A self consistent chemically stratified atmosphere model for the roAp star 10 Aquilae

Context: Chemically peculiar A type (Ap) stars are a subgroup of the CP2 stars which exhibit anomalous overabundances of numerous elements, e.g. Fe, Cr, Sr and rare earth elements. The pulsating subgroup of the Ap stars, the roAp stars, present ideal laboratories to observe and model pulsational signatures as well as the interplay of the pulsations with strong magnetic fields and vertical abundance gradients. Aims: Based on high resolution spectroscopic observations and observed stellar energy distributions we construct a self consistent model atmosphere, that accounts for modulations of the temperature-pressure structure caused by vertical abundance gradients, for the roAp star 10 Aquilae (HD 176232). We demonstrate that such an analysis can be used to determine precisely the fundamental atmospheric parameters required for pulsation modelling. Methods: Average abundances were derived for 56 species. For Mg, Si, Ca, Cr, Fe, Co, Sr, Pr, and Nd vertical stratification profiles were empirically derived using the ddafit minimization routine together with the magnetic spectrum synthesis code synthmag. Model atmospheres were computed with the LLModels code which accounts for the individual abundances and stratification of chemical elements. Results: For the final model atmosphere Teff=7550 K and log g=3.8 were adopted. While Mg, Si, Co and Cr exhibit steep abundance gradients Ca, Fe and Sr showed much wider abundance gradients between log tau_5000=-1.5 and 0.5. Elements Mg and Co were found to be the least stratified, while Ca and Sr showed strong depth variations in abundance of up to ~ 6 dex.Comment: 9 pages, 15 figure

EviGUIDE - a tool for evidence-based decision making in image-guided adaptive brachytherapy for cervical cancer

PURPOSE: To develop a novel decision-support system for radiation oncology that incorporates clinical, treatment and outcome data, as well as outcome models from a large clinical trial on magnetic resonance image-guided adaptive brachytherapy (MR-IGABT) for locally advanced cervical cancer (LACC). METHODS: A system, called EviGUIDE, was developed that combines dosimetric information from the treatment planning system, patient and treatment characteristics, and established tumor control probability (TCP), and normal tissue complication probability (NTCP) models, to predict clinical outcome of radiotherapy treatment of LACC. Six Cox Proportional Hazards models based on data from 1341 patients of the EMBRACE-I study have been integrated. One TCP model for local tumor control, and five NTCP models for OAR morbidities. RESULTS: EviGUIDE incorporates TCP-NTCP graphs to help users visualize the clinical impact of different treatment plans and provides feedback on achievable doses based on a large reference population. It enables holistic assessment of the interplay between multiple clinical endpoints and tumour and treatment variables. Retrospective analysis of 45 patients treated with MR-IGABT showed that there exists a sub-cohort of patients (20%) with increased risk factors, that could greatly benefit from the quantitative and visual feedback. CONCLUSION: A novel digital concept was developed that can enhance clinical decision- making and facilitate personalized treatment. It serves as a proof of concept for a new generation of decision support systems in radiation oncology, which incorporate outcome models and high-quality reference data, and aids the dissemination of evidence-based knowledge about optimal treatment and serve as a blueprint for other sites in radiation oncology

Tools for large-scale data analytics of an international multi-center study in radiation oncology for cervical cancer

PURPOSE: To develop and implement a software that enables centers, treating patients with state-of-the-art radiation oncology, to compare their patient, treatment, and outcome data to a reference cohort, and to assess the quality of their treatment approach. MATERIALS AND METHODS: A comprehensive data dashboard was designed, which al- lowed holistic assessment of institutional treatment approaches. The software was tested in the ongoing EMBRACE-II study for locally advanced cervical cancer. The tool created individualized dashboards and automatic analysis scripts, verified pro- tocol compliance and checked data for inconsistencies. Identified quality assurance (QA) events were analysed. A survey among users was conducted to assess usability. RESULTS: The survey indicated favourable feedback to the prototype and highlighted its value for internal monitoring. Overall, 2302 QA events were identified (0.4% of all collected data). 54% were due to missing or incomplete data, and 46% originated from other causes. At least one QA event was found in 519/1001 (52%) of patients. QA events related to primary study endpoints were found in 16% of patients. Sta- tistical methods demonstrated good performance in detecting anomalies, with precisions ranging from 71% to 100%. Most frequent QA event categories were Treatment Technique (27%), Patient Characteristics (22%), Dose Reporting (17%), Outcome 156 (15%), Outliers (12%), and RT Structures (8%). CONCLUSION: A software tool was developed and tested within a clinical trial in radia- tion oncology. It enabled the quantitative and qualitative comparison of institutional patient and treatment parameters with a large multi-center reference cohort. We demonstrated the value of using statistical methods to automatically detect implau- sible data points and highlighted common pitfalls and uncertainties in radiotherapy for cervical cancer

Investigating conditional GAN performance with different generator architectures, an ensemble model, and different MR scanners for MR-sCT conversion

