IJMPCERO  Vol.4 No.3 , August 2015
Feasibility Study on Deformable Image Registration for Lung SBRT Patients for Dose-Driven Adaptive Therapy
ABSTRACT
The purpose of the study was to evaluate a treatment dose using planning computed tomography (pCT) that was deformed to pre-treatment cone beam computed tomography (CBCT) for lung stereotactic body radiation therapy (SBRT) treatment. Five lung SBRT patients were retrospectively selected, and their daily CBCTs were employed in this study. Dosimetric comparison was performed between the original and recalculated plans from the deformed pCT (dose per fraction) by comparing a target coverage and organs at risk. Dose summation of five fractions was computed and compared to the original plan. A phantom study was conducted to evaluate the dosimetric accuracy for the dose per fraction. In the phantom study, the difference between the mean Hounsfield Unit (HU) values of the original and deformed pCTs is less than 0.5%. In patient study, the mean HU deviation of the five deformed pCTs compared to that of the original pCT was within ±5%, which is dosimetrically insignificant. While the internal target volume (ITV) shrank by 17% on average among the five patients, mean lung dose (MLD) increased by up to 7%, and D95% of PTV decreased slightly but stayed within 5%. Results showed that MLD might be a better indicative metric of normal lung dose than V20Gy as the ITV volume decreases. This study showed a feasibility to use a deformed pCT for evaluation of the dose per fraction and for a possible plan adaptation in lung SBRT cases. Readers should be cautious in selecting patients before clinical application due to the image quality of CBCT.

Cite this paper
Han, E. , Chao, M. , Zhang, X. and Penagaricano, J. (2015) Feasibility Study on Deformable Image Registration for Lung SBRT Patients for Dose-Driven Adaptive Therapy. International Journal of Medical Physics, Clinical Engineering and Radiation Oncology, 4, 224-232. doi: 10.4236/ijmpcero.2015.43027.
References
[1]   Bhatt, A.D., El-Ghamry, M.N., Dunlap, N.E., et al. (2005) Tumor Volume Change with Stereotactic Body Radiotherapy (SBRT) for Early-Stage Lung Cancer: Evaluating the Potential for Adaptive SBRT. American Journal of Clinical Oncology, 38, 41-46.

[2]   Mehta, V. (2005) Radiation Pneumonitis and Pulmonary Fibrosis in Non-Small-Cell Lung Cancer: Pulmonary Function, Prediction, and Prevention. International Journal of Radiation Oncology Biology Physics, 63, 5-24.
http://dx.doi.org/10.1016/j.ijrobp.2005.03.047

[3]   Marks, L.B., Yu, X., Vujaskovic, Z., et al. (2003) Radiation-Induced Lung Injury. Seminars in Radiation Oncology, 13, 333-345.
http://dx.doi.org/10.1016/S1053-4296(03)00034-1

[4]   Maruyama, M., Murakami, R., Nakaguchi, Y., et al. (2012) Cone-Beam Computed Tomography-Derived Adaptive Radiotherapy. Japanese Journal of Radiological Technology, 68, 162-168.
http://dx.doi.org/10.6009/jjrt.2012_JSRT_68.2.162

[5]   Onozato, Y., Kadoya, N., Fujita, Y., et al. (2014) Evaluation of On-Board kV Cone Beam Computed Tomography-Based Dose Calculation with Deformable Image Registration Using Hounsfield Unit Modifications. International Journal of Radiation Oncology Biology Physics, 89, 416-423.
http://dx.doi.org/10.1016/j.ijrobp.2014.02.007

[6]   Galerani, A.P., Grills, I., Hugo, G., et al. (2013) Dosimetric Impact of Online Correction via Cone-Beam CT-Based Image Guidance for Stereotactic Lung Radiotherapy. International Journal of Radiation Oncology Biology Physics, 78, 1571-1578.

