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

106Ru eye plaque brachytherapy : benchmarking and evaluation of a novel 3D treatment planning system for uveal melanoma

Aderhautmelanome zählen zu den häufigsten Augentumoren mit einer Inzidenzrate von 1/100.000 pro Jahr. Die meisten Aderhautmelanompatienten profitieren von den verbesserten Strahlentherapietechniken, sodass eine Enukleation nur noch für sehr weit fortgeschrittene Tumorstadien notwendig wird. Hinsichtlich Tumorkontrolle und Nebenwirkungen erzielt die Brachytherapie mit 106Ru Augenapplikatoren exzellente Resultate in gleicher Weise wie Teletherapie mittels Photonen oder Protonen. Vergleicht man den Entwicklungsstand der Augenapplikator-basierten Brachytherapie mit der bildgesteuerten 3-dimensionalen Teletherapie liegt erstere allerdings hinsichtlich Bestrahlungsplanung und Qualitätssicherung hinter Teletherapie. Derzeit basiert die Bestrahlungsplanung vorwiegend auf simplen 1-dimensionalen Dosisvorschreibungstabellen oder auf überholter Software, die den steigenden Anforderungen bezüglich verbesserter Planungsgenauigkeit, Planungsoptimierung, einer genauen 3D Abbildung von Tumor- und Risikostrukturgeometrie und Postimplantations-Qualitätssicherung nicht mehr genügt. Für die Verbesserung klinischer Ergebnisse sind derartige Weiterentwicklungen hinsichtlich einer Verbesserung der Nebenwirkungen essentiell. Volumetrische Beschreibungen des Tumors und der Risikostrukturen, sowie die applizierte Dosis sind wesentliche Parameter, um die Abhängigkeit zwischen Dosis und Dosiswirkung zu verstehen. Ein erweitertes Verständnis dieser Beziehung wird somit eine individuellere Behandlung mit 106Ru Augenapplikatoren ermöglichen. Im Zuge dieser Doktorarbeit wurde eine Forschungsversion eines Behandlungsplanungssystems für die 106Ru basierte Brachytherapie von Aderhautmelanomen entwickelt. Um Dosis-Volumen Parameter basierend auf tatsächlich applizierten Dosen und einem volumetrischen Augenmodell für jeden Patienten ableiten zu können, wurden 3D Dosisverteilungen für die verschiedenen 106Ru Augenapplikatormodelle berechnet. Die im Monte Carlo Code MCNP6 generierten Nachschlagetabellen wurden mit Daten aus Messungen verglichen. Die Resultate zeigten eine gute Übereinstimmung zwischen errechneten und experimentellen Daten, sowie zu den Referenzwerten. Die resultierende statistische Unsicherheit lag deutlich unter den Angaben des Herstellers. Zusätzlich erlaubten die Filmmessungen eine genauere Beschreibung der 2D Dosisverteilungen über den gesamten Applikator. Die Informationen hieraus wurden genutzt, um Konzepte für Sicherheitssäume zu entwickeln, die auf realistischen dosimetrischen Messunsicherheiten beruhen. Nach der Validierung der Dosisberechnung des neuen Behandlungsplanungssystems, wurden unterschiedliche Szenarien für Tumorgröße und -position untersucht. Applikatorfehlplatzierungen wurden ebenfalls berücksichtigt, um somit Unsicherheiten durch die chirurgische Platzierung der Plaques zu simulieren. Basierend auf den volumetrischen Dosisverteilungen in diesen unterschiedlichen Szenarien, wurde die Robustheit der Behandlungspläne untersucht. Zudem wurde die Empfindlichkeit von Risikostrukturen in Bezug auf eine ungenaue Positionierung des Applikators und der dosimetrischen Unsicherheit analysiert. Infolgedessen konnten Optimierungsstrategien der Behandlungsplanung entwickelt werden, um das Normalgewebe besser zu schonen. Im letzten Schritt wurden Patientendaten der Behandlung der vergangenen 20 Jahre mit Brachytherapie gesammelt und hinsichtlich der Dosis-Wirkungs-Beziehung ausgewertet. Die wissenschaftliche Arbeit, die im Rahmen dieser Doktorarbeit durchgeführt wurde, hat einen neuartigen Software-basierten Ansatz für die brachytherapeutische Behandlung von Aderhautmelanomen geschaffen, der sowohl für die klinische Routine, als auch für pro- und retrospektive Studien genutzt werden kann.Uveal melanoma is the most prominent intraocular malignant tumor with an occurrence of 1 per 100,000 