Surrogate-driven respiratory motion models for MRI-guided lung radiotherapy treatments

An MR-Linac integrates an MR scanner with a radiotherapy delivery system, providing non-ionizing real-time imaging of the internal anatomy before, during and after radiotherapy treatments. Due to spatio-temporal limitations of MR imaging, only high-resolution 2D cine-MR images can be acquired in real-time during MRI-guided radiotherapy (MRIgRT) to monitor the respiratory-induced motion of lung tumours and organs-at-risk. However, temporally-resolved 3D anatomical information is essential for accurate MR guidance of beam delivery and dose estimation of the actually delivered dose. Surrogate-driven respiratory motion models can estimate the 3D motion of the internal anatomy from surrogate signals, producing the required information. The overall aim of this thesis was to tailor a generalized respiratory motion modelling framework for lung MRIgRT. This framework can fit the model directly to unsorted 2D MR images sampling the 3D motion, and to surrogate signals extracted from the 2D cine-MR images acquired on an MR-Linac. It can model breath-to-breath variability and produce a motion compensated super-resolution reconstruction (MCSR) 3D image that can be deformed using the estimated motion. In this work novel MRI-derived surrogate signals were generated from 2D cine-MR images to model respiratory motion for lung cancer patients, by applying principal component analysis to the control point displacements obtained from the registration of the cine-MR images. An MR multi-slice interleaved acquisition potentially suitable for the MR-Linac was developed to generate MRI-derived surrogate signals and build accurate respiratory motion models with the generalized framework for lung cancer patients. The developed models and the MCSR images were thoroughly evaluated for lung cancer patients scanned on an MR-Linac. The results showed that respiratory motion models built with the generalized framework and minimal training data generally produced median errors within the MCSR voxel size of 2 mm, throughout the whole 3D thoracic field-of-view and over the expected lung MRIgRT treatment times

Quantifying, Understanding and Predicting Differences Between Planned and Delivered Dose to Organs at Risk in Head & Neck Cancer Patients Undergoing Radical Radiotherapy to Promote Intelligently Targeted Adaptive Radiotherapy

Introduction: Radical radiotherapy (RT) is an effective but toxic treatment for head and neck cancer (HNC). Contemporary radiotherapy techniques sculpt dose to target disease and avoid organs at risk (OARs), but anatomical change during treatment mean that the radiation dose delivered to the patient – delivered dose (DA), is different to that anticipated at planning – planned dose (DP). Modifying the RT plan during treatment – Adaptive Radiotherapy (ART) – could mitigate these risks by reducing dose to OARs. However, clinical data to guide patient selection for, and timing of ART, are for lacking. Methods: 337 patients with HNC were recruited to the Cancer Research UK VoxTox study. Demographic, disease and treatment data were collated, and both DP and DA to organs at risk (OARs) were computed from daily megavoltage CT image guidance scans, using an open-source deformable image registration package (Elastix). Toxicity data were prospectively collected. Relationships between DP, DA and late toxicities were investigated with univariate, and logistic regression normal tissue complication probability (NTCP) modelling approaches. A sub-study of VoxTox recruited 18 patients who had MRI scans before RT fractions 1, 6, 16, and 26. Changes in salivary gland volumes and relative apparent diffusion coefficient (ADC) values were measured and related to toxicity events. Results: Spinal cord dose differences were small, and not predicted by weight loss or shape change. Mean DA to all other OARs was higher than DP; factors predicting higher DA included primary disease site, concomitant therapy, shape change and advanced neck disease. Nine patients (3.7%) saw DA>DP by 2Gy to more than half of the OARs assessed. These patients all had received bilateral neck RT for N-stage 2b oropharyngeal cancer. Strong uni- and multivariate relationships between OAR dose and toxicity were seen. Differences between DA and DP-based dose-toxicity models were minimal, and not statistically significant. On MRI, both parotid and submandibular glands shrank during treatment, whilst relative ADC rose. Relationships with toxicity were inconclusive. Conclusions: Small differences between OAR DP and DA mean that DA-based toxicity prediction models confer negligible additional benefit at the population level. Factors such as primary disease sub-site, concomitant systemic therapy, staging and shape change may help to select the patients that do develop clinically significant dose differences, and would benefit most from ART for toxicity reduction

Segmentation of pelvic structures from preoperative images for surgical planning and guidance

