Siemens Healthineers at ESTRO 2020
See the future of RT simulation

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Siemens Healthineers at ESTRO 2020
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Coronavirus - Postponement ESTRO 2020

ESTRO 2020 is postponed to July 31 - August 4, 2020

The European Society for Radiotherapy and Oncology announced to postpone ESTRO 2020 to July 31 - August 4, 2020 given the current development of the Coronavirus.

We fully support this decision not to expose people to the risks posed by large gatherings at the moment. We continue to see the ESTRO as an important event and are already looking forward to our participation in July/August.

Keep up to date on the latest information for the upcoming ESTRO congress in July.
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ESTRO 2020 - Radiation Oncology Annual Meeting

July 31 - August 4, 2020

Vienna, Austria

We at Siemens Healthineers push the boundaries of RT simulation in several directions. There is more than one good reason to join us at the 39th ESTRO annual meeting of the European society for Radiotherapy and Oncology this year. This year, we will open the door to the future of RT simulation. Discover our comprehensive imaging portfolio and exciting new AI powered solutions at our booth.

Looking forward to meeting you at ESTRO 2020 in Vienna!


Modern radiotherapy planning demands images that provide reliable information about the tumor and surrounding organs. Yet for years now, the process involved in acquiring this information has been time-consuming and prone to errors. A leap forward in CT simulation is long overdue.

But now things are changing.

We are introducing two brand-new solutions that redefine what a CT simulator should be

We’ve transformed CT technology to create meaningful, large-bore RT imaging solutions that unlock key innovations for your field. And by integrating dedicated RT hardware and AI-supported software, they come ready-equipped to enable you to fight cancer on a new level.

Our new solutions for CT simulation transform care delivery. Every single step is truly tailored to helping you achieve the ideal starting point for optimal RT planning and better outcomes.

Molecular Imaging

The time is now for PET in RT - with Biograph mCT Sim edition.

The intelligent molecular RT simulator
PET/CT utilization in RT treatment planning continues to see steady growth. The overall utilization of PET-based imaging has more than tripled since 2003.1 Our new Biograph™ mCT Sim edition package sets the standard in PET/CT for RT planning. Featuring a large bore, this RT-dedicated solution has access to intelligent imaging applications to make standardized protocols and personalized scans possible. Complex procedures, such as PET motion-free imaging can be transformed to an easy click of a button, and 4D CT workflow can be streamlined by automatically setting optimal scan parameters based on the patient's breathing cycle. Image quality can be optimized for every patient by eliminating the need for tube-dependent calibration in the treatment planning system.2 Biograph mCT Sim edition brings you one comprehensive solution for PET/CT in radiation therapy - driving the right planning for the right treatment.

AI Solutions in Radiotherapy

Leveraging AI and Deep Learning for organs at risk contouring

Organs at risk contouring creates a substantial amount of effort and is considered a major source of variability ​in RT planning.

Yet, modern treatment techniques rely on ​consistent OAR contours as a starting point and time spent on OAR contouring keeps staff from focusing on clinical tasks like devising an optimal treatment plan.

Experience how Siemens Healthineers’ deep learning and cloud technology can help increase efficiency and consistency in organs at risk contouring. Get ready to meet your AI companion.

Learn more about AI Rad Companion

1IMV Radiation Therapy Market Summary Report, September, 2014. Page 138.

2As shown by measurements with a Gammex 467 Tissue Characterization Phantom comparing standard reconstruction (kernel D30) and DirectDensity reconstruction (kernel E30). HU value to relative electron density conversion for the standard reconstruction was based on a two-linear-equations approach with individual calibration for each tube voltage. For DirectDensity images a single tube-voltage-independent linear conversion was used.