[7]   Qin, Y., Zhang, F., Yoo, D.S., et al. (2013) Adaptive Stereotactic Body Radiation Therapy Planning for Lung Cancer. International Journal of Radiation Oncology Biology Physics, 87, 209-215.
http://dx.doi.org/10.1016/j.ijrobp.2013.05.008

[8]   Veiga, C., McClelland, J., Moinuddin, S., et al. (2014) Toward Adaptive Radiotherapy for Head and Neck Patients: Feasibility Study on Using CT-to-CBCT Deformable Registration for “Dose of the Day” Calculations. Medical Physics, 41, Article ID: 031703.
http://dx.doi.org/10.1118/1.4864240

[9]   Winkler, P., Jakse, G., Lodron, G., et al. (2013) Adaptive Radiotherapy Using Deformable Image Registration—A Concept for Individualized Radiation Treatments. Biomedical Technology, 58, Walter de Gruyter, Berlin and Boston.

[10]   Mencarelli, A., van Kranen, S.R., Hamming-Vrieze, O., et al. (2014) Deformable Image Registration for Adaptive Radiation Therapy of Head and Neck Cancer: Accuracy and Precision in the Presence of Tumor Changes. International Journal of Radiation Oncology Biology Physics, 90, 680-687.
http://dx.doi.org/10.1016/j.ijrobp.2014.06.045

[11]   Ma, C., Hou, Y., Li, H., et al. (2014) A Study of the Anatomic Changes and Dosimetric Consequences in Adaptive CRT of Non-Small-Cell Lung Cancer Using Deformable CT and CBCT Image Registration. Technology in Cancer Research & Treatment, 13, 95-100.

[12]   Disher, B., Hajdok, G., Wang, A., et al. (2013) Correction for “Artificial” Electron Disequilibrium Due to Cone-Beam CT Density Errors: Implications for On-Line Adaptive Stereotactic Body Radiation Therapy of Lung. Physics in Medicine & Biology, 58, 4157-4174.
http://dx.doi.org/10.1088/0031-9155/58/12/4157

[13]   Zurl, B., Tiefling, R., Winkler, P., et al. (2007) Hounsfield Units Variations: Impact on CT-Density Based Conversion Tables and Their Effects on Dose Distribution. Strahlentherapie Und Onkologie, 190, 88-93.

[14]   Yang, Y., Schreibmann, E., Li, T., et al. (2007) Evaluation of On-Board kV Cone Beam CT (CBCT)-Based Dose Calculation. Physics in Medicine & Biology, 52, 685-705.
http://dx.doi.org/10.1088/0031-9155/52/3/011

[15]   Hou, J., Guerrero, M., Chen, W., et al. (2011) Deformable Planning CT to Cone-Beam CT Image Registration in Head-and-Neck Cancer. Medical Physics, 38, 2088-2094.
http://dx.doi.org/10.1118/1.3554647

[16]   Yip, C., Thomas, C., Michaelidou, A., et al. (2010) Co-Registration of Cone Beam CT and Planning CT in Head and Neck IMRT Dose Estimation: A Feasible Adaptive Radiotherapy Strategy. British Journal of Radiology, 87, Article ID: 20130532.

[17]   Piper, J.W. (2007) Evaluation of a CT to Cone-Beam CT Deformable Registration Algorithm. International Journal of Radiation Oncology Biology Physics, 69, S418-S419.
http://dx.doi.org/10.1016/j.ijrobp.2007.07.1561

[18]   Chao, M., Xie, Y., Moros, E.G., et al. (2010) Image-Based Modeling of Tumor Shrinkage in Head and Neck Radiation Therapy. Medical Physics, 37, 2351-2358.
http://dx.doi.org/10.1118/1.3399872

[19]   Guerrero, T., Zhang, G., Huang, T.C., et al. (2004) Intrathoracic Tumour Motion Estimation from CT Imaging Using the 3D Optical Flow Method. Physics in Medicine & Biology, 49, 4147-4161.
http://dx.doi.org/10.1088/0031-9155/49/17/022

 
 
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