2014
DOI: 10.1118/1.4888194
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SU‐E‐J‐141: Comparison of Dose Calculation On Automatically Generated MRBased ED Maps and Corresponding Patient CT for Clinical Prostate EBRT Plans

Abstract: Purpose: To analyze the effect of computing radiation dose on automatically generated MR‐based simulated CT images compared to true patient CTs. Methods: Six prostate cancer patients received a regular planning CT for RT planning as well as a conventional 3D fast‐field dual‐echo scan on a Philips 3.0T Achieva, adding approximately 2 min of scan time to the clinical protocol. Simulated CTs (simCT) where synthesized by assigning known average CT values to the tissue classes air, water, fat, cortical and cancello… Show more

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Cited by 5 publications
(5 citation statements)
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“…The commercial MRCAT package for syn-CT generation uses a single mDIXON MRI sequence and proprietary algorithm to generate electron density information (figure 2) (Helle et al 2014, Schadewaldt et al 2014, Köhler et al 2015). MRCAT is based on a dual-echo 3D Cartesian mDIXON acquisition that generates fat only, water only, in-phase and out-of-phase sequences.…”
Section: Methodsmentioning
confidence: 99%
“…The commercial MRCAT package for syn-CT generation uses a single mDIXON MRI sequence and proprietary algorithm to generate electron density information (figure 2) (Helle et al 2014, Schadewaldt et al 2014, Köhler et al 2015). MRCAT is based on a dual-echo 3D Cartesian mDIXON acquisition that generates fat only, water only, in-phase and out-of-phase sequences.…”
Section: Methodsmentioning
confidence: 99%
“…In the following we will briefly outline the main ideas of the approach. MRCAT is a bulk assignment pCT generation method based on sequential intensityand model-based segmentation techniques (Schadewaldt et al 2014). In particular, MRCAT segments the images from the dedicated MR sequence (see section 2.1) into 5 classes, and assigns each class the pseudo-HU values specified in table 1 (middle column).…”
Section: Pct Generationmentioning
confidence: 99%
“…257, Philips Healthcare, Vantaa, Finland). MRCAT is a bulk assignment pCT generation method based on sequential intensity-and model-based segmentation techniques (Schadewaldt et al 2014). In particular, MRCAT segments images from a dedicated MR sequence (see section 2.1) into five classes, and assigns to each class the pseudo-HU specified in table 1.…”
Section: Image Processing For Pct Generationmentioning
confidence: 99%
“…To estimate tissue attenuation properties from MRI, several methods have been proposed in the last few decades (Lee et al 2003, Chen et al 2004, Schmidt and Payne 2015, Prior et al 2016. More recently, MRI vendors have launched solutions as well (Schadewaldt et al 2014, Siversson et al 2015. The proposed methods can be categorised into three classes (Prior et al 2016): (1) atlas-based, (2) voxel-based or (3) bulk assignment-based techniques.…”
Section: Introductionmentioning
confidence: 99%