Project goal

DR THERAPAT’s aim is to create the Digital Radiation Therapy Patient platform.

This platform will integrate available knowledge on tumor imaging, image analysis and interpretation, radiobiological models and radiation therapy planning into a coherent, reusable, multi-scale digital representation. Radiation therapy was chosen as the application to prove the integration of those concepts since inherently imaging plays a major role in radiation therapy planning and delivery, so the imaging information is available as input for various models, and the delivery process is relatively well understood, making the model validation easier compared to e.g. chemotherapy.

Approach

Radiation therapy is a widely accepted modality in cancer treatment. The past decade has seen a revolution in radiation therapy technology. Intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (RapidArc/VMAT) now afford an exceptional flexibility in dose delivery. Image guidance during treatment ensures a reliable targeting of the dose to the tumor. In brachytherapy, where radioactive sources are positioned in close proximity to the tumor, image guidance also has created the possibility to irradiate the tumor with a high dose, with minimal exposure of surrounding tissue. Thus an improvement in tumor control is no longer invariably associated with an increase in radiation-induced toxicity.
With these technological innovations, the capacity exists to create treatment plans that are tailored to the specific characteristics of the patient. Thus, success of radiotherapy depends on proper personalized therapy planning and outcome prediction. Currently the differences between specific cancer types are widely recognized. This is reflected by tremendous gains in insights into tissue characteristics, aggressiveness and sensitivity to different forms of treatment. Furthermore, tremendous progress was made in clinical, pathological, radiological and functional diagnostic technology. To exploit such insights for the design of dose distributions, the concept of dose painting was introduced as early as 2000. Nevertheless, despite this progress, integration of this knowledge into the routine radiation therapy practice is progressing very slowly, in particular because an individualized representational model that informs on radiation therapy planning and outcome prediction is still lacking.
There are several modeling approaches available that have the potential to fill this gap, among the empirical, but established radiobiological models and more sophisticated multi-scale models. The DR THERAPAT framework will allow for an easy integration of different models, thus providing the means to validate them on different levels.

Expected benefits and outcomes

On the clinical side, DR THERAPAT will enable:

  • broad access to dose painting, the precise sculpting of the dose distribution to deliver desired dose to the tumor while sparing the surrounding organs,
  • individualized planning resulting in more effective and safer treatment,
  • accurate prediction of Tumor Control Probability and Normal Tissue Complication Probability, and
  • improved cancer treatment outcome.

On the modeling side, it will:

  • provide a platform demonstrating the integration of the respective modeling into the clinical workflow, thus proving the representation of the “Digital Patient”, and
  • provide a platform for the validation of the models.

A major deliverable of the proposal is a demonstrator of this platform for prostate cancer. A second deliverable is to demonstrate the use of the platform for cervical cancer to show that the model can be translated to other forms of cancer and to external-beam radiotherapy as well as brachytherapy. In these demonstrators, we will adapt and integrate generic models of anatomy, radio- and tissue biology and physiology of the organ system comprising the tumor and surrounding tissues with patient-specific diagnostic information modules of quantitative diagnostic imaging and histology.
DR THERAPAT will adapt and integrate today’s available tools into a digital representation of the patient’s health status and clinical workflow.

Consortium

The following partners participate:

 

philips

 

leuven

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Aarhus combined logo

NKIAVL

TUE