Evidence map›Paper›PMID 40619481›Full record

ArticleAbdominal radiology (New York)2026

Multiparameter pancreatic parenchyma assessment using Dual-layer Spectral-detector CT for postpancreatectomy acute pancreatitis prediction.

Haoda Chen, Yanzhao Yang, Ningzhen Fu, Jingyu Zhong, Yuchen Ji, Weimin Chai, Fuhua Yan, Naiyi Zhu

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Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Haoda ChenDepartment of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. haodac03@126.com.
Yanzhao YangDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ningzhen FuDepartment of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jingyu ZhongDepartment of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yuchen JiDepartment of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Weimin ChaiDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Fuhua YanDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Naiyi ZhuDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. zny11682@rjh.com.cn.

Funding

National Natural Science Foundation of China 82302183Research Fund of Tongren Hospital, Shanghai Jiao Tong University School of Medicine TRKYRC-XX202204
6 · The paper itself

Abstract

backgroundPost-pancreatectomy acute pancreatitis (PPAP) has been increasingly recognized as an independent complication since its formal definition by the International Study Group for Pancreatic Surgery (ISGPS) in 2022. This study aimed to evaluate the diagnostic accuracy of multiparameter assessment of pancreatic parenchyma using dual-layer spectral-detector CT (DLCT) in predicting PPAP after pancreaticoduodenectomy (PD).

methodsConsecutive patients who underwent PD and preoperative DLCT between January 2020 and June 2022 were retrospectively analyzed. Iodine concentration (IC) and Hounsfield unit (HU) values of the pancreatic parenchyma were measured in the non-enhanced (N), arterial (A), portal venous (P), and equilibrium (E) phases. CT enhancement patterns were quantified by the A/E ratios of IC and HU values. The extracellular volume (ECV) fraction was calculated based on iodine concentration (ECV. IC) and HU values (ECV. HU) of the equilibrium phase.

resultsA total of 550 patients were included in the analysis. Of these, 101 (18.3%) patients developed PPAP after PD and had significantly lower IC in the P and E phases compared to those without PPAP (both p < 0.001). Among the composite parameters, the ECV. IC fraction demonstrated the highest accuracy (AUC = 0.784, 95%CI, 0.739-0.829) for predicting PPAP compared to the ECV. HU fraction, A/E HU ratio, (A-N)/(E-N) HU ratio, and A/E IC ratio (AUCs of 0.726, 0.741, 0.743, and 0.751, respectively). On multivariate analysis, an ECV.IC fraction < 30.6% was independently associated with the occurrence of PPAP (OR 7.44, 95% CI: 4.23-13.11, p < 0.001), with sensitivity of 76.2% and specificity of 69.5%.

conclusionsMultiparameter assessment of pancreatic parenchyma derived from DLCT showed excellent accuracy for preoperatively predicting PPAP after PD.

Indexed as

PancreaticoduodenectomyPancreatitisPostoperative ComplicationsTomography, X-Ray ComputedAcute DiseaseAdultAgedFemaleHumansMaleMiddle AgedPancreasPredictive Value of TestsRetrospective StudiesSensitivity and SpecificityComplicationsComputed tomographyDual layer detectorPancreaticoduodenectomyPancreatitis

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PMID40619481

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.