New concept of ESTRO 2020: Virtual Satellite Symposia
Given the current situation, we will not have an in-person congress this summer. This does not mean we will not show you our new exciting AI-powered solutions. We invite you to join our two virtual satellite symposia hosted by ESTRO, where we will open the door to the future of RT simulation:
June 18, 2020 at 4.00 pm CET: See how we set the standard for PET/CT in RT and how our new AI solutions can help increase efficiency
July 1, 2020 at 4.00 pm CET: Learn about our new SOMATOM CT simulators and get first-hand experiences from the University Hospital of Erlangen
The future of PET/CT simulation and AI-powered solutions
Did you miss the live session?
In this virtual symposium we will introduce our latest contributions for intelligent imaging in PET/CT for RT. Highlights include:
- Introduction of our new PET/CT solution for RT
- Launch of our cloud-based AI organs at risk contouring solution: Learn how you can potentially save time and improve consistency in OAR contouring
- Guest speaker: Dr. Patrick Kupelian, VP of Medical Affairs at Varian Medical Systems, discussing the need of PET/CT in RT
- Expert speaker: Bruce Spottiswoode, PhD, Director of Clinical Applications Research at Siemens Healthineers, sharing more about AI and the future of PET/CT
- Only for live participants: Free trial of our new cloud-based OAR autocontouring
Patrick Kupelian, MD, FASTRO
Patrick Kupelian, MD is currently the VP of Medical Affairs at Varian Medical Systems. His responsibilities extend to various aspects including regulatory, feedback on product development, research and education, and cross-functional clinical support on all of our medical affairs initiatives. Prior to joining Varian, Dr. Kupelian served as the Vice-Chair of Clinical Operations and Clinical Research at UCLA where he still has an appointment as Professor of Radiation Oncology. His academic career has included contributions in prostate radiotherapy (hypofractionation and SBRT), and investigation of varied advanced image guided radiotherapy techniques. Dr. Kupelian completed his residency training in radiation oncology at the M.D. Anderson Cancer Center in Houston and fellowship at the Cleveland Clinic Foundation. He has authored more than 250 research papers, multiple review papers and book chapters. He is board certified in Radiation Oncology. He is a Fellow of the American Society of Therapeutic Radiation and Oncology.
Bruce Spottiswoode holds a B.S. in Electrical Engineering and a Ph.D. in Biomedical Engineering. He started his career in the mining industry developing remote sensing electronics before entering the field of medical imaging focusing on multi-spectral X-ray technology. For five years, he served as director of the Cape Universities Brain Imaging Centre primarily conducting neuro MR research. In 2012, Bruce joined Siemens Healthineers as an MR scientist where he managed research collaborations, implemented product features, and developed prototypes for cardiovascular MR. He transitioned to Siemens Healthineers’ molecular imaging business in 2016 as a senior staff scientist in the clinical applications research team, focusing on oncology and intelligent workflows, and now serves as director for clinical applications research. He is inventor of seven issued US patents, authored two book chapters, and contributed to 60 journal papers.
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.
Get a free trial of AI-Rad Companion Organs RT
See the results with your own cases and get a free trial version of our new cloud-based OAR autocontouring solution.
Simply reach out to us via the contact form below and we will get back to you with a free trial version.
The future of CT simulation
Did you miss the live session?
In this virtual satellite symposium we are sharing our solutions for the future of CT simulation by introducing two brand-new CT simulators. Highlights include:
- Introducing the SOMATOM go.Sim and SOMATOM go.Open Pro
- First-hand experiences from Prof. Dr. Bert and Prof. Dr. Ott, University Hospital of Erlangen, Germany
- Expert talks from Siemens Healthineers: Dr. Nilesh Mistry on AI-based autocontouring with DirectORGANS and Dr. Christian Hofmann on intelligent 4D CT scanning with Direct i4D
- Live Q&A with our speakers and experts
Discover our intelligent technologies.
Prof. Dr. Christoph Bert
Prof. Dr. Christoph Bert studied physics at the Friedrich- Alexander University Erlangen-Nürnberg (FAU) and at the Imperial College in London. He received the PhD from Technische Universität (TU) Darmstadt in 2006, for a dissertation on 4D treatment planning for scanned ion beam therapy. This topic was also the focus of his Postdoc at GSI and briefly at the National Institute of Radiological Science (NIRS) in Chiba, Japan. In 2009, Dr. Bert obtained the postdoctoral lecture qualification (Habilitation) in medical physics at the Ruprecht-Karls-Universität of Heidelberg. Since 2012, Dr. Bert is Professor of Medical Radiation Physics at the FAU Erlangen-Nürnberg, and head of medical physics at the Department of Radiation Oncology of the University Clinic Erlangen. His research focus aims at improving therapy techniques and their quality assurance. Current focus topics are the management of organ motion by tracking, SGRT, MRT in RO, and error detection in interstitial brachytherapy.
Prof. Dr. Oliver Ott
Professor Oliver Ott studied medicine and physics at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). In 1999, he earned a doctorate from FAU for surgical studies on gastric cancer. In 2010, Professor Ott completed his postdoctoral qualification (Habilitation) in radiation oncology at FAU. Since 2005, Professor Ott has led the radiotherapy planning, hyperthermia, and low-dose radiotherapy units at University Hospital Erlangen’s department of Radiation Oncology. His major research interests include accelerated partial breast irradiation (APBI) in early breast cancer, development of multimodality treatment approaches for organ preservation in rectal, anal, and bladder cancers, hyperthermic oncology, and low-dose radiotherapy for painful inflammatory benign skeletal disorders.
Dr. Nilesh Mistry
Dr. Nilesh Mistry, is a medical imaging innovator focused on bringing new technologies to market. He has been contributing to the field of Medical Imaging for about 20 years and to the field of Imaging in Therapy for about 10 years– in various capacities both in academia and industry. Nilesh initially served as a research faculty at the University of Maryland (USA) where he focused on developing advanced functional imaging techniques for Radiotherapy. He then joined Siemens Healthineers (USA) about 6 years back serving as link between academic institutions and Siemens in the US. As a Product Manager (Germany), Nilesh has end-to-end responsibility for software products within Radiotherapy from conceptualizing the initial idea to releasing the product and entering the market. He is focused on bringing innovative technologies based on Artificial Intelligence, such as the new DirectORGANS autocontouring solution, to simplify clinical workflow and aide in preparing cases for further treatment.
Dr. Christian Hofmann
Dr. Christian Hofmann is an expert and technical concept manager for CT in RT physics. He is responsible for multiple acquisition and reconstruction topics that provide the basis for the CT scanner technology dedicated for radiotherapy. Together with our clinical collaboration sites, Dr. Christian Hofmann was a main driver in developing Direct i4D, a fundamentally new approach in 4D CT scanning where the CT scan adapts to the patient´s breathing in real time. In addition to respiratory gated acquisition and reconstruction, his main fields of responsibilities in his role as Senior Key Expert and Global CT Technology Manager at Siemens Healthineers relate to Dual Energy acquisition and reconstruction for RT applications, as well as metal artifact reduction.
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.
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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.