A triple-imaging-modality system for simultaneous measurements of prompt gamma photons, prompt x-rays, and induced positrons during proton beam irradiation.

Objective. Prompt gamma photon, prompt x-ray, and induced positron imaging are possible methods for observing a proton beam's shape from outside the subject. However, since these three types of images have not been measured simultaneously nor compared using the same subject, their advantages and disadvantages remain unknown for imaging beam shapes in therapy. To clarify these points, we developed a triple-imaging-modality system to simultaneously measure prompt gamma photons, prompt x-rays, and induced positrons during proton beam irradiation to a phantom.Approach. The developed triple-imaging-modality system consists of a gamma camera, an x-ray camera, and a dual-head positron emission tomography (PET) system. During 80 MeV proton beam irradiation to a polymethyl methacrylate (PMMA) phantom, imaging of prompt gamma photons was conducted by the developed gamma camera from one side of the phantom. Imaging of prompt x-rays was conducted by the developed x-ray camera from the other side. Induced positrons were measured by the developed dual-head PET system set on the upper and lower sides of the phantom.Main results. With the proposed triple-imaging-modality system, we could simultaneously image the prompt gamma photons and prompt x-rays during proton beam irradiation. Induced positron distributions could be measured after the irradiation by the PET system and the gamma camera. Among these imaging modalities, image quality was the best for the induced positrons measured by PET. The estimated ranges were actually similar to those imaged with prompt gamma photons, prompt x-rays and induced positrons measured by PET.Significance. The developed triple-imaging-modality system made possible to simultaneously measure the three different beam images. The system will contribute to increasing the data available for imaging in therapy and will contribute to better estimating the shapes or ranges of proton beam.

Estimating blurless and noise-free Ir-192 source images from gamma camera images for high-dose-rate brachytherapy using a deep-learning approach.

Objective. Precise monitoring of the position and dwell time of iridium-192 (Ir-192) during high-dose-rate (HDR) brachytherapy is crucial to avoid serious damage to normal tissues. Source imaging using a compact gamma camera is a potential approach for monitoring. However, images from the gamma camera are affected by blurring and statistical noise, which impact the accuracy of source position monitoring. This study aimed to develop a deep-learning approach for estimating ideal source images that reduce the effect of blurring and statistical noise from experimental images captured using a compact gamma camera.Approach. A double pix2pix model was trained using the simulated gamma camera images of an Ir-192 source. The first model was responsible for denoising the Ir-192 images, whereas the second model performed super resolution. Trained models were then applied to the experimental images to estimate the ideal images.Main results. At a distance of 100 mm between the compact gamma camera and the Ir-192 source, the difference in full width at half maximum (FWHM) between the estimated and actual source sizes was approximately 0.5 mm for a measurement time of 1.5 s. This difference has been improved from approximately 2.7 mm without the use of DL. Even with a measurement time of 0.1 s, the ideal images could be estimated as accurately as in the 1.5 s measurements. This method consistently achieved accurate estimations of the source images at any position within the field of view; however, the difference increased with the distance between the Ir-192 source and the compact gamma camera.Significance. The proposed method successfully provided estimated images from the experimental images within errors smaller than 0.5 mm at 100 mm. This method is promising for reducing blurring and statistical noise from the experimental images, enabling precise real-time monitoring of Ir-192 sources during HDR brachytherapy.

Simultaneous imaging of luminescence and prompt x-rays during irradiation with spot-scanning proton beams at clinical dose level.

