Objective. Bragg peak measurements play a key role in the beam quality assurance in proton therapy. Used as base data for the treatment planning softwares, the accuracy of the data is crucial when defining the range of the protons in the patient. Approach. In this paper a protocol to reconstruct a Pristine Bragg Peak exploring the direct correlation between the particle flux and the dose deposited by particles is presented. Proton flux measurements at the HollandPTC and FLUKA Monte Carlo simulations are used for this purpose. This new protocol is applicable to plastic scintillator detectors developed for Quality Assurance applications. In order to obtain the Bragg curve using a plastic fiber detector, a PMMA phantom with a decoupled and moveable stepper was designed. The step phantom allows to change the depth of material in front of the fiber detector during irradiations. The Pristine Bragg Peak reconstruction protocol uses the measured flux of particles at each position and multiplies it by the average dose obtained from the Monte Carlo simulation at each position. Main results. The results show that with this protocol it is possible to reconstruct the Bragg Peak with an accuracy of about 470 µm, which is in accordance with the tolerances set by the AAPM. Significance. It has the advantage to be able to overcome the quenching problem of scintillators in the high ionization density region of the Bragg peak.@en

Background
Photon counting detectors (PCDs) for x-ray computed tomography (CT) are the future of CT imaging. At present, semiconductor-based PCDs such as cadmium telluride (CdTe), cadmium zinc telluride, and silicon have been either used or investigated for clinical PCD CT. Unfortunately, all of them have the same major challenges, namely high cost and limited spectral signal-to-noise ratio (SNR). Recent studies showed that some high-quality scintillators, such as lanthanum bromide doped with cerium (LaBr3:Ce), are less expensive and almost as fast as CdTe.

Purpose
The objective of this study is to assess the performance of a LaBr3:Ce PCD for clinical x-ray CT.

Methods
We performed Monte Carlo simulations and compared the performance of 3 mm thick LaBr3:Ce and 2 mm thick CdTe for PCD CT with x-rays at 120 kVp and 20–1000 mA. The two PCDs were operated with either a threshold–subtract (TS) counting scheme or a direct energy binning (DB) counting scheme. The performance was assessed in terms of the accuracy of registered spectra, counting capability, and count-rate-dependent spectral imaging-task performance, for conventional CT imaging, water–bone material decomposition, and K-edge imaging with tungsten as the K-edge material. The performance for these imaging-tasks was quantified by nCRLB, that is, the Cramér–Rao lower bound on the variance of basis line-integral estimation, normalized by the corresponding value of CdTe at 20 mA.

Results
The spectrum recorded by CdTe was distorted significantly due to charge sharing, whereas the spectra recorded by LaBr3:Ce better matched the incident spectrum. The dead time, estimated by fitting a paralyzable detector model to the count-rate curves, was 20.7, 15.0, 37.2, and 13.0 ns for CdTe with TS, CdTe with DB, LaBr3:Ce with TS, and LaBr3:Ce with DB, respectively. Conventional CT imaging showed an adverse effect of reduced geometrical efficiency due to optical reflectors in LaBr3:Ce PCD. The nCRLBs (a lower value indicates a better SNR) for CdTe with TS, CdTe with DB, LaBr3:Ce with TS, LaBr3:Ce with DB, and the ideal PCD, were 1.00 ± 0.01, 1.00 ± 0.01, 1.18 ± 0.02, 1.18 ± 0.02, and 0.79 ± 0.01, respectively, at 20 mA. The nCRLBs for water–bone material decomposition, in the same order, were 1.00 ± 0.02, 1.00 ± 0.02, 0.85 ± 0.02, 0.85 ± 0.02, and 0.24 ± 0.02, respectively, at 20 mA; and 0.98 ± 0.02, 0.98 ± 0.02, 1.09 ± 0.02, 0.83 ± 0.02, and 0.24 ± 0.02, respectively, at 1000 mA. Finally, the nCRLBs for K-edge imaging, the most demanding task among the five, were 1.00 ± 0.02, 1.00 ± 0.02, 0.55 ± 0.02, 0.55 ± 0.02, and 0.13 ± 0.02, respectively, at 20 mA; and 2.45 ± 0.02, 2.29 ± 0.02, 3.12 ± 0.02, 2.11 ± 0.02, and 0.13 ± 0.02, respectively, at 1,000 mA.

