A multi-compartment lumped-parameter model for assessing the role of haematocrit in foetal circulation

Foetal circulation, being different from neonatal and adult circulation, is an intricate system. Current knowledge of its haemodynamics is limited 1, while the role of haematocrit at different gestational ages has not yet been examined extensively. This work aims to investigate the effect of haematocrit variations using a multi-compartment lumped parameter model (LPM) of the foetal circulation. The LPM model is developed in Simulink® and includes19 elastic arterial segments and 12 peripheral vascular beds, represented, respectively, by electrical circuits and a 3-element Windkessel model 2,3. Previous data1,2and allometric laws 4 were used to calculate the inflow and boundary conditions for a 33-week gestational age and foetus weight. Two validation studies were completed, one comparing results with adult flow waveforms and another examining the foetal Isthmic Flow Index. Different values of haematocrit (Hct), ranging from 10% to 80% Hct, were investigated, representing a range of anaemic, healthy, and polycythaemic conditions. Results from the validation studies were in good agreement with literature. The foetal LPM enabled calculations of blood flow waveforms at various arterial positions. Computations with 10%, 45%, and 80% Hct were further performed to demonstrate the effect of haematocrit on the foetal arterial flow. A clear difference between the 45% and 80%Hctmodels at the position of the ascending aorta was evident, whereas no apparent difference was detected between the models for 10% and 45% Hct. Similarly, this effect was manifested at the positions of the aortic isthmus, the thoracic aorta, and the umbilical artery. However, at the position of the ductus arteriosus there was no difference between the three models. Finally, the calculations revealed an almost exponential relationship between mean resistance and Hematocrit. Investigating haematocrit variations revealed an important effect on the foetal circulation, resulting insignificant changes in vascular resistances and the pulsatility indices of the flow rate waveforms. Further investigation is required aiming at the improvement of the accuracy of the inflow and boundary conditions

Investigating the role of haematocrit in foetal circulation : a multi-compartment lumped parameter model

Foetal circulation is a complex system that differs from the corresponding neonatal and adult system. Current understanding of the foetal haemodynamics is limited1, while the role of haematocrit at different gestational ages has not yet been investigated extensively. Computational models can aid elucidate circulation haemodynamics2. To this end, this contribution proposes a multi-compartment lumped parameter model of the foetal circulatory system to investigate the effect of haematocrit variations on the systemic arterial flow

From tumour perfusion to drug delivery and clinical translation of in silico cancer models

In silico cancer models have demonstrated great potential as a tool to improve drug design, optimise the delivery of drugs to target sites in the host tissue and, hence, improve therapeutic efficacy and patient outcome. However, there are significant barriers to the successful translation of in silico technology from bench to bedside. More precisely, the specification of unknown model parameters, the necessity for models to adequately reflect in vivo conditions, and the limited amount of pertinent validation data to evaluate models' accuracy and assess their reliability, pose major obstacles in the path towards their clinical translation. This review aims to capture the state-of-the-art in in silico cancer modelling of vascularised solid tumour growth, and identify the important advances and barriers to success of these models in clinical oncology. Particular emphasis has been put on continuum-based models of cancer since they - amongst the class of mechanistic spatio-temporal modelling approaches - are well-established in simulating transport phenomena and the biomechanics of tissues, and have demonstrated potential for clinical translation. Three important avenues in in silico modelling are considered in this contribution: first, since systemic therapy is a major cancer treatment approach, we start with an overview of the tumour perfusion and angiogenesis in silico models. Next, we present the state-of-the-art in silico work encompassing the delivery of chemotherapeutic agents to cancer nanomedicines through the bloodstream, and then review continuum-based modelling approaches that demonstrate great promise for successful clinical translation. We conclude with a discussion of what we view to be the key challenges and opportunities for in silico modelling in personalised and precision medicine

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

In-silico dynamic analysis of cytotoxic drug administration to solid tumours: Effect of binding affinity and vessel permeability

The delivery of blood-borne therapeutic agents to solid tumours depends on a broad range of biophysical factors. We present a novel multiscale, multiphysics, in-silico modelling framework that encompasses dynamic tumour growth, angiogenesis and drug delivery, and use this model to simulate the intravenous delivery of cytotoxic drugs. The model accounts for chemo-, hapto- and mechanotactic vessel sprouting, extracellular matrix remodelling, mechano-sensitive vascular remodelling and collapse, intra- and extravascular drug transport, and tumour regression as an effect of a cytotoxic cancer drug. The modelling framework is flexible, allowing the drug properties to be specified, which provides realistic predictions of in-vivo vascular development and structure at different tumour stages. The model also enables the effects of neoadjuvant vascular normalisation to be implicitly tested by decreasing vessel wall pore size. We use the model to test the interplay between time of treatment, drug affinity rate and the size of the vessels endothelium pores on the delivery and subsequent tumour regression and vessel remodelling. Model predictions confirm that small-molecule drug delivery is dominated by diffusive transport and further predict that the time of treatment is important for low affinity but not high affinity cytotoxic drugs, the size of the vessel wall pores plays an important role in the effect of low affinity but not high affinity drugs, that high affinity cytotoxic drugs remodel the tumour vasculature providing a large window for the normalisation of the vascular architecture, and that the combination of large pores and high affinity enhances cytotoxic drug delivery efficiency. These results have implications for treatment planning and methods to enhance drug delivery, and highlight the importance of in-silico modelling in investigating the optimisation of cancer therapy on a personalised setting

