RayStation 11B
by RaySearch Laboratories AB (publ)
· Based in Sweden →
— Advanced Treatment Planning for Personalized Radiation Therapy
Contact vendor for pricing details.
Regulatory Status Disclosed
Overview
RayStation 11B is an advanced treatment planning system developed by RaySearch Laboratories AB (publ) for radiation therapy and medical oncology. It is designed to improve cancer treatment through innovative software solutions. The system offers comprehensive features for adaptive workflows, brachytherapy, and various forms of external beam radiation therapy, including photons, electrons, protons, carbon ions, and helium ions.
Key advancements in RayStation 11B include improved dose calculation accuracy on daily images for photon therapy, utilizing advanced algorithms to create synthetic CTs from daily cone beam CTs (CBCTs). It also provides the capability to convert physical doses to biological equivalent doses (EQD2) and supports the evaluation of Linear Energy Transfer (LET) for proton and light ion plans, a pioneering feature in the market. The system integrates machine learning functionalities for automated treatment planning and organ segmentation, aiming to enhance efficiency and consistency in clinical practice.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Improved dose calculation accuracy on daily images for photon therapy
- Advanced algorithms for synthetic CT creation from CBCTs
- Conversion of physical dose to biological equivalent dose (EQD2)
- Evaluation of Linear Energy Transfer (LET) for proton and light ion plans
- GPU-based Monte Carlo dose engine for fast proton dose computation
- Robust optimization and evaluation
- Machine learning autoplanning with robustness
- 4D-optimization
- Multi-criteria optimization
- Fully integrated adaptive planning
- Deep Learning Segmentation for automated organ segmentation
Use Cases
- Treatment planning for various radiation therapy modalities (photon, electron, proton, ion, brachytherapy)
- Adaptive radiation therapy workflows for precise treatment adjustments
- Planning and evaluation of combined treatments with different fractionation schemes
- Automated treatment planning to enhance efficiency and consistency
- Automated organ segmentation for streamlined contouring
- Beam commissioning and CT commissioning activities
What Physicians Need to Know
Key Capabilities
RayStation 11B offers advanced treatment planning with improved dose calculation accuracy on daily images for photon therapy through synthetic CTs. It supports conversion to biological equivalent dose (EQD2) for combined modality treatments and is the first TPS to evaluate Linear Energy Transfer (LET) for proton and light ion plans. The system integrates machine learning for robust autoplanning and deep learning for efficient segmentation (e.g., Head and Neck CT model), alongside multi-criteria optimization, 4D adaptive radiation therapy, and a fast GPU-based Monte Carlo dose engine for proton PBS plans. It also includes an automated breast planning module and improved image registration workflows.
Clinical Utility
This tool enhances adaptive radiation therapy workflows by providing more accurate dose calculations from daily CBCTs, enabling better planning and evaluation of combined treatments. The LET evaluation for particle therapy offers crucial insights into the biological effect of radiation, aiding in tumor control and normal tissue sparing. Machine learning features contribute to more efficient and personalized treatment plan generation, streamlining clinical processes, especially when integrated with RayCare.
Integration Options
RayStation 11B seamlessly integrates with RayCareu00ae oncology information system and supports a wide array of treatment machines, including CyberKnife, TomoTherapy, Elekta Flexitron afterloaders, and Vero LINACs. It boasts robust DICOM conformance for sending and receiving various imaging and radiotherapy data, and offers remote access capabilities via Citrix Virtual Apps & Desktops.
Compliance Status
The system complies with Medical Device Regulation (MDR) 2017/745 in the EU. In the United States and Canada, machine learning models for treatment planning require clearance from the FDA and Health Canada, respectively, prior to clinical use. Certain advanced features like carbon/helium ion planning and BNCT may not be available in all regions due to regulatory restrictions.
Pricing Model
Specific pricing details are not publicly disclosed, but functionality is controlled by licenses. RayStation 11B features updated licensing for machine learning planning, with specific licenses like RayDeepPlanningPhotons and RayDeepPlanningProtons replacing older, technique-specific ones. Deep learning segmentation is included for free for all RayStation customers in versions 11B and later.
User Experience
RayStation 11B emphasizes a patient-centric design and user experience, with improvements such as enhanced image registration workflows, persistent ROI visualization settings, and interactive editing of couch angles. The machine learning planning frameworks have been improved, and deep learning segmentation is designed to be user-friendly.
Support Quality
RaySearch Laboratories provides direct manufacturer contact information, including telephone and email support. Comprehensive documentation, such as Instructions for Use and Release Notes, is available upon request. Upgrades for clinical systems are recommended to be performed by RaySearch authorized service personnel.
