Integration of biomechanical models into image registration in the presence of large deformations

Prone-to-supine breast image registration has potential application in the fields of surgical and radiotherapy planning, and image guided interventions. However, breast image registration of three-dimensional images acquired in different patient positions is a challenging problem, due to large deformations induced to the soft breast tissue caused by the change in gravity loading. Biomechanical modelling is a promising tool to predict gravity induced deformations, however such simulations alone are unlikely to produce good alignment due to inter-patient variability and image acquisition related influences on the breast shape. This thesis presents a symmetric, biomechanical simulation based registration framework which aligns images in a central, stress-free configuration. Soft tissue is modelled as a neo-Hookean material and external forces are considered as the main source of deformation in the original images. The framework successively applies image derived forces directly into the unloading simulation in place of a subsequent image registration step. This results in a biomechanically constrained deformation. Using a finite difference scheme enables simulations to be performed directly in the image space. Motion constrained boundary conditions have been incorporated which can capture tangential motion of membranes and fasciae. The accuracy of the approach is assessed by measuring the target registration error (TRE) using nine prone MRI and supine CT image pairs, one prone-supine CT image pair, and four prone-supine MRI image pairs. The registration reduced the combined mean TRE for all clinical data sets from initially 69.7mm to 5.6mm. Prone-supine image pairs might not always be available in the clinical breast cancer workflow, especially prior to surgery. Hence an alternative surface driven registration methodology was also developed that incorporates biomechanical simulations, material parameter optimisation, and constrained surface matching. For three prone MR images and corresponding supine CT-derived surfaces a final mean TRE of 10.0mm was measured

A scale for assessing the severity of diseases and adverse drug reactions: Application to drug benefit and risk

Physicians were interviewed to assess their willingness to risk adverse drug reactions among patients. These untoward reactions were ranked according to severity and weighted against the primary illness being treated. A specially designed questionnaire in the form of a matrix was used. Severity was divided into seven classes denoted by progressively increasing numerical scores, W1 to W7, whose values could be calculated from analysis of the completed questionnaires. The questionnaires presented several cases, in each of which an illness of specified severity was to be treated with a drug whose untoward reactions differ in severity from that of the primary illness. Each case involved a different permutation of the severities. Analysis of the completed questionnaires yielded the mean values of the scores which were found to range from W1 = 1.00 (the mildest case) to W7 = 817 (the most serious case). It is our opinion that this type of scale is preferable to nonnumerical descriptions of severity such as mild or serious, since, when combined with data on frequency of occurrence, a numerical scale permits a determination of expectation of both benefit and risk

Technical Note: 4D Deformable Digital Phantom for MRI Sequence Development

PURPOSE: MR-guided radiotherapy has different requirements for the images than diagnostic radiology, thus requiring development of novel imaging sequences. MRI simulation is an excellent tool for optimising these new sequences, however currently available software does not provide all the necessary features. In this paper we present a digital framework for testing MRI sequences that incorporates anatomical structure, respiratory motion and realistic presentation of MR physics. METHODS: The extended Cardiac-Torso (XCAT) software was used to create T1, T2 and proton density maps that formed the anatomical structure of the phantom. Respiratory motion model was based on the XCAT deformation vector fields, modified to create a motion model driven by a respiration signal. MRI simulation was carried out with JEMRIS, an open source Bloch simulator. We developed an extension for JEMRIS, which calculates the motion of each spin independently, allowing for deformable motion. RESULTS: The performance of the framework was demonstrated through simulating the acquisition of a 2D cine and demonstrating expected motion ghosts from T2 weighted spin echo acquisitions with different respiratory patterns. All simulations were consistent with behaviour previously described in literature. Simulations with deformable motion were not more time consuming than with rigid motion. CONCLUSIONS: We present a deformable 4D digital phantom framework for MR sequence development. The framework incorporates anatomical structure, realistic breathing patterns, deformable motion and Bloch simulation to achieve accurate simulation of MRI. This method is particularly relevant for testing novel imaging

Prevention and control of apple scab

Improved prevention and control of apple scab caused by Venturia inaequalis is aimed at without the use of copper containing products in the Repco-project. Substantial progress is made in selection of potential products against summer epidemics. A patent application is made for E73. New effective biocontrol agents are selected to reduce inoculum during winter. The product potassium bicarbonate has shown good efficacy and Repco contributes to the registration of this product in Europe. Earthworms tended to be stimulated to consume apple leaves treated with amino acids or beetpulp, especially when applied fresh under controlled environmental condi-tons

Multiscale Mechano-Biological Finite Element Modelling of Oncoplastic Breast Surgery-Numerical Study towards Surgical Planning and Cosmetic Outcome Prediction

Surgical treatment for early-stage breast carcinoma primarily necessitates breast conserving therapy (BCT), where the tumour is removed while preserving the breast shape. To date, there have been very few attempts to develop accurate and efficient computational tools that could be used in the clinical environment for pre-operative planning and oncoplastic breast surgery assessment. Moreover, from the breast cancer research perspective, there has been very little effort to model complex mechano-biological processes involved in wound healing. We address this by providing an integrated numerical framework that can simulate the therapeutic effects of BCT over the extended period of treatment and recovery. A validated, three-dimensional, multiscale finite element procedure that simulates breast tissue deformations and physiological wound healing is presented. In the proposed methodology, a partitioned, continuum-based mathematical model for tissue recovery and angiogenesis, and breast tissue deformation is considered. The effectiveness and accuracy of the proposed numerical scheme is illustrated through patient-specific representative examples. Wound repair and contraction numerical analyses of real MRI-derived breast geometries are investigated, and the final predictions of the breast shape are validated against post-operative follow-up optical surface scans from four patients. Mean (standard deviation) breast surface distance errors in millimetres of 3.1 (±3.1), 3.2 (±2.4), 2.8 (±2.7) and 4.1 (±3.3) were obtained, demonstrating the ability of the surgical simulation tool to predict, pre-operatively, the outcome of BCT to clinically useful accuracy

Consistent and invertible deformation vector fields for a breathing anthropomorphic phantom: a post-processing framework for the XCAT phantom.

