Shingo Ohira1,2, Yasuhiro Imai3, Yuhei Koike4, Shunsuke Ono5, Yoshihiro Ueda5, Masayoshi Miyazaki5, Masahiko Koizumi2, Koji Konishi5. 1. Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan; oohira-si@mc.pref.osaka.jp. 2. Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Osaka, Japan. 3. CT Engineering, GE Healthcare Japan Corporation, Tokyo, Japan. 4. Department of Radiology, Kansai Medical University, Osaka, Japan. 5. Department of Radiation Oncology, Osaka International Cancer Institute, Osaka, Japan.
Abstract
BACKGROUND/AIM: This study evaluated the calculation accuracy of the stopping power ratio (SPR) using dual-energy computed tomography with fast kilovoltage switching (FKSCT) for particle therapy. MATERIALS AND METHODS: A tissue characterization phantom with various reference materials was scanned to obtain single-energy computed tomography (SECT) images and generate virtual monochromatic images at 77 keV (VMI77keV) and 140 keV (VMI140keV), water density (WD) images, and effective Z (Zeff) images. For SECT, VMI77keV and VMI140keV lookup tables were generated to convert the measured Hounsfield value into the theoretical SPR for a normal phantom size. Subsequently, the reference materials were scanned in small and large phantoms. The SPR was calculated using the lookup tables of SECT (SPRSECT) images, VMI77keV (SPR77keV), and VMI140keV (SPR140keV), and it was derived from the WD and Zeff (SPRWD). RESULTS: In the normal-sized phantom, the overall mean difference between SPRWD and theoretical SPR was -0.3%, and remained below 2% for most reference materials. For the large phantom, the overall mean absolute difference for SPR140keV (3.0%, p=0.006) and SPRWD (3.2%, p=0.002) for the reference materials was significantly lower than that for SPRSECT (5.9%). For the small phantom, a significant reduction in the mean difference in the SPR calculation was observed in SPR77keV (1.0%, p=0.001) and SPR140keV (1.1%, p=0.013) compared with SPRSECT (2.2%). CONCLUSION: VMI140keV generated using FKSCT significantly improves the estimation accuracy of SPR compared with SECT. Thus, FKSCT may be used to improve the dose calculation accuracy for treatment planning of particle therapy.
BACKGROUND/AIM: This study evaluated the calculation accuracy of the stopping power ratio (SPR) using dual-energy computed tomography with fast kilovoltage switching (FKSCT) for particle therapy. MATERIALS AND METHODS: A tissue characterization phantom with various reference materials was scanned to obtain single-energy computed tomography (SECT) images and generate virtual monochromatic images at 77 keV (VMI77keV) and 140 keV (VMI140keV), water density (WD) images, and effective Z (Zeff) images. For SECT, VMI77keV and VMI140keV lookup tables were generated to convert the measured Hounsfield value into the theoretical SPR for a normal phantom size. Subsequently, the reference materials were scanned in small and large phantoms. The SPR was calculated using the lookup tables of SECT (SPRSECT) images, VMI77keV (SPR77keV), and VMI140keV (SPR140keV), and it was derived from the WD and Zeff (SPRWD). RESULTS: In the normal-sized phantom, the overall mean difference between SPRWD and theoretical SPR was -0.3%, and remained below 2% for most reference materials. For the large phantom, the overall mean absolute difference for SPR140keV (3.0%, p=0.006) and SPRWD (3.2%, p=0.002) for the reference materials was significantly lower than that for SPRSECT (5.9%). For the small phantom, a significant reduction in the mean difference in the SPR calculation was observed in SPR77keV (1.0%, p=0.001) and SPR140keV (1.1%, p=0.013) compared with SPRSECT (2.2%). CONCLUSION: VMI140keV generated using FKSCT significantly improves the estimation accuracy of SPR compared with SECT. Thus, FKSCT may be used to improve the dose calculation accuracy for treatment planning of particle therapy.
Authors: Nora Hünemohr; Bernhard Krauss; Christoph Tremmel; Benjamin Ackermann; Oliver Jäkel; Steffen Greilich Journal: Phys Med Biol Date: 2013-12-12 Impact factor: 3.609
Authors: David P Labbé; Giorgia Zadra; Meng Yang; Jaime M Reyes; Charles Y Lin; Stefano Cacciatore; Ericka M Ebot; Amanda L Creech; Francesca Giunchi; Michelangelo Fiorentino; Habiba Elfandy; Sudeepa Syamala; Edward D Karoly; Mohammed Alshalalfa; Nicholas Erho; Ashley Ross; Edward M Schaeffer; Ewan A Gibb; Mandeep Takhar; Robert B Den; Jonathan Lehrer; R Jeffrey Karnes; Stephen J Freedland; Elai Davicioni; Daniel E Spratt; Leigh Ellis; Jacob D Jaffe; Anthony V DʼAmico; Philip W Kantoff; James E Bradner; Lorelei A Mucci; Jorge E Chavarro; Massimo Loda; Myles Brown Journal: Nat Commun Date: 2019-09-25 Impact factor: 14.919
Authors: Vicki T Taasti; Christian Bäumer; Christina V Dahlgren; Amanda J Deisher; Malte Ellerbrock; Jeffrey Free; Joanna Gora; Anna Kozera; Antony J Lomax; Ludovic De Marzi; Silvia Molinelli; Boon-Keng Kevin Teo; Patrick Wohlfahrt; Jørgen B B Petersen; Ludvig P Muren; David C Hansen; Christian Richter Journal: Phys Imaging Radiat Oncol Date: 2018-04-30