Intratumoral artery on contrast-enhanced computed tomography imaging: differentiating intrahepatic cholangiocarcinoma from poorly differentiated hepatocellular carcinoma

Tsunematsu, Seiji; Chuma, Makoto; Kamiyama, Toshiya; Miyamoto, Noriyuki; Yabusaki, Satoshi; Hatanaka, Kanako C.; Mitsuhashi, Tomoko; Kamachi, Hirofumi; Yokoo, Hideki; Kakisaka, Tatsuhiko; Tsuruga, Yousuke; Orimo, Tatsuya; Wakayama, Kenji; Ito, Jun; Sato, Fumiyuki; Terashita, Katsumi; Nakai, Masato; Tsukuda, Yoko; Sho, Takuya; Suda, Goki; Morikawa, Kenichi; Natsuizaka, Mitsuteru; Nakanishi, M.; Ogawa, Koji; Taketomi, Akinobu; Matsuno, Yoshihiro; Sakamoto, Naoya

doi:10.1007/s00261-015-0352-9

Cited by 35 publications

(17 citation statements)

References 23 publications

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“…IMCC usually have an appearance of capsule retraction. Some researchers thought scirrhous stroma of ICC was related to the imaging of capsular retraction ( 19 ). Resembling the classic findings of IMCC in noncirrhotic liver, bile duct dilatation is also a characteristic of IMCC in cirrhotic liver, because IMCC arises from the ductular epithelium of the biliary tree and regularly accompanies with bile duct wall infiltration leading to bile ducts stricture or blocking while the adjacent bile ducts dilatate.…”

Section: Discussionmentioning

confidence: 99%

Contrast-enhanced multiple-phase imaging features of intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma with cirrhosis: A comparative study

et al. 2017

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The intrahepatic mass-forming cholangiocarcinoma (IMCC) is frequently misdiagnosed as hepatocellular carcinoma (HCC) in patients with cirrhosis, by numerous radiologists and clinical doctors, which results in the incorrect therapeutic treatment. A retrospective case-control study was conducted, and the contrast-enhanced multiple-phase (CEMP) computed tomography (CT) and magnetic resonance imaging (MRI) findings of 22 pathologically confirmed IMCC patients and 22 HCC controls with underlying liver cirrhosis were analyzed at the present hospital, from January 2010 to December 2015. In addition, serum tests were conducted and clinical symptoms of patients evaluated. A statistical analysis revealed that the enhancement pattern, signal on MRI delayed phase (P<0.001), maximum diameter, capsule retraction, portal vein invasion, bile duct dilation and abdominal lymphadenectasis characteristics were different between IMCC and HCC patients with cirrhosis. On CEMP CT and MRI analysis, the most frequently occurring enhancement patterns of IMCC were progressive patterns (P=0.001 or P<0.001). Conversely, the most frequently occurring enhancement patterns present in HCC were the washout patterns (P<0.001). Therefore, the diagnosis of IMCC in cirrhotic patients should be verified with CEMP CT and MRI analysis for the future, to determine presence or absence of progressive and/or peripheral rim-like enhancement, a hyperintensive delayed phase with capsule retraction, portal vein invasion, bile duct dilation, abdominal lymphadenectasis and increased levels of CA199.

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Section: Discussionmentioning

confidence: 99%

Contrast-enhanced multiple-phase imaging features of intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma with cirrhosis: A comparative study

et al. 2017

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“…The diagnostic utility of the enhancement pattern on multiphasic contrast-enhanced CT has been previously reported for malignant hepatic tumors, renal cell carcinomas, small bowel neoplasms, and lung cancer (10)(11)(12)(13). In a recent article (13), Fukuma et al demonstrated the enhancement pattern of 48 squamous cell carcinomas, and the average HU was 33.94 HU in the unenhanced, 75.40 HU in the early, and 92.01 HU in the late phase.…”