Conclusion
The Monte Carlo simulations showed that, compared to CdTe with either TS or DB, LaBr3:Ce with DB provided more accurate spectra, comparable or better counting capability, and superior spectral imaging-task performances, that is, water–bone material decomposition and K-edge imaging. CdTe had a better performance than LaBr3:Ce for the conventional CT imaging task due to its higher geometrical efficiency. LaBr3:Ce PCD with DB scheme may be an excellent alternative option for CdTe PCD.@en

Cone-beam computed tomography (CBCT) and X-ray projection radiography are commonly used in the proton therapy workflow for the verification of patient positioning. The prospect of using the CBCT images for dose calculation purposes is attractive but currently hampered by the poorer image quality compared to the planning (fan-beam) CT. Ideally, the CBCT scan with the patient's anatomy of the day would provide sufficiently accurate proton stopping power ratios (SPR) to directly replan the treatment if needed. Dual-energy fan-beam CT has been proven to increase the accuracy of calculated SPR values compared to single-energy CT. A similar outcome may therefore be expected for dual-energy/spectral CBCT. This work aims to compare two possible realizations of dual-energy CBCT, namely a rapid kVp-switching source CBCT and a photon-counting detector (PCD) CBCT with two energy bins, with respect to their suitability for extracting SPR values. To perform this comparison, we determine the Cramér-Rao Lower Bound on the variance of the estimated electron density and effective atomic number. In our simulation study, we find that for the rapid kVp-switching setup the optimum voltage pair is 80/140 kVp, and the optimum ratio of the source current at 80 kVp to the source current at 140 kVp is 2:1 (4:1) for extracting the electron density (effective atomic number). In case of the PCD-based setup, a 140 kVp (100 kVp) spectrum and energy bins of [20; 50), [50; 150) keV appear best suited for extracting electron density (effective atomic number), outperforming the kVp-switching setup by a factor of 3.8 (4.9).

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Embedding signal processing in the front-end of radiation detectors represents an approach to cope with the growing complexity of nuclear imaging scanners with increasing field of view (i.e., higher number of channels). Machine learning (ML) offers a good compromise between intrinsic image reconstruction performance and computational power. While most hardware accelerators for ML are based on digital circuits and, thus, require the analog-to-digital conversion of all individual signals from photodetectors, an analog approach allows to streamline the pipeline. We present the study of an analog accelerator implementing a neural network (NN) with 42 neurons in a 0.35- μ m CMOS process node. The specific target is the reconstruction of the position of interaction of gamma-rays in the scintillator crystal of Anger cameras used for PET and SPECT. This chip can be used stand-alone or monolithically integrated within the application specific integrated circuit (ASIC) for the filtering of current signals from arrays of silicon photomultipliers (SiPMs). Computation is performed in charge domain by means of crossbar arrays of programmable capacitor. The architecture of the 64-input ASIC and the training of the NN are presented, discussing the impact of weight quantization on 5 bits. From MATLAB and circuit simulations, consistent with ASIC topology and operations, the NN capabilities were tested using two different datasets, obtained from both simulated data and experimental data, both based on PET detector composed by a monolithic scintillator crystal readout by an 8×8 array of SiPMs. Simulations show an achievable spatial resolution better than 2-mm full-width-at-half-maximum with a 10-mm thick crystal, a max. count rate of 200kHz and the energy efficiency per inference is estimated to be of 93.5GOP/J, i.e., competitive with digital counterparts, with an energy consumption of 38nJ per inference and area of 23mm2.@en

