for seamless integration within the broader Brainlab ecosystem, fostering connections across clinical subspecialties such as neurosurgery, spine surgery, orthopedics, and radiation oncology. It integrates with image-guided surgery platforms (e.g., Curveu2122) and digital OR solutions (e.g., Buzzu00ae). The system supports co-registration of MR and CT images for complex anatomical regions and offers vendor-independent workflows for various imaging modalities and instruments, providing operational flexibility.

Details

Category Oncology AI, Surgical AI
Pricing Not publicly disclosed — Not publicly disclosed
DeploymentOn-premise workstation with cloud-based data sharing capabilities (Brainlab Cloud Services).
Compliance
BAA Available Yes AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Yes AI-estimated

Elements Spine SRS 4.5 is part of the 'RT Elements (4.5)' suite, which received FDA 510(k) clearance under K250440 with a decision date of April 13, 2026. Earlier versions of Elements Spine SRS received FDA clearance in September 2017. The device is intended for radiation treatment planning for stereotactic, conformal, computer-planned, Linac-based radiation treatment of cranial, head and neck, and extracranial lesions, including spine metastases.

Integrations
EHR Not specified
Specialties Neurosurgery, Oncology

What the Web Says

Elements Spine SRS by Brainlab is an advanced software solution designed for stereotactic body radiotherapy (SBRT) treatment of spinal metastases, offering highly automated planning and precise dose delivery. It aims to enhance accuracy, consistency, and efficiency in target volume definition and treatment planning, particularly in complex spinal regions.

Overall: Positive

Strengths

  • Highly automated planning process, including anatomical mapping, curvature adjustments, and target identification.
  • Achieves superior conformity and spinal cord sparing compared to traditional clinical plans.
  • Semiautomatic CTV generation shows good accuracy, comparable to manual contouring by experts.
  • Dedicated spine VMAT algorithm designed for steep dose gradients at the target and spinal cord interface.
  • Reduces treatment planning time and enhances overall patient outcomes in spinal cancer management.
  • Features like PTV splitting can further improve spinal cord sparing.

Limitations

  • May result in higher numbers of monitor units and modulation factors in some cases, particularly with PTV splitting.
  • Increased calculation time can occur when PTV splitting is utilized.
  • Semiautomatic contouring had a Dice similarity coefficient (DSC) less than 0.80 in a few cases, indicating less than 'very good' overlap with expert manual contouring.

Based on reviews from: PMC, PubMed, Frontiers, Slashdot, Novalis Circle, SourceForge, G2

Last updated: 2026-04-18

Ratings & Reviews

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Videos

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Frequently Asked Questions

AI in systems like Brainlab Elements Spine SRS significantly improves efficiency and precision by automating tasks such as anatomical mapping, spinal curvature adjustments, and target identification. It facilitates semi-automatic segmentation of spinal anatomy and tumor volumes, leading to highly conformal dose distributions and superior sparing of the spinal cord compared to manual methods.
AI in healthcare is subject to stringent oversight, including FDA approval in the US and the EU AI Act in Europe, especially for high-risk systems like those used in radiation oncology. Compliance requires robust data governance, risk management, detailed documentation, transparency regarding AI capabilities and limitations, and ensuring human oversight in decision-making.
The primary alternative is traditional manual treatment planning, which relies entirely on human expertise for contouring and dose optimization. While manual planning offers direct physician control and interpretation, it is significantly more time-consuming and can lead to variability in plan quality compared to the efficiency and standardization offered by AI.
The cost structure typically involves initial capital investment for software licenses, necessary hardware, and infrastructure development, which can be substantial. Ongoing costs include maintenance, service, and potentially per-plan fees, with some AI technologies for radiotherapy planning ranging from u00a34 to u00a350 per plan.
Current limitations include the 'black box' nature of some AI models, which can hinder interpretability, and challenges with generalizability due to a lack of external validation across diverse patient populations. Potential risks involve algorithmic bias, reliance on data quality, and the critical need for continuous human oversight to prevent errors and ensure patient safety.
AI models are validated through rigorous testing against established clinical standards and often compared to expert manual contouring, using metrics like the Dice similarity coefficient. Concerns exist regarding the quality and quantity of training data, potential algorithmic biases that could affect diverse patient outcomes, and the generalizability of models across different clinical settings and patient populations without extensive external validation.
AI acts as an assistant, significantly streamlining and standardizing complex planning tasks, thereby allowing the radiation oncologist and team to focus on refining plans and managing complex cases. While AI enhances efficiency and precision, the ultimate responsibility for reviewing, editing, and approving treatment plans, as well as ensuring patient safety and ethical considerations, remains with the human clinical team.

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Suggest an Edit → | Last Verified: 2026-04-17 | First Added: 2026-04-17
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