Enhanced wide-field gamma camera system with hybrid coded aperture and pinhole collimation

Accurate range verification is crucial in hadrontherapy to fully exploit the ballistic advantages of charged particles and prevent damage to healthy tissues. Among the proposed approaches, prompt gamma imaging (PGI) has emerged as an effective technique for real-time monitoring, but its performance is limited by the intense neutron background generated during irradiation, especially withcarbon-ions. This work presents a Monte Carlo study performed with the FLUKA code to investigate prompt gamma and neutron emission in proton and carbon-ion therapy. A prototype detection system based on a knife-edge collimator coupled to a pixelated LYSO scintillator was simulated to evaluate its capability for range verification. The aim is to quantify how neutron fields and neutron induced signals bias or degrade range related quantities, and how these effects differ between proton and carbon-ionbeams. The analysis includes the characterization of prompt gamma energy spectra and spatial profiles, the assessment of neutron fields within a treatment room, and the decomposition of the detector signal into primary gammas, secondary gammas, andneutrons. Results show that prompt gamma profiles correlate well with the Bragg peak position, particularly within the 3-7MeV energy window, while carbon ions exhibit higher prompt gamma yields but also significantly stronger neutron backgrounds compared to protons. Detector simulations highlight the impact of neutron capture on lutetium, producing distinct peaks that must be accounted for in the detector signal analysis. The fall-off retrieval precision (FRP) analysis indicates that the distal fall-off of prompt gamma profiles can be used to estimate the Bragg peak position, while secondary radiation components introduce additional fluctuations that affect the achievable precision, particularly for carbon-ionbeams. The study provides a detailed characterization of prompt gamma and neutron contributions in proton and carbon-ion therapy and highlights the main physical factors affecting PGI-based range monitoring, particularly in the presence of neutron-induced backgrounds. These results provide useful insights for the design and optimization of prompt gamma detection systems in clinicalapplications.

This study presents the first clinical integration and experimental demonstration of a nozzle-mounted Compton camera prompt gamma imaging (PGI) system for in vivo proton range verification. Four position-sensitive solid-state Compton camera modules, each containing four cadmium zinc telluride (CdZnTe) detector crystals, were integrated into a modified range shifter mounted directly on the treatment nozzle of a clinical proton therapy gantry. This compact fixed-geometry configuration maintained alignment with the proton beam axis throughout irradiation and enabled stable synchronized data acquisition during pencil-beam scanning delivery. The system was evaluated under realistic clinical proton beam delivery conditions using single-energy and spread-out Bragg peak (SOBP) irradiations at gantry angles of 90° and 270°, delivered doses of 2 Gy and 7.5 Gy, and controlled distal range shifts of up to 10 mm. Prompt gamma events were reconstructed into three-dimensional emission distributions using a physics-based Compton scatter reconstruction framework. The system operated reliably during all irradiations and produced reproducible prompt-gamma localization across repeated measurements. Reconstructed emission distributions remained geometrically consistent across gantry angles and demonstrated sensitivity to controlled distal range perturbations, with measurable upstream shifts of the emission hotspot corresponding to reduced proton penetration depth. These results demonstrate the feasibility of a clinically integrated nozzle-mounted quad-camera Compton PGI system for detecting millimeter-scale proton range variations during beam delivery and represent an important step toward clinically deployable prompt gamma-based in vivo treatment verification in proton therapy.

Abstract Gamma imaging encompasses a broad range of studies spanning multiple organ systems. The myriad of radiopharmaceuticals, the dynamic nature of imaging protocols, and the complexity of image interpretation render mastery of this topic a source of great challenge. This two-part series provides an educational resource that introduces the basic concepts of gamma nuclear imaging, with a focus on the most commonly encountered studies across institutions.