Objective. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. To assess the need for adaptation, motion models can be used to simulate dominant motion patterns and assess anatomical robustness before delivery. Traditionally, such models are based on principal component analysis (PCA) and are either patient-specific (requiring several scans per patient) or population-based, applying the same set of deformations to all patients. We present a hybrid approach which, based on population data, allows to predict patient-specific inter-fraction variations for an individual patient. Approach. We propose a deep learning probabilistic framework that generates deformation vector fields warping a patient's planning computed tomography (CT) into possible patient-specific anatomies. This daily anatomy model (DAM) uses few random variables capturing groups of correlated movements. Given a new planning CT, DAM estimates the joint distribution over the variables, with each sample from the distribution corresponding to a different deformation. We train our model using dataset of 312 CT pairs with prostate, bladder, and rectum delineations from 38 prostate cancer patients. For 2 additional patients (22 CTs), we compute the contour overlap between real and generated images, and compare the sampled and ‘ground truth’ distributions of volume and center of mass changes. Results. With a DICE score of 0.86 ± 0.05 and a distance between prostate contours of 1.09 ± 0.93 mm, DAM matches and improves upon previously published PCA-based models, using as few as 8 latent variables. The overlap between distributions further indicates that DAM’s sampled movements match the range and frequency of clinically observed daily changes on repeat CTs. Significance. Conditioned only on planning CT values and organ contours of a new patient without any pre-processing, DAM can accurately deformations seen during following treatment sessions, enabling anatomically robust treatment planning and robustness evaluation against inter-fraction anatomical changes.

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Due to recent development in detector technology, photon-counting computed tomography (PCCT) has become a rapidly emerging medical imaging technology. Current PCCT systems rely on the direct conversion of X-ray photons into charge pulses, using CdTe, CZT, or Si semiconductor detectors. Indirect detection using ultrafast scintillators coupled to silicon photomultipliers (SiPM) offers a potentially more straightforward and cost-effective alternative. In this work a new 2D perovskite scintillator, benzylamonium lead bromide (BZA)₂PbBr₄, is experimentally characterised as function of temperature. The material exhibits a 4.2 ns decay time under X-ray excitation at room temperature and a light yield of 3700 photons/MeV. The simulation tool developed by Van der Sar et al. was used to model the pulse trains produced by a SiPM-based (BZA)₂PbBr₄ detector. The fast decay time of (BZA)₂PbBr₄ results in outstanding count-rate performance as well as very low statistical fluctuations in the simulated pulses. These features of (BZA)₂PbBr₄, combined with its cost-effective synthesis make (BZA)₂PbBr₄ very promising for PCCT.

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X-ray detectors with photon-counting capabilities promise to revolutionise medical imaging. For an efficient comparison of detectors of various materials and with different setup choices, reliable detector performance measures are needed. The detector point spread function (PSF) is a commonly used measure, which describes the spatial response of an X-ray detector to the irradiation of a single pixel, given the energy spectrum of the source. In the case of an energy-resolving PCD, the detector PSF is typically derived for each energy bin and characterises its resolution. Moreover, it is commonly determined under low count rate conditions, to avoid dead time and pile-up related distortions. Under these assumptions, the PSF can be determined in a straightforward manner, but does not fully characterise the detector under all conditions encountered in clinical practice. This is especially true since the number of registered counts per energy bin depends on both the incident spectrum and the fluence rate, due to pile-up and dead time. We therefore propose a new metric, the differential point spread function (dPSF), which describes the change in the output count rate due to a small change in the input spectrum, for a given combination of incident spectrum and fluence rate. The dPSF can be used to characterize the spectral and spatial performance of a PCD under high-fluence conditions, i.e. when its response becomes non-linear. We illustrate the use of the dPSF by performing a Monte-Carlo study in which we compare the response of direct-conversion and scintillationbased PCDs at different fluence rates.

