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Congress: ECR25
Poster Number: C-24967
Type: Poster: EPOS Radiologist (scientific)
Authorblock: W. Shen, Z. Ouyang; Kunming/CN
Disclosures:
Wan Shen: Nothing to disclose
Zhiqiang Ouyang: Nothing to disclose
Keywords: Pancreas, MR, Technical aspects, Cancer
Purpose Perineural invasion (PNI) is a common pathological feature in pancreatic cancer, closely associated with increased pain, higher rates of metastasis, and poorer prognosis. Accurate preoperative prediction of PNI is crucial for informing surgical strategies and optimizing individualized treatment planning. However, at present, the diagnosis of PNI in pancreatic cancer relies solely on postoperative pathological examination, with no effective preoperative assessment methods available. This study aims to develop a predictive model for PNI using a novel habitat analysis based on multiparametric...
Read more Methods and materials This study is a multicenter retrospective analysis that included a total of 106 patients diagnosed with pancreatic cancer, who underwent surgical treatment and were confirmed by postoperative pathological examination. The patients were enrolled from four medical institutions, spanning the period from January 2019 to December 2024. The patients were randomly assigned to a training set (n = 74) and a validation set (n = 32). Multiparametric MRI sequences, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) sequences,...
Read more Results The combined model, incorporating radiomic features from both traditional and habitat analysis along with clinical variables, outperformed the traditional radiomics-only and habitat-only models. The combined model achieved an area under the curve (AUC) of 0.862 in the training set and 0.843 in the validation set, demonstrating high predictive value for identifying PNI preoperatively. Additionally, the combined model exhibited superior sensitivity and specificity compared to the individual models, highlighting its potential clinical utility.
Read more Conclusion Habitat analysis based on multiparametric MRI combined with traditional radiomics and clinical features offers significant predictive value for preoperative detection of PNI in pancreatic cancer patients. This approach could improve patient stratification, guide surgical and treatment decisions, and ultimately enhance patient outcomes by enabling more precise and individualized management strategies.
Read more References Bapat AA, Hostetter G, Von Hoff DD, Han H. Perineural invasion and associated pain in pancreatic cancer. Nat Rev Cancer. 2011;11(10):695-707. doi:10.1038/nrc3131 Capodanno Y, Hirth M. Targeting the Cancer–Neuronal Crosstalk in the Pancreatic Cancer Microenvironment. IJMS. 2023;24(19):14989. doi:10.3390/ijms241914989 Tu W, Gottumukkala RV, Schieda N, Lavallée L, Adam BA, Silverman SG. Perineural Invasion and Spread in Common Abdominopelvic Diseases: Imaging Diagnosis and Clinical Significance. RadioGraphics. 2023;43(7):e220148. doi:10.1148/rg.220148 Michelotti FC. Editorial for “The Association Between Tumor Radiomic Analysis and Peritumor Habitat‐Derived Radiomic Analysis on Gadoxetate...
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