Predicting lymph node metastasis in pancreatobiliary cancer with magnetic resonance imaging: A prospective analysis

To prospectively investigate the diagnostic potential of lymph node (LN) magnetic resonance (MR) imaging features.

A radiologist determined the maximum diameters in the short and long axes, shape, signal intensities on T1- and T2-weighted imaging, pattern of enhancement, and apparent diffusion coefficient (ADC) on diffusion-weighted MR images of LNs and annotated measurable (≥5 mm in short-axis diameter) LNs. Surgically harvested LNs were correlated with the pathologic findings. Univariable and multivariable generalized estimating equation analyses were performed to evaluate predictive power.

Of 80 LNs, 29 (36.3%) were positive and 51 (63.7%) negative for metastasis. The mean short-axis diameter of metastatic LNs (10.59 ± 4.30 mm) was larger than that of benign LNs (7.96 ± 2.10 mm). The ADC was significantly (P < 0.001) lower in metastatic than non-metastatic LNs. The area under the curve (AUC) of a univariable model using only the mean ADC was 0.845 (95% confidence interval [CI], 0.743-0.927), and the mean-ADC cutoff value for predicting LN metastasis was 0.901 × 10^-3 mm²/s. The AUC of a multivariable model including round shape, heterogeneous enhancement, and the mean ADC was 0.917 (95% CI, 0.845-0.972), with a sensitivity, specificity, overall accuracy, and positive and negative predictive values of 89.7%, 82.4%, 85.0%, 74.3%, and 93.3%, respectively.

The short-axis diameter and ADC were different between benign and metastatic LNs in pancreatobiliary cancer. However, round shape, heterogeneous enhancement, and a low ADC value (<0.901 × 10^-3 mm²/s) may be the most reliable diagnostic features of multiple metastatic LNs.