Recent developments in magnetic resonance (MR) to synthetic computed tomography (sCT) conversion have shown that treatment planning is possible without an initial planning CT. Promising conversion results have been demonstrated recently using conditional generative adversarial networks (cGANs). However, the performance is generally only tested on images from one MR scanner, which neglects the potential of neural networks to find general high-level abstract features. In this study, we explored the generalizability of the generator models, trained on a single field strength scanner, to data acquired with higher field strengths. T2-weighted 0.35T MRIs and CTs from 51 patients treated for prostate (40) and cervical cancer (11) were included. 25 of them were used to train four different generators (SE-ResNet, DenseNet, U-Net, and Embedded Net). Further, an ensemble model was created from the four network outputs. The models were validated on 16 patients from a 0.35T MR scanner. Further, the trained models were tested on the Gold Atlas dataset, containing T2-weighted MR scans of different field strengths; 1.5T(7) and 3T(12), and 10 patients from the 0.35T scanner. The sCTs were dosimetrically compared using clinical VMAT plans for all test patients. For the same scanner (0.35T), the results from the different models were comparable on the test set, with only minor differences in the mean absolute error (MAE) (35-51HU body). Similar results were obtained for conversions of 3T GE Signa and the 3T GE Discovery images (40-62HU MAE) for three of the models. However, larger differences were observed for the 1.5T images (48-65HU MAE). The overall best model was found to be the ensemble model. All dose differences were below 1%. This study shows that it is possible to generalize models trained on images of one scanner to other scanners and different field strengths. The best metric results were achieved by the combination of all networks

Physics Contributions Improved source path localisation in ring applicators and the clinical impact for gynecological brachytherapy

Abstract Purpose: The path of subsequent dwell positions of an afterloader source being moved through a ring applicator for cervix cancer brachytherapy deviates from an ideal circle and the position of marker wires. This can lead to deviations of several millimetres between real and assumed dwell positions for treatment planning with simplified source path models. The aim of this study was to test video-and autoradiography-based methods for source path determination, and to study the influence of dwell position accuracy on dose-volume histogram (DVH)-parameters. Material and methods: Videos of the exact motion of the source wire through three different (r = 26, 30, 34 mm) computed tomography/magnetic resonance (CT/MR) compatible plastic ring applicators were recorded. Observed dwell positions covering the whole length of each applicators channel were used to adjust the circular source path model. The agreement of the true source positions derived from video analysis with those of the corrected circular source path was verified using autoradiography. The impact of an accurate source path definition on dose planning was analysed by simulating clinically relevant uncertainties in 10 clinical treatment plans. Results: Depending on the ring size, source path diameters had to be increased by 0.5-1.0 mm in order to achieve acceptable maximum differences between observed and corrected dwell positions (1.3-2.0 mm). Autoradiography analysis showed a positional accuracy within ± 3 mm (extended standard deviation k = 2). For shifts of ± 2.5 mm for even all dwell positions, the systematic and random variation of the D 2cm³ for bladder, rectum, and sigmoid was within 3%, while the impact on DVH uncertainties was much smaller for clinical target volume (CTV) HR and gross tumour volume (GTV). Conclusions: It is strongly advised to verify the real source path for ring applicators during acceptance testing in order to assure accurate source path definition and dose planning. Autoradiography can be used for source path verification with acceptable accuracy for treatment planning and dose reporting

Definitive radiotherapy with image-guided adaptive brachytherapy for primary vaginal cancer

Primary vaginal cancer is a rare cancer and clinical evidence to support recommendations on its optimal management is insufficient. Because primary vaginal cancer resembles cervical cancer in many aspects, treatment strategies are mainly adopted from evidence in locally advanced cervical cancer. To date, the organ-sparing treatment of choice is definitive radiotherapy, consisting of external beam radiotherapy and brachytherapy, combined with concurrent chemotherapy. Brachytherapy is an important component of the treatment and its steep dose gradient enables the delivery of high doses of radiation to the primary tumour, while simultaneously sparing the surrounding organs at risk. The introduction of volumetric CT or MRI image-guided adaptive brachytherapy in cervical cancer has led to better pelvic control and survival, with decreased morbidity, than brachytherapy based on x-ray radiographs. MRI-based image-guided adaptive brachytherapy with superior soft-tissue contrast has also been adopted sporadically for primary vaginal cancer. This therapy has had promising results and is considered to be the state-of-the-art treatment for primary vaginal cancer in standard practice

Ultrasound

Clinical ultrasound (US) or sonography is an imaging modality using high frequency sound waves typically between 1 and 20 MHz. US pulses are created in transducers, often piezo-electrical crystal, which converts changes of thickness of the crystal into sound waves by alternating applying voltage. In brachytherapy, transrectal ultrasound (TRUS) probes are commonly used. They can be used for prostate and anal cancers, as well as, with some restrictions, for gynecological brachytherapy treatments. US is extensively used for diagnostic purposes in oncology. The high image resolution and good soft-tissue contrast allow for assessment of different oncologic sites such as abdominal or pelvic tumors, breast cancer, or various lymph node regions. For selected indications, US is considered equal or even superior to computed tomography (CT) or magnetic resonance imaging (MRI). The ultrasound contrast agents (UCA) used in contrast-enhanced ultrasound (CEUS) imaging consist of small bubbles of gas encapsulated in biocompatible shell, which resonate when excited by US waves at certain frequencies