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Dowling JA, Sun J, Pichler P, Rivest-Hénault D, Ghose S, Richardson H, Wratten C, Martin J, Arm J, Best L, Chandra SS, Fripp J, Menk FW, Greer PB. Automatic Substitute Computed Tomography Generation and Contouring for Magnetic Resonance Imaging (MRI)-Alone External Beam Radiation Therapy From Standard MRI Sequences. Int J Radiat Oncol Biol Phys 2015; 93:1144-53. [PMID: 26581150 DOI: 10.1016/j.ijrobp.2015.08.045] [Citation(s) in RCA: 119] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 08/05/2015] [Accepted: 08/25/2015] [Indexed: 11/28/2022]
Abstract
PURPOSE To validate automatic substitute computed tomography CT (sCT) scans generated from standard T2-weighted (T2w) magnetic resonance (MR) pelvic scans for MR-Sim prostate treatment planning. PATIENTS AND METHODS A Siemens Skyra 3T MR imaging (MRI) scanner with laser bridge, flat couch, and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole-pelvis MRI scan (1.6 mm 3-dimensional isotropic T2w SPACE [Sampling Perfection with Application optimized Contrasts using different flip angle Evolution] sequence) was acquired. Three additional small field of view scans were acquired: T2w, T2*w, and T1w flip angle 80° for gold fiducials. Patients received a routine planning CT scan. Manual contouring of the prostate, rectum, bladder, and bones was performed independently on the CT and MR scans. Three experienced observers contoured each organ on MRI, allowing interobserver quantification. To generate a training database, each patient CT scan was coregistered to their whole-pelvis T2w using symmetric rigid registration and structure-guided deformable registration. A new multi-atlas local weighted voting method was used to generate automatic contours and sCT results. RESULTS The mean error in Hounsfield units between the sCT and corresponding patient CT (within the body contour) was 0.6 ± 14.7 (mean ± 1 SD), with a mean absolute error of 40.5 ± 8.2 Hounsfield units. Automatic contouring results were very close to the expert interobserver level (Dice similarity coefficient): prostate 0.80 ± 0.08, bladder 0.86 ± 0.12, rectum 0.84 ± 0.06, bones 0.91 ± 0.03, and body 1.00 ± 0.003. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same dose prescription was found to be 0.3% ± 0.8%. The 3-dimensional γ pass rate was 1.00 ± 0.00 (2 mm/2%). CONCLUSIONS The MR-Sim setup and automatic sCT generation methods using standard MR sequences generates realistic contours and electron densities for prostate cancer radiation therapy dose planning and digitally reconstructed radiograph generation.
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Affiliation(s)
- Jason A Dowling
- CSIRO Australian e-Health Research Centre, Herston, Queensland, Australia; University of Newcastle, Callaghan, New South Wales, Australia.
| | - Jidi Sun
- University of Newcastle, Callaghan, New South Wales, Australia
| | - Peter Pichler
- Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | | | - Soumya Ghose
- CSIRO Australian e-Health Research Centre, Herston, Queensland, Australia
| | - Haylea Richardson
- Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | - Chris Wratten
- University of Newcastle, Callaghan, New South Wales, Australia; Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | - Jarad Martin
- University of Newcastle, Callaghan, New South Wales, Australia; Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | - Jameen Arm
- Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | - Leah Best
- Department of Radiology, Hunter New England Health, New Lambton, New South Wales, Australia
| | - Shekhar S Chandra
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Queensland, Australia
| | - Jurgen Fripp
- CSIRO Australian e-Health Research Centre, Herston, Queensland, Australia
| | | | - Peter B Greer
- University of Newcastle, Callaghan, New South Wales, Australia; Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
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154
