Evaluation on lung cancer patients adaptive planning of TomoTherapy utilising radiobiological measures and planned adaptive module

Fan Chi Su, Chengyu Shi, Panayiotis Mavroidis, Prema Rassiah-Szegedi, Niko Papanikolaou

Research output: Contribution to journalArticle

2 Scopus citations


Adaptive radiation therapy is a promising concept that allows individualised, dynamic treatment planning based on feedback of measurements. The TomoTherapy Planned Adaptive application, integrated to the helical TomoTherapy planning system, enables calculation of actual dose delivered to the patient for each treatment fraction according to the pretreatment megavoltage computed tomography (MVCT) scan and image registration. As a result, new fractionation treatment plans are available if correction is necessary. In order to evaluate the real clinical effect, biological dose is preferred to physical dose. A biological parameter, biologically effective uniform dose (D≓), has the advantages of not only reporting delivered dose but also facilitating the analysis of dose-response relations, which link radiation dose to the clinical effect. Therefore, in this study, four lung patients adaptive plans were evaluated using the D≓ in addition to physical doses estimated from the TomoTherapy Planned Adaptive module. Higher complication-free tumour control probability (P+) (of about 8%) was observed in patients treated with larger dose-per-fraction by using the D≓ in addition to the physical dose. Moreover, a significant increase of 13.2% in the P+ for the adaptive TomoTherapy plan in one of the lung cancer patients was also observed, which indicates the clinical benefit of adaptive TomoTherapy.

Original languageEnglish (US)
Pages (from-to)185-194
Number of pages10
JournalJournal of Radiotherapy in Practice
Issue number4
StatePublished - Dec 1 2009



  • Adaptive radiotherapy
  • Biologically effective uniform dose
  • Helical TomoTherapy
  • Radiobiological objectives
  • Treatment planning

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Oncology

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