Feasibility of Prospective Assignment of Initial Method of Detection of Breast Cancer: A Multicenter Pilot Study.

OBJECTIVE: To determine the feasibility of standardized, prospective assignment of initial method of detection (MOD) of breast cancer by radiologists in diverse practice settings. METHODS: This multicenter, retrospective study analyzed the rate of assignment of MOD in four geographically varied health systems. A universal protocol for basic MOD assignment was agreed upon by the authors before start of the pilot study. Radiologists at each site were instructed how to assign MOD. Charts were then reviewed to determine the frequency and accuracy of MOD assignment for all cases subsequently diagnosed with breast cancer. When available, data regarding frequency of tumor registry abstraction were also reviewed for frequency and accuracy. RESULTS: A total of 2,328 patients with a new diagnosis of breast cancer were evaluated across the sites over the study period. Of these patients, initial MOD was prospectively assigned by the radiologist in 94% of cases. Of the cases in which MOD was assigned, retrospective review confirmed accurate assignment in 96% of cases. CONCLUSIONS: Prospective, standardized assignment of initial MOD of breast cancer is feasible across different practice sites and can be accurately captured in tumor registries. Standard collection of MOD would provide critical data about the impact of screening mammography in the United States.

Advanced neuroimaging in the clinic: critical appraisal of the evidence base.

The shortage of high-quality systematic reviews in the field of radiology limits evidence-based integration of imaging methods into clinical practice and may perpetuate misconceptions regarding the efficacy and appropriateness of imaging techniques for specific applications. Diffusion tensor imaging for patients with mild traumatic brain injury (DTI-mTBI) and dynamic susceptibility contrast MRI for patients with glioma (DSC-glioma) are applications of quantitative neuroimaging, which similarly detect manifestations of disease where conventional neuroimaging techniques cannot. We performed a critical appraisal of reviews, based on the current evidence-based medicine methodology, addressing the ability of DTI-mTBI and DSC-glioma to (a) detect brain abnormalities and/or (b) predict clinical outcomes. 23 reviews of DTI-mTBI and 26 reviews of DSC-glioma met criteria for inclusion. All reviews addressed detection of brain abnormalities, whereas 12 DTI-mTBI reviews and 22 DSC-glioma reviews addressed prediction of a clinical outcome. All reviews were assessed using a critical appraisal worksheet consisting of 19 yes/no questions. Reviews were graded according to the total number of positive responses and the 2011 Oxford Centre for evidence-based medicine levels of evidence criteria. Reviews addressing DTI-mTBI detection had moderate quality, while those addressing DSC-glioma were of low quality. Reviews addressing prediction of outcomes for both applications were of low quality. Five DTI-mTBI reviews, but only one review of DSC-glioma met criteria for classification as a meta-analysis/systematic/quantitative review.