Abstract Background: Neoadjuvant chemotherapy (NAC) is the standard treatment for locally advanced breast cancer. Achieving a pathologic complete response (pCR) is strongly associated with favorable long-term outcomes. However, current imaging modalities, such as magnetic resonance imaging (MRI), have limitations in quantifying residual metabolic activity following NAC. Breast-specific gamma imaging (BSGI) provides functional assessment through the tumor-to-normal ratio (TNR), with established diagnostic value in prior studies. Prospective validation of TNR's predictive value for pCR and survival outcomes is currently lacking. This study aims to evaluate whether post-NAC TNR can identify patients with chemo-sensitive tumors and a superior prognosis. Methods: This single-center prospective trial (NCT02556684) enrolled 137 patients with stage I-III breast cancer who received standard NAC followed by surgery between 2014 and 2023. Inclusion criteria required patients to have clinical stage T1-4 and N0-3, baseline biopsy-confirmed invasive carcinoma, and completion of the planned NAC regimen. Exclusion criteria were bilateral or metastatic disease or incomplete NAC. Breast-specific gamma imaging was performed after 2 cycles of NAC using 99mTc-sestamibi (MIBI) and dual-head gamma cameras. The tumor-to-normal ratio (TNR) was calculated as the maximum tumor uptake divided by the mean uptake in the contralateral breast parenchyma. The primary endpoints were pathological complete response (pCR) and 3-year disease-free survival (DFS). Statistical analyses included χ2 tests for associations, Kaplan-Meier analysis with log-rank tests for survival comparisons, and multivariate Cox regression models adjusted for clinicopathologic covariates. Results: Baseline characteristics were balanced between groups for age, nodal status, grade, and Ki-67 (p>0.05), though TNR-low patients had significantly higher HER2+ subtype prevalence (65% vs. 46%, p = 0.026). TNR-low was strongly associated with pathologic complete response (pCR), with 34.8% achieving pCR versus 14.7% in TNR-high group. Survival analysis demonstrated significantly improved disease-free survival (DFS) for TNR-low patients after median follow-up of 42.5 months. DFS benefits were consistently observed in the overall population and key clinical subgroups: overall cohort (hazard ratio [HR] = 0.33, 95% confidence interval [CI]:0.14-0.81, p = 0.002), HR+HER2- (HR = 0.23; 95% CI:0.07-0.73; p = 0.001), HER2+ (HR = 0.23; 95% CI:0.04-1.48; p = 0.009), pCR patients (HR = 0, p = 0.016), and non-pCR patients (HR = 0.42; 95% CI:0.18-1.00; p = 0.02). The triple-negative subgroup showed non-significant trends likely due to limited sample size (n = 19). TNR demonstrated independent prognostic value in multivariate Cox regression. After adjusting for established factors (including pCR status, T stage, nodal stage, Grade and Ki-67 index), TNR-low status confirmed as a significant predictor of superior disease-free survival (DFS), with a hazard ratio of 0.43 (95% CI: 0.20-0.93; p = 0.031). Notably, TNR demonstrated predictive capacity beyond pathologic complete response. No endpoint events occurred in TNR-low/pCR patients, whereas TNR-low/non-pCR patients had 58% lower risk of recurrence versus TNR-high/non-pCR patients. Conclusion: These results establish TNR as a robust imaging biomarker which serves as a valuable complement to current assessment methods. The prospective design and consistent survival benefit across multiple subgroups support clinical integration of BSGI-derived parameters to guide post-neoadjuvant risk stratification, potentially enabling therapy escalation for TNR-high/non-pCR patients and de-escalation strategies for TNR-low/pCR patients. Citation Format: T. Qian, X. Ye, Y. Wu, L. Pang, L. Li, X. Yu, Z. Wang, J. Huang. Predictive Value of Breast-Specific Gamma Imaging for Pathologic Response and Prognosis in Early Breast Cancer After Neoadjuvant Therapy: A Prospective Trial [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS1-06-01.

The calibration and performance of a 2D planar neutron and gamma imaging detector

This study presents a novel simulation study for integrating four Compton Cameras (CC) into proton therapy systems by mounting them directly on the snout of the treatment gantry for prompt gamma imaging (PGI). This compact, fixed geometry simplifies detector integration, maintains alignment with the proton beam axis, and supports in vivo proton range verification. A Geant4-based Monte Carlo framework, PJ-MC, was used to simulate prompt gamma emissions (PGE) in water and patient-specific geometry. PG image reconstruction was performed using the Kernel Weighted Back Projection (KWBP) algorithm. To improve range accuracy, we introduced a post-processing method called Point Source Normalization (PSN), which uses precomputed PGI responses for monoenergetic gamma point sources at different depths to normalize PGI images and correct distortions from attenuation, geometric factors, and detector responses from PGE detected curve. Simulations with monoenergetic sources confirmed the influence of depth-dependent attenuation and inverse square losses, especially at higher proton energies. Clinical beam energies of 70, 150, and 200 MeV were tested. KWBP reconstructions showed increasing range discrepancies with energy, reaching 176 mm (water) and 144 mm (patient) at 200 MeV. PSN correction reduced these errors by up to 70%, bringing PG hotspots closer to the Bragg peak . Simulations with anterior/posterior shifts showed that the PSN-corrected system could detect millimeter-scale range deviations from setup uncertainties and beam shifts. This is the first study to simulate and evaluate a snout-mounted CC system for PGI in proton therapy. Results support future validation under clinical beam conditions in phantoms and patients.