Prostate cancer is one of the most frequently diagnosed malignancies globally and the second leading cause of cancer-related mortality in males in the developed world. In recent decades, many techniques have been proposed for prostate cancer diagnosis and treatment. With the development of imaging technologies such as CT and MRI, image-guided procedures have become increasingly important as a means to improve clinical outcomes. Analysis of the preoperative images and construction of 3D models prior to treatment would help doctors to better localize and visualize the structures of interest, plan the procedure, diagnose disease and guide the surgery or therapy. This requires efficient and robust medical image analysis and segmentation technologies to be developed. The thesis mainly focuses on the development of segmentation techniques in pelvic MRI for image-guided robotic-assisted laparoscopic radical prostatectomy and external-beam radiation therapy. A fully automated multi-atlas framework is proposed for bony pelvis segmentation in MRI, using the guidance of MRI AE-SDM. With the guidance of the AE-SDM, a multi-atlas segmentation algorithm is used to delineate the bony pelvis in a new \ac{MRI} where there is no CT available. The proposed technique outperforms state-of-the-art algorithms for MRI bony pelvis segmentation. With the SDM of pelvis and its segmented surface, an accurate 3D pelvimetry system is designed and implemented to measure a comprehensive set of pelvic geometric parameters for the examination of the relationship between these parameters and the difficulty of robotic-assisted laparoscopic radical prostatectomy. This system can be used in both manual and automated manner with a user-friendly interface. A fully automated and robust multi-atlas based segmentation has also been developed to delineate the prostate in diagnostic MR scans, which have large variation in both intensity and shape of prostate. Two image analysis techniques are proposed, including patch-based label fusion with local appearance-specific atlases and multi-atlas propagation via a manifold graph on a database of both labeled and unlabeled images when limited labeled atlases are available. The proposed techniques can achieve more robust and accurate segmentation results than other multi-atlas based methods. The seminal vesicles are also an interesting structure for therapy planning, particularly for external-beam radiation therapy. As existing methods fail for the very onerous task of segmenting the seminal vesicles, a multi-atlas learning framework via random decision forests with graph cuts refinement has further been proposed to solve this difficult problem. Motivated by the performance of this technique, I further extend the multi-atlas learning to segment the prostate fully automatically using multispectral (T1 and T2-weighted) MR images via hybrid \ac{RF} classifiers and a multi-image graph cuts technique. The proposed method compares favorably to the previously proposed multi-atlas based prostate segmentation. The work in this thesis covers different techniques for pelvic image segmentation in MRI. These techniques have been continually developed and refined, and their application to different specific problems shows ever more promising results.Open Acces

Evaluation of proton treatment strategies for head and neck cancer and lung cancer based on treatment planning studies

The clinical introduction of proton therapy requires an extensive analysis of its benefits compared to conventional radiotherapy and a detailed analysis of possible uncertainties which might have serious consequences for patient treatment. In the first part of the presented thesis, the expected toxicities were evaluated for a treatment of head and neck cancer patients using a biologically adapted dose escalation schedule with photon and proton therapy. The feasibility of the dose escalation schedule could be demonstrated for both photon and proton therapy, since only a small increase in toxicity risk occurred for most toxicities. However, the expected toxicity risks were in most cases smaller with proton therapy. Furthermore, a higher benefit was found for patients with primary tumour locations in the upper head and neck area, who thus might be preferably referred to proton therapy. In the second part of this thesis, an extensive analysis of the impact of tumour motion in lung cancer treatment with active-scanning proton therapy was conducted. It could be shown, that dose degradations were small for tumour motion amplitudes below 5 mm. Parameters like the target volume concept, the optimisation approach, changes in the motion pattern and application sequence times had additional impact on the dose degradation. However, their magnitude was patient specific. Since not all parameters can be assessed before treatment, e.g. the motion pattern during treatment, prospective estimations should be supplemented by retrospective analyses.Die Einführung der Protonentherapie in die klinische Praxis erfordert umfassende Analysen ihrer Vor- und Nachteile im Vergleich zur konventionellen Photonentherapie sowie detaillierte Untersuchungen der Auswirkungen von Unsicherheiten in der Therapieapplikation. Im ersten Teil der vorliegenden Arbeit wurden die zu erwartenden Nebenwirkungen bei der Behandlung von Patienten mit Kopf-Hals-Tumoren mit einem biologisch-adaptierten Fraktionierungsschema inklusive Dosiseskalation mit Photonen- und Protonentherapie evaluiert. Dabei konnte gezeigt werden, dass die Dosiseskalation sowohl mit Photonen- als auch Protonentherapie angewandt werden kann, da die Wahrscheinlichkeit für das Auftreten von Nebenwirkungen in den meisten Fällen kaum erhöht wurde. Weiterhin wurden die Nebenwirkungswahrscheinlichkeiten mit der Protonentherapie im Vergleich zur Photonentherapie reduziert. Dies war vor allem für Patienten mit Tumoren im oberen Kopf-Hals-Bereich der Fall. Diese könnten daher bevorzugt zur Protonentherapie überwiesen werden. Darüber hinaus wurde im zweiten Teil der Arbeit eine umfassende Analyse des Einflusses der Tumorbewegung auf die Dosisverteilung bei Behandlung von Lungentumoren mit aktiver Protonenstrahlformierung durchgeführt. Dabei zeigte sich, dass Dosisdegradierungen bei Bewegungsamplituden unter 5mm gering sind. Parameter wie das Zielvolumenkonzept, Veränderungen des Bewegungsmusters oder der Applikationszeiten nehmen zusätzlich Einfluss auf die Dosisdegradierung, allerdings in unterschiedlichem Maß für individuelle Patienten. Da nicht alle Parameter vor Behandlung bekannt sein können, sollten prospektive Dosisabschätzungen durch retrospektive Analysen ergänzt werden

