Non-invasive MR imaging of inflammation in a patient with both asymptomatic carotid atheroma and an abdominal aortic aneurysm: A case report

Inflammation is a recognized risk factor for the vulnerable atherosclerotic plaque. USPIO-enhanced MRI imaging is a promising non-i nvasive method to identify high-risk atheromatous plaque inflammation in vivo in humans, in which areas of focal signal loss on MR images have been shown to correspond to the location of activated macrophages, typically at the shoulder regions of the plaque. This is the first report in humans describing simultaneous USPIO uptake within atheroma in two different arterial territories and again emphasises that atherosclerosis is a truly systemic disease. With further work, USPIO-enhanced MR imaging may be useful in identifying inflamed vulnerable atheromatous plaques in vivo, so refining patient selection for intervention and allowing appropriate early aggressive pharmacotherapy to prevent plaque rupture.

Staff perspectives of a cardiology short stay unit

Objective To evaluate staff perceptions about working environment, efficiency and the clinical safety of a cardiovascular intervention short stay unit (SSU) during the first year of operation. Design Postal questionnaire. Setting Cardiac catheterisation laboratory (CCL), coronary care unit (CCU), general cardiology ward (GCW) and the short stay unit (SSU) of a tertiary referral hospital situated in the mid coastal region of NSW. Subjects Cardiologists (including visiting medical officers [VMO]), cardiology fellows, cardiology advanced trainees and nurses. Results Responses on the working environment of the SSU and the discharge process were statistically significant. A substantial proportion of both nurses and doctors had concerns about patient safety, even though no adverse events were formally recorded in the database. Conclusions Though the participants of the survey agree on the efficiency of the SSU in providing beds to the hospital, they disagree on aspects that are important in the functioning of the SSU, including the working environment, patient selection and clinical safety. The results highlight potential issues that could be improved or addressed and are relevant to the rollout of SSUs across NSW.

Recruiting older adults to health research studies : a systematic review

Objective: To provide a systematic review of papers comparing the effectiveness of different strategies to recruit older adults (aged 50 years and over) to participate in health research studies, to guide successful recruitment in future research. Methods: Four major databases were searched for papers published between 1995 and 2008 with: target group aged 50 years or over; participants allocated to receive one of two or more recruitment strategies; and an outcome measure of response rate or enrolment in study. Results: Twelve papers were included in the review. Conclusion: For postal questionnaires, recruitment strategies used with older adults had comparable outcomes to those used to recruit from the general population. For other types of studies, strategies involving face-to-face contact may be more effective than indirect methods, but this needs to be balanced against feasibility. Overall, little evidence on the topic exists and more rigorous investigation is necessary.

Phase II clinical trial of first or second-line treatment with bortezomib in patients with malignant pleural mesothelioma

Based on promising preclinical efficacy of bortezomib in mesothelioma, a single-arm phase II trial (Ireland Cooperative Oncology Research Group 05-10 study), with Simon's two-stage design, was undertaken to assess efficacy of bortezomib monotherapy in the first-line (poor performance status) and second-line settings. The Bcl-2 homology domain 3-only protein Noxa has been implicated as a key inducer of apoptosis by bortezomib. Thus, in a biomarker research substudy, we hypothesized that deficiency in Noxa expression might correlate with resistance. In the second-line setting, 23 patients were enrolled. Partial response was confirmed in one patient (4.8%) who received four cycles of bortezomib. One patient had stable disease; however, progression occurred in the majority of patients within the first two cycles. Median progression-free survival and overall survival were 2.1 and 5.8 months, respectively. In the first-line setting, ten patients were accrued, and there was no evidence of objective response. In the tumor analysis, expression of Noxa was seen in all biopsies. Bortezomib monotherapy exhibits insufficient activity to warrant further investigation in unselected patients with mesothelioma. © 2012 by the International Association for the Study of Lung.

The role of the molecular footprint of EGFR in tailoring treatment decisions in NSCLC

