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The linear no-threshold dose response model (LNT) is used to estimate health effects due to exposure to ionizing radiation. It has been used extensively by US regulatory agencies for many decades to establish radiation exposure limits and to estimate future health (primarily cancer) effects for both projected (e.g., for a proposed nuclear facility or activity) and previous radiation exposures. The model assumes a linear relationship between dose and health effects, even for very low doses within the range of natural background radiation, where biological effects may be difficult or impossible to observe or may not exist. The LNT model implies that all exposure to ionizing radiation is harmful, regardless of how low the dose, since it assumes there is "no safe threshold" for exposure to radiation. That is, based on the implications of the LNT model, any exposure could result in increased cancer and possibly undesirable genetic effects. A major objective of this paper is to provide data and approaches that we as health physicists can use to communicate these highly controversial and misunderstood concepts more effectively to the public. Our target audience is often not health physicists or physical scientists but a reasonably educated audience where the data, concepts, and approaches suggested herein can be useful. As health physicists, it is our nature to try and be as "rigorous" and "precise" as we can with our terminology and mathematical expressions. Trying to be effective communicators of scientific concepts to nonscientists in this manner can often be self-defeating rather than just communicating in a simple and "familiar" manner. For example, although it is suggested that both the international and US units of effective radiation dose [millisieverts (mSv) and millirem (mrem) respectively] are explained, it unnecessary to include in discussions with "the public" equivalences with other larger or smaller units such as Sieverts vs. Rem or microsieverts vs. microrem, which confuse and do not add to understanding of the basic concepts we are attempting to communicate. A similar approach should be used with units of radioactivity present, e.g., picocuries (pCi) vs. the international and/or larger equiveillances such as Becquerels (Bq) or Curies (Ci). The pCi is the only unit the US EPA uses for remedial action soil concentrations in their applications of the LNT described here and is the unit used by US commercial laboratories to report results, so it is already "familiar" to many people. Additionally, nonscientists/engineers are not necessarily familiar with scientific notation using powers of ten (10x, e.g.) and in particular, negative exponents such as 3 × 10-4, but most people can understand that the decimal equivalent, 0.0003, is a very small number. Accordingly, some flexibility in communication is suggested relative to the health physics profession's usual rigorous (and appropriate) application of our professional standards of practice. This paper attempts to present data and rationales for public communication that demonstrate (1) that numerous national and international professional and scientific bodies refute the appropriateness of the LNT "no threshold" model to estimate health effects from very low levels of radiation dose, including within the range of and/or below natural background; (2) "exposure thresholds" exist below which experts believe there is no evidence of measurable health effects; and (3) continued use of the LNT model for purposes of defining safety or "acceptable risk" at very low radiation doses and estimating cancer risks based on the LNT model is contrary to logic and common sense and is potentially detrimental to US society's long term interests.

