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Touati R, Trung Le W, Kadoury S. Multi-planar dual adversarial network based on dynamic 3D features for MRI-CT head and neck image synthesis. Phys Med Biol 2024; 69:155012. [PMID: 38981593 DOI: 10.1088/1361-6560/ad611a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/09/2024] [Indexed: 07/11/2024]
Abstract
Objective.Head and neck radiotherapy planning requires electron densities from different tissues for dose calculation. Dose calculation from imaging modalities such as MRI remains an unsolved problem since this imaging modality does not provide information about the density of electrons.Approach.We propose a generative adversarial network (GAN) approach that synthesizes CT (sCT) images from T1-weighted MRI acquisitions in head and neck cancer patients. Our contribution is to exploit new features that are relevant for improving multimodal image synthesis, and thus improving the quality of the generated CT images. More precisely, we propose a Dual branch generator based on the U-Net architecture and on an augmented multi-planar branch. The augmented branch learns specific 3D dynamic features, which describe the dynamic image shape variations and are extracted from different view-points of the volumetric input MRI. The architecture of the proposed model relies on an end-to-end convolutional U-Net embedding network.Results.The proposed model achieves a mean absolute error (MAE) of18.76±5.167in the target Hounsfield unit (HU) space on sagittal head and neck patients, with a mean structural similarity (MSSIM) of0.95±0.09and a Frechet inception distance (FID) of145.60±8.38. The model yields a MAE of26.83±8.27to generate specific primary tumor regions on axial patient acquisitions, with a Dice score of0.73±0.06and a FID distance equal to122.58±7.55. The improvement of our model over other state-of-the-art GAN approaches is of 3.8%, on a tumor test set. On both sagittal and axial acquisitions, the model yields the best peak signal-to-noise ratio of27.89±2.22and26.08±2.95to synthesize MRI from CT input.Significance.The proposed model synthesizes both sagittal and axial CT tumor images, used for radiotherapy treatment planning in head and neck cancer cases. The performance analysis across different imaging metrics and under different evaluation strategies demonstrates the effectiveness of our dual CT synthesis model to produce high quality sCT images compared to other state-of-the-art approaches. Our model could improve clinical tumor analysis, in which a further clinical validation remains to be explored.
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Affiliation(s)
- Redha Touati
- MedICAL Laboratory, Polytechnique Montreal, Montreal, QC, Canada
| | - William Trung Le
- MedICAL Laboratory, Polytechnique Montreal, Montreal, QC, Canada
| | - Samuel Kadoury
- MedICAL Laboratory, Polytechnique Montreal, Montreal, QC, Canada
- CHUM Research Center, Montreal, QC, Canada
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Damyanovich AZ, Tadic T, Foltz WD, Jelveh S, Bissonnette JP. Time-course assessment of 3D-image distortion on the 1.5 T Marlin/Elekta Unity MR-LINAC. Phys Med 2022; 100:90-98. [PMID: 35777256 DOI: 10.1016/j.ejmp.2022.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 04/04/2022] [Accepted: 05/25/2022] [Indexed: 11/29/2022] Open
Abstract
PURPOSE The efficacy of MR-guided radiotherapy on a MR-LINAC (MR-L) is dependent on the geometric accuracy of its MR images over clinically relevant Fields-of-View (FOVs). Our objectives were to: evaluate gradient non-linearity (GNL) on the Elekta Unity MR-L across time via 76 weekly measurements of 3D-distortion over concentrically larger diameter spherical volumes (DSVs); quantify distortion measurement error; and assess the temporal stability of spatial distortion using statistical process control (SPC). METHODS MR-image distortion was assessed using a large-FOV 3D-phantom containing 1932 markers embedded in seven parallel plates, spaced 25 mm × 25 mm in- and 55 mm through-plane. Automatically analyzed T1 images yielded distortions in 200, 300, 400 and 500 mm concentric DSVs. Distortion measurement error was evaluated using median absolute difference analysis of imaging repeatability tests. RESULTS Over the measurement period absolute time-averaged distortion varied between: dr = 0.30 - 0.49 mm, 0.53 - 0.80 mm, 1.0 - 1.4 mm and 2.28 - 2.37 mm, for DSVs 200, 300, 400 and 500 mm at the 98th percentile level. Repeatability tests showed that imaging/repositioning introduces negligible error: mean ≤ 0.02 mm (max ≤ 0.3 mm). SPC analysis showed image distortion was stable across all DSVs; however, noticeable changes in GNL were observed following servicing at the one-year mark. CONCLUSIONS Image distortion on the MR-L is in the sub-millimeter range for DSVs ≤ 300 mm and stable across time, with SPC analysis indicating all measurements remain within control for each DSV.
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Affiliation(s)
- Andrei Z Damyanovich
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; Techna Institute, Toronto, Ontario, Canada.
| | - Tony Tadic
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; Techna Institute, Toronto, Ontario, Canada
| | - Warren D Foltz
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; Techna Institute, Toronto, Ontario, Canada
| | - Salomeh Jelveh
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada
| | - Jean-Pierre Bissonnette
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; Techna Institute, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
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Anto GJ, Sekaran S, Perumal B, Ramar N, Vaitheeswaran R, Karthikeyan SK. A study to determine the impact of IMPT optimization techniques on prostate synthetic CT image sets dose comparison against CT image sets. Rep Pract Oncol Radiother 2022; 27:161-169. [PMID: 35402035 PMCID: PMC8989438 DOI: 10.5603/rpor.a2022.0015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 01/20/2022] [Indexed: 11/25/2022] Open
Abstract
Background The objective of this study is to determine the impact of intensity modulated proton therapty (IMPT) optimization techniques on the proton dose comparison of commercially available magnetic resonance for calculating attenuation (MRCA T) images, a synthetic computed tomography CT (sCT) based on magnetic resonance imaging (MRI) scan against the CT images and find out the optimization technique which creates plans with the least dose differences against the regular CT image sets. Material and methods Regular CT data sets and sCT image sets were obtained for 10 prostate patients for the study. Six plans were created using six distinct IMPT optimization techniques including multi-field optimization (MFO), single field uniform dose (SFUD) optimization, and robust optimization (RO) in CT image sets. These plans were copied to MRCA T, sCT datasets and doses were computed. Doses from CT and MRCA T data sets were compared for each patient using 2D dose distribution display, dose volume histograms (DVH), homogeneity index (HI), conformation number (CN) and 3D gamma analysis. A two tailed t-test was conducted on HI and CN with 5% significance level with a null hypothesis for CT and sCT image sets. Results Analysis of ten CT and sCT image sets with different IMPT optimization techniques shows that a few of the techniques show significant differences between plans for a few evaluation parameters. Isodose lines, DVH, HI, CN and t-test analysis shows that robust optimizations with 2% range error incorporated results in plans, when re-computed in sCT image sets results in the least dose differences against CT plans compared to other optimization techniques. The second best optimization technique with the least dose differences was robust optimization with 5% range error. Conclusion This study affirmatively demonstrates the impact of IMPT optimization techniques on synthetic CT image sets dose comparison against CT images and determines the robust optimization with 2% range error as the optimization technique which gives the least dose difference when compared to CT plans.
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Affiliation(s)
- Gipson Joe Anto
- Department of Medical Physics, Bharathiar University, Coimbatore, India
| | - Sureka Sekaran
- Department of Medical Physics, Bharathiar University, Coimbatore, India
| | - Bojarajan Perumal
- Department of Medical Physics, Bharathiar University, Coimbatore, India
| | - Natarajan Ramar
- Department of Physics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, India
| | - R Vaitheeswaran
- Department of Medical Physics, Bharathiar University, Coimbatore, India
| | - S K Karthikeyan
- Department of Medical Physics, Bharathiar University, Coimbatore, India
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Touati R, Le WT, Kadoury S. A feature invariant generative adversarial network for head and neck MRI/CT image synthesis. Phys Med Biol 2021; 66. [PMID: 33761478 DOI: 10.1088/1361-6560/abf1bb] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 03/24/2021] [Indexed: 12/12/2022]
Abstract
With the emergence of online MRI radiotherapy treatments, MR-based workflows have increased in importance in the clinical workflow. However proper dose planning still requires CT images to calculate dose attenuation due to bony structures. In this paper, we present a novel deep image synthesis model that generates in an unsupervised manner CT images from diagnostic MRI for radiotherapy planning. The proposed model based on a generative adversarial network (GAN) consists of learning a new invariant representation to generate synthetic CT (sCT) images based on high frequency and appearance patterns. This new representation encodes each convolutional feature map of the convolutional GAN discriminator, leading the training of the proposed model to be particularly robust in terms of image synthesis quality. Our model includes an analysis of common histogram features in the training process, thus reinforcing the generator such that the output sCT image exhibits a histogram matching that of the ground-truth CT. This CT-matched histogram is embedded then in a multi-resolution framework by assessing the evaluation over all layers of the discriminator network, which then allows the model to robustly classify the output synthetic image. Experiments were conducted on head and neck images of 56 cancer patients with a wide range of shape sizes and spatial image resolutions. The obtained results confirm the efficiency of the proposed model compared to other generative models, where the mean absolute error yielded by our model was 26.44(0.62), with a Hounsfield unit error of 45.3(1.87), and an overall Dice coefficient of 0.74(0.05), demonstrating the potential of the synthesis model for radiotherapy planning applications.
