Combined single- and dual-energy CT workflow for dose calculation in radiotherapy
DOI:
https://doi.org/10.2340/1651-226X.2025.43827Keywords:
radiotherapy planning, imaging, computed tomography, phantom, algorithmAbstract
Background and purpose: Dual-energy computed tomography (DECT) is increasingly used in radiotherapy delineation due to its enhanced soft tissue contrast. DECT also supports direct dose calculation. However, as most current DECT scanners allow for use in only certain body regions, conventional single-energy computed tomography (SECT) is still needed for some patients. A safe clinical introduction of DECT thus requires a combined workflow. This study therefore investigates whether a unified Hounsfield look-up table (HLUT) can be applied across SECT and DECT reconstructions.
Patient/material and methods: A Gammex Advanced Electron Density phantom containing
tissue-equivalent inserts was scanned using SECT (70–140 kVp and Sn100–Sn140 kVp, Sn meaning tin-filtered) and dual-spiral DECT to identify matching HLUTs for three SECT methods, including a standard reconstruction (only 120 kVp; Method 1), and kVp-independent reconstructions providing mass density (MD; Method 2) or relative electron density (RED; Method 3). Dose agreement was subsequently tested on two anthropomorphic phantoms. For each SECT method, DECT reconstructions were compared through voxel-wise analysis of computed tomography (CT) numbers, and by performing dose calculations in three anatomical regions: head, thorax, and abdomen/pelvis.
Results: Across all three SECT methods, DECT reconstructions with acceptable clinical CT number agreement were identified. Corresponding dose calculations between SECT- and DECT-based plans showed minimal differences.
Interpretation: This phantom study demonstrates that a unified HLUT can be applied across SECT and DECT using standard 120 kVp, MD, or RED reconstructions. This approach may streamline clinical workflows and support a safe and practical transition to DECT-based treatment planning.
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References
Gardner SJ, Kim J, Chetty IJ. Modern radiation therapy planning and delivery. Hematol Oncol Clin North Am. 2019;33:947–62.
https://doi.org/10.1016/j.hoc.2019.08.005 DOI: https://doi.org/10.1016/j.hoc.2019.08.005
Goldman LW. Principles of CT and CT technology. J Nucl Med Technol. 2007;35:115–30.
https://doi.org/10.2967/jnmt.107.042978 DOI: https://doi.org/10.2967/jnmt.107.042978
Kang P, Liao M, Wester MR, Leeder JS, Pearce RE. Standardization and optimization of computed tomography protocols to achieve low-dose. Ratio. 2014;36:490–9.
https://doi.org/10.1016/j.jacr.2013.10.016 DOI: https://doi.org/10.1016/j.jacr.2013.10.016
Saini A, Pandey V, Kumar P, Singh A, Pasricha R. Investigation of tube voltage dependence on CT number and its effect on dose calculation algorithms using thorax phantom in Monaco treatment planning system for external beam radiation therapy. J Med Phys. 2021;46:315–23.
https://doi.org/10.4103/jmp.JMP_124_20 DOI: https://doi.org/10.4103/jmp.JMP_124_20
Flatten V, Friedrich A, Engenhart-Cabillic R, Zink K. A phantom based evaluation of the dose prediction and effects in treatment plans, when calculating on a direct density CT reconstruction. J Appl Clin Med Phys. 2020;21:52–61.
https://doi.org/10.1002/acm2.12824 DOI: https://doi.org/10.1002/acm2.12824
van der Heyden B, Öllers M, Ritter A, Verhaegen F, van Elmpt W. Clinical evaluation of a novel CT image reconstruction algorithm for direct dose calculations. Phys Imaging Radiat Oncol. 2017;2:11–16.
https://doi.org/10.1016/j.phro.2017.03.001 DOI: https://doi.org/10.1016/j.phro.2017.03.001
Nelson G, Pigrish V, Sarkar V, Su FC, Salter B. Technical note: the use of DirectDensity TM and dual-energy CT in the radiation oncology clinic. J Appl Clin Med Phys. 2019;20:125–31.
https://doi.org/10.1002/acm2.12546 DOI: https://doi.org/10.1002/acm2.12546
Kruis MF. Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT. J Appl Clin Med Phys. 2022;23:1–17.
https://doi.org/10.1002/acm2.13468 DOI: https://doi.org/10.1002/acm2.13468
Tatsugami F, Higaki T, Nakamura Y, Honda Y, Awai K. Dual-energy CT: minimal essentials for radiologists. Jpn J Radiol. 2022;40:547–59.
https://doi.org/10.1007/s11604-021-01233-2 DOI: https://doi.org/10.1007/s11604-021-01233-2
Kraft J, Lutyj P, Grabenbauer F, Ströhle SP, Tamihardja J, Razinskas G, et al. Assessment of dual-energy computed tomography derived virtual monochromatic imaging for target volume delineation of brain metastases. Radiother Oncol. 2023;187:109840.
https://doi.org/10.1016/j.radonc.2023.109840 DOI: https://doi.org/10.1016/j.radonc.2023.109840
Noid G, Zhu J, Tai A, Mistry N, Schott D, Prah D, et al. Improving structure delineation for radiation therapy planning using dual-energy CT. Front Oncol. 2020;10:1–11.