Computerized radiotherapy chart checking tools have revolutionized the initial physics chart review process as they offer verification of large amounts of plan parameters in seconds and allow physicists to concentrate on high-skill-level items that are challenging for automation. Both commercialized and in-house chart check solutions typically rely on access to the patient data within the live SQL database of the radiation oncology information system (ROS). This is a complex task potentially posing risks to both database integrity and overall system performance when accessed during clinic operation hours. The aim of this study was to develop and test a chart checking tool based on AURA reports that utilize the reporting database to detect and analyze the errors occurring during treatment plan preparation in external beam radiotherapy. An Automated AURA Report-based Chart Checking Tool (AARCCT) was developed using the python-based programming environment in the RayStation treatment planning system (TPS). Following TG-275 recommendations, the tool verifies specific physics check items in TPS plan data and Varian's ARIA ROS. The ARIA data was captured leveraging advanced Physics Summary (AURA) reports. The AARCCT was tested on > 600 patients receiving various modalities of treatment, including 3D-CRT, IMRT and electron treatments. In addition to applying the script to the plans immediately following plan development (i.e., before physics check), it was applied to ∼160 plans already reviewed by medical physicists. The detected errors were assessed with failure mode and effect analysis. The AARCCT was able to analyze over fifty plan parameters in near to real-time. Before physics review, ∼48.6% of plans contained at least one error, largely low severity. The error rate was relatively constant throughout the year of testing. After physics checks were completed, AARCCT detected errors in ∼37.1% of physicists checked plans. Both before and after physics check, the most common errors were related to inaccuracies in patient setup imaging (24%), prescription (5.6%), written directive (6.3%), patient shifts (5.4%) and contours (2.6%). The error occurrence rate across the dosimetry team was found to be between ∼22% to 62% with no correlation to dosimetrist's experience. The relative error occurrence rate across the radiation oncologist (RO) team was found to be ∼40%-60%. The higher error rates were observed in ROs who were either recent hires or who had > 20 years of experience. Across the physics team, the error occurrence rate was ∼22%-47% with higher rates among those with less than three or more than twenty years of experience. The AARCCT was found to be an essential tool to reduce error propagation following manual physics plan checks. The automated nature and omission of live ROS database access uniquely allows for smooth integration of the developed tool into the clinical workflow while minimizing the impact to ROS speed, functionality and security. The tool could also be used for evaluation of staff training and establishing uniformity of practice across the radiation therapy team members to improve quality and operational efficiency.

Quality assurance (QA) in radiation therapy is a critical component of ensuring accurate and consistent patient treatments, but many tasks are time consuming and rely on human visual acuity, which limits their accuracy. We aimed to automate monthly mechanical QA tests, improve measurement accuracy and precision, and decrease inter-user variability using a computer vision-based quality assurance (CVQA) system. A custom marker board incorporating four ArUco markers was created along with a custom camera holder that mounted onto the gantry head. OpenCV was utilized to automate tests for couch translation, collimator and table angles, collimator and table walkout, optical distance indicator (ODI), and field size detection. A GUI was created to guide users through the tests, determine passing status of measurements based on MPPG8.b criteria, and display image captures to allow users to troubleshoot if needed. Reproducibility tests were taken across four days. The system was tested against manual measurements by graph paper or digital level for each test. Field sizes and ODI were read by 12 different physicists to determine human variability and comparisons for CVQA. The CVQA system took 5 min to set up and 7 min to perform all tests. All field sizes, collimator/table angles, collimator/table walkout, and table translations were reproducible within 0.5 mm and 0.5°. ODI measurements were reproducible within 1 mm. Table travel, ODI, and walkout measurements agreed with manual measurements within 0.5 mm and 0.4°, except for vertical table motions that agreed within 0.9 mm due to the lens focus being optimized for the 100 cm SSD plane. The standard deviation between physicists for almost all symmetric and asymmetric jaws was larger than the reproducibility of CVQA. CVQA has been utilized for five years and has demonstrated ability to identify mechanical machine issues. CVQA successfully automates mechanical QA tasks, providing an efficient and precise system. CVQA is open source and freely available for academic institutions. Its adoption can improve workflow efficiency and consistency in clinical environments.

Troubleshooting linear accelerator faults during patient care is time-critical and cognitively demanding. Access to relevant historical information is often slow and experience-dependent. To streamline information retrieval and support decision-making, a TrueBeam troubleshooting chatbot powered by a large language model (LLM) was developed and tested. Troubleshooting records from five TrueBeam linacs over eight years were extracted from an in-house database. After removing non-UTF-8 characters and normalizing formatting, each issue was stored as a structured text file for retrieval. Files were indexed in a GPT-4.1-based environment, with parameters (e.g., temperature, retrieved chunks) iteratively tuned. Performance was evaluated using standardized questions across domains including recall, real-time troubleshooting, aggregation, safety, and temporal filtering. Four physicists scored responses using a predefined rubric. A total of 1394 logs (5.4 MB) were indexed, with indexing completed in 16 min. Mean response time was 7.5 ± 2.5 s. The chatbot performed well in retrieving prior events, summarizing institutional experience, and recognizing when information was unavailable. Performance was largely insensitive to temperature and chunk number, except under severely limited retrieval. Weaknesses included occasional procedural misordering, unclear responsibility between physicists and service personnel, verbosity, and inconsistent temporal filtering. A GPT-4.1-based RAG chatbot can rapidly surface relevant institutional knowledge for linac troubleshooting and may reduce cognitive burden during machine faults. However, important safety and workflow risks remain. Such systems should function as decision-support tools and require explicit guardrails, role definition, and formal risk evaluation prior to broad clinical deployment.

