Quantitative imaging in medicine and surgery · 2025
Evaluation of histological tumor necrosis in pancreatic ductal adenocarcinoma via the quantitative parameters from enhanced computed tomography and its relationship with tumor prognosis.
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Zhong Shiling, Yang Aoran, Pan Chen, Huo Yunlong, Song Qike, Li Chunli, Du Bai, Shi Yu
Аннотация
BACKGROUND: Contrast-enhanced computed tomography (CE-CT) is considered the standard tool for depicting, staging, and resecting pancreatic ductal adenocarcinoma (PDAC). This study aimed to assess the utility of CE-CT in evaluating histological tumor necrosis (HTN) in patients with PDAC and to evaluate the prognostic significance of computed tomography (CT)-defined necrosis in patients with resectable PDAC.
METHODS: Among 1,116 patients with PDAC [our hospital (Shengjing Hospital of China Medical University): 966; external hospitals (Guangdong Provincial People's Hospital and Tianjin Tumor Hospital): 150] undergoing CE-CT and R0 pancreatectomy between January 2010 and December 2020, 328 patients were reevaluated for HTN. CE-CT images were processed using dense energy displacement sampling (DEEDS) and three-dimensional no new UNet (3D-nnUNet) for tumor segmentation. The subtraction map and attenuation difference (delta) of the portal venous phase and the unenhanced phase of the tumor were obtained with a MATLAB script (MathWorks). Necrosis detected by CT was defined as a weak or no-enhancement area on the subtraction image [delta: 10-30 Hounsfield units (HU)]. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance, and Cox models were applied to estimate disease-free survival (DFS) and overall survival (OS).
RESULTS: CT-defined necrosis (delta ≤15 HU) demonstrated superior diagnostic efficacy for HTN as compared to other cutoffs and radiologist-diagnosed necrosis [area under the ROC curve (AUC): 0.93 vs. 0.74-0.87; all P values <0.05]. In the multivariate Cox model, CT-defined necrosis was an independent influencing factor of DFS [preoperative model at our hospital: hazard ratio (HR) =2.33, 95% confidence interval (CI): 1.98-2.76, P<0.001; comprehensive model at our hospital: HR =2.22, 95% CI: 1.88-2.62, P<0.001; preoperative model at the external hospitals: HR =2.82, 95% CI: 1.88-4.26, P<0.001; comprehensive model at the external hospitals: HR =2.31, 95% CI: 1.51-3.51, P<0.001]. In the Cox model for predicting OS, CT-defined necrosis was an independent influencing factor in the preoperative model in our hospital (HR =1.79, 95% CI: 1.50-2.13, P<0.001) and the comprehensive model (HR =1.70, 95% CI: 1.43-2.02, P<0.001) and an independent influencing factor of the preoperative model in the external hospitals (HR =1.92, 95% CI: 1.30-2.84, P=0.001). There was no independent correlation of CT-defined necrosis with OS in the comprehensive model at external hospitals (HR =1.28, 95% CI: 0.86-1.92, P =0.230).
CONCLUSIONS: CT-defined necrosis can be used as an objective imaging biomarker to diagnose HTN and preoperatively predict poor prognosis among patients with PDAC.
METHODS: Among 1,116 patients with PDAC [our hospital (Shengjing Hospital of China Medical University): 966; external hospitals (Guangdong Provincial People's Hospital and Tianjin Tumor Hospital): 150] undergoing CE-CT and R0 pancreatectomy between January 2010 and December 2020, 328 patients were reevaluated for HTN. CE-CT images were processed using dense energy displacement sampling (DEEDS) and three-dimensional no new UNet (3D-nnUNet) for tumor segmentation. The subtraction map and attenuation difference (delta) of the portal venous phase and the unenhanced phase of the tumor were obtained with a MATLAB script (MathWorks). Necrosis detected by CT was defined as a weak or no-enhancement area on the subtraction image [delta: 10-30 Hounsfield units (HU)]. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance, and Cox models were applied to estimate disease-free survival (DFS) and overall survival (OS).
RESULTS: CT-defined necrosis (delta ≤15 HU) demonstrated superior diagnostic efficacy for HTN as compared to other cutoffs and radiologist-diagnosed necrosis [area under the ROC curve (AUC): 0.93 vs. 0.74-0.87; all P values <0.05]. In the multivariate Cox model, CT-defined necrosis was an independent influencing factor of DFS [preoperative model at our hospital: hazard ratio (HR) =2.33, 95% confidence interval (CI): 1.98-2.76, P<0.001; comprehensive model at our hospital: HR =2.22, 95% CI: 1.88-2.62, P<0.001; preoperative model at the external hospitals: HR =2.82, 95% CI: 1.88-4.26, P<0.001; comprehensive model at the external hospitals: HR =2.31, 95% CI: 1.51-3.51, P<0.001]. In the Cox model for predicting OS, CT-defined necrosis was an independent influencing factor in the preoperative model in our hospital (HR =1.79, 95% CI: 1.50-2.13, P<0.001) and the comprehensive model (HR =1.70, 95% CI: 1.43-2.02, P<0.001) and an independent influencing factor of the preoperative model in the external hospitals (HR =1.92, 95% CI: 1.30-2.84, P=0.001). There was no independent correlation of CT-defined necrosis with OS in the comprehensive model at external hospitals (HR =1.28, 95% CI: 0.86-1.92, P =0.230).
CONCLUSIONS: CT-defined necrosis can be used as an objective imaging biomarker to diagnose HTN and preoperatively predict poor prognosis among patients with PDAC.