Eclipse v19.0 is now available in the EU!*

Designed to support the complexity of modern radiotherapy, Eclipse treatment planning system combines advanced radiation therapy planning capabilities with connected workflows to help care teams deliver high-quality patient care with confidence.

Whether supporting treatment continuity across evolving treatment environments, enabling efficient clinical decision-making, or providing advanced planning tools for complex cases, Eclipse helps connect planning, treatment delivery, and clinical workflows within a broader integrated ecosystem.

Eclipse v19 Feature Sheet

Connection

Bringing people, systems, and workflows together

  • Connect care teams, systems, and workflows across technologies, sites, and treatment approaches
  • Support treatment continuity with the optional Backup Planner, enabling efficient plan conversion across machines, techniques, and energies
  • Maintain flexibility across current and next-generation treatment delivery systems, including Accela*

Control

Bringing people, systems, and workflows together

  • Connect care teams, systems, and workflows across technologies, sites, and treatment approaches
  • Support treatment continuity with the optional Backup Planner, enabling efficient plan conversion across machines, techniques, and energies
  • Maintain flexibility across current and next-generation treatment delivery systems, including Accela
  • Benefit from GPU-enabled optimization algorithms that help accelerate treatment plan generation
  • Tailor planning workflows with scripting and automation tools to support institutional needs

Confidence

Supporting accuracy and consistency in every plan

  • Improve confidence in dose calculation with Enhanced Leaf Modeling (ELM), supporting a more realistic representation of MLC behavior and closer alignment between planned and delivered dose, particularly for highly modulated treatments and off-axis targets1
  • Plan advanced stereotactic treatments with HyperArc high-definition radiotherapy
  • Support conformity goals in complex SBRT cases with automated optimization tools such as SBRT NTO

AI Contouring — Integrated in Eclipse

High-quality, deep learning-driven structure delineation directly within your treatment planning workflow

  • Automatically generates contours from CT and MRI images for over 200 anatomical structures — including organs-at-risk, lymph nodes, and brain metastases
  • Built on multiple clinical guidelines (RTOG, ESTRO, DAHANCA, and more) for consistent, evidence-based results
  • Seamlessly integrated within Eclipse, with no additional hardware, no separate platform, and single vendor support
  • Validated by leading institutions2,3 worldwide, with auto contouring results on par with expert physicians4

Resources

Complimenting Eclipse

Treatment Delivery

Explore the entire Digital Oncology portfolio

Ready to connect your planning strategy to what's next?

Connect with your Siemens Healthineers representative to explore how Eclipse can help your team strengthen workflow continuity, maintain clinical control, and plan with confidence across today's evolving radiotherapy environment

If you are a current customer and need product support, please visit our Customer Support page

*510(k) pending. Not available for sale in the US.

  1. Van Esch A, et al. Testing of an enhanced leaf model for improved dose calculation in a commercial treatment planning system. Med Phys. 2022 Dec;49(12):7754-7765. doi:10.1002/mp.16019. PMID: 36190516.
  2. Putz, F. Is AI-powered tumor autocontouring ready for clinical use? Evaluation of Siemens Healthineers research prototype for the autosegmentation of brain metastases. Poster presented at DEGRO; Jun 2025, Dresden, Germany. Datasets: 101 patients; 391 lesions; 1.5T MRI series T1-SPACE. University of Erlangen-Nuremberg.
  3. Tezcanli, E. Evaluation of a Deep Learning Contouring Algorithm for Target Delineation in HyperArc Radiosurgery. Webinar, Oct 2025. Datasets: 10 patients; 82 lesions. Acibadem University.
  4. Putz, F. Die OAR Turing-Test Studie: Ein verblindeter Vergleich von expertenbasierter Organ at Risk Erstellung und drei kommerziellen Autosegmentierungslösungen. Presented at DEGRO; July 2021. University Clinic Erlangen. Blinded evaluation of 50 datasets in which three physicians rated AI-generated and physician-generated contours; investigators reported OAR autosegmentations "on par with human experts."