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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.

Pleural disseminated thymic tumors are therapeutically challenging due to their complex target volumes and the need to preserve lung function. This retrospective study aimed to compare the dosimetric parameters of helical tomotherapy (TOMO), volumetric modulated arc therapy (VMAT), and dynamic multileaf collimator intensity-modulated radiotherapy (DMLC-IMRT) for the treatment of pleural disseminated thymic tumors, focusing on target coverage and organ at risk (OAR) sparing, particularly the lungs. Twenty patients requiring ipsilateral whole-pleural irradiation were enrolled. Three distinct radiotherapy plans (TOMO, VMAT, and DMLC-IMRT) were designed for each patient and collaboratively evaluated by radiation oncologists and medical physicists. Dosimetric parameters for the planning target volume (PTV) and OARs, including the lungs, spinal cord, heart, esophagus, liver, and whole body, were compared. The optimal plan for each technique was selected for dosimetric comparison. All enrolled patients ultimately underwent TOMO-based radiation treatment planning. TOMO demonstrated superior PTV coverage (95.12%&#x202f;&#xb1;&#x202f;2.76%) compared with VMAT and DMLC-IMRT (p&#x202f;< 0.0001). TOMO also demonstrated better control of hotspots and dose gradients outside the target area. For OARs, TOMO significantly reduced the mean dose and V5, V10, and V20 values for the ipsilateral and total lungs compared with VMAT and DMLC-IMRT (p&#x202f;< 0.05). Specifically, the ipsilateral lung V20 was reduced by more than 12% (TOMO: 60.15%&#x202f;&#xb1;&#x202f;16.21%; VMAT: 72.61%&#x202f;&#xb1;&#x202f;20.26%; DMLC-IMRT: 72.03%&#x202f;&#xb1;&#x202f;18.82%), and the contralateral lung V5 was reduced by 11% (TOMO: 34.07%&#x202f;&#xb1;&#x202f;24.35%; VMAT: 45.91%&#x202f;&#xb1;&#x202f;25.88%; DMLC-IMRT: 44.57%&#x202f;&#xb1;&#x202f;21.63%). The mean lung dose with TOMO was 13.45&#x202f;Gy, with V20 < 30% and V5 < 65%, meeting stringent lung-sparing criteria. No significant differences were observed in the dose to other OARs between the 3 techniques. For the treatment of pleural disseminated thymomas, TOMO offered significant dosimetric advantages over VMAT and DMLC-IMRT in terms of target coverage and protection of the lungs. These differences could be clinically meaningful, with the potential to reduce the risk of radiation pneumonitis, a critical consideration in thoracic radiotherapy. Therefore, we recommend TOMO as the first-line clinical approach in these cases, with further studies required to validate long-term clinical outcomes.

Identifying and classifying quantum phases from measurable time series in many-body dynamics have significant values, yet lack details and face formidable challenges, requiring the profound knowledge of physicists. Here, to achieve a purely data-driven machine intelligent classification, we introduce a temporal fluctuation-amplified distance measure that captures the inherent temporal fluctuation complexity of dynamic evolution series in different quantum many-body phases. Significantly, the introduction of complexity-powered distance leads to remarkable improvements of unsupervised manifold learning of quantum many-body dynamics, as exemplified in models such as the discrete time crystal (DTC) and Aubry-Andr&#xe9; (AA) models. Our method does not require any prior knowledge and exhibits effectiveness even in imperfect, disordered, and noisy situations that are challenging for human scientists. Successful classification of dynamic phases in many-body systems holds the potential to enable crucial applications, including identification of tsunamis, earthquakes, catastrophes, and future trends in finance.

Spontaneous collapse models (SCM) employ an imaginary noise term in the modification of Schr&#xf6;dinger's equation in order to achieve a stochastic collapse process. Such noise term is typically assumed to be white, and therefore uncorrelated in time, which results in the dynamics being Markovian. In the first part of this paper I discuss the reasons why physicists are exploring the possibility to instead employ non-white stochastic noise terms in the dynamics of SCM, and I then briefly introduce these models. In the second part, my aim is to provide an evaluation of the major conceptual and philosophical consequences of the generalised collapse models with colored noise. In particular, I will focus on the broad class of implications having to do with the non-Markovian nature of the dynamics, with its resulting temporal non-locality, and on the possibility to consider the noise field as a real physical entity.