Radiation oncology is central to multidisciplinary cancer care but remains poorly visible to students. Early educational exposure may improve awareness of the discipline and of the professional roles involved in radiotherapy. This study evaluated the short-term educational impact of a case-based school-work orientation program for high school students. Between December 2025 and March 2026, 80 high school students participated in the "Invisible Scalpel" program at Fondazione Policlinico Universitario A. Gemelli IRCCS and Università Cattolica del Sacro Cuore, Rome. The program included 18 h of classroom-based teaching and 12 h of supervised group activities focused on a simulated clinical case. Students explored the roles of radiation oncologists, radiotherapy technicians/radiation therapists, medical physicists, and biomedical engineers. Anonymous pre- and post-program questionnaires were completed by 60 students and analyzed descriptively. Likert scales (1-5) were used to evaluate attitudes towards the discipline. Baseline knowledge of the purpose of radiotherapy was high, but awareness of professional roles, particularly medical physicists and biomedical engineers, was limited. After the program, all students correctly identified radiotherapy as a cancer treatment, 90% reported being informed about the professional roles involved, and correct identification of the radiation oncologist as responsible for treatment prescription increased from 33.3% to 71.7%. Misconceptions regarding radiation visibility and post-treatment radioactivity decreased. The proportion of students considering radiation oncology as a possible future career increased modestly from 11.7% to 16.6%. Program satisfaction was high, with all respondents stating that they would recommend the experience to peers. A case-based, multidisciplinary school-work orientation program was associated with improved knowledge of radiotherapy, reduced misconceptions about radiation safety, and greater awareness of professional roles within the radiotherapy team. Although the short-term effect on career interest was modest, this educational format may represent a feasible model for early exposure to radiation oncology and related healthcare, physics, and engineering careers.

The kagome lattice has long been a subject of fascination for physicists due to its rich physics, encompassing phenomena such as superconductivity, charge density waves, and flat bands. In this work, we report the discovery of a novel ferroelectricity-induced dual-breathing mode in the kagome semiconductor Nb3I8. This dual-breathing mode involves both intralayer and interlayer breathing motions that are driven by the polarization within the layers. We demonstrate that, both theoretically and experimentally, such a breathing pattern will disappear in the absence of ferroelectric polarization in each layer. This discovery not only broadens our understanding of complex interactions within kagome lattices but also paves the way for the development of new types of electronic devices based on ferroelectricity.

Objectives: Our objective was to develop and evaluate a locally trained knowledge-based planning (KBP) model for head and neck (H&N), brain, and central nervous system malignancies using RapidPlan, and to determine whether standard statistical metrics such as the coefficient of determination (R2) and outlier frequency are definitive predictors of clinical utility. Methods: An institutional dataset of 594 plans was retrospectively curated into a 497-plan training set. Performance was evaluated in 370 paired plan comparisons generated with identical beam geometry. Training-validation overlap was explicitly quantified at both plan and patient levels, and a plan-level held-out sensitivity analysis was performed. Additional analyses included monitor units (MUs), subgroup assessment, clinically relevant OAR threshold achievement, and 95% confidence intervals for paired differences. Results: The validation set included 370 plans from 289 patients. At the plan level, 303 validation plans overlapped with the training model, and 67 were held-out cases; at the patient level, no fully patient-independent validation cohort was available. RapidPlan maintained target coverage while reducing OAR doses, including oral cavity Dmean (-7.62%Rx; 95% CI: -8.91 to -6.32; p < 0.001) and larynx Dmean (-7.57%Rx; 95% CI: -9.14 to -6.00; p < 0.001). The same direction of benefit was observed in the plan-level held-out subset. MU did not increase with RapidPlan and decreased from 764.2 &#xb1; 275.5 to 695.8 &#xb1; 210.3 MU (Delta = -68.4 MU; 95% CI: -89.4 to -47.4; p < 0.001). Conclusions: A high R2 was not required for clinically useful optimization objectives in this heterogeneous cohort. However, the retrospective design and patient-level overlap limit claims of full generalizability. The model should therefore be interpreted as a clinically useful standardization and decision-support tool requiring expert review rather than as a replacement for the judgment of physicists and radiation oncologists.

Computational modelling can deepen understanding of topics such as radiotracer pharmacokinetics, internal dosimetry, and decay-chain processes. However, modelling is often regarded as the exclusive domain of medical physicists and is not routinely included in the training of other medical professionals, including those in the radiation sciences such as radiographers, physicians, radiation therapists and nuclear medicine technologists. Using the intuitive bathtub analogy of system dynamics, we facilitate the inclusion of computational modelling in the training of healthcare professionals. Drawing on the example of a 99Mo/99mTc radionuclide generator used in nuclear medicine "hot labs", we illustrate how complex dynamics can be described and modelled through the highly visual, intuitive framework of system dynamics. We then examine the performance of first-year students, on modelling a 99Mo/99mTc generator in an examination question. Parent and daughter activity-time curves generated with system dynamics agree closely with the predictions of the Bateman equations. Student performance in modelling transient equilibrium under examination conditions using system dynamics (bathtub dynamics), demonstrates the accessibility of this approach. The highly visual and intuitive system dynamics approach facilitates modelling of complex processes including multi-compartment dynamics, tracer kinetics, internal dosimetry, and radionuclide generators. This is particularly relevant for students who lack the requisite quantitative training to engage with differential equations. System dynamics is a promising tool for democratising access to computational modelling among trainees and professionals in the radiation sciences. Computer models can help people understand how radioactive medicines behave in the body. This study explored a simple teaching approach that uses the familiar example of a bathtub filling and emptying to help students learn modelling concepts, and tested it using an example from nuclear medicine education. This study found that students were able to use this approach to model complex radioactive decay processes, with results that closely matched established scientific methods. This matters because it could help a wider range of healthcare students and professionals learn important modelling skills without needing advanced mathematics.

An increasing discrepancy between the measured reference air kerma rate (RAKR) of high-dose-rate (HDR) iridium-192 (192Ir) sources and that reported by the manufacturer on the source certificate was observed at a hospital in Australia. This study aimed to determine whether the drift recorded in a single clinic was a local anomaly or more widespread. A survey was distributed to physicists at brachytherapy clinics across Australia, New Zealand, the United Kingdom (UK), France, and Ireland, gathering details on HDR 192Ir source model and origin, well chamber model, well chamber calibration provider, and each department's history on the discrepancy between locally measured and manufacturer's source certificate RAKR. Data from each clinic was assigned to a separate series, with an additional series if a clinic changed well chamber calibration provider. Linear regression analysis was performed on data from each series. One thousand one hundred fifty observations from 32 clinics were analyzed, with RAKR measurement histories ranging from 2 to 20 years (mean, 9 years). The manufacturer of all sources included in this analysis was Curium. A trend of increasing local measurement value compared with the manufacturer certificate value was observed for all series, with 20 or more observations. Sites with well chambers calibrated at NPL or UWADCL showed an increase in discrepancy between measured and source certificate RAKR, approximately 0.2% per year on average, from 2015 to present. There is an increasing discrepancy between locally measured 192Ir HDR source strength compared with the manufacturer's certificate. The manufacturer's measurement procedure does not meet the same standard set for the user. Unless the agreement between the Curium and user measurements can improve, brachytherapy societies may need to re-examine the requirement for direct comparison between local and manufacturer's measurements.

Magnetic resonance imaging (MRI) for radiation therapy treatment planning is currently being used in many anatomical sites to better visualize soft tissue landmarks, a technique known as an MRI simulation. A core component of modern MRI simulation configurations are the use of external laser positioning systems (ELPS) to help set up the patient. Though necessary for accurate and reproducible patient setup, the ELPS, if left on during imaging, may interfere negatively with image quality due to leaking electronic noise, of which MRI is sensitive to. It is currently unknown whether this leakage of electronic noise may further affect quantitative values derived from clinically employed relaxometric, diffusion, and fat fraction sequences. Therefore, in this study, we aim to characterize the impact of MRI simulation lasers on general image quality and quantitative imaging accuracy. First, a cine acquisition was used to visualize the real-time changes in image signal-to-noise ratio (SNR) from when the ELPS was deactivated to activated. To validate this effect quantitatively, the SNR was measured using the American College of Radiology (ACR) recommended T1-weighted protocol in a homogeneous phantom with the integrated body, 18-channel UltraFlex small, 18-channel UltraFlex large, 32-channel spine, and 16-channel shoulder coils. Next, a geometric distortion algorithm was tested in two vendor-provided phantoms while using the integrated body coil and the ACR Large Phantom protocol was tested. Finally, a series of quantitative MRI scans were performed using a CaliberMRI Model 137 Mini Hybrid phantom to validate quantitative T1, T2, and ADC while a Calimetrix PDFF-R2* phantom was used for quantitative PDFF and R2*. All scans were performed with both the ELPS both deactivated and activated. Visible electronic noise artifacts were seen when using the integrated body coil when the ELPS was activated on the cine acquisition which led to a two-fold decrease in SNR using the ACR protocol, however geometric distortion quantification was not affected. This SNR drop was not seen when using the remaining tested coils. Degradation in image intensity uniformity, percent signal ghosting, and low contrast object detectability was seen during ACR Large Phantom testing using the 20-channel Head/Neck coil. Concordance across quantitative MRI values was similar when the ELPS was both deactivated and activated while a consistent increase in standard deviation inside the ADC vials was seen when the ELPS was activated. The extra noise induced from the activation of the ELPS during imaging should be avoided due to its potential to unnecessarily increase image noise. This is particularly true when conducting mandatory quality assurance testing for image quality and geometric distortion which utilize the integrated body coil which is most susceptible to ELPS-induced noise. Clear clinical guidelines should be implemented to make this issue known to the MRI technologists, physicists, and other relevant staff using an MRI with a supplementary ELPS for patient alignment.

Electronic medical devices (EMDs) must be carefully managed in radiation oncology to prevent radiation-induced malfunction. Only one EMD, cardiovascular implantable electronic devices (CIEDs), currently has a recommended protocol for clinical management. This international survey aims to improve understanding of the current state of EMD management for CIEDs and six other EMDs. Characterizing the current state of EMD management is a crucial step towards the development of additional protocols. This survey was distributed to more than 2500 physicists via email. The survey consisted of multiple-choice, short-answer, and matrix-style questions addressing many topics, including the desire for guidance, frequency of EMD observance, existence of current policies, documentation and training regarding current policies, allowance of devices in primary beams, discouragement of neutron-producing energies and hypofractionation, estimation of cumulative dose, access to specialists for consultation, and difficulties experienced in implementing current protocols. A total of 258 completed responses were collected representing a variety of clinical perspectives. Responses demonstrated a community desire for additional guidance, with 69% of respondents indicating that their clinic would benefit from additional guidance regarding six non-CIED devices. A lack of institutional policies was also observed for these devices, with 73% of respondents indicating that their clinic lacks institutional policies. Among the policies that do exist for these devices there is considerable variability. This study demonstrates both a need and a desire for additional guidance regarding the clinical management of patients with EMDs in radiotherapy. This desire is reflected in the lack of institutional policies addressing EMDs and the variability among the policies that do exist.

Management of second ipsilateral breast cancer events (iBCEs) remains controversial, and there is a need to collate existing evidence and international guidance on patient selection and local treatment strategies. This project, endorsed by US and European surgical and radiation oncology societies, aimed to gather expert consensus on these issues. A questionnaire on second iBCE local treatment was developed and reviewed by a core group of eight experts, and Delphi methodology was applied over two rounds to 36 panellists, including radiation oncologists, breast surgeons, a plastic surgeon, and medical physicists. Consensus was predefined as agreement of 75% or higher. After two rounds, consensus was reached for 78 (80%) of 97 items. Panellists agreed that patient preferences are central to decision making (100%) and that a second breast-conserving therapy represents a reasonable option for selected patients (100%). Criteria associated with greater suitability for second breast-conserving therapy included an interval between surgeries of at least 60 months, low-risk accelerated partial breast irradiation classification, luminal molecular profile, and no grade 3 late toxicity related to the first breast-conserving therapy. HER2 (also known as ERBB2)-positive or triple negative subtypes were not viewed as absolute contraindications. Strong consensus was also observed regarding the importance of tumour-to-breast volume ratio, clear surgical margins, and tumour bed reirradiation. For patients undergoing mastectomy, immediate autologous reconstruction was preferred (94%) over implant-based approaches (75%). This international Delphi consensus offers structured guidance for the local management of second iBCE and supports shared decision making and individualised treatment planning.

Background Diagnostic reference levels (DRLs) and achievable doses (ADs) are intended to reflect contemporary CT practice, but national benchmarks are updated infrequently. Purpose To update U.S. national adult CT DRLs and ADs derived from 2025 data and to demonstrate a scalable, acquisition-level, size-normalized benchmarking framework for generating timely and clinically relevant national benchmarks. Materials and Methods This retrospective observational study analyzed adult CT acquisitions performed between January 1 and December 31, 2025, across U.S. facilities using the Imalogix radiology optimization platform. The 10 most common adult CT examination categories, matching the 2014 benchmark study, were mapped using standardized RadLex Playbook identifiers. Dose metrics (volume CT dose index [CTDIvol] and dose-length product [DLP]) were extracted from dose structured reports and normalized at the acquisition level. Patient size was quantified using attenuation-based water-equivalent diameter from axial images with automated truncation correction, and size-specific dose estimates (SSDE) were calculated using standardized American Association of Physicists in Medicine task group methods. ADs and DRLs were calculated as the 50th and 75th percentiles, respectively, of facility-level median dose distributions per International Commission on Radiological Protection Publication 135 and compared with 2014 U.S. benchmarks. Results A total of 5&#x2009;234&#x2009;285 CT acquisitions performed in 2&#x2009;802&#x2009;416 adults (mean age, 58.1 years &#xb1; 19.7 [SD], 1&#x2009;575&#x2009;029 female) at 592 U.S. facilities were analyzed, representing a nearly fourfold larger sample than the 2014 study. Relative to 2014, national CTDIvol ADs and DRLs decreased by 9.3% and 21.8%, respectively. The largest reductions were observed for chest examinations with contrast material (31.2%), whereas smaller reductions were observed for head examinations without contrast material (3.5%). Dose metrics demonstrated consistent size dependence across all torso examinations. Conclusion U.S. adult CT radiation doses have decreased substantially over the past decade. This acquisition-level, size-normalized methodology enables near-real-time generation of national DRLs and ADs for modern CT dose benchmarking. &#xa9; RSNA, 2026 Supplemental material is available for this article. See also the editorial by McCollough in this issue.

Our objective is to investigate a novel knowledge-based planning model that utilizes the newly developed dense U-Net architecture to predict three-dimensional (3D) dose distributions in patients with head and neck cancer. We utilized data published by the American Association of Physicists in Medicine Institute, which includes treatment plans for 340 patients with head and neck cancer who were treated using intensity modulated radiotherapy treatment with a prescribed dose of 70 Gy. The data were divided into three subsets, and the proposed dense U-Net was applied to predict full volumetric dose distributions. Model performance was evaluated using the mean absolute error (MAE) between predicted and clinical doses across all subsets. The MAE between the reference and predicted dose distributions for the training, validation, and testing datasets was 1.60 Gy, 3.09 Gy, and 3.14 Gy, respectively. The mean absolute dose error was measured at 1.53 Gy in the brainstem, 3.43 Gy in the left parotid, 3.29 Gy in the right parotid, 2.05 Gy in the spinal cord, 2.40 Gy in the esophagus, 3.81 Gy in the mandible, 3.35 Gy in the larynx, 1.56 Gy in planning target volume (PTV70), 1.82 Gy in PTV63, 1.91 Gy in PTV56, and 3.14 Gy in the body contour for the testing data. The proposed framework enabled rapid generation of complete 3D dose distributions for each patient's plan in a few seconds, demonstrating strong potential to accelerate clinical workflows. The proposed dense U-Net model demonstrated proficiency in accurately predicting dose distributions for the head and neck region, ensuring consistent quality.

Size-specific dose estimate (SSDE) uses linear dimensions measured on a computed tomographic (CT) image to scale the scanner-reported volumetric computed tomography dose index (CTDIvol) and thereby estimate dose. The objectives of this retrospective observational study were to evaluate whether the American Association of Physicists in Medicine (AAPM) geometric size metrics for abdominal CT, when implemented using canine-specific size measurements, correlate with water-equivalent diameter (Dw) in canine patients and to compare institutional SSDEs with human benchmarks. Abdominal CT scans from 30 dogs across three body weight categories (<10, 10-30, and >30&#xa0;kg) were analyzed. The relationships between effective diameters calculated using four geometric metrics-dorsoventral dimension (DV), lateral dimension (LAT), the sum of DV and LAT, and the square root of their product-and Dw, which incorporates both size and attenuation, were analyzed using linear regression. The strongest correlation with Dw was observed for the combined DV and LAT metrics (R2 0.94, p&#xa0;<&#xa0;0.001). The displayed CTDIvol underestimated SSDE by 50%. The 75th percentile of the SSDE for a single-phase, pre-contrast abdominal examination was 21&#xa0;mGy, two to four times higher than the US human dose reference level. In conclusion, geometric size metrics measured from a single CT image were in close agreement with attenuation-based SSDE (Dw) for canine abdominal CT scans, supporting the feasibility of applying the AAPM SSDE estimation method to canine abdominal CT imaging. These findings demonstrate the importance of incorporating patient size into CT dose estimation and suggest that institutional SSDE values may warrant dose optimization in veterinary abdominal CT practice.

Artificial Intelligence-based radiomics models for thyroid ultrasound (US) often lack interpretability, limiting clinical trust. This study develops and evaluates an interpretable radiomic feature (RF) framework for thyroid-nodule classification by linking quantitative-US features to the Thyroid-Imaging-Reporting-and-Data-System (TI-RADS) semantic lexicon through a clinically grounded radiomics dictionary. A radiomics dictionary was constructed to map TI-RADS categories, including composition, echogenicity, shape, margin, and echogenic foci, to Image-Biomarker-Standardization-Initiative-compliant RFs extracted from two-dimensional-US images. Relationships were defined through expert consensus (four physicians, three physicists, one radiology expert, one biologist) and further examined using Shapley-Additive-Explanations (SHAP) as a model-based interpretability analysis. Three multicenter datasets were combined, yielding 5,542 nodules, from which 107-RFs were extracted using PyRadiomics and normalized with min-max scaling. Twenty-seven feature-selection methods were paired with twenty-five classifiers and evaluated using stratified five-fold cross-validation on 70&#xa0;% of the data, followed by evaluation on a held-out multicenter testing set comprising the remaining 30&#xa0;% for benign-versus-malignant nodule classification. Robust model selection employed a stability-aware-composite-scoring framework combining mean performance and variability across accuracy, precision, recall, F1-score, and Receiver-Operating-Characteristic-Area-Under-the-Curve (ROC-AUC). The dictionary enabled direct interpretation of radiomic signatures in TI-RADS terms. The Select-From-Model (logistic regression) plus Extra-Trees classifier achieved strong testing performance (ROC-AUC:0.941&#xa0;&#xb1;&#xa0;0.004). SHAP identified texture heterogeneity as the dominant malignancy signal, with Gray Level Run Length Matrix non-uniformity, intensity dispersion, and kurtosis aligning predictions with high-risk TI-RADS descriptors. This study introduces an interpretable radiomics dictionary and stability-aware model selection framework, addressing interpretability limitations and enabling transparent thyroid nodule risk stratification from US.

Photon-counting detector CT (PCD-CT) is moving from laboratory development to clinical deployment. However, its threshold-bin data arise from a tightly coupled detector-readout chain that can be difficult to understand as a whole. These data are not a direct readout of photon energy, but the outcome of a sequence of physical and electronic processes that begins with x-ray interaction and charge creation and ends with threshold decisions applied to processed electrical pulses. Understanding this chain is essential for interpreting detector behavior, evaluating performance, and identifying the origins of spectral distortion, count loss, and instability under clinical operating conditions. This primer presents a physics-grounded framework for semiconductor photon-counting detectors in CT by organizing the discussion around a single causal chain: energy deposition, charge creation, charge transport, signal induction, pulse formation, and final event counting and multi-threshold energy binning. Within this framework, we show how charge sharing, detector pixel geometry, dead time, pileup, dark current, contact-controlled leakage, and operating conditions shape spectral response, count-rate performance, threshold stability, and reproducibility at clinical flux. By linking detector physics, waveform formation, threshold logic, contact physics, operating conditions, and practical performance characterization within one coherent framework, this primer aims to give medical physicists and imaging researchers a scientifically rigorous and operationally useful understanding of how photon-counting CT detectors work and what governs their&#xa0;performance.

This study aimed to identify the methods currently used to evaluate fetal dose in pregnant patients undergoing radiotherapy, the strategies implemented to optimize fetal exposure, and the fetal dose ranges reported in the literature. A systematic review was conducted and complemented by a survey. Data related to fetal-dose assessment, optimization approaches, and reported fetal-dose levels were extracted and analyzed. Seventy-eight studies were included in the systematic review, and twelve clinical cases were collected through the survey. In the literature, fetal-dose evaluation most frequently relied on measurements performed in anthropomorphic phantoms using passive dosimeters and ionization chambers. Among published clinical case reports, in-vivo dosimetry was commonly implemented to monitor fetal exposure. Several strategies were found to substantially reduce fetal dose, including the use of shielding blocks, flattening-filter-free beam modes instead of flattened beams, and collimator-angle optimization. Overall, most estimated fetal doses were well below 100&#xa0;mGy, regardless of tumor site or treatment technique. The lowest fetal doses were reported with proton pencil beam scanning, while optimized IMRT and VMAT plans achieved fetal exposures comparable to those obtained with 3DCRT. This systematic review and survey provide a comprehensive overview of current fetal-dose assessment methods and optimization strategies in radiotherapy. The lack of up-to-date recommendations adapted to modern radiotherapy highlight the need for practical guidance. As part of the SONORA project, the development of a dedicated leaflet will support medical physicists by providing structured, practical recommendations to ensure safer and more consistent management of radiotherapy during pregnancy.