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Affiliation(s)
- Redha Touati
- MedICAL Laboratory, Polytechnique Montreal, Montreal, QC, Canada
| | - William Trung Le
- MedICAL Laboratory, Polytechnique Montreal, Montreal, QC, Canada
| | - Samuel Kadoury
- MedICAL Laboratory, Polytechnique Montreal, Montreal, QC, Canada.,CHUM Research Center, Montreal, QC, Canada
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Zhou Y, Yuan J, Wong OL, Fung WWK, Cheng KF, Cheung KY, Yu SK. Assessment of positional reproducibility in the head and neck on a 1.5-T MR simulator for an offline MR-guided radiotherapy solution. Quant Imaging Med Surg 2018; 8:925-935. [PMID: 30505721 DOI: 10.21037/qims.2018.10.03] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Recently, a shuttle-based offline magnetic resonance-guided radiotherapy (MRgRT) approach was proposed. This study aims to evaluate the positional reproducibility in the immobilized head and neck using a 1.5-T MR-simulator (MR-sim) on healthy volunteers. Methods A total of 159 scans of 14 healthy volunteers were conducted on a 1.5-T MR-sim with thermoplastic mask immobilization. MR images with isotropic 1.053 mm3 voxel size were rigidly registered to the first scan based on fiducial, anatomical and gross positions. Mean and standard deviation of positional displacements in translation and rotation were assessed. Systematic error and random errors of positioning in the head and neck on the MR-sim were determined in the translation of, and in the rotation of roll, pitch and yaw. Results The systematic error (Σ) of translation in left-right (LR), anterior-posterior (AP) and superior-inferior (SI) direction was 0.57, 0.22 and 0.26 mm for fiducial displacement, 0.28, 0.10 and 0.52 mm for anatomical displacement, and 0.53, 0.22 and 0.49 mm for gross displacement, respectively. The random error (σ) in corresponding translation direction was 2.07, 0.54 and 1.32 mm for fiducial displacement, 1.34, 0.73 and 2.04 mm for anatomical displacement, and 2.24, 0.86 and 2.61 mm for gross displacement. The systematic error and random error of rotation were generally smaller than 1°. Conclusions Our results suggested that high gross positional reproducibility (<1 mm translational and <1° rotational systematic error) could be achieved on an MR-sim for the proposed offline MRgRT.
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Affiliation(s)
- Yihang Zhou
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Jing Yuan
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Oi Lei Wong
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Winky Wing Ki Fung
- Department of Radiotherapy, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Ka Fai Cheng
- Department of Radiotherapy, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Kin Yin Cheung
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Siu Ki Yu
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
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Adjeiwaah M, Bylund M, Lundman JA, Söderström K, Zackrisson B, Jonsson JH, Garpebring A, Nyholm T. Dosimetric Impact of MRI Distortions: A Study on Head and Neck Cancers. Int J Radiat Oncol Biol Phys 2018; 103:994-1003. [PMID: 30496879 DOI: 10.1016/j.ijrobp.2018.11.037] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 11/13/2018] [Accepted: 11/19/2018] [Indexed: 10/27/2022]
Abstract
PURPOSE To evaluate the effect of magnetic resonance (MR) imaging (MRI) geometric distortions on head and neck radiation therapy treatment planning (RTP) for an MRI-only RTP. We also assessed the potential benefits of patient-specific shimming to reduce the magnitude of MR distortions for a 3-T scanner. METHODS AND MATERIALS Using an in-house Matlab algorithm, shimming within entire imaging volumes and user-defined regions of interest were simulated. We deformed 21 patient computed tomography (CT) images with MR distortion fields (gradient nonlinearity and patient-induced susceptibility effects) to create distorted CT (dCT) images using bandwidths of 122 and 488 Hz/mm at 3 T. Field parameters from volumetric modulated arc therapy plans initially optimized on dCT data sets were transferred to CT data to compute a new plan. Both plans were compared to determine the impact of distortions on dose distributions. RESULTS Shimming across entire patient volumes decreased the percentage of voxels with distortions of more than 2 mm from 15.4% to 2.0%. Using the user-defined region of interest (ROI) shimming strategy, (here the Planning target volume (PTV) was the chosen ROI volume) led to increased geometric for volumes outside the PTV, as such voxels within the spinal cord with geometric shifts above 2 mm increased from 11.5% to 32.3%. The worst phantom-measured residual system distortions after 3-dimensional gradient nonlinearity correction within a radial distance of 200 mm from the isocenter was 2.17 mm. For all patients, voxels with distortion shifts of more than 2 mm resulting from patient-induced susceptibility effects were 15.4% and 0.0% using bandwidths of 122 Hz/mm and 488 Hz/mm at 3 T. Dose differences between dCT and CT treatment plans in D50 at the planning target volume were 0.4% ± 0.6% and 0.3% ± 0.5% at 122 and 488 Hz/mm, respectively. CONCLUSIONS The overall effect of MRI geometric distortions on data used for RTP was minimal. Shimming over entire imaging volumes decreased distortions, but user-defined subvolume shimming introduced significant errors in nearby organs and should probably be avoided.
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Affiliation(s)
- Mary Adjeiwaah
- Department of Radiation Sciences, Umeå University, Umeå, Sweden.
| | - Mikael Bylund
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Josef A Lundman
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | | | | | | | | | - Tufve Nyholm
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
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Magnetic resonance imaging in radiotherapy treatment target volumes definition for brain tumours: a systematic review and meta-analysis. JOURNAL OF RADIOTHERAPY IN PRACTICE 2018. [DOI: 10.1017/s1460396917000693] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
AbstractPurposeThe aim of this study is to establish clinical evidence regarding the use of magnetic resonance imaging (MRI) in target volume definition for radiotherapy treatment planning of brain tumours.MethodsPrimary studies were systematically retrieved from six electronic databases and other sources. Studies included were only those that quantitatively compared computed tomography (CT) and MRI in target volume definition for radiotherapy of brain tumours. Study characteristics and quality were assessed and the data were extracted from eligible studies. Effect estimates for each study was computed as mean percentage difference based on individual patient data where available. The included studies were then combined in meta-analysis using Review Manager (RevMan) software version 5.0.ResultFive studies with a total number of 72 patients were included in this review. The quality of the studies was rated strong. The percentages mean differences of the studies were 7·47, 11·36, 30·70, 41·69 and −24·6% using CT as the baseline. The result of statistical analysis showed small-to-moderate heterogeneity; τ2=36·8; χ2=6·23; df=4 (p=0·18); I2=36%. The overall effect estimate was −1·85 [95% confidence interval (CI); −7·24, 10·94], Z=0·40 (p=0·069>0·5).ConclusionBrain tumour volumes measured using MRI-based method for radiotherapy treatment planning were larger compared with CT defined volumes but the difference lacks statistical significance.
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Muller M, Paganelli C, Keall P. A phantom study to create synthetic CT from orthogonal twodimensional cine MRI and evaluate the effect of irregular breathing. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2018:4162-4165. [PMID: 30441272 DOI: 10.1109/embc.2018.8513236] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
An exciting innovation in radiotherapy is the use of real-time MRI for treatment adaptation. This study proposes an in-silico framework for the generation of 3D synthetic CT (sCT) from orthogonal interleaved 2D cine MRI data to overcome the lack of electron density information in MR images. The method uses pre-treatment data to build a patient breathing motion model. This model is then driven by surrogates extracted from cine MR images during the treatment. The effect of irregular breathing on the motion model is also evaluated by simulating different motion components related to uncorrelated diaphragm, chest and tumor motion. 3D sCT were successfully created for each of the 512 cine MRI pairs in the digital phantom study. The analysis showed that the diaphragm position was a good surrogate to rescale the 3D breathing motion for the current regular breathing phase. However, respiratory and tumor motion were correlated in only 59% of the phases, resulting in tumor position uncertainties of up to 3mm. The inclusion of additional chest and tumor motion information improved the accuracy for irregular changes in breathing pattern and enhanced the tumor position uncertainties to less than 1mm. This study successfully demonstrated a proof-ofprinciple for a digital phantom dataset based on patient parameters, providing a way to create real-time 3D electron density volumes and enhancing the need to account for irregular breathing pattern.
