Planificación de tratamiento para el sistema ProBeam

Planificación rápida y precisa para lograr una atención avanzada del cáncer

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Sistema de planificación del tratamiento Eclipse™

Al combinar un algoritmo de cálculo de dosis de protones Monte Carlo preciso, un contorno automatizado y funciones de planificación sólidas, Eclipse simplifica el proceso de planificación sin sacrificar la calidad del plan.
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Planificación basada en el conocimiento RapidPlan™

El aprendizaje automático permite a los médicos crear planes de mayor calidad en una fracción del tiempo.
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Terapia de protones adaptativa que integra el software Velocity™

Permite determinar cuándo los tratamientos requieren adaptación proporcionando información diaria sobre la dosis y la acumulación de dosis.

Machine learning
Human intelligence

Eclipse treatment planning system

When machine learning, human intelligence, and patient data unite to build optimal treatment plans. By integrating our ProBeam system knowledge, your clinical expertise, and big data, we’re advancing treatment planning—a consistent, data-driven, easy-to-implement way to create optimal treatment plans.

RapidPlan PT is the first clinical application of machine learning in proton therapy.
Robust Optimization gives you confidence for range and patient setup uncertainties.
Dual Energy CT for planning improves range uncertainty and reduce margins for healthy tissue sparing.
GPU Acuros PT offers increased accuracy and efficiency with a true GPU-accelerated Monte Carlo algorithm.
CTV-based robust planning for all treatment techniques.
Eclipse is a unified platform, harmonizing the planning process for all the planning modalities.

RapidPlan knowledge-based planning

Machine learning

The power of RapidPlan PT is the innovative software that leverages existing clinical knowledge combined with machine learning to create quality plans, quickly and consistently. By building and sharing models based on previously treated patients, RapidPlan PT can allow clinics to reduce variability in treatment planning to achieve greater consistency, efficiency, and quality in patient care.

High quality plans in a fraction of the time

Knowledge-guided decision support

In the first study of its kind, researchers from VU University Medical Center (VUMC), now part of Amsterdam University Medical Centers, were able to build a decision support tool using RapidPlan. They were able to automate the creation of a proton and photon plan in order to accurately predict the right treatment for each patient.

This is the first investigation which demonstrates the feasibility of patient selection for proton therapy based solely on patient-specific knowledge-based predictions of proton and photon plan dosimetry without necessitating actual plan creation.
A. Delaney et. al

Adaptive proton therapy integrating Velocity software

Multi-Modality Image Registration
Quick and easy to use rigid and deformable registration tools for CT, CBCT, MRI, PET, SPECT, AND RT images.

Share data easily
Sync with ARIA OIS and Eclipse treatment planning with one click. Scripting allows for automation of dose calculation and accumulation between Eclipse and Velocity

Map and model dose changes over time
Track patient dose information from different vendors at different times to sum total dose across tumors and healthy tissue.