scholarly journals CT differentiation of gastric ectopic pancreas from gastric stromal tumor

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chang Liu ◽  
Fang Yang ◽  
Wenming Zhang ◽  
Weiqun Ao ◽  
Yongyu An ◽  
...  
Keyword(s):  
Stromal Tumor ◽  
Ectopic Pancreas ◽  
Arterial Phase ◽  
Portal Venous Phase ◽  
Test Efficiency ◽  
Ct Attenuation ◽  
Gastric Stromal Tumor ◽  
Venous Phase ◽  
Ct Attenuation Value ◽  
Ct Features

Abstract Background Gastric ectopic pancreas (GEPs) is a rare developmental anomaly which is difficult to differentiate it from submucosal tumor such as gastric stromal tumor (GST) by imaging methods. Since the treatments of the GEPs and GST are totally different, a correct diagnosis is essential. Therefore, we retrospectively investigated the CT features of them to help us deepen the understanding of GEPs and GST. Methods This study enrolled 17 GEPs and 119 GST, which were proven pathologically. We assessed clinical and CT features to identify significant differential features of GEPs from GST using univariate and multivariate analyses. Results In univariate analysis, among all clinicoradiologic features, features of age, symptom, tumor marker, location, contour, peritumoral infiltration or fat-line of peritumor, necrosis, calcification, CT attenuation value of unenhancement phase/arterial phase/portal venous phase (CTu/CTa/CTp), the CT attenuation value of arterial phase/portal venous phase minus that of unenhanced phase (DEAP/DEPP), long diameter (LD), short diameter (SD) were considered statistically significant for the differentiation of them. And the multivariate analysis revealed that location, peritumoral infiltration or fat-line of peritumor, necrosis and DEPP were independent factors affecting the identification of them. In addition, ROC analysis showed that the test efficiency of CTp was perfect (AUC = 0.900). Conclusion Location, the presence of peritumoral infiltration or fat-line of peritumor, necrosis and DEPP are useful CT differentiators of GEPs from GST. In addition, the test efficiency of CTp in differentiating them was perfect (AUC = 0.900).

scholarly journals CT differentiation of gastric ectopic pancreas from gastric stromal tumors

2020 ◽  
Author(s):  
Jian Wang ◽  
Chang LIU ◽  
Fang Yang ◽  
Wenming Zhang ◽  
Weiqun Ao ◽  
...  
Keyword(s):  
Univariate Analysis ◽  
Ectopic Pancreas ◽  
Arterial Phase ◽  
Portal Venous Phase ◽  
Test Efficiency ◽  
Attenuation Value ◽  
Ct Attenuation ◽  
Venous Phase ◽  
Ct Attenuation Value ◽  
Ct Features

Abstract BackgroundGastric ectopic pancreas (GEPs) is a rare developmental anomaly which is difficult to differentiate it from submucosal tumor such as gastrointestinal stromal tumor (GIST) by imaging methods. So we retrospectively investigated the CT features of them to help us make the correct diagnosis.Materials and MethodsThis study enrolled 17 GEPs and 119 GSTs, which were proven pathologically. We assessed clinical and CT features to identify significant differential features of GEPs from GSTs using univariate and multivariate analyses.ResultsIn univariate analysis, among all clinicoradiologic features, features of age, symptom, tumor marker, location, contour, blurred serosa or fat-line of peritumor, necrosis, calcification, CT attenuation value of unenhancement phase/arterial phase/portal venous phase (CTu/CTa/CTp), the CT attenuation value of arterial phase/portal venous phase minus that of unenhanced phase (DEAP/DEPP), long diameter (LD), short diameter (SD) were considered statistically significant for the differentiation of them. And the multivariate analysis revealed that location, blurred serosa or fat-line of peritumor, necrosis and DEPP were independent factors affecting the identification of them.What's more, ROC analysis showed that the test efficiency of CTp was perfect(AUC= 0.900).ConclusionLocation, blurred serosa or fat-line of peritumor, necrosis and DEPP are useful CT differentiators of GEPs from GSTs. In addition, the test efficiency of CTp in differentiating them was perfect (AUC=0.900).

