Hyun Jeong Park1, Kyung Mi Jang2, Tae Wook Kang3, Kyoung Doo Song3, Seong Hyun Kim3, Young Kon Kim3, Dong Ik Cha3, Joungyoun Kim4, Juna Goo4. 1. Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul, 156-755, Republic of Korea. 2. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. kmmks.jang@samsung.com. 3. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 4. Biostatistics and Clinical Epidemiology Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Abstract
OBJECTIVES: To identify predictors for the discrimination of intrahepatic cholangiocarcinoma (IMCC) and combined hepatocellular-cholangiocarcinoma (CHC) from hepatocellular carcinoma (HCC) for primary liver cancers on gadoxetic acid-enhanced MRI among high-risk chronic liver disease (CLD) patients using classification tree analysis (CTA). METHODS: A total of 152 patients with histopathologically proven IMCC (n = 40), CHC (n = 24) and HCC (n = 91) were enrolled. Tumour marker and MRI variables including morphologic features, signal intensity, and enhancement pattern were used to identify tumours suspicious for IMCC and CHC using CTA. RESULTS: On CTA, arterial rim enhancement (ARE) was the initial splitting predictor for assessing the probability of tumours being IMCC or CHC. Of 43 tumours that were classified in a subgroup on CTA based on the presence of ARE, non-intralesional fat, and non-globular shape, 41 (95.3 %) were IMCCs (n = 29) or CHCs (n = 12). All 24 tumours showing fat on MRI were HCCs. The CTA model demonstrated sensitivity of 84.4 %, specificity of 97.8 %, and accuracy of 92.3 % for discriminating IMCCs and CHCs from HCCs. CONCLUSIONS: We established a simple CTA model for classifying a high-risk group of CLD patients with IMCC and CHC. This model may be useful for guiding diagnosis for primary liver cancers in patients with CLD. KEY POINTS: • Arterial rim enhancement was the initial splitting predictor on CTA. • CTA model achieved high sensitivity, specificity, and accuracy for discrimination of tumours. • This model may be useful for guiding diagnosis of primary liver cancers.
OBJECTIVES: To identify predictors for the discrimination of intrahepatic cholangiocarcinoma (IMCC) and combined hepatocellular-cholangiocarcinoma (CHC) from hepatocellular carcinoma (HCC) for primary liver cancers on gadoxetic acid-enhanced MRI among high-risk chronic liver disease (CLD) patients using classification tree analysis (CTA). METHODS: A total of 152 patients with histopathologically proven IMCC (n = 40), CHC (n = 24) and HCC (n = 91) were enrolled. Tumour marker and MRI variables including morphologic features, signal intensity, and enhancement pattern were used to identify tumours suspicious for IMCC and CHC using CTA. RESULTS: On CTA, arterial rim enhancement (ARE) was the initial splitting predictor for assessing the probability of tumours being IMCC or CHC. Of 43 tumours that were classified in a subgroup on CTA based on the presence of ARE, non-intralesional fat, and non-globular shape, 41 (95.3 %) were IMCCs (n = 29) or CHCs (n = 12). All 24 tumours showing fat on MRI were HCCs. The CTA model demonstrated sensitivity of 84.4 %, specificity of 97.8 %, and accuracy of 92.3 % for discriminating IMCCs and CHCs from HCCs. CONCLUSIONS: We established a simple CTA model for classifying a high-risk group of CLD patients with IMCC and CHC. This model may be useful for guiding diagnosis for primary liver cancers in patients with CLD. KEY POINTS: • Arterial rim enhancement was the initial splitting predictor on CTA. • CTA model achieved high sensitivity, specificity, and accuracy for discrimination of tumours. • This model may be useful for guiding diagnosis of primary liver cancers.
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