Classifying geometric variability by dominant eigenmodes of deformation in regressing tumours during active breath-hold lung cancer radiotherapy
- 15 December 2011
- journal article
- Published by IOP Publishing in Physics in Medicine & Biology
- Vol. 57 (2), 395-413
- https://doi.org/10.1088/0031-9155/57/2/395
Abstract
The purpose of this study is to develop and evaluate a lung tumour interfraction geometric variability classification scheme as a means to guide adaptive radiotherapy and improve measurement of treatment response. Principal component analysis (PCA) was used to generate statistical shape models of the gross tumour volume (GTV) for 12 patients with weekly breath hold CT scans. Each eigenmode of the PCA model was classified as 'trending' or 'non-trending' depending on whether its contribution to the overall GTV variability included a time trend over the treatment course. Trending eigenmodes were used to reconstruct the original semi-automatically delineated GTVs into a reduced model containing only time trends. Reduced models were compared to the original GTVs by analyzing the reconstruction error in the GTV and position. Both retrospective (all weekly images) and prospective (only the first four weekly images) were evaluated. The average volume difference from the original GTV was 4.3% ± 2.4% for the trending model. The positional variability of the GTV over the treatment course, as measured by the standard deviation of the GTV centroid, was 1.9 ± 1.4 mm for the original GTVs, which was reduced to 1.2 ± 0.6 mm for the trending-only model. In 3/13 cases, the dominant eigenmode changed class between the prospective and retrospective models. The trending-only model preserved GTV and shape relative to the original GTVs, while reducing spurious positional variability. The classification scheme appears feasible for separating types of geometric variability by time trend.Keywords
This publication has 28 references indexed in Scilit:
- Localization Accuracy of the Clinical Target Volume During Image-Guided Radiotherapy of Lung CancerInternational Journal of Radiation Oncology*Biology*Physics, 2011
- Anatomic and Pathologic Variability During Radiotherapy for a Hybrid Active Breath-Hold Gating TechniqueInternational Journal of Radiation Oncology*Biology*Physics, 2010
- Adaptive Radiotherapy for Lung CancerSeminars in Radiation Oncology, 2010
- Role of Adaptive Radiotherapy During Concomitant Chemoradiotherapy for Lung Cancer: Analysis of Data From a Prospective Clinical TrialInternational Journal of Radiation Oncology*Biology*Physics, 2009
- Variability of Four-Dimensional Computed Tomography Patient ModelsInternational Journal of Radiation Oncology*Biology*Physics, 2008
- Analysis of the rigid and deformable component of setup inaccuracies on portal images in head and neck radiotherapyPhysics in Medicine & Biology, 2007
- A method to calculate coverage probability from uncertainties in radiotherapy via a statistical shape modelPhysics in Medicine & Biology, 2007
- A technique for adaptive image-guided helical tomotherapy for lung cancerInternational Journal of Radiation Oncology*Biology*Physics, 2006
- Cone-beam CT based image-guidance for extracranial stereotactic radiotherapy of intrapulmonary tumorsActa Oncologica, 2006
- Modelling individual geometric variation based on dominant eigenmodes of organ deformation: implementation and evaluationPhysics in Medicine & Biology, 2005