people per year. Nowadays, most patients with uveal melanoma benefit from advancements in conservative radiotherapy techniques and the necessity of enucleation is given only for very late stage patients. Among the different modalities utilized in the treatment, such as external beam photon and particle therapy, a long tradition of brachytherapy using 106Ru eye plaques achieves excellent tumor control and low toxicity rates. However, especially when compared to the recent advancements in image-guided three-dimensional external photon beam therapy on linear accelerators, the level of sophistication in aspects of treatment planning and quality assurance is very basic in eye plaque brachytherapy. So far, treatment planning relies either on simplistic one-dimensional dose prescription tools or on software that appears outdated and does not live up to the requirements for improving the planning accuracy, treatment plan optimization, tumor and critical structure geometry, and post-implantation quality assurance. Such improvements, however, are necessary if the clinical outcome should be amended, especially with respect to side effects. The low radiation sensitivity of uveal melanomas requires the application of very high doses which in turn pose a threat to the functionality of the radiosensitive structures. This frail balance between tumor control and normal tissue complication probabilities (NTCP) demands an accurate dose delivery and provides room for optimization. Volumetric descriptions of the tumor and critical structures and the dose deposited within these volumes are crucial parameters in order to understand the relationship between dose and response. By expanding the knowledge on this relationship, a more individual application of 106Ru eye plaques will become possible. The work carried out for this thesis was aimed to tackle these deficiencies in the current treatment methodology. A research version of a treatment planning system for brachytherapy of uveal melanomas was developed, within the scope of this thesis. In order to derive dose volume metrics based on actual delivered doses and a volumetric eye model for each patient, full three-dimensional dose distributions were calculated for different 106Ru plaque models. In a first step, these lookup tables, generated by the Monte Carlo code MCNP6, were compared to experimental data obtained from measurements using radiochromic films, diodes and Diamond detectors. The resulting data showed good agreement among the calculational, experimental and reference absolute and relative doses well within the uncertainties specified by the manufacturer. Additionally, the film measurements gave a better understanding of 2D dose distributions across the plaque. The information gained was used to establish margin concepts based on realistic dosimetric uncertainties. Once the dose calculation of the novel TPS was validated, different scenarios of tumor location and size including plaque misplacements to simulate uncertainties after surgery were generated. Based on the calculated volumetric dose distributions in these scenarios, treatment plan robustness and sensitivities of critical structures to an inaccurate plaque positioning and dosimetric uncertainties were analyzed. This step helped to develop treatment plan optimization strategies to improve the sparing of normal tissue. In a last step, patient data from the last 20 years of brachytherapy treatments at the Medical University of Vienna was collected and evaluated with respect to dose response relationships. The work carried out for the thesis allowed to establish a novel software based approach for treatment planning of ophthalmic plaque brachytherapy of uveal melanoma which can be used for clinical practice as well as a tool for pro- and retrospective studies, respectively.submitted by Gerd Heilemann, MScZusammenfassung in deutscher SpracheAbweichender Titel laut Übersetzung der Verfasserin/des VerfassersMedizinische Universität Wien, Dissertation, 2017OeB

