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Diagnosis, management, and follow-up of upper tract urothelial carcinoma: an interdisciplinary collaboration between urology and radiology

Upper tract urothelial carcinoma (UTUC) is a common and lethal malignancy. Patients diagnosed with this illness often face invasive workups, morbid therapies, and prolonged post-operative surveillance. UTUC represents approximately 5–10% of urothelial malignancies in the United States and affect 4600–7800 new patients annually. Various environmental exposures as well as smoking have been implicated in the development of UTUC. The diagnosis and workup of UTUC relies on heavily on imaging studies, a close working relationship between Urologists and Radiologists, and invasive procedures such as ureteroscopy. Treatments range from renal-sparing endoscopic surgery to radical extirpative surgery depending on the specific clinical situation. Follow-up is crucial as UTUC has a high recurrence rate. Here we review the epidemiology, diagnosis, management strategies, and follow-up of UTUC from an interdisciplinary perspective.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Future Plans of the ATLAS Collaboration for the HL-LHC

These proceedings report the current plans to upgrade the ATLAS detector at CERN for the High Luminosity LHC (HL-LHC). The HL-LHC is expected to start operations in the middle of 2026, aiming to reach an ultimate peak instantaneous luminosity of \(7.5\times 10^{34}~\hbox {cm}^{-2}~\hbox {s}^{-1}\) , corresponding to approximately 200 inelastic proton–proton collisions per bunch crossing, and to deliver over a period of twelve years more than ten times the integrated luminosity of the large hadron collider (LHC) Runs 1–3 combined (up to \(4000\,\text{ fb }^{-1}\) ). This is a huge challenge to all sub-systems of the detector which will need extensive upgrades to allow the experiment to pursue a rich and interesting physics programme in the future.

Physics↗

Collaborative and Reproducible Research: Goals, Challenges, and Strategies

Combining imaging biomarkers with genomic and clinical phenotype data is the foundation of precision medicine research efforts. Yet, biomedical imaging research requires unique infrastructure compared with principally text-driven clinical electronic medical record (EMR) data. The issues are related to the binary nature of the file format and transport mechanism for medical images as well as the post-processing image segmentation and registration needed to combine anatomical and physiological imaging data sources. The SiiM Machine Learning Committee was formed to analyze the gaps and challenges surrounding research into machine learning in medical imaging and to find ways to mitigate these issues. At the 2017 annual meeting, a whiteboard session was held to rank the most pressing issues and develop strategies to meet them. The results, and further reflections, are summarized in this paper.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

The application of radiochronometry during the 4th collaborative materials exercise of the nuclear forensics international technical working group (ITWG) [Radiochronometry in the CMX-4 exercise]

In a recent international exercise, 10 international nuclear forensics laboratories successfully performed radiochronometry on three low enriched uranium oxide samples, providing 12 analytical results using three different parent-daughter pairs serving as independent chronometers. The vast majority of the results were consistent with one another and consistent with the known processing history of the materials. In general, for these particular samples, mass spectrometry gave more accurate and more precise analytical results than decay counting measurements. Additionally, the concordance of the 235 U– 231 Pa and 234 U– 230 Th chronometers confirmed the validity of the age dating assumptions, increasing confidence in the resulting conclusions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An interlaboratory collaboration to determine consensus 231 Pa/ 235 U model ages of a uranium certified reference material for nuclear forensics

Application of the 231 Pa/ 235 U radiochronometer for nuclear forensic investigations is challenged by a lack of certified reference materials with 231 Pa/ 235 U model purification dates. The Japan Atomic Energy Agency, Los Alamos National Laboratory, and Lawrence Livermore National Laboratory completed an interlaboratory study measuring 231 Pa/ 235 U model ages of New Brunswick Laboratory CRM U100. Results from independent laboratories were combined to calculate a consensus 231 Pa/ 235 U model purification date for CRM U100 of March 26, 1959 ± 237 days. This 231 Pa/ 235 U consensus date for CRM U100 may be used by the nuclear forensic community for quality control of 231 Pa/ 235 U radiochronometry measurements of unknown materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Collaborative Study for Certification of Trace Elements in Uranium Ore Concentrate CRMs UCLO-1, UCHI-1, and UPER-1