The majority of patients with non-small-cell lung cancer (NSCLC) present with advanced disease, with targeted therapies providing some improvement in clinical outcomes. The epidermal growth factor receptor (EGFR) tyrosine kinase (TK) plays an important role in the pathogenesis of NSCLC. Tyrosine kinase inhibitors (TKIs), which target the EGFR TK domain, have proven to be an effective treatment strategy; however, patient responses to treatment vary considerably. Therefore, the identification of patients most likely to respond to treatment is essential to optimise the benefit of TKIs. Tumour-associated activating mutations in EGFR can identify patients with NSCLC who are likely to have a good response to TKIs. Nonetheless, the majority of patients relapse within a year of starting treatment. Studies of tumours at relapse have demonstrated expression of a T790M mutation in exon 20 of the EGFR TK domain in approximately 50% of cases. Although conferring resistance to reversible TKIs, these patients may remain sensitive to new-generation irreversible/panerb inhibitors. A number of techniques have been employed for genotypic assessment of tumourassociated DNA to identify EGFR mutations, each of which has advantages and disadvantages. This review presents an overview of the current methodologies used to identify such molecular markers. Recent developments in technology may make the monitoring of changes in patients' tumour genotypes easier in clinical practice, which may enable patients' treatment regimens to be tailored during the course of their disease, potentially leading to improved patient outcomes.

EGFR expression as a predictor of survival for first-line chemotherapy plus cetuximab in patients with advanced non-small-cell lung cancer : analysis of data from the phase 3 FLEX study

Background: Findings from the phase 3 First-Line ErbituX in lung cancer (FLEX) study showed that the addition of cetuximab to first-line chemotherapy significantly improved overall survival compared with chemotherapy alone (hazard ratio [HR] 0·871, 95% CI 0·762-0·996; p=0·044) in patients with advanced non-small-cell lung cancer (NSCLC). To define patients benefiting most from cetuximab, we studied the association of tumour EGFR expression level with clinical outcome in FLEX study patients. Methods: We used prospectively collected tumour EGFR expression data to generate an immunohistochemistry score for FLEX study patients on a continuous scale of 0-300. We used response data to select an outcome-based discriminatory threshold immunohistochemistry score for EGFR expression of 200. Treatment outcome was analysed in patients with low (immunohistochemistry score <200) and high (≥200) tumour EGFR expression. The primary endpoint in the FLEX study was overall survival. We analysed patients from the FLEX intention-to-treat (ITT) population. The FLEX study is registered with ClinicalTrials.gov, number NCT00148798. Findings: Tumour EGFR immunohistochemistry data were available for 1121 of 1125 (99·6%) patients from the FLEX study ITT population. High EGFR expression was scored for 345 (31%) evaluable patients and low for 776 (69%) patients. For patients in the high EGFR expression group, overall survival was longer in the chemotherapy plus cetuximab group than in the chemotherapy alone group (median 12·0 months [95% CI 10·2-15·2] vs 9·6 months [7·6-10·6]; HR 0·73, 0·58-0·93; p=0·011), with no meaningful increase in side-effects. We recorded no corresponding survival benefit for patients in the low EGFR expression group (median 9·8 months [8·9-12·2] vs 10·3 months [9·2-11·5]; HR 0·99, 0·84-1·16; p=0·88). A treatment interaction test assessing the difference in the HRs for overall survival between the EGFR expression groups suggested a predictive value for EGFR expression (p=0·044). Interpretation: High EGFR expression is a tumour biomarker that can predict survival benefit from the addition of cetuximab to first-line chemotherapy in patients with advanced NSCLC. Assessment of EGFR expression could offer a personalised treatment approach in this setting. Funding: Merck KGaA. © 2012 Elsevier Ltd.

The silent and apparent neurological injury in transcatheter aortic valve implantation study (SANITY) : concept, design and rationale

Background The incidence of clinically apparent stroke in transcatheter aortic valve implantation (TAVI) exceeds that of any other procedure performed by interventional cardiologists and, in the index admission, occurs more than twice as frequently with TAVI than with surgical aortic valve replacement (SAVR). However, this represents only a small component of the vast burden of neurological injury that occurs during TAVI, with recent evidence suggesting that many strokes are clinically silent or only subtly apparent. Additionally, insult may manifest as slight neurocognitive dysfunction rather than overt neurological deficits. Characterisation of the incidence and underlying aetiology of these neurological events may lead to identification of currently unrecognised neuroprotective strategies. Methods The Silent and Apparent Neurological Injury in TAVI (SANITY) Study is a prospective, multicentre, observational study comparing the incidence of neurological injury after TAVI versus SAVR. It introduces an intensive, standardised, formal neurologic and neurocognitive disease assessment for all aortic valve recipients, regardless of intervention (SAVR, TAVI), valve-type (bioprosthetic, Edwards SAPIEN-XT) or access route (sternotomy, transfemoral, transapical or transaortic). Comprehensive monitoring of neurological insult will also be recorded to more fully define and compare the neurological burden of the procedures and identify targets for harm minimisation strategies. Discussion The SANITY study undertakes the most rigorous assessment of neurological injury reported in the literature to date. It attempts to accurately characterise the insult and sustained injury associated with both TAVI and SAVR in an attempt to advance understanding of this complication and associations thus allowing for improved patient selection and procedural modification.