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Damyanovich AZ, Rieker M, Zhang B, Bissonnette JP, Jaffray DA. Design and implementation of a 3D-MR/CT geometric image distortion phantom/analysis system for stereotactic radiosurgery. ACTA ACUST UNITED AC 2018; 63:075010. [DOI: 10.1088/1361-6560/aab33e] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Ghose S, Greer PB, Sun J, Pichler P, Rivest-Henault D, Mitra J, Richardson H, Wratten C, Martin J, Arm J, Best L, Dowling JA. Regression and statistical shape model based substitute CT generation for MRI alone external beam radiation therapy from standard clinical MRI sequences. Phys Med Biol 2017; 62:8566-8580. [PMID: 28976369 DOI: 10.1088/1361-6560/aa9104] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
In MR only radiation therapy planning, generation of the tissue specific HU map directly from the MRI would eliminate the need of CT image acquisition and may improve radiation therapy planning. The aim of this work is to generate and validate substitute CT (sCT) scans generated from standard T2 weighted MR pelvic scans in prostate radiation therapy dose planning. A Siemens Skyra 3T 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 (1.6 mm 3D isotropic T2w SPACE sequence) was acquired. Patients received a routine planning CT scan. Co-registered whole pelvis CT and T2w MRI pairs were used as training images. Advanced tissue specific non-linear regression models to predict HU for the fat, muscle, bladder and air were created from co-registered CT-MRI image pairs. On a test case T2w MRI, the bones and bladder were automatically segmented using a novel statistical shape and appearance model, while other soft tissues were separated using an Expectation-Maximization based clustering model. The CT bone in the training database that was most 'similar' to the segmented bone was then transformed with deformable registration to create the sCT component of the test case T2w MRI bone tissue. Predictions for the bone, air and soft tissue from the separate regression models were successively combined to generate a whole pelvis sCT. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same IMRT dose plan was found to be [Formula: see text] (mean ± standard deviation) for 39 patients. The 3D Gamma pass rate was [Formula: see text] (2 mm/2%). The novel hybrid model is computationally efficient, generating an sCT in 20 min from standard T2w images for prostate cancer radiation therapy dose planning and DRR generation.
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Affiliation(s)
- Soumya Ghose
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
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Johnstone E, Wyatt JJ, Henry AM, Short SC, Sebag-Montefiore D, Murray L, Kelly CG, McCallum HM, Speight R. Systematic Review of Synthetic Computed Tomography Generation Methodologies for Use in Magnetic Resonance Imaging-Only Radiation Therapy. Int J Radiat Oncol Biol Phys 2017; 100:199-217. [PMID: 29254773 DOI: 10.1016/j.ijrobp.2017.08.043] [Citation(s) in RCA: 210] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 07/07/2017] [Accepted: 08/30/2017] [Indexed: 10/18/2022]
Abstract
Magnetic resonance imaging (MRI) offers superior soft-tissue contrast as compared with computed tomography (CT), which is conventionally used for radiation therapy treatment planning (RTP) and patient positioning verification, resulting in improved target definition. The 2 modalities are co-registered for RTP; however, this introduces a systematic error. Implementing an MRI-only radiation therapy workflow would be advantageous because this error would be eliminated, the patient pathway simplified, and patient dose reduced. Unlike CT, in MRI there is no direct relationship between signal intensity and electron density; however, various methodologies for MRI-only RTP have been reported. A systematic review of these methods was undertaken. The PRISMA guidelines were followed. Embase and Medline databases were searched (1996 to March, 2017) for studies that generated synthetic CT scans (sCT)s for MRI-only radiation therapy. Sixty-one articles met the inclusion criteria. This review showed that MRI-only RTP techniques could be grouped into 3 categories: (1) bulk density override; (2) atlas-based; and (3) voxel-based techniques, which all produce an sCT scan from MR images. Bulk density override techniques either used a single homogeneous or multiple tissue override. The former produced large dosimetric errors (>2%) in some cases and the latter frequently required manual bone contouring. Atlas-based techniques used both single and multiple atlases and included methods incorporating pattern recognition techniques. Clinically acceptable sCTs were reported, but atypical anatomy led to erroneous results in some cases. Voxel-based techniques included methods using routine and specialized MRI sequences, namely ultra-short echo time imaging. High-quality sCTs were produced; however, use of multiple sequences led to long scanning times increasing the chances of patient movement. Using nonroutine sequences would currently be problematic in most radiation therapy centers. Atlas-based and voxel-based techniques were found to be the most clinically useful methods, with some studies reporting dosimetric differences of <1% between planning on the sCT and CT and <1-mm deviations when using sCTs for positional verification.
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Affiliation(s)
- Emily Johnstone
- Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, United Kingdom.
| | - Jonathan J Wyatt
- The Northern Centre for Cancer Care, The Newcastle-upon-Tyne NHS Foundation Trust, Newcastle-upon-Tyne, United Kingdom
| | - Ann M Henry
- Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, United Kingdom; Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Susan C Short
- Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, United Kingdom; Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - David Sebag-Montefiore
- Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, United Kingdom; Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Louise Murray
- Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, United Kingdom; Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Charles G Kelly
- The Northern Centre for Cancer Care, The Newcastle-upon-Tyne NHS Foundation Trust, Newcastle-upon-Tyne, United Kingdom
| | - Hazel M McCallum
- The Northern Centre for Cancer Care, The Newcastle-upon-Tyne NHS Foundation Trust, Newcastle-upon-Tyne, United Kingdom
| | - Richard Speight
- Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
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Soliman AS, Burns L, Owrangi A, Lee Y, Song WY, Stanisz G, Chugh BP. A realistic phantom for validating MRI-based synthetic CT images of the human skull. Med Phys 2017. [PMID: 28644905 DOI: 10.1002/mp.12428] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To introduce a new realistic human skull phantom for the validation of synthetic CT images of cortical bone from ultra-short echo-time (UTE) sequences. METHODS A human skull of an adult female was utilized as a realistic representation of skull cortical bone. The skull was stabilized in a special acrylic container and was filled with contrast agents that have T1 and T2 relaxation times similar to human brain. The phantom was MR scanned at 3T with UTE and T2 -weighted sequences, followed by CT. A clustering approach was developed to extract the cortical bone signal from MR images. T2∗ maps of the skull were calculated. Synthetic CT images of the bone were compared to cortical bone signal extracted from CT images and confounding factors, such as registration errors, were analyzed. RESULTS Dice similarity coefficient (DSC) of UTE-detected cortical bone was 0.84 and gradually decreased with decreasing number of spokes. DSC did not significantly depend on echo-time. Registration errors were found to be significant confounding factors, with 25% decrease in DSC for consistent 2 mm error at each axis. CONCLUSION This work introduced a new realistic human skull phantom, specifically for the evaluation and analysis of synthetic CT images of cortical bone.
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Affiliation(s)
- Abraam S Soliman
- Medical Physics, Sunnybrook Health Sciences Centre, Toronto, ON, M4N 3M5, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, ON, M4N 3M5, Canada
| | - Levi Burns
- Medical Physics, Sunnybrook Health Sciences Centre, Toronto, ON, M4N 3M5, Canada.,Physics and Astronomy, University of British Columbia, Vancouver, BC, V6T 1Z1, Canada
| | - Amir Owrangi
- Medical Physics, Sunnybrook Health Sciences Centre, Toronto, ON, M4N 3M5, Canada.,Radiation Oncology, University of Toronto, Toronto, ON, M5S 3E2, Canada
| | - Young Lee
- Medical Physics, Sunnybrook Health Sciences Centre, Toronto, ON, M4N 3M5, Canada.,Radiation Oncology, University of Toronto, Toronto, ON, M5S 3E2, Canada
| | - William Y Song
- Medical Physics, Sunnybrook Health Sciences Centre, Toronto, ON, M4N 3M5, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, ON, M4N 3M5, Canada.,Radiation Oncology, University of Toronto, Toronto, ON, M5S 3E2, Canada
| | - Greg Stanisz
- Medical Physics, Sunnybrook Health Sciences Centre, Toronto, ON, M4N 3M5, Canada.,Physical Sciences, Sunnybrook Research Institute, Toronto, ON, M4N 3M5, Canada.,Medical Biophysics, University of Toronto, Toronto, ON, M4N 3M5, Canada
| | - Brige P Chugh
- Medical Physics, Sunnybrook Health Sciences Centre, Toronto, ON, M4N 3M5, Canada.,Radiation Oncology, University of Toronto, Toronto, ON, M5S 3E2, Canada
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13
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Arivarasan I, Anuradha C, Subramanian S, Anantharaman A, Ramasubramanian V. Magnetic resonance image guidance in external beam radiation therapy planning and delivery. Jpn J Radiol 2017; 35:417-426. [DOI: 10.1007/s11604-017-0656-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 05/29/2017] [Indexed: 12/14/2022]
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14
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Ghose S, Dowling JA, Rai R, Liney GP. Substitute CT generation from a single ultra short time echo MRI sequence: preliminary study. Phys Med Biol 2017; 62:2950-2960. [PMID: 28306546 DOI: 10.1088/1361-6560/aa508a] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
In MR guided radiation therapy planning both MR and CT images for a patient are acquired and co-registered to obtain a tissue specific HU map. Generation of the HU map directly from the MRI would eliminate the CT acquisition and may improve radiation therapy planning. In this preliminary study of substitute CT (sCT) generation, two porcine leg phantoms were scanned using a 3D ultrashort echo time (PETRA) sequence and co-registered to corresponding CT images to build tissue specific regression models. The model was created from one co-registered CT-PETRA pair to generate the sCT for the other PETRA image. An expectation maximization based clustering was performed on the co-registered PETRA image to identify the soft tissues, dense bone and air class membership probabilities. A tissue specific non linear regression model was built from one registered CT-PETRA pair dataset to predict the sCT of the second PETRA image in a two-fold cross validation schema. A complete substitute CT is generated in 3 min. The mean absolute HU error for air was 0.3 HU, bone was 95 HU, fat was 30 HU and for muscle it was 10 HU. The mean surface reconstruction error for the bone was 1.3 mm. The PETRA sequence enabled a low mean absolute surface distance for the bone and a low HU error for other classes. The sCT generated from a single PETRA sequence shows promise for the generation of fast sCT for MRI based radiation therapy planning.
