High Quality and Low Dose Cone-beam CT Imaging with Anisotropic Regularized FDK Reconstruction...
1
also indicates a strong correlation with treatment technique (p \0.0001, F = 21.6). The Tukey HSD test indicates that the HT plans are not significantly different from the conformal plans. Conclusions: Our results for this sample indicate that shifting from conformal to IMRT techniques does not necessarily result in an increase in integral dose, and may in fact lead to a reduction. HT planning resulted in an 8% and 14% increase in mean integral dose compared to dynamic MLC IMRT and VMAT, respectively. If integral dose is of concern to the clinician, explicit care should be taken to minimize the dose to all normal tissue when using IMRT techniques. Author Disclosure: H.K. Warkentin, None; L. Capelle, None; G.C. Field, None; K. Joseph, None; B. Warkentin, None. 149 High Quality and Low Dose Cone-beam CT Imaging with Anisotropic Regularized FDK Reconstruction Algorithm H. Lee 1 , R. Lee 2 , T. Suh 3 , W. Jeong 3 , L. Xing 1 1 Stanford University, Stanford, CA, 2 Ewha Women’s University, Seoul, Republic of Korea, 3 The Catholic University of Korea, Seoul, Republic of Korea Purpose/Objective(s): In current radiation therapy, CBCT scans are repeatedly performed on the same patient during the whole treatment course, which lasts 4 to 6 weeks. While acquiring projection data with a lower mAs protocol is an effective way to reduce radiation dose incurred to the patients, excessive noise of projection data leads to significantly degraded image quality of CBCT when it is reconstructed by the well-known Feldkamp-Davis-Kress (FDK) algorithm. Therefore, we propose an improved FDK reconstruction algorithm with an anisotropic regularization to enhance image quality of CBCT using low dose projections. Materials/Methods: The algorithm firstly applied a modified filtering that integrates shepp and logan filter into window function on all projections for impulse noise removal. Anisotropic regularization method was then applied on the filtered projection images. Anisotropic diffusion filter (ADF) was used as anisotropic regularization and minimized by the standard steepest gradient decent optimization strategy. Minimizing ADF of the filtered projection image indicates that edges having high contrast relative to the surroundings are preserved and noisy pixels having low contrast are smoothed. The preserving parameter to adjust the separation between noise-free and noisy areas was adaptively determined by calculating the cumulative histogram of the gradient magnitude of the updated projection image in each steepest gradient decent step. In this work, the parameter value was set to be 90% of the cumulative histogram. With these anisotropic regularized projections, backprojection operation was finally performed. The perfor- mance of our anisotropic regularized FDK algorithm was evaluated with phantom and patient data sets acquired from a low-dose protocol (10mA/10ms) and compared with conventional FDK algorithm. Results: High quality CBCT images were obtained with an order of magnitude lower dose using the proposed algorithm. A quan- titative analysis of the images with low dose shows that the contrast-to-noise ratio with spatial resolution comparable to images reconstructed with projections acquired from a high-dose protocol (80mA/12ms). Artifacts seen in traditional FDK algorithm were markedly suppressed in images reconstructed by the proposed algorithm. Conclusions: The proposed algorithm reduces radiation dose and provides high contrast-to-noise CBCT images by removing noisy corrupted areas and preserving the edges in the repeated CBCT scans. The work may have significant implication in image guided and adaptive radiation therapy as CBCT is used repeatedly. Author Disclosure: H. Lee, This work was supported by the National Research Foundation of Korea, NRF, (Grant no. 2008-1768-2 and Grant no. 2009-1311-1) funded by Ministry of Education, Science, and Technology., C. Other Research Support; R. Lee, None; T. Suh, None; W. Jeong, None; L. Xing, None. 150 Dosimetric Evaluation of a Volume Segmentation Algorithm for MRI-based Treatment Planning for Head and Neck Cancer C. Chang, B. K. Teo, M. Altschuler, A. Lin, T. C. Zhu University of Pennsylvania, Philadelphia, PA Purpose/Objective(s): The objective of this study is to evaluate the dosimetric accuracy of IMRT dose calculation using only a T1 MR image. MRI based radiotherapy dose calculation techniques have previously been applied to the pelvic and brain regions. For head and neck region, tissue heterogeneity can have