Towards Accurate Tumour Tracking in Lungs

International audienceMotivated by radiotherapy and hadrontherapy improvement, we consider in a first step the potential of simple elastic mechanical modelling of the lung. We propose to simulate his deformation and motion during respiration towards tracking tumours. We present two approaches, based on finite-elements method and mass-spring system. For this, we suggest a personalised model based on the measurement of patient's physical and geometrical data

A chest wall model based on rib kinematics

International audienceThe success of radiotherapy treatment could be compromised by motion. Lung tumours are particularly concerned by this problem because their positions are subject to breathing motion. To reduce the uncertainty on the position of pulmonary tumours during breathing cycle, we propose to develop a complete thoracic biomechanical model. This model will be monitored through the measurement of external parameters (thorax outer-surface motion, air flow...) and should predict in real-time the location of lung tumour. In this paper, we expose a biomechanical model of the lung environment, based on anatomical and physiological knowledge. The model includes the skin, the ribs, the pleura and the soft tissue between the skin and the ribcage. Motions and deformations are computed with the Finite Element Method. The ribcage direct kinematics model, permits to compute the skin position from the ribs motion. Conversely, the inverse kinematics provides rib motion and consequently lung motion. It can be computed from the outer-surface motion. With regards to available clinical data the results are promising. In particular, the average error is lower than the resolution of the CT-scan images used as input data.Le succès du traitement par radiothérapie pourrait être compromis par le mouvement. Les tumeurs pulmonaires sont particulièrement concernées par ce problème, parce que leurs positions sont soumises à la respiration. Pour réduire l'incertitude sur la position des tumeurs pulmonaires au cours de la respiration, nous proposons de développer un modèle biomécanique de la cage thoracique. Ce modèle sera suivi par la mesure des paramètres externes (mouvement de la surface du thorax extérieur, quantité d'air inspirée et expirée ...) et devrait prévoir en temps réel la localisation de la tumeur du poumon. Dans ce document, nous exposons un modèle biomécanique de l'appareil respiratoire, fondé sur les connaissances anatomiques et physiologiques. Le modèle comprend la peau, les côtes, la plèvre et les tissus mous entre la peau et la cage thoracique. Les mouvements et les déformations sont calculées avec la méthode des éléments finis. Le modèle cinématique direct de la cage thoracique permet de calculer la position de la peau à partir du mouvement des côtes. Inversement, la cinématique inverse permet de déduire le mouvement des côtes et des poumons à partir du mouvement externe de la peau. Les résultats obtenus par ce modèle sont satisfaisants surtout que l’erreur moyenne est inférieure à la résolution des images CT-scan utilisées comme données d’entrée

Developing multi-modal imaging agents for stem cell tracking

Clinical trials using stem cells as a regenerative therapy or a delivery vehicle for anti-cancer agents have been increasing but the outcomes are highly variable. In vivo imaging of stem cell delivery to target organs will help improve their therapeutic efficacy. However, a single imaging modality cannot provide the complete answer. The work in this thesis aims to develop a multi-modal imaging approach to overcome the limitations of each modality. To understand the distribution pattern of transplanted stem cells in vivo, luciferase expressing adipocyte derived mesenchymal stem cells (ADSCs) were labelled with novel bimodal (nuclear/magnetic resonance imaging) nanoparticles and the following hypotheses were tested; 1) that the distribution pattern of transplanted ADSCs would be different between venous and arterial routes, 2) that the arterial route would provide a more efficient way of delivering ADSC to tumours. In addition, ultrasound-guided renal artery injection was developed to improve stem cell delivery to kidney and the efficiency of this injection was assessed using photoacoustic and bioluminescence imaging. Moreover, the applicability of gold nanoparticles (GNP) as cell tracking agents was explored using multi-modal imaging. Results demonstrated the advantages of multi-modal imaging in assessing different cell distribution patterns after two systemic injections and confirmed that the arterial route was more efficient in delivering ADSCs to tumours. The assessment of cell localisation and viability in the kidney suggests that the level of cell engraftment improved after ultrasound-guided renal artery injection. Multi-modal imaging results indicated that GNPs are a promising cell tracking agent for computed tomography but further studies are required to define their specific applications. In conclusion, this work has demonstrated the successful application of multi-modal imaging for stem cell tracking in different organs. The findings from this thesis proved that combining the strengths of each modality can provide greater insight into cell migration and distribution

Real-time intrafraction motion monitoring in external beam radiotherapy

© 2019 Institute of Physics and Engineering in Medicine. Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to 'see what we treat, as we treat' and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT

Dosimetry and 4D Modelling for Advanced Radiotherapy Treatments: Towards MRI-Guided Lung SBRT