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Affiliation(s)
- Soumya Ghose
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America
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15
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Kraus KM, Pfaffenberger A, Jäkel O, Debus J, Sterzing F. Evaluation of Dosimetric Robustness of Carbon Ion Boost Therapy for Anal Carcinoma. Int J Part Ther 2017; 3:382-391. [PMID: 31772987 DOI: 10.14338/ijpt-16-00028.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Accepted: 01/13/2017] [Indexed: 12/15/2022] Open
Abstract
Purpose The radiation therapy treatment outcome of human papillomavirus-negative anal carcinoma may be improved by the biological effectiveness of carbon ions. However, abdominal tissue motion can compromise the precision of carbon ion therapy. This work aims to evaluate the dosimetric feasibility of carbon ion boost (CIB) therapy for anal carcinoma. Materials and Methods An algorithm to generate computed tomographies based on daily magnetic resonance imaging data and deformable image registration was developed. By means of this algorithm, fractional computed tomography data for 54 treatment fractions for 3 different patients with anal carcinoma were derived. The dose for a sequential CIB (CIBseq) treatment plan was recalculated on the fractional computed tomography data and accumulated over the number of fractions. The resulting dose distributions were compared to standard intensity-modulated radiation therapy treatment with an integrated photon boost. Results For the investigated patient cases, similar dosimetric results for CIBseq treatment and for intensity-modulated radiation therapy with an integrated photon boost were found. For CIBseq treatment, bladder-filling variation had the strongest influence on the dose distribution. However, the detrimental effects on the mean target dose remained below 1 Gy (RBE) as compared to photon therapy. Conclusion This study shows the dosimetric feasibility of CIB therapy for anal carcinoma for the first time and gives reason for clinical exploitation of the enhanced biological effect of carbon ions for patients with human papillomavirus-negative anal cancer.
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Affiliation(s)
- Kim Melanie Kraus
- Department of Radiation Oncology and Radiation Therapy, University Hospital Heidelberg, Heidelberg, Germany.,Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Asja Pfaffenberger
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oliver Jäkel
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology and Radiation Therapy, University Hospital Heidelberg, Heidelberg, Germany.,Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany
| | - Florian Sterzing
- Department of Radiation Oncology and Radiation Therapy, University Hospital Heidelberg, Heidelberg, Germany.,Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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16
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Kraus KM, Jäkel O, Niebuhr NI, Pfaffenberger A. Generation of synthetic CT data using patient specific daily MR image data and image registration. Phys Med Biol 2017; 62:1358-1377. [DOI: 10.1088/1361-6560/aa5200] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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17
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Ito K, Kadoya N, Nakajima Y, Saito M, Sato K, Nagasaka T, Yamanaka K, Dobashi S, Takeda K, Matsushita H, Jingu K. Feasibility of a Direct-Conversion Method from Magnetic Susceptibility to Relative Electron Density for Radiation Therapy Treatment Planning. ACTA ACUST UNITED AC 2017. [DOI: 10.4236/ijmpcero.2017.63023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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18
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Walker A, Metcalfe P, Liney G, Batumalai V, Dundas K, Glide‐Hurst C, Delaney GP, Boxer M, Yap ML, Dowling J, Rivest‐Henault D, Pogson E, Holloway L. MRI geometric distortion: Impact on tangential whole-breast IMRT. J Appl Clin Med Phys 2016; 17:7-19. [PMID: 28297426 PMCID: PMC5495026 DOI: 10.1120/jacmp.v17i5.6242] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2015] [Accepted: 03/21/2016] [Indexed: 12/04/2022] Open
Abstract
The purpose of this study was to determine the impact of magnetic resonance imaging (MRI) geometric distortions when using MRI for target delineation and planning for whole-breast, intensity-modulated radiotherapy (IMRT). Residual system distortions and combined systematic and patient-induced distortions are considered. This retrospective study investigated 18 patients who underwent whole-breast external beam radiotherapy, where both CT and MRIs were acquired for treatment planning. Distortion phantoms were imaged on two MRI systems, dedicated to radiotherapy planning (a wide, closed-bore 3T and an open-bore 1T). Patient scans were acquired on the 3T system. To simulate MRI-based planning, distortion maps representing residual system distortions were generated via deformable registration between phantom CT and MRIs. Patient CT images and structures were altered to match the residual system distortion measured by the phantoms on each scanner. The patient CTs were also registered to the corresponding patient MRI scans, to assess patient and residual system effects. Tangential IMRT plans were generated and optimized on each resulting CT dataset, then propagated to the original patient CT space. The resulting dose distributions were then evaluated with respect to the standard clinically acceptable DVH and visual assessment criteria. Maximum residual systematic distortion was measured to be 7.9 mm (95%<4.7mm) and 11.9 mm (95%<4.6mm) for the 3T and 1T scanners, respectively, which did not result in clinically unacceptable plans. Eight of the plans accounting for patient and systematic distortions were deemed clinically unacceptable when assessed on the original CT. For these plans, the mean difference in PTV V95 (volume receiving 95% prescription dose) was 0.13±2.51% and -0.73±1.93% for right- and left-sided patients, respectively. Residual system distortions alone had minimal impact on the dosimetry for the two scanners investigated. The combination of MRI systematic and patient-related distortions can result in unacceptable dosimetry for whole-breast IMRT, a potential issue when considering MRI-only radiotherapy treatment planning. PACS number(s): 87.61.-c, 87.57.cp, 87.57.nj, 87.55.D.
