Imaging sequences in the GNC, as in many other research projects, differ from clinically used sequences. They often do not have the particular purpose to obtain a certain clinical diagnosis. In the GNC, MR sequences were chosen with an emphasis on maximizing morphologic data acquisition in a restricted time frame, sacrificing some of the MRI-inherent benefits of analyzing a lesion based on a multitude of MR-characteristic tissue features. Therefore, IF-reading has to be based mostly on T1- and T2-weighted images without common, clinically applied sequences such as diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), etc. Due to their invasive nature, contrast agents, gut motility suppressing medications, bowel distending procedures, and endorectal/endovaginal coils have also been forgone. With the limited imaging set to characterize a finding, great uncertainty in specifying a finding and a large list of differential diagnoses including artifacts has to be expected.

While reacquisition of only one sequence is allowed, more reacquisitions, for example, because of motion or breathing artifacts, cannot be afforded due to time restrictions. Similarly, sequence protocols are fixed for comparability. No sequences can be swapped for, for example, less motion susceptible ones or more lesion appropriate ones, as it happens in clinical settings. This substantially reduces the sensitivity to pick up a lesion and hugely widens the gap between the ability to detect and characterize a finding.

To afford unbiased reporting, and because of strict German privacy and data protection laws, radiologists are blinded to personal and clinical information of the participant, except for gender and the year of birth. Moreover, no data from exams conducted in other areas of the GNC (e.g., blood tests) are shared with the radiologist in charge of the IF-reporting. This severely hampers guidance toward a probable diagnosis of an observed lesion.

The probability of a lesion being a certain diagnosis is possibly distorted by the fact that examinees randomly selected from the general population are more likely to be healthy individuals, in contrast to patients with clinical indications for imaging. It is a mathematical phenomenon that the positive and negative predictive value of a particular imaging finding depends on the prevalence of the appendant disease in the examined population (Bender et al. 1998). Compared to a clinical setting where MRI is often applied to further characterize an already known or suspected lesion, a mostly healthy general population leads to a lower positive predictive value and accordingly to an increase in false-positive reports. Taking the generally poorer specificity of the applied scientific imaging sequences compared to clinical sequences into account, the report of a potentially harmful finding would come at the expense of an even larger number of false positives. Along with health care costs, physical and psychologic side effects of follow-up procedures would increase disproportionately, compared to true positive disease detection. The effect of false-positive reports is aggravated by the fact that possibly healthy individuals, that otherwise would not have been subjected to medical exams, might undergo harmful or side effect-stricken follow-up investigations.

For the assessment of 30,000 MR scans acquired at five different sites, a relatively large number of radiologists are involved in reading the acquired data. Furthermore, with this imaging round expected to last at least 4 years, a significant fluctuation of involved radiologists is anticipated. Therefore, high-quality standards must be met to ensure consistency and reliability. It is well known from reproducibility studies that variability is induced by radiologists in image interpretation and diagnoses making (Robinson 1997). Considering the fundamental obligation to provide the same service and the same quality of service to each of the participants, variability should be limited as much as possible. This can be theoretically achieved by either reducing the number of involved radiologists, and/or by involving only highly and specifically trained radiologists, and/or by standardized reporting and/or by conducting quality assurance in IF-reporting.

It was decided to develop a specified, categorized, and concise list of reportable findings, limiting uncertainty and false positives as well as establishing consistency. The ground work for this system was laid by expert radiologists familiar with the applied sequences and the ethical considerations.

The ratios of false-positive and false-negative findings are significantly determined by the applied MR sequences. As these ratios are specific to the set of sequences used, comparability with previous cohort studies using different imaging protocols might be severely hampered. Based on the extrapolation of extensive literature research data (excerpt (Abeloos and Lefranc 2011; Al-Shahi Salman 2007; Atalay et al. 2011; Ballantyne 2008; Beigelman-Aubry et al. 2007; Berland et al. 2010; Berlin 2011; Boland et al. 2008; Booth et al. 2012; Borra and Sorensen 2011; Bradley et al. 2011; Childs and Leyendecker 2008; Chow and Drummond 2010; Cordell 2011; Cramer et al. 2011; de Rave and Hussain 2002; Erdogan et al. 2007; Esmaili et al. 2011; Gore et al. 2011; Gross et al. 2010; Hartwigsen et al. 2010; Hoggard et al. 2009; Illes 2008; Irwin et al. 2013; Johnson et al. 2011; Kamath et al. 2009; Khosa et al. 2011; Ladd 2009; Lee et al. 2011; Legmann 2009; Lund-Johansen 2013; MacMahon et al. 2005; McKenna et al. 2008; Megibow et al. 2011; Milstein 2008; Morin et al. 2009; Morris et al. 2009; Nelson 2008; Orme et al. 2010; Pierce et al. 2009; Puls et al. 2010; Richardson 2008; Royal and Peterson 2008; Shoemaker et al. 2011; Subhas et al. 2009; van der Lugt 2009; Vanel et al. 2009; Vernooij et al. 2007; Zarzeczny and Caulfield 2012)), radiologic clinical experience and the knowledge and limitations of the applied sequences, a list of reportable IFs has been specifically tailored to the imaging data available (Table 2). Similarly, a list was created exemplarily specifying IFs that should not be reported.