Section: Discussionmentioning

confidence: 93%

Gradual enhancement pattern of tracheobronchial adenoid cystic carcinoma on multiphasic dynamic computed tomography : a case series

et al. 2020

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Tracheobronchial adenoid cystic carcinoma is a rare malignancy. To the best of our knowledge, its enhancement pattern on multiphasic contrast-enhanced multidetector computed tomography has not been reported. Herein, we report the computed tomography findings of three consecutive cases of tracheobronchial adenoid cystic carcinoma. All lesions presented a gradual enhancement pattern on multiphasic contrast-enhanced computed tomography. We speculate that the gradual enhancement pattern on multiphasic contrast-enhanced computed tomography could potentially serve as a characteristic imaging feature and may therefore be a clue to diagnose tracheobronchial adenoid cystic carcinoma.

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“…RevIBS = NorIBS random p y (10) Most equations and notation meanings here are consistent with CCNN [21]. NorIBS represents the normalized IBS whose value lies in a narrow range between 0 and 1.…”

Section: ) Disibsmentioning

confidence: 96%

“…Tsunematsu et al [10] used the Chi square test as well as the non-parametric Mann-Whitney U test which were common feature-selection methods to analysis the preselected features, 14 clinical characteristics and some CT imaging features. The logistic regression analysis was applied to find the best features to distinguish between ICC and HCC.…”

Section: Introductionmentioning

confidence: 99%

SCCNN: A Diagnosis Method for Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Siamese Cross Contrast Neural Network

Wang

Sun

et al. 2020

IEEE Access

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This paper proposes a novel siamese cross contrast neural network (SCCNN) to classify the hepatocellular carcinoma (HCC) and the intrahepatic cholangiocarcinoma (ICC) on computed tomography (CT) images. This method is inspired from cross contrast neural networks (CCNN) which is based on tailored CNN and information based similarity(IBS) theory. A new IBS-based measurement named as discriminative IBS(DisIBS) is designed for SCCNN. SCCNN is composed of two main parts including siamese feature extractors with DisIBS operator and MLP classifiers. Siamese networks extract features with DisIBS calculated by DisIBS operator as metric at the top. MLP classifiers are connected with but gradient-stop to feature extractors deriving classification results. We assign different loss functions with different parts to make better practice, specially DisIBS-based loss for feature extractors and softmax-based for MLP classifiers. SCCNN preserves the advantages of CCNN that can fit the insufficient medical images and small lesions. Furthermore, it extends CCNN with the siamese mechanism and gradient-stop MLP classifiers to accept the random inputs and predict like traditional CNN. To present the effectiveness of SCCNN empirically, we apply this method on a 234-person (157/77 for train/test) dataset and achieve better results than other classic CNN and CCNN methods. We try different base models of siamese structures and display prediction accuracy in two levels (slice/patient). The highest slice/patient accuracy which we have achieved on three-categories classification (HCC/ICC/Normal) is 90.22%/94.92% and the accuracy rises to 94.17%/97.44% on binary classification(HCC/ICC).INDEX TERMS Siamese networks, multiple loss, cross contrast neural networks, hepatocellular carcinoma, intrahepatic cholangiocarcinoma.

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Intratumoral artery on contrast-enhanced computed tomography imaging: differentiating intrahepatic cholangiocarcinoma from poorly differentiated hepatocellular carcinoma

Abstract: The presence of an intratumoral artery in the arterial phase on contrast-enhanced dynamic CT was a predictable finding for ICC, and the presence of a washout pattern was a predictable finding for p-HCC, differentiating between ICC and p-HCC.

Cited by 35 publications

References 23 publications

Contrast-enhanced multiple-phase imaging features of intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma with cirrhosis: A comparative study

Contrast-enhanced multiple-phase imaging features of intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma with cirrhosis: A comparative study

Gradual enhancement pattern of tracheobronchial adenoid cystic carcinoma on multiphasic dynamic computed tomography : a case series

SCCNN: A Diagnosis Method for Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Siamese Cross Contrast Neural Network

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