Acute-onset abdominal pain in a woman in her 30s

Heart ◽  
2018 ◽  
Vol 105 (4) ◽  
pp. 275-322 ◽  
Author(s):  
Rory O’Donohoe ◽  
Samantha Fitzsimmons ◽  
Timothy J C Bryant
Keyword(s):  
Abdominal Pain ◽  
Hepatocellular Adenoma ◽  
Sudden Onset ◽  
Acute Onset ◽  
Arterial Phase ◽  
List Type ◽  
Portal Venous Phase ◽  
Venous Phase ◽  
Axial Ct ◽  
Multiphase Ct

Clinical introductionA woman in her 30s presented to the emergency department with sudden-onset abdominal pain with hypotension and tachycardia. She gave a history of congenital heart disease for which she had previously undergone multiple operations. On examination she demonstrated right upper quadrant tenderness. She underwent an urgent multiphase CT (figure 1A–C).Figure 1(A) Arterial phase coronal CT. (B) Arterial phase axial CT. (C) Portal venous phase axial CT.QuestionWhat is the underlying liver pathology?Hepatocellular adenomaCholangiocarcinomaHepatocellular carcinomaFocal nodular hyperplasiaHepatoblastoma

Case 5.6

2014 ◽  
pp. 253-253
Author(s):  
Christine U. Lee ◽  
James F. Glockner
Keyword(s):  
Abdominal Pain ◽  
Equilibrium Phase ◽  
Arterial Phase ◽  
Recurrent Pancreatitis ◽  
Portal Venous Phase ◽  
History Of ◽  
Venous Phase ◽  
Delayed Phase

37-year-old woman with a history of recurrent pancreatitis and abdominal pain Arterial phase (Figure 5.6.1A), portal venous phase (Figure 5.6.1B), equilibrium phase (Figure 5.6.1C), and 8-minute delayed phase (Figure 5.6.1D) postgadolinium 3D SPGR images show multiple splenic lesions that are initially hypoenhancing relative to adjacent spleen and become hyperintense on delayed images....

scholarly journals Advanced Deep Learning Approach to Automatically Segment Malignant Tumors and Ablation Zone in the Liver With Contrast-Enhanced CT

2021 ◽  
Vol 11 ◽  
Author(s):  
Kan He ◽  
Xiaoming Liu ◽  
Rahil Shahzad ◽  
Robert Reimer ◽  
Frank Thiele ◽  
...  
Keyword(s):  
Deep Learning ◽  
Liver Tumors ◽  
Treatment Success ◽  
Detection Sensitivity ◽  
Arterial Phase ◽  
Liver Segmentation ◽  
Portal Venous Phase ◽  
Venous Phase ◽  
Pre Treatment ◽  
Multi Phase

ObjectiveLiver cancer is one of the most commonly diagnosed cancer, and energy-based tumor ablation is a widely accepted treatment. Automatic and robust segmentation of liver tumors and ablation zones would facilitate the evaluation of treatment success. The purpose of this study was to develop and evaluate an automatic deep learning based method for (1) segmentation of liver and liver tumors in both arterial and portal venous phase for pre-treatment CT, and (2) segmentation of liver and ablation zones in both arterial and portal venous phase for after ablation treatment.Materials and Methods252 CT images from 63 patients undergoing liver tumor ablation at a large University Hospital were retrospectively included; each patient had pre-treatment and post-treatment multi-phase CT images. 3D voxel-wise manual segmentation of the liver, tumors and ablation region by the radiologist provided reference standard. Deep learning models for liver and lesion segmentation were initially trained on the public Liver Tumor Segmentation Challenge (LiTS) dataset to obtain base models. Then, transfer learning was applied to adapt the base models on the clinical training-set, to obtain tumor and ablation segmentation models both for arterial and portal venous phase images. For modeling, 2D residual-attention Unet (RA-Unet) was employed for liver segmentation and a multi-scale patch-based 3D RA-Unet for tumor and ablation segmentation.ResultsOn the independent test-set, the proposed method achieved a dice similarity coefficient (DSC) of 0.96 and 0.95 for liver segmentation on arterial and portal venous phase, respectively. For liver tumors, the model on arterial phase achieved detection sensitivity of 71%, DSC of 0.64, and on portal venous phase sensitivity of 82%, DSC of 0.73. For liver tumors >0.5cm3 performance improved to sensitivity 79%, DSC 0.65 on arterial phase and, sensitivity 86%, DSC 0.72 on portal venous phase. For ablation zone, the model on arterial phase achieved detection sensitivity of 90%, DSC of 0.83, and on portal venous phase sensitivity of 90%, DSC of 0.89.ConclusionThe proposed deep learning approach can provide automated segmentation of liver tumors and ablation zones on multi-phase (arterial and portal venous) and multi-time-point (before and after treatment) CT enabling quantitative evaluation of treatment success.

