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Updated: Jun 14, 2026
Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model
Published on: April 18, 2015
Neutrophil-albumin ratio and multi-phase computed tomography for lymph node metastasis in pancreatic cancer
Huan Wang1, Tian-Yu Fu2, Fang Zhang1
1Department of Imaging, Ordos Central Hospital, Ordos 017000, Inner Mongolia Autonomous Region, China.
Background:
Reliable preoperative detection of lymph node metastasis (LNM) in pancreatic cancer remains elusive: Conventional computed tomography (CT) underestimates micrometastases, and carbohydrate antigen 19-9 is hampered by low specificity. The neutrophil-albumin ratio (NAR) simultaneously reflects systemic inflammation and nutritional depletion, but its contribution to LNM prediction in pancreatic cancer is unexplored. We hypothesised that integrating NAR with multi-phase CT findings would significantly improve the accuracy of preoperative LNM assessment in patients undergoing curative-intent resection.
Aim:
To determine whether preoperative NAR plus multi-phase CT reliably predicts nodal metastasis in pancreatic cancer.
Methods:
In this single-centre retrospective cohort study (February 2022 to February 2025, Ordos Central Hospital, China), 129 consecutive patients undergoing curative pancreatic resection were histologically classified as LNM+ (n = 61) and LNM- (n = 68). Preoperative NAR and platelet-albumin ratio (PAR) were calculated; optimal cut-offs were determined with X-tile. Multi-phase CT images were re-reviewed by two blinded radiologists. Independent predictors of nodal metastasis were identified by multivariate logistic regression, and model performance was evaluated with receiver operating characteristic (ROC) analysis.
Results:
Between the two cohorts, univariate comparison revealed significant divergence in age, tumour diameter, concomitant hemangioma thrombosis, PAR, NAR, and CT-detected nodal status (P < 0.05). Subsequent multivariate modelling identified hemangioma thrombosis, PAR above 6.35, NAR exceeding 0.13, and radiologically positive lymph nodes as independent predictors of nodal metastasis (P < 0.05). ROC evaluation indicated that the NAR-plus-CT-nodes model (model 1) reached an area under the curve (AUC) of 0.758, whereas the four-variable composite (model 3) achieved the best performance with an AUC of 0.830 (95%CI: 0.753-0.890), sensitivity 83.61%, and specificity 67.65%.
Conclusion:
The model 3 (NAR > 0.13, PAR > 6.35, CT nodal positivity, hemangioma thrombosis) provides robust, clinically actionable preoperative identification of pancreatic cancer patients at high risk of LNM.