Acute liver failure in children : a regional experience

Objective: To review the outcome of acute liver failure (ALF) and the effect of liver transplantation in children in Australia. Methodology: A retrospective review was conducted of all paediatric patients referred with acute liver failure between 1985 and 2000 to the Queensland Liver Transplant Service, a paediatric liver transplant centre based at the Royal Children's Hospital, Brisbane, that is one of three paediatric transplant centres in Australia. Results: Twenty-six patients were referred with ALF. Four patients did not require transplantation and recovered with medical therapy while two were excluded because of irreversible neurological changes and died. Of the 20 patients considered for transplant, three refused for social and/or religious reasons, with 17 patients listed for transplantation. One patient recovered spontaneously and one died before receiving a transplant. There were 15 transplants of which 40% (6/15) were < 2 years old. Sixty-seven per cent (10/15) survived > 1 month after transplantation. Forty per cent (6/15) survived more than 6 months after transplant. There were only four long term survivors after transplant for ALF (27%). Overall, 27% (6/22) of patients referred with ALF survived. Of the 16 patients that died, 44% (7/16) were from neurological causes. Most of these were from cerebral oedema but two patients transplanted for valproate hepatotoxicity died from neurological disease despite good graft function. Conclusions: Irreversible neurological disease remains a major cause of death in children with ALF. We recommend better patient selection and early referral and transfer to a transplant centre before onset of irreversible neurological disease to optimize outcome of children transplanted for ALF.

Invasive and non-invasive modalities of imaging carotid stenosis

Despite recent therapeutic advances, acute ischemic complications of atherosclerosis remain the primary cause of morbidity and mortality in Western countries, with carotid atherosclerotic disease one of the major preventable causes of stroke. As the impact of this disease challenges our healthcare systems, we are becoming aware that factors influencing this disease are more complex than previously realized. In current clinical practice, risk stratification relies primarily on evaluation of the degree of luminal stenosis and patient symptomatology. Adequate investigation and optimal imaging are important factors that affect the quality of a carotid endarterectomy (CEA) service and are fundamental to patient selection. Digital subtraction angiography is still perceived as the most accurate imaging modality for carotid stenosis and historically has been the cornerstone of most of the major CEA trials but concerns regarding potential neurological complications have generated substantial interest in non-invasive modalities, such as contrast-enhanced magnetic resonance angiography. The purpose of this review is to give an overview to the vascular specialist of the current imaging modalities in clinical practice to identify patients with carotid stenosis. Advantages and disadvantages of each technique are outlined. Finally, limitations of assessing luminal stenosis in general are discussed. This article will not cover imaging of carotid atheroma morphology, function and other emerging imaging modalities of assessing plaque risk, which look beyond simple luminal measurements.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

The Early Prevention of Obesity in CHildren (EPOCH) collaboration : an individual patient data prospective meta-analysis

Background: Efforts to prevent the development of overweight and obesity have increasingly focused early in the life course as we recognise that both metabolic and behavioural patterns are often established within the first few years of life. Randomised controlled trials (RCTs) of interventions are even more powerful when, with forethought, they are synthesised into an individual patient data (IPD) prospective meta-analysis (PMA). An IPD PMA is a unique research design where several trials are identified for inclusion in an analysis before any of the individual trial results become known and the data are provided for each randomised patient. This methodology minimises the publication and selection bias often associated with a retrospective meta-analysis by allowing hypotheses, analysis methods and selection criteria to be specified a priori. Methods/Design: The Early Prevention of Obesity in CHildren (EPOCH) Collaboration was formed in 2009. The main objective of the EPOCH Collaboration is to determine if early intervention for childhood obesity impacts on body mass index (BMI) z scores at age 18-24 months. Additional research questions will focus on whether early intervention has an impact on children’s dietary quality, TV viewing time, duration of breastfeeding and parenting styles. This protocol includes the hypotheses, inclusion criteria and outcome measures to be used in the IPD PMA. The sample size of the combined dataset at final outcome assessment (approximately 1800 infants) will allow greater precision when exploring differences in the effect of early intervention with respect to pre-specified participant- and intervention-level characteristics. Discussion: Finalisation of the data collection procedures and analysis plans will be complete by the end of 2010. Data collection and analysis will occur during 2011-2012 and results should be available by 2013. Trial registration number: ACTRN12610000789066

Geometric sensitivity of patient-specific finite element models of the spine to variability in user-selected anatomical landmarks

