The objective of this study is to test the ability of dual-energy CBCT to extract proton stopping power ratio (SPR) values for proton radiotherapy planning and to compare its performance to single-energy CBCT, while optimising the operating parameters of both single- and dual-energy CBCT for SPR extraction. We scanned three phantoms with a clinical CBCT installed in the gantry of a proton therapy facility at different source voltage and current settings. Dual-energy CBCT was emulated by combining scans from different kVps. We employed the Hünemohr-Saito method to predict SPR values for dual-energy CBCT scans, whereas we used a Hounsfield look-up table for predicting SPR values based on single-energy CT scans. The optimum operating parameters for dual-energy CBCT scans were an 80/125 kVp combination with a low/high kVp dose ratio of 75/25. This resulted in a relative mean error (RME) and a relative root mean square error (RRMSE) of (0.1 ± 1.2) % and (2.53±0.73) %, respectively. For single-energy CBCT scans, 125 kVp was determined to be the optimum voltage, yielding a RME and RRMSE value of (1.5±3.3) % and (7.1±6.9) %, respectively. Although limited in scope and in need of further experiments, this study indicates that dual-energy CBCT performs better than single-energy CBCT.

We investigate silicon photomultiplier (SiPM)-based scintillation detectors for medical X-ray photon-counting applications, where the input count rate (ICR) can reach a few Mcps/mm2 in cone-beam CT for radiotherapy, for example, up to a few hundred Mcps/mm2 in diagnostic CT. Thus, pulse pile-up can severely distort the measurement of counts and energies. Here, we experimentally evaluate the counting and spectral performance of SiPM-based scintillation detectors at 60 keV as a function of ICR/pile-up level. We coupled 0.9×0.9×3.5 mm3 LYSO:Ce and 0.9×0.9×4.5 mm3 YAP:Ce scintillators to 1.0×1.0 mm2 ultrafast SiPMs and exposed these single-pixel detectors to a 10-GBq Am-241 source. We varied ICR from 0 to 5 Mcps/pixel and studied detector performance for paralyzable-like (p-like) and nonparalyzable-like (np-like) counting algorithms, after applying a second-order low-pass filter with cut-off frequencies fc of 5, 10, or 20 MHz to the pulse trains. Counting performance was quantified by the output count rate (OCR) and the count-rate loss factor (CRLF). In addition to the traditional spectral performance measure of the fullwidth- at-half-maximum (FWHM) energy resolution at low ICR, we propose the spectral degradation factor (SDF) to quantify spectral effects of pile-up at any ICR. Best counting performance is obtained with np-like counting and fc = 20 MHz, for which the count-rate loss is at most 10% in the investigated range of ICRs, whereas p-like counting yields best spectral performance. Due to less pile-up, the fastest pulses obtained with fc = 20 MHz already provide the best SDF values at ICRs of a few Mcps/pixel, despite their worse low-rate energy resolution. Hence, spectral performance under pile-up conditions appears to benefit more from substantially faster pulses than a somewhat better low-rate energy resolution. Moreover, we show that the pulse shape of SiPM-based detectors allows to improve spectral performance under pile-up conditions using dedicated peak detection windows.

X-ray photon-counting detectors (PCDs) are a rapidly developing technology. Current PCDs used in medical imaging are based on CdTe, CZT, or Si semiconductor detectors, which directly convert X-ray photons into electrical pulses. An alternative approach is to combine ultrafast scintillators with silicon photomultipliers (SiPMs). Here, an overview is presented of different classes of scintillators, with the aim of assessing their potential application in scintillator-SiPM based indirect X-ray PCDs. To this end, three figures of merit (FOMs) are defined: the pulse intensity, the pulse duration, and the pulse quality. These FOMs quantify how characteristics such as light yield, pulse shape, and energy resolution affect the suitability of scintillators for application in indirect PCDs. These FOMs are based on emissive characteristics; a fourth FOM (ρZ_eff^3.5) is used to also take stopping power into account. Other important properties for the selection process include low self-absorption, low after-glow, possibility to produce sub-mm pitch pixel arrays, and cost-effectiveness. It is shown that material classes with promising emission properties are Ce³⁺- or Pr³⁺-doped materials, near band gap exciton emitters, plastics, and core-valence materials. Possible shortcomings of each of these groups, e.g., suboptimal emission wavelength, nonproportionality, and density, are discussed. Additionally, the engineering approach of quenching the scintillator emission, resulting in a targeted shortening of the decay time, and the possibility of codoping are explored. When selecting and/or engineering a material, it is important to consider not only the characteristics of the scintillator but also relevant SiPM properties, such as recharge time and photodetection efficiency.

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).

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.

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.

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.

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.

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.