Original paper| Volume 60, P83-90, April 2019

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Volumetric modulated arc therapy planning based on virtual monochromatic images: Effect of inaccurate CT numbers on dose distributions

Published:March 29, 2019DOI:


      • CT numbers in the low energy VMI can be inaccurate for high density materials.
      • HU values in the VMI77keV is less affected by the scanning protocols than 120 kVp image.
      • The effect of the inaccurate CT numbers on PTV was more prominent in AXB than AAA.
      • Maximum dosimetric error in VMAT planning based on the VMI50keV was 0.5 Gy.
      • The dosimetric error due to the inaccurate HU estimation may be clinically insignificant.



      Though virtual monochromatic images (VMIs) at low energy levels can improve image quality, the measured Hounsfield unit (HU) values can be inaccurate. We assessed the dosimetric error due to inaccurate HU estimation in volumetric modulated arc therapy (VMAT) planning.


      Based on the VMIs at 50 keV (VMI50keV), 77 keV (VMI77keV) and single-energy CT (SECT) image for a phantom with different sizes, lookup tables (LUTL and LUTS) were created. Using an anthropomorphic phantom (head and spine regions), VMAT plans were generated based on VMI50keV, VMI77keV and SECT using the corresponding LUTL, and then, the doses were re-calculated using LUTS. For clinical cases, 30 VMAT plans (prostate, brain, and spine cases) were generated based on VMI50keV and VMI77keV.


      In the anthropomorphic phantom study, the difference in the dosimetric parameters for planning target volume (PTV) in the VMAT plan based on the VMI77keV was smallest (within 0.1 Gy) among three types of treatment planning approach. In clinical cases, in general, the differences of the 3-dimensional gamma passing rate and dosimetric parameters in the treatment plans based on the VMI50keV were larger than those in the VMI77keV. Especially for brain cases, the difference for PTV was more prominent when AXB was used (the maximum difference was 0.5 Gy) than AAA.


      The dosimetric error due to the inaccurate HU estimation was larger in the VMIs at low energy levels. This may be clinically insignificant, but should be avoided in the VMAT treatment planning.


      DECT (dual-energy CT), VMI (virtual monochromatic image), SECT (single-energy CT), LUT (lookup table)


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        • Verbakel W.F.A.R.
        • Senan S.
        • Cuijpers J.P.
        • Slotman B.J.
        • Lagerwaard F.J.
        Rapid delivery of stereotactic radiotherapy for peripheral lung tumors using volumetric intensity-modulated arcs.
        Radiother Oncol. 2009; 93: 122-124
        • Quan E.M.
        • Li X.
        • Li Y.
        • Wang X.
        • Kudchadker R.J.
        • Johnson J.L.
        • et al.
        Clinical investigation: genitourinary cancer a comprehensive comparison of IMRT and VMAT plan quality for prostate cancer treatment.
        Int J Radiat Oncol Biol Phys. 2012; 83: 1169-1178
        • Balaji K.
        • Yadav P.
        • BalajiSubramanian S.
        • Anu Radha C.
        • Ramasubramanian V.
        Hybrid volumetric modulated arc therapy for chest wall irradiation: for a good plan, get the right mixture.
        Phys Med. 2018; 52: 86-92
        • Johnson T.R.C.
        Dual-energy CT: general principles.
        AJR Am J Roentgenol. 2012; 199: S3-S8
        • Ohira S.
        • Wada K.
        • Hirata T.
        • Kanayama N.
        • Ikawa T.
        • Karino T.
        • et al.
        Clinical implementation of contrast-enhanced four-dimensional dual-energy computed tomography for target delineation of pancreatic cancer.
        Radiother Oncol. 2018; (in press)
        • Wichmann J.L.
        • Nöske E.-M.
        • Kraft J.
        • Burck I.
        • Wagenblast J.
        • Eckardt A.
        • et al.
        Virtual monoenergetic dual-energy computed tomography: optimization of kiloelectron volt settings in head and neck cancer.
        Invest Radiol. 2014; 49: 735-741
        • Shuman W.P.
        • Green D.E.
        • Busey J.M.
        • Mitsumori L.M.
        • Choi E.
        • Koprowicz K.M.
        • et al.
        Dual-energy liver CT: effect of monochromatic imaging on lesion detection, conspicuity, and contrast-to-noise ratio of hypervascular lesions on late arterial phase.
        Am J Roentgenol. 2014; 203: 601-606
        • Goodsitt M.M.
        • Christodoulou E.G.
        • Larson S.C.
        Accuracies of the synthesized monochromatic CT numbers and effective atomic numbers obtained with a rapid kVp switching dual energy CT scanner.
        Med Phys. 2011; 38: 2222-2232
        • Ohira S.
        • Karino T.
        • Ueda Y.
        • Nitta Y.
        • Kanayama N.
        • Miyazaki M.
        • et al.
        How well does dual-energy CT with fast kilovoltage switching quantify CT number and iodine and calcium concentrations?.
        Acad Radiol. 2018; 25: 519-528
        • Ohira S.
        • Yagi M.
        • Iramina H.
        • Karino T.
        • Washio H.
        • Ueda Y.
        • et al.
        Treatment planning based on water density image generated using dual- energy computed tomography for pancreatic cancer with contrast-enhancing agent: phantom and clinical study.
        Med Phys. 2018; 45: 5208-5217
        • Nelms B.E.
        • Opp D.
        • Robinson J.
        • Wolf T.K.
        • Zhang G.
        • Moros E.
        • et al.
        VMAT QA: measurement-guided 4D dose reconstruction on a patient.
        Med. Phys. 2012; 39: 4228-4238
        • Yagi M.
        • Ueguchi T.
        • Koizumi M.
        • Ogata T.
        • Yamada S.
        • Takahashi Y.
        • et al.
        Gemstone spectral imaging: determination of CT to ED conversion curves for radiotherapy treatment planning.
        J Appl Clin Med Phys. 2013; 14: 173-186
        • Zurl B.
        • Tiefling R.
        • Winkler P.
        • Kindl P.
        • Kapp K.S.
        Hounsfield units variations: impact on CT-density based conversion tables and their effects on dose distribution.
        Strahlenther Onkol. 2014; 190: 88-93
        • Tsukihara M.
        • Noto Y.
        • Sasamoto R.
        • Hayakawa T.
        • Saito M.
        Initial implementation of the conversion from the energy-subtracted CT number to electron density in tissue inhomogeneity corrections: an anthropomorphic phantom study of radiotherapy treatment planning.
        Med Phys. 2015; 42: 1378-1388
        • Pelgrim G.J.
        • van Hamersvelt R.W.
        • Willemink M.J.
        • Schmidt B.T.
        • Flohr T.
        • Schilham A.
        • et al.
        Accuracy of iodine quantification using dual energy CT in latest generation dual source and dual layer CT.
        Eur Radiol. 2017; 27: 3904-3912
        • Sakabe D.
        • Funama Y.
        • Taguchi K.
        • Nakaura T.
        • Utsunomiya D.
        • Oda S.
        • et al.
        Image quality characteristics for virtual monoenergetic images using dual-layer spectral detector CT: comparison with conventional tube-voltage images.
        Phys Med. 2018; 49: 5-10