Dataset Information

3 Tesla breast MR imaging as a problem-solving tool: Diagnostic performance and incidental lesions.

ABSTRACT: To investigate the diagnostic performance and incidental lesion yield of 3T breast MRI if used as a problem-solving tool.This retrospective, IRB-approved, cross-sectional, single-center study comprised 302 consecutive women (mean: 50±12 years; range: 20-79 years) who were undergoing 3T breast MRI between 03/2013-12/2014 for further workup of conventional and clinical breast findings. Images were read by experienced, board-certified radiologists. The reference standard was histopathology or follow-up ? two years. Sensitivity, specificity, PPV, and NPV were calculated. Results were stratified by conventional and clinical breast findings.The reference standard revealed 53 true-positive, 243 true-negative, 20 false-positive, and two false-negative breast MRI findings, resulting in a sensitivity, specificity, PPV, and NPV of 96.4% (53/55), 92.4% (243/263), 72.6% (53/73), and 99.2% (243/245), respectively. In 5.3% (16/302) of all patients, incidental MRI lesions classified BI-RADS 3-5 were detected, 37.5% (6/16) of which were malignant. Breast composition and the imaging findings that had led to referral had no significant influence on the diagnostic performance of breast MR imaging (p>0.05).3T breast MRI yields excellent diagnostic results if used as a problem-solving tool independent of referral reasons. The number of suspicious incidental lesions detected by MRI is low, but is associated with a substantial malignancy rate.

SUBMITTER: Spick C

PROVIDER: S-EPMC5749752 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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3 Tesla breast MR imaging as a problem-solving tool: Diagnostic performance and incidental lesions.

Spick Claudio C Szolar Dieter H M DHM Preidler Klaus W KW Reittner Pia P Rauch Katharina K Brader Peter P Tillich Manfred M Baltzer Pascal A PA

PloS one 20180102 1

<h4>Purpose</h4>To investigate the diagnostic performance and incidental lesion yield of 3T breast MRI if used as a problem-solving tool.<h4>Methods</h4>This retrospective, IRB-approved, cross-sectional, single-center study comprised 302 consecutive women (mean: 50±12 years; range: 20-79 years) who were undergoing 3T breast MRI between 03/2013-12/2014 for further workup of conventional and clinical breast findings. Images were read by experienced, board-certified radiologists. The reference stan ...[more]

PMID: 29293582

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Project description:This study is based on one collaborative problem solving task from an international assessment: the Xandar task. It was developed and delivered by the Organization for Economic Co-operation and Development Program for International Student Assessment (OECD PISA) 2015. We have investigated the relationship of problem solving performance with invested time and number of actions in collaborative episodes for the four parts of the Xandar task. The parts require the respondent to collaboratively plan a process for problem solving, implement the process, reach a solution, and evaluate the solution (For a full description, see the Materials and Methods section, "Parts of the Xandar Task.") Examples of an action include posting to a chat log, accessing a shared resource, or conducting a search on a map tool. Actions taken in each part of the task were identified by PISA and recorded in the data set numerically. A confirmatory factor analysis (CFA) model looks at two types of relationship: at the level of latent variables (the factors) and at extra dependencies, which here are direct effects and correlated residuals (independent of the factors). The model, which is well-fitting, has three latent variables: actions (A), times (T), and level of performance (P). Evidence for the uni-dimensionality of performance level is also found in a separate analysis of the binary items. On the whole for the entire task, participants with more activities are less successful and faster, based on the United States data set employed in the analysis. By contrast, successful participants take more time. By task part, the model also investigates relationships between activities, time, and performance level within the parts. This was done because one can expect dependencies within parts of such a complex task. Results indicate some general and some specific relationships within the parts, see the full manuscript for more detail. We conclude with a discussion of what the investigated relationships may reveal. We also describe why such investigations may be important to consider when preparing students for improved skills in collaborative problem solving, considered a key aspect of successful 21st century skills in the workplace and in everyday life in many countries.

Dataset Information

3 Tesla breast MR imaging as a problem-solving tool: Diagnostic performance and incidental lesions.

Publications

3 Tesla breast MR imaging as a problem-solving tool: Diagnostic performance and incidental lesions.

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