Prompt x-ray imaging is a promising method for observing the beam shape from outside a subject. However, its distribution is different from dose distribution, and thus a comparison with the dose is required. Meanwhile, luminescence imaging of water is a possible method for imaging the dose distribution. Consequently, we performed simultaneous imaging of luminescence and prompt x-rays during irradiation by proton beams to compare the distributions between these two different imaging methods. Optical imaging of water was conducted with spot-scanning proton beams at clinical dose level during irradiation to a fluorescein (FS) water phantom set in a black box. Prompt x-ray imaging was also conducted simultaneously from outside the black box using a developed x-ray camera during proton beam irradiation to the phantom. We measured images of the luminescence of FS water and prompt x-rays for various types of proton beams, including pencil beams, spread-out Bragg peak (SOBP) beams, and clinically used therapy beams. After the imaging, ranges were estimated from FS water and prompt x-rays and compared with those calculated with a treatment planning system (TPS). We could measure the prompt x-ray and FS water images simultaneously for all types of proton beams. The ranges estimated from the FS water and those calculated with the TPS closely matched, within a difference of several mm. Similar range difference was found between the results estimated from prompt x-ray images and those calculated with the TPS. We confirmed that the simultaneous imaging of luminescence and prompt x-rays were possible during irradiation with spot-scanning proton beams at a clinical dose level. This method can be applied to range estimation as well as comparison with the dose for prompt x-ray imaging or other imaging methods used in therapy with various types of proton beams at a clinical dose level.

Hybrid imaging of prompt x-rays and induced positrons using a pinhole gamma camera during and after irradiation of protons.

Objective. Prompt x-ray imaging using a low-energy x-ray camera is a promising method for observing a proton beam's shape from outside the subject. Furthermore, imaging of positrons produced by nuclear reactions with protons is a possible method for observing the beam shape. However, it has not been possible to measure these two types of images with a single imaging system due to the limited imaging capability of existing systems. Imaging of both prompt x-rays and the distribution of positrons may compensate for the shortcomings of each method.Approach. We conducted imaging of the prompt x-ray using a pinhole x-ray camera during irradiation with protons in list mode. Then, after irradiation with protons, imaging of annihilation radiations from the produced positrons was conducted using the same pinhole x-ray camera in list mode. After this imaging, list-mode data were sorted to obtain prompt x-ray images and positron images.Main results. With the proposed procedure, we could measure both prompt x-ray images and induced positron images with a single irradiation by a proton beam. From the prompt x-ray images, ranges and widths of the proton beams could be estimated. The distributions of positrons were slightly wider than those of the prompt x-rays. From the time sequential positron images, we could derive the time activity curves of the produced positrons.Significance. Hybrid imaging of prompt x-rays and induced positrons using a pinhole x-ray camera was achieved. The proposed procedure would be useful for measuring prompt x-ray images during irradiation to estimate the beam structures as well as for measuring the induced positron images after irradiation to estimate the distributions and time activity curves of the induced positrons.

Prompt X-ray imaging during irradiation with spread-out Bragg peak (SOBP) beams of carbon ions.

Prompt secondary electron bremsstrahlung X-ray (prompt X-ray) imaging using a low-energy X-ray camera is a promising method for observing a beam shape from outside the subject. However, such imaging has so far been conducted only for pencil beams without a multi-leaf collimator (MLC). The use of spread-out Bragg peak (SOBP) with an MLC may increase the scattered prompt gamma photons and decrease the contrast of the images of prompt X-rays. Consequently, we performed prompt X-ray imaging of SOBP beams formed with an MLC. This imaging was carried out in list mode during irradiation of SOBP beams to a water phantom. An X-ray camera with a 1.5-mm diameter as well as 4-mm-diameter pinhole collimators was used for the imaging. List mode data were sorted to obtain the SOBP beam images as well as energy spectra and time count rate curves. Due to the high background counts from the scattered prompt gamma photons penetrating the tungsten shield of the X-ray camera, the SOBP beam shapes were difficult to observe with a 1.5-mm-diameter pinhole collimator. With the 4-mm-diameter pinhole collimators, images of SOBP beam shapes at clinical dose levels could be obtained with the X-ray camera. The use of a 4-mm-diameter pinhole collimator attached to the X-ray camera is effective for prompt X-ray imaging with high sensitivity and low background counts. This approach makes it possible to image SOBP beams with an MLC when the counts are low and the background levels are high.

The prevalence of locomotive syndrome and its associated factors in patients with Type 2 diabetes mellitus.

