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Computed Tomography simulation

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Computed Tomography simulation Imaging, the foundation of Radiation Therapy

Discover why we believe that the very first CT image plays a crucial role throughout a patient's RT treatment pathway.

There is no second chance to make a first impression. In radiation therapy, the first impression for the patient will be marked at the beginning of the treatment pathway with CT simulation. The resulting image will serve throughout the whole treatment. At Siemens Healthineers, our goal is to make this acquired CT image the foundation to improve treatment outcomes. It should serve to support modern treatment approaches and manage the individual complexities of patients.

Because we believe that imaging is the foundation of radiation therapy.

Customer voices

Intelligence in RT imaging and planning at The Queen's Centre, Cottingham, UK

Today’s healthcare providers are under increasing pressure to deliver radiotherapy to more patients than ever before. This demands innovative solutions that will allow you to work more efficiently and lay the foundations for the best possible treatments and optimal patient outcomes. See how SOMATOM go.Open Pro and its intelligent and AI-supported features can help tackle those challenges at The Queen's Center at Castle Hill Hospital, Cottingham, UK.

Learn more about SOMATOM go.Open Pro

Enhancing radiotherapy workflows with DirectSetup Notes at Universitätsklinikum Würzburg, Germany

A significant step during CT simulation is the accurate documentation of the patient's position. It helps to achieve a greater reproducibility for subsequent treatment delivery. Watch how Gary Razinskas and his colleagues at Universitätsklinikum Würzburg have implemented DirectSetup Notes¹, an advanced tool that streamlines documentation for radiotherapy patient simulation.

Intelligence in RT imaging and planning at The Queen's Centre, Cottingham, UK

Today’s healthcare providers are under increasing pressure to deliver radiotherapy to more patients than ever before. This demands innovative solutions that will allow you to work more efficiently and lay the foundations for the best possible treatments and optimal patient outcomes. See how SOMATOM go.Open Pro and its intelligent and AI-supported features can help tackle those challenges at The Queen's Center at Castle Hill Hospital, Cottingham, UK.

Learn more about SOMATOM go.Open Pro

Enhancing radiotherapy workflows with DirectSetup Notes at Universitätsklinikum Würzburg, Germany

A significant step during CT simulation is the accurate documentation of the patient's position. It helps to achieve a greater reproducibility for subsequent treatment delivery. Watch how Gary Razinskas and his colleagues at Universitätsklinikum Würzburg have implemented DirectSetup Notes¹, an advanced tool that streamlines documentation for radiotherapy patient simulation.

Intelligence in RT imaging and planning at The Queen's Centre, Cottingham, UK

Today’s healthcare providers are under increasing pressure to deliver radiotherapy to more patients than ever before. This demands innovative solutions that will allow you to work more efficiently and lay the foundations for the best possible treatments and optimal patient outcomes. See how SOMATOM go.Open Pro and its intelligent and AI-supported features can help tackle those challenges at The Queen's Center at Castle Hill Hospital, Cottingham, UK.

Learn more about SOMATOM go.Open Pro

Our intelligent CT simulators

Together, along the radiation therapy patient journey

Around 40% of cancer patients will undergo a course of radiation therapy as part of their cancer treatment². By simplifying the routine simulation tasks, we are enhancing the radiation therapy workflow.

Positioning verification Radiation Therapy SOMATOM go.Open Pro

Courtesy of Universitätsklinikum Erlangen, Germany

Positioning

Within the radiation therapy workflow, the initial image is going to be compared to the positioning image at the treatment workstation for accurate patient positioning. By having a good starting point, the introduction of random errors can potentially be reduced.¹¹

SOMATOM go.Sim and SOMATOM go.Open Pro have been designed to provide clinicians the optimal starting point to support modern treatment approaches. It comes with tools that are necessary to manage the complexities of individual cases.

CT scan Radiotherapy Siemens Healthineers go.Open Pro

Courtesy of Universitätsklinikum Erlangen, Germany

Imaging

The CT planning image is the foundation for the whole radiation therapy workflow. It is key for the treatment pathway and is helping to tumor and organs-at-risk delineation, as well as the dose that the patient will receive.^3,4

Organs-at-risk contouring SOMATOM go.Open Pro

Courtesy of Universitätsklinikum Erlangen, Germany

Organs-at-risk contouring

Organs-at-risk contouring are a cost and time intensive task.⁵In addition, inter-observer variability can make it difficult to achieve consistent contouring results.⁶ If we also consider that the quality of the image is influencing the OAR delination, the challenge of quality OAR-contours even increases.^7,8

To meet these challenges, we introduced DirectORGANS: the first intelligent integrated OAR contouring. It is based on two core elements: Optimized reconstruction and deep-learning based contouring. This enables us to increase efficiency on this time-consuming task.

PTV Delineation Imaging in RT

Courtesy of Universitätsklinikum Erlangen, Germany

PTV delineation

Imaging creates opportunities for improved therapeutic targeting of cancer. At the same time, conceptual thinking about radiotherapy target volume definition and dose prescription is not keeping up.³

With our solutions we want to enable clinicians with images that can help overcome daily hurdles when it comes to image quality and accurate planning target volume (PTV) visualization.

By using innovative iterative reconstructions, enabling the use of Dual Energy and reducing artifacts, we can help improving the tissue contrast. Therefore, we are also aiming to reduce of the variability in target delineation.⁹

Dose distribution Imaging RT SOMATOM go.Open Pro

Courtesy of Universitätsklinikum Erlangen, Germany

Dose calculation

In radiation therapy, the CT image also plays an important role when it comes to treatment planning. The image used for planning needs to reflect an accurate geometric model of the patient and enable dose calculation. At the same time, it needs to provide the physicians an optimal contrast to delineate the target volumes.