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We investigate fast silicon photomultiplier (SiPM)-based scintillation detectors for X-ray photon-counting applications, e.g., photon-counting computed tomography (CT). Such detectors may be an alternative to CdTe/CdZnTe (CZT) and Si detectors, which face challenges related to availability and cost-effective growth of detector-grade material, and detection efficiency, respectively. Here, we experimentally study energy response and count rate performance of a 1 mm × 1 mm single-pixel detector consisting of the readily available LaBr3:Ce scintillator and an ultrafast SiPM. We used three radio-isotopes and an X-ray tube for the experiments. Raw detector signals were processed by a second-order low-pass filter with a cut-off frequency f_c equal to 25 MHz or 100 MHz. The detector pulse height was shown to be proportional to photon energy. We measured FWHM energy resolutions of 19.5% (f_c=25 MHz) and 21.5% (f_c=100 MHz) at 60 keV. The measured X-ray tube spectra showed signs of the expected features of such spectra. The best count rate performance was achieved using f_c=100 MHz. In case of paralyzable-like counting and a 30 keV counting threshold, the maximum observed count rate (OCR) was 10.5 Mcps/pixel. For nonparalyzable-like counting and the same threshold, the OCR appeared to approach an asymptotic value greater than 20 Mcps/pixel. These numbers are close to those of CdTe/CZT detectors highly optimized for photon-counting CT. In conclusion, we show promising spectral X-ray photon-counting performance of an LaBr3:Ce scintillation detector with SiPM readout. Depending on the application-specific requirements, miniaturization of the pixel size may be necessary, for which we discuss potential dose-efficient implementations.

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Background: Accuracy and precision assessment in radiomic features is important for the determination of their potential to characterize cancer lesions. In this regard, simulation of different imaging conditions using specialized phantoms is increasingly being investigated. In this study, the design and evaluation of a modular multimodality imaging phantom to simulate heterogeneous uptake and enhancement patterns for radiomics quantification in hybrid imaging is presented. Methods: A modular multimodality imaging phantom was constructed that could simulate different patterns of heterogeneous uptake and enhancement patterns in positron emission tomography (PET), single-photon emission computed tomography (SPECT), computed tomography (CT), and magnetic resonance (MR) imaging. The phantom was designed to be used as an insert in the standard NEMA-NU2 IEC body phantom casing. The entire phantom insert is composed of three segments, each containing three separately fillable compartments. The fillable compartments between segments had different sizes in order to simulate heterogeneous patterns at different spatial scales. The compartments were separately filled with different ratios of 99mTc-pertechnetate, 18F-fluorodeoxyglucose ([18F]FDG), iodine- and gadolinium-based contrast agents for SPECT, PET, CT, and T1-weighted MR imaging respectively. Image acquisition was performed using standard oncological protocols on all modalities and repeated five times for repeatability assessment. A total of 93 radiomic features were calculated. Variability was assessed by determining the coefficient of quartile variation (CQV) of the features. Comparison of feature repeatability at different modalities and spatial scales was performed using Kruskal-Wallis-, Mann-Whitney U-, one-way ANOVA- and independent t-tests. Results: Heterogeneous uptake and enhancement could be simulated on all four imaging modalities. Radiomic features in SPECT were significantly less stable than in all other modalities. Features in PET were significantly less stable than in MR and CT. A total of 20 features, particularly in the gray-level co-occurrence matrix (GLCM) and gray-level run-length matrix (GLRLM) class, were found to be relatively stable in all four modalities for all three spatial scales of heterogeneous patterns (with CQV < 10%). Conclusion: The phantom was suitable for simulating heterogeneous uptake and enhancement patterns in [18F]FDG-PET, 99mTc-SPECT, CT, and T1-weighted MR images. The results of this work indicate that the phantom might be useful for the further development and optimization of imaging protocols for radiomic quantification in hybrid imaging modalities.@en

We investigate X-ray photon-counting scintillation detectors with silicon photomultiplier (SiPM) readout. These circumvent some drawbacks of direct-conversion detectors. We measured observed count rate (OCR) versus X-ray tube current for single-pixel detectors consisting of LYSO:Ce and YAP:Ce scintillators coupled to ultrafast SiPMs. For a 30 keV threshold, the maximum OCRs equal 4.5 Mcps/pixel (LYSO:Ce) and 5.5 Mcps/pixel (YAP:Ce) for paralyzable-like counting and 10 Mcps/pixel (LYSO:Ce) and 12.5 Mcps/pixel (YAP:Ce) for nonparalyzable-like counting. We estimate that the twice as fast LaBr3:Ce scintillator yields OCRs approaching those of CdTe/CZT-based photon-counting CT detectors. We also show energy response data and discuss dose-efficient pixel miniaturization.

