期刊论文详细信息
Radiation Oncology
Evaluating organ delineation, dose calculation and daily localization in an open-MRI simulation workflow for prostate cancer patients
Benjamin Movsas4  Eleanor Walker4  Mohamed A Elshaikh4  Kenneth Levin4  Joshua Kim4  Melanie Traughber3  Milan Pantelic2  David Hearshen2  Teamour Nurushev1  Carri Glide-Hurst4  Indrin J Chetty4  Anthony Doemer4 
[1] Department of Radiation Oncology, 21st Century Oncology, 28585 Orchard Lake Rd, Suite 110, Farmington Hills 48334, MI, USA;Department of Radiology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit 48202, MI, USA;Philips Healthcare, 603 Alpha Park, Cleveland 44143, OH, USA;Department of Radiation Oncology, Henry Ford Health System, 2799 W. Grand Blvd, Detroit 48202, MI, USA
关键词: Radiation Oncology;    Anatomical delineation;    MRI dose calculation;    CBCT localization;    MRI simulation;   
Others  :  1149670
DOI  :  10.1186/s13014-014-0309-0
 received in 2014-08-08, accepted in 2014-12-15,  发布年份 2015
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【 摘 要 】

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.

【 授权许可】

   
2015 Doemer et al.; licensee BioMed Central.

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【 参考文献 】
  • [1]Datta NR, David R, Gupta RK, Lal P. Implications of contrast-enhanced CT-based and MRI-based target volume delineations in radiotherapy treatment planning for brain tumors. J Cancer Res Ther. 2008; 4(1):9-13.
  • [2]Lemort M, Canizares AC, Kampouridis S. Advances in imaging head and neck tumours. Curr Opin Oncol. 2006; 18(3):234-9.
  • [3]Prabhakar R, Haresh KP, Ganesh T, Joshi RC, Julka PK, Rath GK. Comparison of computed tomography and magnetic resonance based target volume in brain tumors. J Cancer Res Ther. 2007; 3(2):121-3.
  • [4]McLaughlin PW, Troyer S, Berri S, Narayana V, Meirowitz A, Roberson PL, Montie J. Functional anatomy of the prostate: implications for treatment planning. Int J Radiat Oncol Biol Phys. 2005; 63(2):479-91.
  • [5]Debois M, Oyen R, Maes F, Verswijvel G, Gatti G, Bosmans H, Feron M, Bellon E, Kutcher G, Van Poppel H, Vanuytsel L. The contribution of magnetic resonance imaging to the three-dimensional treatment planning of localized prostate cancer. Int J Radiat Oncol Biol Phys. 1999; 45(4):857-65.
  • [6]Hricak H. MR imaging and MR spectroscopic imaging in the pre-treatment evaluation of prostate cancer. Br J Radiol. 2005; 78 Suppl. 2:S103-11.
  • [7]McLaughlin PW, Narayana V, Meirovitz A, Troyer S, Roberson PL, Gonda R, Sandler H, Marsh L, Lawrence T, Kessler M. Vessel-sparing prostate radiotherapy: dose limitation to critical erectile vascular structures (internal pudendal artery and corpus cavernosum) defined by MRI. Int J Radiat Oncol Biol Phys. 2005; 61(1):20-31.
  • [8]Devic S. MRI simulation for radiotherapy treatment planning. Med Phys. 2012; 39(11):6701-11.
  • [9]Mutic S, Dempsey JF. The ViewRay system: magnetic resonance-guided and controlled radiotherapy. Semin Radiat Oncol. 2014; 24(3):196-9.
  • [10]Lagendijk JJ, Raaymakers BW, van Vulpen M. The magnetic resonance imaging-linac system. Semin Radiat Oncol. 2014; 24(3):207-9.
  • [11]Stanescu T, Wachowicz K, Jaffray DA. Characterization of tissue magnetic susceptibility-induced distrotions for MRIgRT. Med Phys. 2012; 39(12):7185-93.
  • [12]Klein E, Chen Z, Chetty IJ, Dogan N. Oncology Scan – Physics. Int J Radiat Oncol Biol Phys. 2012; 84(4):871-3.
  • [13]Karlsson M, Karlsson MG, Nyholm T, Amies C, Zackrisson B. Dedicated magnetic resonance imaging in the radiotherapy clinic. Int J Radiat Oncol Biol Phys. 2009; 74(2):644-51.
  • [14]Lee YK, Bollet M, Charles-Edwards G, Flower MA, Leach MO, McNair H, Moore E, Rowbottom C, Webb S. Radiotherapy treatment planning of prostate cancer using magnetic resonance imaging alone. Radiother Oncol. 2003; 66(2):203-16.
  • [15]Prabhakar R, Julka PK, Ganesh T, Munshi A, Joshi RC, Rath GK. Feasibility of using MRI alone for 3D radiation treatment planning in brain tumors. Jpn J Clin Oncol. 2007; 37(6):405-11.
  • [16]Janke A, Zhao H, Cowin GJ, Galloway GJ, Doddrell DM. Use of spherical harmonic deconvolution methods to compensate for nonlinear gradient effects on MRI images. Magn Reson Med. 2004; 52(1):115-22.