Surface guided radiotherapy

Modern radiotherapy aims to treat the decease while minimizing the radiation dose to the adjacent normal tissue, to minimize acute and late effects of the treatment. The foremost technological approaches have been intensity modulated radiotherapy (IMRT) and intensity modulated proton therapy (IMPT) in combination with image guided radiotherapy (IGRT). IMRT and IMPT is characterized by a more conform dose distribution, often accompanied by steep dose gradients. In turn, accurate patient localization and motion management becomes more important. Several image guidance systems are available for radiotherapy (RT), with 3-dimensional (3D) volumetric images with cone beam computed tomography (CBCT) as a gold standard. In recent years, surface imaging (SI) using an optical surface scanning system has been included in the IGRT toolbox. The SI system CatalystTM (C-rad Positioning AB, Uppsala Sweden) visualize 3D surface images of the patient topography, and direct correlate the patient localization to the initial planned position. SI offers the largest field-of-view in RT, does not contribute to radiation exposure, provides real-time feedback and sub-millimeter spatial resolution. These characteristics are suitable for both patient positioning and motion management during RT.Integration with the linac provides beam control and automatic couch shifts, which imposes rigorous attention to quality assurance (QA) of the SI systems. In order to integrate the beam control, beam latency times (beam-on and beam-off) should be characterized, which required the development PIN diode circuit as a QA tool. Of extra importance was the measurements of the beam-off latency time, since it represents the time the linac continues to irradiate after the beam hold signal was sent from the SI system. The automatic couch shift is calculated by a deformable image registration (DIR) algorithm, unique for the CatalystTM surface scanning system. Positioning accuracy is dependent on the image registration, and hence, a deformable thorax phantom was developed to investigate accuracy of the DIR with anatomical realistic deformations present as a QA tool.Compared to traditional 3-point localization for patient positioning, this thesis has shown that SI improve the positioning for both breast and prostate cancer patients. Also, the SI workflow has shown to be time efficient for positioning of prostate cancer patients. A respiratory motion management technique is deep inspiration breath hold (DIBH), where the patient is instructed to hold his/her breath during the treatment delivery. The aim using DIBH, is to create an anatomical distance between the treatment volume and surrounding organs-at-risk (OARs). Comparative treatment planning studies, within the work of this thesis, showed that DIBH can be an effective method for both left sided breast cancer and Hodgkin’s lymphoma (HL) in order to spare dose to the heart. For HL, the combination of IMPT and DIBH was found to spare dose to OARs, however, due to the spread in target localization individual deviations from this treatment technique were observed. The real-time feedback from the surface image system was used to investigate the reproducibility of the DIBH to ensure correct dose distribution during the treatment delivery. High reproducibility of the isocenter position during DIBH was observed, however, for a few breath holds larger deviations occurred which urges the need to use beam control tolerance for the isocenter. The overall conclusion is that optical imaging systems, developed within the work of this thesis, can be used as an imaging tool for accurate and faster patient setup, intrafractional motion monitoring and reduced dose to OARs during treatment in DIBH