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Sato K, Tanaka S, Urakawa H, Murayama R, Hisatomi E, Takayama Y, Yoshimitsu K. Gallbladder fossa nodularity in the liver as observed in alcoholic liver disease patients: Analysis based on hepatobiliary phase signal intensity on gadoxetate-enhanced MRI and extracellular volume fraction calculated from routine CT data. Glob Health Med 2024; 6:183-189. [PMID: 38947406 PMCID: PMC11197160 DOI: 10.35772/ghm.2023.01085] [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: 08/06/2023] [Revised: 12/25/2023] [Accepted: 01/29/2024] [Indexed: 07/02/2024]
Abstract
The purpose of this study is to further verify the concept utilizing signal intensity on hepatobiliary phase (HBP) of gadoxetate-enhanced MRI and extracellular volume fraction (ECV) calculated from CT data. Between Jan 2013 and September 2018, consecutive ALD patients who had both quadruple phase CT and gadoxetate-enhanced MRI within six months were retrospectively recruited. Those who had any intervention or disease involvement around gallbladder fossa were excluded. All images were reviewed and ECV was measured by two experienced radiologists. GBFN grades, and their HBP signal intensity or ECV relative to the surrounding background liver (BGL) were analyzed. There were 48 patients who met the inclusion criteria. There were GBFN grade 0/1/2/3 in 11/15/18/4 patients, respectively. The signal intensity on HBP relative to BGL were iso/slightly high/high in 30/15/3 patients, respectively, and ECV ratio (ECV of GBFN divided by that of BGL) was 0.88 ± 0.18, indicating there are more functioning hepatocytes and less fibrosis in GBFN than in BGL. The GBFN grades were significantly correlated to relative signal intensity at HBP (Spearman's rank correlation, p < 0.01, rho value 0.53), and ECV ratio (p < 0.01, rho value -0.45). Our results suggest GBFN in ALD would represent liver tissues with preserved liver function with less fibrosis, as compared to BGL, which are considered to support our hypothesis as shown above.
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Affiliation(s)
- Keisuke Sato
- Department of Radiology, Faculty of Medicine, Fukuoka University, Fukuoka, Japan
| | - Shinji Tanaka
- Department of Radiology, Faculty of Medicine, Fukuoka University, Fukuoka, Japan
| | - Hiroshi Urakawa
- Department of Radiology, Fukuoka University Chikushi Hospital, Chikushino, Japan
| | - Ryo Murayama
- Department of Radiology, Faculty of Medicine, Fukuoka University, Fukuoka, Japan
| | - Eiko Hisatomi
- Department of Radiology, Faculty of Medicine, Fukuoka University, Fukuoka, Japan
| | - Yukihisa Takayama
- Department of Radiology, Faculty of Medicine, Fukuoka University, Fukuoka, Japan
| | - Kengo Yoshimitsu
- Department of Radiology, Faculty of Medicine, Fukuoka University, Fukuoka, Japan
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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: 0] [Impact Index Per Article: 0] [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
Abstract
BACKGROUND Liver cirrhosis-acute decompensation (LC-AD) has rapid short-term disease progression and difficult early risk stratification. The purpose is to develop and validate a model based on dual-energy CT quantification of extracellular liver volume (ECVIC-liver) for predicting the occurrence of acute-on-chronic liver failure (ACLF) within 90 days in patients with hepatitis B (HBV) LC-AD. METHODS The retrospective study included patients with HBV LC-AD who underwent dual-energy CT scans of the liver from January 2018 to March 2022 and were randomized to training group (215 patients) and validation group (92 patients). The primary outcome was the need for readmission within 90 days due to ACLF. Based on the training group data, independent risk factors for disease progression in clinical and dual-energy CT parameters were identified and modeled by logistic regression analysis. Based on the training and validation groups data, receiver operating characteristic (ROC) curves, calibration curves, and decision analysis curves (DCA) were used to verify the discrimination, calibration, and clinical validity of the nomogram. RESULTS Chronic liver failure consortium-acute decompensation score (CLIF-C ADs) (p = 0.008) and ECVIC-liver (p < 0.001) were independent risk factors for ACLF within 90 days. The AUC of the model combined ECVIC-liver and CLIF-C ADs were 0.893 and 0.838 in the training and validation groups, respectively. The calibration curves show good agreement between predicted and actual risks. The DCA indicates that the model has good clinical application. CONCLUSION The model combined ECVIC-liver and CLIF-C ADs can early predict the occurrence of ACLF within 90 days in HBV LC-AD patients.