Implementation Complexity
Implementation involves adherence to system environment guidelines for hardware and software, supporting various deployment options (e.g., client at desk, virtual desktop, VM hosted). The upgrade process includes evaluation and transition phases with options for batch or parallel patient upgrades. Specific hardware, like NVIDIA GPUs with ECC RAM, and particular SQL Server versions are required, and an Installation Test Specification must be run for clinical verification.
Evidence Base
RayStation's algorithms are supported by an evidence base including peer-reviewed algorithms for plan optimization and dose calculation. Its Monte Carlo dose engine for proton PBS has been rapidly commissioned clinically due to its speed and accuracy. Synthetic CT algorithms have demonstrated good dosimetric agreement and rapid online evaluation capabilities. Validation studies for various dose engines and treatment machines have been performed, and RaySearch collaborates with institutions like Princess Margaret Cancer Centre on machine learning models.
Physician Tip
Leverage RayStation 11B's advanced adaptive therapy capabilities, especially the synthetic CT generation from daily CBCTs, for more precise dose delivery and timely replanning. Utilize the EQD2 conversion for comprehensive evaluation of combined modality treatments. Explore the deep learning segmentation and machine learning autoplanning features to streamline contouring and plan generation, freeing up time for complex cases and patient interaction. Be mindful of regional regulatory clearances for specific advanced features, particularly concerning machine learning models and particle therapy options.
RayStation 11B's strong DICOM conformance ensures broad compatibility with existing imaging and radiotherapy systems. Its tight integration with RayCare facilitates a unified oncology workflow, enhancing data exchange and coordination. For optimal performance and to access advanced features like GPU-accelerated dose calculations, ensure your IT infrastructure meets the specified hardware and software requirements, including appropriate GPU and SQL Server configurations. Regular consultation with RaySearch support is recommended for seamless integration and upgrades.
Details
| Category | Oncology AI, Radiology & Imaging AI |
| Pricing | Contact vendor for pricing details. |
| Deployment | On-premise, operating within a Microsoft Windows environment with Microsoft SQL Server hosting databases. |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated RayStation 11B received 510(k) premarket notification clearance (K220141) from the U.S. FDA on April 15, 2022. It is classified as a Medical Charged-Particle Radiation Therapy System (Product Code MUJ). |
| Integrations | |
| EHR | Not specified |
| Specialties | Oncology |
What the Web Says
RayStation 11B is an advanced treatment planning system for radiation therapy, offering significant improvements in dose calculation accuracy, particularly for photon therapy using daily cone beam CTs (CBCTs). It introduces new algorithms for creating synthetic CTs and supports the conversion of physical dose to biological equivalent dose (EQD2), crucial for combined treatment modalities like brachytherapy and conventional photon therapy. The system also stands out as the first to support the evaluation of linear energy transfer (LET) for proton and light ion plans, providing valuable insights into the biological effect of radiation.
Overall: PositiveStrengths
- Improved dose calculation accuracy on daily images for photon therapy using new synthetic CT algorithms.
- Ability to convert physical dose to biological equivalent dose (EQD2) for enhanced planning and evaluation of combined treatments.
- First treatment planning system to support clinical evaluation of Linear Energy Transfer (LET) for proton and light ion plans.
- Includes a versatile tool for fine-tuning treatment plan optimization, leading to improved plan quality.
- Enhanced integration with the oncology information system RayCare.
- Offers a user-friendly graphical interface and scripting capabilities (IronPython) for flexibility and automation.
Limitations
- Potential for slower GPU computations on Windows Server 2016 with GPUs in WDDM mode.
- Auto-recovery feature does not handle all types of crashes and may show error messages.
- Some functionality can be slow or cause crashes when using large image sets (>2GB), such as Smart brush/Smart contour and certain deformable registrations.
- Plan total dose is not available for plans with multiple beam sets that have different planning image sets, limiting plan approval, report generation, and adaptive replanning.
- Slight inconsistencies in dose display in patient views.
- Importing an approved plan can automatically approve existing unapproved ROIs.
Based on reviews from: DOTmed, RaySearch Laboratories, AuntMinnie, Reddit
Last updated: 2026-07-20
Ratings & Reviews
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Press & Coverage
RaySearch Laboratories
RayStation 11B brings new features for adaptive workflows, brachytherapy, and radiation therapy with ions
RaySearch Laboratories launched RayStation 11B, featuring improved dose calculation accuracy on daily images for photon therapy, new algorithms for synthetic CTs, and support for evaluating linear energy transfer (LET) for proton and light ion plans.