OBJECTIVES: We investigated the prevalence of locomotive syndrome (LS) and related musculoskeletal diseases [osteoarthritis (OA), lumbar spondylosis, and spinal alignment] in Type 2 diabetes mellitus (DM) patients. METHODS: Clinical data were collected from 101 patients (55 males; 46 females) admitted to our hospital for diabetes education from October 2018 to April 2021. Patients underwent full-spine and whole-legs standing radiography and physical measurements (10-m walking and grip strength tests and three LS risk tests). RESULTS: The estimated prevalence of LS was 86.1% (Stage 1: 44.5%, Stage 2: 41.6%), lumbar spondylosis was 11.9%, and hip, knee, and ankle OA were 16.9%, 51.5%, and 12.9%, respectively. Multiple logistic regression analysis identified grip strength [odds ratio (OR) = 0.89, confidence interval (CI) = 0.83-0.94], diabetic retinopathy (OR = 5.85, CI = 1.64-20.78), knee OA (OR = 3.34, CI = 1.11-10.02), and a sagittal vertical axis >40 mm (OR = 3.42, CI = 1.13-10.39) as significantly associated risk factors for worsening LS in Type 2 DM patients. CONCLUSIONS: This study clarified the epidemiological indicators of LS and associated factors in DM patients. Exercise therapy and DM management are effective strategies to reduce the occurrence and progression of LS.

Optimization of the energy window setting in Ir-192 source imaging for high-dose-rate brachytherapy using a YAP(Ce) gamma camera.

PURPOSE: Although real-time imaging of the high-activity iridium-192 (Ir-192) source position during high-dose-rate (HDR) brachytherapy using a high-energy gamma camera system is a promising approach, the energy window was not optimized for spatial resolution or scatter fraction. METHODS: By using a list-mode data-acquisition system that can acquire energy information of a cerium-doped yttrium aluminum perovskite (YA1O3: YAP(Ce)) gamma camera, we tried to optimize the energy window's setting to improve the spatial resolution and reduce scatter fraction. RESULTS: The spatial resolution was highest for the central energy of the window at ∼300 keV. The scatter fraction was also smallest for the central energy of the window at ∼300 keV, and the scatter fraction was more than 48 % smaller than that for the full energy window. CONCLUSIONS: We clarified that the spatial resolution can be improved and the scatter fraction can be reduced through optimizing the energy window of the YAP(Ce) gamma camera by setting the central energy of the window to ∼300 keV for HDR brachytherapy.

Technical note: Short-time sequential high-energy gamma photon imaging using list-mode data acquisition system for high-dose-rate brachytherapy.

PURPOSE: Measurement of the dwell time and moving speed of a high-activity iridium-192 (Ir-192) source used for high-dose-rate (HDR) brachytherapy is important for estimating the precise dose delivery to a tumor. For this purpose, we used a cerium-doped yttrium aluminum perovskite (YA1O3 :YAP(Ce)) gamma camera system, combined with a list-mode data acquisition system that can acquire short-time sequential images, and measured the dwell times and moving speeds of the Ir-192 source. METHODS: Gamma photon imaging was conducted using the gamma camera in list mode for the Ir-192 source of HDR brachytherapy with fixed dwell times and positions. The acquired list-mode images were sorted to millisecond-order interval time sequential images to evaluate the dwell time at each position. Time count rate curves were derived to calculate the dwell time at each source position and moving speed of the source. RESULTS: We could measure the millisecond-order time sequential images for the Ir-192 source. The measured times for the preset dwell times of 2 s and 10 s were 1.98 to 2.00 s full width at half maximum (FWHM) and 10.0 s FWHM, respectively. The dwell times at the first dwell position were larger than those at other positions. We also measured the moving speeds of the source after the dwells while moving back to the afterloader and found the speed increased with the distance from the edge of the field of view to the last dwell position. CONCLUSION: We conclude that millisecond-order time sequential imaging of the Ir-192 source is possible by using a gamma camera and is useful for evaluating the dwell times and moving speeds of the Ir-192 source.

Deep learning-based in vivo dose verification from proton-induced secondary-electron-bremsstrahlung images with various count level.

