Purpose: The heterogeneity of lung tissue compromises the therapeutic quality of conventional dose‐volume based intensity modulated radiation therapy (IMRT) treatment planning, particularly when the lung volume varies with patient's respiration. An innovative inverse planning strategy was developed based on the concept of dose mass constraint as a more physical descriptor of dose delivered to lung. Methods: To better represent the actual lung cells being damaged by ionizing radiation, lung mass rather than lung volume was introduced in the inverse planning process. The conversion from volume of each voxel to mass was achieved with its local density, which was obtained from the computed tomography (CT or Hounsfield) number as a function of density relationship that is used by the treatment planning system. The dose mass constraints for targets and critical structures were integrated into the optimization cost function. For instance, a mass constraint would limit the dose to 20% of the lung mass to 20 Gy or less(coined as M20). The dose‐mass based inverse planning was applied on six thoracic cancer patients. To assess the dosimetric impact, comparisons were made between the dose mass histograms (DMH) and the dose volume histograms (DVH) and resulting dose distributions. Results: While the same planning target volume was covered, dose to lung from the DMH based plans were about 2% lower than DVH based plans. Lower doses could have important implications in terms of therapeutic effects. Conclusions: Dose mass‐based IMRT inverse planning framework was successfully implemented to take into account tissue density variations during plan optimization. Preliminary results suggest that gains in terms of lower dose to healthy lung are possible.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging