scholarly journals Incidentally Detected Liver Metastases during Pancreas Contrast-enhanced Ultrasound

2021 ◽  
Author(s):  
Dan Zuo ◽  
Ji-Jiang Qian ◽  
Yi Dong ◽  
Wen-Ping Wang ◽  
Xiao-Fan Tian ◽  
...  
Keyword(s):  
Liver Metastases ◽  
Predictive Value ◽  
Clinical Decision Making ◽  
Late Phase ◽  
Clinical Decision ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced ◽  
Multiple Imaging ◽  
Liver Scan ◽  
Histopathological Results

Purpose: The purpose of current study was to investigate the value of the late-phase enhancement features of pancreas contrast-enhanced ultrasound (CEUS) in the detection of liver metastases in patients with pancreatic ductal adenocarcinomas (PDAC).Methods: From October 2020 to March 2021, 86 patients were prospectively enrolled. The gold standard of liver metastatic and PDAC lesions were based on histopathologically diagnoses and multiple imaging modalities results. B-mode ultrasound (BMUS) was performed to detect suspected liver metastases before CEUS. During the late phase of pancreas CEUS, the entire liver was scanned again to detect hypoenhanced liver metastases. Liver metastases were confirmed by biopsy and histopathological results. The number and size of liver metastases detected by BMUS and during CEUS late phase were recorded and compared.Results: Suspected liver metastases were detected in 14 patients by BMUS (n = 23). During the late phase of CEUS, hypoenhanced liver metastases were detected in 23 patients (n = 87). When compared with BMUS, whole-liver scan during the late phase of CEUS detected more isoechoic, small, or superficially located lesions. Compared with BMUS, the specificity, sensitivity, positive predictive value, and negative predictive value of CEUS in diagnosing of liver metastases in PDAC patients were significantly improved (96.72% vs. 100%, 48% vs. 92%, 85.71% vs. 100%, and 83.10% vs. 96.83%, respectively) (P < 0.05).Conclusion: The late phase whole liver scan during CEUS of pancreas helps to detect more liver metastases, which is important for further clinical decision-making.

scholarly journals Contrast-Enhanced Ultrasound for Assessing Abdominal Conditions in Pregnancy

Medicina ◽  
2020 ◽  
Vol 56 (12) ◽  
pp. 675
Author(s):  
Thomas Geyer ◽  
Johannes Rübenthaler ◽  
Matthias F. Froelich ◽  
Laura Sabel ◽  
Constantin Marschner ◽  
...  
Keyword(s):  
Contrast Agents ◽  
Pregnant Women ◽  
Clinical Decision Making ◽  
Imaging Modality ◽  
Clinical Decision ◽  
Renal Angiomyolipoma ◽  
Contrast Enhanced Ultrasound ◽  
Vein Thrombosis ◽  
Contrast Enhanced ◽  
Level 3

Background and objectives: Native ultrasound is the most common imaging modality in obstetrics. The use of contrast-enhanced ultrasound (CEUS) during pregnancy has not been officially approved by leading societies for obstetrics and ultrasound. The present study aims to monitor the safety and diagnostic performance of CEUS for assessing abdominal issues in five pregnant women. Materials and Methods: Five pregnant patients who underwent a total of 11 CEUS examinations between June 2020 and October 2020 were included (mean age: 34 years; mean time of pregnancy: 21 weeks). All CEUS scans were interpreted by one experienced consultant radiologist (EFSUMB Level 3). Results: Upon contrast application, no maternal nor fetal adverse effects were observed. Moreover, no fetal contrast enhancement was observed in any patient. CEUS helped to diagnose renal angiomyolipoma, pyelonephritis, necrotic uterine fibroid, gallbladder polyp, and superior mesenteric vein thrombosis. Conclusions: In our study, off-label use of CEUS showed an excellent safety profile allowing the avoidance of ionizing radiation exposure as well as contrast agents in case of CT or use of gadolinium-based contrast agents in case of MRI. CEUS is a promising diagnostic instrument for facilitating clinical decision-making and improving the management of pregnant women.

scholarly journals How to perform Contrast-Enhanced Ultrasound (CEUS)

2018 ◽  
Vol 04 (01) ◽  
pp. E2-E15 ◽  
Author(s):  
Christoph Dietrich ◽  
Michalakis Averkiou ◽  
Michael Nielsen ◽  
Richard Barr ◽  
Peter Burns ◽  
...  
Keyword(s):  
Decision Making ◽  
Personal Experience ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Ultrasound Contrast Agents ◽  
Contrast Enhanced Ultrasound ◽  
Technical Parameters ◽  
Ultrasound Contrast ◽  
Published Evidence ◽  
Contrast Enhanced

Abstract“How to perform contrast-enhanced ultrasound (CEUS)” provides general advice on the use of ultrasound contrast agents (UCAs) for clinical decision-making and reviews technical parameters for optimal CEUS performance. CEUS techniques vary between centers, therefore, experts from EFSUMB, WFUMB and from the CEUS LI-RADS working group created a discussion forum to standardize the CEUS examination technique according to published evidence and best personal experience. The goal is to standardise the use and administration of UCAs to facilitate correct diagnoses and ultimately to improve the management and outcomes of patients.

