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For: Bak S, Kim JE, Bae K, Cho JM, Choi HC, Park MJ, Choi HY, Shin HS, Lee SM, Kim HO. Quantification of liver extracellular volume using dual-energy CT: utility for prediction of liver-related events in cirrhosis. Eur Radiol 2020;30:5317-26. [DOI: 10.1007/s00330-020-06876-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 01/22/2020] [Accepted: 04/08/2020] [Indexed: 12/30/2022]

For:	Bak S, Kim JE, Bae K, Cho JM, Choi HC, Park MJ, Choi HY, Shin HS, Lee SM, Kim HO. Quantification of liver extracellular volume using dual-energy CT: utility for prediction of liver-related events in cirrhosis. Eur Radiol 2020;30:5317-26. [DOI: 10.1007/s00330-020-06876-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 01/22/2020] [Accepted: 04/08/2020] [Indexed: 12/30/2022]

Number

Cited by Other Article(s)

Chen J, Zhang F, Wu S, Liu D, Yang L, Li M, Yin M, Ma K, Wen G, Huang W. Predictive value of high-risk esophageal varices in cirrhosis based on dual-energy CT combined with clinical and serologic features. BMC Med Imaging 2025;25:137. [PMID: 40281459 PMCID: PMC12032664 DOI: 10.1186/s12880-025-01681-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2024] [Accepted: 04/18/2025] [Indexed: 04/29/2025] Open

Abstract

OBJECTIVE

To investigate the predictive value of dual-energy CT (DECT) in combination with clinical and serologic features for noninvasive assessment of high-risk esophageal variceal (EV) in cirrhosis patients.

DATA AND METHODS

120 patients who had undergone DECT and gastroscopy were retrospectively enrolled. They were categorized into low-risk variceal (LRV) and high-risk variceal (HRV) groups by gastroscopy (LRV: none, mild, HRV: moderate, severe). Clinical data, serologic and DECT parameters were recorded respectively. Multifactorial logistic regression analyses were conducted to develop clinical, serological, DECT, and combined models. AUC was utilized to assess the diagnostic performance. Non-parametric tests were employed to analyze differences in DECT parameters among different grading of EV.

RESULTS

In clinical model, ascites was the independent risk predictor, with 78.3% accuracy,50% sensitivity, 100% specificity, and an AUC of 0.693. The serological model revealed white blood cell count, hematocrit, alanine aminotransferase, and platelet count as predictors for HRV, demonstrating 83.3% accuracy, 90.9% sensitivity, 76.9% specificity, and an AUC of 0.784. The DECT model, identified liver normalized iodine volume (NIV-L) and spleen volume (V-S) as key predictors, with 84% accuracy, 72.7% sensitivity, 92.9% specificity, and an AUC of 0.84. The combined model, integrating NIV-L, V-S, and Ascites, demonstrated superior performance with 82.6% accuracy, 90% sensitivity, 76.9% specificity, and an AUC of 0.878, compared to the other models. Additionally, severe EV had higher V-S and NIV-S values than other grades (p < 0.05), with AUC of 0.874 and 0.864, respectively.

CONCLUSION

DECT-based NIV-L, V-S, and presence of ascites can predict high-risk esophageal varices.

CLINICAL RELEVANCE STATEMENT

Quantitative parameters of DECT can predict high-risk esophageal varices in cirrhotic patients, avoid gastroscopy, if possible, continue hierarchical management.

TRIAL REGISTRATION

retrospectively registered.

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Hamami A, Aljamal M, Almuqbil N, Al-Harbi M, Hamd ZY. Assessment of Spectral Computed Tomography Image Quality and Detection of Lesions in the Liver Based on Image Reconstruction Algorithms and Virtual Tube Voltage. Diagnostics (Basel) 2025;15:1043. [PMID: 40310426 PMCID: PMC12025537 DOI: 10.3390/diagnostics15081043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2025] [Revised: 04/07/2025] [Accepted: 04/15/2025] [Indexed: 05/02/2025] Open

Hideura K, Tanabe M, Higashi M, Ihara K, Kiyoyama H, Kamamura N, Inoue A, Kawano Y, Nomura K, Ito K. Pancreatic changes in patients with visceral fat obesity: an evaluation with contrast-enhanced dual-energy computed tomography with automated three-dimensional volumetry. LA RADIOLOGIA MEDICA 2025;130:577-585. [PMID: 39987364 DOI: 10.1007/s11547-025-01963-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2024] [Accepted: 01/23/2025] [Indexed: 02/24/2025]

Abstract

PURPOSE

To investigate pancreatic changes associated with visceral fat obesity (VFO) and their clinical relevance using contrast-enhanced dual-energy CT (DE-CT) with automated 3D volumetry.

