3D single vessel fractional moving blood volume (3D-svFMBV): fully automated tissue perfusion estimation using ultrasound

Power Doppler ultrasound (PD-US) is the ideal modality to assess tissue perfusion as it is cheap, patient-friendly and does not require ionizing radiation. However, meaningful inter-patient comparison only occurs if differences in tissue-attenuation are corrected for. This can be done by standardizing the PD-US signal to a blood vessel assumed to have 100% vascularity. The original method to do this is called fractional moving blood volume (FMBV). We describe a novel, fully-automated method combining image processing, numerical modelling, and deep learning to estimate three-dimensional single vessel fractional moving blood volume (3D-svFMBV). We map the PD signals to a characteristic intensity profile within a single large vessel to define the standardization value at the high shear vessel margins. This removes the need for mathematical correction for background signal which can introduce error. The 3D-svFMBV was first tested on synthetic images generated using the characteristics of uterine artery and physiological ultrasound noise levels, demonstrating prediction of standardization value close to the theoretical ideal. Clinical utility was explored using 143 first-trimester placental ultrasound volumes. More biologically plausible perfusion estimates were obtained, showing improved prediction of pre-eclampsia compared with those generated with the semi-automated original 3D-FMBV technique. The proposed 3D-svFMBV method overcomes the limitations of the original technique to provide accurate and robust placental perfusion estimation. This not only has the potential to provide an early pregnancy screening tool but may also be used to assess perfusion of different organs and tumors

In silico modeling of oxygen-enhanced MRI of specific ventilation.

Specific ventilation imaging (SVI) proposes that using oxygen-enhanced 1H MRI to capture signal change as subjects alternatively breathe room air and 100% O2 provides an estimate of specific ventilation distribution in the lung. How well this technique measures SV and the effect of currently adopted approaches of the technique on resulting SV measurement is open for further exploration. We investigated (1) How well does imaging a single sagittal lung slice represent whole lung SV? (2) What is the influence of pulmonary venous blood on the measured MRI signal and resultant SVI measure? and (3) How does inclusion of misaligned images affect SVI measurement? In this study, we utilized two patient-based in silico models of ventilation, perfusion, and gas exchange to address these questions for normal healthy lungs. Simulation results from the two healthy young subjects show that imaging a single slice is generally representative of whole lung SV distribution, with a calculated SV gradient within 90% of that calculated for whole lung distributions. Contribution of O2 from the venous circulation results in overestimation of SV at a regional level where major pulmonary veins cross the imaging plane, resulting in a 10% increase in SV gradient for the imaging slice. A worst-case scenario simulation of image misalignment increased the SV gradient by 11.4% for the imaged slice

A review of feto-placental vasculature flow modelling

The placenta provides the vital nutrients and removal of waste products required for fetal growth and development. Understanding and quantifying the differences in structure and function between a normally functioning placenta compared to an abnormal placenta is vital to provide insights into the aetiology and treatment options for fetal growth restriction and other placental disorders. Computational modelling of blood flow in the placenta allows a new understanding of the placental circulation to be obtained. This structured review discusses multiple recent methods for placental vascular model development including analysis of the appearance of the placental vasculature and how placental haemodynamics may be simulated at multiple length scales

Protocol of the process evaluation of cluster randomised control trial for estimating the effectiveness and cost-effectiveness of a complex intervention to increase care home staff influenza vaccination rates compared to usual practice (FluCare)

