The Feasibility of Synthetic Computed Tomography (sCT) Generated from Magnetic Resonance for Calculating ATenuation (MRCAT) in Prostate Cancer for External Beam Radiotherapy Dose Calculation

Authors

  • pronpawee pudsena Master degree of Science Program in Medical Physics, Faculty of Medical Siriraj Hospital, Mahidol University
  • Tanwiwat Jaikuna Division of Radiation Oncology, Department of Radiology, Faculty of Medical Siriraj Hospital, Mahidol University
  • Pitchayut Nakkrasae Division of Radiation Oncology, Department of Radiology, Faculty of Medical Siriraj Hospital, Mahidol University
  • Wisawa Phongprapun Division of Radiation Oncology, Department of Radiology, Faculty of Medical Siriraj Hospital, Mahidol University
  • Pittaya Dankulchai Division of Radiation Oncology, Department of Radiology, Faculty of Medical Siriraj Hospital, Mahidol University

Keywords:

MRCAT, MR-only planning, Prostate cancer, Synthetic CT

Abstract

Background: Magnetic resonance (MR) image has recently become a trendy use for external beam radiotherapy (EBRT) dose calculation according to the dominance of high soft tissue contrast. However, the main challenge of applying an MR image for dose calculation is the lack of a correlation between the material's density and the computed tomography (CT) number in the MR image, which is mandatory for dose calculation in a commercial treatment planning system. Thus, synthetic CT (sCT) is introduced for EBRT dose calculation.

Objectives: This study aims to examine the feasibility of using MR image for Calculating ATtenuation (MRCAT)-sCT imaging in prostate cancer patients to calculate the external beam dose.

Materials and methods: Ten prospective prostate cancer patients were enrolled in this study. The pCT and MR images were acquired using the pre-imaging protocol. Tumors and organs at risk (OARs) were delineated on planning CT (pCT) and sCT. The Hounsfield unit (HU) of each organ was compared between pCT and sCT. The volumetric modulated arc therapy (VMAT) plan was generated on pCT and calculated based on the Acuros XB (AXB) algorithm using Eclipse, then recalculated on sCT. The similarity between pCT- and sCT-based dose was evaluated using dosimetric data extracted from the dose-volume histogram and 3D gamma analysis.

Results: This study demonstrated a minor difference in HU between sCT and pCT in soft tissue (13.02 15.58 HU) while the discrimination of HU was larger in femur bone (51.59 49.08 HU). The mean HU of soft tissue in sCT was greater than in pCT; contrastingly, the mean HU of bone from sCT was lower than in pCT. The dose distributions calculated from sCT and pCT were similar (>95% gamma passing rate at all criteria (varies from 3%3mm to 1%1mm). Each dosimetric determination showed insignificant differences across all relevant contours.

Conclusion: MRCAT-generated sCT can calculate prostate cancer EBRT doses with a negligible dose difference from pCT. This study promotes prostate EBRT using MR-only workflow.

References

Engeler CE, Wasserman NF, Zhang G. Preoperative assessment of prostatic carcinoma by computerized tomography. Weaknesses and new perspectives. Urol 1992;40:346-50.

Rasch C, Barillot I, Remeijer P, Touw A, van Herk M, Lebesque JV. Definition of the prostate in CT and MRI: a multi-observer study. Int J Radiat Oncol Biol Phys 1999;43:57-66.

den Hartogh MD, Philippens MEP, van Dam IE, Kleynen CE, Tersteeg RJHA, Pijnappel RM, et al. MRI and CT imaging for preoperative target volume delineation in breast-conserving therapy. Radiat Oncol 2014;9:63.

Platt JF, Bree RL, Schwab RE. The accuracy of CT in the staging of carcinoma of the prostate. Am J Roentgenol 1987;149:315-8.

Claus FG, Hricak H, Hattery RR. Pretreatment evaluation of prostate cancer: role of MR imaging and 1H MR spectroscopy. Radiographics 2004;24 Suppl 1:S167-80.

Turkbey B, Albert PS, Kurdziel K, Choyke PL. Imaging localized prostate cancer: current approaches and new developments. Am J Roentgenol 2009;192:1471-80.

Tyagi N, Fontenla S, Zelefsky M, Chong TM, Ostergren K, Shah N, et al. Clinical workflow for MR-only simulation and planning in prostate. Radiat Oncol 2017;12:119.

Goudschaal K, Beeksma F, Boon M, Bijveld M, Visser J, Hinnen K, et al. Accuracy of an MR-only workflow for prostate radiotherapy using semi-automatically burned-in fiducial markers. Radiat Oncol 2021;16:37-49.

Nierer L, Eze C, da Silva Mendes V, Braun J, Thum P, von Bestenbostel R, et al. Dosimetric benefit of MR-guided online adaptive radiotherapy in different tumor entities: liver, lung, abdominal lymph nodes, pancreas and prostate. Radiat Oncol 2022;17:53-66.

Chen L, Price RA, Jr., Nguyen TB, Wang L, Li JS, Qin L, et al. Dosimetric evaluation of MRI-based treatment planning for prostate cancer. Phys Med Biol 2004;49:5157-70.

