A framework for power analysis using a structural equation modelling procedure

BACKGROUND: This paper demonstrates how structural equation modelling (SEM) can be used as a tool to aid in carrying out power analyses. For many complex multivariate designs that are increasingly being employed, power analyses can be difficult to carry out, because the software available lacks sufficient flexibility. Satorra and Saris developed a method for estimating the power of the likelihood ratio test for structural equation models. Whilst the Satorra and Saris approach is familiar to researchers who use the structural equation modelling approach, it is less well known amongst other researchers. The SEM approach can be equivalent to other multivariate statistical tests, and therefore the Satorra and Saris approach to power analysis can be used. METHODS: The covariance matrix, along with a vector of means, relating to the alternative hypothesis is generated. This represents the hypothesised population effects. A model (representing the null hypothesis) is then tested in a structural equation model, using the population parameters as input. An analysis based on the chi-square of this model can provide estimates of the sample size required for different levels of power to reject the null hypothesis. CONCLUSIONS: The SEM based power analysis approach may prove useful for researchers designing research in the health and medical spheres

Additional Clinical Value for PET/MRI in Oncology: Moving Beyond Simple Diagnosis

Initial clinical research comparing the diagnostic performance of PET/MRI and PET/CT has largely shown equivalent diagnostic capabilities for these modalities in oncology. These uncertainties about the magnitude of diagnostic benefit are compounded by the considerable health economic challenges associated with clinical implementation. Therefore, there is a need to identify ways to extend the use of this technology beyond simple diagnosis so that PET/MRI can add sufficient clinical value beyond PET/CT or MRI alone and become a cost-effective imaging modality in clinical practice. A major advantage of PET/MRI over other imaging modalities is the ability to generate multiple quantitative images from a single examination. This article describes how a multiparametric PET/MRI approach not only can add clinical value through contributing to precision medicine but also can establish PET/MRI as a potentially cost-effective imaging modality in oncology

Radiologist Engagement as a Potential Barrier to the Clinical Translation of Quantitative Imaging for the Assessment of Tumor Heterogeneity

Rationale and Objective: This study aims to identify potential barriers to the clinical implementation of quantitative imaging for the assessment of tumor heterogeneity. // Materials and Methods: An 18-month prospective observational study was undertaken in which the clinical implementation of computed tomography texture analysis (CTTA) as a technique for quantifying tumor heterogeneity in patients with non–small cell lung cancer was assessed using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework.// Results: Adopters of the technology comprised five specialists with dual accreditation in radiology and nuclear medicine supervising two trainees. Tumor heterogeneity information was extracted and reported in 190 of 322 eligible cases (59%) and presented at the multidisciplinary team meeting in 124 of 152 patients (82%) for whom CTTA had been performed. The maximum proportion of eligible cases in which heterogeneity information had been extracted and reported in any quarter was 80%, but fell in the latter half of the study. The maximum frequency with which available CTTA results were presented at the multidisciplinary team meeting in any quarter was 92% and was maintained in the latter part of the study. Significant differences in survival were observed for patients categorized using the two reported CTTA values (P = 0.004 and P = 0.0057, respectively). // Conclusions: Radiologist engagement is a potential barrier to the effective translation of quantitative imaging assessments of tumor heterogeneity into clinical practice and will need to be addressed before tumor heterogeneity information can successfully contribute to clinical decision making in oncology

CT-based texture analysis potentially provides prognostic information complementary to interim fdg-pet for patients with hodgkin's and aggressive non-hodgkin's lymphomas

