Comparison of Synthetic Computed Tomography Generation Methods, Incorporating Male and Female Anatomical Differences, for Magnetic Resonance Imaging-Only Definitive Pelvic Radiotherapy

被引:13
作者
O'Connor, Laura M. [1 ,2 ]
Choi, Jae H. [1 ,3 ]
Dowling, Jason A. [4 ]
Warren-Forward, Helen [2 ]
Martin, Jarad [1 ,5 ]
Greer, Peter B. [1 ,3 ]
机构
[1] Calvary Mater Hosp, Dept Radiat Oncol, Newcastle, NSW, Australia
[2] Univ Newcastle, Sch Hlth Sci, Callaghan, NSW, Australia
[3] Univ Newcastle, Sch Math & Phys Sci, Callaghan, NSW, Australia
[4] CSIRO, Australian E Hlth Res Ctr, Herston, Qld, Australia
[5] Univ Newcastle, Sch Med & Publ Hlth, Callaghan, NSW, Australia
来源
FRONTIERS IN ONCOLOGY | 2022年 / 12卷
关键词
MRI radiotherapy planning; image-guided radiotherapy; synthetic CT; computer-assisted radiotherapy planning; rectum neoplasms; cervix neoplasms; endometrium neoplasms; anal canal neoplasms; BEAM RADIATION-THERAPY; CT GENERATION; ELECTRON-DENSITY; MRI; FEASIBILITY;
D O I
10.3389/fonc.2022.822687
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
PurposeThere are several means of synthetic computed tomography (sCT) generation for magnetic resonance imaging (MRI)-only planning; however, much of the research omits large pelvic treatment regions and female anatomical specific methods. This research aimed to apply four of the most popular methods of sCT creation to facilitate MRI-only radiotherapy treatment planning for male and female anorectal and gynecological neoplasms. sCT methods were validated against conventional computed tomography (CT), with regard to Hounsfield unit (HU) estimation and plan dosimetry. Methods and MaterialsPaired MRI and CT scans of 40 patients were used for sCT generation and validation. Bulk density assignment, tissue class density assignment, hybrid atlas, and deep learning sCT generation methods were applied to all 40 patients. Dosimetric accuracy was assessed by dose difference at reference point, dose volume histogram (DVH) parameters, and 3D gamma dose comparison. HU estimation was assessed by mean error and mean absolute error in HU value between each sCT and CT. ResultsThe median percentage dose difference between the CT and sCT was <1.0% for all sCT methods. The deep learning method resulted in the lowest median percentage dose difference to CT at -0.03% (IQR 0.13, -0.31) and bulk density assignment resulted in the greatest difference at -0.73% (IQR -0.10, -1.01). The mean 3D gamma dose agreement at 3%/2 mm among all sCT methods was 99.8%. The highest agreement at 1%/1 mm was 97.3% for the deep learning method and the lowest was 93.6% for the bulk density method. Deep learning and hybrid atlas techniques gave the lowest difference to CT in mean error and mean absolute error in HU estimation. ConclusionsAll methods of sCT generation used in this study resulted in similarly high dosimetric agreement for MRI-only planning of male and female cancer pelvic regions. The choice of the sCT generation technique can be guided by department resources available and image guidance considerations, with minimal impact on dosimetric accuracy.
引用
收藏
页数:10
相关论文
共 37 条
[1]   Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region [J].
Arabi, Hossein ;
Dowling, Jason A. ;
Burgos, Ninon ;
Han, Xiao ;
Greer, Peter B. ;
Koutsouvelis, Nikolaos ;
Zaidi, Habib .
MEDICAL PHYSICS, 2018, 45 (11) :5218-5233
[2]   Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning [J].
Arabi, Hossein ;
Koutsouvelis, Nikolaos ;
Rouzaud, Michel ;
Miralbell, Raymond ;
Zaidi, Habib .
PHYSICS IN MEDICINE AND BIOLOGY, 2016, 61 (17) :6531-6552
[3]   Multicentre, deep learning, synthetic-CT generation for ano-rectal MR-only radiotherapy treatment planning [J].
Bird, David ;
Nix, Michael G. ;
McCallum, Hazel ;
Teo, Mark ;
Gilbert, Alexandra ;
Casanova, Nathalie ;
Cooper, Rachel ;
Buckley, David L. ;
Sebag-Montefiore, David ;
Speight, Richard ;
Al-Qaisieh, Bashar ;
Henry, Ann M. .
RADIOTHERAPY AND ONCOLOGY, 2021, 156 :23-28
[4]  
Cancer Institute NSW, 2019, CLIN RES GYN END ADJ
[5]  
Cancer Institute NSW, 2021, CLIN RES COL RECT NE
[6]   Bulk Anatomical Density Based Dose Calculation for Patient-Specific Quality Assurance of MRI-Only Prostate Radiotherapy [J].
Choi, Jae Hyuk ;
Lee, Danny ;
O'Connor, Laura ;
Chalup, Stephan ;
Welsh, James S. ;
Dowling, Jason ;
Greer, Peter B. .
FRONTIERS IN ONCOLOGY, 2019, 9
[7]   An evaluation of four CT-MRI co-registration techniques for radiotherapy treatment planning of prone rectal cancer patients [J].
Dean, C. J. ;
Sykes, J. R. ;
Cooper, R. A. ;
Hatfield, P. ;
Carey, B. ;
Swift, S. ;
Bacon, S. E. ;
Thwaites, D. ;
Sebag-Montefiore, D. ;
Morgan, A. M. .
BRITISH JOURNAL OF RADIOLOGY, 2012, 85 (1009) :61-68
[8]   Automatic Substitute Computed Tomography Generation and Contouring for Magnetic Resonance Imaging (MRI)-Alone External Beam Radiation Therapy From Standard MRI Sequences [J].
Dowling, Jason A. ;
Sun, Jidi ;
Pichler, Peter ;
Rivest-Henault, David ;
Ghose, Soumya ;
Richardson, Haylea ;
Wratten, Chris ;
Martin, Jarad ;
Arm, Jameen ;
Best, Leah ;
Chandra, Shekhar S. ;
Fripp, Jurgen ;
Menk, Frederick W. ;
Greer, Peter B. .
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2015, 93 (05) :1144-1153
[9]   An Atlas-Based Electron Density Mapping Method for Magnetic Resonance Imaging (MRI)-Alone Treatment Planning and Adaptive MRI-Based Prostate Radiation Therapy [J].
Dowling, Jason A. ;
Lambert, Jonathan ;
Parker, Joel ;
Salvado, Olivier ;
Fripp, Jurgen ;
Capp, Anne ;
Wratten, Chris ;
Denham, James W. ;
Greer, Peter B. .
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2012, 83 (01) :E5-E11
[10]  
Goodfellow IJ, 2014, ADV NEUR IN, V27, P2672