Self-reported transvaginal ultrasound visualization of normal ovaries in postmenopausal women is not reliable: results of expert review of archived images in UKCTOCS.

OBJECTIVE: In UKCTOCS self-reported visualization rates(srVR) at annual TVS scan was a key quality control(QC) metric. Our objective was to independently assess srVR using expert review and develop software capable of monitoring it. METHODS: Images from 1,000 examinations randomly selected from 68,951 archived annual TVS exams undertaken between 2008-2011 where the ovaries were reported as 'seen and normal' were reviewed by a single expert. Software was developed to identify exact images used to measure ovaries by measuring caliper dimensions and matching them to that recorded by the sonographer. A logistic regression classifier to determine visualization was trained and validated using ovarian dimension and visualization data reported by the expert . RESULTS: The expert confirmed both ovaries were visualized (cVR-Both) in 50.2%(502/1000) of the exams. The software identified the measurement image in 534 exams which were split 2:1:1 providing training, validating and testing data. Classifier accuracy on validation data was 70.9%(CI-95% 70.0,71.8). Analysis of test data (133 exams) resulted in sensitivity of 90.5%(CI-95% 80.9,95.8) and specificity of 47.5%(CI-95% 34.5,60.8) in detecting expert confirmed cVR-Both. CONCLUSIONS: Our results suggest that in a significant proportion of TVS annual screens the sonographers may have mistaken other structures for normal ovaries. It is uncertain whether or not this affected the sensitivity and stage at detection of ovarian cancer in the ultrasound arm of UKCTOCS, but we conclude QC metrics based on self-reported visualization of normal ovaries are unreliable. The classifier shows some potential for addressing this problem, though further research is needed

Sonographers' self-reported visualization of normal postmenopausal ovaries on transvaginal ultrasound is not reliable: results of expert review of archived images from UKCTOCS.

OBJECTIVE: In the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), self-reported visualization rate (VR) of the ovaries by the sonographer on annual transvaginal sonographic (TVS) examinations was a key quality control (QC) metric. The objective of this study was to assess self-reported VR using expert review of a random sample of archived images of TVS examinations from UKCTOCS, and then to develop software for measuring VR automatically. METHODS: A single expert reviewed images archived from 1000 TVS examinations selected randomly from 68 931 TVS scans performed in UKCTOCS between 2008 and 2011 with ovaries reported as 'seen and normal'. Software was developed to identify the exact images used by the sonographer to measure the ovaries. This was achieved by measuring caliper dimensions in the image and matching them to those recorded by the sonographer. A logistic regression classifier to determine visualization was trained and validated using ovarian dimensions and visualization data reported by the expert. RESULTS: The expert reviewer confirmed visualization of both ovaries (VR-Both) in 50.2% (502/1000) of the examinations. The software identified the measurement image in 534 exams, which were split 2:1:1 providing training, validation and test data. Classifier mean accuracy on validation data was 70.9% (95% CI, 70.0-71.8%). Analysis of test data (133 exams) provided a sensitivity of 90.5% (95% CI, 80.9-95.8%) and specificity of 47.5% (95% CI, 34.5-60.8%) in detecting expert confirmed visualization of both ovaries. CONCLUSIONS: Our results suggest that, in a significant proportion of TVS annual screens, the sonographers may have mistaken other structures for normal ovaries. It is uncertain whether or not this affected the sensitivity and stage at detection of ovarian cancer in the ultrasound arm of UKCTOCS, but we conclude that QC metrics based on self-reported visualization of normal ovaries are unreliable. The classifier shows some potential for addressing this problem, though further research is needed. © 2017 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology

Towards a novel biologically-inspired cloud elasticity framework

With the widespread use of the Internet, the popularity of web applications has significantly increased. Such applications are subject to unpredictable workload conditions that vary from time to time. For example, an e-commerce website may face higher workloads than normal during festivals or promotional schemes. Such applications are critical and performance related issues, or service disruption can result in financial losses. Cloud computing with its attractive feature of dynamic resource provisioning (elasticity) is a perfect match to host such applications. The rapid growth in the usage of cloud computing model, as well as the rise in complexity of the web applications poses new challenges regarding the effective monitoring and management of the underlying cloud computational resources. This thesis investigates the state-of-the-art elastic methods including the models and techniques for the dynamic management and provisioning of cloud resources from a service provider perspective. An elastic controller is responsible to determine the optimal number of cloud resources, required at a particular time to achieve the desired performance demands. Researchers and practitioners have proposed many elastic controllers using versatile techniques ranging from simple if-then-else based rules to sophisticated optimisation, control theory and machine learning based methods. However, despite an extensive range of existing elasticity research, the aim of implementing an efficient scaling technique that satisfies the actual demands is still a challenge to achieve. There exist many issues that have not received much attention from a holistic point of view. Some of these issues include: 1) the lack of adaptability and static scaling behaviour whilst considering completely fixed approaches; 2) the burden of additional computational overhead, the inability to cope with the sudden changes in the workload behaviour and the preference of adaptability over reliability at runtime whilst considering the fully dynamic approaches; and 3) the lack of considering uncertainty aspects while designing auto-scaling solutions. This thesis seeks solutions to address these issues altogether using an integrated approach. Moreover, this thesis aims at the provision of qualitative elasticity rules. This thesis proposes a novel biologically-inspired switched feedback control methodology to address the horizontal elasticity problem. The switched methodology utilises multiple controllers simultaneously, whereas the selection of a suitable controller is realised using an intelligent switching mechanism. Each controller itself depicts a different elasticity policy that can be designed using the principles of fixed gain feedback controller approach. The switching mechanism is implemented using a fuzzy system that determines a suitable controller/- policy at runtime based on the current behaviour of the system. Furthermore, to improve the possibility of bumpless transitions and to avoid the oscillatory behaviour, which is a problem commonly associated with switching based control methodologies, this thesis proposes an alternative soft switching approach. This soft switching approach incorporates a biologically-inspired Basal Ganglia based computational model of action selection. In addition, this thesis formulates the problem of designing the membership functions of the switching mechanism as a multi-objective optimisation problem. The key purpose behind this formulation is to obtain the near optimal (or to fine tune) parameter settings for the membership functions of the fuzzy control system in the absence of domain experts’ knowledge. This problem is addressed by using two different techniques including the commonly used Genetic Algorithm and an alternative less known economic approach called the Taguchi method. Lastly, we identify seven different kinds of real workload patterns, each of which reflects a different set of applications. Six real and one synthetic HTTP traces, one for each pattern, are further identified and utilised to evaluate the performance of the proposed methods against the state-of-the-art approaches

Ovarian cancer symptoms in pre-clinical invasive epithelial ovarian cancer - An exploratory analysis nested within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).

OBJECTIVE: UKCTOCS provides an opportunity to explore symptoms in preclinical invasive epithelial ovarian cancer (iEOC). We report on symptoms in women with pre-clinical (screen-detected) cancers (PC) compared to clinically diagnosed (CD) cancers. METHODS: In UKCTOCS, 202638 postmenopausal women, aged 50-74 were randomly allocated (April 17, 2001-September 29, 2005) 2:1:1 to no screening or annual screening till Dec 31,2011, using a multimodal or ultrasound strategy. Follow-up was through national registries. An outcomes committee adjudicated on OC diagnosis, histotype, stage. Eligible women were those diagnosed with iEOC at primary censorship (Dec 31, 2014). Symptom details were extracted from trial clinical-assessment forms and medical records. Descriptive statistics were used to compare symptoms in PC versus CD women with early (I/II) and advanced (III/IV/unable to stage) stage high-grade-serous (HGSC) cancer. ISRCTN-22488978; ClinicalTrials.gov-NCT00058032. RESULTS: 1133 (286PC; 847CD) women developed iEOC. Median age (years) at diagnosis was earlier in PC compared to CD (66.8PC, 68.7CD, p = 0.0001) group. In the PC group, 48% (112/234; 90%, 660/730CD) reported symptoms when questioned. Half PC (50%, 13/26PC; 36%, 29/80CD; p = 0.213) women with symptomatic HGSC had >1symptom, with abdominal symptoms most common, both in early (62%, 16/26, PC; 53% 42/80, CD; p = 0.421) and advanced (57%, 49/86, PC; 74%, 431/580, CD; p = 0.001) stages. In symptomatic early-stage HGSC, compared to CD, PC women reported more gastrointestinal (change in bowel habits and dyspepsia) (35%, 9/26PC; 9%, 7/80CD; p = 0.001) and systemic (mostly lethargy/tiredness) (27%, 7/26PC; 9%, 7/80CD; p = 0.017) symptoms. CONCLUSIONS: Our findings, add to the growing evidence, that we should reconsider what constitutes alert symptoms for early tubo-ovarian cancer. We need a more nuanced complex of key symptoms which is then evaluated and refined in a prospective trial

Exploring relationships between land use intensity, habitat heterogeneity and biodiversity to identify and monitor areas of High Nature Value farming

Understanding how species richness is distributed across landscapes and which variables may be used as predictors is important for spatially targeting management interventions. This study uses finely resolved data over a large geographical area to explore relationships between land-use intensity, habitat heterogeneity and species richness of multiple taxa. It aims to identify surrogate landscape metrics, valid for a range of taxa, which can be used to map and monitor High Nature Value farmland (HNV). Results show that variation in species richness is distributed along two axes: land-use intensity and habitat heterogeneity. At low intensity land-use, species rich groups include wetland plants, plant habitat indicators, upland birds and rare invertebrates, whilst richness of other species groups (farmland birds, butterflies, bees) was associated with higher land-use intensity. Habitat heterogeneity (broadleaved woodland connectivity, hedgerows, habitat diversity) was positively related to species richness of many taxa, both generalists (plants, butterflies, bees) and specialists (rare birds, woodland birds, plants, butterflies). The results were used to create maps of HNV farmland. The proportion of semi-natural vegetation is a useful metric for identifying HNV type 1. HNV type 2 (defined as a mosaic of low-intensity habitats and structural elements) is more difficult to predict from surrogate variables, due to complex relationships between biodiversity and habitat heterogeneity and inadequacies of current remotely sensed data. This approach, using fine-scaled field survey data collected at regular intervals, in conjunction with remotely sensed data offers potential for extrapolating modelled results nationally, and importantly, can be used to assess change over time

