An optimized workflow for the integration of biological information into radiotherapy planning: experiences with T1w DCE-MRI

Phys Med Biol. 2005 Sep 7;50(17):4209-23. doi: 10.1088/0031-9155/50/17/020. Epub 2005 Aug 24.


Planning of radiotherapy is often difficult due to restrictions on morphological images. New imaging techniques enable the integration of biological information into treatment planning and help to improve the detection of vital and aggressive tumour areas. This might improve clinical outcome. However, nowadays morphological data sets are still the gold standard in the planning of radiotherapy. In this paper, we introduce an in-house software platform enabling us to combine images from different imaging modalities yielding biological and morphological information in a workflow driven approach. This is demonstrated for the combination of morphological CT, MRI, functional DCE-MRI and PET data. Data of patients with a tumour of the prostate and with a meningioma were examined with DCE-MRI by applying pharmacokinetic two-compartment models for post-processing. The results were compared with the clinical plans for radiation therapy. Generated parameter maps give additional information about tumour spread, which can be incorporated in the definition of safety margins.

Publication types

  • Evaluation Study

MeSH terms

  • Algorithms
  • Computational Biology / methods
  • Computer Simulation
  • Decision Support Systems, Clinical*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Magnetic Resonance Spectroscopy
  • Models, Biological
  • Neoplasms / diagnosis
  • Neoplasms / radiotherapy*
  • Radiometry / methods*
  • Radiotherapy Dosage
  • Radiotherapy Planning, Computer-Assisted / methods*
  • Radiotherapy, Computer-Assisted / methods
  • Software*
  • Systems Integration
  • User-Computer Interface*