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Affiliation(s)
- Amy Walker
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
| | - Peter Metcalfe
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
| | - Gary Liney
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
- Institute of Medical Physics, School of Physics, University of SydneySydneyNSWAustralia
| | - Vikneswary Batumalai
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
| | - Kylie Dundas
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
| | - Carri Glide‐Hurst
- Department of Radiation OncologyHenry Ford Health SystemDetroitMIUSA
| | - Geoff P Delaney
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
- Collaboration for Cancer Outcomes Research and Evaluation, Liverpool HospitalLiverpoolNSWAustralia
- School of Medicine, University of Western SydneySydneyNSWAustralia
| | - Miriam Boxer
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
| | - Mei Ling Yap
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
- Collaboration for Cancer Outcomes Research and Evaluation, Liverpool HospitalLiverpoolNSWAustralia
- School of Medicine, University of Western SydneySydneyNSWAustralia
| | - Jason Dowling
- Commonwealth Scientific and Industrial Research Organisation Computational Informatics, Australian E‐Health Research CentreBrisbaneAustralia
| | - David Rivest‐Henault
- Commonwealth Scientific and Industrial Research Organisation Computational Informatics, Australian E‐Health Research CentreBrisbaneAustralia
| | - Elise Pogson
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
| | - Lois Holloway
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
- Institute of Medical Physics, School of Physics, University of SydneySydneyNSWAustralia
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19
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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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20
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Hu Y, Zhao W, Du D, Wooten HO, Olsen JR, Gay HA, Michalski JM, Mutic S. Magnetic resonance imaging-based treatment planning for prostate cancer: Use of population average tissue densities within the irradiated volume to improve plan accuracy. Pract Radiat Oncol 2015; 5:248-56. [DOI: 10.1016/j.prro.2014.12.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Revised: 12/09/2014] [Accepted: 12/23/2014] [Indexed: 11/16/2022]
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21
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Ding Y, Mohamed ASR, Yang J, Colen RR, Frank SJ, Wang J, Wassal EY, Wang W, Kantor ME, Balter PA, Rosenthal DI, Lai SY, Hazle JD, Fuller CD. Prospective observer and software-based assessment of magnetic resonance imaging quality in head and neck cancer: Should standard positioning and immobilization be required for radiation therapy applications? Pract Radiat Oncol 2015; 5:e299-308. [PMID: 25544553 PMCID: PMC4470880 DOI: 10.1016/j.prro.2014.11.003] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2014] [Revised: 10/10/2014] [Accepted: 11/05/2014] [Indexed: 10/24/2022]
Abstract
PURPOSE The purpose of this study was to investigate the potential of a head and neck magnetic resonance simulation and immobilization protocol on reducing motion-induced artifacts and improving positional variance for radiation therapy applications. METHODS AND MATERIALS Two groups (group 1, 17 patients; group 2, 14 patients) of patients with head and neck cancer were included under a prospective, institutional review board-approved protocol and signed informed consent. A 3.0-T magnetic resonance imaging (MRI) scanner was used for anatomic and dynamic contrast-enhanced acquisitions with standard diagnostic MRI setup for group 1 and radiation therapy immobilization devices for group 2 patients. The impact of magnetic resonance simulation/immobilization was evaluated qualitatively by 2 observers in terms of motion artifacts and positional reproducibility and quantitatively using 3-dimensional deformable registration to track intrascan maximum motion displacement of voxels inside 7 manually segmented regions of interest. RESULTS The image quality of group 2 (29 examinations) was significantly better than that of group 1 (50 examinations) as rated by both observers in terms of motion minimization and imaging reproducibility (P < .0001). The greatest average maximum displacement was at the region of the larynx in the posterior direction for patients in group 1 (17 mm; standard deviation, 8.6 mm), whereas the smallest average maximum displacement was at the region of the posterior fossa in the superior direction for patients in group 2 (0.4 mm; standard deviation, 0.18 mm). Compared with group 1, maximum regional motion was reduced in group 2 patients in the oral cavity, floor of mouth, oropharynx, and larynx regions; however, the motion reduction reached statistical significance only in the regions of the oral cavity and floor of mouth (P < .0001). CONCLUSIONS The image quality of head and neck MRI in terms of motion-related artifacts and positional reproducibility was greatly improved by use of radiation therapy immobilization devices. Consequently, immobilization with external and intraoral fixation in MRI examinations is required for radiation therapy application.
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Affiliation(s)
- Yao Ding
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Abdallah S R Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, University of Alexandria, Alexandria, Egypt
| | - Jinzhong Yang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Rivka R Colen
- Department of Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Steven J Frank
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas Graduate School of Biomedical Sciences, Houston, Texas
| | - Jihong Wang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas Graduate School of Biomedical Sciences, Houston, Texas
| | - Eslam Y Wassal
- Department of Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Diagnostic and Interventional Radiology, Kasr Al-Ainy Faculty of Medicine, Cairo University, Egypt
| | - Wenjie Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Michael E Kantor
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peter A Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas Graduate School of Biomedical Sciences, Houston, Texas
| | - David I Rosenthal
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Stephen Y Lai
- Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - John D Hazle
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas Graduate School of Biomedical Sciences, Houston, Texas
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas Graduate School of Biomedical Sciences, Houston, Texas.
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Doemer A, Chetty IJ, Glide-Hurst C, Nurushev T, Hearshen D, Pantelic M, Traughber M, Kim J, Levin K, Elshaikh MA, Walker E, Movsas B. Evaluating organ delineation, dose calculation and daily localization in an open-MRI simulation workflow for prostate cancer patients. Radiat Oncol 2015; 10:37. [PMID: 25889107 PMCID: PMC4340286 DOI: 10.1186/s13014-014-0309-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2014] [Accepted: 12/15/2014] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND This study describes initial testing and evaluation of a vertical-field open Magnetic Resonance Imaging (MRI) scanner for the purpose of simulation in radiation therapy for prostate cancer. We have evaluated the clinical workflow of using open MRI as a sole modality for simulation and planning. Relevant results related to MRI alignment (vs. CT) reference dataset with Cone-Beam CT (CBCT) for daily localization are presented. METHODS Ten patients participated in an IRB approved study utilizing MRI along with CT simulation with the intent of evaluating the MRI-simulation process. Differences in prostate gland volume, seminal vesicles, and penile bulb were assessed with MRI and compared to CT. To evaluate dose calculation accuracy, bulk-density-assignments were mapped onto respective MRI datasets and treated IMRT plans were re-calculated. For image localization purposes, 400 CBCTs were re-evaluated with MRI as the reference dataset and daily shifts compared against CBCT-to-CT registration. Planning margins based on MRI/CBCT shifts were computed using the van Herk formalism. RESULTS Significant organ contour differences were noted between MRI and CT. Prostate volumes were on average 39.7% (p = 0.002) larger on CT than MRI. No significant difference was found in seminal vesicle volumes (p = 0.454). Penile bulb volumes were 61.1% higher on CT, without statistical significance (p = 0.074). MRI-based dose calculations with assigned bulk densities produced agreement within 1% with heterogeneity corrected CT calculations. The differences in shift positions for the cohort between CBCT-to-CT registration and CBCT-to-MRI registration are -0.15 ± 0.25 cm (anterior-posterior), 0.05 ± 0.19 cm (superior-inferior), and -0.01 ± 0.14 cm (left-right). CONCLUSIONS This study confirms the potential of using an open-field MRI scanner as primary imaging modality for prostate cancer treatment planning simulation, dose calculations and daily image localization.
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Affiliation(s)
- Anthony Doemer
- Department of Radiation Oncology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
| | - Carri Glide-Hurst
- Department of Radiation Oncology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
| | - Teamour Nurushev
- Department of Radiation Oncology, 21st Century Oncology, 28585 Orchard Lake Rd, Suite 110, Farmington Hills, MI, 48334, USA.
| | - David Hearshen
- Department of Radiology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
| | - Milan Pantelic
- Department of Radiology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
| | | | - Joshua Kim
- Department of Radiation Oncology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
| | - Kenneth Levin
- Department of Radiation Oncology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
| | - Mohamed A Elshaikh
- Department of Radiation Oncology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
| | - Eleanor Walker
- Department of Radiation Oncology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
| | - Benjamin Movsas
- Department of Radiation Oncology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit, MI, 48202, USA.
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Jonsson JH, Akhtari MM, Karlsson MG, Johansson A, Asklund T, Nyholm T. Accuracy of inverse treatment planning on substitute CT images derived from MR data for brain lesions. Radiat Oncol 2015; 10:13. [PMID: 25575414 PMCID: PMC4299127 DOI: 10.1186/s13014-014-0308-1] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2013] [Accepted: 12/15/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In this pilot study we evaluated the performance of a substitute CT (s-CT) image derived from MR data of the brain, as a basis for optimization of intensity modulated rotational therapy, final dose calculation and derivation of reference images for patient positioning. METHODS S-CT images were created using a Gaussian mixture regression model on five patients previously treated with radiotherapy. Optimizations were compared using D max, D min, D median and D mean measures for the target volume and relevant risk structures. Final dose calculations were compared using gamma index with 1%/1 mm and 3%/3 mm acceptance criteria. 3D geometric evaluation was conducted using the DICE similarity coefficient for bony structures. 2D geometric comparison of digitally reconstructed radiographs (DRRs) was performed by manual delineation of relevant structures on the s-CT DRR that were transferred to the CT DRR and compared by visual inspection. RESULTS Differences for the target volumes in optimization comparisons were small in general, e.g. a mean difference in both D min and D max within ±0.3%. For the final dose calculation gamma evaluations, 100% of the voxels passed the 1%/1 mm criterion within the PTV. Within the entire external volume between 99.4% and 100% of the voxels passed the 3%/3 mm criterion. In the 3D geometric comparison, the DICE index varied between approximately 0.8-0.9, depending on the position in the skull. In the 2D DRR comparisons, no appreciable visual differences were found. CONCLUSIONS Even though the present work involves a limited number of patients, the results provide a strong indication that optimization and dose calculation based on s-CT data is accurate regarding both geometry and dosimetry.