Trace impurity patterns are important nuclear forensic signatures in uranium ore concentrates (UOCs) and Certified Reference Materials (CRMs) are used to validate the analysis methods employed by end users. Herein, we discuss the certification campaign for three new UOC CRMs from the National Research Council Canada: UCLO-1 (https://doi.org/10.4224/crm.2020.uclo-1), UCHI-1 (https://doi.org/10.4224/crm.2020.uchi-1), and UPER-1 (https://doi.org/10.4224/crm.2020.uper-1). This study involved 15 laboratories from 10 countries, using sector-field and (triple) quadrupole inductively-coupled plasma mass spectrometry to analyze 64 trace element impurities. We discuss the importance of the acids used for sample digestion, difficulties analyzing in a high uranium matrix, and data combination and uncertainty evaluation for this large dataset.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Collaborative Research Activities of the Arase and Van Allen Probes

This paper presents the highlights of joint observations of the inner magnetosphere by the Arase spacecraft, the Van Allen Probes spacecraft, and ground-based experiments integrated into spacecraft programs. The concurrent operation of the two missions in 2017–2019 facilitated the separation of the spatial and temporal structures of dynamic phenomena occurring in the inner magnetosphere. Because the orbital inclination angle of Arase is larger than that of Van Allen Probes, Arase collected observations at higher L-shells up to L ~ 10. After March 2017, similar variations in plasma and waves were detected by Van Allen Probes and Arase. We describe plasma wave observations at longitudinally separated locations in space and geomagnetically-conjugate locations in space and on the ground. The results of instrument intercalibrations between the two missions are also presented. Arase continued its normal operation after the scientific operation of Van Allen Probes completed in October 2019. The combined Van Allen Probes (2012-2019) and Arase (2017-present) observations will cover a full solar cycle. This will be the first comprehensive long-term observation of the inner magnetosphere and radiation belts.

97 MATHEMATICS AND COMPUTING↗

DECOVALEX-2015: an international collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems

Here, an important part of the performance and safety assessment of disposal systems for radioactive waste and spent nuclear fuel in deep geological formations is to evaluate the impact of the coupled effects of mechanical deformation, fluid and gas flow through the repository, and thermal loading from the decaying waste. It was recognized early on in safety and performance assessments conducted for geologic disposal sites that to be able to conduct such an evaluation, there was a need to rigorously enhance the theoretical background and to develop models capable of simulating coupled thermo-hydro-mechanical (THM) processes. More recently, chemical processes have also been added to enable the study of fully coupled THMC processes in geosystems.

58 GEOSCIENCES↗

Collaborative simulations and experiments for a novel yield model of coal devolatilization in oxy-coal combustion conditions

Oxy-coal combustion is an emerging low-cost “clean coal” technology for emissions reduction and Carbon Capture and Sequestration (CCS). The use of Computational Fluid Dynamics (CFD) tools is crucial for the development of cost-effective oxy-fuel technologies and the minimization of environmental concerns at industrial scale. The coupling of detailed chemistry models and CFD simulations is still challenging, especially for large-scale plants, because of the high computational efforts required. The development of scale-bridging models is therefore necessary, to find a good compromise between computational efforts and the physical-chemical modeling precision. This paper presents a procedure for scale-bridging modeling of coal devolatilization, in the presence of experimental error, that puts emphasis on the thermodynamic aspect of devolatilization, namely the final volatile yield of coal, rather than kinetics. The procedure consists of an engineering approach based on dataset consistency and Bayesian methodology including Gaussian-Process Regression (GPR). Experimental data from devolatilization tests carried out in an oxy-coal entrained flow reactor were considered and CFD simulations of the reactor were performed. Jointly evaluating experiments and simulations, a novel yield model was validated against the data via consistency analysis. In parallel, a Gaussian-Process Regression was performed, to improve the understanding of the uncertainty associated to the devolatilization, based on the experimental measurements. Potential model forms that could predict yield during devolatilization were obtained. The set of model forms obtained via GPR includes the yield model that was proven to be consistent with the data. Finally, the overall procedure has resulted in a novel yield model for coal devolatilization and in a valuable evaluation of uncertainty in the data, in the model form, and in the model parameters.

01 COAL, LIGNITE, AND PEAT↗