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Clinical Implementation of Intensity Modulated Radiotherapy using Carbon Ions
I. J. Radiation Oncology d Biology d Physics
S592
2943
Volume 72, Number 1, Supplement, 2008
Automatic Definition of Radiation Targets using Textural Characteristics of Co-registered PET-CT Images
1
H. Yu , C. Caldwell1,2, K. Mah3,2 1
Dept of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2Medical Physics, Odette Cancer Centre, Toronto, ON, Canada, 3Dept of Radiation Oncology, University of Toronto, Toronto, ON, Canada Purpose/Objective(s): To automatically segment the radiation target in head and neck cancers (HNC) from FDG-PET/CT images using a textural classifier. To compare the automated results with targets defined by experts. Background: The common approaches to quantitative segmentation of radiation targets with PET have involved simple threshold-based techniques such as SUV 2.5, 50% maximum signal intensity and signal and background ratio. Unfortunately, such techniques are seldom successful and ignore the wealth of information available from medical images. We have developed a novel approach to voxel by voxel based automated segmentation for HNC using co-registered FDG PET-CT images. The method was based on using feature characterization of PET-CT images. Our previous work revealed that texture features such as PET contrast, PET busyness, CT asymmetry, and CT busyness can better discriminate between abnormal and normal tissues than previously reported methods. Materials/Methods: Twenty-seven image features, including textural features from Spatial Gray-Level Dependence Matrices and Neighborhood Gray-Tone-Difference Matrices, as well as statistical and structural features were calculated for 476 head and neck regions of interest (ROIs) in the PET-CT images of 40 patients (20 HNC and 20 with lung cancer). There were 77 and 399 abnormal and normal ROIs, respectively. The former were contoured by a radiation oncologist. A voxel based segmentation using a Decision Tree based K nearest neighbors classifier was developed based on these features. PET-CT images of another 10 HNC patients who had primary tumors and positive nodes manually segmented by three radiation oncologists were used to evaluate the method. Features were calculated for each voxel within a window centered on the voxel. All voxels between the eyes and lung apices were automatically segmented. Results: In general, the automated segmentations were qualitatively similar to those of the radiation oncologists. The specificity was 95% ± 2% when all ‘‘true negative’’ was defined using all voxels excluding the ROIs considered abnormal by any one of the radiation oncologists. Sensitivity was 84% ± 19% and 90% ± 16% when ‘‘true positive’’ was defined as the intersection of at least two physicians’ and of all three physicians’ abnormal ROIs, respectively. Conclusions: Automated segmentation based on texture classification of PET-CT images has potential to provide accurate delineation of targets in HNC. This could potentially lead to reduction in inter-observer variability in target delineation and improved accuracy of treatment delivery. Author Disclosure: H. Yu, National Cancer Institute of Canada, B. Research Grant; C. Caldwell, National Cancer Institute of Canada, B. Research Grant; K. Mah, National Cancer Institute of Canada, B. Research Grant.