In recent years, intensity interferometry has seen renewed interest and successful application at imaging atmospheric cherenkov telescope arrays such as the High Energy Stereoscopic System (H.E.S.S.), Major Atmospheric Gamma Imaging Cherenkov Telescopes (MAGIC), and Very Energetic Radiation Imaging Telescope Array System (VERITAS). These measurements are usually performed during bright moon periods, whereas the instruments’ primary purpose—gamma-ray observations—cannot be fulfilled. The mobile intensity interferometer for stellar observations was designed as a proof of concept for a purpose-built intensity interferometer. Using acrylic Fresnel lenses 1 m in diameter with a 1.2 m focal length, a compact, economical, and lightweight design was realized. The detector fixture allows for translation in the z-axis to adjust for measurements at different wavelengths (and therefore focal points) and easy swapping of the detector in its entirety. Both mobility and scalability in quantity of this design allow for specific targeting of projected baselines and orientations based on the target. Particularly for potential binary systems, selective coverage of a target’s u–v plane is essential to probing the characteristics accurately. A first campaign demonstrated the capability of these Fresnel lens telescopes by measuring the spatial coherence curve of Arcturus (α Boo). In an observation time of less than 11 h, the angular diameter was measured with milliarcsecond precision, in agreement with the values in the literature.

Prompt Gamma Imaging (PGI) holds strong potential for range verification in hadrontherapy, yet its performance is challenged by neutron-induced background, especially in carbon ion treatments. To mitigate this issue, a dedicated imaging system integrating Pulse Shape Discrimination (PSD) capabilities for real-time neutron discrimination was designed and experimentally validated. The detector employs a CLYC scintillator coupled to SiPM arrays and compact acquisition electronics, allowing real-time computation of digital PSD coefficients. Interaction point reconstruction within the crystal is achieved through an Artificial Neural Network (ANN), whose inputs are the SiPM signal amplitudes processed by four custom 16-channel GAMMA ASICs. In this work, the system is operated as a Prompt Gamma (PG) camera using a knife-edge collimator to retrieve PG emission profiles from the irradiated target, enabling range verification while efficiently reducing uncorrelated neutron contributions. We present the outcomes of the first experimental PGI campaign at Centro Nazionale di Adroterapia Oncologica (CNAO) in Pavia (Italy), during carbon ion irradiation, demonstrating, according to our knowledge, the first improvement in Bragg Peak (BP) localization precision enabled by PSD-based neutron background rejection.

Accurate 3-D Radiation Field Measurement via Focus-Enhanced Gamma Imaging and Density-Adaptive Point Cloud Fusion

Fuel assemblies represent the fundamental structural elements within nuclear reactors, and their operational safety is of paramount importance for ensuring overall reactor reliability. Under complex service conditions, including elevated temperatures, high pressures, and intense neutron radiation environments, fuel pellets housed within rod assemblies are susceptible to deformation, swelling, and potential cladding failure, all of which pose significant safety risks. Accurate characterization of the spatial distribution uniformity of uranium within the fuel matrix is essential for assessing nuclear fuel integrity and enhancing safety margins. This study conducts a computational analysis of uranium distribu tion uniformity in nuclear fuel using gamma imaging methodologies. A dedicated nuclear fuel inspection platform employing gamma imaging techniques was established, with detailed physical models developed and implemented in the MCNP simulation environment. The approach simulates and quantifies uranium distribution through gamma-ray absorption analysis. Scanning gamma imaging simulations were performed, effectively differentiating regions with uniform and non-uniform uranium distributions. These results offer a robust foundation for optimizing detection system configurations and advancing nuclear fuel inspection technologies.

Purpose of research . Improving the reliability of object recognition in an image by investigating the effect of gamma correction of the input image on the quality coefficient of object recognition on it. Methods . Pre-processing of images obtained using the complex of video recording of traffic violations installed in the city of Kursk includes gamma correction, conversion from RGB to grayscale, blurring with a Gauss filter, highlighting the boundaries of objects based on the Canny algorithm, classification of objects using the YOLO algorithm. Results . The main advantages of adaptive control traffic control systems are considered. The structural scheme of the pedestrian crossing control system and the stages of input image preprocessing, including gamma correction, and their effect on the reliability of object detection are described. The Recall indicator was calculated to quantify the detection efficiency at different gamma correction values for each of the classes under consideration: pedestrians (Recall = 0.46), cars (Recall =0.824), traffic lights (Recall =0.60). Conclusion . The results of a series of experimental studies prove the positive effect of gamma correction on the recognition efficiency of only certain classes of objects, such as traffic lights, requiring a minimum value of γ ≈ 1.5 (gamma 100) to start recognition. The detection of other classes considered, such as pedestrians and cars, remains stable at any gamma values from the range [0; 200]. The largest number of detections was recorded at ranges of 20 and 80 for pedestrians and at ranges of 60, 100 and 120 for cars.

