Precision imaging of 4.4 MeV gamma rays using a 3-D position sensitive Compton camera

Koide, A.; Kataoka, J.; Masuda, Tomoya; Mochizuki, Seibu; Taya, T.; Sueoka, Koki; Tagawa, Leo; Fujieda, Kazuya; Maruhashi, Takuya; Kurihara, Takuya; Inaniwa, Taku

doi:10.1038/s41598-018-26591-2

Cited by 47 publications

(21 citation statements)

References 54 publications

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“…Although ToF cannot be measured in the compact configuration, back-scattering gamma rays from the absorber are avoided using the energy cut of the scatterer. Various methods to reduce background contamination have been considered, and we successfully proved these methods could exclude the background events and improve the quality of the MeV gamma-ray images 20,21 .…”

Section: Introductionmentioning

confidence: 86%

Development and performance verification of a 3-D position-sensitive Compton camera for imaging MeV gamma rays

Hosokoshi

Kataoka

Mochizuki

et al. 2019

Sci Rep

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In gamma-ray astronomy, the 1–10 MeV range is one of the most challenging energy bands to observe owing to low photon signals and a considerable amount of background contamination. This energy band, however, comprises a substantial number of nuclear gamma-ray lines that may hold the key to understanding the nucleosynthesis at the core of stars, spatial distribution of cosmic rays, and interstellar medium. Although several studies have attempted to improve observation of this energy window, development of a detector for astronomy has not progressed since NASA launched the Compton Gamma Ray Observatory (CGRO) in 1991. In this work, we first developed a prototype 3-D position-sensitive Compton camera (3D-PSCC), and then conducted a performance verification at NewSUBARU, Hyogo in Japan. To mimic the situation of astronomical observation, we used a MeV gamma-ray beam produced by laser inverse Compton scattering. As a result, we obtained sharp peak images of incident gamma rays irradiating from incident angles of 0° and 20°. The angular resolution of the prototype 3D-PSCC was measured by the Angular Resolution Measure and estimated to be 3.4° ± 0.1° (full width at half maximum (FWHM)) at 1.7 MeV and 4.0° ± 0.5° (FWHM) at 3.9 MeV. Subsequently, we conceived a new geometry of the 3D-PSCC optimized for future astronomical observations, assuming a 50-kg class small satellite mission. The SΩ of the 3D-PSCC is 11 cm2sr, anticipated at 1 MeV, which is small but provides an interesting possibility to observe bright gamma-ray sources owing to the high intrinsic efficiency and large field of view (FoV).

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Section: Introductionmentioning

confidence: 86%

Development and performance verification of a 3-D position-sensitive Compton camera for imaging MeV gamma rays

Hosokoshi

Kataoka

Mochizuki

et al. 2019

Sci Rep

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“…In our case, we preferred not to assume that the beam is described by a perfect line given the non-negligible extension of the simulated beam and the resulting activity distribution. (e) Energy Peaks: A common approach in PGI is to select events whose total deposited energy corresponds to certain transitions of the excited nuclei within the patient, reflected as peaks in the spectrum [28], [34]. Here, we selected the most prominent energy peaks that are seen in Fig.…”

Section: Data Selectionmentioning

confidence: 99%

Capability of MLEM and OE to Detect Range Shifts With a Compton Camera in Particle Therapy

Kohlhase

Wegener

Schaar

et al. 2020

IEEE Trans. Radiat. Plasma Med. Sci.

