Magnetic Resonance Imaging Radiomics‐Based Nomogram From Primary Tumor for Pretreatment Prediction of Peripancreatic Lymph Node Metastasis in Pancreatic Ductal Adenocarcinoma: A Multicenter Study

Abstract

Background Determining the absence or presence of peripancreatic lymph nodal metastasis (PLNM) is important to the pathologic staging, prognostication, and guidance of treatment in pancreatic ductal adenocarcinoma (PDAC) patients. Computed tomography and MRI had a poor sensitivity and diagnostic accuracy in the assessment of PLNM. Purposes To develop and validate a 3 T MRI primary tumor radiomics‐based nomogram from multicenter datasets for pretreatment prediction of the PLNM in PDAC patients. Study Type Retrospective. Subjects A total of 251 patients (156 men and 95 women; mean age, 60.85 ± 8.23 years) with histologically confirmed pancreatic ductal adenocarcinoma from three hospitals. Field Strength and Sequences A 3.0 T and fat‐suppressed T1‐weighted imaging. Assessment Quantitative imaging features were extracted from fat‐suppressed T1‐weighted (FS T1WI) images at the arterial phase. Statistical Tests Normally distributed data were compared by using t‐tests, while the Mann–Whitney U test was used to evaluate non‐normally distributed data. The diagnostic performances of the preoperative and postoperative nomograms were assessed in the external validation cohort with the area under receiver operating characteristics curve (AUC), calibration curve, and decision curve analysis (DCA). AUCs were compared with the De Long test. A p value below 0.05 was considered to be statistically significant. Results The AUCs of magnetic resonance imaging (MRI) Rad‐score were 0.868 (95% confidence level [CI]: 0.613–0.852) and 0.772 (95% CI: 0.659–0.879) in the training and internal validation cohort, respectively. The preoperative and postoperative nomograms could accurately predict PLNM in the training cohort (AUC = 0.909 and 0.851) and were validated in both the internal and external cohorts (AUC = 0.835 and 0.805, 0.808 and 0.733, respectively). DCA indicated that the two novel nomograms are of similar clinical usefulness. Data Conclusion Pre−/postoperative nomograms and the constructed radiomics signature from primary tumor based on FS T1WI of arterial phase could serve as a potential tool to predict PLNM in patients with PDAC. Evidence Level 3 Technical Efficacy Stage 2

Comparison of MRI and CT-based radiomics for preoperative prediction of lymph node metastasis in pancreatic ductal adenocarcinoma

“…It is superior to CT in detecting PDAC (34). In the present study, multiparametric MRI-based radiomics achieved a good predictive accuracy for LNM in PDAC, consistent with the study by Shi et al (35). In that study, ≤3 positive lymph nodes were defined as negative LNM and >3 as positive LNM.…”

Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging

“…The study from Chaddad et al, (2021) divided patients into short- and long-term survivors with a set threshold [ 64 ]. Only two papers used an external dataset to validate their performance [ 65 , 66 ].…”

Preoperative Prediction of Lymph Node Metastasis of Pancreatic Ductal Adenocarcinoma Based on a Radiomics Nomogram of Dual-Parametric MRI Imaging

“…Radiomics is an advanced method for quantitative analysis that can reveal information from microscopic features that are not easily observable by the naked eye in medical imaging (17,36). In recent years, various studies have attempted to predict LNM based on MRI radiomic analysis of primary lesions (22,(37)(38)(39)(40)(41)(42)(43). To the best of our knowledge, only one study has analyzed the predictive efficacy of radiomics based on MRI for LNM of PDAC (43), but only the arterial phase of the T1WI enhanced sequence was used.…”

“…In recent years, various studies have attempted to predict LNM based on MRI radiomic analysis of primary lesions (22,(37)(38)(39)(40)(41)(42)(43). To the best of our knowledge, only one study has analyzed the predictive efficacy of radiomics based on MRI for LNM of PDAC (43), but only the arterial phase of the T1WI enhanced sequence was used. T2WI can reflect the signal intensity of the tumor tissue and its structure, and the enhanced sequence can better reflect tumor-related information such as internal heterogeneity and vascular regeneration (18-20, 24, 44).…”