OBJECTIVES: The purpose of this study was to investigate the ability of computed tomography texture analysis (CTTA) to provide additional prognostic information in patients with Hodgkin's lymphoma (HL) and high-grade non-Hodgkin's lymphoma (NHL). METHODS: This retrospective, pilot-study approved by the IRB comprised 45 lymphoma patients undergoing routine 18F-FDG-PET-CT. Progression-free survival (PFS) was determined from clinical follow-up (mean-duration: 40 months; range: 10-62 months). Non-contrast-enhanced low-dose CT images were submitted to CTTA comprising image filtration to highlight features of different sizes followed by histogram-analysis using kurtosis. Prognostic value of CTTA was compared to PET FDG-uptake value, tumour-stage, tumour-bulk, lymphoma-type, treatment-regime, and interim FDG-PET (iPET) status using Kaplan-Meier analysis. Cox regression analysis determined the independence of significantly prognostic imaging and clinical features. RESULTS: A total of 27 patients had aggressive NHL and 18 had HL. Mean PFS was 48.5 months. There was no significant difference in pre-treatment CTTA between the lymphoma sub-types. Kaplan-Meier analysis found pre-treatment CTTA (medium feature scale, p=0.010) and iPET status (p<0.001) to be significant predictors of PFS. Cox analysis revealed that an interaction between pre-treatment CTTA and iPET status was the only independent predictor of PFS (HR: 25.5, 95% CI: 5.4-120, p<0.001). Specifically, pre-treatment CTTA risk stratified patients with negative iPET. CONCLUSION: CTTA can potentially provide prognostic information complementary to iPET for patients with HL and aggressive NHL

Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

<p>Abstract</p> <p>Background</p> <p>A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available.</p> <p>Results</p> <p>In this study we show that the sequence prediction methods have accuracies nearly comparable to those of spectroscopic methods. However, we also demonstrate that combining the spectroscopic and sequences techniques produces significant overall improvements in secondary structure determinations. In addition, combining the extra information content available from synchrotron radiation circular dichroism data with sequence methods also shows improvements.</p> <p>Conclusion</p> <p>Combining sequence prediction with experimentally determined spectroscopic methods for protein secondary structure content significantly enhances the accuracy of the overall results obtained.</p

Faith in thy threshold

The current study focussed on the decision making processes of jurors. The study investigated how jurors make a decision, if they integrated information within their decision making process, and if cue utilisation thresholds promoted confirmation bias. To do this, 108 participants listened to one of nine cases. These participants were asked to give a likelihood of guilt rating after each piece of evidence, to state what was the last piece of information they needed to make a decision and give a final verdict at the end of a trial. The results highlighted that threshold decision making was being utilised, that information integration may allow thresholds to be reached and that thresholds may promote confirmation bias to reduce cognitive dissonance. In conclusion, this suggests that jurors integrate information until they reach a leading verdict, then the evaluation of information is distorted to support the leading threshold. Implications relate to von Dire and legal instructions

Quantitative analysis of CT-perfusion parameters in the evaluation of brain gliomas and metastases

<p>Abstract</p> <p>Background</p> <p>The paper reports a quantitative analysis of the perfusion maps of 22 patients, affected by gliomas or by metastasis, with the aim of characterizing the malignant tissue with respect to the normal tissue. The gold standard was obtained by histological exam or nuclear medicine techniques. The perfusion scan provided 11 parametric maps, including Cerebral Blood Volume (CBV), Cerebral Blood Flow (CBF), Average Perfusion (P_mean) and Permeability-surface area product (PS).</p> <p>Methods</p> <p>The perfusion scans were performed after the injection of 40 ml of non-ionic contrast agent, at an injection rate of 8 ml/s, and a 40 s cine scan with 1 s interval was acquired. An expert radiologist outlined the region of interest (ROI) on the unenhanced CT scan, by using a home-made routine. The mean values with their standard deviations inside the outlined ROIs and the contralateral ROIs were calculated on each map. Statistical analyses were used to investigate significant differences between diseased and normal regions. Receiving Operating Characteristic (ROC) curves were also generated.</p> <p>Results</p> <p>Tumors are characterized by higher values of all the perfusion parameters, but after the statistical analysis, only the <it>PS</it>, <it>Pat</it>_{<it>Rsq </it>}(Patlak Rsquare) and <it>T</it>_{<it>peak </it>}(Time to Peak) resulted significant. ROC curves, confirmed both <it>Pat</it>_{<it>Rsq </it>}and <it>PS </it>as equally reliable metrics for discriminating between malignant and normal tissues, with areas under curves (AUCs) of 0.82 and 0.81, respectively.</p> <p>Conclusion</p> <p>CT perfusion is a useful and non invasive technique for evaluating brain neoplasms. Malignant and normal tissues can be accurately differentiated using perfusion map, with the aim of performing tumor diagnosis and grading, and follow-up analysis.</p