Software to create individualised finite element (FE) models of the osseoligamentous spine using pre-operative computed tomography (CT) data-sets for spinal surgery patients has recently been developed. This study presents a geometric sensitivity analysis of this software to assess the effect of intra-observer variability in user-selected anatomical landmarks. User-selected landmarks on the osseous anatomy were defined from CT data-sets for three scoliosis patients and these landmarks were used to reconstruct patient-specific anatomy of the spine and ribcage using parametric descriptions. The intra-observer errors in landmark co-ordinates for these anatomical landmarks were calculated. FE models of the spine and ribcage were created using the reconstructed anatomy for each patient and these models were analysed for a loadcase simulating clinical flexibility assessment. The intra-observer error in the anatomical measurements was low in comparison to the initial dimensions, with the exception of the angular measurements for disc wedge and zygapophyseal joint (z-joint) orientation and disc height. This variability suggested that CT resolution may influence such angular measurements, particularly for small anatomical features, such as the z-joints, and may also affect disc height. The results of the FE analysis showed low variation in the model predictions for spinal curvature with the mean intra-observer variability substantially less than the accepted error in clinical measurement. These findings demonstrate that intra-observer variability in landmark point selection has minimal effect on the subsequent FE predictions for a clinical loadcase.

Development of reverse phase protein microarrays for clinical applications and patient-tailored therapy

While genomics provide important information about the somatic genetic changes, and RNA transcript profiling can reveal important expression changes that correlate with outcome and response to therapy, it is the proteins that do the work in the cell. At a functional level, derangements within the proteome, driven by post-translational and epigenetic modifications, such as phosphorylation, is the cause of a vast majority of human diseases. Cancer, for instance, is a manifestation of deranged cellular protein molecular networks and cell signaling pathways that are based on genetic changes at the DNA level. Importantly, the protein pathways contain the drug targets in signaling networks that govern overall cellular survival, proliferation, invasion and cell death. Consequently, the promise of proteomics resides in the ability to extend analysis beyond correlation to causality. A critical gap in the information knowledge base of molecular profiling is an understanding of the ongoing activity of protein signaling in human tissue: what is activated and “in use” within the human body at any given point in time. To address this gap, we have invented a new technology, called reverse phase protein microarrays, that can generate a functional read-out of cell signaling networks or pathways for an individual patient obtained directly from a biopsy specimen. This “wiring diagram” can serve as the basis for both, selection of a therapy and patient stratification.

Supine to standing Cobb angle change in idiopathic scoliosis : the effect of endplate pre-selection

Background Supine imaging modalities provide valuable 3D information on scoliotic anatomy, but the altered spine geometry between the supine and standing positions affects the Cobb angle measurement. Previous studies report a mean 7°-10° Cobb angle increase from supine to standing, but none have reported the effect of endplate pre-selection or whether other parameters affect this Cobb angle difference. Methods Cobb angles from existing coronal radiographs were compared to those on existing low-dose CT scans taken within three months of the reference radiograph for a group of females with adolescent idiopathic scoliosis. Reformatted coronal CT images were used to measure supine Cobb angles with and without endplate pre-selection (end-plates selected from the radiographs) by two observers on three separate occasions. Inter and intra-observer measurement variability were assessed. Multi-linear regression was used to investigate whether there was a relationship between supine to standing Cobb angle change and eight variables: patient age, mass, standing Cobb angle, Risser sign, ligament laxity, Lenke type, fulcrum flexibility and time delay between radiograph and CT scan. Results Fifty-two patients with right thoracic Lenke Type 1 curves and mean age 14.6 years (SD 1.8) were included. The mean Cobb angle on standing radiographs was 51.9° (SD 6.7). The mean Cobb angle on supine CT images without pre-selection of endplates was 41.1° (SD 6.4). The mean Cobb angle on supine CT images with endplate pre-selection was 40.5° (SD 6.6). Pre-selecting vertebral endplates increased the mean Cobb change by 0.6° (SD 2.3, range −9° to 6°). When free to do so, observers chose different levels for the end vertebrae in 39% of cases. Multi-linear regression revealed a statistically significant relationship between supine to standing Cobb change and fulcrum flexibility (p = 0.001), age (p = 0.027) and standing Cobb angle (p < 0.001). The 95% confidence intervals for intra-observer and inter-observer measurement variability were 3.1° and 3.6°, respectively. Conclusions Pre-selecting vertebral endplates causes minor changes to the mean supine to standing Cobb change. There is a statistically significant relationship between supine to standing Cobb change and fulcrum flexibility such that this difference can be considered a potential alternative measure of spinal flexibility.