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Affiliation(s)
- Joakim H Jonsson
- Department of Radiation Sciences, Umeå University, Umeå, SE-901 87, Sweden.
| | - Mohammad M Akhtari
- Department of Radiation Sciences, Umeå University, Umeå, SE-901 87, Sweden.
| | - Magnus G Karlsson
- Department of Radiation Sciences, Umeå University, Umeå, SE-901 87, Sweden.
| | - Adam Johansson
- Department of Radiation Sciences, Umeå University, Umeå, SE-901 87, Sweden.
| | - Thomas Asklund
- Department of Radiation Sciences, Umeå University, Umeå, SE-901 87, Sweden.
| | - Tufve Nyholm
- Department of Radiation Sciences, Umeå University, Umeå, SE-901 87, Sweden.
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Edmund JM, Kjer HM, Van Leemput K, Hansen RH, Andersen JAL, Andreasen D. A voxel-based investigation for MRI-only radiotherapy of the brain using ultra short echo times. Phys Med Biol 2014; 59:7501-19. [DOI: 10.1088/0031-9155/59/23/7501] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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25
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Korhonen J, Kapanen M, Keyriläinen J, Seppälä T, Tenhunen M. A dual model HU conversion from MRI intensity values within and outside of bone segment for MRI-based radiotherapy treatment planning of prostate cancer. Med Phys 2014; 41:011704. [PMID: 24387496 DOI: 10.1118/1.4842575] [Citation(s) in RCA: 121] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE The lack of electron density information in magnetic resonance images (MRI) poses a major challenge for MRI-based radiotherapy treatment planning (RTP). In this study the authors convert MRI intensity values into Hounsfield units (HUs) in the male pelvis and thus enable accurate MRI-based RTP for prostate cancer patients with varying tissue anatomy and body fat contents. METHODS T1/T2*-weighted MRI intensity values and standard computed tomography (CT) image HUs in the male pelvis were analyzed using image data of 10 prostate cancer patients. The collected data were utilized to generate a dual model HU conversion technique from MRI intensity values of the single image set separately within and outside of contoured pelvic bones. Within the bone segment local MRI intensity values were converted to HUs by applying a second-order polynomial model. This model was tuned for each patient by two patient-specific adjustments: MR signal normalization to correct shifts in absolute intensity level and application of a cutoff value to accurately represent low density bony tissue HUs. For soft tissues, such as fat and muscle, located outside of the bone contours, a threshold-based segmentation method without requirements for any patient-specific adjustments was introduced to convert MRI intensity values into HUs. The dual model HU conversion technique was implemented by constructing pseudo-CT images for 10 other prostate cancer patients. The feasibility of these images for RTP was evaluated by comparing HUs in the generated pseudo-CT images with those in standard CT images, and by determining deviations in MRI-based dose distributions compared to those in CT images with 7-field intensity modulated radiation therapy (IMRT) with the anisotropic analytical algorithm and 360° volumetric-modulated arc therapy (VMAT) with the Voxel Monte Carlo algorithm. RESULTS The average HU differences between the constructed pseudo-CT images and standard CT images of each test patient ranged from -2 to 5 HUs and from 22 to 78 HUs in soft and bony tissues, respectively. The average local absolute value differences were 11 HUs in soft tissues and 99 HUs in bones. The planning target volume doses (volumes 95%, 50%, 5%) in the pseudo-CT images were within 0.8% compared to those in CT images in all of the 20 treatment plans. The average deviation was 0.3%. With all the test patients over 94% (IMRT) and 92% (VMAT) of dose points within body (lower than 10% of maximum dose suppressed) passed the 1 mm and 1% 2D gamma index criterion. The statistical tests (t- and F-tests) showed significantly improved (p ≤ 0.05) HU and dose calculation accuracies with the soft tissue conversion method instead of homogeneous representation of these tissues in MRI-based RTP images. CONCLUSIONS This study indicates that it is possible to construct high quality pseudo-CT images by converting the intensity values of a single MRI series into HUs in the male pelvis, and to use these images for accurate MRI-based prostate RTP dose calculations.
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Affiliation(s)
- Juha Korhonen
- Clinical Research Institute Helsinki University Central Hospital Ltd., POB-700, 00029 HUS, Finland and Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland
| | - Mika Kapanen
- Clinical Research Institute Helsinki University Central Hospital Ltd., POB-700, 00029 HUS, Finland; Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland; and Department of Medical Physics, Tampere University Hospital, POB-2000, 33521 Tampere, Finland
| | - Jani Keyriläinen
- Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland
| | - Tiina Seppälä
- Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland
| | - Mikko Tenhunen
- Department of Oncology, Helsinki University Central Hospital, POB-180, 00029 HUS, Finland
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Nyholm T, Jonsson J. Counterpoint: Opportunities and Challenges of a Magnetic Resonance Imaging–Only Radiotherapy Work Flow. Semin Radiat Oncol 2014; 24:175-80. [DOI: 10.1016/j.semradonc.2014.02.005] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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MRI distortion: considerations for MRI based radiotherapy treatment planning. AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE 2014; 37:103-13. [DOI: 10.1007/s13246-014-0252-2] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2013] [Accepted: 02/01/2014] [Indexed: 10/25/2022]
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MRI-based simulation of treatment plans for ion radiotherapy in the brain region. Radiother Oncol 2013; 109:414-8. [DOI: 10.1016/j.radonc.2013.10.034] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2013] [Revised: 10/14/2013] [Accepted: 10/24/2013] [Indexed: 11/23/2022]
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Nyholm T, Jonsson J, Söderström K, Bergström P, Carlberg A, Frykholm G, Behrens CF, Geertsen PF, Trepiakas R, Hanvey S, Sadozye A, Ansari J, McCallum H, Frew J, McMenemin R, Zackrisson B. Variability in prostate and seminal vesicle delineations defined on magnetic resonance images, a multi-observer, -center and -sequence study. Radiat Oncol 2013; 8:126. [PMID: 23706145 PMCID: PMC3680182 DOI: 10.1186/1748-717x-8-126] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2012] [Accepted: 03/28/2013] [Indexed: 11/22/2022] Open
Abstract
Background The use of magnetic resonance (MR) imaging as a part of preparation for radiotherapy is increasing. For delineation of the prostate several publications have shown decreased delineation variability using MR compared to computed tomography (CT). The purpose of the present work was to investigate the intra- and inter-physician delineation variability for prostate and seminal vesicles, and to investigate the influence of different MR sequence settings used clinically at the five centers participating in the study. Methods MR series from five centers, each providing five patients, were used. Two physicians from each center delineated the prostate and the seminal vesicles on each of the 25 image sets. The variability between the delineations was analyzed with respect to overall, intra- and inter-physician variability, and dependence between variability and origin of the MR images, i.e. the MR sequence used to acquire the data. Results The intra-physician variability in different directions was between 1.3 - 1.9 mm and 3 – 4 mm for the prostate and seminal vesicles respectively (1 std). The inter-physician variability for different directions were between 0.7 – 1.7 mm and approximately equal for the prostate and seminal vesicles. Large differences in variability were observed for individual patients, and also for individual imaging sequences used at the different centers. There was however no indication of decreased variability with higher field strength. Conclusion The overall delineation variability is larger for the seminal vesicles compared to the prostate, due to a larger intra-physician variability. The imaging sequence appears to have a large influence on the variability, even for different variants of the T2-weighted spin-echo based sequences, which were used by all centers in the study.
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Stam MK, Crijns SPM, Zonnenberg BA, Barendrecht MM, van Vulpen M, Lagendijk JJW, Raaymakers BW. Navigators for motion detection during real-time MRI-guided radiotherapy. Phys Med Biol 2012; 57:6797-805. [PMID: 23032581 DOI: 10.1088/0031-9155/57/21/6797] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
An MRI-linac system provides direct MRI feedback and with that the possibility of adapting radiation treatments to the actual tumour position. This paper addresses the use of fast 1D MRI, pencil-beam navigators, for this feedback. The accuracy of using navigators was determined on a moving phantom. The possibility of organ tracking and breath-hold monitoring based on navigator guidance was shown for the kidney. Navigators are accurate within 0.5 mm and the analysis has a minimal time lag smaller than 30 ms as shown for the phantom measurements. The correlation of 2D kidney images and navigators shows the possibility of complete organ tracking. Furthermore the breath-hold monitoring of the kidney is accurate within 1.5 mm, allowing gated radiotherapy based on navigator feedback. Navigators are a fast and precise method for monitoring and real-time tracking of anatomical landmarks. As such, they provide direct MRI feedback on anatomical changes for more precise radiation delivery.