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Edmund JM, Andreasen D, Mahmood F, Van Leemput K. Cone beam computed tomography guided treatment delivery and planning verification for magnetic resonance imaging only radiotherapy of the brain. Acta Oncol 2015. [PMID: 26198652 DOI: 10.3109/0284186x.2015.1062546] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND Radiotherapy based on MRI only (MRI-only RT) shows a promising potential for the brain. Much research focuses on creating a pseudo computed tomography (pCT) from MRI for treatment planning while little attention is often paid to the treatment delivery. Here, we investigate if cone beam CT (CBCT) can be used for MRI-only image-guided radiotherapy (IGRT) and for verifying the correctness of the corresponding pCT. MATERIAL AND METHODS Six patients receiving palliative cranial RT were included in the study. Each patient had three-dimensional (3D) T1W MRI, a CBCT and a CT for reference. Further, a pCT was generated using a patch-based approach. MRI, pCT and CT were placed in the same frame of reference, matched to CBCT and the differences noted. Paired pCT-CT and pCT-CBCT data were created in bins of 10 HU and the absolute difference calculated. The data were converted to relative electron densities (RED) using the CT or a CBCT calibration curve. The latter was either based on a CBCT phantom (phan) or a paired CT-CBCT population (pop) of the five other patients. RESULTS Non-significant (NS) differences in the pooled CT-CBCT, MRI-CBCT and pCT-CBCT transformations were noted. The largest deviations from the CT-CBCT reference were < 1 mm and 1°. The average median absolute error (MeAE) in HU was 184 ± 34 and 299 ± 34 on average for pCT-CT and pCT-CBCT, respectively, and was significantly different (p < 0.01) in each patient. The average MeAE in RED was 0.108 ± 0.025, 0.104 ± 0.011 and 0.099 ± 0.017 for pCT-CT, pCT-CBCT phan (p < 0.01 on 2 patients) and pCT-CBCT pop (NS), respectively. CONCLUSIONS CBCT can be used for patient setup with either MRI or pCT as reference. The correctness of pCT can be verified from CBCT using a population-based calibration curve in the treatment geometry.
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Affiliation(s)
- Jens M Edmund
- a Radiotherapy Research Unit, Department of Oncology , Gentofte and Herlev Hospital, University of Copenhagen , Herlev , Denmark
| | - Daniel Andreasen
- a Radiotherapy Research Unit, Department of Oncology , Gentofte and Herlev Hospital, University of Copenhagen , Herlev , Denmark
- b DTU Compute, Technical University of Denmark , Lyngby , Denmark
| | - Faisal Mahmood
- a Radiotherapy Research Unit, Department of Oncology , Gentofte and Herlev Hospital, University of Copenhagen , Herlev , Denmark
| | - Koen Van Leemput
- b DTU Compute, Technical University of Denmark , Lyngby , Denmark
- c Department of Radiology , Harvard Medical School, Massachusetts General Hospital , Boston , USA
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155
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Militello C, Vitabile S, Rundo L, Russo G, Midiri M, Gilardi MC. A fully automatic 2D segmentation method for uterine fibroid in MRgFUS treatment evaluation. Comput Biol Med 2015; 62:277-92. [DOI: 10.1016/j.compbiomed.2015.04.030] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Revised: 04/01/2015] [Accepted: 04/18/2015] [Indexed: 11/17/2022]
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156
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Thorwarth D. Functional imaging for radiotherapy treatment planning: current status and future directions-a review. Br J Radiol 2015; 88:20150056. [PMID: 25827209 PMCID: PMC4628531 DOI: 10.1259/bjr.20150056] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
In recent years, radiotherapy (RT) has been subject to a number of technological innovations. Today, RT is extremely flexible, allowing irradiation of tumours with high doses, whilst also sparing normal tissues from doses. To make use of these additional degrees of freedom, integration of functional image information may play a key role (i) for better staging and tumour detection, (ii) for more accurate RT target volume delineation, (iii) to assess functional information about biological characteristics and individual radiation resistance and (iv) to apply personalized dose prescriptions. In this article, we discuss the current status and future directions of different clinically available functional imaging modalities; CT, MRI, positron emission tomography (PET) as well as the hybrid imaging techniques PET/CT and PET/MRI and their potential for individualized RT.
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Affiliation(s)
- D Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, Eberhard Karls University Tübingen, Tübingen, Germany
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