Magnetic resonance-only simulation and dose calculation in external beam radiation therapy: a feasibility study for pelvic cancers

Abstract Background: The clinical feasibility of using pseudo-computed tomography (pCT) images derived from magnetic resonance (MR) images for external bean radiation therapy (EBRT) planning for prostate cancer patients has been well demonstrated. This paper investigates the feasibility of applying an MR-derived, pCT planning approach to additional types of cancer in the pelvis. Material and methods: Fifteen patients (five prostate cancer patients, five rectal cancer patients, and five gynecological cancer patients) receiving EBRT at Turku University Hospital (Turku, Finland) were included in the study. Images from an MRCAT (Magnetic Resonance for Calculating ATtenuation, Philips, Vantaa, Finland) pCT method were generated as a part of a clinical MR-simulation procedure. Dose calculation accuracy was assessed by comparing the pCT-based calculation with a CT-based calculation. In addition, the degree of geometric accuracy was studied. Results: The median relative difference of PTV mean dose between CT and pCT images was within 0.8% for all tumor types. When assessing the tumor site-specific accuracy, the median [range] relative dose differences to the PTV mean were 0.7 [−0.11;1.05]% for the prostate cases, 0.3 [−0.25;0.57]% for the rectal cases, and 0.09 [−0.69;0.25]% for the gynecological cancer cases. System-induced geometric distortion was measured to be less than 1 mm for all PTV volumes and the effect on the PTV median dose was less than 0.1%. Conclusions: According to the comparison, using pCT for clinical EBRT planning and dose calculation in the three investigated types of pelvic cancers is feasible. Further studies are required to demonstrate the applicability to a larger cohort of patients.

[1]  Fredrik Nordström,et al.  Technical Note: MRI only prostate radiotherapy planning using the statistical decomposition algorithm. , 2015, Medical physics.

[2]  Maria A Schmidt,et al.  Radiotherapy planning using MRI , 2015, Physics in medicine and biology.

[3]  J. Dimopoulos,et al.  Systematic evaluation of MRI findings in different stages of treatment of cervical cancer: potential of MRI on delineation of target, pathoanatomic structures, and organs at risk. , 2006, International journal of radiation oncology, biology, physics.

[4]  Koen Van Leemput,et al.  A patch-based pseudo-CT approach for MRI-only radiotherapy in the pelvis. , 2016, Medical physics.

[5]  R. Hoogeveen,et al.  MR-only simulation for radiotherapy planning , 2015 .

[6]  Mary Feng,et al.  Quantitative characterizations of ultrashort echo (UTE) images for supporting air–bone separation in the head , 2015, Physics in medicine and biology.

[7]  H. Eggers,et al.  Dual‐echo Dixon imaging with flexible choice of echo times , 2011, Magnetic resonance in medicine.

[8]  Peter Metcalfe,et al.  Continuous table acquisition MRI for radiotherapy treatment planning: distortion assessment with a new extended 3D volumetric phantom. , 2015, Medical physics.

[9]  R. Adams,et al.  Imaging for target volume delineation in rectal cancer radiotherapy--a systematic review. , 2012, Clinical oncology (Royal College of Radiologists (Great Britain)).

[10]  Peter Metcalfe,et al.  MRI distortion: considerations for MRI based radiotherapy treatment planning , 2014, Australasian Physical & Engineering Sciences in Medicine.

[11]  Tufve Nyholm,et al.  Systematisation of spatial uncertainties for comparison between a MR and a CT-based radiotherapy workflow for prostate treatments , 2009, Radiation oncology.

[12]  Carri Glide-Hurst,et al.  Dosimetric evaluation of synthetic CT relative to bulk density assignment-based magnetic resonance-only approaches for prostate radiotherapy , 2015, Radiation oncology.

[13]  Olivier Salvado,et al.  An atlas-based electron density mapping method for magnetic resonance imaging (MRI)-alone treatment planning and adaptive MRI-based prostate radiation therapy. , 2012, International journal of radiation oncology, biology, physics.

[14]  Tiina Seppälä,et al.  A dual model HU conversion from MRI intensity values within and outside of bone segment for MRI-based radiotherapy treatment planning of prostate cancer. , 2013, Medical physics.

[15]  Mark Jenkinson,et al.  Fast, automated, N‐dimensional phase‐unwrapping algorithm , 2003, Magnetic resonance in medicine.

[16]  J. Edmund,et al.  Patch-based generation of a pseudo CT from conventional MRI sequences for MRI-only radiotherapy of the brain. , 2015, Medical physics.

[17]  Ken-Pin Hwang,et al.  Spatial Precision in Magnetic Resonance Imaging-Guided Radiation Therapy: The Role of Geometric Distortion. , 2016, International journal of radiation oncology, biology, physics.

[18]  Fang-Fang Yin,et al.  Four-dimensional magnetic resonance imaging using axial body area as respiratory surrogate: initial patient results. , 2014, International Journal of Radiation Oncology, Biology, Physics.

[19]  B Gino Fallone,et al.  A two-step scheme for distortion rectification of magnetic resonance images. , 2009, Medical physics.

[20]  D A Jaffray,et al.  Characterization of tissue magnetic susceptibility-induced distortions for MRIgRT. , 2012, Medical physics.

[21]  J. Sonke,et al.  Feasibility of MRI-based reference images for image-guided radiotherapy of the pelvis with either cone-beam computed tomography or planar localization images , 2015, Acta oncologica.