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Affiliation(s)
- Yuan Xu
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China
| | - Yufeng Li
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China
| | - Shenglin Li
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China
| | - Shouxiao Xue
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China
| | - Jianli Liu
- Department of Radiology, Lanzhou University Second Hospital, Lanzhou, China.
- Second Clinical School, Lanzhou University, Lanzhou, China.
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou University Second Hospital, Lanzhou, China.
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Zhang X, Song J, Zhang Y, Wen B, Dai L, Xi R, Wu Q, Li Y, Luo X, Lan X, He Q, Luo W, Lai Q, Ji Y, Zhou L, Qi T, Liu M, Zhou F, Wen W, Li H, Liu Z, Chen Y, Zhu Y, Li J, Huang J, Cheng X, Tu M, Hou J, Wang H, Chen J. Baveno VII algorithm outperformed other models in ruling out high-risk varices in individuals with HBV-related cirrhosis. J Hepatol 2023; 78:574-583. [PMID: 36356684 DOI: 10.1016/j.jhep.2022.10.030] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 10/06/2022] [Accepted: 10/13/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND & AIMS The Baveno VII consensus recommends that spleen stiffness measurement (SSM) ≤40 kPa is safe for ruling out high-risk varices (HRVs) and avoiding endoscopic screening in patients who do not meet the Baveno VI criteria. This study aimed to validate the performance of the Baveno VII algorithm in individuals with HBV-related cirrhosis. METHODS Consecutive individuals with HBV-related cirrhosis who underwent liver stiffness measurement (LSM) and SSM - using a 50 Hz shear wave frequency, spleen diameter measurement, and esophagogastroduodenoscopy (EGD) were prospectively enrolled from June 2020. A 100 Hz probe has been adopted for additional SSM assessment since July 2021. RESULTS From June 2020 to January 2022, 996 patients were screened and 504 were enrolled for analysis. Among the 504 patients in whom SSM was assessed using a 50 Hz probe, the Baveno VII algorithm avoided more EGDs (56.7% vs. 39.1%, p <0.001) than Baveno VI criteria, with a comparable missed HRV rate (3.8% vs. 2.5%). Missed HRV rates were >5% for all other measures: 11.3% for LSM-longitudinal spleen diameter to platelet ratio score, 20.0% for platelet count/longitudinal spleen diameter ratio, and 8.8% for Rete Sicilia Selezione Terapia-hepatitis. SSM@100 Hz was assessed in 232 patients, and the Baveno VII algorithm with SSM@100 Hz spared more EGDs (75.4% vs. 59.5%, p <0.001) than that with SSM@50 Hz, both with a missed HRV rate of 3.0% (1/33). CONCLUSIONS We validated the Baveno VII algorithm, demonstrating the excellent performance of SSM@50 Hz and SSM@100 Hz in ruling out HRV in individuals with HBV-related cirrhosis. Furthermore, the Baveno VII algorithm with SSM@100 Hz could safely rule out more EGDs than that with SSM@50 Hz. CLINICAL TRIAL NUMBER NCT04890730. IMPACT AND IMPLICATIONS The Baveno VII guideline proposed that for patients who do not meet the Baveno VI criteria, SSM ≤40 kPa could avoid further unnecessary endoscopic screening. The current study validated the Baveno VII algorithm using 50 Hz and 100 Hz probes, which both exhibited excellent performance in ruling out HRVs in individuals with HBV-related cirrhosis. Compared with the Baveno VII algorithm with SSM@50 Hz, SSM@100 Hz had a better capability to safely rule out unnecessary EGDs. Baveno VII algorithm will be a practical tool to triage individuals with cirrhosis in future clinical practice.