METHODS

This retrospective study included patients who underwent triple-phase contrast-enhanced dynamic abdominal DE-CT. The patients were divided into two groups based on the measured visceral fat area: the VFO group (≥ 100 cm2) and the non-VFO group (< 100 cm2). Pancreatic changes in 3D CT volumetric measurement parameters were evaluated.

RESULTS

In total, 119 patients were evaluated (mean age, 67.6 ± 12.9 years old; 80 men). The extracellular volume fraction calculated from iodine maps (ECV-ID) (r = -0.683, p < 0.001) was most strongly associated with the visceral fat area, followed by the fat volume fraction (FVF) of the pancreas (r = 0.582, p < 0.001) with a statistically moderate correlation. The pancreatic volume and FVF of the pancreas were significantly higher in the VFO group than in the non-VFO group (volume: 84.9 ± 22.9 vs. 76.5 ± 25.8, p = 0.025, FVF: 15.5 ± 7.7 vs. 8.7 ± 9.5, p < 0.001). Conversely, the pancreatic CT attenuation value on unenhanced CT (19.9 ± 12.0 vs. 29.6 ± 13.8, p < 0.001), pancreatic iodine concentration in the equilibrium phase (EP) (18.4 ± 5.7 vs. 19.8 ± 4.7, p = 0.003), contrast enhancement (CE) value of pancreas (32.2 ± 5.3 vs. 34.5 ± 8.5, p = 0.005), and ECV-ID (26.7 ± 5.4 vs. 34.1 ± 7.4, p < 0.001) in the VFO group were significantly lower than those in the non-VFO group.

CONCLUSION

An increase in the pancreatic volume and FVF of the pancreas, as well as a reduction in the ECV fraction and the CE value in EP of the pancreas measured by automated 3D DE-CT volumetry, were the characteristic pancreatic changes in patients with VFO.

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Xu Y, Li F, Liu B, Ren T, Sun J, Li Y, Liu H, Liu J, Zhou J. A short-term predictive model for disease progression in acute-on-chronic liver failure: integrating spectral CT extracellular liver volume and clinical characteristics. BMC Med Imaging 2025;25:69. [PMID: 40033256 PMCID: PMC11877947 DOI: 10.1186/s12880-025-01600-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2024] [Accepted: 02/16/2025] [Indexed: 03/05/2025] Open

Abstract

BACKGROUND

Acute-on-chronic liver failure (ACLF) is a life-threatening hepatic syndrome. Therefore, this study aimed to develop a comprehensive model combining extracellular liver volume derived from spectral CT (ECVIC-liver) and sarcopenia, for the early prediction of short-term (90-day) disease progression in ACLF.

MATERIALS AND METHODS

A retrospective cohort of 126 ACLF patients who underwent hepatic spectral CT scans was included. According to the Asia-Pacific Association for the Study of the Liver (APASL) criteria, patients were divided into the progression group (n = 70) and the stable group (n = 56). ECVIC-liver was measured on the equilibrium period (EP) images of spectral CT, and L3-SMI was measured on unenhanced CT images, with sarcopenia assessed. A comprehensive model was developed by combining independent predictors. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA).

RESULTS

In the univariate analysis, BMI, WBC, PLT, PTA, L3-SMI, IC-EP, Z-EP, K140-EP, NIC-EP, ECVIC-liver, and Sarcopenia demonstrated associations with disease progression status at 90 days in ACLF patients. In multivariate logistic regression, white blood cell count (WBC) (OR = 1.19, 95% CI: 1.02-1.40; P = 0.026), ECVIC-liver (OR = 1.27, 95% CI: 1.15-1.40; P < 0.001), sarcopenia (OR = 4.15, 95% CI: 1.43-12.01; P = 0.009), MELD-Na score (OR = 1.06, 95%CI: 1.01-1.13;P = 0.042), and CLIF-SOFA score (OR = 1.37, 95%CI:1.15-1.64; P<0.001) emerged as independent risk factors for ACLF progression. The combined model exhibited superior predictive performance (AUCs = 0.910, sensitivity = 80.4%, specificity = 90.0%, PPV = 0.865, NPV = 0.851) compared to CLIF-SOFA, MELD-Na, MELD and CTP scores(both P < 0.001). Calibration curves and DCA confirmed the high clinical utility of the combined model.

CONCLUSIONS

Patients without sarcopenia and/or with a lower ECVIC-liver have a better prognosis, and the integration of WBC, ECVIC-liver, Sarcopenia, CLIF-SOFA and MELD-Na scores in a composite model offers a concise and effective tool for predicting disease progression in ACLF patients.

TRIAL REGISTRATION

Not Applicable.