a more pronounced effect on dose calculation accuracy. Using an automated segmen- tation based algorithm with thresholding, a heterogeneous pseudo CT image is derived from a T1 MRI volume with four distinct types- air, lung, tissue, and bone. Each class is assigned a CT number corresponding to fixed relative electron densities of 0, 0.25, 1.0, and 2.0, respectively. We assess the accuracy of dose calculation using this four level electron density model to account for tissue heterogeneity. Materials/Methods: A fast 3D volume segmentation algorithm is developed to delineate the different tissue types from a MR image. In addition to the external body contour, the program provides a tool to obtain internal MR boundaries onto which the initial physician- drawn tumor contours can be mapped and correlated. Direct comparison is made between the actual CT and MR derived pseudo CT to assess segmentation accuracy. Radiotherapy dose was first calculated and optimized on the CT using the Eclipse treatment planning system (Varian Medical) with heterogeneity correction and subsequently recalculated using the pseudo CT image for comparison. Results: For T1 MRI, we found a good one-to-one correspondence for air, lung, and tissue between CT and MRI numbers. For our MRI sequence, preliminary data show that this correspondence is: 0-15 for air; 15-60 for lung, and 60-500 for tissue. There is an overlap between lung and bone: 40-60 for bone and 15-60 for lung probably due to the similarly decreased hydrogen contents in these materials compared to tissue. This degeneracy can be removed through image processing by first identifying the lung contour and segmenting regions that are either inside or outside the lungs. Comparison of the coverage to head and neck IMRT treatment planning show good concordance of the dose volume histograms between CT and MR image calculated plans. The mean and max- imum dose values of the structures were typically within less than 2% between the two methods. Conclusions: MRI-based treatment planning has proven to be feasible for sites where tissue heterogeneity is insignificant (e.g., prostate). Our study extends that to sites with substantial tissue heterogeneity. Using a multi-organ segmentation algorithm, we are able to convert the MR image into a four level CT with electron density information for dose calculation. Preliminary verification for head and neck patients show that MRI based dose calculation is a feasible method and can potentially be useful for future integrated MRI/Linac systems. Author Disclosure: C. Chang, None; B.K. Teo, None; M. Altschuler, None; A. Lin, None; T.C. Zhu, None. S70 I. J. Radiation Oncology d Biology d Physics Volume 78, Number 3, Supplement, 2010
Transcript of High Quality and Low Dose Cone-beam CT Imaging with Anisotropic Regularized FDK Reconstruction...
S70 I. J. Radiation Oncology d Biology d Physics Volume 78, Number 3, Supplement, 2010
also indicates a strong correlation with treatment technique (p\0.0001, F = 21.6). The Tukey HSD test indicates that the HT plansare not significantly different from the conformal plans.
Conclusions: Our results for this sample indicate that shifting from conformal to IMRT techniques does not necessarily result in anincrease in integral dose, and may in fact lead to a reduction. HT planning resulted in an 8% and 14% increase in mean integral dosecompared to dynamic MLC IMRT and VMAT, respectively. If integral dose is of concern to the clinician, explicit care should betaken to minimize the dose to all normal tissue when using IMRT techniques.
Author Disclosure: H.K. Warkentin, None; L. Capelle, None; G.C. Field, None; K. Joseph, None; B. Warkentin, None.
149 High Quality and Low Dose Cone-beam CT Imaging with Anisotropic Regularized FDK
Reconstruction AlgorithmH. Lee1, R. Lee2, T. Suh3, W. Jeong3, L. Xing1
1Stanford University, Stanford, CA, 2Ewha Women’s University, Seoul, Republic of Korea, 3The Catholic University of Korea,Seoul, Republic of Korea
Purpose/Objective(s): In current radiation therapy, CBCT scans are repeatedly performed on the same patient during the wholetreatment course, which lasts 4 to 6 weeks. While acquiring projection data with a lower mAs protocol is an effective way to reduceradiation dose incurred to the patients, excessive noise of projection data leads to significantly degraded image quality of CBCTwhen it is reconstructed by the well-known Feldkamp-Davis-Kress (FDK) algorithm. Therefore, we propose an improved FDKreconstruction algorithm with an anisotropic regularization to enhance image quality of CBCT using low dose projections.