Breathing motion is challenging for radiotherapy planning and delivery. This requires advanced four-dimensional (4D) imaging and motion mitigation strategies and associated validation tools with known deformations. Numerical phantoms such as the XCAT provide reproducible and realistic data for simulation-based validation. However, the XCAT generates partially inconsistent and non-invertible deformations where tumours remain rigid and structures can move through each other. We address these limitations by post-processing the XCAT deformation vector fields (DVF) to generate a breathing phantom with realistic motion and quantifiable deformation. An open-source post-processing framework was developed that corrects and inverts the XCAT-DVFs while preserving sliding motion between organs. Those post-processed DVFs are used to warp the first XCAT-generated image to consecutive time points providing a 4D phantom with a tumour that moves consistently with the anatomy, the ability to scale lung density as well as consistent and invertible DVFs. For a regularly breathing case, the inverse consistency of the DVFs was verified and the tumour motion was compared to the original XCAT. The generated phantom and DVFs were used to validate a motion-including dose reconstruction (MIDR) method using isocenter shifts to emulate rigid motion. Differences between the reconstructed doses with and without lung density scaling were evaluated. The post-processing framework produced DVFs with a maximum [Formula: see text]-percentile inverse-consistency error of 0.02 mm. The generated phantom preserved the dominant sliding motion between the chest wall and inner organs. The tumour of the original XCAT phantom preserved its trajectory while deforming consistently with the underlying tissue. The MIDR was compared to the ground truth dose reconstruction illustrating its limitations. MIDR with and without lung density scaling resulted in small dose differences up to 1 Gy (prescription 54 Gy). The proposed open-source post-processing framework overcomes important limitations of the original XCAT phantom and makes it applicable to a wider range of validation applications within radiotherapy

Adenosine Triphosphate and Carbon Efficient Route to Second Generation Biofuel Isopentanol.

Climate change necessitates the development of CO2 neutral or negative routes to chemicals currently produced from fossil carbon. In this paper we demonstrate a pathway from the renewable resource glucose to next generation biofuel isopentanol by pairing the isovaleryl-CoA biosynthesis pathway from Myxococcus xanthus and a butyryl-CoA reductase from Clostridium acetobutylicum. The best plasmid and Escherichia coli strain combination makes 80.50 ± 8.08 (SD) mg/L of isopentanol after 36 h under microaerobic conditions with an oleyl alcohol overlay. In addition, the system also shows a strong preference for isopentanol production over prenol in microaerobic conditions. Finally, the pathway requires zero adenosine triphosphate and can be paired theoretically with nonoxidative glycolysis, the combination being redox balanced from glucose thus avoiding unnecessary carbon loss as CO2. These pathway properties make the isovaleryl-CoA pathway an attractive isopentanol production route for further optimization

Tumour auto-contouring on 2d cine MRI for locally advanced lung cancer: A comparative study

BACKGROUND AND PURPOSE: Radiotherapy guidance based on magnetic resonance imaging (MRI) is currently becoming a clinical reality. Fast 2d cine MRI sequences are expected to increase the precision of radiation delivery by facilitating tumour delineation during treatment. This study compares four auto-contouring algorithms for the task of delineating the primary tumour in six locally advanced (LA) lung cancer patients. MATERIAL AND METHODS: Twenty-two cine MRI sequences were acquired using either a balanced steady-state free precession or a spoiled gradient echo imaging technique. Contours derived by the auto-contouring algorithms were compared against manual reference contours. A selection of eight image data sets was also used to assess the inter-observer delineation uncertainty. RESULTS: Algorithmically derived contours agreed well with the manual reference contours (median Dice similarity index: ⩾0.91). Multi-template matching and deformable image registration performed significantly better than feature-driven registration and the pulse-coupled neural network (PCNN). Neither MRI sequence nor image orientation was a conclusive predictor for algorithmic performance. Motion significantly degraded the performance of the PCNN. The inter-observer variability was of the same order of magnitude as the algorithmic performance. CONCLUSION: Auto-contouring of tumours on cine MRI is feasible in LA lung cancer patients. Despite large variations in implementation complexity, the different algorithms all have relatively similar performance

Modelling the effect of time varying organ deformations in head and neck cancer using a PCA model

Throughout the radiotherapy treatment process, geometrical changes in the patient often occur, e.g. organs differing in shape from that of the planning CT scan (pCT). This organ deformation leads to uncertainties in the dose distribution throughout the treatment course. We present a method to statistically model the time dependent effect of organ deformation on organ at risk (OAR) dose, with the aim of later incorporating it into advanced treatment planning methods i.e. probabilistic planning