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Affiliation(s)

Yuan Xu Department of Radiology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Fukai Li Department of Radiology, Second Affiliated Hospital of Navy Medical University, Shanghai, China
Bo Liu Department of General Surgery, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China
Tiezhu Ren Department of Radiology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Jiachen Sun Department of Radiology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Yufeng Li Department of Radiology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Hong Liu Department of Radiology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
Jianli Liu Department of Radiology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China. Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China. Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China.
Junlin Zhou Department of Radiology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China. Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China. Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China.

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Qiu Q, Ai Y, Pan Y, Luo W, Xu Z, Chen S, Lin J. Assessment of high-risk gastroesophageal varices in cirrhotic patients using quantitative parameters from dual-source dual-energy CT. Abdom Radiol (NY) 2024:10.1007/s00261-024-04666-1. [PMID: 39542947 DOI: 10.1007/s00261-024-04666-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2024] [Revised: 10/27/2024] [Accepted: 10/28/2024] [Indexed: 11/17/2024]

Abstract

PURPOSE

To investigate the clinical value of dual-source dual-energy CT (dsDECT) quantitative parameters in evaluating hemodynamics and predicting high-risk gastroesophageal varices in cirrhotic patients.

METHODS

98 consecutive patients were collected in this prospectively study and all patients underwent an abdominal triple-phase contrasted-enhanced examination with dsDECT. Iodine concentration (IC) and normalized iodine concentration (NIC) of the liver parenchyma, spleen parenchyma and aorta at different phases were recorded, and arterial iodine fraction (AIF), iodine washout rate (IWR), and extracellular volume (ECV) were calculated. Using upper gastrointestinal endoscopy as the reference standard, patients who met the inclusion and exclusion criteria were divided into groups with varices need treatment (VNT) and non-VNT. The clinical characteristics, traditional CT features and quantitative dsDECT parameters were compared between the VNT group and the non-VNT group using univariate analysis. The binary logistics analysis was used to build a model for diagnosing VNT. The receiver operating characteristic (ROC) curve was used for analysis and the DeLong test was used to compare different ROC curves.

RESULTS

Finally, 57 patients were included in this study. Univariate analysis showed statistically significant differences in NIC of the liver at the portal venous phase (NIC-LPVP), IWR of the liver (IWR-L) and spleen volume between the VNT group and the non-VNT group (p < 0.05). The mixed-CT model was built by binary logistics analysis. The ROC curves of NIC-LPVP, IWR-L, spleen volume and the mixed-CT model were statistically significant (p < 0.05) for predicting VNT in cirrhotic patients, among which the area under the ROC curve of the mixed-CT model was the highest.

CONCLUSION

Dual-source dual-energy CT has added clinical value in evaluating hepatic hemodynamics and diagnosing VNT in patients with liver cirrhosis.

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Bai XH, Yin J, Yu SY, Shu YP, Lu ZP, Jiang KR, Xu Q. Extracellular volume fraction derived from dual-energy CT: a potential predictor for acute pancreatitis after pancreatoduodenectomy. Eur Radiol 2024;34:6957-6966. [PMID: 38760508 DOI: 10.1007/s00330-024-10750-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/07/2024] [Accepted: 03/09/2024] [Indexed: 05/19/2024]

Abstract

OBJECTIVES

To investigate the value of extracellular volume (ECV) fraction and fat fraction (FF) derived from dual- energy CT (DECT) for predicting postpancreatectomy acute pancreatitis (PPAP) after pancreatoduodenectomy (PD).

METHODS

This retrospective study included patients who underwent DECT and PD between April 2022 and September 2022. PPAP was determined according to the International Study Group for Pancreatic Surgery (ISGPS) definition. Iodine concentration (IC) and FF of the pancreatic parenchyma were measured on preoperative DECT. The ECV fraction was calculated from iodine map images of the equilibrium phase. The independent predictors for PPAP were assessed by univariate and multivariable logistic regression analysis and receiver operating characteristic (ROC) curve analysis.

RESULTS

Sixty-nine patients were retrospectively enrolled (median age, 60 years; interquartile range, 55-70 years; 47 men). Of these, nine patients (13.0%) developed PPAP. These patients had lower portal venous phase IC, equilibrium phase IC, FF, and ECV fraction, and higher pancreatic parenchymal-to-portal venous phase IC ratio and pancreatic parenchymal-to-equilibrium phase IC ratio, compared with patients without PPAP. After multivariable analysis, ECV fraction was independently associated with PPAP (odd ratio [OR], 0.87; 95% confidence interval [CI]: 0.79, 0.96; p < 0.001), with an area under the curve (AUC) of 0.839 (sensitivity 100.0%, specificity 58.3%).

CONCLUSIONS

A lower ECV fraction is independently associated with the occurrence of PPAP after PD. ECV fraction may serve as a potential predictor for PPAP after PD.

