Cherenkov imaging during radiotherapy provides a real time visualization of beam delivery on patient tissue, which can be used dynamically for incident detection or to review a summary of the delivered surface signal for treatment verification. Very few photons form the images, and one limitation is that the noise level per frame can be quite high, and mottle in the cumulative processed images can cause mild overall noise. This work focused on removing or suppressing noise via image postprocessing. Images were analyzed for peak-signal-to-noise and spatial frequencies present, and several established noise/mottle reduction algorithms were chosen based upon these observations. These included total variation minimization (TV-L1), non-local means filter (NLM), block-matching 3D (BM3D), alpha (adaptive) trimmed mean (ATM), and bilateral filtering. Each were applied to images acquired using a BeamSite camera (DoseOptics) imaged signal from 6x photons from a TrueBeam linac delivering dose at 600 MU/min incident on an anthropomorphic phantom and tissue slab phantom in various configurations and beam angles. The standard denoised images were tested for PSNR, noise power spectrum (NPS) and image sharpness. The average peak-signal-to-noise ratio (PSNR) increase was 17.4% for TV-L1. NLM denoising increased the average PSNR by 19.1%, BM3D processing increased it by12.1% and the bilateral filter increased the average PSNR by 19.0%. Lastly, the ATM filter resulted in the lowest average PSNR increase of 10.9%. Of all of these, the NLM and bilateral filters produced improved edge sharpness with, generally, the lowest NPS curve. For cumulative image Cherenkov data, NLM and the bilateral filter yielded optimal denoising with the TV-L1 algorithm giving comparable results. Single video frame Cherenkov images exhibit much higher noise levels compared to cumulative images. Noise suppression algorithms for these frame rates will likely be a different processing pipeline involving these filters incorporated with machine learning.

In preclinical research, in vivo imaging of mice and rats is more
common than any other animal species, since their physiopathology is very well-
known and many genetically altered disease models exist. Animal studies based on
small rodents are usually performed using dedicated preclinical imaging systems
with high spatial resolution. For studies that require animal models such as mini-
pigs or New-Zealand White (NZW) rabbits, imaging systems with larger bore
sizes are required. In case of hybrid imaging using Positron Emission Tomography
(PET) and Magnetic Resonance Imaging (MRI), clinical systems have to be used,
as these animal models do not typically fi t in preclinical simultaneous PET-MRI
scanners.
Approach. In this paper, we present initial imaging results obtained with the
Hyperion IID PET insert which can accommodate NZW rabbits when combined
with a large volume MRI RF coil. First, we developed a rabbit-sized image
quality phantom of comparable size to a NZW rabbit in order to evaluate the
PET imaging performance of the insert under high count rates. For this phantom,
radioactive spheres with inner diameters between 3.95 and 7.86 mm were visible
in a warm background with a tracer activity ratio of 4.1 to 1 and with a total
18-F activity in the phantom of 58MBq at measurement start. Second, we performed
simultaneous PET-MR imaging of atherosclerotic plaques in a rabbit in vivo using
a single injection containing 18-F-FDG for detection of infl ammatory activity,
and Gd-ESMA for visualization of the aortic vessel wall and plaques with MRI.
Main results. The fused PET-MR images reveal 18-F-FDG uptake within an
active plaques with plaque thicknesses in the sub-millimeter range. Histology
showed colocalization of 18-F-FDG uptake with macrophages in the aortic vessel wall lesions. 
Significance. Our initial results demonstrate that this PET insert
is a promising system for simultaneous high-resolution PET-MR atherosclerotic
plaque imaging studies in NZW rabbits.

Objective.This study proposes a robust optimization (RO) strategy utilizing virtual CTs (vCTs) predicted by an anatomical model in intensity-modulated proton therapy (IMPT) for nasopharyngeal cancer (NPC).Methods and Materials.For ten NPC patients, vCTs capturing anatomical changes at different treatment weeks were generated using a population average anatomy model. Two RO strategies of a 6 beams IMPT with 3 mm setup uncertainty (SU) and 3% range uncertainty (RU) were compared: conventional robust optimization (cRO) based on a single planning CT (pCT), and anatomical RO incorporating 2 and 3 predicted anatomies (aRO2 and aRO3). The robustness of these plans was assessed by recalculating them on weekly CTs (week 2-7) and extracting the voxel wise-minimum and maximum doses with 1 mm SU and 3% RU (voxmin\voxmax1mm3%).Results.The aRO plans demonstrated improved robustness in high-risk CTV1 and low-risk CTV 2 coverage compared to cRO plans. The weekly evaluation showed a lower plan adaptation rate for aRO3 (40%) vs. cRO (70%). The weekly nominal and voxmax1mm3%doses to OARs, especially spinal cord, are better controlled relative to their baseline doses at week 1 with aRO plans. The accumulated dose analysis showed that CTV1&2 had adequate coverage and serial organs (spinal cord and brainstem) were within their dose tolerances in the voxmin\voxmax1mm3%, respectively.Conclusion.Incorporating predicted weekly CTs from a population based average anatomy model in RO improves week-to-week target dose coverage and reduces false plan adaptations without increasing normal tissue doses. This approach enhances IMPT plan robustness, potentially facilitating reduced SU and further lowering OAR doses.