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Affiliation(s)
- Xiaofeng Zhang
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; Department of Hepatology, Zengcheng Branch, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jiankang Song
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yuanjian Zhang
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Biao Wen
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; Chengdu Medical College, Chengdu, Sichuan, China
| | - Lin Dai
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Ranran Xi
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Qiaoping Wu
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yuan Li
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Xiaoqin Luo
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; Department of Hepatology, Zengcheng Branch, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Xiaoqin Lan
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Qinjun He
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Wenfan Luo
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Qintao Lai
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yali Ji
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Ling Zhou
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Tingting Qi
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Miaoxia Liu
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Fuyuan Zhou
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Weiqun Wen
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Hui Li
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; Department of Hepatology, Zengcheng Branch, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Zhihua Liu
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yongpeng Chen
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Youfu Zhu
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Junying Li
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; Department of Hepatology, Zengcheng Branch, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jing Huang
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; Department of Hepatology, Zengcheng Branch, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Xiao Cheng
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; Department of Hepatology, Zengcheng Branch, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Minghan Tu
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; Department of Hepatology, Zengcheng Branch, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jinlin Hou
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Guangzhou, China
| | - Haiyu Wang
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China.
| | - Jinjun Chen
- Hepatology Unit, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China; Department of Hepatology, Zengcheng Branch, Nanfang Hospital, Southern Medical University, Guangzhou, China; State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Guangzhou, China.
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Sakamoto K, Tanaka S, Sato K, Ito E, Nishiyama M, Urakawa H, Arima H, Yoshimitsu K. What is the "washout" of hepatocellular carcinoma as observed on the equilibrium phase CT?: consideration based on the concept of extracellular volume fraction. Jpn J Radiol 2022; 40:1148-1155. [PMID: 35687200 DOI: 10.1007/s11604-022-01295-w] [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: 04/26/2022] [Accepted: 05/12/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE To verify the hypothesis that extracellular volume fraction (ECV) and precontrast CT density are the main determinants of washout of hepatocellular carcinoma (HCC) at the equilibrium phase CT. MATERIALS AND METHODS Between 2018 and 2020, patients with surgically resected HCC were recruited who had undergone preoperative 4-phase CT. Those larger than 6 cm were excluded to minimize the possibility of intratumoral hemorrhage or degeneration. Two radiologists reviewed the whole images in consensus and divided cases into washout positive and negative groups. Washout positive group at the equilibrium phase was defined as "HCC showing relatively low density as compared to the surrounding background liver (BGL), irrespective of the presence of early enhancement or fibrous capsule". Several clinico-pathological and radiological features, including ECV and precontrast CT density, were correlated to the presence of washout, using uni- and multi-variable analyses. RESULTS 27 HCC in 24 patients met the inclusion criteria. 22 (82%) and five HCC belonged to washout positive and negative groups, respectively. Univariable analysis revealed ECV of HCC and BGL, ECV difference between HCC and BGL, and presence of fibrous capsule on the equilibrium phase CT were the significant factors. Multivariable analysis showed ECV of HCC and BGL, and precontrast CT density of BGL, were the independently significant factors related to washout, suggesting washout is more likely observed with lower HCC ECV, higher BGL ECV, and higher BGL precontrast CT density. CONCLUSION Major determinants of washout of HCC may be ECV of HCC and BGL, and precontrast CT density of BGL.
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Affiliation(s)
- Keiko Sakamoto
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan
| | - Shinji Tanaka
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan
| | - Keisuke Sato
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan
| | - Emi Ito
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan
| | - Marie Nishiyama
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan
| | - Hiroshi Urakawa
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan
| | - Hisatomi Arima
- Department of Preventive Medicine and Public Health, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan
| | - Kengo Yoshimitsu
- Department of Radiology, Faculty of Medicine, Fukuoka University, 7-45-1 Nanakuma, Jonanku, Fukuoka, Japan.
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