https://doi.org/10.3389/fonc.2020.01694 DOI: https://doi.org/10.3389/fonc.2020.01694
Taasti VT, Wohlfahrt P. From computed tomography innovation to routine clinical application in radiation oncology – a joint initiative of close collaboration. Phys Imaging Radiat Oncol. 2024;29:100550.
https://doi.org/10.1016/j.phro.2024.100550 DOI: https://doi.org/10.1016/j.phro.2024.100550
Johnson TRC. Dual-energy CT: general principles. AJR Am J Roentgenol. 2012;199:S3–8.
https://doi.org/10.2214/AJR.12.9116 DOI: https://doi.org/10.2214/AJR.12.9116
McCollough CH, Leng S, Yu L, Fletcher JG. Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology. 2015;276:637–53.
https://doi.org/10.1148/radiol.2015142631 DOI: https://doi.org/10.1148/radiol.2015142631
Albrecht MH, Vogl TJ, Martin SS, Nance JW, Duguay TM, Wichmann JL, et al. Review of clinical applications for virtual monoenergetic dual-energy CT. Radiology. 2019;293:260–71.
https://doi.org/10.1148/radiol.2019182297 DOI: https://doi.org/10.1148/radiol.2019182297
Zhu Q, Wei S, Wang Z, Xu H, Zhou B, Qu H, et al. Feasibility of dose calculation for treatment plans using electron density maps from a novel dual-layer detector spectral CT simulator. Radiat Oncol. 2024;19:1–9.
https://doi.org/10.1186/s13014-024-02479-6 DOI: https://doi.org/10.1186/s13014-024-02479-6
Yang M, Wohlfahrt P, Shen C, Bouchard H. Dual- and multi-energy CT for particle stopping-power estimation: current state, challenges and potential. Phys Med Biol. 2023;68:04TR01.
https://doi.org/10.1088/1361-6560/acabfa DOI: https://doi.org/10.1088/1361-6560/acabfa
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;45:5208–17.
https://doi.org/10.1002/mp.13180 DOI: https://doi.org/10.1002/mp.13180
Ohira S, Komiyama R, Karino T, Washio H, Ueda Y, Miyazaki M, et al. Volumetric modulated arc therapy planning based on virtual monochromatic images: effect of inaccurate CT numbers on dose distributions. Phys Medica. 2019;60:83–90.
https://doi.org/10.1016/j.ejmp.2019.03.022 DOI: https://doi.org/10.1016/j.ejmp.2019.03.022
Edmund J, Feen Rønjom M, van Overeem Felter M, Maare C, Margrete Juul Dam A, Tsaggari E, et al. Split-filter dual energy computed tomography radiotherapy: from calibration to image guidance. Phys Imaging Radiat Oncol. 2023;28:100495.
https://doi.org/10.1016/j.phro.2023.100495 DOI: https://doi.org/10.1016/j.phro.2023.100495
Noid G, Schott D, Paulson E, Zhu J, Shah J, Li XA. Technical note: using virtual noncontrast images from dual-energy CT to eliminate the need of precontrast CT for x-ray radiation treatment planning of abdominal tumors. Med Phys. 2021;48:1365–71.
https://doi.org/10.1002/mp.14702 DOI: https://doi.org/10.1002/mp.14702
Peters N, Trier Taasti V, Ackermann B, Bolsi A, Vallhagen Dahlgren C, Ellerbrock M, et al. Consensus guide on CT-based prediction of stopping-power ratio using a Hounsfield look-up table for proton therapy. Radiother Oncol. 2023;184:109675.
https://doi.org/10.1016/j.radonc.2023.109675 DOI: https://doi.org/10.1016/j.radonc.2023.109675
Lifton JJ, Malcolm AA. Estimating the product of the x-ray spectrum and quantum detection efficiency of act system and its application to beam hardening correction. Sensors. 2021;21:3284.
https://doi.org/10.3390/s21093284 DOI: https://doi.org/10.3390/s21093284
Low DA, Harms WB, Mutic S, Purdy JA. A technique for the quantitative evaluation of dose distributions. Med Phys. 1998;25:656–61.
https://doi.org/10.1118/1.598248 DOI: https://doi.org/10.1118/1.598248
Browne JE, Bruesewitz MR, Thomas V, Thomas KB, Hull NC, McCollough CH, et al. Procedure for optimal implementation of automatic tube potential selection in pediatric CT to reduce radiation dose and improve workflow. J Appl Clin Med Phys. 2021;22:194–202.
https://doi.org/10.1002/acm2.13098 DOI: https://doi.org/10.1002/acm2.13098
International Atomic Energy Agency. Absorbed Dose Determination in External Beam Radiotherapy, Technical Reports Series No. 398 (Rev. 1), IAEA, Vienna, 2024.
International Commission on Radiation Units and Measurements. ICRU Report 44: Tissue substitutes in radiation dosimetry and measurement. Bethesda (MD): ICRU; 1989.
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Copyright (c) 2025 Hella Sand, Jens Edmund, Ane Appelt, Patrick Wohlfahrt, Vicki Trier Taasti , Laurids Østergaard Poulsen, Jimmi Søndergaard, Martin Skovmos Nielsen
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