Patient-specific model of brain deformation: application to medical image registration

This contribution presents finite element computation of the deformation field within the brain during craniotomy-induced brain shift. The results were used to illustrate the capabilities of non-linear (i.e. accounting for both geometric and material non-linearities) finite element analysis in non-rigid registration of pre- and intra-operative magnetic resonance images of the brain. We used patient-specific hexahedron-dominant finite element mesh, together with realistic material properties for the brain tissue and appropriate contact conditions at boundaries. The model was loaded by the enforced motion of nodes (i.e. through prescribed motion of a boundary) at the brain surface in the craniotomy area. We suggest using explicit time-integration scheme for discretised equations of motion, as the computational times are much shorter and accuracy, for practical purposes, the same as in the case of implicit integration schemes. Application of the computed deformation field to register (i.e. align) the pre-operative images with the intra-operative ones indicated that the model very accurately predicts the displacements of the tumour and the lateral ventricles even for limited information about the brain surface deformation. The prediction accuracy improves when information about deformation of not only exposed (during craniotomy) but also unexposed parts of the brain surface is used when prescribing loading. However, it appears that the accuracy achieved using information only about the deformation of the exposed surface, that can be determined without intra-operative imaging, is acceptable. The presented results show that non-linear biomechanical models can complement medical image processing techniques when conducting non-rigid registration. Important advantage of such models over the previously used linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain stress-strain relationship is linear.     

Patient-specific modelling of the foot: automated hexahedral meshing of the bones

Subject-specific finite element modelling is a powerful tool for carrying out controlled investigations of the effects of geometric and material property differences on performance and injury risk. Unfortunately, the creation of suitable meshes for these models is a challenging and time-intensive task. This paper presents an automated method of generating fully hexahedral meshes of the bones of the feet which requires only surface representations as inputs. The method is outlined and example meshes, using two human feet and the foot of a Japanese macaque, are given to demonstrate its flexibility. Mesh quality is also evaluated for the calcaneus, first metatarsal, navicular and talus. Streamlining the generation of finite element meshes of the foot will ease investigations into the patient-specific biomechanics of injury.     

Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time; Application to non-rigid neuroimage registration

Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer.     

Modeling of airflow in the pharynx with application to sleep apnea.

A three-dimensional numerical modeling of airflow in the human pharynx using an anatomically accurate model was conducted. The pharynx walls were assumed to be passive and rigid. The results showed that the pressure drop in the pharynx lies in the range 200-500 Pa. The onset of turbulence was found to increase the pressure drop by 40 percent. A wide range of pharynx geometries covering three sleep apnea treatment therapies (CPAP, mandibular repositioning devices, and surgery) were modeled and the resulting flow characteristics were investigated and compared. The results confirmed that the airflow in the pharynx lies in the laminar-to-turbulence transitional flow regime and thus, a subtle change in the morphology caused by these treatment therapies can significantly affect the airflow characteristics.     

A variational Bayesian mixture modelling framework for cluster analysis of gene-expression data

MOTIVATION: Accurate subcategorization of tumour types through gene-expression profiling requires analytical techniques that estimate the number of categories or clusters rigorously and reliably. Parametric mixture modelling provides a natural setting to address this problem. RESULTS: We compare a criterion for model selection that is derived from a variational Bayesian framework with a popular alternative based on the Bayesian information criterion. Using simulated data, we show that the variational Bayesian method is more accurate in finding the true number of clusters in situations that are relevant to current and future microarray studies. We also compare the two criteria using freely available tumour microarray datasets and show that the variational Bayesian method is more sensitive to capturing biologically relevant structure.     

Measures for assessing practice change in medical practitioners

Background

A randomised trial of a multifaceted intervention for improving adherence to clinical practice guidelines for the pharmacological management of hypertension and hypercholesterolemia increased prescribing of thiazides, butdetected no impact onthe use of cardiovascular risk assessment toolsor achievement of treatment targets. We carried out a predominantly quantitative process evaluation to help explain and interpret the trial-findings.