Contrast-Enhanced Ultrasound: a Simple and Effective Tool in Defining a Rapid Diagnostic Work-up for Small Nodules Detected in Cirrhotic Patients during Surveillance

2016 ◽  
Vol 25 (2) ◽  
pp. 205-211 ◽  
Author(s):  
Antonio Giorgio ◽  
Luca Montesarchio ◽  
Piero Gatti ◽  
Ferdinando Amendola ◽  
Paolo Matteucci ◽  
...  
Keyword(s):  
Predictive Value ◽  
Imaging Modality ◽  
Dynamic Imaging ◽  
Contrast Enhanced Ultrasound ◽  
Histologic Diagnosis ◽  
Therapeutic Work ◽  
Contrast Enhanced ◽  
Arterial Vascularization ◽  
Cirrhotic Patients ◽  
Work Up

  Background & Aims: Disappearance of portal blood flow and arterial vascularization is the hallmark of hepatocarcinogenesis. The capability of a dynamic imaging modality detecting arterial hypervascularization of small nodules is crucial to promote a rapid diagnostic and therapeutic work-up improving survival. We aimed to evaluate the capability of CEUS to detect arterial vascularization of ≤ 2 cm HCC nodules arising during surveillance so as to shorten the diagnostic and therapeutic work-up. Methods: From October 2009 to September 2014, among 1757 consecutive cirrhotic patients under surveillance with ultrasound (US), 243 patients had new single nodules 7-20 mm; 229/243 had a conclusive histologic diagnosis and comprised the study group. All patients underwent CEUS followed by enhanced MRI and US guided percutaneous 18G needle core biopsy of the nodules. Of the 229 nodules, 27 were hyperechoic, 171 hypoechoic and 31 isoechoic lesions. Results: The histology results revealed that 199/229 nodules were HCC and 30 were benign. Of 199 HCC, CEUS evidenced arterial hypervascularity in 190 nodules (95.5%) (sensitivity 94.48 %, specificity 100%, PPV 100%, NPV 76.92 %). Of the 39 CEUS arterial-unenhanced nodules, 30 were benign and 9 (23%) were well-differentiated HCC. eMRI showed arterial hypervascularity in 199 nodules (86,9%). Of these, only 193 (97%) were histologically HCCs while 6 were benign (sensitivity: 97%, specificity: 80%, PPV: 97%, NPV: 80%). Conclusions: CEUS has a great capability to detect arterial hypervascularity of small HCC. Because only 4.5% of new nodules escape the demonstration of arterial hyervascularity, CEUS must be performed immediately after conventional US to contrast the malignant fate of small lesions arising in a cirrhotic liver.. Abbreviations: CEUS: contrast-enhanced ultrasound; CT: computed tomography; HCC: hepatocellular carcinoma;MRI: magnetic resonance; NPV: negative predictive value; PPV: positive predictive value; US: ultrasonography.

scholarly journals Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver Lesions

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1244
Author(s):  
Sonja Schwarz ◽  
Dirk-André Clevert ◽  
Michael Ingrisch ◽  
Thomas Geyer ◽  
Vincent Schwarze ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Diagnostic Accuracy ◽  
Late Phase ◽  
Focal Liver Lesions ◽  
Liver Lesions ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced ◽  
Malignant Lesions ◽  
Benign Liver ◽  
Benign Liver Lesions

Background: To evaluate the diagnostic accuracy of quantitative perfusion parameters in contrast-enhanced ultrasound to differentiate malignant from benign liver lesions. Methods: In this retrospective study 134 patients with a total of 139 focal liver lesions were included who underwent contrast enhanced ultrasound (CEUS) between 2008 and 2018. All examinations were performed by a single radiologist with more than 15 years of experience using a second-generation blood pool contrast agent. The standard of reference was histopathology (n = 60), MRI or CT (n = 75) or long-term CEUS follow up (n = 4). For post processing regions of interests were drawn both inside of target lesions and the liver background. Time–intensity curves were fitted to the CEUS DICOM dataset and the rise time (RT) of contrast enhancement until peak enhancement, and a late-phase ratio (LPR) of signal intensities within the lesion and the background tissue, were calculated and compared between malignant and benign liver lesion using Student’s t-test. Quantitative parameters were evaluated with respect to their diagnostic accuracy using receiver operator characteristic curves. Both features were then combined in a logistic regression model and the cumulated accuracy was assessed. Results: RT of benign lesions (14.8 ± 13.8 s, p = 0.005), and in a subgroup analysis, particular hemangiomas (23.4 ± 16.2 s, p < 0.001) differed significantly to malignant lesions (9.3 ± 3.8 s). The LPR was significantly different between benign (1.59 ± 1.59, p < 0.001) and malignant lesions (0.38 ± 0.23). Logistic regression analysis with RT and LPR combined showed a high diagnostic accuracy of quantitative CEUS parameters with areas under the curve of 0.923 (benign vs. malignant) and 0.929 (hemangioma vs. malignant. Conclusions: Quantified CEUS parameters are helpful to differentiate malignant from benign liver lesions, in particular in case of atypical hemangiomas.