2944
Clinical Implementation of Intensity Modulated Radiotherapy using Carbon Ions
M. Ellerbrock1, O. Ja¨kel1, M. Kra¨mer2, A. Nikoghosyan3, D. Schulz-Ertner3, C. P. Karger4, B. Ackermann5, P. Heeg5, J. Debus3 1 Heidelberg Ion Beam Therapy Center and German Cancer Research Centre, Heidelberg, Germany, 2Gesellschaft fu¨r Schwerionenforschung, Darmstadt, Germany, 3Dept. of Radiation Oncology, University of Heidelberg, Heidelberg, Germany, 4 Dep. Medical Physics, German Cancer Research Centre, Heidelberg, Germany, 5Heidelberg Ion Beam Therapy Center, Heidelberg, Germany
Purpose/Objective(s): The clinical implementation of intensity modulated radiotherapy (IMRT) using a scanned beam of carbon ions in order to improve the sparing of organs at risk and to investigate the robustness of treatment plans against range and positioning uncertainties. Materials/Methods: Since 1997 more than 400 patients have been treated with a scanned beam of carbon ions at the German heavy ion pilot facility for radiotherapy at the Gesellschaft fu¨r Schwerionenforschung (GSI). An advanced version of our treatment planning software TRiP98BEAM allows a simultaneous optimization of several treatment fields using a biological optimization, rather than optimizing the fields separately for a homogeneous biological effect. The local effect model (LEM) developed at GSI is used to calculate and optimize the biological effective dose directly. A planning study was performed using data of patients with skull base tumors close to critical structures. Multiple field dose optimization relies on dose constraints to organs at risk given by the maximum doses for organs at risk and the penalty weights for corresponding doses. The dose distributions are compared for single and multiple field optimization using dose volume statistics. Typical field numbers that have been applied are two or three fields. Since the derived dose distributions are more dependent on accurate positioning and range calculations, the robustness of IMRT plans with regard to uncertainties in both procedures was investigated by recalculating the dose distributions using varying patient positions and range parameters. Results: Multiple field dose optimization as implemented in TRiP98BEAM can provide significant improvement of treatment plans for the scanned carbon ion beam at GSI. The robustness due to positioning and range uncertainties doesn’t seem to be a major issue and at worst may compensate the benefit in the dose conformation. Conclusions: IMRT for carbon ion beams provides further improvements in the dose conformation potential of ions. It is ready for broader clinical use and is used routinely at the GSI since late 2006. Author Disclosure: M. Ellerbrock, None; O. Ja¨kel, None; M. Kra¨mer, None; A. Nikoghosyan, None; D. Schulz-Ertner, None; C.P. Karger, None; B. Ackermann, None; P. Heeg, None; J. Debus, None.
2945
Plan Degradation in Head and Neck Cancers
C. P. Chen, J. Wong, C. W. Chang, M. El-Gabry, S. Merrick, Z. Gao Morristown Memorial Hospital, Morristown, NJ Purpose/Objective(s): Our image guided radiation therapy (IGRT) system couples a linear accelerator with a CT-on-rails, which offers the advantage of diagnostic CT quality images for IGRT guidance. Using our IGRT system, we undertook a detailed analysis of the impact of patient setup and tissue volume changes on dose delivery for head and neck (H&N) cancers.
S592
2943
Volume 72, Number 1, Supplement, 2008
Automatic Definition of Radiation Targets using Textural Characteristics of Co-registered PET-CT Images
1
H. Yu , C. Caldwell1,2, K. Mah3,2 1
Dept of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2Medical Physics, Odette Cancer Centre, Toronto, ON, Canada, 3Dept of Radiation Oncology, University of Toronto, Toronto, ON, Canada Purpose/Objective(s): To automatically segment the radiation target in head and neck cancers (HNC) from FDG-PET/CT images using a textural classifier. To compare the automated results with targets defined by experts. Background: The common approaches to quantitative segmentation of radiation targets with PET have involved simple threshold-based techniques such as SUV 2.5, 50% maximum signal intensity and signal and background ratio. Unfortunately, such techniques are seldom successful and ignore the wealth of information available from medical images. We have developed a novel approach to voxel by voxel based automated segmentation for HNC using co-registered FDG PET-CT images. The method was based on using feature characterization of PET-CT images. Our previous work revealed that texture features such as PET contrast, PET busyness, CT asymmetry, and CT busyness can better discriminate between abnormal and normal tissues than previously reported methods. Materials/Methods: Twenty-seven image features, including textural features from Spatial Gray-Level Dependence Matrices and Neighborhood Gray-Tone-Difference Matrices, as well as statistical and structural features were calculated for 476 head and neck regions of interest (ROIs) in the PET-CT images of 40 patients (20 HNC and 20 with lung cancer). There were 77 and 399 abnormal and normal ROIs, respectively. The former were contoured by a radiation oncologist. A voxel based segmentation using a Decision Tree based K nearest neighbors classifier was developed based on these features. PET-CT images of another 10 HNC patients who had primary tumors and positive nodes manually segmented by three radiation oncologists were used to evaluate the method. Features were calculated for each voxel within a window centered on the voxel. All voxels between the eyes and lung apices were automatically segmented. Results: In general, the automated segmentations were qualitatively similar to those of the radiation oncologists. The specificity was 95% ± 2% when all ‘‘true negative’’ was defined using all voxels excluding the ROIs considered abnormal by any one of the radiation oncologists. Sensitivity was 84% ± 19% and 90% ± 16% when ‘‘true positive’’ was defined as the intersection of at least two physicians’ and of all three physicians’ abnormal ROIs, respectively. Conclusions: Automated segmentation based on texture classification of PET-CT images has potential to provide accurate delineation of targets in HNC. This could potentially lead to reduction in inter-observer variability in target delineation and improved accuracy of treatment delivery. Author Disclosure: H. Yu, National Cancer Institute of Canada, B. Research Grant; C. Caldwell, National Cancer Institute of Canada, B. Research Grant; K. Mah, National Cancer Institute of Canada, B. Research Grant.