Methods

Several data-sources were used including: questionnaires completed by pharmacists immediately after educational outreach visits, semi-structured interviews with physicians subjected to the intervention, and data extracted from their electronic medical records. Multivariate regression analyses were conducted to explore the association between possible explanatory variables and the observed variation across practices for the three main outcomes.

Results

The attendance rate during the educational sessions in each practice was high; few problems were reported, and the physicians were perceived as being largely supportive of the recommendations we promoted, except for some scepticism regarding the use of thiazides as first-line antihypertensive medication. Multivariate regression models could explain only a small part of the observed variation across practices and across trial-outcomes, and key factors that might explain the observed variation in adherence to the recommendations across practices were not identified.

Conclusion

This study did not provide compelling explanations for the trial results. Possible reasons for this include a lack of statistical power and failure to include potential explanatory variables in our analyses, particularly organisational factors. More use of qualitative research methods in the course of the trial could have improved our understanding.     

Response of pulmonary circulation to oral pirbuterol in chronic airflow obstruction.

The effects of the oral beta agonist pirbuterol on pulmonary haemodynamics and gas exchange were studied in nine patients with severe irreversible airflow obstruction and moderate arterial hypoxaemia. After administration of 15 mg pirbuterol pulmonary vascular resistance fell by 19% but cardiac output rose by 24%, so that pulmonary arterial pressure showed no significant change. Systemic arterial oxygen pressure fell by 7%, limiting the rise in oxygen delivery to 21%. All changes were significant at the 2% level. These results show that pirbuterol dilates the pulmonary bed at the cost of a slight worsening of gas exchange, which is compensated by an independent rise in blood flow.     

Patient-specific stress analyses in the ascending thoracic aorta using a finite-element implementation of the constrained mixture theory

It is now a rather common approach to perform patient-specific stress analyses of arterial walls using finite-element models reconstructed from gated medical images. However, this requires to compute for every Gauss point the deformation gradient between the current configuration and a stress-free reference configuration. It is technically difficult to define such a reference configuration, and there is actually no guarantee that a stress-free configuration is physically attainable due to the presence of internal stresses in unloaded soft tissues. An alternative framework was proposed by Bellini et al. (Ann Biomed Eng 42(3):488–502, 2014). It consists of computing the deformation gradients between the current configuration and a prestressed reference configuration. We present here the first finite-element results based on this concept using the Abaqus software. The reference configuration is set arbitrarily to the in vivo average geometry of the artery, which is obtained from gated medical images and is assumed to be mechanobiologically homeostatic. For every Gauss point, the stress is split additively into the contributions of each individual load-bearing constituent of the tissue, namely elastin, collagen, smooth muscle cells. Each constituent is assigned an independent prestretch in the reference configuration, named the deposition stretch. The outstanding advantage of the present approach is that it simultaneously computes the in situ stresses existing in the reference configuration and predicts the residual stresses that occur after removing the different loadings applied onto the artery (pressure and axial load). As a proof of concept, we applied it on an ideal thick-wall cylinder and showed that the obtained results were consistent with corresponding experimental and analytical results of the well-known literature. In addition, we developed a patient-specific model of a human ascending thoracic aneurysmal aorta and demonstrated the utility in predicting the wall stress distribution in vivo under the effects of physiological pressure. Finally, we simulated the whole process preceding traditional in vitro uniaxial tensile testing of arteries, including excision from the body, radial cutting, flattening and subsequent tensile loading, showing how this process may impact the final mechanical properties derived from these in vitro tests.     

