Purpose: Minimal axial diameter (MIAD) in magnetic resonance imaging (MRI) was recognized as the most useful parameter in diagnosing lateral retropharyngeal lymph (LRPL) nodes in nasopharyngeal carcinoma (NPC). This study aims to explore the additional nodal parameters in MRI and positron emission tomography - computed tomography for increasing the prediction accuracy. Materials and Methods: A total of 663 LRPL nodes were retrospectively collected from 335 patients with NPC. The LRPL nodes ascertained on follow-up MRI were considered positive for metastases. First, the optimal cutoff value of each parameter was derived for each parameter. In addition, neural network (NN) nodal evaluation was tested for all combinations of three parameters, namely MIAD, maximal axial diameter (MAAD), and maximal coronal diameter (MACD). The optimal approach was determined through brute force attack, and the results of two methods were compared using a bootstrap sampling method. Second, the mean standard uptake value (NSUVmean) was added as the fourth parameter and tested in the same manner for 410 nodes in 219 patients. Results: In first and second analysis, the accuracy rate (percentage) for the MIAD was 89.0% (590/663) and 89.0% (365/410), with the optimal cutoff values being 6.1 mm and 6.0 mm, respectively. With the combination of all three and four parameters, the accuracy rate of the NN was 89% (288/332) and 88.8% (182/205), respectively. In prediction, the optimal combinations of the three and four parameters resulted in correct identification of three (accuracy: 593/663, 89.4%) and six additional nodes (371/410, 90.5%), representing 4% (3/73) and 13.3% (6/45) decreases in incorrect prediction, respectively. Conclusion: NPC LRPL nodes with an MIAD ≥ 6.1 mm are positive. Among nodes with an MIAD < 6.1 mm, if the NSUVmean ≥ 2.6 or MACD ≥ 25 mm and MAAD ≥ 8 mm, the nodes are positive; otherwise, they are negative.
All Science Journal Classification (ASJC) codes