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To identify range deviations by using Compton cameras (CCs), tomographic image reconstruction of CC data is needed. Within this context, image reconstruction is usually performed using maximum likelihood expectation maximization (MLEM), and more recently, the origin ensemble (OE) algorithm. In this article, we investigate how MLEM and OE affect the precision and accuracy of estimated range deviations. In particular, we focus on the effects of data selection, statistical fluctuations, and artifact reduction. The use of external information of the beam path through a hodoscope was also explored. Additionally, two methods to calculate range deviations were tested. To this aim, realistic proton beams were simulated using GATE and data from single spots as well as from seven contiguous spots of an energy layer were reconstructed. MLEM and OE reacted differently to the poor data statistics. In general, both algorithms were able to detect range shifts for single spots, particularly when multiple coincidences were also considered. Selection of events corresponding to the most relevant energy peaks decreased the identification performance due to the lower statistics. When data from several contiguous spots were jointly reconstructed, the accuracy of the results degraded significantly, and nonzero shifts were assigned when no shifts had occurred. The limited size of the cameras and the subsequent restriction in the orientation and aperture of detected cones, as well as in the number of detected events are major challenges. Future efforts should be devoted to noise regularization and compensation for data truncation. Index Terms-Compton camera (CC), image reconstruction, particle therapy, prompt gamma imaging, range verification. I. INTRODUCTION I N RECENT years, Compton cameras (CCs) have attracted attention for range verification in particle therapy [1]-[6]. Within this context, the goal of the CC is to detect prompt gamma-rays (PG) that are emitted during de-excitation of Manuscript

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“…However, there are several challenges that need to be addressed for a reliable implementation of this methodology in the clinical case 17 . Indeed, in-vivo range monitoring remains still an issue for most of the Compton cameras under development 16,[18][19][20][21][22][23][24][25][26][27][28][29] . These limitations are related to the limited coincidence efficiency of some of the detectors 20,21,25 , the high counting rates in clinical conditions 16,24,30 , the spatial resolution 22 , the signal-to-background ratio that is challenged by contaminant reactions 18,31 , and the CPU processing-time required by the corresponding image-reconstruction algorithm 26 .…”

Section: Introductionmentioning

confidence: 99%

Towards machine learning aided real-time range imaging in proton therapy

Lerendegui-Marco¹,

Balibrea-Correa²,

Babiano-Súarez³

et al. 2022

Preprint

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Compton imaging represents a promising technique for range verification in proton therapy treatments. In this work, we report on the advantageous aspects of the i-TED detector for proton-range monitoring, based on the results of the first Monte Carlo study of its applicability to this field. i-TED is an array of Compton cameras, that have been specifically designed for neutron-capture nuclear physics experiments, which are characterized by γ-ray energies spanning up to 5-6 MeV, rather low γ-ray emission yields and very intense neutron induced γ-ray backgrounds. Our developments to cope with these three aspects are concomitant with those required in the field of hadron therapy, especially in terms of high efficiency for real-time monitoring, low sensitivity to neutron backgrounds and reliable performance at the high γ-ray energies. We find that signal-to-background ratios can be appreciably improved with i-TED thanks to its light-weight design and the low neutron-capture cross sections of its LaCl 3 crystals, when compared to other similar systems based on LYSO, CdZnTe or LaBr 3 . Its high time-resolution (CRT∼500 ps) represents an additional advantage for background suppression when operated in pulsed HT mode. Each i-TED Compton module features two detection planes of very large LaCl 3 monolithic crystals, thereby achieving a high efficiency in coincidence of 0.2% for a point-like 1 MeV γ-ray source at 5 cm distance. This leads to sufficient statistics for reliable image reconstruction with an array of four i-TED detectors assuming clinical intensities of 10 8 protons per treatment point. The use of a two-plane design instead of three-planes has been preferred owing to the higher attainable efficiency for double time-coincidences than for threefold events. The loss of full-energy events for high energy γ-rays is compensated by means of Machine-Learning based algorithms, which allow one to enhance the signal-to-total ratio up to a factor of 2.

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Precision imaging of 4.4 MeV gamma rays using a 3-D position sensitive Compton camera

Cited by 47 publications

References 54 publications

Development and performance verification of a 3-D position-sensitive Compton camera for imaging MeV gamma rays

Development and performance verification of a 3-D position-sensitive Compton camera for imaging MeV gamma rays

Capability of MLEM and OE to Detect Range Shifts With a Compton Camera in Particle Therapy

Towards machine learning aided real-time range imaging in proton therapy

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