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Breathing interplay effects in Intensity Modulated Proton Therapy (IMPT) arise from the interaction between target motion and the scanning beam. Assessing the detrimental effect of interplay and the clinical robustness of several mitigation techniques requires statistical evaluation procedures that take into account the variability of breathing during dose delivery. In this study, we present such a statistical method to model intra-fraction respiratory motion based on breathing signals and assess clinical relevant aspects related to the practical evaluation of interplay in IMPT such as how to model irregular breathing, how small breathing changes affect the final dose distribution, and what is the statistical power (number of different scenarios) required for trustworthy quantification of interplay effects. First, two data-driven methodologies to generate artificial patient-specific breathing signals are compared: a simple sinusoidal model, and a precise probabilistic deep learning model generating very realistic samples of patient breathing. Second, we investigate the highly fluctuating relationship between interplay doses and breathing parameters, showing that small changes in breathing period result in large local variations in the dose. Our results indicate that using a limited number of samples to calculate interplay statistics introduces a bigger error than using simple sinusoidal models based on patient parameters or disregarding breathing hysteresis during the evaluation. We illustrate the power of the presented statistical method by analyzing interplay robustness of 4DCT and Internal Target Volume (ITV) treatment plans for a 8 lung cancer patients, showing that, unlike 4DCT plans, even 33 fraction ITV plans systematically fail to fulfill robustness requirements.

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Purpose: The implementation of photon-counting detectors is widely expected to be the next breakthrough in X-ray computed tomography (CT) instrumentation. A small number of prototype scanners equipped with direct-conversion detectors based on room-temperature semiconductors, such as CdTe and CdZnTe (CZT), are currently installed at medical centers. Here, we investigate the feasibility of using silicon photomultiplier (SiPM)-based scintillation detectors in photon-counting computed tomography (PCCT) scanners, as a potential alternative to CdTe and CZT detectors. Methods: We introduce a model that allows us to compute the expected energy resolution as well as the expected pulse shape and associated rate capability of SiPM-based PCCT detectors. The model takes into account SiPM saturation and optical crosstalk, because these phenomena may substantially affect the performance of SiPM-based PCCT detectors with sub-mm pixels. We present model validation experiments using a single-pixel detector consisting of a 0.9 × 0.9 × 1.0 mm³ LuAP:Ce scintillation crystal coupled to a 1 × 1 mm² SiPM. We subsequently use the validated model to compute the expected performance of the fast scintillators LYSO:Ce, LuAP:Ce, and LaBr₃:Ce, coupled to currently available SiPMs, as well as to a more advanced SiPM prototype with improved dynamic range, for sub-mm pixel sizes. Results: The model was found to be in good agreement with the validation experiments, both with respect to energy resolution and pulse shape. It shows how saturation progressively degrades the energy resolution of detectors equipped with currently available SiPMs as the pixel size decreases. Moreover, the expected pulse duration is relatively long (~200 ns) with these SiPMs. However, when LuAP:Ce and LaBr₃:Ce are coupled to the more advanced SiPM prototype, the pulse duration improves to less than 60 ns, which is in the same order of magnitude as pulses from CdTe and CZT detectors. It follows that sufficient rate capability can be achieved with pixel sizes of 400 μm or smaller. Moreover, LaBr₃:Ce detectors can provide an energy resolution of 11.5%-13.5% at 60 keV, comparable to CdTe and CZT detectors. Conclusions: This work provides first evidence that it may be feasible to develop SiPM-based scintillation detectors for PCCT that can compete with CdTe and CZT detectors in terms of energy resolution and rate capability.