The streamlined solution of SOMATOM go.Sim and SOMATOM go.Open Pro aims to improve access to tailored treatment. This is done by enabling improved tissue contrast and intelligent real-time breathing adaptation¹⁰ – driving towards enhanced image quality for confident treatment planning. It has been developed aiming to reduce the likelihood of errors in a complex RT workflow and therefore potentially reduce time to treatment.

Positioning verification Radiation Therapy SOMATOM go.Open Pro

Courtesy of Universitätsklinikum Erlangen, Germany

Positioning

Within the radiation therapy workflow, the initial image is going to be compared to the positioning image at the treatment workstation for accurate patient positioning. By having a good starting point, the introduction of random errors can potentially be reduced.¹¹

SOMATOM go.Sim and SOMATOM go.Open Pro have been designed to provide clinicians the optimal starting point to support modern treatment approaches. It comes with tools that are necessary to manage the complexities of individual cases.

Organs-at-risk contouring SOMATOM go.Open Pro

Courtesy of Universitätsklinikum Erlangen, Germany

Organs-at-risk contouring

Organs-at-risk contouring are a cost and time intensive task.⁵In addition, inter-observer variability can make it difficult to achieve consistent contouring results.⁶ If we also consider that the quality of the image is influencing the OAR delination, the challenge of quality OAR-contours even increases.^7,8

To meet these challenges, we introduced DirectORGANS: the first intelligent integrated OAR contouring. It is based on two core elements: Optimized reconstruction and deep-learning based contouring. This enables us to increase efficiency on this time-consuming task.

PTV Delineation Imaging in RT

Courtesy of Universitätsklinikum Erlangen, Germany

PTV delineation

Imaging creates opportunities for improved therapeutic targeting of cancer. At the same time, conceptual thinking about radiotherapy target volume definition and dose prescription is not keeping up.³

With our solutions we want to enable clinicians with images that can help overcome daily hurdles when it comes to image quality and accurate planning target volume (PTV) visualization.

By using innovative iterative reconstructions, enabling the use of Dual Energy and reducing artifacts, we can help improving the tissue contrast. Therefore, we are also aiming to reduce of the variability in target delineation.⁹

Dose distribution Imaging RT SOMATOM go.Open Pro

Courtesy of Universitätsklinikum Erlangen, Germany

Dose calculation

In radiation therapy, the CT image also plays an important role when it comes to treatment planning. The image used for planning needs to reflect an accurate geometric model of the patient and enable dose calculation. At the same time, it needs to provide the physicians an optimal contrast to delineate the target volumes.

The streamlined solution of SOMATOM go.Sim and SOMATOM go.Open Pro aims to improve access to tailored treatment. This is done by enabling improved tissue contrast and intelligent real-time breathing adaptation¹⁰ – driving towards enhanced image quality for confident treatment planning. It has been developed aiming to reduce the likelihood of errors in a complex RT workflow and therefore potentially reduce time to treatment.

Positioning verification Radiation Therapy SOMATOM go.Open Pro

Courtesy of Universitätsklinikum Erlangen, Germany

Positioning

Within the radiation therapy workflow, the initial image is going to be compared to the positioning image at the treatment workstation for accurate patient positioning. By having a good starting point, the introduction of random errors can potentially be reduced.¹¹

SOMATOM go.Sim and SOMATOM go.Open Pro have been designed to provide clinicians the optimal starting point to support modern treatment approaches. It comes with tools that are necessary to manage the complexities of individual cases.

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The products/features mentioned herein are not commercially available in all countries. Due to regulatory reasons their future availability cannot be guaranteed.

1

DirectSetup Notes is intended for digitalizing patient setup documentation to ease the RT workflow. The operation and the configuration of the tool must be conducted by trained healthcare professionals. DirectSetup Notes is available with SOMATOM go.Sim and SOMATOM go.Open Pro with syngo CTVB10 only.

2

Beaton L et al. How rapid advances in imaging are defining the future of precision radiation oncology. Br J Cancer. 2019 Apr;120(8):779-790.

3

Kaanders JHAM et al. Advances in cancer imaging require renewed radiotherapy dose and target volume concepts. Radiother Oncol. 2020 Jul;148:140-142. Epub 2020 Apr 23. PMID: 32361663.

4

Christian Rønn Hansen et al. 2017. Contouring and dose calculation in head and neck cancer radiotherapy after reduction of metal artifacts in CT images, Acta Oncologica, 56:6, 874-878.

5

Radiotherapy in Cancer Care: Facing the Global Challenge, IAEA 2017

6

van der Veen J. et al. Interobserver variability in organ at risk delineation in head and neck cancer, 2021

7

Wu X et al. (2017) Knowledge-Based Auto Contouring for Radiation Therapy: Object Definitions, Ground Truth Delineations, Object Quality, and I mage Quality. Int J Radiat Oncol Biol Phys.

8

Pednekar, G. V.et al. (2018). Image quality and segmentation. Proc SPIE Int Soc Opt Eng.

9

Dual Energy CT cookbook: A guide to Monoenergetic Plus imaging in RT, 2018

10

Direct i4D is only available on SOMATOM go.Open Pro. Optional. Requires Varian RGSC or Anzai as online gating device.

11

van Herk M. Errors and margins in radiotherapy. Semin Radiat Oncol. 2004 Jan;14(1):52-64.