This study describes the development, validation, and integration of a detector response model that accounts for the combined effects of x-ray crosstalk, charge sharing, and pulse pileup in photon-counting detectors. The x-ray photon transport was simulated using Geant4, followed by analytical charge sharing simulation in MATLAB. The analytical simulation models charge clouds with Gaussian-distributed charge densities, which are projected on a 3x3 pixel neighborhood of interaction location to compute detected counts. For pulse pileup, a prior analytical method for redistribution of energy-binned counts was implemented for delta pulses. The x-ray photon transport and charge sharing components were validated using experimental data acquired on the CdTe-based Pixirad-1/Pixie-III detector using monoenergetic beams at 26, 33, 37, and 50 keV. The pulse pileup implementation was verified with a comparable Monte Carlo simulation. The model output without pulse pileup was used to generate spatio-energetic response matrices for efficient simulation of scanner-specific photon-counting CT (PCCT) images with DukeSim, with pulse pileup modeled as a post-processing step on simulated projections. For analysis, images for the Gammex multi-energy phantom and the XCAT chest phantom were simulated at 120 kV, both with and without pulse pileup for a range of doses (27-1344 mAs). The XCAT images were evaluated qualitatively at 120 mAs, while images for the Gammex phantom were evaluated quantitatively for all doses using measurements of attenuation coefficients and Calcium concentrations. Reasonable agreement was observed between simulated and experimental spectra with Mean Absolute Percentage Error Values (MAPE) between 10%-31% across all incident energies and detector modes. The increased pulse pileup from increased dose affected attenuation coefficients and calcium concentrations, with an effect on calcium quantification as high as MAPE of 28%. The presented approach demonstrates the viability of the model for enabling VITs to assess and optimize the clinical performance of PCCT.

High atomic number element nanoparticles have shown potential in tumor diagnosis and therapy. X-ray fluorescence computed tomography (XFCT) technology enables quantitative imaging of high atomic number elements by specifically detecting characteristic X-ray signals. The potential for further biomedical applications of XFCT depends on balancing sensitivity, spatial resolution, and imaging speed in existing XFCT imaging systems. In this study, we utilized a high-energy resolution pixelated photon-counting detector for XFCT imaging. We tackled degradation caused by multi-pixel events in the photon-counting detector through energy and interaction position corrections. Sensitivity and spatial resolution imaging experiments were conducted using PMMA phantoms to validate the effectiveness of the multi-pixel events correction algorithm. After correction, the system's sensitivity and spatial resolution have both improved. Furthermore, XFCT/CBCT dual-modality imaging of gadolinium nanoparticles within mice subcutaneous tumor was successfully achieved. These results demonstrate the preclinical research application potential of the XFCT/CBCT dual-modality imaging system in high atomic number nanoparticle-based tumor diagnosis and therapy.

Purpose&#xD;Patient-tailored intracavitary/interstitial (IC/IS) brachytherapy (BT) applicators may increase dose conformity in cervical cancer patients. Current configuration planning methods in these custom applicators rely on manual specification or a small set of (straight) needles. This work introduces and validates a two-stage approach for establishing channel configurations in the 3D printed patient-tailored ARCHITECT applicator. &#xD;&#xD;Methods&#xD;For each patient, the patient-tailored applicator shape was based on the first BT application with a commercial applicator and integrated connectors to a commercial (Geneva) intrauterine tube and two lunar ring channels. First, a large candidate set was generated of channels that steer the needle to desired poses in the target region and are contained in the applicator. The channels' centrelines were represented by Bézier curves. Channels running between straight target segments and entry points were optimised and refined to ensure (dynamic) feasibility. Second, channel configurations were selected using geometric coverage optimisation. This workflow was applied to establish patient-tailored geometries for twenty-two patients previously treated using the Venezia applicator. Treatment plans were automatically generated using the in-house developed algorithm BiCycle. Plans for the clinically used configuration, TPclin, and patient-tailored configuration, TParch, were compared.&#xD;&#xD;Results&#xD;Channel configurations could be generated in clinically feasible time (median: 2651s, range 1826-3812s). All TParchand TPclinplans were acceptable, but planning aims were more frequently attained with patient-tailored configurations (115/132 versus 100/132 instances). Median CTVIRD98and bladderD2cm3doses significantly improved (p< 0.001 andp< 0.01 respectively) in TParchplans in comparison with TPclinplans, and in approximately half of the patients dosimetric indices improved. &#xD;&#xD;Conclusion&#xD;Automated patient-tailored BT channel configuration planning for 3D printed applicators is clinically feasible. A treatment planning study showed that all plans met planning limits for the patient-tailored configurations, and in selected cases improved the plan quality in comparison with commercial applicator configurations.&#xD.

