Literature DB >> 30198189

Treatment planning based on water density image generated using dual-energy computed tomography for pancreatic cancer with contrast-enhancing agent: Phantom and clinical study.

Shingo Ohira1,2, Masashi Yagi3, Hiraku Iramina4,5, Tsukasa Karino1, Hayate Washio1, Yoshihiro Ueda1, Masayoshi Miyazaki1, Masahiko Koizumi2, Teruki Teshima1.   

Abstract

PURPOSE: A contrast-enhancing agent is imperative for the accurate target delineation of pancreatic tumors. This study demonstrates the potential use of treatment planning for patients with pancreatic tumors based on the water density image (WDI) generated by dual-energy computed tomography (DECT).
METHODS: Tissue characterization and multi-energy phantom scanning were performed through DECT and the physical characteristics of the WDI and a virtual monochromatic image (VMI) were assessed. The measured and the corresponding theoretical electron density relative to water (RED) and mass density (MD) were compared. Treatment plans based on the WDI (TPWDI ) and VMI (TPVMI ) were compared for 22 pancreatic cancer patients who underwent contrast-enhanced DECT scan.
RESULTS: The total absolute difference in the HU value between the conventional 120 kVp images and the VMI was the smallest at the energy level of 77 keV (3.3 HU), and the VMI at 77 keV was used for subsequent analysis. The difference between the measured and theoretical values of RED and MD for iodine using the VMI (>15%) was larger than that using WDI (<4%). In clinical cases, the maximum difference in the dosimetric parameters between TPWDI and TPWDI for the planning target volume was 3.0% when the doses were calculated using AXB, and for the duodenum, it was 1.7%.
CONCLUSIONS: The WDI estimated the RED and MD accurately and could form the basis for a new treatment planning approach for pancreatic cancer using contrast-enhancing agent.
© 2018 American Association of Physicists in Medicine.

Entities:  

Keywords:  contrast-enhancing agent; dual-energy computed tomography; pancreatic cancer; treatment planning; water density image

Mesh:

Substances:

Year:  2018        PMID: 30198189     DOI: 10.1002/mp.13180

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  4 in total

1.  Evaluation of Stopping Power Ratio Calculation Using Dual-energy Computed Tomography With Fast Kilovoltage Switching for Treatment Planning of Particle Therapy.

Authors:  Shingo Ohira; Yasuhiro Imai; Yuhei Koike; Shunsuke Ono; Yoshihiro Ueda; Masayoshi Miyazaki; Masahiko Koizumi; Koji Konishi
Journal:  In Vivo       Date:  2022 Jan-Feb       Impact factor: 2.155

2.  Convolutional neural network-based automatic liver delineation on contrast-enhanced and non-contrast-enhanced CT images for radiotherapy planning.

Authors:  Naohiro Sakashita; Kiyonori Shirai; Yoshihiro Ueda; Ayuka Ono; Teruki Teshima
Journal:  Rep Pract Oncol Radiother       Date:  2020-10-02

3.  Volumetric modulated arc therapy treatment planning based on virtual monochromatic images for head and neck cancer: effect of the contrast-enhanced agent on dose distribution.

Authors:  Riho Komiyama; Shingo Ohira; Naoyuki Kanayama; Tsukasa Karino; Hayate Washio; Yoshihiro Ueda; Masayoshi Miyazaki; Teruki Teshima
Journal:  J Appl Clin Med Phys       Date:  2019-10-21       Impact factor: 2.102

Review 4.  Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT.

Authors:  Matthijs Ferdinand Kruis
Journal:  J Appl Clin Med Phys       Date:  2021-11-07       Impact factor: 2.102

  4 in total

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