A major problem for radiation therapy of lung cancer is respiration-induced motion, which causes both the tumour and surrounding normal tissue to move during treatment. This motion often results in inadequate target coverage and increases the likelihood of additional healthy tissue exposure; therefore detracting from the therapeutic benefits and increasing the risk of radiation induced toxicity. Some motion-management techniques include additional treatment margins to encompass the range of tumour motion, monitoring the respiratory cycle and treating only when in a particular phase i.e. respiratory gating, or imaging the tumour during treatment and adapting the radiation beam aperture to follow the tumour i.e. image guidance and tracking. Magnetic-Resonance-Imaging (MRI)-linacs are a form of image guided radiotherapy, these systems offer high soft-tissue contrast imaging (with MRI) while simultaneously treating with a therapeutic radiation beam (linear accelerator or linac). The effects of the magnetic field on dose deposition and detector response should be well understood to safely translate this technology to clinical treatments. For MRI-linacs where the magnetic field is inline with respect to the beam, the effects of the magnetic field on electron trajectories in lung can be significant and therefore it is important to study the impacts of this on dose distribution in order to treat lung SBRT on these systems. In this thesis, a 4D Monte Carlo dose calculation tool is developed and implemented for assessing current radiotherapy techniques for lung Stereotactic Body Radiotherapy (SBRT). In recent years there has been an increasing interest in MRI-guided radiotherapy and its potential to be used for lung SBRT. With the higher doses per fraction used for SBRT there is an increased need for highly accurate dose calculations and localised delivery; particularly for MRI-linac lung treatments, where the magnetic field strongly influences lung tissue and tumour dose distributions. This thesis also presents work towards translating the 4D Monte Carlo method for inline MRI-linacs

A biomechanical approach for real-time tracking of lung tumors during External Beam Radiation Therapy (EBRT)

Lung cancer is the most common cause of cancer related death in both men and women. Radiation therapy is widely used for lung cancer treatment. However, this method can be challenging due to respiratory motion. Motion modeling is a popular method for respiratory motion compensation, while biomechanics-based motion models are believed to be more robust and accurate as they are based on the physics of motion. In this study, we aim to develop a biomechanics-based lung tumor tracking algorithm which can be used during External Beam Radiation Therapy (EBRT). An accelerated lung biomechanical model can be used during EBRT only if its boundary conditions (BCs) are defined in a way that they can be updated in real-time. As such, we have developed a lung finite element (FE) model in conjunction with a Neural Networks (NNs) based method for predicting the BCs of the lung model from chest surface motion data. To develop the lung FE model for tumor motion prediction, thoracic 4D CT images of lung cancer patients were processed to capture the lung and diaphragm geometry, trans-pulmonary pressure, and diaphragm motion. Next, the chest surface motion was obtained through tracking the motion of the ribcage in 4D CT images. This was performed to simulate surface motion data that can be acquired using optical tracking systems. Finally, two feedforward NNs were developed, one for estimating the trans-pulmonary pressure and another for estimating the diaphragm motion from chest surface motion data. The algorithm development consists of four steps of: 1) Automatic segmentation of the lungs and diaphragm, 2) diaphragm motion modelling using Principal Component Analysis (PCA), 3) Developing the lung FE model, and 4) Using two NNs to estimate the trans-pulmonary pressure values and diaphragm motion from chest surface motion data. The results indicate that the Dice similarity coefficient between actual and simulated tumor volumes ranges from 0.76±0.04 to 0.91±0.01, which is favorable. As such, real-time lung tumor tracking during EBRT using the proposed algorithm is feasible. Hence, further clinical studies involving lung cancer patients to assess the algorithm performance are justified

Improving clinical outcomes for patients with locally advanced non-small cell lung cancer treated with photon and proton radiotherapy