PURPOSE: Proton-induced secondary-electron-bremsstrahlung (SEB) imaging is a promising method for estimating the ranges of particle beam. However, SEB images do not directly represent dose distributions of particle beams. In addition, the ranges estimated from measured images were deviated because of limited spatial resolutions of the developed x-ray camera as well as statistical noise in the images. To solve these problems, we proposed a method for predicting high-resolution dose images from SEB images with various count level using a deep learning (DL) approach for range and width verification. METHODS: In this study, we adopted the double U-Net model, which is a previously proposed deep convolutional network model. The first U-Net model in the double U-Net model was used to denoise the SEB images with various count level. The first U-Net model for denoising was trained on 8000 pairs of SEB images with various count level and noise-free images which were created by a sophisticated in-house developed model function. The second U-Net model for dose prediction was trained using 8000 pairs of denoised SEB images from the first U-Net model and high-resolution dose images generated by Monte Carlo simulation. RESULTS: For both simulation and measurement data, the trained DL model could successfully predict high-resolution dose images which showed a clear Bragg peak and no statistical noise. The difference of the range and width was less than 2.1 mm, even from the SEB images measured with a decrease in the number of irradiated protons to less than 11% of 3.2 × 1011 protons. CONCLUSIONS: High-resolution dose images from measured and simulated SEB images were successfully predicted by using the trained DL model for protons. Our proposed DL model was feasible to predict dose images accurately even with smaller number of irradiated protons.

Technical note: Correcting angular dependencies using non-polarized components of Cherenkov light in water during high-energy X-ray irradiation.

OBJECTIVE: Dose distribution measurements of high-energy X-rays from medical linear accelerators (LINAC) in water are important for quality control (QC) of the system. Although Cherenkov-light imaging is a useful method for measuring the high-energy X-ray dose distribution, depth profiles have an underestimated dose at increased depths due to the angular dependency of the Cherenkov light generated in water. In this study, we use a linear polarizer to separate the majority of polarized components from the majority of unpolarized components of Cherenkov-light images in water and then use this information to correct for angular dependencies. METHODS: A water phantom, a cooled charge-coupled device (CCD) camera, and a polarizer were installed in a black box. Then, the water phantom was irradiated from the upper side with 6 or 10 MV X-rays, and the Cherenkov light generated in water was imaged with the polarizer axis at both parallel and perpendicular orientations to the beam. By using these images from the two orientations relative to the beam, we corrected the angular dependency of the Cherenkov light. RESULTS: By subtracting the images measured with the polarizer perpendicular to the beams from the images measured with the polarizer parallel to the beams, we could obtain images with only the polarized components. Using these images, we could calculate the images with non-polarized components that had similar depth profiles to those calculated with a planning system. The average difference between corrected depth profiles and those calculated with the planning system was less than 1%, while that between uncorrected depth profiles and the planning system was more than 8.3% in depths of water from 20 to 100 mm. CONCLUSION: We conclude that the use of the polarizer has the potential to improve the accuracy of dose distribution in Cherenkov-light imaging of water using high-energy X-rays.

Technical note: Optical imaging of lithium-containing zinc sulfate plate in water during irradiation of neutrons from boron neutron capture therapy (BNCT) system.

PURPOSE: Optical imaging of ionizing radiation is a possible method for dose distribution measurements. However, it is not clear whether the imaging method is also applicable to neutrons. To clarify this, we performed the imaging of neutrons in water from boron neutron capture therapy (BNCT) systems. Such systems require efficient distribution measurements of neutrons for quality assessment (QA) of the beams. METHOD: A water-filled phantom was irradiated from the side with an epithermal neutron beam, in which a lithium-containing zinc sulfate (Li-ZnS(Ag)) plate was set in the beam direction, and during this irradiation the scintillation of the plate was imaged using a cooled charge-coupled device (CCD) camera. In the imaging, Li-6 in the Li-ZnS(Ag) plate captures neutrons and converts them to alpha particles (He-4) and tritium (H-3), while ZnS(Ag) in the Li-ZnS(Ag) plate produces scintillation light in the plate. We also conducted Monte Carlo simulation and compared its results with the experimental results. RESULTS: The image of the emitted light from the Li-ZnS(Ag) plate was clearly obtained with an imaging time of 0.5 s. The depth and lateral profiles of the measured image using the Li-ZnS(Ag) plate showed the same shapes as the neutron distributions measured with gold foil, within a difference of 8%. The destructive effect of neutrons on the CCD camera increased approximately three times, but the unit was still working after the measurement. CONCLUSION: The optical imaging of neutrons in water is possible, and it has the potential to be a new method for efficient QA as well as for research on neutrons.

