High-acceleration pancreatobiliary MRI with deep learning-based super-resolution reconstruction for evaluating presumed pancreatic intraductal papillary mucinous neoplasm

利用基于深度学习的超分辨率重建技术进行高加速胰胆MRI成像,以评估疑似胰腺导管内乳头状黏液性肿瘤

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Abstract

BACKGROUND: To evaluate the feasibility and diagnostic utility of a deep learning (DL)-based super-resolution (SR) reconstruction algorithm applied to pancreatobiliary MRI for assessing pancreatic intraductal papillary mucinous neoplasms (IPMNs). METHODS: This retrospective study included 162 patients with presumed pancreatic IPMN (≥ 1 cm) who underwent pancreatobiliary MRI between May 2019 and May 2022. Two portal venous phase (PVP) images of dynamic T1-wegithed imaging were sequentially acquired: early PVP image obtained using standard compressed sensing (CS)-volumetric interpolated breath-hold examination (VIBE) (standard CS-VIBE) and late PVP image obtained using CS-VIBE with DL-based SR reconstruction algorithm to generate 1 mm-thickness images (DL-SR CS-VIBE). Arterial phase and 3-min delayed phase were also acquired using DL-SR CS-VIBE. The image quality of standard and DL-SR CS-VIBE PVP sequences was compared using Wilcoxon signed-rank test. The diagnostic performance of full-sequence pancreatobiliaryMRI including DL-SR CS-VIBE for predicting malignant IPMN was assessed using multi-reader multi-case analysis. Diagnostic accuracy was assessed using receiver operating characteristic analysis, while sensitivity and specificity were estimated with corresponding 95% confidence intervals. RESULTS: Among 162 patients, 15 had malignant IPMN, while 147 had benign IPMN. DL-SR CS-VIBE demonstrated significantly better overall image quality (3.73 ± 0.33 vs. 3.22 ± 0.43) and cystic lesion conspicuity (3.37 ± 0.50 vs. 2.71 ± 0.52) than standard CS-VIBE (all Ps < 0.001). The area under the ROC curve (AUC) for predicting malignant IPMN was 0.858 (95% CI: 0.807, 0.909). Using the presence of high-risk stigmata as an indicator of test-positive, pooled sensitivity and pooled specificity of pancreatobiliary MRI including DL-SR CS-VIBE for malignant IPMN were 71.1% (95% confidence interval [CI]: 55.7, 83.6) and 82.8% (95% CI: 78.9, 86.2), respectively. Among MRI features, diagnostic accuracy was highest for mural nodules ≥ 5 mm (AUC, 0.736) and main pancreatic duct size ≥ 10 mm (AUC, 0.720). CONCLUSION: Pancreatobiliary MRI with DL-SR CS-VIBE enhances image quality and lesion conspicuity, offering promising diagnostic accuracy for malignant IPMN, though further studies with larger cohorts are needed to refine these findings and evaluate clinical impact.

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