Objectives To identify mechanisms improving clinical outcomes for patients with unresectable locally advanced non-small-cell lung cancer (LA-NSCLC) treated with photon and proton radiotherapy. Strategies explored include 1. Investigating using routine healthcare datasets to estimate survival outcomes for patients with LA-NSCLC treated with definitive radiotherapy, in order to assess the effectiveness of current strategies; 2. Assessing the physical advantages of protons by conducting a retrospective planning study comparing volumetric modulated arc therapy (VMAT) and pencil beam scanning (PBS) proton plans of superior sulcus tumours (SSTs), a rare subset of LA-NSCLC; 3. Exploring potential biological advantages of protons by examining major cell death pathways following XRT, high and low linear energy transfer (LET) proton irradiation of NSCLC cells. Methods Workflow 1: LA-NSCLC patients receiving definitive radiotherapy were identified. For each, key time points (date of diagnosis, recurrence, death or last clinical encounter) were used to calculate overall survival (OS) and progression free survival (PFS) from manual-data (hospital notes) and compared to estimated OS and PFS from routine-data (electronic databases). Dataset correlations were then tested to establish if routine-data were a reliable proxy measure for manual-data. Workflow 2: Patients with SSTs treated with 4D radiotherapy were identified. Tumour motion was assessed and excluded if >5 mm. Comparative VMAT and PBS plans were generated retrospectively. Robustness analysis was assessed for both plans involving: 1. 5 mm geometric uncertainty scenarios, with an additional 3.5% range uncertainty for proton plans; 2. verification plans at breathing extremes. Comparative dosimetric and robustness analyses were carried out. Workflow 3: Human NSCLC cell lines were irradiated with single doses of 2-15 Gy photon radiotherapy, high- or low-linear energy transfer (LET) protons (12 keV/µm and 1 keV/µm, respectively) and analysed 24-144 hours post-irradiation. DNA damage foci and cell death mechanisms were investigated. Results Workflow 1: In forty-three patients, routine data underestimated PFS by 0.09 months (p=0.86; 95% CI -0.86-1.03) and OS by 1.02 months (p=0.00; 95% CI 0.34-1.69) but there was good correlation with a Pearson correlation coefficient of 0.94 (p=0.00, 95% CI 0.90-0.97) for PFS and 0.97 (p= 0.00, 95% CI 0.95-0.98) for OS. Workflow 2: In ten patients, both modalities achieved similar target coverage with mean clinical target volume D95 of 98.1% + 0.4 (97.5-98.8) and 98.4% + 0.2 (98.1-98.9) for PBS and VMAT plans, respectively. The same four PBS and VMAT plans failed robustness. Proton plans significantly reduced mean lung dose (by 21.9%), lung V5, V10, V20 (by 47.9%, 36.4%, 12.1%, respectively), mean heart dose (by 21.4%) and vertebra dose (by 29.2%) (p<0.05). Workflow 3: XRT predominantly induced mitotic catastrophe, autophagy and senescence. Senescence, established via the p53/p21 pathway, was the major cell death pathway by which protons more effectively reduce clonogenic potential compared to XRT in NSCLC cell lines. High LET protons at a dose of 10 Gy(RBE) resulted in the lowest cell survival. The mechanisms driving the LET- and dose-dependent senescence was unclear but did not appear to be related to differential DNA repair machineries. Conclusions Proton radiotherapy could be pivotal in improving outcomes in select cases of LA-NSCLC. These studies demonstrate that 1. survival-outcomes are reliably estimated by routine data and such a methodology could enable rapid outcomes analysis to keep pace with trial development; 2. robust PBS plans are achievable in carefully selected patients and considerable dose reductions to the lung, heart and thoracic vertebra are possible without compromising target coverage; 3. Identification of LET- and dose-dependent proton-induced cellular senescence may guide radiotherapy optimisation and drug-radiotherapy combinations, maximising tumour cell kill. This work contributes to important preliminary research required to understand the physical and biological strengths and weaknesses prior to trials

Improving the Accuracy of CT-derived Attenuation Correction in Respiratory-Gated PET/CT Imaging

The effect of respiratory motion on attenuation correction in Fludeoxyglucose (18F) positron emission tomography (FDG-PET) was investigated. Improvements to the accuracy of computed tomography (CT) derived attenuation correction were obtained through the alignment of the attenuation map to each emission image in a respiratory gated PET scan. Attenuation misalignment leads to artefacts in the reconstructed PET image and several methods were devised for evaluating the attenuation inaccuracies caused by this. These methods of evaluation were extended to finding the frame in the respiratory gated PET which best matched the CT. This frame was then used as a reference frame in mono-modality compensation for misalignment. Attenuation correction was found to affect the quantification of tumour volumes; thus a regional analysis was used to evaluate the impact of mismatch and the benefits of compensating for misalignment. Deformable image registration was used to compensate for misalignment, however, there were inaccuracies caused by the poor signal-to-noise ratio (SNR) in PET images. Two models were developed that were robust to a poor SNR allowing for the estimation of deformation from very noisy images. Firstly, a cross population model was developed by statistically analysing the respiratory motion in 10 4DCT scans. Secondly, a 1D model of respiration was developed based on the physiological function of respiration. The 1D approach correctly modelled the expansion and contraction of the lungs and the differences in the compressibility of lungs and surrounding tissues. Several additional models were considered but were ruled out based on their poor goodness of fit to 4DCT scans. Approaches to evaluating the developed models were also used to assist with optimising for the most accurate attenuation correction. It was found that the multimodality registration of the CT image to the PET image was the most accurate approach to compensating for attenuation correction mismatch. Mono-modality image registration was found to be the least accurate approach, however, incorporating a motion model improved the accuracy of image registration. The significance of these findings is twofold. Firstly, it was found that motion models are required to improve the accuracy in compensating for attenuation correction mismatch and secondly, a validation method was found for comparing approaches to compensating for attenuation mismatch