In vivo dynamic imaging, in silico modeling and global sensitivity analysis for the study and the diagnosis of epithelial neoplasia.

We present a method for detecting and studying neoplasia-specific functional and structural features through the combination of in vivo dynamic imaging, in silico modeling and global sensitivity analysis. We particularly present the case of cervical epithelium interacting with acetic acid solution, which is employed as an optical biomarker. The in vivo measured dynamic scattering characteristics are strongly correlated with the output of the biomarker's pharmacokinetic model that we have developed. Model global sensitivity analysis has shown that the measured/modeled bio-optical processes can be used for probing, in vivo, the number of neoplastic layers, the extracellular pH, the intracellular buffering efficiency and the size of the extracellular space.

Comparison of predictors for high-grade cervical intraepithelial neoplasia in women with abnormal smears.

BACKGROUND: The detection of high-risk human papillomavirus (HPV) DNA provides higher sensitivity but lower specificity than cytology for the identification of high-grade cervical intraepithelial neoplasia (CIN). This study compared the sensitivity and specificity of several adjunctive tests for the detection of high-grade CIN in a population referred to colposcopy because of abnormal cytology. METHODS: 953 women participated in the study. Up to seven tests were carried out on a liquid PreservCyt sample: Hybrid Capture II (Digene), Amplicor (Roche), PreTect HPV-Proofer (NorChip), APTIMA HPV assay (Gen-Probe), Linear Array (Roche), Clinical-Arrays (Genomica), and CINtec p16INK4a Cytology (mtm Laboratories) immunocytochemistry. Sensitivity, specificity, and positive predictive value (PPV) were based on the worst histology seen on either the biopsy or the treatment specimen after central review. RESULTS: 273 (28.6%) women had high-grade disease (CIN2+) on worst histology, with 193 (20.2%) having CIN3+. For the detection of CIN2+, Hybrid Capture II had a sensitivity of 99.6%, specificity of 28.4%, and PPV of 36.1%. Amplicor had a sensitivity of 98.9%, specificity of 21.7%, and PPV of 33.5%. PreTect HPV-Proofer had a sensitivity of 73.6%, specificity of 73.1%, and PPV of 52.0%. APTIMA had a sensitivity of 95.2%, specificity of 42.2%, and PPV of 39.9%. CINtec p16INK4a Cytology had a sensitivity of 83.0%, specificity of 68.7%, and PPV of 52.3%. Linear Array had a sensitivity of 98.2%, specificity of 32.8%, and PPV of 37.7%. Clinical-Arrays had a sensitivity of 80.9%, specificity of 37.1%, and PPV of 33.0%.

MiMiR--an integrated platform for microarray data sharing, mining and analysis.

BACKGROUND: Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. RESULTS: A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. CONCLUSION: The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.