Background: Influenza (flu) vaccination rates in UK care home staff are extremely low. Less than 40% of staff in care homes are vaccinated for influenza (flu), presenting risks to the health of frail residents and potential staff absence from cross-infection. Staff often do not perceive a need for vaccination and are unaware they are entitled to free flu vaccination. The FluCare study, a cluster randomised control trial (RCT), uses behavioural interventions to address barriers. Videos, posters, and leaflets are intended to raise awareness of flu vaccination benefits and debunk myths. On-site staff vaccination clinics increase accessibility. Financial incentives to care homes for improved vaccination rates and regular monitoring influence the environment. This paper outlines the planned process evaluation which will describe the intervention’s mechanisms of action, explain any changes in outcomes, identify local adaptations, and inform design of the implementation phase. Methods/design: A mixed method process evaluation to inform the interpretation of trial findings. Objectives: • Describe the intervention as delivered in terms of dose and fidelity, including adaptations and variations across care homes. • Explore the effects of individual intervention components on primary outcomes. • Investigate the mechanisms of impact. • Describe the perceived effectiveness of relevant intervention components (including videos, leaflets, posters, and flu clinics) from participant perspectives (care home manager, care home staff, flu clinic providers). • Describe the characteristics of care homes and participants to assess reach. A purposive sample of twenty care homes (ten in the intervention arm, ten in the control arm) for inclusion in the process evaluation. Data will include (1) study records including care home site profiles, (2) responses to a mechanism of action questionnaire, and (3) semi-structured interviews with care home staff and clinic providers. Quantitative data will be descriptively reported. Interview data will be thematically analysed and then categories mapped to the Theoretical Domains Framework. Discussion: Adopting this systematic and comprehensive process evaluation approach will help ensure data is captured on all aspects of the trial, enabling a full understanding of the intervention implementation and RCT findings

FluCare: Results from a randomised feasibility study of a complex intervention to increase care home staff influenza vaccination rates

Background: To protect care home residents, annual staff influenza vaccination uptake is recommended to be greater than 75%. In the UK it is under 40%. With barriers and enablers to care home staff flu vaccine uptake identified, the purpose of this study was to feasibility test a theory informed intervention to improve vaccination rates. Methods: This was a five-arm (one intervention, four different control) study designed to inform the development of a definitive trial protocol. The intervention comprised of videos/posters to change vaccination attitudes, on-site clinics to increase access, a financial incentive for homes to reach target, and monthly monitoring of vaccination uptake. Control arms consisted of a mix of monthly or end of the study monitoring and provision of informational materials to identify the most suitable control arm for a definitive trial. Care homes were recruited via sector associations and purposively allocated. The feasibility outcomes were: ability to recruit enough homes; data quality (variables reported, variable completeness and consistency with a national reporting system); intervention implementation; control arm reactivity bias and signal of efficacy. Staff vaccination data was collated from homes and via a national healthcare tracking system. Process evaluation and economic data collation were undertaken to optimise intervention and research design. Results: Ten homes were recruited as per target within 11 weeks. Recruitment delays meant intervention delivery began towards end of flu season. Only 2 clinics took place in each home. All homes in intervention and chosen control arm (monthly monitoring only) reported all variables with over 90% completeness. There was a 15% difference between control homes’ reported vaccination rates and that in the national healthcare tracker, home reported data was more reliable. Signal of efficacy: intervention arm had a vaccination rate 13.6% higher than control arm. Bias: control arm did not have a higher vaccination rate than usual care control. Conclusions: Better recruitment processes, earlier start in flu season, and data collection direct from care homes are required for a definitive trial. A control arm of monthly monitoring only was identified as optimal for data collection purposes and minimising reactivity bias. The signal of efficacy was acceptable

Cluster randomised control trial protocol for estimating the effectiveness and cost-effectiveness of a complex intervention to increase care home staff influenza vaccination rates compared to usual practice (FLUCARE)