Christiansen RL, Jensen HR, Brink C. Magnetic resonance only workflow and validation of dose calculations for radiotherapy of prostate cancer. Acta Oncol 2017;56:787-91.

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;5:62-9.

Dowling JA, Sun J, Pichler P, Rivest-Hénault D, Ghose S, Richardson H, et al. Automatic Substitute Computed Tomography Generation and Contouring for Magnetic Resonance Imaging (MRI)-Alone External Beam Radiation Therapy From Standard MRI Sequences. International Journal of Radiation Oncology Biology Physics 2015;93:1144-53.

Johnstone E, Wyatt JJ, Henry AM, Short SC, Sebag-Montefiore D, Murray L, et al. Systematic Review of Synthetic Computed Tomography Generation Methodologies for Use in Magnetic Resonance Imaging-Only Radiation Therapy. Int J Radiat Oncol Biol Phys 2018;100:199-217.

Rank CM, Tremmel C, Hünemohr N, Nagel AM, Jäkel O, Greilich S. MRI-based treatment plan simulation and adaptation for ion radiotherapy using a classification-based approach. Radiat Oncol 2013;8:51-63.

Nyholm T, Nyberg M, Karlsson MG, Karlsson M. Systematisation of spatial uncertainties for comparison between a MR and a CT-based radiotherapy workflow for prostate treatments. Radiat Oncol 2009;4:54-62.

Dean CJ, Sykes JR, Cooper RA, Hatfield P, Carey B, Swift S, et al. An evaluation of four CT-MRI co-registration techniques for radiotherapy treatment planning of prone rectal cancer patients. Br J Radiol 2012;85:61-8.

Korsager AS, Carl J, Riis Østergaard L. Comparison of manual and automatic MR-CT registration for radiotherapy of prostate cancer. J Appl Clin Med Phys 2016;17:294-303.

Köhler M, Vaara T, Grootel Mv, Hoogeveen RM, Kemppainen R, Renisch S, editors. MR-only simulation for radiotherapy planning White paper: Philips MRCAT for prostate dose calculations using only MRI data. 2015.

eviQ. Prostate adenocarcinoma definitive EBRT hypofractionation: Cancer Institute NSW; 2018 [updated 30 Dec 2021; cited 2023 8 Aug]. Available from: https://www.eviq.org.au/p/3370.

Aisen AM, Martel W, Braunstein EM, McMillin KI, Phillips WA, Kling TF. MRI and CT evaluation of primary bone and soft-tissue tumors. Am J Roentgenol 1986;146:749-56.

Davis AT, Palmer AL, Nisbet A. Can CT scan protocols used for radiotherapy treatment planning be adjusted to optimize image quality and patient dose? A systematic review. Br J Radiol 2017;90:20160406.

Farjam R, Tyagi N, Deasy JO, Hunt MA. Dosimetric evaluation of an atlas-based synthetic CT generation approach for MR-only radiotherapy of pelvis anatomy. J Appl Clin Med Phys 2019;20:101-9.

Kemppainen R, Suilamo S, Tuokkola T, Lindholm P, Deppe MH, Keyrilainen J. Magnetic resonance-only simulation and dose calculation in external beam radiation therapy: a feasibility study for pelvic cancers. Acta Oncol 2017;56:792-8.

Tyagi N, Fontenla S, Zhang J, Cloutier M, Kadbi M, Mechalakos J, et al. Dosimetric and workflow evaluation of first commercial synthetic CT software for clinical use in pelvis. Phys Med Biol 2017;62:2961-75.

Bratova I, Paluska P, Grepl J, Sykorova P, Jansa J, Hodek M, et al. Validation of dose distribution computation on sCT images generated from MRI scans by Philips MRCAT. Rep Pract Oncol Radiother 2019;24:245-50.

Yan C, Combine AG, Bednarz G, Lalonde RJ, Hu B, Dickens K, et al. Clinical implementation and evaluation of the Acuros dose calculation algorithm. J Appl Clin Med Phys 2017;18:195-209.

Buranaporn P, Dankulchai P, Jaikuna T, Prasartseree T. Relation between DIR recalculated dose based CBCT and GI and GU toxicity in postoperative prostate cancer patients treated with VMAT. Radiother Oncol 2021;157:8-14.

Bouyer C, Fargier-Voiron M, Beneux A. Comparison of algorithms AAA and Acuros (AxB) on heterogenous medium. Physica Medica 2017;44:286-91.

Kerkmeijer LGW, Maspero M, Meijer GJ, van der Voort van Zyp JRN, de Boer HCJ, et al. Magnetic resonance imaging only workflow for radiotherapy simulation and planning in prostate cancer. Clin Oncol 2018;30:692-701.

Downloads

Published

2024-04-05

How to Cite

1.
pudsena pronpawee, Jaikuna T, Nakkrasae P, Phongprapun W, Dankulchai P. The Feasibility of Synthetic Computed Tomography (sCT) Generated from Magnetic Resonance for Calculating ATenuation (MRCAT) in Prostate Cancer for External Beam Radiotherapy Dose Calculation. J Thai Assn of Radiat Oncol [Internet]. 2024 Apr. 5 [cited 2024 Jul. 3];30(1):R1-R18. Available from: https://he01.tci-thaijo.org/index.php/jtaro/article/view/267120

Issue

Section

Original articles