CLINICAL RELEVANCE STATEMENT

DECT-derived ECV fraction of pancreatic parenchyma is a promising biomarker for surgeons to preoperatively identify patients with higher risk for postpancreatectomy acute pancreatitis after PD and offer selective perioperative management.

KEY POINTS

PPAP is a complication of pancreatic surgery, early identification of higher-risk patients allows for risk mitigation. Lower DECT-derived ECV fraction was independently associated with the occurrence of PPAP after PD. DECT aids in preoperative PAPP risk stratification, allowing for appropriate treatment to minimize complications.

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Peng Y, Tang H, Huang Y, Yuan X, Wang X, Ran Z, Deng W, Liu R, Lan X, Shen H, Zhang J. CT-derived extracellular volume and liver volumetry can predict posthepatectomy liver failure in hepatocellular carcinoma. Insights Imaging 2023;14:145. [PMID: 37697217 PMCID: PMC10495294 DOI: 10.1186/s13244-023-01496-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 08/08/2023] [Indexed: 09/13/2023] Open

Abstract

OBJECTIVES

Posthepatectomy liver failure (PHLF) is a severe complication of liver resection. We aimed to develop and validate a model based on extracellular volume (ECV) and liver volumetry derived from computed tomography (CT) for preoperative predicting PHLF in resectable hepatocellular carcinoma (HCC) patients.

METHODS

A total of 393 resectable HCC patients from two hospitals were enrolled and underwent multiphasic contrast-enhanced CT before surgery. A total of 281 patients from our hospital were randomly divided into a training cohort (n = 181) and an internal validation cohort (n = 100), and 112 patients from another hospital formed the external validation cohort. CT-derived ECV was measured on nonenhanced and equilibrium phase images, and liver volumetry was measured on portal phase images. The model is composed of independent predictors of PHLF. The under the receiver operator characteristic curve (AUC) and calibration curve were used to reflect the predictive performance and calibration of the model. Comparison of AUCs used the DeLong test.

RESULTS

CT-derived ECV, measured future liver remnant (mFLR) ratio, and serum albumin were independent predictors for PHLF in resectable HCC patients. The AUC of the model was significantly higher than that of the ALBI score in the training cohort, internal validation cohort, and external validation cohort (all p < 0.001). The calibration curve of the model showed good consistency in the training cohort and the internal and external validation cohorts.

CONCLUSIONS

The novel model contributes to the preoperative prediction of PHLF in resectable HCC patients.

CRITICAL RELEVANCE STATEMENT

The novel model combined CT-derived extracellular volume, measured future liver remnant ratio, and serum albumin outperforms the albumin-bilirubin score for predicting posthepatectomy liver failure in patients with resectable hepatocellular carcinoma.

KEY POINTS

• CT-derived ECV correlated well with the fibrosis stage of the background liver. • CT-derived ECV and mFLR ratio were independent predictors for PHLF in HCC. • The AUC of the model was higher than the CT-derived ECV and mFLR ratio. • The model showed a superior predictive performance than that of the ALBI score.

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Affiliation(s)

Yangling Peng Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China
Hao Tang Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China
Yuanying Huang Department of Hematology, Chongqing General Hospital, University of the Chinese Academy of Sciences, Chongqing, People's Republic of China
Xiaoqian Yuan Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China
Xing Wang Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China
Zijuan Ran Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China
Wei Deng Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China
Renwei Liu Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China
Xiaosong Lan Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China
Hesong Shen Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China.
Jiuquan Zhang Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, People's Republic of China.

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Chen Y, Shi K, Li Z, Wang H, Liu N, Zhan P, Liu X, Shang B, Hou P, Gao J, Lyu P. Survival prediction of hepatocellular carcinoma by measuring the extracellular volume fraction with single-phase contrast-enhanced dual-energy CT imaging. Front Oncol 2023;13:1199426. [PMID: 37538109 PMCID: PMC10394647 DOI: 10.3389/fonc.2023.1199426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 06/23/2023] [Indexed: 08/05/2023] Open

Franco PN, Spasiano CM, Maino C, De Ponti E, Ragusi M, Giandola T, Terrani S, Peroni M, Corso R, Ippolito D. Principles and Applications of Dual-Layer Spectral CT in Gastrointestinal Imaging. Diagnostics (Basel) 2023;13:diagnostics13101740. [PMID: 37238224 DOI: 10.3390/diagnostics13101740] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 05/12/2023] [Indexed: 05/28/2023] Open

Xu Y, Li Y, Li S, Xue S, Liu J. Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation. Insights Imaging 2023;14:51. [PMID: 36977956 PMCID: PMC10050608 DOI: 10.1186/s13244-023-01393-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 02/19/2023] [Indexed: 03/30/2023] Open