  • [17]Karger CP, Höss A, Bendl R, Canda V, Schad L. Accuracy of device-specific 2D and 3D image distortion correction algorithms for magnetic resonance imaging of the head provided by a manufacturer. Phys Med Biol. 2006; 51(12):N253-61.
  • [18]Pasquier D, Lartiqau E. MRI prostate radiation therapy planning: when the patient distorts his own image (Regarding Lambert et al., Radiother Oncol 2011; 98:330–334). Radiother Oncol. 2012; 102(1):163.
  • [19]Wang H, Balter J, Cao Y. Patient-induced susceptibility effect on geometric distortion of clinical brain MRI for radiation treatment planning on a 3 T scanner. Phys Med Biol. 2013; 58(3):465-77.
  • [20]Hsu SH, Cao Y, Huang K, Feng M, Balter JM. Investigation of a method for generating synthetic CT models from MRI scans of the head and neck for radiotherapy. Phys Med Biol. 2013; 58(23):8419-35.
  • [21]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(4):97-104.
  • [22]Johansson A, Karlsson M, Nyholm T. CT subsititute derived from MRI sequences with ultrashort echo time. Med Phys. 2011; 38(5):2708-14.
  • [23]Marks LB, Yorke ED, Jackson A, Ten Haken RK, Constine LS, Eisbruch A, Bentzen SM, Nam J, Deasy JO. Use of normal tissue complication probability models in the clinic. Int J Radiat Oncol Biol Phys. 2010; 76(3 Suppl):S10-9.
  • [24]van Herk M, Remeijer P, Rasch C, Lebesque JV. The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys. 2000; 47(4):1121-35.
  • [25]Roach M, Faillace-Akazawa P, Malfatti C, Holland J, Hricak H. Prostate volumes defined by magnetic resonance imaging and computerized tomographic scans for three-dimensional conformal radiotherapy. Int J Radiat Oncol Biol Phys. 1996; 35(5):1011-8.
  • [26]Buhl SK, Duun-Christensen AK, Kristensen BH, Behrens CF. Clinical evaluation of 3D/3D MRI-CBCT automatching on brain tumors for online patient setup verification – A step towards MRI-based treatment planning. Acta Oncol. 2010; 49(7):1085-91.
  • [27]Helle M, Stehning C, Traughber MS, Schadewaldt N, Schulz H, Renisch S, et al. Comparison of sequences for MR-based cortical bone imaging and tissue classification in the pelvis at 3.0 T with subsequent generation of electron density maps and digitally reconstructed radiographs. ISMRM proceedings 2013. www.ismrm.org/13/session76.htm.
  • [28]Enders J, Rief M, Zimmermann E, Asbach P, Diederichs G, Wetz C, Siebert E, Wagner M, Hamm B, Dewey M. High-field open versus short-bore magnetic resonance imaging of the spine: a randomized controlled comparison of image quality. PLoS One. 2013; 8(12):e83427.
  • [29]Wang D, Doddrell DM, Cowin G. A novel phantom and method for comprehensive 3-dimensional measurement and correction of geometric distortion in magnetic resonance imaging. Magn Reson Imaging. 2004; 22(4):529-42.
  • [30]Moerland MA, Beersma R, Bhagwandien R, Wijrdeman HK, Bakker CJ. Analysis and correction of geometric distortions in 1.5 T magnetic resonance images for use in radiotherapy treatment planning. Phys Med Biol. 1995; 40:1651-4.
  • [31]Baldwin LN, Wachowicz K, Fallone BG. A two-step scheme for distortion rectification of magnetic resonance images. Med Phys. 2009; 36(9):3917-26.
  • [32]Cao Y, Wang H, Balter J. Characterization of Patient-Induced Geometric Distortions in Clincal Brain MRI on a 3 T MR Simulator. Pract Radiat Oncol. 2013; 3(2 Suppl 1):S7.
  • [33]Wachowicz K, Stanescu T, Thomas SD, Fallone BG. Implications of tissue magnetic susceptibility-related distortion on the rotating magnet in an MR-linac design. Med Phys. 2010; 37(4):1714-21.
  • [34]Kim J, Glide-Hurst C, Doemer A, Wen N, Movsas B, Chetty IJ. Implementation of a novel algorithm for generating synthetic CT images from magnetic resonance imaging datasets for prostate cancer radiation therapy. Int J Radiat Oncol Biol Phys 2014 Nov 7. [Epub ahead of print].
  • [35]Li H, Noel C, Chen H, Harold Li H, Low D, Moore K, Klahr P, Michalski J, Gay HA, Thorstad W, Mutic S. Clinical evaluation of commercial orthopedic metal artifact reduction tool for CT simulations in radiation therapy. Med Phys. 2012; 39(12):7507-17.
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