The X and Gamma Imager and Spectrometer (XGIS) on board THESEUS is a finely pixelized and modular instrument designed for broadband high-energy transient detection. XGIS consists of two cameras, each composed of 10 supermodules, with each supermodule further divided into 10 modules and each module made with 64 independent readout pixels based on Silicon Drift Detectors coupled with 5 × 5 × 30 mm3 CsI scintillator bars. An algorithm to quickly read out the signals from the 64 pixels and send them in chronological order through the module and supermodule logic up to the camera logic is under development. Furthermore, a challenge for space-based high-energy instruments is distinguishing X-/gamma-ray photons while effectively rejecting background photons and particles, including electrons, protons, and heavier cosmic rays. Unlike traditional systems that rely on anticoincidence systems, XGIS aims to achieve background rejection through an innovative readout logic that analyzes the spatial and temporal properties of energy deposits in the detector. By leveraging the finely pixelized structure, the readout system can differentiate single-photon events from charged-particle tracks based on energy deposition patterns and event topology.

BackgroundIn online adaptive proton therapy (OAPT), additional treatment verification techniques are crucial for detecting treatment deviations and acting as a safety net, as phantom‐based patient‐specific quality assurance methods are not applicable. Prompt gamma imaging (PGI) has the potential for online treatment verification without adding dose nor prolonging treatment. PGI has proven to detect relevant anatomical changes under real‐world clinical conditions. Range probing (RP) has shown its clinical applicability for in‐vivo proton range assessment before treatment, thereby helping to address uncertainties. It has been proven useful for quality control of cone‐beam CT‐based synthetic CTs, suggesting its adoption into OAPT.PurposeThe performance of PGI and RP, two different yet complementary treatment verification methods, was compared by consecutive measurements within one experimental setup. Anatomical changes (AC) and setup errors (SE) were mimicked in an anthropomorphic head phantom.MethodsThe PGI‐system was positioned beneath the phantom while the RP‐system was positioned distally, allowing a simultaneous setup of both systems at a horizontal gantry angle. A brain target was irradiated with a 1‐field pencil‐beam scanning treatment plan and a low‐dose RP‐plan with high‐energy protons that passed through the phantom. Upstream and downstream positioned water‐equivalent material slabs of 2/3/5 mm or 5 mm thicknesses mimicked AC within the beam path or beyond the target, respectively. Additionally, the couch was shifted 2 and 3 mm in left, down and upstream direction in beam's eye view (BEV), mimicking SE. Both plans were delivered and monitored 10 times for each AC and SE configuration. Geometrical range shifts measured with PGI were converted to water‐equivalent thickness range shifts for direct comparison between PGI and RP results.ResultsBoth systems detected range deviations relevant for the treatment field, caused by AC within the clinical beam path. RP measurements were more precise for all scenarios (RP: 1σ ≤ 0.3 mm, PGI: 1σ ≤ 0.8 mm). PGI was similarly accurate for the 2 mm slab while slightly underestimating 3 and 5 mm slabs (≤ 0.7 mm). Only RP detected AC beyond the target, which are irrelevant for the monitored treatment field.Both systems detected expected range shifts of all SEs. RP was more accurate than PGI (RP: within 0.3 mm, PGI: within 0.8 mm). The couch movement left in BEV was detected with slightly higher precision using PGI (RP: 1σ ≤ 1.0 mm, PGI: 1σ ≤ 0.9 mm), while the precision of detecting the couch movement down in BEV was the same for both systems (1σ ≤ 0.7 mm). Only PGI recognized couch movements upstream (accuracy within 0.4 mm).ConclusionBoth PGI and RP precisely detected introduced AC relevant for the monitored treatment field. SE were detected, but with greater uncertainty. While the current implementation of RP enables pretreatment range verification after setup imaging with a low‐dose RP‐field, PGI enables treatment verification during field delivery, detecting range deviations relevant for the treatment field. The simultaneous setup of PGI and RP clearly demonstrated their compatibility in a clinical setting, the unique advantages of each system and their crucial role as safety nets in OAPT.