Abstract W P266: A Simple Score for Prediction of Outcome after Cerebral Venous Thrombosis

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Miguel A Barboza ◽  
Erwin Chiquete ◽  
Antonio Arauz ◽  
Jonathan Colín ◽  
Alejandro Quiroz-Compean ◽  
...  
Keyword(s):  
Decision Making ◽  
Venous Thrombosis ◽  
Predictive Value ◽  
Cerebral Venous Thrombosis ◽  
Goodness Of Fit ◽  
Clinical Decision Making ◽  
Case Fatality ◽  
Clinical Decision ◽  
Classification Systems ◽  
Cox Proportional Hazards Model

Background and purpose: Cerebral venous thrombosis (CVT) not always implies a good prognosis. There is a need for robust and simple classification systems of severity after CVT that help in clinical decision-making. Methods: We studied 467 patients (81.6% women, median age: 29 years, interquartile range: 22-38 years) with CVT who were hospitalized from 1980 to 2014 in two third-level referral hospitals. Bivariate analyses were performed to select variables associated with 30-day mortality to integrate a further multivariate analysis. The resultant model was evaluated with the Hosmer-Lemeshow test for goodness of fit, and on Cox proportional hazards model for reliability of the effect size. After the scale was configured, security and validity were tested for 30-day mortality and modified Rankin scale (mRS) >2. The prognostic performance was compared with that of the CVT risk score (CVT-RS, 0-6 points) as the reference system. Results: The 30-day case fatality rate was 8.7%. The CVT grading scale (CVT-GS, 0-9 points) was integrated by stupor/coma (4 points), parenchymal lesion >6 cm (2 points), mixed (superficial and deep systems) CVT (1 point), meningeal syndrome (1 point) and seizures (1 point). CVT-GS was categorized into mild (0-3 points, 1.1% mortality), moderate (4-6 points, 19.6% mortality) and severe (7-9 points, 61.4% mortality). For 30-day mortality prediction, as compared with CVT-RS (cut-off 4 points), CVT-GS (cut-off 5 points) was globally better in sensitivity (85% vs 37%), specificity (90% vs 95%), positive predictive value (44% vs 40%), negative predictive value (98% vs 94%), and accuracy (94% vs 80%). For 30-day mRS >2 the performance of CVT-GS over CVT-RS was comparably improved. Conclusion: The CVT-GS is a simple and reliable score for predicting outcome that may help in clinical decision-making and that could be used to stratify patients recruited into clinical trials.

scholarly journals CT-Based Radiomics Analysis for Preoperative Diagnosis of Pancreatic Mucinous Cystic Neoplasm and Atypical Serous Cystadenomas

2021 ◽  
Vol 11 ◽  
Author(s):  
Tiansong Xie ◽  
Xuanyi Wang ◽  
Zehua Zhang ◽  
Zhengrong Zhou
Keyword(s):  
Predictive Value ◽  
Cross Validation ◽  
Clinical Decision Making ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Cystic Neoplasm ◽  
Cystic Neoplasms ◽  
Serous Cystadenomas ◽  
Radiological Model ◽  
Fold Cross Validation

ObjectivesTo investigate the value of CT-based radiomics analysis in preoperatively discriminating pancreatic mucinous cystic neoplasms (MCN) and atypical serous cystadenomas (ASCN).MethodsA total of 103 MCN and 113 ASCN patients who underwent surgery were retrospectively enrolled. A total of 764 radiomics features were extracted from preoperative CT images. The optimal features were selected by Mann-Whitney U test and minimum redundancy and maximum relevance method. The radiomics score (Rad-score) was then built using random forest algorithm. Radiological/clinical features were also assessed for each patient. Multivariable logistic regression was used to construct a radiological model. The performance of the Rad-score and the radiological model was evaluated using 10-fold cross-validation for area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy.ResultsTen screened optimal features were identified and the Rad-score was then built based on them. The radiological model was built based on four radiological/clinical factors. In the 10-fold cross-validation, the Rad-score was proved to be robust and reliable (average AUC: 0.784, sensitivity: 0.847, specificity: 0.745, PPV: 0.767, NPV: 0.849, accuracy: 0.793). The radiological model performed slightly less well in classification (average AUC: average AUC: 0.734 sensitivity: 0.748, specificity: 0.705, PPV: 0.732, NPV: 0.798, accuracy: 0.728.ConclusionsThe CT-based radiomics analysis provided promising performance for preoperatively discriminating MCN from ASCN and showed good potential in improving diagnostic power, which may serve as a novel tool for guiding clinical decision-making for these patients.

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