A pragmatic cluster randomized controlled trial of early intervention for chronic obstructive pulmonary disease by practice nurse-general practitioner teams: Study Protocol

ABSTRACT: BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of disability, hospitalization, and premature mortality. General practice is well placed to diagnose and manage COPD, but there is a significant gap between evidence and current practice, with a low level of awareness and implementation of clinical practice guidelines. Under-diagnosis of COPD is a world-wide problem, limiting the benefit that could potentially be achieved through early intervention strategies such as smoking cessation, dietary advice, and exercise. General practice is moving towards more structured chronic disease management, and the increasing involvement of practice nurses in delivering chronic care. DESIGN: A pragmatic cluster randomised trial will test the hypothesis that intervention by a practice nurse-general practitioner (GP) team leads to improved health-related quality of life and greater adherence with clinical practice guidelines for patients with newly-diagnosed COPD, compared with usual care. Forty general practices in greater metropolitan Sydney Australia will be recruited to identify patients at risk of COPD and invite them to attend a case finding appointment. Practices will be randomised to deliver either practice nurse-GP partnership care, or usual care, to patients newly-diagnosed with COPD. The active intervention will involve the practice nurse and GP working in partnership with the patient in developing and implementing a care plan involving (as appropriate), smoking cessation, immunisation, pulmonary rehabilitation, medication review, assessment and correction of inhaler technique, nutritional advice, management of psycho-social issues, patient education, and management of co-morbidities. The primary outcome measure is health-related quality of life, assessed with the St George's Respiratory Questionnaire 12 months after diagnosis. Secondary outcome measures include validated disease-specific and general health related quality of life measures, smoking and immunisation status, medications, inhaler technique, and lung function. Outcomes will be assessed by project officers blinded to patients' randomization groups. DISCUSSION: This study will use proven case-finding methods to identify patients with undiagnosed COPD in general practice, where improved care has the potential for substantial benefit in health and healthcare utilization. The study provides the capacity to trial a new model of team-based assessment and management of newly diagnosed COPD in Australian primary care. Trial registration ACTRN12610000592044     

Electrophysiological modelling of pulmonary artery smooth muscle cells in the rabbits--special consideration to the generation of hypoxic pulmonary vasoconstriction

In vascular smooth muscle cells, it has been suggested that membrane potential is an important component that initiates contraction. We developed a mathematical model to elucidate the quantitative contributions of major ion currents [a voltage-gated L-type Ca²⁺ current (I_CaL), a voltage-sensitive K⁺ current (I_KV), a Ca²⁺-activated K⁺ current (I_KCa) and a nonselective cation current (I_NSC)] to membrane potential. In order to typify the diverse nature of pulmonary artery smooth muscle cells (PASMCs), we introduced parameters that are not fixed (variable parameters). The population of cells with different parameters was constructed and the cells that have the electrophysiological properties of PASMCs were selected. The contributions of each membrane current were investigated by sensitivity analysis and modification of the current parameters. Consequently, I_KV and I_NSC were found to be the most important currents that affect the membrane potential. The occurrence of depolarisation in hypoxic pulmonary vasoconstriction (HPV) was also examined. In hypoxia, I_KV and I_KCa were reduced, but the consequent depolarisation in simulation was not enough to initiate contractions. If we add an increase of I_NSC (2.5-fold), the calculated membrane potential was enough to induce contraction. From the results, we conclude that the balance of various ion channel activities determines the resting membrane potential of PASMCs and our model was successful in explaining the depolarisation in HPV. Therefore, this model can be a powerful tool to investigate the various electrical properties of PASMCs in both normal and pathological conditions.     

A program for the application of the radial distribution function to cluster analysis in cell biology

The radial distribution function g(r) is one measure of spatialpattern commonly used in statistical physics to analyze thestructure of liquids and has been used in several cellular systems.The graphs of the radial distribution function present threedifferent functional forms. The first form indicates a randomdistribution; in the second form the graph is characteristicof the cluster distribution; and the third type is characteristicof substantial order. The Funct_G program uses the coordinates(x,y) of each point on m photographs to calculate the radialdistribution function g(r) and produce a histogram to analyzegraphically this function and to define the distribution model.