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Affiliation(s)
- Mette K Stam
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
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Johansson A, Karlsson M, Yu J, Asklund T, Nyholm T. Voxel-wise uncertainty in CT substitute derived from MRI. Med Phys 2012; 39:3283-90. [PMID: 22755711 DOI: 10.1118/1.4711807] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE In an earlier work, we demonstrated that substitutes for CT images can be derived from MR images using ultrashort echo time (UTE) sequences, conventional T2 weighted sequences, and Gaussian mixture regression (GMR). In this study, we extend this work by analyzing the uncertainties associated with the GMR model and the information contributions from the individual imaging sequences. METHODS An analytical expression for the voxel-wise conditional expected absolute deviation (EAD) in substitute CT (s-CT) images was derived. The expression depends only on MR images and can thus be calculated along with each s-CT image. The uncertainty measure was evaluated by comparing the EAD to the true mean absolute prediction deviation (MAPD) between the s-CT and CT images for 14 patients. Further, the influence of the different MR images included in the GMR model on the generated s-CTs was investigated by removing one or more images and evaluating the MAPD for a spectrum of predicted radiological densities. RESULTS The largest EAD was predicted at air-soft tissue and bone-soft tissue interfaces. The EAD agreed with the MAPD in both these regions and in regions with lower EADs, such as the brain. Two of the MR images included in the GMR model were found to be mutually redundant for the purpose of s-CT generation. CONCLUSIONS The presented uncertainty estimation method accurately predicts the voxel-wise MAPD in s-CT images. Also, the non-UTE sequence previously used in the model was found to be redundant.
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Affiliation(s)
- Adam Johansson
- Department of Radiation Sciences, Umeå University, Umeå, SE-901 87 Sweden.
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Chowdhury N, Toth R, Chappelow J, Kim S, Motwani S, Punekar S, Lin H, Both S, Vapiwala N, Hahn S, Madabhushi A. Concurrent segmentation of the prostate on MRI and CT via linked statistical shape models for radiotherapy planning. Med Phys 2012; 39:2214-28. [PMID: 22482643 DOI: 10.1118/1.3696376] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Prostate gland segmentation is a critical step in prostate radiotherapy planning, where dose plans are typically formulated on CT. Pretreatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to perform, compared to delineation on CT. In this work, the authors present a novel framework for building a linked statistical shape model (LSSM), a statistical shape model (SSM) that links the shape variation of a structure of interest (SOI) across multiple imaging modalities. This framework is particularly relevant in scenarios where accurate boundary delineations of the SOI on one of the modalities may not be readily available, or difficult to obtain, for training a SSM. In this work the authors apply the LSSM in the context of multimodal prostate segmentation for radiotherapy planning, where the prostate is concurrently segmented on MRI and CT. METHODS The framework comprises a number of logically connected steps. The first step utilizes multimodal registration of MRI and CT to map 2D boundary delineations of the prostate from MRI onto corresponding CT images, for a set of training studies. Hence, the scheme obviates the need for expert delineations of the gland on CT for explicitly constructing a SSM for prostate segmentation on CT. The delineations of the prostate gland on MRI and CT allows for 3D reconstruction of the prostate shape which facilitates the building of the LSSM. In order to perform concurrent prostate MRI and CT segmentation using the LSSM, the authors employ a region-based level set approach where the authors deform the evolving prostate boundary to simultaneously fit to MRI and CT images in which voxels are classified to be either part of the prostate or outside the prostate. The classification is facilitated by using a combination of MRI-CT probabilistic spatial atlases and a random forest classifier, driven by gradient and Haar features. RESULTS The authors acquire a total of 20 MRI-CT patient studies and use the leave-one-out strategy to train and evaluate four different LSSMs. First, a fusion-based LSSM (fLSSM) is built using expert ground truth delineations of the prostate on MRI alone, where the ground truth for the gland on CT is obtained via coregistration of the corresponding MRI and CT slices. The authors compare the fLSSM against another LSSM (xLSSM), where expert delineations of the gland on both MRI and CT are employed in the model building; xLSSM representing the idealized LSSM. The authors also compare the fLSSM against an exclusive CT-based SSM (ctSSM), built from expert delineations of the gland on CT alone. In addition, two LSSMs trained using trainee delineations (tLSSM) on CT are compared with the fLSSM. The results indicate that the xLSSM, tLSSMs, and the fLSSM perform equivalently, all of them out-performing the ctSSM. CONCLUSIONS The fLSSM provides an accurate alternative to SSMs that require careful expert delineations of the SOI that may be difficult or laborious to obtain. Additionally, the fLSSM has the added benefit of providing concurrent segmentations of the SOI on multiple imaging modalities.
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Affiliation(s)
- Najeeb Chowdhury
- Department of Biomedical Engineering, Rutgers University, Piscataway, NJ 08854, USA
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Breunig J, Hernandez S, Lin J, Alsager S, Dumstorf C, Price J, Steber J, Garza R, Nagda S, Melian E, Emami B, Roeske JC. A system for continual quality improvement of normal tissue delineation for radiation therapy treatment planning. Int J Radiat Oncol Biol Phys 2012; 83:e703-8. [PMID: 22583604 DOI: 10.1016/j.ijrobp.2012.02.003] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2011] [Revised: 02/03/2012] [Accepted: 02/03/2012] [Indexed: 02/08/2023]
Abstract
PURPOSE To implement the "plan-do-check-act" (PDCA) cycle for the continual quality improvement of normal tissue contours used for radiation therapy treatment planning. METHODS AND MATERIALS The CT scans of patients treated for tumors of the brain, head and neck, thorax, pancreas and prostate were selected for this study. For each scan, a radiation oncologist and a diagnostic radiologist, outlined the normal tissues ("gold" contours) using Radiation Therapy Oncology Group (RTOG) guidelines. A total of 30 organs were delineated. Independently, 5 board-certified dosimetrists and 1 trainee then outlined the same organs. Metrics used to compare the agreement between the dosimetrists' contours and the gold contours included the Dice Similarity Coefficient (DSC), and a penalty function using distance to agreement. Based on these scores, dosimetrists were re-trained on those organs in which they did not receive a passing score, and they were subsequently re-tested. RESULTS Passing scores were achieved on 19 of 30 organs evaluated. These scores were correlated to organ volume. For organ volumes <8 cc, the average DSC was 0.61 vs organ volumes ≥8 cc, for which the average DSC was 0.91 (P=.005). Normal tissues that had the lowest scores included the lenses, optic nerves, chiasm, cochlea, and esophagus. Of the 11 organs that were considered for re-testing, 10 showed improvement in the average score, and statistically significant improvement was noted in more than half of these organs after education and re-assessment. CONCLUSIONS The results of this study indicate the feasibility of applying the PDCA cycle to assess competence in the delineation of individual organs, and to identify areas for improvement. With testing, guidance, and re-evaluation, contouring consistency can be obtained across multiple dosimetrists. Our expectation is that continual quality improvement using the PDCA approach will ensure more accurate treatments and dose assessment in radiotherapy treatment planning and delivery.
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Affiliation(s)
- Jennifer Breunig
- Department of Radiation Oncology, Loyola University Medical Center, Maywood, Illinois, USA
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Internal Fiducial Markers and Susceptibility Effects in MRI—Simulation and Measurement of Spatial Accuracy. Int J Radiat Oncol Biol Phys 2012; 82:1612-8. [DOI: 10.1016/j.ijrobp.2011.01.046] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2010] [Revised: 01/04/2011] [Accepted: 01/18/2011] [Indexed: 11/19/2022]
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Karotki A, Mah K, Meijer G, Meltsner M. Comparison of bulk electron density and voxel-based electron density treatment planning. J Appl Clin Med Phys 2011; 12:3522. [PMID: 22089006 PMCID: PMC5718732 DOI: 10.1120/jacmp.v12i4.3522] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2010] [Revised: 05/10/2011] [Accepted: 05/13/2011] [Indexed: 12/04/2022] Open
Abstract
The use of magnetic resonance imaging (MRI) alone for radiation planning is limited by the lack of electron density for dose calculations. The purpose of this work is to evaluate the dosimetric accuracy of using bulk electron density as a substitute for computed tomography (CT)‐derived electron density in intensity‐modulated radiation therapy (IMRT) treatment planning of head and neck (HN) cancers. Ten clinically‐approved, CT‐based IMRT treatment plans of HN cancer were used for this study. Three dose distributions were calculated and compared for each treatment plan. The first calculation used CT‐derived density and was assumed to be the most accurate. The second calculation used a homogeneous patient density of 1 g/cm3. For the third dose calculation, bone and air cavities were contoured and assigned a uniform density of 1.5 g/cm3 and 0 g/cm3, respectively. The remaining tissues were assigned a density of 1 g/cm3. The use of homogeneous anatomy resulted in up to 4%–5% deviations in dose distribution as compared to CT‐derived electron density calculations. Assigning bulk density to bone and air cavities significantly improved the accuracy of the dose calculations. All parameters used to describe planning target volume coverage were within 2% of calculations based on CT‐derived density. For organs at risk, most of the parameters were within 2%, with the few exceptions located in low‐dose regions. The data presented here show that if bone and air cavities are overridden with the proper density, it is feasible to use a bulk electron density approach for accurate dose calculation in IMRT treatment planning of HN cancers. This may overcome the problem of the lack of electron density information should MRI‐only simulation be performed. PACS number: 87.55.D‐
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Affiliation(s)
- Aliaksandr Karotki
- Department of Medical Physics, Sunnybrook Health Sciences Center, Toronto, ON, Canada.