Ozaki K, Ohtani T, Ishida S, Higuchi S, Ishida T, Takahashi K, Matta Y, KImura H, Gabata T. Extracellular volume fraction obtained by dual-energy CT depicting the etiological differences of liver fibrosis. Abdom Radiol (NY) 2023;48:1975-1986. [PMID: 36939910 DOI: 10.1007/s00261-023-03873-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 02/23/2023] [Accepted: 02/23/2023] [Indexed: 03/21/2023]

Efficacy Analysis of Double-Low Dynamic Contrast-Enhanced CT and Hepatic Extracellular Volume Fraction in the Diagnosis of Liver Fibrosis. CONTRAST MEDIA & MOLECULAR IMAGING 2022;2022:8089914. [PMID: 36072627 PMCID: PMC9402376 DOI: 10.1155/2022/8089914] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 07/29/2022] [Accepted: 08/03/2022] [Indexed: 02/07/2023]

Wada N, Fujita N, Ishimatsu K, Takao S, Yoshizumi T, Miyazaki Y, Oda Y, Nishie A, Ishigami K, Ushijima Y. A novel fast kilovoltage switching dual-energy computed tomography technique with deep learning: Utility for non-invasive assessments of liver fibrosis. Eur J Radiol 2022;155:110461. [DOI: 10.1016/j.ejrad.2022.110461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 07/22/2022] [Accepted: 08/03/2022] [Indexed: 11/26/2022]

Virarkar MK, Vulasala SSR, Gupta AV, Gopireddy D, Kumar S, Hernandez M, Lall C, Bhosale P. Virtual Non-contrast Imaging in The Abdomen and The Pelvis: An Overview. Semin Ultrasound CT MR 2022;43:293-310. [PMID: 35738815 DOI: 10.1053/j.sult.2022.03.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]

Hepatobiliary Dual-Energy Computed Tomography. Radiol Clin North Am 2022;60:731-743. [DOI: 10.1016/j.rcl.2022.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]

Zhou Y, Geng D, Su GY, Chen XB, Si Y, Shen MP, Xu XQ, Wu FY. Extracellular Volume Fraction Derived From Dual-Layer Spectral Detector Computed Tomography for Diagnosing Cervical Lymph Nodes Metastasis in Patients With Papillary Thyroid Cancer: A Preliminary Study. Front Oncol 2022;12:851244. [PMID: 35756662 PMCID: PMC9213667 DOI: 10.3389/fonc.2022.851244] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Accepted: 05/18/2022] [Indexed: 11/13/2022] Open

Abstract

Objectives

The current study evaluates the performance of dual-energy computed tomography (DECT) derived extracellular volume (ECV) fraction based on dual-layer spectral detector CT for diagnosing cervical lymph nodes (LNs) metastasis from papillary thyroid cancer (PTC) and compares it with the value of ECV derived from conventional single-energy CT (SECT).

Methods

One hundred and fifty-seven cervical LNs (81 non-metastatic and 76 metastatic) were recruited. Among them, 59 cervical LNs (27 non-metastatic and 32 metastatic) were affected by cervical root artifact on the contrast-enhanced CT images in the arterial phase. Both the SECT-derived ECV fraction (ECV_S) and the DECT-derived ECV fraction (ECV_D) were calculated. A Pearson correlation coefficient and a Bland–Altman analysis were performed to evaluate the correlations between ECV_D and ECV_S. Receiver operator characteristic curves analysis and the Delong method were performed to assess and compare the diagnostic performance.

Results

ECV_D correlated significantly with ECV_S (r = 0.925; p <0.001) with a small bias (−0.6). Metastatic LNs showed significantly higher ECV_D (42.41% vs 22.53%, p <0.001) and ECV_S (39.18% vs 25.45%, p <0.001) than non-metastatic LNs. By setting an ECV_D of 36.45% as the cut-off value, optimal diagnostic performance could be achieved (AUC = 0.813), which was comparable with that of ECV_S (cut-off value = 34.99%; AUC = 0.793) (p = 0.265). For LNs affected by cervical root artifact, ECV_D also showed favorable efficiency (AUC = 0.756), which was also comparable with that of ECV_S (AUC = 0.716) (p = 0.244).

Conclusions

ECV_D showed a significant correlation with ECV_S. Compared with ECV_S, ECV_D showed comparable performance in diagnosing metastatic cervical LNs in PTC patients, even though the LNs were affected by cervical root artifacts on arterial phase CT.

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Peng Y, Shen H, Tang H, Huang Y, Lan X, Luo X, Zhang X, Zhang J. Nomogram based on CT-derived extracellular volume for the prediction of post-hepatectomy liver failure in patients with resectable hepatocellular carcinoma. Eur Radiol 2022;32:8529-8539. [PMID: 35678856 DOI: 10.1007/s00330-022-08917-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/19/2022] [Accepted: 05/30/2022] [Indexed: 12/12/2022]

Abstract

OBJECTIVES

This study aimed to develop and validate a nomogram based on extracellular volume (ECV) derived from computed tomography (CT) for predicting post-hepatectomy liver failure (PHLF) in patients with resectable hepatocellular carcinoma (HCC).