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The imaging performance of clinical positron emission tomography (PET) systems has evolved impressively during the last ∼15 years. A main driver of these improvements has been the introduction of time-of-flight (TOF) detectors with high spatial resolution and detection efficiency, initially based on photomultiplier tubes, later silicon photomultipliers. This review aims to offer insight into the challenges encountered, solutions developed, and lessons learned during this period. Detectors based on fast, bright, inorganic scintillators form the scope of this work, as these are used in essentially all clinical TOF-PET systems today. The improvement of the coincidence resolving time (CRT) requires the optimization of the entire detection chain and a sound understanding of the physics involved facilitates this effort greatly. Therefore, the theory of scintillation detector timing is reviewed first. Once the fundamentals have been set forth, the principal detector components are discussed: the scintillator and the photosensor. The parameters that influence the CRT are examined and the history, state-of-the-art, and ongoing developments are reviewed. Finally, the interplay between these components and the optimization of the overall detector design are considered. Based on the knowledge gained to date, it appears feasible to improve the CRT from the values of 200-400 ps achieved by current state-of-the-art TOF-PET systems to about 100 ps or less, even though this may require the implementation of advanced methods such as time resolution recovery. At the same time, it appears unlikely that a system-level CRT in the order of ∼10 ps can be reached with conventional scintillation detectors. Such a CRT could eliminate the need for conventional tomographic image reconstruction and a search for new approaches to timestamp annihilation photons with ultra-high precision is therefore warranted. While the focus of this review is on timing performance, it attempts to approach the topic from a clinically driven perspective, i.e. bearing in mind that the ultimate goal is to optimize the value of PET in research and (personalized) medicine.

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The first time-of-flight positron emission tomography (TOF-PET) scanners were developed as early as in the 1980s. However, the poor light output and low detection efficiency of TOF-capable detectors available at the time limited any gain in image quality achieved with these TOF-PET scanners over the traditional non-TOF PET scanners. The discovery of LSO and other Lu-based scintillators revived interest in TOF-PET and led to the development of a second generation of scanners with high sensitivity and spatial resolution in the mid-2000s. The introduction of the silicon photomultiplier (SiPM) has recently yielded a third generation of TOF-PET systems with unprecedented imaging performance. Parallel to these instrumentation developments, much progress has been made in the development of image reconstruction algorithms that better utilize the additional information provided by TOF. Overall, the benefits range from a reduction in image variance (SNR increase), through allowing joint estimation of activity and attenuation, to better reconstructing data from limited angle systems. In this work, we review these developments, focusing on three broad areas: 1) timing theory and factors affecting the time resolution of a TOF-PET system; 2) utilization of TOF information for improved image reconstruction; and 3) quantification of the benefits of TOF compared to non-TOF PET. Finally, we offer a brief outlook on the TOF-PET developments anticipated in the short and longer term. Throughout this work, we aim to maintain a clinically driven perspective, treating TOF as one of multiple (and sometimes competitive) factors that can aid in the optimization of PET imaging performance.

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Organ-specific, targeted field-of-view (FoV) positron emission tomography (PET)/magnetic resonance imaging (MRI) inserts are viable solutions for a number of imaging tasks where whole-body PET/MRI systems lack the necessary sensitivity and resolution. To meet the required PET detector performance of these systems, high count-rates and effective spatial resolutions on the order of a few mm, a novel two-axis patterned reflector foil pixelated scintillator crystal array design is developed and its proof-of-concept illustrated in-silico with the Monte Carlo radiation transport modeling toolkit Geant4. It is shown that the crystal surface roughness and phased open reflector cross-sectional patterns could be optimized to maximize either the PET radiation detector's effective spatial resolution, or count rate before event pile up. In addition, it was illustrated that these two parameters had minimal impact on the energy and time resolution of the proposed PET radiation detector design. Finally, it is shown that a PET radiation detector with balance performance could be constructed using ground crystals and phased open reflector cross-sectional pattern corresponding to the middle of the tested range.