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MRI-guided prostate radiation therapy planning: Investigation of dosimetric accuracy of MRI-based dose planning. Radiother Oncol 2011; 98:330-4. [PMID: 21339009 DOI: 10.1016/j.radonc.2011.01.012] [Citation(s) in RCA: 110] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2010] [Revised: 01/06/2011] [Accepted: 01/09/2011] [Indexed: 11/20/2022]
Abstract
BACKGROUND AND PURPOSE Dose planning requires a CT scan which provides the electron density distribution for dose calculation. MR provides superior soft tissue contrast compared to CT and the use of MR-alone for prostate planning would provide further benefits such as lower cost to the patient. This study compares the accuracy of MR-alone based dose calculations with bulk electron density assignment to CT-based dose calculations for prostate radiotherapy. MATERIALS AND METHODS CT and whole pelvis MR images were contoured for 39 prostate patients. Plans with uniform density and plans with bulk density values assigned to bone and tissue were compared to the patient's gold standard full density CT plan. The optimal bulk density for bone was calculated using effective depth measurements. The plans were evaluated using ICRU point doses, dose volume histograms, and Chi comparisons. Differences in spatial uniformity were investigated for the CT and MR scans. RESULTS The calculated dose for CT bulk bone and tissue density plans was 0.1±0.6% (mean±1 SD) higher than the corresponding full density CT plan. MR bulk bone and tissue density plans were 1.3±0.8% lower than the full density CT plan. CT uniform density plans and MR uniform density plans were 1.4±0.9% and 2.6±0.9% lower, respectively. Paired t-tests performed on specific points on the DVH graphs showed that points on DVHs for all bulk electron density plans were equivalent with two exceptions. There was no significant difference between doses calculated on Pinnacle and Eclipse. The dose distributions of six patients produced Chi values outside the acceptable range of values when MR-based plans were compared to the full density plan. CONCLUSIONS MR-alone bulk density planning is feasible provided bone is assigned a density, however, manual segmentation of bone on MR images will have to be replaced with automatic methods. The major dose differences for MR bulk density plans are due to differences in patient external contours introduced by the MR couch-top and pelvic coil.
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Fast Automatic Multi-atlas Segmentation of the Prostate from 3D MR Images. LECTURE NOTES IN COMPUTER SCIENCE 2011. [DOI: 10.1007/978-3-642-23944-1_2] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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Crijns SPM, Raaymakers BW, Lagendijk JJW. Real-time correction of magnetic field inhomogeneity-induced image distortions for MRI-guided conventional and proton radiotherapy. Phys Med Biol 2010; 56:289-97. [DOI: 10.1088/0031-9155/56/1/017] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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O TM, Kwak R, E. Portnof J, Berke DM, Lipari B, Waner M. Analysis of skeletal mandibular abnormalities associated with cervicofacial lymphatic malformations. Laryngoscope 2010; 121:91-101. [DOI: 10.1002/lary.21161] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Jonsson JH, Karlsson MG, Karlsson M, Nyholm T. Treatment planning using MRI data: an analysis of the dose calculation accuracy for different treatment regions. Radiat Oncol 2010; 5:62. [PMID: 20591179 PMCID: PMC2909248 DOI: 10.1186/1748-717x-5-62] [Citation(s) in RCA: 158] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2010] [Accepted: 06/30/2010] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Because of superior soft tissue contrast, the use of magnetic resonance imaging (MRI) as a complement to computed tomography (CT) in the target definition procedure for radiotherapy is increasing. To keep the workflow simple and cost effective and to reduce patient dose, it is natural to strive for a treatment planning procedure based entirely on MRI. In the present study, we investigate the dose calculation accuracy for different treatment regions when using bulk density assignments on MRI data and compare it to treatment planning that uses CT data. METHODS MR and CT data were collected retrospectively for 40 patients with prostate, lung, head and neck, or brain cancers. Comparisons were made between calculations on CT data with and without inhomogeneity corrections and on MRI or CT data with bulk density assignments. The bulk densities were assigned using manual segmentation of tissue, bone, lung, and air cavities. RESULTS The deviations between calculations on CT data with inhomogeneity correction and on bulk density assigned MR data were small. The maximum difference in the number of monitor units required to reach the prescribed dose was 1.6%. This result also includes effects of possible geometrical distortions. CONCLUSIONS The dose calculation accuracy at the investigated treatment sites is not significantly compromised when using MRI data when adequate bulk density assignments are made. With respect to treatment planning, MRI can replace CT in all steps of the treatment workflow, reducing the radiation exposure to the patient, removing any systematic registration errors that may occur when combining MR and CT, and decreasing time and cost for the extra CT investigation.
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Affiliation(s)
- Joakim H Jonsson
- Radiation Physics Section, Department of Radiation Sciences, Umeå University, 90187 Umeå, Sweden
| | - Magnus G Karlsson
- Department of Radiation Physics, Umeå University Hospital, 90185 Umeå, Sweden
| | - Mikael Karlsson
- Radiation Physics Section, Department of Radiation Sciences, Umeå University, 90187 Umeå, Sweden
| | - Tufve Nyholm
- Section of Oncology, Department of Radiation Sciences, Umeå University, 90187 Umeå, Sweden
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Baldwin LN, Wachowicz K, Fallone BG. A two-step scheme for distortion rectification of magnetic resonance images. Med Phys 2009; 36:3917-26. [DOI: 10.1118/1.3180107] [Citation(s) in RCA: 81] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Eilertsen K, Nilsen Tor Arne Vestad L, Geier O, Skretting A. A simulation of MRI based dose calculations on the basis of radiotherapy planning CT images. Acta Oncol 2009; 47:1294-302. [PMID: 18663645 DOI: 10.1080/02841860802256426] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
BACKGROUND The advantage of MRI-based radiotherapy planning is the superior soft tissue differentiation. However, for accurate patient dose calculations, a conversion of the MR images into Hounsfield CT maps is necessary. The aim of the present study was to investigate the dose accuracy that can be achieved with segmented MR-images derived from the planning CT images by assigning fixed densities to different classes of tissues. METHODS Treatment plans for ten prostate cancer patients were selected. A collapsed cone algorithm was used to calculate patient dose distributions. The dose calculations were based on four different image sets: (1) the original CT-series (DD(DP)), (2) a simulated MR series with all tissue set to a homogenous water equivalent material of density 1.02 g/cm(3) (DD(W)), (3) a simulated MR series with soft tissue set to a water equivalent material with density 1.02 g/cm(3) and the bone set to a density of 1.3 g/cm(3) (DD(W+B1.3)), and (4) a simulated MR series identical to (3) but with a bone density equal to 2.1 g/cm(3) (DD(W+B2.1)). The dose distributions were compared by analysing dose difference histograms as well as through a visual display of spatial dose deviations. RESULTS The population based minimum, mean and maximum dose difference between the DD(DP) and DD(W) in the target volume was -2.8, -1.0 and 0.6%, respectively. Corresponding differences between DD(DP) and DD(W+B1.3) were -1.6, 0.2 and 1.5%, respectively, and between DD(DP) and DD(W+B2.1) -4.3, 4.2 and 9.7%, respectively. For the rectum, the differences between CT(DP) and the other image sets were in the range of -19.5 to 8.8%. For the bladder, the differences were in the range of -9.6 to 7.0%. CONCLUSIONS A systematic study using segmented MR images was undertaken. To achieve an acceptable accuracy in the CTV dose, the MR images should be segmented into bone and water equivalent tissue. Still, significant dose deviation for the organs at risk may be present. As tissue segmentation in real MR images is introduced, segmentation errors and errors that stem from geometrical non-linearities may further reduce the accuracy.
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Dedicated Magnetic Resonance Imaging in the Radiotherapy Clinic. Int J Radiat Oncol Biol Phys 2009; 74:644-51. [DOI: 10.1016/j.ijrobp.2009.01.065] [Citation(s) in RCA: 118] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2008] [Revised: 01/09/2009] [Accepted: 01/14/2009] [Indexed: 11/21/2022]
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Current world literature. Trauma and rehabilitation. Curr Opin Neurol 2008; 21:762-4. [PMID: 18989123 DOI: 10.1097/wco.0b013e32831cbb85] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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