METHODS

A total of 202 patients with resectable HCC from two hospitals were enrolled and underwent multiphasic contrast-enhanced CT before surgery. One hundred twenty-one patients from our hospital and 81 patients from another hospital were assigned to the training cohort and the validation cohort, respectively. CT-derived ECV was measured using nonenhanced and equilibrium-phase-enhanced CT images. The nomogram was developed with independent predictors of PHLF. Predictive performance and calibration were assessed by receiver operator characteristic (ROC) analysis and Hosmer-Lemeshow test, respectively. The Delong test was used to compare the areas under the curve (AUCs).

RESULTS

CT-derived ECV had a strong correlation with the postoperative pathological fibrosis stage of the background liver (p < 0.001, r = 0.591). The nomogram combining CT-derived ECV, serum albumin (Alb), and serum total bilirubin (Tbil) obtained higher AUCs than the albumin-bilirubin (ALBI) score for predicting PHLF in both the training cohort (0.828 vs. 0.708; p = 0.004) and the validation cohort (0.821 vs. 0.630; p < 0.001). The nomogram showed satisfactory goodness of fit for PHLF prediction in the training and validation cohorts (p = 0.621 and 0.697, respectively).

CONCLUSIONS

The nomogram contributes to the preoperative prediction of PHLF in patients with resectable HCC.

KEY POINTS

• CT-derived ECV had a strong correlation with the postoperative pathological fibrosis stage of the background liver. • CT-derived ECV was an independent predictor of PHLF in patients with resectable HCC. • The nomogram based on CT-derived ECV showed a superior prediction efficacy than that of clinical models (including Child-Pugh stage, MELD score, and ALBI score).

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Duan T, Jiang HY, Ling WW, Song B. Noninvasive imaging of hepatic dysfunction: A state-of-the-art review. World J Gastroenterol 2022;28:1625-1640. [PMID: 35581963 PMCID: PMC9048786 DOI: 10.3748/wjg.v28.i16.1625] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 07/17/2021] [Accepted: 03/27/2022] [Indexed: 02/06/2023] Open

Deep learning image reconstruction for improving image quality of contrast-enhanced dual-energy CT in abdomen. Eur Radiol 2022;32:5499-5507. [PMID: 35238970 DOI: 10.1007/s00330-022-08647-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 02/05/2022] [Accepted: 02/11/2022] [Indexed: 11/04/2022]

Abstract

OBJECTIVES

To evaluate the usefulness of deep learning image reconstruction (DLIR) to improve the image quality of dual-energy computed tomography (DECT) of the abdomen, compared to hybrid iterative reconstruction (IR).

METHODS

This study included 40 patients who underwent contrast-enhanced DECT of the abdomen. Virtual monochromatic 40-, 50-, and 70-keV and iodine density images were reconstructed using three reconstruction algorithms, including hybrid IR (ASiR-V50%) and DLIR (TrueFidelity) at medium- and high-strength level (DLIR-M and DLIR-H, respectively). The standard deviation of attenuation in liver parenchyma was measured as image noise. The contrast-to-noise ratio (CNR) for the portal vein on portal venous phase CT was calculated. The vessel conspicuity and overall image quality were graded on a 5-point scale ranging from 1 (poor) to 5 (excellent). The comparative scale of lesion conspicuity in 47 abdominal solid lesions was evaluated on a 5-point scale ranging from 0 (best) to -4 (markedly inferior).

RESULTS

The image noise of virtual monochromatic 40-, 50 -, and 70-keV and iodine density images was significantly decreased by DLIR compared to hybrid IR (p < 0.0001). The CNR was significantly higher in DLIR-H and DLIR-M than in hybrid IR (p < 0.0001). The vessel conspicuity and overall image quality scores were also significantly greater in DLIR-H and DLIR-M than in hybrid IR (p < 0.05). The lesion conspicuity scores for DLIR-M and DLIR-H were significantly higher than those for hybrid IR in the virtual monochromatic image of all energy levels (p ≤ 0.001).

CONCLUSIONS

DLIR improves vessel conspicuity, CNR, and lesion conspicuity of virtual monochromatic and iodine density images in abdominal contrast-enhanced DECT, compared to hybrid IR.

KEY POINTS

• Deep learning image reconstruction (DLIR) is useful for reducing image noise and improving the CNR of visual monochromatic 40-, 50-, and 70-keV images in dual-energy CT. • DLIR can improve lesion conspicuity of abdominal solid lesions on virtual monochromatic images compared to hybrid iterative reconstruction. • DLIR can also be applied to iodine density maps and significantly improves their image quality.