Materials/Methods: The algorithm firstly applied a modified filtering that integrates shepp and logan filter into window functionon all projections for impulse noise removal. Anisotropic regularization method was then applied on the filtered projection images.Anisotropic diffusion filter (ADF) was used as anisotropic regularization and minimized by the standard steepest gradient decentoptimization strategy. Minimizing ADF of the filtered projection image indicates that edges having high contrast relative to thesurroundings are preserved and noisy pixels having low contrast are smoothed. The preserving parameter to adjust the separationbetween noise-free and noisy areas was adaptively determined by calculating the cumulative histogram of the gradient magnitudeof the updated projection image in each steepest gradient decent step. In this work, the parameter value was set to be 90% of thecumulative histogram. With these anisotropic regularized projections, backprojection operation was finally performed. The perfor-mance of our anisotropic regularized FDK algorithm was evaluated with phantom and patient data sets acquired from a low-doseprotocol (10mA/10ms) and compared with conventional FDK algorithm.
Results: High quality CBCT images were obtained with an order of magnitude lower dose using the proposed algorithm. A quan-titative analysis of the images with low dose shows that the contrast-to-noise ratio with spatial resolution comparable to imagesreconstructed with projections acquired from a high-dose protocol (80mA/12ms). Artifacts seen in traditional FDK algorithmwere markedly suppressed in images reconstructed by the proposed algorithm.
Conclusions: The proposed algorithm reduces radiation dose and provides high contrast-to-noise CBCT images by removingnoisy corrupted areas and preserving the edges in the repeated CBCT scans. The work may have significant implication in imageguided and adaptive radiation therapy as CBCT is used repeatedly.
Author Disclosure: H. Lee, This work was supported by the National Research Foundation of Korea, NRF, (Grant no. 2008-1768-2and Grant no. 2009-1311-1) funded by Ministry of Education, Science, and Technology., C. Other Research Support; R. Lee,None; T. Suh, None; W. Jeong, None; L. Xing, None.
150 Dosimetric Evaluation of a Volume Segmentation Algorithm for MRI-based Treatment Planning for Head
and Neck CancerC. Chang, B. K. Teo, M. Altschuler, A. Lin, T. C. Zhu
University of Pennsylvania, Philadelphia, PA
Purpose/Objective(s): The objective of this study is to evaluate the dosimetric accuracy of IMRT dose calculation using only a T1MR image. MRI based radiotherapy dose calculation techniques have previously been applied to the pelvic and brain regions. For headand neck region, tissue heterogeneity can have a more pronounced effect on dose calculation accuracy. Using an automated segmen-tation based algorithm with thresholding, a heterogeneous pseudo CT image is derived from a T1 MRI volume with four distinct types-air, lung, tissue, and bone. Each class is assigned a CT number corresponding to fixed relative electron densities of 0, 0.25, 1.0, and 2.0,respectively. We assess the accuracy of dose calculation using this four level electron density model to account for tissue heterogeneity.
Materials/Methods: A fast 3D volume segmentation algorithm is developed to delineate the different tissue types from a MR image.In addition to the external body contour, the program provides a tool to obtain internal MR boundaries onto which the initial physician-drawn tumor contours can be mapped and correlated. Direct comparison is made between the actual CT and MR derived pseudo CT toassess segmentation accuracy. Radiotherapy dose was first calculated and optimized on the CT using the Eclipse treatment planningsystem (Varian Medical) with heterogeneity correction and subsequently recalculated using the pseudo CT image for comparison.
Results: For T1 MRI, we found a good one-to-one correspondence for air, lung, and tissue between CT and MRI numbers. For ourMRI sequence, preliminary data show that this correspondence is: 0-15 for air; 15-60 for lung, and 60-500 for tissue. There is anoverlap between lung and bone: 40-60 for bone and 15-60 for lung probably due to the similarly decreased hydrogen contents inthese materials compared to tissue. This degeneracy can be removed through image processing by first identifying the lung contourand segmenting regions that are either inside or outside the lungs. Comparison of the coverage to head and neck IMRT treatmentplanning show good concordance of the dose volume histograms between CT and MR image calculated plans. The mean and max-imum dose values of the structures were typically within less than 2% between the two methods.
Conclusions: MRI-based treatment planning has proven to be feasible for sites where tissue heterogeneity is insignificant (e.g., prostate).Our study extends that to sites with substantial tissue heterogeneity. Using a multi-organ segmentation algorithm, we are able to convertthe MR image into a four level CT with electron density information for dose calculation. Preliminary verification for head and neckpatients show that MRI based dose calculation is a feasible method and can potentially be useful for future integrated MRI/Linac systems.
Author Disclosure: C. Chang, None; B.K. Teo, None; M. Altschuler, None; A. Lin, None; T.C. Zhu, None.
