The accurate staging of ovarian cancer using 3T magnetic resonance imaging - a realistic option

Objectives: The aim of the study was to determine whether staging primary ovarian cancer using 3.0 Tesla (3T) magnetic resonance imaging (MRI) is comparable to surgical staging of the disease. Design: A retrospective study consisting of a search of the pathology database to identify women with ovarian pathology from May 2004 to January 2007. Setting: All women treated for suspected ovarian cancer in our cancer centre region. Sample: All women suspected of ovarian pathology who underwent 3T MRI prior to primary surgical intervention between May 2004 and January 2007. Methods: All women found to have ovarian pathology, both benign and malignant, were then cross checked with the magnetic resonance (MR) database to identify those who had undergone 3T MRI prior to surgery. The resulting group of women underwent comparison of the MR, surgical and histopathological findings for each individual including diagnosis of benign or malignant disease and International Federation of Gynecology and Obstetrics (FIGO) staging where appropriate. Main outcome measures: Comparisons were made between the staging accuracy of 3T MRI and surgical staging compared with histopathological findings and FIGO stage using weighted kappa. Sensitivity, specificity and accuracy were calculated for diagnosing malignant ovarian disease with 3T MRI. Results: A total of 191 women identified as having ovarian pathology underwent imaging with 3T MR and primary surgical intervention. In 19 of these women, the ovarian disease was an incidental finding. The group for which staging methods were compared consisted of 77 women of primary ovarian malignancy (20 of whom had borderline tumours). 3T MRI was able to detect ovarian malignancy with a sensitivity of 92% and a specificity of 76%. The overall accuracy in detecting malignancy with 3T MRI was 84%, with a positive predictive value of 80% and negative predictive value of 90%. Statistical analysis of the two methods of staging using weighted kappa, gave a K value of 0.926 (SE ±0.121) for surgical staging and 0.866 (SE ±0.119) for MR staging. A further analysis of the staging data for ovarian cancers alone, excluding borderline tumours resulted in a K value of 0.931 (SE ±0.136) for histopathological staging versus MR staging and 0.958 (±0.140) for histopathological stage versus surgical staging. Conclusion: Our study has shown that MRI can achieve staging of ovarian cancer comparable with the accuracy seen with surgical staging. No previous studies comparing different modalities have used the higher field strength 3T MRI. In addition, all other studies comparing radiological assessment of ovarian cancer have grouped the stages into I, II, III and IV rather than the more clinically appropriate a, b and c subgroups. © 2008 The Authors

Using NVivo™ for Literature Reviews: The Eight Step Pedagogy (N7+1)

While a literature review is a necessary milestone to be completed by all researchers in a timely and efficient manner, it is often one of the most difficult aspects of the research journey. Moreover, traditional approaches often leave novice researchers, to struggle with the conceptualisation of their literature review, now complicated by the overwhelming quantity of research available online. This paper presents a rationale the use of Qualitative Data Analysis Software (QDAS) programs for literature reviews. QDAS tools allow the researcher to explore large amounts of textual documents to see patterns. These programs are often overlooked by novice researchers due to their complexity and the lack of expertise provided to assist them. To combat this dilemma our paper outlines the N7+1 approach to using Nvivo11™ for literature reviews. Through this approach researchers can develop an “auditable footprint,” keep everything in one place, and go paperless

Isolated and dynamical horizons and their applications

Over the past three decades, black holes have played an important role in quantum gravity, mathematical physics, numerical relativity and gravitational wave phenomenology. However, conceptual settings and mathematical models used to discuss them have varied considerably from one area to another. Over the last five years a new, quasi-local framework was introduced to analyze diverse facets of black holes in a unified manner. In this framework, evolving black holes are modeled by dynamical horizons and black holes in equilibrium by isolated horizons. We review basic properties of these horizons and summarize applications to mathematical physics, numerical relativity and quantum gravity. This paradigm has led to significant generalizations of several results in black hole physics. Specifically, it has introduced a more physical setting for black hole thermodynamics and for black hole entropy calculations in quantum gravity; suggested a phenomenological model for hairy black holes; provided novel techniques to extract physics from numerical simulations; and led to new laws governing the dynamics of black holes in exact general relativity.Comment: 77 pages, 12 figures. Typos and references correcte

Interferon-λ rs12979860 genotype and liver fibrosis in viral and non-viral chronic liver disease

Tissue fibrosis is a core pathologic process that contributes to mortality in ∼45% of the population and is likely to be influenced by the host genetic architecture. Here we demonstrate, using liver disease as a model, that a single-nucleotide polymorphism (rs12979860) in the intronic region of interferon-λ4 (IFNL4) is a strong predictor of fibrosis in an aetiology-independent manner. In a cohort of 4,172 patients, including 3,129 with chronic hepatitis C (CHC), 555 with chronic hepatitis B (CHB) and 488 with non-alcoholic fatty liver disease (NAFLD), those with rs12979860CC have greater hepatic inflammation and fibrosis. In CHC, those with rs12979860CC also have greater stage-constant and stage-specific fibrosis progression rates (P<0.0001 for all). The impact of rs12979860 genotypes on fibrosis is maximal in young females, especially those with HCV genotype 3. These findings establish rs12979860 genotype as a strong aetiology-independent predictor of tissue inflammation and fibrosis