Added value of multifrequency magnetic resonance elastography in predicting pathological grading of pancreatic neuroendocrine neoplasms - Jiaxin Yuan; Jiawei Liu; Tingting Wen; Liqin Wang; Zhenpeng Peng; Ning Zhang; Shi-Ting Feng; Jinhui Yu; Siya Shi; Yanji Luo (Insights into Imaging)
Abstract Objectives To prospectively investigate the pancreatic stiffness (c) and fluidity (φ) of pancreatic neuroendocrine neoplasms (pNENs), measured using multifrequency magnetic resonance elastography (MRE), and evaluate their performance in predicting pNENs pathological grade. Materials and methods This study included 96 untreated patients with pathologically confirmed pNENs who underwent multifrequency MRE within 2 weeks before surgery between September 2021 and November 2023. Independent predictors of pathological grade were identified using multivariate regression analysis, and predictive performance was assessed using receiver operating characteristic curves. Results The study included 76 patients with low-grade pNENs (45 men; mean age: 48.7 ± 14.0 years; Grade 1: 34 patients, Grade 2: 42 patients) and 20 patients with high-grade pNENs (10 men; mean age: 54.4 ± 13.8 years; Grade 3: 15 patients, neuroendocrine carcinoma: 5 patients). The two radiologists showed substantial or near-perfect interobserver agreement in evaluating the quantitative parameters. The multivariate regression analysis identified c and relative enhancement in the portal venous phase (V) as independent predictors of pathological grade. The combined model (V + c) had the best predictive performance (area under the curve (AUC) = 0.930; sensitivity: 95.0%; specificity: 82.9%) and outperformed V (AUC = 0.806, p = 0.010), c (AUC = 0.847, p = 0.021), and φ (AUC = 0.709, p = 0.003) alone, as well as other clinical and conventional MRI parameters (all p < 0.05) in Delong’s test. Conclusions Tumour stiffness quantified via multifrequency MRE improved the predictive performance for the pathological grade of pNENs when combined with conventional MRI parameters. Critical relevance statement Tumour stiffness quantified using multifrequency magnetic resonance elastography provides a non-invasive, preoperative method for predicting the pathological grade of pancreatic neuroendocrine neoplasms. Predictive performance improves when combined with conventional MRI parameters, facilitating clinical decision-making and prognostic prediction. Key Points Multifrequency magnetic resonance elastography (MRE) can indicate stiffness and fluidity of pancreatic neuroendocrine neoplasms (pNENs). Tumour stiffness combined with conventional MRI parameters can independently predict pNENs pathological grade. Multifrequency MRE can serve as a biomarker for the prediction of pNENs pathological grade. Graphical Abstract