The aim of this study was to establish an optimal treatment strategy for functional liver-sparing radiotherapy by incorporating technetium-99&#xa0;m galactosyl human serum albumin (99mTc-GSA) single-photon emission computed tomography (SPECT) into radiotherapy planning for recurrent hepatocellular carcinoma (rHCC). Three irradiation techniques-volumetric-modulated arc therapy (VMAT), intensity-modulated radiotherapy (IMRT), and three-dimensional conformal radiotherapy (3D-CRT)-were systematically compared. Six patients with rHCC who underwent stereotactic body radiotherapy (SBRT) were included. Eligible patients had previously received SBRT to a different hepatic segment and had undergone 99mTc-GSA SPECT before the current course of radiotherapy. For treatment planning, planning computed tomography (CT) images were rigidly registered with 99mTc-GSA SPECT images, and functional liver regions were manually contoured by radiation oncologists. Using identical functional liver contours, three treatment plans-VMAT, IMRT, and 3D-CRT-were independently generated by medical physicists. The prescribed dose was 40&#xa0;Gy, delivered in four fractions. These treatment plans were retrospectively created for research purposes and were separate from actual clinical treatments. Under identical planning target volume dose-coverage conditions, the dose-volume histogram indices (V2-V40) of the functional liver were compared among the three techniques. VMAT consistently demonstrated the best preservation of functional liver regions, particularly in the low-dose range, followed by IMRT and 3D-CRT. These findings demonstrate the feasibility of 99mTc-GSA SPECT-guided function-avoidance radiotherapy planning for the re-irradiation of rHCC and suggest that VMAT provides an optimal balance between target coverage and functional liver preservation.

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.

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.

Gossip protocols propagate information through peer-to-peer networks analogously to epidemic spreading, yet this analogy has remained informal. Here, we formalise it for blockchain consensus by means of a phase-encoding under which the dynamics reduce, at leading order and in a weak-coupling regime, to coupled-oscillator synchronisation on complex networks. Block preferences correspond to oscillator phases, communication latencies to natural frequencies, and network topology to the coupling graph. The resulting order parameter (a synchronisation measure from statistical physics) tracks simulated network consensus with a correlation of [Formula: see text] and represents it as a phase transition. Consensus disruptions then appear as phase-coherence disturbances, providing candidate anomaly signals for node isolation, network partitions, and block withholding (three typical attacks on blockchains). On real blockchain data, where continuous phase dynamics are not observable, we construct a static phase proxy from per-pool block-attribution statistics; applied to Bitcoin, this proxy-based detector identifies the 2013 chain fork at [Formula: see text] significance on unmodified data. Validation on a second protocol family confirms that the phenomenology generalises. This framework expands physicists' reach into adversarial systems, provides epidemic modellers with an empirical testbed, and offers blockchain operators a complementary, consensus-layer anomaly signal.

Accurate heterogeneity correction in high-precision radiotherapy relies on precise computed tomography (CT) number-to-density conversion via the Hounsfield unit look-up table (HLUT). While physical properties of tissue-equivalent materials are generally assumed consistent with manufacturer specifications, an independent audit identified clinically significant density discrepancies in commercially available lung-equivalent phantom inserts. This study evaluates the physical properties of nonconforming lung inserts through mass measurements and stoichiometric analysis, and assesses the clinical dosimetric impact of the associated density discrepancies. Five lung-inhale inserts manufactured in 2010, 2015, and 2024 (10A, 10B, 15A, 15B, and 24A) were analyzed. Mass and physical dimensions were measured in triplicate using a precision balance (1&#xa0;mg resolution) and vernier calipers. Stoichiometric analysis was conducted using reference materials to evaluate the tissue-equivalence of the inserts and quantify deviations from the theoretical baseline. A nonconforming table and a conforming reference table (RT) were established, derived from inserts 10A and 24A, respectively. For clinical impact assessment, volumetric modulated arc therapy (VMAT) plans for three clinical cases involving centrally located lung tumors (utilizing both inspiration breath-hold (IBH) and free-breathing) were optimized for stereotactic body radiotherapy (SBRT) and recalculated with the RT using the Acuros XB algorithm. Differences in gross tumor volume (GTV) mean dose and planning target volume (PTV) D95% were evaluated to quantify the dosimetric consequences. The 2010 inserts (10A and 10B) exhibited a 17.1% mass reduction and lower CT numbers compared to the reference 24A insert. Dimensional variations were negligible (&#x2264; 0.2&#xa0;mm) across all samples. Clinical recalculation revealed maximum dose reductions of 2.1% for the GTV mean dose and 3.0% for the PTV D95% in the worst-case scenario. These errors exceed the 2% clinical tolerance, propagated by HLUT interpolation across the low-density range. Substantial inter-lot density variations in commercial calibration phantoms can lead to dosimetric errors that exceed established clinical limits, particularly for centrally located tumors treated with IBH. Medical physicists must not implicitly rely on nominal manufacturer values; independent audits and initial mass screening at acceptance are highly recommended for maintaining dose calculation accuracy.

We present the updated recommendations from the Soci&#xe9;t&#xe9; fran&#xe7;aise de radioth&#xe9;rapie oncologique (SFRO, the French society for radiation oncology) regarding radiation dose constraints for organs at risk in adult patients, with the aim of supporting clinical decision-making in contemporary radiotherapy practice. These guidelines address a wide range of clinical scenarios, including normofractionation, hypofractionation, stereotactic radiotherapy, and reirradiation. Dose constraints are essential to ensure both the safety and efficacy of radiotherapy, especially with the growing use of advanced techniques such as intensity-modulated radiotherapy and stereotactic body radiotherapy. However, given the wide range of existing dose constraints and the lack of harmonization across different practices, this work aims to provide a unified and updated framework adapted to modern radiotherapy techniques. Moreover, many of these constraints are still based on data derived from three-dimensional conformal radiotherapy, which necessitates cautious application when extrapolated to more advanced techniques. Clinical judgment remains crucial, particularly in complex cases such as re-irradiation or treatments using altered fractionation schedules. These updated consensus aim to provide a practical and evidence-based framework to help radiation oncologists and medical physicists minimize the risk of toxicity to normal tissues. By consolidating and adapting current knowledge to modern radiotherapy techniques, they serve as a useful tool in daily clinical practice.

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&#x2009;&#xd7;&#x2009;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.

MRI is the modality of choice for detection, characterization, and noninvasive diagnosis of focal liver observations. It offers excellent tissue contrast using multiple sequences and postcontrast multiphasic imaging. However, its diagnostic accuracy depends on appropriate selection of pulse sequences and imaging parameters. Poorly acquired images or suboptimal sequence parameter selection can lead to medical errors, such as missed lesions and inaccurate characterization of focal liver observations. A solid understanding of applied MRI physics can help optimize image quality and prevent such errors. In this educational review, the authors aim to (a) guide radiologists in assessing MRI quality, (b) promote effective communication using appropriate terminology when collaborating with technologists and medical physicists, and (c) establish a reference liver MRI protocol. First, they detail metrics of MRI quality-contrast-to-noise ratio, spatial resolution, and signal-to-noise ratio-along with the impact of key technical parameters on acquisition time and step-by-step guidance for improving image quality. Second, they review the range of pulse sequences used in liver MRI, discussing their respective strengths and limitations in achieving optimal imaging quality. Third, they address key ancillary considerations for performance of liver MRI, including fat suppression techniques, respiratory motion suppression strategies, and acceleration methods. &#xa9;RSNA, 2026 Supplemental material is available for this article.

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.

Biologists and physicists have a rich tradition of modeling dynamics of living systems with simple models composed of a few interacting components. Despite the remarkable success of this approach, it remains unclear how to use such finely tuned models to study complex biological systems composed of numerous heterogeneous, interacting components. One possible strategy for taming this biological complexity is to embrace the idea that many biological behaviors we observe are "typical" and can be modeled using random systems that respect biologically motivated constraints. Here, we review recent works showing how this approach can be used to make close connection with experiments in biological systems ranging from neuroscience to ecology and evolution and beyond. Collectively, these works suggest that the "random-with-constraints" paradigm represents a promising new modeling strategy for capturing experimentally observed dynamical and statistical features in high-dimensional biological data and provides a powerful minimal modeling philosophy for biology.

I pose the epistemological question of what makes the transfer of statistical approaches across disciplines, specifically between physics and biology, legitimate and fruitful despite intrinsic differences in their objects of study - a problem that resurfaces in contemporary interdisciplinary research relying on machine learning for statistical model building. I address it through the historical reconstruction of pivotal steps in the development of statistical thinking in the 19th century, where the appeal to the mathematical formalism of the Gaussian distribution acted as the visible trace of the diffusion of statistical approaches from astronomy to biological and social sciences. My analysis positions the wide-reaching, nowadays accepted applicability of statistics as something historically acquired through gradual conceptual and technical elaboration. It expounds the forms of re-sanctioning that accompanied and enabled the cross-domain transfer of the statistical approach, articulating them in terms of re-interpretation of the mathematical descriptions involved, re-formulation of the underlying assumptions, and re-conceptualization of their theoretical status and foundations from theory-related abstractions to approximations. The latter culminated in a shift of attitude that led to perceiving, as is standard nowadays, statistical mathematical descriptions as convenient tools for quantitative analysis, further legitimating and accelerating their interdisciplinary transfer. This work aims to familiarize historians and philosophers of science, as well as physicists, mathematicians and biologists with an interest in the history of their discipline, with these key episodes, and to dissect the epistemological assumptions and implications, as well as the interpretive frameworks, at stake in the application of a statistical approach across disciplines.

The American Association of Physicists in Medicine Task Group 307 (AAPM TG-307) recommends validation of electronic portal imaging device (EPID) patient-specific quality assurance (PSQA), including verification of measured and calculated components. This study established a TG-307-aligned commissioning and benchmarking framework for non-transit EPID pre-treatment PSQA. Fraction Zero Absolute Dose (FZAD) was commissioned on two TrueBeam linear accelerators equipped with amorphous silicon (aS) aS1000 and aS1200 EPIDs across flattened and flattening filter-free (FFF) photon beams (6MV/10MV) and two multi-leaf-collimator models. EPID performance was characterised for dose-rate linearity. Independent validation of measured and predicted dose components was performed using ion chamber, phantom-based, and treatment planning system dose planes in geometry replicating EPID configuration. System performance was benchmarked against Portal Dosimetry (PDIP) and phantom-based PSQA across >800 clinical fields. Error-detection sensitivity was evaluated using receiver operating characteristic (ROC) analysis of externally supplied audit plans. The aS1200 panel was linear across dose-rate and source-to-imager distance (SID) conditions, whereas the aS1000 exhibited saturation for FFF beams at shorter SIDs, with up to 5% under-response, with linearity restored at &#x2265;150&#xa0;cm SID. Independent component validation achieved mean gamma pass rates &#x2265;97% (3%/2&#xa0;mm). Bland-Altman analysis showed concordance within 95% limits of agreement, supporting equivalence in clinical decision-making. Sensitivity testing demonstrated discrimination at 2%/2&#xa0;mm (area under ROC curve of 0.886), with improved detection compared to phantom-based PSQA at high specificity. A TG-307-aligned framework enables component-level interpretability and actionable insight for tolerance definition and model optimisation of EPID PSQA.

Radiopharmaceutical therapy (RPT) is a multidisciplinary treatment increasingly integrated within both radiation oncology and nuclear medicine departments. Dosimetry is an emerging aspect of RPT clinical practice that can inform prognosis and treatment decisions and facilitate more personalized care. Establishing an institutional RPT dosimetry program requires coordination across clinical, technical, and administrative teams to enable patient-specific absorbed dose calculations. This report summarizes the University of Wisconsin's experience in developing and operationalizing a multidisciplinary clinical RPT dosimetry program, leveraging the strengths of radiation oncology and nuclear medicine physicians, medical physicists, and staff, and offering a practical framework for other institutions. The program was designed through collaboration among radiation oncology, nuclear medicine, medical physics, radiation safety, and nuclear pharmacy. Core elements include quantitative single-photon emission computed tomography/computed tomography imaging, multitimepoint image registration, voxel-level Monte Carlo dose calculation, and structured multidisciplinary patient review. Standardized quality assurance processes were implemented to ensure accuracy and reproducibility. A billing model was incorporated to streamline authorization and cost recovery among stakeholders. The University of Wisconsin experience demonstrates that multitimepoint RPT dosimetry is feasible and can be integrated into routine clinical workflows with appropriate infrastructure, interdepartmental coordination, and leadership support. Utilizing the expertise of multiple departments is key to an effective program. Early engagement of stakeholders, harmonized imaging protocols, and streamlined data management are critical to success. Broader adoption may be facilitated with the development of standardized reimbursement models, national quality assurance standards, and educational efforts to prepare radiation oncology and nuclear medicine teams for patient-specific RPT care.