Deep learning (DL) is becoming increasingly important in generating attenuation maps for accurate attenuation correction in cardiac perfusion SPECT imaging. Typically, DL models take inputs from initial reconstructed SPECT images, which are performed on the photopeak window and often also on scatter windows. While prior studies have demonstrated improvements in DL performance when scatter window images are incorporated into the DL input, the comprehensive analysis of the impact of employing different scatter windows remains unassessed. Additionally, existing research mainly focuses on applying DL to SPECT scans obtained at clinical standard count levels. This study aimed to assess utilities of DL from two aspects: 1) investigating the impact when different scatter windows were used as input to DL, and 2) evaluating the performance of DL when applied on SPECT scans acquired at a reduced count level. We utilized 1517 subjects, with 386 subjects for testing and the remaining 1131 for training and validation. The results showed that as scatter window width increased from 4% to 30%, a slight improvement was observed in DL estimated attenuation maps. The application of DL models to quarter-count (¼-count) SPECT scans, compared to full-count scans, showed a slight reduction in performance. Nonetheless, discrepancies across different scatter window configurations and between count levels were minimal, with all normalized mean square error (NMSE) values remaining within 2.1% when comparing the different DL attenuation maps to the reference CT maps. For attenuation corrected SPECT slices using DL estimated maps, NMSE values were within 0.5% when compared to CT correction. This study, leveraging an extensive clinical dataset, showed that the performance of DL seemed to be consistent across the use of varied scatter window settings. Moreover, our investigation into reduced count studies indicated that DL could provide accurate attenuation correction even at a ¼-count level.

&#xD;The integration of proton beamlines with X-ray imaging/irradiation platforms has opened up possibilities for image-guided Bragg peak irradiations in small animals. Such irradiations allow selective targeting of normal tissue substructures and tumours. However, their small size and location pose challenges in designing experiments. This work presents a simulation framework useful for optimizing beamlines, imaging protocols, and design of animal experiments. The usage of the framework is demonstrated, mainly focusing on the imaging part.&#xD;Approach:&#xD;The fastCAT toolkit was modified with Monte Carlo (MC)-calculated primary and scatter data of a small animal imager for the simulation of micro-CT scans. The simulated CT of a mini-calibration phantom from fastCAT was validated against a full MC TOPAS CT simulation. A realistic beam model of a preclinical proton facility was obtained from beam transport simulations to create irradiation plans in matRad. Simulated CT images of a digital mouse phantom were generated using single-energy CT (SECT) and dual-energy CT (DECT) protocols and their accuracy in proton stopping power ratio (SPR) estimation and their impact on calculated proton dose distributions in a mouse were evaluated.&#xD;Main Results:&#xD;The CT numbers from fastCAT agree within 11 HU with TOPAS except for materials at the centre of the phantom. Discrepancies for central inserts are caused by beam hardening issues. The root mean square deviation in the SPR for the best SECT (90kV/Cu) and DECT (50kV/Al-90kV/Al) protocols are 3.7% and 1.0%, respectively. Dose distributions calculated for SECT and DECT datasets revealed range shifts <0.1 mm, gamma pass rates (3%/0.1mm) greater than 99%, and no substantial dosimetric differences for all structures. The outcomes suggest that SECT is sufficient for proton treatment planning in animals.&#xD;Significance:&#xD;The framework is a useful tool for the development of an optimized experimental configuration without using animals and beam time.&#xD.

Cone beam CT is integral to most modern radiotherapy treatments. The application of daily and repeat CBCT imaging can lead to high imaging doses over a large volume of tissue that extends beyond the treatment site. Hence, it is important to ensure exposures are optimised to keep doses as low as reasonably achievable, whilst ensuring images are suitable for the clinical task. &#xD;This IPEM topical report presents the results of the first UK survey of dose indices in radiotherapy CBCT. Dose measurements, as defined by the Cone Beam Dose Index (CBDIw), were collected along with protocol information for seven treatment sites. Where a range of optimised protocols were available in a centre, a sample of patient data demonstrating the variation in protocol use were requested. Protocol CBDIw values were determined from the average dosimetry data for each type of linear accelerator, and median CBDIw and scan length were calculated for each treatment site at each centre. Median CBDIw values were compared and summary statistics derived that enable the setting of national dose reference levels (DRLs). &#xD;A total of 63 UK radiotherapy centres contributed data. The proposed CBDIw DRLs are; prostate 20.6 mGy, gynaecological 20.8 mGy, breast 5.0 mGy, 3D-lung 6.0 mGy, 4D-lung 11.8 mGy, brain 3.5 mGy and head/neck 4.2 mGy. However, large differences between models of imaging system were noted. Where centres had pro-active optimisation strategies in place, such as sized based protocols with selection criteria, dose reductions on the 'average' patient were possible compared with vendor defaults. Optimisation of scan length was noted in some clinical sites, with Elekta users tending to fit different collimators for prostate imaging (relatively short) compared with gynaecological treatments (longest). This contrasts with most Varian users who apply the default scan length in most cases.