2944
Clinical Implementation of Intensity Modulated Radiotherapy using Carbon Ions
M. Ellerbrock1, O. Ja¨kel1, M. Kra¨mer2, A. Nikoghosyan3, D. Schulz-Ertner3, C. P. Karger4, B. Ackermann5, P. Heeg5, J. Debus3 1 Heidelberg Ion Beam Therapy Center and German Cancer Research Centre, Heidelberg, Germany, 2Gesellschaft fu¨r Schwerionenforschung, Darmstadt, Germany, 3Dept. of Radiation Oncology, University of Heidelberg, Heidelberg, Germany, 4 Dep. Medical Physics, German Cancer Research Centre, Heidelberg, Germany, 5Heidelberg Ion Beam Therapy Center, Heidelberg, Germany
Purpose/Objective(s): The clinical implementation of intensity modulated radiotherapy (IMRT) using a scanned beam of carbon ions in order to improve the sparing of organs at risk and to investigate the robustness of treatment plans against range and positioning uncertainties. Materials/Methods: Since 1997 more than 400 patients have been treated with a scanned beam of carbon ions at the German heavy ion pilot facility for radiotherapy at the Gesellschaft fu¨r Schwerionenforschung (GSI). An advanced version of our treatment planning software TRiP98BEAM allows a simultaneous optimization of several treatment fields using a biological optimization, rather than optimizing the fields separately for a homogeneous biological effect. The local effect model (LEM) developed at GSI is used to calculate and optimize the biological effective dose directly. A planning study was performed using data of patients with skull base tumors close to critical structures. Multiple field dose optimization relies on dose constraints to organs at risk given by the maximum doses for organs at risk and the penalty weights for corresponding doses. The dose distributions are compared for single and multiple field optimization using dose volume statistics. Typical field numbers that have been applied are two or three fields. Since the derived dose distributions are more dependent on accurate positioning and range calculations, the robustness of IMRT plans with regard to uncertainties in both procedures was investigated by recalculating the dose distributions using varying patient positions and range parameters. Results: Multiple field dose optimization as implemented in TRiP98BEAM can provide significant improvement of treatment plans for the scanned carbon ion beam at GSI. The robustness due to positioning and range uncertainties doesn’t seem to be a major issue and at worst may compensate the benefit in the dose conformation. Conclusions: IMRT for carbon ion beams provides further improvements in the dose conformation potential of ions. It is ready for broader clinical use and is used routinely at the GSI since late 2006. Author Disclosure: M. Ellerbrock, None; O. Ja¨kel, None; M. Kra¨mer, None; A. Nikoghosyan, None; D. Schulz-Ertner, None; C.P. Karger, None; B. Ackermann, None; P. Heeg, None; J. Debus, None.
2945
Plan Degradation in Head and Neck Cancers
C. P. Chen, J. Wong, C. W. Chang, M. El-Gabry, S. Merrick, Z. Gao Morristown Memorial Hospital, Morristown, NJ Purpose/Objective(s): Our image guided radiation therapy (IGRT) system couples a linear accelerator with a CT-on-rails, which offers the advantage of diagnostic CT quality images for IGRT guidance. Using our IGRT system, we undertook a detailed analysis of the impact of patient setup and tissue volume changes on dose delivery for head and neck (H&N) cancers.