Liao et al. BMC Cancer 2012, 12:236 http://www.biomedcentral.com/1471-2407/12/236 Page 3 of 7 Figure 1 Flow chart of the study selection process. Of the 168 identified relevant articles, 7 studies fulfilled all inclusion criteria for CT, 6 studies for MRI, 11 studies for PET and 8 studies for US. evaluate the relevant study design characteristics of each study. This tool and the definitions of the characteristics have previously been fully described [6]. We assigned a design characteristic with a score of 1 if the evaluation criteria were met or 0 if the design characteristic was not preset or was unclear. Each study that met the inclusion criteria was analyzed by two independent reviewers (Wang CT and Lo WC). When there was a discrepancy between the reviewers, a consensus reviewer (Liao LJ) resolved these differences. Difference in the QUADAS score among different modalities was tested using the Kruskal-Wallis test. Data analysis/synthesis The primary outcome for analysis was the diagnostic performance of imaging examinations that detected the neck lymph node metastasis compared with the refer- ence standard of neck dissection specimens. Sensitivities and specificities with a 95% confidence interval (CI) values were reported for individual studies. Pooled sensi- tivities and specificities of CT, MRI, PET and US in neck lymph node metastasis of cN0 neck from individual studies were calculated using a bivariate random effect model [7]. The random effect model incorporated the heterogeneity of the studies into the analysis of the over- all efficacy. The differences in sensitivities and specifici- ties were tested using a bivariate random effect model. Likelihood ratios are metrics that are calculated using a combination of sensitivity and specificity values. The positive likelihood ratio (LR+) is defined as the ratio of sensitivity (1-specificity), whereas the negative likelihood ratio (LR-) is defined as the ratio of specificity (1- sensitivity). When a diagnostic test has absolutely no dis- criminating ability, both likelihood ratios equal 1. The performance of each diagnostic modality was shown using summary receiver operating characteristic (ROC) curves. The positive and negative post-test probability was generated based on Bayesian theory, and collected data were tabulated for 10%, 20% and 30% pre-test prob- abilities of cN0 neck. Statistical analyses were completed using STATA version 10.0 (Stata Corp.). Results The abstracts and titles of 168 primary studies were identified for initial review based on the described search strategy. Full-text reviews were required for 65 publications to determine study eligibility. Subse- quently, a total of 21 articles were selected based on agreement between the two reviewers. During the search process (Figure 1), we found that most studies were excluded due to a mix of cN0 and cN + patients without individual patient data for 2 × 2 tables. Seven studies fulfilled all inclusion criteria for CT, 6 studies for MRI, 11 studies for PET and 8 studies for US. The sensitivities and specificities with 95% confidence inter- val (CI) values and QUDAS scores for individual stud- ies are summarized in Table 1. There was no difference in the pooled sensitivity among these imaging modalities. The pooled estimates (Table 2 and Figure 2) for sensitivity were 52% (95% con- fidence interval [CI], 39% ~ 65%), 65% (34 ~ 87%), 66% (47 ~ 80%) and 66% (54 ~ 77%) on a per-neck basis for CT, MRI, PET and US, respectively. CT was superior to US in specificity, but there was no difference among CT,