scholarly journals Conspicuity of Malignant Pleural Mesothelioma in Contrast Enhanced MDCT – Arterial Phase or Late Phase?

2021 ◽  
Author(s):  
Lukas Luerken ◽  
Philipp Laurin Thurn ◽  
Florian Zeman ◽  
Christian Stroszczynski ◽  
Okka Wilkea Hamer
Keyword(s):  
Multiple Regression ◽  
Late Phase ◽  
Objective Analysis ◽  
Surrounding Tissue ◽  
Arterial Phase ◽  
Subjective Analysis ◽  
Portal Venous Phase ◽  
Contrast Enhanced ◽  
Venous Phase ◽  
Phase Scan

Abstract Background: To compare two different contrast phases intraindividually regarding conspicuity of MPM in chest MDCT. Methods: 28 patients with MPM were included in this retrospective study. For all patients, chest CT in standard arterial phase and abdominal CT in portal venous phase (scan delay ca. 70 s) was performed. First, subjective analysis of tumor conspicuity was done independently by two radiologists. Second, objective analysis was done by measuring Hounsfield units (HU) in tumor lesions and in the surrounding tissue in identical locations in both phases. Differences of absolute HUs in tumor lesions between phases and differences of contrast (HU in lesion – HU in surrounding tissue) between phases were determined. HU measurements were compared using paired t-test for related samples. Potential confounding effects by different technical and epidemiological parameters between phases were evaluated performing a multiple regression analysis.Results: Subjective analysis: In all 28 patients and for both readers conspicuity of MPM was better on late phase compared to arterial phase. Objective analysis: MPM showed a significantly higher absolute HU in late phase (75.4 vs 56.7 HU, p < 0.001). Contrast to surrounding tissue was also significantly higher in late phase (difference of contrast between phases 18.5 HU, SD 10.6 HU, p < 0.001). Multiple regression analysis revealed contrast phase and tube voltage to be the only significant independent predictors for tumor contrast.Conclusions: In contrast enhanced chest-MDCT for MPM late phase scanning seems to provide better conspicuity and higher contrast to surrounding tissue compared to standard arterial phase scans.

scholarly journals Imaging features of hepatocellular carcinoma with bile duct tumor thrombus：a multicenter study

2020 ◽  
Author(s):  
Li-Ming Huang ◽  
Jun-Yi Wu ◽  
Yan-Nan Bai ◽  
Jia-Yi Wu ◽  
Yong-Gang Wei ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Bile Duct ◽  
Ct Scans ◽  
Arterial Phase ◽  
Imaging Features ◽  
Portal Venous Phase ◽  
Bile Duct Tumor ◽  
Hepatic Arterial Phase ◽  
Mri Scans ◽  
Venous Phase