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Hong S, Kim JE, Cho JM, Choi HC, Won JH, Na JB, Choi DS, Park MJ, Choi HY, Shin HS, Cho HC, Kim HO. Quantification of liver extracellular volume using dual-energy CT for ruling out high-risk varices in cirrhosis. Eur J Radiol 2022;148:110151. [PMID: 35032849 DOI: 10.1016/j.ejrad.2022.110151] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 12/10/2021] [Accepted: 01/03/2022] [Indexed: 11/03/2022]

Affiliation(s)

Seokjin Hong Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Ji Eun Kim Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea.
Jae Min Cho Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Ho Cheol Choi Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Jung Ho Won Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Jae Beom Na Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Dae Seob Choi Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Mi Jung Park Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Hye Young Choi Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Hwa Seon Shin Department of Radiology, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Hyun Chin Cho Department of Internal Medicine, Gyeongsang National University College of Medicine and Gyeongsang National University Hospital, Jinju, Republic of Korea
Hyun Ok Kim Department of Internal Medicine, Gyeongsang National University College of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea

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Haberman DM, Andriani OC, Segaran NL, Volpacchio MM, Micheli ML, Russi RH, Pérez Fernández IA. Role of CT in Two-Stage Liver Surgery. Radiographics 2022;42:106-124. [PMID: 34990325 DOI: 10.1148/rg.210067] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]

Affiliation(s)

Diego M Haberman From the Body Imaging Section, Centro de Diagnóstico Rossi, Esmeralda 141, Buenos Aires C1035ABD, Argentina (D.M.H., M.M.V., M.L.M.); Oncosurgical HPB Unit, Sanatorio de los Arcos, Swiss Medical Group, HPB, Buenos Aires, Argentina (O.C.A., R.H.R., I.A.P.F.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (N.L.S.)
Oscar C Andriani From the Body Imaging Section, Centro de Diagnóstico Rossi, Esmeralda 141, Buenos Aires C1035ABD, Argentina (D.M.H., M.M.V., M.L.M.); Oncosurgical HPB Unit, Sanatorio de los Arcos, Swiss Medical Group, HPB, Buenos Aires, Argentina (O.C.A., R.H.R., I.A.P.F.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (N.L.S.)
Nicole L Segaran From the Body Imaging Section, Centro de Diagnóstico Rossi, Esmeralda 141, Buenos Aires C1035ABD, Argentina (D.M.H., M.M.V., M.L.M.); Oncosurgical HPB Unit, Sanatorio de los Arcos, Swiss Medical Group, HPB, Buenos Aires, Argentina (O.C.A., R.H.R., I.A.P.F.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (N.L.S.)
Mariano M Volpacchio From the Body Imaging Section, Centro de Diagnóstico Rossi, Esmeralda 141, Buenos Aires C1035ABD, Argentina (D.M.H., M.M.V., M.L.M.); Oncosurgical HPB Unit, Sanatorio de los Arcos, Swiss Medical Group, HPB, Buenos Aires, Argentina (O.C.A., R.H.R., I.A.P.F.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (N.L.S.)
Maria Lucrecia Micheli From the Body Imaging Section, Centro de Diagnóstico Rossi, Esmeralda 141, Buenos Aires C1035ABD, Argentina (D.M.H., M.M.V., M.L.M.); Oncosurgical HPB Unit, Sanatorio de los Arcos, Swiss Medical Group, HPB, Buenos Aires, Argentina (O.C.A., R.H.R., I.A.P.F.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (N.L.S.)
Rodolfo H Russi From the Body Imaging Section, Centro de Diagnóstico Rossi, Esmeralda 141, Buenos Aires C1035ABD, Argentina (D.M.H., M.M.V., M.L.M.); Oncosurgical HPB Unit, Sanatorio de los Arcos, Swiss Medical Group, HPB, Buenos Aires, Argentina (O.C.A., R.H.R., I.A.P.F.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (N.L.S.)
Ignacio A Pérez Fernández From the Body Imaging Section, Centro de Diagnóstico Rossi, Esmeralda 141, Buenos Aires C1035ABD, Argentina (D.M.H., M.M.V., M.L.M.); Oncosurgical HPB Unit, Sanatorio de los Arcos, Swiss Medical Group, HPB, Buenos Aires, Argentina (O.C.A., R.H.R., I.A.P.F.); and Department of Radiology, Mayo Clinic, Phoenix, Ariz (N.L.S.)