The care home staff influenza vaccination rate in England is significantly lower than the 75% World Health Organisation recommendation. This represents a substantial potential for resident harm. Barriers to staff vaccination stem from individual and organisational levels. Existing interventions address some but not all barriers and are not underpinned by behavioural science theory. This study aims to estimate the effectiveness and cost-effectiveness of a theory-informed intervention to improve care home staff vaccination rates compared to routine practice. Set in care homes with both nursing and residential focus, and a range of ownership status, only homes providing long stay care to older people with a staff vaccination rate below 40% are eligible to participate. Participation expressions of interest will be sought using a variety of approaches prior to seeking consent. The primary outcome measure is the proportion of staff vaccinated at 6 months, with secondary outcome measures being proportion vaccinated at 3 months, numbers of staff sick days, general practitioner and nurse visits to care home, care home resident hospitalisations and mortality. Based on the assumptions that the mean cluster (care home) size is 54 staff, a coefficient of variation of 0.48, control vaccination rate is 55%, intervention 75%, intra-cluster correlation coefficient of 0.2 and with 90% power, and 20% attrition, we require 39 care homes per arm. Blocked randomisation will be at the level of care home, stratified by the proportion of non-white care home staff, and implemented by Norwich Clinical Trials Unit. The intervention comprises co-designed information videos and posters, provision of in-house staff vaccination clinics, and incentive scheme and monthly data collection on trial outcomes. Beyond usual practice, the control arm will additionally contribute monthly data. Data will be collected at the start, monthly and at 6 months, and analysis will be blind to allocation. Statistical analysis will use the intention-to-treat principle with the difference in vaccination rates between groups compared using a random effect logistic regression model at the staff-level. This will be the first study to use a theory-informed intervention designed to comprehensively address identified barriers to care home staff influenza vaccination. Trial registration: ISRCTN ISRCTN22729870. Registered on 24 August 22. Secondary identifiers: R209939, IRAS 316820, CPMS 53812

Mathematical modelling and experimental investigation of nutrient supply to the mammalian oocyte.

The harvesting of immature mammalian oocytes (eggs) and their maturation in a laboratory environment, known as in-vitro maturation (IVM), provides an alternative to the harvesting of mature oocytes for in-vitro fertilisation (IVF) programs. The nutrient environment of an oocyte matured in vitro is known to have a significant effect on its potential to successfully mature, and it is desirable for the in-vitro nutrient environment to mimic the natural environment in vivo. This thesis describes an interaction between mathematical modelling and experimental investigation designed to build upon understanding of the nutrient environment of the oocyte in vivo, which is difficult to determine via experiment alone. A general mathematical model of nutrient transport to the oocyte, through its surrounding cumulus cells is developed. This model is applicable in-vivo and in-vitro across several species and to a number of important nutrients. Nutrient transport in this system - the cumulus-oocyte complex (COC) - is of particular importance, as it is this system that is normally removed for IVM treatments, and its solution under in-vivo conditions allows the nutrient concentration reaching the oocyte to be determined, given a known concentration immediately surrounding the COC. To successfully apply this model, parameters representing the rate of nutrient transport into cells within the COC must be accurately determined. These parameters are determined by a combination of experimental procedures and mathematical modelling in the case of an important nutrient to oocyte development, glucose. This work gives insight into the concentration dependence of glucose uptake into cell types that are important in regulating oocyte development, and to the behaviour of the oocyte itself with regard to glucose uptake. Finally models to describe the transport of two key nutrients, oxygen and glucose, from the vascular system in the ovary, through the ovarian follicle to the oocyte are developed. These make use of experimental results found in the study of glucose transport in the COC, and show that the geometry of the follicle has a significant impact on the nutrient environment of the COC, and hence by inference the nutrient environment of the oocyte. Work discussed in this thesis has been published [31, 156] and submitted for publication [30].Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Science, 200

ABI_PH_Models.pptx

Presentation regarding Auckland Bioengineering progress toward subject specific modelling of pulmonary hypertensio

Proceedings of the 13th Engineering Mathematics and Applications Conference

EMAC2017 was the 13th biennial Engineering Mathematics and Applications Conference, and took place at University of Auckland, New Zealand from 29th November to 1st December 2017. EMAC is held under the auspices of the Engineering Mathematics Group which is a special interest group of the Australian and New Zealand Industrial and Applied Mathematics division of the Australian Mathematics Society. All of the articles included in the EMAC 2017 Proceedings have been peer reviewed by at least two referees and revised (when required) to satisfy the referees comments