Lauri Koivula1, Leonard Wee2, Juha Korhonen3. 1. Department of Radiation Oncology, Comprehensive Cancer Center, Helsinki University Central Hospital, P.O. Box 180, Helsinki 00029 HUS, Finland and Department of Medical Physics, Oncology Services, Vejle Hospital, Kabbeltoft 25, Vejle DK-7100, Denmark. 2. Department of Medical Physics, Oncology Services, Vejle Hospital, Kabbeltoft 25, Vejle DK-7100, Denmark and Danish Colorectal Cancer Centre South, Vejle Hospital, Kabbeltoft 25, Vejle DK-7100, Denmark. 3. Department of Radiation Oncology, Comprehensive Cancer Center, Helsinki University Central Hospital, P.O. Box 180, Helsinki 00029 HUS, Finland; Danish Colorectal Cancer Centre South, Vejle Hospital, Kabbeltoft 25, Vejle DK-7100, Denmark; and Department of Radiology, Helsinki University Central Hospital, P.O. Box 180, Helsinki 00029 HUS, Finland.
Abstract
PURPOSE: Magnetic resonance imaging (MRI) is increasingly used for radiotherapy target delineation, image guidance, and treatment response monitoring. Recent studies have shown that an entire external x-ray radiotherapy treatment planning (RTP) workflow for brain tumor or prostate cancer patients based only on MRI reference images is feasible. This study aims to show that a MRI-only based RTP workflow is also feasible for proton beam therapy plans generated in MRI-based substitute computed tomography (sCT) images of the head and the pelvis. METHODS: The sCTs were constructed for ten prostate cancer and ten brain tumor patients primarily by transforming the intensity values of in-phase MR images to Hounsfield units (HUs) with a dual model HU conversion technique to enable heterogeneous tissue representation. HU conversion models for the pelvis were adopted from previous studies, further extended in this study also for head MRI by generating anatomical site-specific conversion models (a new training data set of ten other brain patients). This study also evaluated two other types of simplified sCT: dual bulk density (for bone and water) and homogeneous (water only). For every clinical case, intensity modulated proton therapy (IMPT) plans robustly optimized in standard planning CTs were calculated in sCT for evaluation, and vice versa. Overall dose agreement was evaluated using dose-volume histogram parameters and 3D gamma criteria. RESULTS: In heterogeneous sCTs, the mean absolute errors in HUs were 34 (soft tissues: 13, bones: 92) and 42 (soft tissues: 9, bones: 97) in the head and in the pelvis, respectively. The maximum absolute dose differences relative to CT in the brain tumor clinical target volume (CTV) were 1.4% for heterogeneous sCT, 1.8% for dual bulk sCT, and 8.9% for homogenous sCT. The corresponding maximum differences in the prostate CTV were 0.6%, 1.2%, and 3.6%, respectively. The percentages of dose points in the head and pelvis passing 1% and 1 mm gamma index criteria were over 91%, 85%, and 38% with heterogeneous, dual bulk, and homogeneous sCTs, respectively. There were no significant changes to gamma index pass rates for IMPT plans first optimized in CT and then calculated in heterogeneous sCT versus IMPT plans first optimized in heterogeneous sCT and then calculated on standard CT. CONCLUSIONS: This study demonstrates that proton therapy dose calculations on heterogeneous sCTs are in good agreement with plans generated with standard planning CT. An MRI-only based RTP workflow is feasible in IMPT for brain tumors and prostate cancers.
PURPOSE: Magnetic resonance imaging (MRI) is increasingly used for radiotherapy target delineation, image guidance, and treatment response monitoring. Recent studies have shown that an entire external x-ray radiotherapy treatment planning (RTP) workflow for brain tumor or prostate cancerpatients based only on MRI reference images is feasible. This study aims to show that a MRI-only based RTP workflow is also feasible for proton beam therapy plans generated in MRI-based substitute computed tomography (sCT) images of the head and the pelvis. METHODS: The sCTs were constructed for ten prostate cancer and ten brain tumorpatients primarily by transforming the intensity values of in-phase MR images to Hounsfield units (HUs) with a dual model HU conversion technique to enable heterogeneous tissue representation. HU conversion models for the pelvis were adopted from previous studies, further extended in this study also for head MRI by generating anatomical site-specific conversion models (a new training data set of ten other brain patients). This study also evaluated two other types of simplified sCT: dual bulk density (for bone and water) and homogeneous (water only). For every clinical case, intensity modulated proton therapy (IMPT) plans robustly optimized in standard planning CTs were calculated in sCT for evaluation, and vice versa. Overall dose agreement was evaluated using dose-volume histogram parameters and 3D gamma criteria. RESULTS: In heterogeneous sCTs, the mean absolute errors in HUs were 34 (soft tissues: 13, bones: 92) and 42 (soft tissues: 9, bones: 97) in the head and in the pelvis, respectively. The maximum absolute dose differences relative to CT in the brain tumor clinical target volume (CTV) were 1.4% for heterogeneous sCT, 1.8% for dual bulk sCT, and 8.9% for homogenous sCT. The corresponding maximum differences in the prostate CTV were 0.6%, 1.2%, and 3.6%, respectively. The percentages of dose points in the head and pelvis passing 1% and 1 mm gamma index criteria were over 91%, 85%, and 38% with heterogeneous, dual bulk, and homogeneous sCTs, respectively. There were no significant changes to gamma index pass rates for IMPT plans first optimized in CT and then calculated in heterogeneous sCT versus IMPT plans first optimized in heterogeneous sCT and then calculated on standard CT. CONCLUSIONS: This study demonstrates that proton therapy dose calculations on heterogeneous sCTs are in good agreement with plans generated with standard planning CT. An MRI-only based RTP workflow is feasible in IMPT for brain tumors and prostate cancers.
Authors: Paul T Weavers; Shengzhen Tao; Joshua D Trzasko; Yunhong Shu; Erik J Tryggestad; Jeffrey L Gunter; Kiaran P McGee; Daniel V Litwiller; Ken-Pin Hwang; Matt A Bernstein Journal: Magn Reson Imaging Date: 2016-12-27 Impact factor: 2.546
Authors: Samaneh Kazemifar; Ana M Barragán Montero; Kevin Souris; Sara T Rivas; Robert Timmerman; Yang K Park; Steve Jiang; Xavier Geets; Edmond Sterpin; Amir Owrangi Journal: J Appl Clin Med Phys Date: 2020-03-26 Impact factor: 2.102
Authors: Ghazal Shafai-Erfani; Yang Lei; Yingzi Liu; Yinan Wang; Tonghe Wang; Jim Zhong; Tian Liu; Mark McDonald; Walter J Curran; Jun Zhou; Hui-Kuo Shu; Xiaofeng Yang Journal: Int J Part Ther Date: 2019-09-30