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Assessing the progression of segmental fibrosis in chronic liver disease using extracellular volume fractions. Eur J Radiol 2021;145:110033. [PMID: 34808581 DOI: 10.1016/j.ejrad.2021.110033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 10/02/2021] [Accepted: 11/12/2021] [Indexed: 02/08/2023]

The extracellular volume fraction of the pancreas measured by dual-energy computed tomography: The association with impaired glucose tolerance. Eur J Radiol 2021;141:109775. [PMID: 34020172 DOI: 10.1016/j.ejrad.2021.109775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 04/29/2021] [Accepted: 05/07/2021] [Indexed: 11/21/2022]

Non-invasive assessment of cirrhosis using multiphasic dual-energy CT iodine maps: correlation with model for end-stage liver disease score. Abdom Radiol (NY) 2021;46:1931-1940. [PMID: 33211150 DOI: 10.1007/s00261-020-02857-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 10/29/2020] [Accepted: 11/05/2020] [Indexed: 12/23/2022]

Abstract

PURPOSE

To determine whether multiphasic dual-energy (DE) CT iodine quantitation correlates with the severity of chronic liver disease.

METHODS

We retrospectively included 40 cirrhotic and 28 non-cirrhotic patients who underwent a multiphasic liver protocol DECT. All three phases (arterial, portal venous (PVP), and equilibrium) were performed in DE mode. Iodine (I) values (mg I/ml) were obtained by placing regions of interest in the liver, aorta, common hepatic artery, and portal vein (PV). Iodine slopes (λ) were calculated as follows: (I_equilibrium-I_arterial)/time and (I_equilibrium-I_PVP)/time. Spearman correlations between λ and MELD scores were evaluated, and the area under the curve of the receiver operating characteristic (AUROC) was calculated to distinguish cirrhotic and non-cirrhotic patients.

RESULTS

Cirrhotic and non-cirrhotic patients had significantly different λ_{equilibrium-arterial} [IQR] for the caudate (λ = 2.08 [1.39-2.98] vs 1.46 [0.76-1.93], P = 0.007), left (λ = 2.05 [1.50-2.76] vs 1.51 [0.59-1.90], P = 0.002) and right lobes (λ = 1.72 [1.12-2.50] vs 1.13 [0.41-0.43], P = 0.003) and for the PV (λ = 3.15 [2.20-5.00] vs 2.29 [0.85-2.71], P = 0.001). λ_{equilibrium-PVP} were significantly different for the right (λ = 0.11 [- 0.45-1.03] vs - 0.44 [- 0.83-0.12], P = 0.045) and left lobe (λ = 0.30 [- 0.25-0.98] vs - 0.10 [- 0.35-0.24], P = 0.001). Significant positive correlations were found between MELD scores and λ_{equilibrium-arterial} for the caudate lobe (ρ = 0.34, P = 0.004) and λ_{equilibrium-PVP} for the caudate (ρ = 0.26, P = 0.028) and right lobe (ρ = 0.33, P = 0.007). AUROC in distinguishing cirrhotic and non-cirrhotic patients were 0.72 (P = 0.002), 0.71 (P = 0.003), and 0.75 (P = 0.001) using λ_{equilibrium-arterial} for the left lobe, right lobe, and PV, respectively. The λ_{equilibrium-PVP} AUROC of the right lobe was 0.73 (P = 0.001).

CONCLUSION

Multiphasic DECT iodine quantitation over time is significantly different between cirrhotic and non-cirrhotic patients, correlates with the MELD score, and it could potentially serve as a non-invasive measure of cirrhosis and disease severity with acceptable diagnostic accuracy.

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Yoon JH, Lee JM, Kim JH, Lee KB, Kim H, Hong SK, Yi NJ, Lee KW, Suh KS. Hepatic fibrosis grading with extracellular volume fraction from iodine mapping in spectral liver CT. Eur J Radiol 2021;137:109604. [PMID: 33618210 DOI: 10.1016/j.ejrad.2021.109604] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 01/28/2021] [Accepted: 02/11/2021] [Indexed: 12/15/2022]

Affiliation(s)

Jeong Hee Yoon Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
Jeong Min Lee Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea.
Jae Hyun Kim Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
Kyoung-Bun Lee Department of Pathology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
Haeryoung Kim Department of Pathology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
Suk Kyun Hong Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
Nam-Joon Yi Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
Kwang-Woong Lee Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea
Kyung-Suk Suh Department of Surgery, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03087, Republic of Korea

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Morita K, Nishie A, Ushijima Y, Takayama Y, Fujita N, Kubo Y, Ishimatsu K, Yoshizumi T, Maehara J, Ishigami K. Noninvasive assessment of liver fibrosis by dual-layer spectral detector CT. Eur J Radiol 2021;136:109575. [PMID: 33548853 DOI: 10.1016/j.ejrad.2021.109575] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 01/08/2021] [Accepted: 01/25/2021] [Indexed: 01/08/2023]