The cost-effectiveness of screening for ovarian cancer: results from the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS)

Background: To assess the within trial cost-effectiveness of an NHS ovarian cancer screening (OCS) programme using data from UKCTOCS and extrapolate results based on average life expectancy. Methods: Within trial economic evaluation of no screening (C) versus either (1) an annual OCS programme using transvaginal ultrasound (USS) or (2) an annual ovarian cancer multimodal screening programme with serum CA125 interpreted using a risk algorithm (ROCA) and transvaginal ultrasound as a second line test (MMS), plus comparison of lifetime extrapolation of the no screening arm and the MMS programme using both a predictive and a Markov model. Results: Using a CA125-ROCA cost of £20, the within trial results show USS to be strictly dominated by MMS, with the MMS versus C comparison returning an Incremental Cost-Effectiveness ratio (ICER) of £91,452 per life year gained (LYG). If the CA125-ROCA unit cost is reduced to £15 the ICER becomes £77,818 per LYG. Predictive extrapolation over the expected lifetime of the UKCTOCS women returns an ICER of £30,033 per LYG, while Markov modelling produces an ICER of £46,922 per QALY. Conclusions: Analysis suggests that, after accounting for the lead-time required to establish full mortality benefits, a national OCS programme based on the MMS strategy quickly approaches the current NICE thresholds for cost-effectiveness when extrapolated out to lifetime as compared to the within trial ICER estimates. Whether MMS could be recommended on economic grounds would depend on the confirmation and size of the mortality benefit at the end of an ongoing follow-up of the UKCTOCS cohort

Alteration of the serum levels of the epidermal growth factor receptor and its ligands in patients with non-small cell lung cancer and head and neck carcinoma

Serum levels of the soluble epidermal growth factor receptor (sEGFR) and its ligands epidermal growth factor (EGF), transforming growth factor-α (TGF-α) and amphiregulin (AR) were measured in healthy donors and patients with non-small cell lung cancer (NSCLC) and head and neck carcinoma (HNC). In NSCLC, we found sEGFR and EGF levels significantly lowered in patients with respect to healthy donors. In HNC patients, significantly diminished levels were found in the case of sEGFR, EGF and also AR. In both malignancies, no significant association was found between the serum levels of the molecules and the patients' gender, age or smoking habit. Only a significant association was found between the decrease of sEGFR and the absence of distant metastasis in NSCLC and the tumour stage in HNC. The most interesting result was that combining sEGFR and EGF, sensitivities of 88% in NSCLC and 100% in HNC were reached without losing specificity (97.8% in both cases). The use of discriminant analysis and logistic regression improved the sensitivity for NSCLC and the specificity for HNC. These data demonstrate a potentially interesting value of the serum levels of sEGFR and EGF, especially when combined, as markers for NSCLC and HNC

Claudin-containing exosomes in the peripheral circulation of women with ovarian cancer

<p>Abstract</p> <p>Background</p> <p>The absence of highly sensitive and specific serum biomarkers makes mass screening for ovarian cancer impossible. The claudin proteins are frequently overexpressed in ovarian cancers, but their potential as prognostic, diagnostic, or detection markers remains unclear. Here, we have explored the possible use of these proteins as screening biomarkers for ovarian cancer detection.</p> <p>Methods</p> <p>Claudin protein shedding from cells was examined by immunoblotting of conditioned culture media. The presence of claudins in exosomes released from ovarian cancer cells was demonstrated by sucrose gradient separation and immunogold electron microscopy experiments. Claudin-4-containing exosomes in the plasma of ovarian cancer patients were evaluated in a pilot panel of 63 ovarian cancer patients and 50 healthy volunteers. The CA125 marker was also assessed in these samples and compared with claudin-4 positivity.</p> <p>Results</p> <p>We show that full-length claudins can be shed from ovarian cancer cells in culture and found in the media as part of small lipid vesicles known as exosomes. Moreover, 32 of 63 plasma samples from ovarian cancer patients exhibited the presence of claudin-4-containing exosomes. In contrast, only one of 50 samples from individuals without cancer exhibited claudin-4-positive exosomes. In our small panel, at a specificity of 98%, the claudin-4 and CA125 tests had sensitivities of 51% and 71%, respectively. The two tests did not appear to be independent and were strongly correlated.</p> <p>Conclusion</p> <p>Our work shows for the first time that claudin-4 can be released from ovarian cancer cells and can be detected in the peripheral circulation of ovarian cancer patients. The development of sensitive assays for the detection of claudin-4 in blood will be crucial in determining whether this approach can be useful, alone or in combination with other screening methods, for the detection of ovarian cancer.</p