Energy window selection is a critical parameter for optimizing planar gamma image quality in nuclear medicine. In this study, we developed dedicated nuclear medicine phantoms using 3D printing technology to evaluate the impact of varying energy window levels on image quality. Three types of phantoms—a Derenzo phantom with six different sphere diameters, a modified Hoffman phantom incorporating lead for attenuation, and a quadrant bar phantom with four bar thicknesses constructed from bronze filament—were fabricated using Fusion 360 and an Ultimaker S5 3D printer with PLA and bronze-based materials. Planar images were acquired using 37 MBq of Tc-99m for 60 s at energy windows centered at 122, 140, and 159 keV. Quantitative assessments included contrast-to-noise ratio (CNR), coefficient of variation (COV), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM), comparing all images with the 140 keV image as the reference. The results showed a consistent decline in image quality at 122 keV and 159 keV, with the highest CNR, lowest COV, and optimal PSNR/SSIM values obtained at 140 keV. In visual analysis using the quadrant bar phantom, thinner bars were more clearly discernible at 140 keV than at other energy levels. These findings demonstrate that the application of an appropriate energy window—particularly 140 keV for Tc-99m—substantially improves image quality in planar gamma imaging. The use of customized, material-specific 3D-printed phantoms also enables flexible, reproducible evaluation protocols for energy-dependent imaging optimization and quality assurance in clinical nuclear medicine.

The hit position reconstruction algorithm for neutron and gamma imaging detectors based on artificial neural networks

Research on gamma image reconstruction method for estimating radiation source distance using the dichotomy method.

One of the common challenges in medical artificial intelligence (AI) applications using echocardiography is the lack of image data harmonization. This study aims to improve the prediction accuracy of left ventricular ejection fraction (LVEF) AI models by incorporating data augmentation (DA) techniques to address the variability in image data across different vendor machines. A database comprising 15,770 echocardiographic videos from 3154 patients across five different centers was utilized, with the data acquired using various vendor machines. We prepared datasets specific to GE healthcare (GE), philips (PH), and canon medical systems (CA) vendors, including 1911, 804, and 427 cohorts, respectively. A three-dimensional convolutional neural network (3D-CNN) was trained to predict LVEF, using videos consisting of 20 images per heartbeat as input, with training performed exclusively on data from GE machines (GE-based model). DA techniques, including gamma correction, scaling, median filtering, unsharp masking, translation, rotation, noise correction, and image conversion using a cycle generative adversarial network, were applied. A regression analysis using five different chamber views was performed on the GE test data. The accuracy of LVEF prediction using the GE-based model with DA—specifically gamma correction, scaling, and translation corrections—was excellent. The mean absolute error (root mean square error) in test cohorts was 4.33 (5.58) for GE, 4.42 (5.57) for PH, and 4.89 (6.57) for CA, which were comparable to the results of a model developed using data from all vendors, demonstrating the effectiveness of DA in harmonizing images. This study demonstrates that echocardiographic videos are transferable across vendors and that DA is highly effective in improving LVEF predictions from data acquired using different vendor machines.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-21277-y.

Edge detection for dimensional characterization in AI-enhanced gamma tomography of reinforced concrete

The development of an electronic readout platform specifically designed for real-time range verification systems to be used in hadrontherapy is presented. Such modular systems are composed of multiple 64-channel gamma camera modules based on pixelated LYSO scintillator coupled with 15 μm cell SiPM arrays. Both the detector and the associated electronics are specifically designed to support range verification through Prompt Gamma Imaging (PGI). Such an application requires a specific electronics readout able to operate in a wide energy range (up to 10 MeV) and at high counting rates (up to 1 Mcps/ch). The system's modular structure allows it to accommodate various treatment plans and overcomes limitations related to patient anatomy and beam positioning. The detector is composed of 64-channel modules, each covering an area of 52.6 × 52.6 mm2, with each module consisting of two 32-channel front-end electronics readout and data acquisition systems (DAQ). The SiPMs outputs are processed by two 16-channel SITH ASICs. These integrated circuits are optimized for reading SiPM arrays and can handle high input currents (on the order of tens of milliamps), which makes them suitable for large-area photodetectors and high energy gamma rays. The DAQ architecture is based on a 32-channel sub-module and consists of two multi-channel Analog to Digital Converters (ADC) and an FPGA. The energy signals from the ASICs are digitized by an octal-channel, 12-bit, 65 Msps ADC. This ADC is multiplexed 2:1 to read all 16 channels of each ASIC. For precise timing measurements, 32 Time-to-Digital Converters (TDCs) are integrated within the FPGA, achieving a temporal resolution better than 300 ps (FWHM). In FPGA firmware a time-coincidence strategy has been implemented in order to reconstruct interactions resulting from Compton scattering and pair production.