Basic Properties of a New Polymer Gel for 3D-Dosimetry at High Dose-Rates Typical for FFF Irradiation Based on Dithiothreitol and Methacrylic Acid (MAGADIT): Sensitivity, Range, Reproducibility, Accuracy, Dose Rate Effect and Impact of Oxygen Scavenger

The photon induced radical-initiated polymerization in polymer gels can be used for high-resolution tissue equivalent dosimeters in quality control of radiation therapy. The dose (D) distribution in radiation therapy can be measured as a change of the physical measurement parameter T2 using T2-weighted magnetic resonance imaging. The detection by T2 is relying on the local change of the molecular mobility due to local polymerization initiated by radicals generated by the ionizing radiation. The dosimetric signals R2 = 1/T2 of many of the current polymer gels are dose-rate dependent, which reduces the reliability of the gel for clinical use. A novel gel dosimeter, based on methacrylic acid, gelatin and the newly added dithiothreitol (MAGADIT) as an oxygen-scavenger was analyzed for basic properties, such as sensitivity, reproducibility, accuracy and dose-rate dependence. Dithiothreitol features no toxic classification with a difference to THPC and offers a stronger negative redox-potential than ascorbic acid. Polymer gels with three different concentration levels of dithiothreitol were irradiated with a preclinical research X-ray unit and MR-scanned (T2) for quantitative dosimetry after calibration. The polymer gel with the lowest concentration of the oxygen scavenger was about factor 3 more sensitive to dose as compared to the gel with the highest concentration. The dose sensitivity (α = ∆R2/∆D) of MAGADIT gels was significantly dependent on the applied dose rate D ˙ (≈48% reduction between D ˙ = 0.6 Gy/min and D ˙ = 4 Gy/min). However, this undesirable dose-rate effect reduced between 4–8 Gy/min (≈23%) and almost disappeared in the high dose-rate range (8 ≤   D ˙ ≤   12 Gy/min) used in flattening-filter-free (FFF) irradiations. The dose response varied for different samples within one manufacturing batch within 3%–6% (reproducibility). The accuracy ranged between 3.5% and 7.9%. The impact of the dose rate on the spatial integrity is demonstrated in the example of a linear accelerator (LINAC) small sized 5 × 10 mm2 10 MV photon field. For MAGADIT the maximum shift in the flanks in this field is limited to about 0.8 mm at a FFF dose rate of 15 Gy/min. Dose rate sensitive polymer gels likely perform better at high dose rates; MAGADIT exhibits a slightly improved performance compared to the reference normoxic polymer gel methacrylic and ascorbic acid in gelatin initiated by copper (MAGIC) using ascorbic acid

Metastases-directed local therapies (MDT) beyond genuine oligometastatic disease (OMD): Indications, endpoints and the role of imaging

To further personalise treatment in metastatic cancer, the indications for metastases-directed local therapy (MDT) and the biology of oligometastatic disease (OMD) should be kept conceptually apart. Both need to be vigorously investigated. Tumour growth dynamics – growth rate combined with metastatic seeding efficiency – is the single most important biological feature determining the likelihood of success of MDT in an individual patient, which might even be beneficial in slowly developing polymetastatic disease. This can be reasonably well assessed using appropriate clinical imaging. In the context of considering appropriate indications for MDT, detecting metastases at the edge of image resolution should therefore suggest postponing MDT. While three to five lesions are typically used to define OMD, it could be argued that countability throughout the course of metastatic disease, rather than a specific maximum number of lesions, could serve as a better parameter for guiding MDT. Here we argue that the unit of MDT as a treatment option in metastatic cancer might best be defined not as a single procedure at a single point in time, but as a series of treatments that can be delivered in a single or multiple sessions to different lesions over time. Newly emerging lesions that remain amenable to MDT without triggering the start of a new systemic treatment, a change in systemic therapy, or initiation of best supportive care, would thus not constitute a failure of MDT. This would have implications for defining endpoints in clinical trials and registries: Rather than with any disease progression, failure of MDT would only be declared when there is progression to polymetastatic disease, which then precludes further options for MDT

Latent space manipulation for high-resolution medical image synthesis via the StyleGAN

Introduction: This paper explores the potential of the StyleGAN model as an high-resolution image generator for synthetic medical images. The possibility to generate sample patient images of different modalities can be helpful for training deep learning algorithms as e.g. a data augmentation technique. Methods: The StyleGAN model was trained on Computed Tomography (CT) and T2- weighted Magnetic Resonance (MR) images from 100 patients with pelvic malignancies. The resulting model was investigated with regards to three features: Image Modality, Sex, and Longitudinal Slice Position. Further, the style transfer feature of the StyleGAN was used to move images between the modalities. The root-mean-squard error (RMSE) and the Mean Absolute Error (MAE) were used to quantify errors for MR and CT, respectively. Results: We demonstrate how these features can be transformed by manipulating the latent style vectors, and attempt to quantify how the errors change as we move through the latent style space. The best results were achieved by using the style transfer feature of the StyleGAN (58.7 HU MAE for MR to CT and 0.339 RMSE for CT to MR). Slices below and above an initial central slice can be predicted with an error below 75 HU MAE and 0.3 RMSE within 4 cm for CT and MR, respectively. Discussion: The StyleGAN is a promising model to use for generating synthetic medical images for MR and CT modalities as well as for 3D volumes

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