Increase in the intensity of an optical signal with fluorescein during proton and carbon-ion irradiation.

PURPOSE: Although the imaging of luminescence emitted in water during irradiation of protons and carbon ions is a useful method for range and dose estimations, the intensity of the images is relatively low due to the low photon production of the luminescence phenomenon. Therefore, a relatively long time is required for the imaging. Since a fluorescent dye, fluorescein, may increase the intensity of the optical signal, we measured the luminescence images of water with different concentrations of fluorescein during irradiation of protons and carbon ions and compared the results with those by measurements with water. METHODS: A cooled charge-coupled device (CCD) camera was used for imaging a water phantom with different concentrations of fluorescein from 0.0063 to 0.025 mg/cm3 , in addition to a water phantom without fluorescein during irradiation of 150-MeV protons and 241.5-MeV/n carbon ions. RESULTS: For both protons and carbon ions, the intensity of the luminescence images increased as the concentration of fluorescein increased. With a fluorescein concentration of 0.025 mg/cm3 , the intensities increased to more than 10 times those of water for both protons and carbon ions. Although the shape of the depth profiles of luminescence images of water with fluorescein appeared similar to that of water for protons, those for carbon ions were different from those of water due to the increase in the Cherenkov light component at shallow depths by the decrease in the angular dependencies of the Cherenkov light. CONCLUSION: We confirmed the increase in intensity of the luminescence of water by adding fluorescein for particle ions. With a small amount of Cherenkov light contamination in the images, such as protons, the relative distributions of the luminescence images with fluorescein were similar to that of water and will be used for range or dose determination in a short time.

Possibility evaluation of the optical imaging of proton mini-beams.

Proton therapy using mini-beams is a promising method to reduce radiation damage to normal tissue. However, distribution measurements of mini-beams are difficult due to their small structures. Since optical imaging is a possible method to measure high-resolution two-dimensional dose distribution, we conducted optical imaging of an acrylic block during the irradiation of mini-beams of protons. Mini-beams were made from a proton pencil beam irradiated to 1 mm slits made of tungsten plate. During irradiation of the mini-beams to the acrylic block, we measured the luminescence of the acrylic block using a charge-coupled device camera. With the measurements, we could obtain slit beam images that have slit shapes in the shallow area while they were uniform in their Bragg peaks, which was similar to the case of simulated optical images by Monte Carlo simulations. We confirmed that high-resolution optical imaging of mini-beams is possible and provides a promising method for efficient quality assessment of mini-beams as well as research on mini-beam therapy.

Imaging of polarized components of Cerenkov light and luminescence of water during carbon-ion irradiation.

PURPOSE: The luminescence image of water during the irradiation of carbon ions showed higher intensity at shallow depths than dose distribution due to the contamination of Cerenkov light from secondary electrons. Since Cerenkov light is coherent and polarized for the light produced during the irradiation of carbon ions to water, the reduction of Cerenkov light may be possible with a polarizer. In addition, there is no information on the polarization of the luminescence of water. To clarify these points, we measured the optical images of water during the irradiation of carbon ions with a polarizer by changing the directions of the transmission axis. METHODS: Imaging was conducted using a cooled charge-coupled device (CCD) camera during the irradiation of 241.5 MeV/n energy carbon ions to a water phantom with a polarizer in front of the lens by changing the transmission axis parallel and perpendicular to the carbon-ion beam. RESULTS: With the polarizer parallel to the carbon-ion beam, the intensity at the shallow depth was ~26% higher than that measured with the polarizer perpendicular to the beam. We found no significant intensity difference between these two images at deeper depths where the Cerenkov light was not included. The difference image of the parallel and perpendicular directions showed almost the same image as the simulated Cerenkov light distribution. Using the measured difference image, correction of the Cerenkov component was possible from the measured luminescence image of water during the irradiation of carbon ions. CONCLUSION: We could measure the difference of the Cerenkov light component by changing the transmission axis of the polarizer. Also we clarified that there was no difference in the luminescence of water by changing the transmission axis of the polarizer.