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A broad range of scientific and industrial disciplines require precise optical measurements at very low light levels. Single-photon detectors combining high efficiency and high time resolution are pivotal in such experiments. By using relatively thick films of NbTiN (8-11 nm) and improving the pattern fidelity of the nanostructure of the superconducting nanowire single-photon detectors (SNSPD), we fabricated devices demonstrating superior performance over all previously reported detectors in the combination of efficiency and time resolution. Our findings prove that small variations in the nanowire width, in the order of a few nanometers, can lead to a significant penalty on their temporal response. Addressing these issues, we consistently achieved high time resolution (best device 7.7 ps, other devices a10-16 ps) simultaneously with high system detection efficiencies (80-90%) in the wavelength range of 780-1000 nm, as well as in the telecom bands (1310-1550 nm). The use of thicker films allowed us to fabricate large-area multipixel devices with homogeneous pixel performance. We first fabricated and characterized a 100 × 100 μm2 16-pixel detector and showed there was little variation among individual pixels. Additionally, to showcase the power of our platform, we fabricated and characterized 4-pixel multimode fiber-coupled detectors and carried out photon-correlation experiments on a nanowire quantum dot resulting in g2(0) values lower than 0.04. The multipixel detectors alleviate the need for beamsplitters and can be used for higher order correlations with promising prospects not only in the field of quantum optics, but also in bioimaging applications, such as fluorescence microscopy and positron emission tomography.

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The aim of this study was to investigate the feasibility of using prompt gamma (PG) ray emission profiles to monitor changes in dose to the planning target volume (PTV) during pencil beam scanning (PBS) proton therapy as a result of day-to-day variation in patient anatomy.&#13; For 11 prostate patients, we simulated treatment plan delivery using the patients' daily anatomy as observed in the planning CT and 7-9 control CT scans, including the detected PG profiles resulting from the 5%, 10%, and 20% most intense proton pencil beams. For each patient, we determined the changes in dosimetric parameters for the high- and low-dose PTVs between the simulations performed using the planning CT scan and the different control CT scans and correlated these to changes in the PG emission profiles.&#13; Changes in coverage of the high- and low-dose PTV correlated most strongly with the median and mean absolute PG emission profile shifts of the 5% most intense pencil beams, respectively. With a mean Pearson correlation coefficient of -0.76 (SD: 0.17) for the high-dose PTV and of -0.60 (SD: 0.51) for the low-dose PTV.&#13; We showed, as a proof of principle, that PG emission profiles obtained during PBS proton therapy could be used to detect changes in PTV coverage due to day-to-day anatomical variation.@en

Various methods for in vivo range estimation during proton therapy based on the measurement of prompt gamma (PG) photons have been proposed. However, optimizing the method of detection by trial-and-error is a tedious endeavor. Here, we investigate the feasibility of using the Cramér-Rao lower bound (CRLB) to more quickly arrive at an optimum detector design. The CRLB provides the smallest possible variance on the proton range obtained from any unbiased estimator, given a statistical model of the observations. We simulated clinical proton pencil beams targeting a cylindrical, soft-tissue equivalent phantom and scored the PG photons around the phantom. Spatially, temporally, and spectrally resolved PG emission profiles corresponding to different proton ranges were generated. We calculated the proton range estimation uncertainty as a function of several detector setup parameters, such as detector size, bin size, and photon acceptance angle. We found a minimum uncertainty for the proton range estimation based on either spatial, spectral, or temporal information of 2.13, 1.97, and 2.05 mm 2.05 mm, respectively, if the detection parameters were optimized for each case. We conclude that the CRLB is a promising tool for the optimization of the detector setup for PG-based range estimation in particle therapy.

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In proton therapy high energy protons are used to irradiate a tumor. Ideally, the delivered proton dose distribution is measured during treatment to ensure patient safety and treatment effectiveness. Here we investigate if we can use the ionoacoustic wave field to monitor the actual proton dose distribution for the two most commonly used proton accelerators; the isochronous cyclotron and the synchrocyclotron. To this end we model the acoustic field generated by the protons when irradiating a heterogeneous cancerous breast with a 89 MeV proton beam. To differentiate between the systems, idealized temporal micro-structures of the beams have been implemented. Results show that by employing model-based inversion we are able to reconstruct the 3D dose distributions from the simulated noisy pressure fields. Good results are obtained for both systems; the absolute error in the position of the maximum amplitude of the dose distribution is 5.0 mm for the isochronous cyclotron and 5.2 mm for the synchrocyclotron. In conclusion, this numerical study suggests that the ionoacoustic wave field may be used to monitor the proton dose distribution during breast cancer treatment.@en