Abstract:
PURPOSE:Multiple metrics are proposed to characterize and compare the complexity of helical tomotherapy (HT) plans created for different treatment sites. METHODS:A cohort composed of 208 HT plans from head and neck (105), prostate (51) and brain (52) tumor sites was considered. For each plan, 14 complexity metrics were calculated. Those metrics evaluate the percentage of leaves with small opening times or approaching the projection duration, the percentage of closed leaves, the amount of tongue-and-groove effect, and the overall modulation of the planned sinogram. To enable data visualization, an approach based on principal component analysis was followed to reduce the dataset dimensionality. This allowed the calculation of a global plan complexity score. The correlation between plan complexity and pretreatment verification results using the Spearman's rank correlation coefficients was investigated. RESULTS:According to the global score, the most complex plans were the head and neck tumor cases, followed by the prostate and brain lesions irradiated with stereotactic technique. For almost all individual metrics, head and neck plans confirmed to be the plans with the highest complexity. Nevertheless, prostate cases had the highest percentage of leaves with an opening time approaching the projection duration, whereas the stereotactic brain plans had the highest percentage of closed leaves per projection. Significant correlations between some of the metrics and the pretreatment verification results were identified for the stereotactic brain group. CONCLUSIONS:The proposed metrics and the global score demonstrated to be useful to characterize and quantify the complexity of HT plans of different treatment sites. The reported differences inter- and intra-group may be valuable to guide the planning process aiming at reducing uncertainties and harmonize planning strategies.
journal_name
J Appl Clin Med Physjournal_title
Journal of applied clinical medical physicsauthors
Santos T,Ventura T,Mateus J,Capela M,Lopes MDCdoi
10.1002/acm2.12895subject
Has Abstractpub_date
2020-07-01 00:00:00pages
107-118issue
7issn
1526-9914journal_volume
21pub_type
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