Double contrast-enhanced ultrasonography in the detection of periampullary cancer: Comparison with B-mode ultrasonography and MR imaging

Zhang, Ting; Su, Zhongzhen; Wang, Ping; Wu, Tao; Tang, Wen; Xu, Erjiao; Ju, Jinxiu; Quan, Xianyue; Zheng, Rongqin

doi:10.1016/j.ejrad.2016.08.021

Cited by 10 publications

(22 citation statements)

References 23 publications

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“…Meanwhile, MRCP can show the morphology of the bile and pancreatic ducts, and MRI can uncover periductal masses and pancreatic parenchymal abnormalities, which improves the specificity of MRCP [25, 26]. In our study, the diagnostic accuracy for PSOLs by MRI was 91.17%, which is similar to a previous study [6]. The similarity may be attributed to DCE-MRI, which can quantify the blood flow, microvascular, and capillary permeability of tumors [27].…”

Section: Discussionsupporting

confidence: 87%

“…Currently, there are no specific symptoms or laboratory markers to quickly and accurately diagnose patients with benign or malignant PSOLs. Diagnostic imaging modalities, including magnetic resonance imaging (MRI) and contrast-enhanced ultrasound (CEUS), have been successfully used for the detection and diagnosis of PSOLs [6]. MRI is the preferred method for evaluating PSOLs due to its high soft-tissue resolution and lack of ionizing irradiation.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, MRI requires a magnetic field that is contradicted for patients with cardiac pacemakers, metal clips, or metal stents [8]. Previously, the specificity and accuracy of MRI for PSOLs were found to be 78.3 and 91.5%, respectively [6, 11].…”

Section: Introductionmentioning

confidence: 99%

“…The primary advantages of CEUS include its high temporal resolution, lack of ionizing radiation, and real-time imaging capabilities [15]. However, CEUS is not preferred for imaging of PAC as its specificity and accuracy are inferior to MRI [6, 15]. Moreover, CEUS has some limitations, including its dependence on the operator experience and inability to visualize tissues at depths greater than 3 cm [16].…”

Section: Introductionmentioning

confidence: 99%

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Combination of CEUS and MRI for the diagnosis of periampullary space-occupying lesions: a retrospective analysis

et al. 2019

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Background The value of magnetic resonance imaging (MRI), contrast-enhanced ultrasound (CEUS), and the combination of CEUS and MRI (CCWM) for the diagnosis of periampullary space-occupying lesions (PSOL) was investigated. Methods A total of 102 patients diagnosed with PSOLs by surgery or biopsy were recruited retrospectively. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of MRI, CEUS, and CCWM were analyzed. Results MRI, CEUS, and CCWM allowed for the accurate detection of 91.17, 92.15, and 99.01% of PSOLs, respectively. The specificity, PPV, and accuracy of CCWM were significantly different from MRI and CEUS ( p < 0.05). However, there the sensitivity and NPV were not significantly different among the three diagnostic technologies. In addition, the specificity, PPV, and accuracy were not significantly different between MRI and CEUS (all p > 0.05). Conclusions CCWM is valuable for differentiating benign and malignant PSOL, which provides important guiding significances for the clinic.

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Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Combination of CEUS and MRI for the diagnosis of periampullary space-occupying lesions: a retrospective analysis

et al. 2019

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“…Meanwhile, due to the multiple kinds of lesions in PA, as well as the lack of special serum markers, it is particularly difficult to early diagnose tumors accurately, which lead to poor prognosis of PAC. 5,6 Currently, non-invasive diagnostic methods, including ultrasound scan, computed tomography (CT) imaging as well as magnetic resonance imaging (MRI), have been successfully applied to the detection and diagnosis of PAC. 7,8 So far, among all these modern imaging techniques, MRI is a preferable choice to detect PAC for its advantages of excellent soft-tissue contrast and less radiation exposures.…”

Section: Introductionmentioning

confidence: 99%

Identifying Periampullary Regions in MRI Images Using Deep Learning

Tang

Chen

Wang

et al. 2020

Preprint

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Background: Development and validation of a deep learning method to automatically segment the peri-ampullary (PA) region in magnetic resonance imaging (MRI) images. Methods: A group of patients with or without periampullary carcinoma (PAC) was included. The PA regions were manually annotated in MRI images by experts. Patients were randomly divided into one training set and one validation set. A deep learning method to automatically segment the PA region in MRI images was developed using the training set. The segmentation performance of the method was evaluated in the validation set. Results: The deep learning algorithm achieved optimal accuracies in the segmentation of the PA regions in both T1 and T2 MRI images. The value of the intersection over union (IoU) was 0.67 and 0.68 for T1 and T2 images, respectively. Conclusions: Deep learning algorithm is promising with accuracies of concordance with manual human assessment in segmentation of the PA region in MRI images. This automated non-invasive method helps clinicians to identify and locate the PA region using preoperative MRI scanning.

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Differential diagnostic value of periampullary mass: A nomogram established by random forest based on clinical characteristics and contrast‐enhanced ultrasound

Zhu

Yang

et al. 2022

J of Clinical Ultrasound

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Purposes: To develop a nomogram model for distinguishing benign from malignant ampullary lesions more intuitive and accurate. Materials and Methods: A total of 124 patients with periampullary lesions from January 2016 to June 2020 were enrolled in this retrospective study. Their clinical information, ultrasound (US), dual contrast-enhanced ultrasound (DCEUS) and MRI image features were used for research. Twenty features were collected in our study. Random forest was used to select the first five most important indicators to construct the prediction model. Results: Patients' age, common bile duct (CBD) diameter, the shape, vascularity, and boundary of lesion, lesion size with or without enlarged after CEUS, the enhancement patterns of arterial phase, the washout patterns of venous phase, CEUS diagnosis, and MRI diagnosis were statistically significant (p < 0.05). After screening for statistically significant indicators by random forest, the first five most important indicators were age,CBD diameter, the enhancement patterns of arterial phase, the washout patterns of venous phase, lesion size with or without enlarged after CEUS, which were used to construct nomogram. The area under curves (AUC) and 95% confidence intervals (CI) for nomogram, MRI + MRCP + DCEUS, DCEUS, MRI + MRCP were 0.98(0.94-1.00), 0.91 (0.84-0.97), 0.89(0.80-0.98), 0.68(0.60-0.77), respectively. The sensitivity and specificity were 100.00% and 84.62% for nomogram, 88.29% and 92.31% for MRI + MRCP+-DCEUS, 86.49% and 92.31% for DCEUS, 51.35%, and 100.00% for MRI + MRCP. Conclusions:We combined clinical indicators, gray-scale ultrasound characteristics, and CEUS characteristics to build the nomogram, which can be intuitively and accurately used for preoperative malignant prediction of ampullary lesion patients, worthy of clinical generalizability and application.

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Double contrast-enhanced ultrasonography in the detection of periampullary cancer: Comparison with B-mode ultrasonography and MR imaging

Cited by 10 publications

References 23 publications

Combination of CEUS and MRI for the diagnosis of periampullary space-occupying lesions: a retrospective analysis

Combination of CEUS and MRI for the diagnosis of periampullary space-occupying lesions: a retrospective analysis

Identifying Periampullary Regions in MRI Images Using Deep Learning

Differential diagnostic value of periampullary mass: A nomogram established by random forest based on clinical characteristics and contrast‐enhanced ultrasound

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