2021-12
AuntMinnie.com
RaySearch launches new RayStation treatment planning software - AuntMinnie
RaySearch Laboratories released RayStation 11B, an upgraded version of its treatment planning software, which includes improved dose calculation accuracy using daily conebeam CT images and the ability to convert physical dose estimates to biological equivalent dose EQD2.
2021-12
Imaging Technology News
Latest innovations from RayStation, RayIntelligence and RayCare to be presented at ESTRO 2022 | Imaging Technology News
RaySearch Laboratories showcased RayStation 11B at ESTRO 2022, highlighting features such as advanced algorithms for synthetic CTs, EQD2 dose conversion, and LET evaluation for ion plans, along with improvements in machine learning and integration with RayCare.
2022-05
FDA
Class 2 Device Recall RayStation 11B - accessdata.fda.gov
The FDA issued a Class 2 Device Recall for RayStation 11B due to two issues related to the display of Linear Energy Transfer (LET), where the display might be misleading or out of sync with the selected beam.
2022-06
RaySearch Laboratories
SYNTHETIC CT GENERATION IN RAYSTATION FOR ENHANCED WORKFLOWS IN ADAPTIVE RADIOTHERAPY - RaySearch Laboratories
This white paper details the two advanced algorithms introduced in RayStation 11B that create synthetic CTs from daily CBCTs, enabling more accurate dose computation and strengthening adaptive replanning workflows in radiation therapy.
2022-10
Acta Oncologica (via Taylor & Francis Online)
Extensive clinical testing of Deep Learning Segmentation models for thorax and breast cancer radiotherapy planning - Taylor & Francis
A study published in Acta Oncologica tested the performance of Deep Learning Segmentation models, RSL Breast CT and RSL Thorax-Abdomen CT, available in RayStation 11B SP2 for CT images in thorax and breast cancer radiotherapy planning.
2023-10
Journal of Radiation Research (via PMC)
Dosimetric comparison of robust angles in carbon-ion radiation therapy for prostate cancer
This peer-reviewed article compares RBE-weighted dose and LET values in carbon-ion radiation therapy for prostate cancer using different beam angle configurations in RayStation 11B, including setup uncertainties with robust optimization.
2023-02
Medical Sciences (via MJS Publishing)
Robust optimization of the Gross Tumor Volume compared to conventional Planning Target Volume-based planning in photon Stereotactic Body Radiation Therapy of lung tumors - MJS Publishing
A study utilized RayStation 11B for target delineation and treatment planning in photon Stereotactic Body Radiation Therapy (SBRT) of lung tumors, comparing robust optimization of the Gross Tumor Volume to conventional Planning Target Volume-based planning.
2024-06
Videos
Product demos, reviews, and walkthroughs for RayStation 11B.
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Frequently Asked Questions
RayStation 11B incorporates machine learning for deep learning segmentation of structures and deep learning-based dose prediction, which aids in automated treatment plan generation. This allows for rapid creation of clinically robust plans and helps unify planning techniques, potentially improving plan quality and efficiency.
RayStation 11B complies with Medical Device Regulation (MDR) 2017/745. In the United States, machine learning models for treatment planning must be cleared by the FDA prior to clinical use, and training machine learning segmentation models using multiple image sets is not allowed. Similarly, in Canada, Health Canada clearance is required for machine learning models, and user training of these models is not available.
Yes, there are regional limitations. For instance, in the United States and Canada, certain advanced features like carbon and helium ion treatment planning are not available due to regulatory reasons. Additionally, in Canada, deep learning segmentation is limited to Computed Tomography imaging, and user training of machine learning planning models is not available.
Key alternatives to RayStation 11B in the treatment planning system market include Varian's Eclipse, which is a direct competitor, and oncology information systems like Varian's ARIA and Elekta's Mosaiq, which have overlapping functionalities in treatment planning and workflow management. Specialized AI tools like MVision AI also offer automated contouring capabilities that integrate with treatment planning workflows.
While specific details on AI data privacy are not extensively detailed in public documents, RayStation operates within a Microsoft Windows environment with Microsoft SQL Server hosting patient information in separate databases. The system also mentions FIPS compatibility, which relates to federal information processing standards for security.
RayStation 11B's machine learning capabilities, such as automated planning and segmentation, aim to significantly reduce the time spent on repetitive tasks, allowing physicians more time for patient consultations and complex cases. This can lead to faster turnaround times for plans, improved plan quality, and greater harmonization across planning techniques.
Specific pricing for RayStation 11B and its AI modules is not publicly disclosed, as is common for specialized medical software. Interested clinics and physicians typically need to contact RaySearch Laboratories directly for detailed quotations and licensing information. Licensing for machine learning planning has been updated to specific licenses for photons and protons.
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| Last Verified: 2026-04-20 | First Added: 2026-04-20