Abstract Background: There are still difficult and challenging problems in diagnosis of hepatocellular carcinoma (HCC) with bile duct tumor thrombus (BDTT) before operation. This study aimed to analyze the imaging features of HCC with B1-B3 BDTT. Methods: The clinicopathological data and imaging findings of 30 HCC patients with B1-B3 BDTT from three high-volume institutions were retrospectively reviewed. Eighteen patients underwent computed tomography (CT) scans and twelve patients underwent magnetic resonance imaging (MRI) scans before operation, respectively. The diagnosis of HCC with BDTT was confirmed by postoperative pathologic examination.Results: According to Japanese classification, 5 patients were classified as B1 BDTT, 12 B2, 13 B3, and 82 B4, respectively. The HCC lesions were detected in all patients, and the localized bile duct dilation were detected in 28 (93.3%) patients. The BDTT was observed in all B3 patients and 3 B2 patients, but it was not observed in all B1 patients on CT or MRI. The BDTT showed relatively hypoattenuation on plain CT scans and T1W images, relatively hyperattenuation signals on T2W. The BDTT showed hyperattenuation at hepatic arterial phase with washout at portal venous phase. The localized biliary dilation showed no enhancement at hepatic arterial phase and no progressively delayed enhancement at portal venous phase, but it was more obvious at portal venous phase on CT.Conclusions: The HCC lesions and the localized bile duct dilatation on CT or MRI scans are imaging features of HCC with BDTT, which might facilitate the early diagnosis for B1-B3 BDTT.

Case 2.19

2014 ◽  
pp. 99-100
Author(s):  
Christine U. Lee ◽  
James F. Glockner
Keyword(s):  
Liver Transplantation ◽  
Portal Vein ◽  
Living Donor ◽  
Living Donor Liver Transplantation ◽  
Phase Image ◽  
Arterial Phase ◽  
Main Portal Vein ◽  
Portal Venous Phase ◽  
Donor Liver Transplantation ◽  
Venous Phase

32-year-old man status post living donor liver transplantation for PSC Postgadolinium arterial phase image (Figure 2.19.1) demonstrates a hepatic artery stump (cutoff) at the level of the anastomosis. A subsequent axial portal venous phase image (Figure 2.19.2) at the level of the porta hepatis shows an absent main portal vein, which is confirmed on the coronal reformatted image (...

Value of CT Imaging in the Differentiation of Gastric Leiomyoma From Gastric Stromal Tumor

2020 ◽  
pp. 084653711988567
Author(s):  
Jian Wang ◽  
Xiaoxuan Zhou ◽  
Fangyi Xu ◽  
Weiqun Ao ◽  
Hongjie Hu
Keyword(s):  
Computed Tomography ◽  
Multivariate Logistic Regression Analysis ◽  
Fisher Exact Test ◽  
Exact Test ◽  
Portal Venous Phase ◽  
Ct Value ◽  
Unenhanced Ct ◽  
Gastric Stromal Tumor ◽  
Venous Phase ◽  
Gastric Leiomyoma

Purpose: To discuss significant computed tomography (CT) findings that differentiate gastric leiomyomas (GLs) from small gastric stromal tumors (GSTs). Methods: One hundred sixty cases with pathologically proven GLs (n = 50) and GSTs (n = 110) with comprehensive CT images were enrolled in this retrospective study. Computed tomography findings (ie, size, location, contour, growth pattern, enhancement degree, necrosis, ulceration, calcification, and lymph nodes) were analyzed through the χ2 or Fisher exact test, independent T test, and multivariate (logistic regression) analysis. Sensitivity and specificity were also calculated. Results: Features of cardia location, endophytic growth, homogeneous gradual enhancement, absent of necrosis, long diameter less than 24 mm, short diameter less than 20 mm, unenhanced CT value larger than 35.2 Hounsfield units (HU), portal venous phase CT value larger than 67.4 HU, and enhancement degree of arterial and venous phase less than 16.2 HU and 32.4 HU were found to be statistically significant between GLs and small GSTs ( P < .05). On multivariate analysis, cardia location, endophytic growth, and homogeneous gradual enhancement were independent predictive factors for GLs and small GSTs. Conclusion: These 10 CT criteria are very helpful to differentiate GLs from small GSTs. Especially cardia location, endophytic growth, and homogeneous gradual enhancement are of high value in differential diagnosis.

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