Prediction of dose distribution from luminescence image of water using a deep convolutional neural network for particle therapy.

PURPOSE: We recently obtained nearly the same depth profiles of luminescence images of water as dose for protons by subtracting the Cerenkov light component emitted by secondary electrons of prompt gamma photons. However, estimating the distribution of Cerenkov light with this correction method is time-consuming, depending on the irradiated energy of protons by Monte Carlo simulation. Therefore, we proposed a method of estimating dose distributions from the measured luminescence images of water using a deep convolutional neural network (DCNN). METHODS: In this study, we adopted the U-Net architectures as the DCNN. To prepare a large amount of image data for DCNN training, we calculated the training data pairs of two-dimensional (2D) dose distributions and luminescence images of water by Monte Carlo simulation for protons and carbon ions. After training the U-Net model for protons or carbon ions using these dose distributions and luminescence images calculated by Monte Carlo simulation, we predicted the dose distributions from the calculated and measured luminescence images of water using the trained U-Net model. RESULTS: All of the U-Net model's predicted images were in good agreement with the MC-calculated dose distributions and showed lower values of the root mean square percentage error (RSMPE) and higher values in the structural similarity index (SSIM) in comparison with these values for calculated or measured luminescence images. CONCLUSION: We confirmed that the DCNN effectively predicts dose distributions in water from the measured as well as calculated luminescence images of water for particle therapy.

Estimation and correction of Cerenkov-light on luminescence image of water for carbon-ion therapy dosimetry.

PURPOSE: The luminescence images of water during the irradiation of carbon-ions provide useful information such as the ranges and the widths of carbon-ion beams. However, measured luminescence images show higher intensities in shallow depths and wider lateral profiles than those of the dose distributions. These differences prevent the luminescence imaging of water from being applied to a quality assurance for carbon-ion therapy. We assumed that the differences were due to the contaminations of Cerenkov-light from the secondary electrons of carbon-ions as well as the prompt gamma photons in the measured image. In this study, we applied a correction method to a luminescence image of water during the irradiation of carbon-ion beams. METHODS: We estimated the distribution of the Cerenkov-light in water during the irradiation of carbon-ions by Monte Carlo simulation and subtracted the simulated Cerenkov-light from the depth and lateral profiles of the measured luminescence image for 241.5 MeV/u-carbon-ions. RESULTS: With these corrections, we successfully obtained depth and lateral profiles whose distributions are almost identical to the dose distributions of carbon-ions. The high intensities in the shallow depth areas decreased and the Bragg peak intensity increased. The beam widths of the measured images approached those of the ionization chamber. CONCLUSIONS: These results indicate that the luminescence imaging of water with our proposed correction has potential to be used for dose distribution measurements for carbon-ion therapy dosimetry.

Dose image prediction for range and width verifications from carbon ion-induced secondary electron bremsstrahlung x-rays using deep learning workflow.

PURPOSE: Imaging of the secondary electron bremsstrahlung (SEB) x rays emitted during particle-ion irradiation is a promising method for beam range estimation. However, the SEB x-ray images are not directly correlated to the dose images. In addition, limited spatial resolution of the x-ray camera and low-count situation may impede correctly estimating the beam range and width in SEB x-ray images. To overcome these limitations of the SEB x-ray images measured by the x-ray camera, a deep learning (DL) approach was proposed in this work to predict the dose images for estimating the range and width of the carbon ion beam on the measured SEB x-ray images. METHODS: To prepare enough data for the DL training efficiently, 10,000 simulated SEB x-ray and dose image pairs were generated by our in-house developed model function for different carbon ion beam energies and doses. The proposed DL neural network consists of two U-nets for SEB x ray to dose image conversion and super resolution. After the network being trained with these simulated x-ray and dose image pairs, the dose images were predicted from simulated and measured SEB x-ray testing images for performance evaluation. RESULTS: For the 500 simulated testing images, the average mean squared error (MSE) was 2.5 × 10-5 and average structural similarity index (SSIM) was 0.997 while the error of both beam range and width was within 1 mm FWHM. For the three measured SEB x-ray images, the MSE was no worse than 5.5 × 10-3 and SSIM was no worse than 0.980 while the error of the beam range and width was 2 mm and 5 mm FWHM, respectively. CONCLUSIONS: We have demonstrated the advantages of predicting dose images from not only simulated data but also measured data using our deep learning approach.

