Hanyu Jiang1,2, Bin Song1, Yun Qin1, Jie Chen1, Dong Xiao3, Hong Ii Ha2, Xijiao Liu1, Omobonike Oloruntoba-Sanders4, Alaattin Erkanli3, Andrew J Muir4, Mustafa R Bashir5,6. 1. Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China. 2. Department of Radiology and Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Box 3808, Durham, NC, 27710, USA. 3. Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, 27710, USA. 4. Department of Medicine (Gastroenterology), Duke University Medical Center, Durham, NC, 27710, USA. 5. Department of Radiology and Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Box 3808, Durham, NC, 27710, USA. mustafa.bashir@duke.edu. 6. Department of Medicine (Gastroenterology), Duke University Medical Center, Durham, NC, 27710, USA. mustafa.bashir@duke.edu.
Abstract
OBJECTIVES: The LI-RADS M (LR-M) category describes hepatic lesions probably or definitely malignant, but not specific for hepatocellular carcinoma in at-risk patients. Differentiation among LR-M entities, particularly detecting cholangiocarcinoma-containing tumors (M-CCs), is essential for treatment and prognosis. Thus, we aimed to develop diagnostic models on gadoxetate disodium-enhanced MRI comprising serum tumor markers and LI-RADS imaging features for M-CC. METHODS: Consecutive at-risk patients with LR-M lesions exclusively (no co-existing LR-4 and/or LR-5 lesions) were retrieved retrospectively from a prospectively collected database spanning 3 years. Intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular-cholangiocarcinoma (c-HCC-CCA) were classified together as M-CC. LI-RADS features determined by three independent radiologists and clinically relevant serum tumor markers were used to generate M-CC diagnostic models through logistic regression analysis against histology. Per-patient performance was evaluated using area under the receiver operating curve (AUC), sensitivity, and specificity. RESULTS: Forty-five patients were included, 42.2% (19/45) with hepatocellular carcinoma, 33.3% (15/45) with ICC, 13.3% (6/45) with c-HCC-CCA, and 11.1% (5/45) with other hepatic lesions. Carbohydrate antigen (CA)19-9 > 38 U/mL, α-fetoprotein (AFP) > 4.8 ng/mL, and absence of the LI-RADS feature "blood products in mass" were significant predictors of M-CC. Combining three predictors demonstrated AUC of 0.862, sensitivity of 76%, and specificity of 88%. The risk of M-CC with all three criteria fulfilled was 98% (AUC, 0.690; sensitivity, 38%; specificity, 100%). CONCLUSIONS: In at-risk patients with LR-M lesions, integrating CA19-9, AFP, and the LI-RADS feature "blood products in mass" achieved high diagnostic performance for M-CC. When all three criteria were fulfilled, the specificity for M-CC was 100%. KEY POINTS: • In at-risk patients who had LR-M lesions exclusively (no concomitant LR-4/5 lesions), a model with carbohydrate antigen > 38 U/mL, α-fetoprotein > 4.8 ng/mL, and absence of the LI-RADS feature "blood products in mass" achieved high accuracy for diagnosing cholangiocarcinoma-containing tumors. • In patients of whom all three criteria were fulfilled, the specificity for M-CC was 100%, which might reduce or eliminate the need for biopsy confirmation.
OBJECTIVES: The LI-RADS M (LR-M) category describes hepatic lesions probably or definitely malignant, but not specific for hepatocellular carcinoma in at-risk patients. Differentiation among LR-M entities, particularly detecting cholangiocarcinoma-containing tumors (M-CCs), is essential for treatment and prognosis. Thus, we aimed to develop diagnostic models on gadoxetate disodium-enhanced MRI comprising serum tumor markers and LI-RADS imaging features for M-CC. METHODS: Consecutive at-risk patients with LR-M lesions exclusively (no co-existing LR-4 and/or LR-5 lesions) were retrieved retrospectively from a prospectively collected database spanning 3 years. Intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular-cholangiocarcinoma (c-HCC-CCA) were classified together as M-CC. LI-RADS features determined by three independent radiologists and clinically relevant serum tumor markers were used to generate M-CC diagnostic models through logistic regression analysis against histology. Per-patient performance was evaluated using area under the receiver operating curve (AUC), sensitivity, and specificity. RESULTS: Forty-five patients were included, 42.2% (19/45) with hepatocellular carcinoma, 33.3% (15/45) with ICC, 13.3% (6/45) with c-HCC-CCA, and 11.1% (5/45) with other hepatic lesions. Carbohydrate antigen (CA)19-9 > 38 U/mL, α-fetoprotein (AFP) > 4.8 ng/mL, and absence of the LI-RADS feature "blood products in mass" were significant predictors of M-CC. Combining three predictors demonstrated AUC of 0.862, sensitivity of 76%, and specificity of 88%. The risk of M-CC with all three criteria fulfilled was 98% (AUC, 0.690; sensitivity, 38%; specificity, 100%). CONCLUSIONS: In at-risk patients with LR-M lesions, integrating CA19-9, AFP, and the LI-RADS feature "blood products in mass" achieved high diagnostic performance for M-CC. When all three criteria were fulfilled, the specificity for M-CC was 100%. KEY POINTS: • In at-risk patients who had LR-M lesions exclusively (no concomitant LR-4/5 lesions), a model with carbohydrate antigen > 38 U/mL, α-fetoprotein > 4.8 ng/mL, and absence of the LI-RADS feature "blood products in mass" achieved high accuracy for diagnosing cholangiocarcinoma-containing tumors. • In patients of whom all three criteria were fulfilled, the specificity for M-CC was 100%, which might reduce or eliminate the need for biopsy confirmation.
Entities:
Keywords:
Biomarkers; Cholangiocarcinoma; Diagnosis; Magnetic resonance imaging; Tumor
Authors: Fernando Timoteo Fernandes; Tiago Almeida de Oliveira; Cristiane Esteves Teixeira; Andre Filipe de Moraes Batista; Gabriel Dalla Costa; Alexandre Dias Porto Chiavegatto Filho Journal: Sci Rep Date: 2021-02-08 Impact factor: 4.379