ROLE OF MULTIPHASE STUDY OF LIVER LESIONS ON 128 SLICE DUAL SOURCE COMPUTED TOMOGRAPHY (CT) WITH CYTOLOGY OR HISTOPATHOLOGICAL CORRELATION

2016 ◽  
Vol 1 (2) ◽  
Author(s):  
Nisma Waheed ◽  
Rajneesh Madhok ◽  
Ashish Kumar Gupta ◽  
Tanu Agarwal
Keyword(s):  
Computed Tomography ◽  
Radiology Department ◽  
Arterial Phase ◽  
Liver Lesions ◽  
Common Pattern ◽  
Portal Venous Phase ◽  
Histopathological Correlation ◽  
Dual Source ◽  
Venous Phase ◽  
Delayed Scan

Introduction: Dual source Multidetector Computed Tomography (MDCT) provides multiphase study of various liver lesions for better detection and characterization. This study aims to detect and characterize the liver lesions in multiphase Computed Tomography (CT) with cytological and histopathological correlation to confirm the diagnosis. Material and Methods: This cross-sectional study included 65 patients who were referred to the Radiology Department of Shri Ram Murti Smarak Institute of Medical Sciences, Bareilly, Uttar Pradesh, India with clinical features jaundice, pain in abdomen, nausea and vomiting. All patients were evaluated by five phase CT (unenhanced, early and late arterial, portal venous and delayed scan) of liver with Siemens128 slice dual source spiral CT. Protocols with a scan delay of 06 seconds, 09 seconds, 45 seconds and 180-300 seconds from contrast bolus was preselected for early and late arterial, portovenous and delayed scans. Results: Sixty five (age 10yrs- 90yrs) patients were included in the study. Most common neoplasm was metastases 33(51%). Hepatocellular carcinoma (HCC) were 18(28%), hemangioma 10(15%), peripheral intrahepatic cholangiocarcinoma 1 and 3 were non-neoplastic which included hepatic abscesses and hydatid cyst. Most common pattern of enhancement of metastasis in arterial phase was hypodense with peripheral enhancement and most were hypodense in portal venous phase. Portal venous phase had highest grade for hypovascular metastases and arterial phase had high grade to detect hypervascular metastasis. Delayed scan was better for smaller lesions less than 1cm. The sensitivity to detect metastases was 94%. Most common pattern of enhancement in HCC (variegated or heterogeneous enhancement in arterial phase with rapid washout in the portal venous phase. Total sensitivity to detect HCC was 83.3%. Hemangioma showed peripheral globular enhancement in arterial phase. In portal venous and delayed phase showed progressive enhancement with more centripetal filling. Sensitivity was 90% in case of hemangiomas. Conclusion: Multiphasic CT scan is a good non-invasive tool and can be used as first line imaging modality for differentiating benign and malignant liver lesions.

Assessment of Cirrhotic Liver Enhancement with Multiphasic Computed Tomography Using a Faster Injection Rate, Late Arterial Phase, and Weight-Based Contrast Dosing

2017 ◽  
Vol 68 (4) ◽  
pp. 371-378 ◽  
Author(s):  
Kathleen Eddy ◽  
Andreu F. Costa
Keyword(s):  
Computed Tomography ◽  
Injection Rate ◽  
Fixed Dose ◽  
Arterial Phase ◽  
Intravenous Contrast ◽  
Portal Venous Phase ◽  
Liver Ct ◽  
Iodinated Contrast ◽  
Ct Protocol ◽  
Venous Phase

Purpose This study aimed to update our liver computed tomography (CT) protocol according to published guidelines, and to quantitatively evaluate the effect of these modifications. Methods The modified liver CT protocol employed a faster injection rate (5 vs 3 mL/s), later arterial phase (20-second vs 10-second postbolus trigger), and weight-based dosing of iodinated contrast (1.7 mL/kg vs 100 mL fixed dose). Liver and vascular attenuation values were measured on CTs of patients with cirrhosis from January to September 2015 (old protocol, n = 49) and from October to December 2015 (modified protocol, n = 31). CTs were considered adequate if liver enhancement exceeded 50 Hounsfield units (HU) in portal venous phase, or when the unenhanced phase was unavailable, if a minimum iodine concentration of 500 mg I/kg was achieved. Attenuations and iodine concentrations were compared using the t test and the number of suboptimal studies was compared with Fisher's exact test. Results CTs acquired with the modified protocol demonstrated higher aortic ( P = .001) and portal vein ( P < .0001) attenuations in the arterial phase as well as greater hepatic attenuation on all postcontrast phases ( P = .0006, .002, and .003 for arterial, venous, and equilibrium phases, respectively). Hepatic enhancement in the portal venous phase (61 ± 15 HU vs 51 ± 16 HU; P = .0282) and iodine concentrations (595 ± 88 mg I/kg vs 456 ± 112 mg I/kg; P < .0001) were improved, and the number of suboptimal studies was reduced from 57% to 23% ( P = .01). Conclusions A liver CT protocol with later arterial phase, faster injection rate, and weight-based dosing of intravenous contrast significantly improves liver enhancement and iodine concentrations in patients with cirrhosis, resulting in significantly fewer suboptimal studies.

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....

Virtual Monoenergetic Images From a Novel Dual-Layer Spectral Detector Computed Tomography Scanner in Portal Venous Phase

2018 ◽  
Vol 42 (3) ◽  
pp. 350-356 ◽  
Author(s):  
Tilman Hickethier ◽  
Andra-Iza Iuga ◽  
Simon Lennartz ◽  
Myriam Hauger ◽  
Jonathan Byrtus ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Portal Venous Phase ◽  
Venous Phase ◽  
Virtual Monoenergetic Images ◽  
Computed Tomography Scanner ◽  
Monoenergetic Images

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).

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 &gt;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.

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