Imaging of fragment particles in water by nuclear spallation during carbon-ion irradiation.

Recently we found that the luminescence imaging of water during carbon-ion irradiation was possible using a cooled charge-coupled device (CCD) camera and the method could be used for range estimation of the beam. In the luminescence image, we found luminescence from the fragment particles produced by the nuclear spallation reaction of carbon ions. The luminescence may be used for the estimation of the distribution of the fragment particles by the nuclear spallation. For this purpose, we irradiated carbon ions of 241.5 MeV u-1 to a water phantom and measured the luminescence image of water using a CCD camera. Then, we carefully observed the luminescence distribution after the Bragg peak to find the luminescence from the nuclear spallation reaction. In the luminescence image, we could clearly observe the luminescence from the fragment particles produced by the nuclear spallation reaction during irradiation of carbon ions. The beam widths of the luminescence image of the nuclear spallation were compared with those measured by the ionization chamber. The relative difference of the beam width at FWHM between luminescence image and ionization chamber was 23%. With these results, we conclude that the luminescence image of water during carbon-ion irradiation has a potential to be a new and efficient method for the width estimation of the fragment particles by the nuclear spallation reaction.

Addition of luminescence process in Monte Carlo simulation to precisely estimate the light emitted from water during proton and carbon-ion irradiation.

Although luminescence of water lower in energy than the Cerenkov-light threshold during proton and carbon-ion irradiation has been found, the phenomenon has not yet been implemented for Monte Carlo simulations. The results provided by the simulations lead to misunderstandings of the physical phenomenon in optical imaging of water during proton and carbon-ion irradiation. To solve the problems, as well as to clarify the light production of the luminescence of water, we modified a Monte Carlo simulation code to include the light production from the luminescence of water and compared them with the experimental results of luminescence imaging of water. We used GEANT4 for the simulation of emitted light from water during proton and carbon-ion irradiation. We used the light production from the luminescence of water using the scintillation process in GEANT4 while those of Cerenkov light from the secondary electrons and prompt gamma photons in water were also included in the simulation. The modified simulation results showed similar depth profiles to those of the measured data for both proton and carbon-ion. When the light production of 0.1 photons/MeV was used for the luminescence of water in the simulation, the simulated depth profiles showed the best match to those of the measured results for both the proton and carbon-ion compared with those used for smaller and larger numbers of photons/MeV. We could successively obtain the simulated depth profiles that were basically the same as the experimental data by using GEANT4 when we assumed the light production by the luminescence of water. Our results confirmed that the inclusion of the luminescence of water in Monte Carlo simulation is indispensable to calculate the precise light distribution in water during irradiation of proton and carbon-ion.

Luminescence imaging of water during uniform-field irradiation by spot scanning proton beams.

Luminescence was found during pencil-beam proton irradiation to water phantom and range could be estimated from the luminescence images. However, it is not yet clear whether the luminescence imaging is applied to the uniform fields made of spot-scanning proton-beam irradiations. For this purpose, imaging was conducted for the uniform fields having spread out Bragg peak (SOBP) made by spot scanning proton beams. We designed six types of the uniform fields with different ranges, SOBP widths and irradiation fields. One of the designed fields was irradiated to water phantom and a cooled charge coupled device camera was used to measure the luminescence image during irradiations. We estimated the ranges, field widths, and luminescence intensities from the luminescence images and compared those with the dose distribution calculated by a treatment planning system. For all types of uniform fields, we could obtain clear images of the luminescence showing the SOBPs. The ranges and field widths evaluated from the luminescence were consistent with those of the dose distribution calculated by a treatment planning system within the differences of -4 mm and -11 mm, respectively. Luminescence intensities were almost proportional to the SOBP widths perpendicular to the beam direction. The luminescence imaging could be applied to uniform fields made of spot scanning proton beam irradiations. Ranges and widths of the uniform fields with SOBP could be estimated from the images. The luminescence imaging is promising for the range and field width estimations in proton therapy.