Jongmin Cho1, Kira Grogg2, Chul Hee Min3, Xuping Zhu2, Harald Paganetti4, Hyun Cheol Lee3, Georges El Fakhri2. 1. Department of Physics, Oklahoma State University, Stillwater, 74078, OK, USA. 2. Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA. 3. Department of Radiological Science, College of Health Science, Yonsei University, Wonju, Kangwon-Do, Republic of Korea. 4. Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA.
Abstract
PURPOSE: While positron emission tomography (PET) allows for the imaging of tissues activated by proton beams in terms of monitoring the therapy administered, most endogenous tissue elements are activated by relatively high-energy protons. Therefore, a relatively large distance off-set exists between the dose fall-off and activity fall-off. However, 16 O(p,2p,2n)13 N has a relatively low energy threshold which peaks around 12 MeV and also a residual proton range that is approximately 1 to 2 mm. In this phantom study, we tested the feasibility of utilizing the 13 N production peak as well as the differences in activity fall-off between early and late PET scans for proton range verification. One of the main purposes for this research was developing a proton range verification methodology that would not require Monte Carlo simulations. METHODS AND MATERIALS: Both monoenergetic and spread-out Bragg peak beams were delivered to two phantoms - a water-like gel and a tissue-like gel where the proton ranges came to be approximately 9.9 and 9.1 cm, respectively. After 1 min of postirradiation delay, the phantoms were scanned for a period of 30 min using an in-room PET. Two separate (Early and Late) PET images were reconstructed using two different postirradiation delays and acquisition times; Early PET: 1 min delay and 3 min acquisition, Late PET: 21 min delay and 10 min acquisition. The depth gradients of the PET signals were then normalized and plotted as functions of depth. The normalized gradient of the early PET images was subtracted from that of the late PET images, to observe the 13 N activity distribution in relation to depth. Monte Carlo simulations were also conducted with the same set-up as the measurements stated previously. RESULTS: The subtracted gradients show peaks at 9.4 and 8.6 cm in water-gel and tissue-gel respectively for both pristine and SOBP beams. These peaks are created in connection with the sudden change of 13 N signals with depth and consistently occur 2 mm upstream to where 13 N signals were most abundantly created (9.6 and 8.8 cm in water-gel and tissue-gel, respectively). Monte Carlo simulations provided similar results as the measurements. CONCLUSIONS: The subtracted PET signal gradient peaks and the proton ranges for water-gel and tissue-gel show distance off-sets of 4 to 5 mm. This off-set may potentially be used for proton range verification using only the PET measured data without Monte Carlo simulations. More studies are necessary to overcome various limitations, such as perfusion-driven washout, for the feasibility of this technique in living patients.
PURPOSE: While positron emission tomography (PET) allows for the imaging of tissues activated by proton beams in terms of monitoring the therapy administered, most endogenous tissue elements are activated by relatively high-energy protons. Therefore, a relatively large distance off-set exists between the dose fall-off and activity fall-off. However, 16 O(p,2p,2n)13 N has a relatively low energy threshold which peaks around 12 MeV and also a residual proton range that is approximately 1 to 2 mm. In this phantom study, we tested the feasibility of utilizing the 13 N production peak as well as the differences in activity fall-off between early and late PET scans for proton range verification. One of the main purposes for this research was developing a proton range verification methodology that would not require Monte Carlo simulations. METHODS AND MATERIALS: Both monoenergetic and spread-out Bragg peak beams were delivered to two phantoms - a water-like gel and a tissue-like gel where the proton ranges came to be approximately 9.9 and 9.1 cm, respectively. After 1 min of postirradiation delay, the phantoms were scanned for a period of 30 min using an in-room PET. Two separate (Early and Late) PET images were reconstructed using two different postirradiation delays and acquisition times; Early PET: 1 min delay and 3 min acquisition, Late PET: 21 min delay and 10 min acquisition. The depth gradients of the PET signals were then normalized and plotted as functions of depth. The normalized gradient of the early PET images was subtracted from that of the late PET images, to observe the 13 N activity distribution in relation to depth. Monte Carlo simulations were also conducted with the same set-up as the measurements stated previously. RESULTS: The subtracted gradients show peaks at 9.4 and 8.6 cm in water-gel and tissue-gel respectively for both pristine and SOBP beams. These peaks are created in connection with the sudden change of 13 N signals with depth and consistently occur 2 mm upstream to where 13 N signals were most abundantly created (9.6 and 8.8 cm in water-gel and tissue-gel, respectively). Monte Carlo simulations provided similar results as the measurements. CONCLUSIONS: The subtracted PET signal gradient peaks and the proton ranges for water-gel and tissue-gel show distance off-sets of 4 to 5 mm. This off-set may potentially be used for proton range verification using only the PET measured data without Monte Carlo simulations. More studies are necessary to overcome various limitations, such as perfusion-driven washout, for the feasibility of this technique in living patients.
Authors: Xuping Zhu; Samuel España; Juliane Daartz; Norbert Liebsch; Jinsong Ouyang; Harald Paganetti; Thomas R Bortfeld; Georges El Fakhri Journal: Phys Med Biol Date: 2011-06-15 Impact factor: 3.609
Authors: H Mizuno; T Tomitani; M Kanazawa; A Kitagawa; J Pawelke; Y Iseki; E Urakabe; M Suda; A Kawano; R Iritani; S Matsushita; T Inaniwa; T Nishio; S Furukawa; K Ando; Y K Nakamura; T Kanai; K Ishii Journal: Phys Med Biol Date: 2003-08-07 Impact factor: 3.609
Authors: Katia Parodi; Harald Paganetti; Helen A Shih; Susan Michaud; Jay S Loeffler; Thomas F DeLaney; Norbert J Liebsch; John E Munzenrider; Alan J Fischman; Antje Knopf; Thomas Bortfeld Journal: Int J Radiat Oncol Biol Phys Date: 2007-07-01 Impact factor: 7.038
Authors: Samuel España; Daniel Sánchez-Parcerisa; Paloma Bragado; Álvaro Gutiérrez-Uzquiza; Almudena Porras; Carolina Gutiérrez-Neira; Andrea Espinosa; Víctor V Onecha; Paula Ibáñez; Víctor Sánchez-Tembleque; José M Udías; Luis M Fraile Journal: Sci Rep Date: 2022-04-30 Impact factor: 4.996