Symmetric Biomechanically Guided Prone-to-Supine Breast Image Registration

Prone-to-supine breast image registration has potential application in the fields of surgical and radiotherapy planning, image guided interventions, and multi-modal cancer diagnosis, staging, and therapy response prediction. 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. We present a symmetric, biomechanical simulation based registration framework which aligns the images in a central, virtually unloaded configuration. The breast tissue is modelled as a neo-Hookean material and gravity is considered as the main source of deformation in the original images. In addition to gravity, our 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 avoids an explicit meshing step and enables simulations to be performed directly in the image space. The explicit time integration scheme allows the motion at the interface between chest and breast to be constrained along the chest wall. The feasibility and accuracy of the approach presented here was assessed by measuring the target registration error (TRE) using a numerical phantom with known ground truth deformations, nine clinical prone MRI and supine CT image pairs, one clinical prone-supine CT image pair and four prone-supine MRI image pairs. The registration reduced the mean TRE for the numerical phantom experiment from initially 19.3 to 0.9 mm and the combined mean TRE for all fourteen clinical data sets from 69.7 to 5.6 mm

Radiation-induced fibrosis in breast cancer: A protocol for an observational cross-sectional pilot study for personalised risk estimation and objective assessment

Introduction: About 30% of patients request breast reconstruction following surgery for breast cancer, but radiation therapy negatively influences the outcome. Post-reconstruction radiotherapy is associated with more complications, including more severe capsular contracture and inferior cosmetic results. In general, less fibrosis is seen if autologous reconstruction is performed after radiotherapy, so surgeons will often delay reconstruction until after radiotherapy is complete. Drawbacks to this approach include additional surgery, recuperation, cost, and an extended reconstructive process. Randomised clinical trials are required to determine the best approach. Methods and analysis: The aim of this cross-sectional pilot study is to see if it is feasible to recruit women, and gather the required data. This information will be used to design a subsequent, larger study whose aim is to identify factors that increase the risk of radiation-induced fibrosis, and use these to develop a personalised risk-prediction tool, to enable the clinician and patient to have a more informed discussion when treatment for breast cancer is being discussed. Identification of the risk factors will also enable the development of methods to minimise the risk, which would have applications in other medical conditions where fibrosis is a problem. In addition, the project will develop objective methods of assessing fibrosis, and will determine the psychological and economic impacts that fibrosis has affected individuals. A better understanding of the long-term effects of radiotherapy on normal tissues such as the heart and lungs may also have applications in other medical conditions where fibrosis is a problem. Ethics and dissemination: The study has been submitted for ethical approval (REC reference). Findings will be made available to patients and clinicians through presentations at national and international meetings, peer-reviewed publications, social media and patient support groups

Tapering Analysis of Airways with Bronchiectasis

Bronchiectasis is the permanent dilation of airways. Patients with the disease can suffer recurrent exacerbations, reducing their quality of life. The gold standard to diagnose and monitor bronchiectasis is accomplished by inspection of chest computed tomography (CT) scans. A clinician examines the broncho-arterial ratio to determine if an airway is brochiectatic. The visual analysis assumes the blood vessel diameter remains constant, although this assumption is disputed in the literature. We propose a simple measurement of tapering along the airways to diagnose and monitor bronchiectasis. To this end, we constructed a pipeline to measure the cross-sectional area along the airways at contiguous intervals, starting from the carina to the most distal point observable. Using a phantom with calibrated 3D printed structures, the precision and accuracy of our algorithm extends to the sub voxel level. The tapering measurement is robust to bifurcations along the airway and was applied to chest CT images acquired in clinical practice. The result is a statistical difference in tapering rate between airways with bronchiectasis and controls

Surface Driven Biomechanical Breast Image Registration

Biomechanical modelling enables large deformation simulations of breast tissues under different loading conditions to be performed. Such simulations can be utilised to transform prone Magnetic Resonance (MR) images into a different patient position, such as upright or supine. We present a novel integration of biomechanical modelling with a surface registration algorithm which optimises the unknown material parameters of a biomechanical model and performs a subsequent regularised surface alignment. This allows deformations induced by effects other than gravity, such as those due to contact of the breast and MR coil, to be reversed. Correction displacements are applied to the biomechanical model enabling transformation of the original pre-surgical images to the corresponding target position. The algorithm is evaluated for the prone-to-supine case using prone MR images and the skin outline of supine Computed Tomography (CT) scans for three patients. A mean target registration error (TRE) of 10:9 mm for internal structures is achieved. For the prone-to-upright scenario, an optical 3D surface scan of one patient is used as a registration target and the nipple distances after alignment between the transformed MRI and the surface are 10:1 mm and 6:3 mm respectively