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Herrmann J, Petit P, Grabhorn E, Lenz A, Jürgens J, Franchi-Albella S. Liver cirrhosis in children - the role of imaging in the diagnostic pathway. Pediatr Radiol 2023; 53:714-726. [PMID: 36040526 PMCID: PMC10027649 DOI: 10.1007/s00247-022-05480-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 06/23/2022] [Accepted: 07/31/2022] [Indexed: 10/14/2022]
Abstract
Liver cirrhosis in children is a rare disease with multifactorial causes that are distinct from those in adults. Underlying reasons include cholestatic, viral, autoimmune, hereditary, metabolic and cardiac disorders. Early detection of fibrosis is important as clinical stabilization or even reversal of fibrosis can be achieved in some disorders with adequate treatment. This article focuses on the longitudinal evaluation of children with chronic liver disease with noninvasive imaging tools, which play an important role in detecting cirrhosis, defining underlying causes, grading fibrosis and monitoring patients during follow-up. Ultrasound is the primary imaging modality and it is used in a multiparametric fashion. Magnetic resonance imaging and computed tomography are usually applied second line for refined tissue characterization, clarification of nodular lesions and full delineation of abdominal vessels, including portosystemic communications.
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Affiliation(s)
- Jochen Herrmann
- Section of Pediatric Radiology, Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20251, Hamburg, Germany.
| | - Philippe Petit
- Aix Marseille Université, Hopital Timone-Enfants, Marseille, France
| | - Enke Grabhorn
- Department of Pediatric Gastroenterology and Hepatology, University Medical Center Hamburg, Hamburg, Germany
| | - Alexander Lenz
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center, Hamburg, Germany
| | - Julian Jürgens
- Section of Pediatric Radiology, Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20251, Hamburg, Germany
| | - Stéphanie Franchi-Albella
- Department of Pediatric Radiology, Hôpital Bicêtre, National Reference Centre for Rare Pediatric Liver Diseases, Paris, France
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Ye H, Wang Q, Huang H, Zhao K, Li P, Liu Z, Wang G, Liang C. L-distance ratio: a new distance ratio-based evaluation method for the diagnosis of cirrhosis using enhanced computed tomography. Quant Imaging Med Surg 2023; 13:1499-1509. [PMID: 36915361 PMCID: PMC10006107 DOI: 10.21037/qims-22-861] [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: 08/15/2022] [Accepted: 12/14/2022] [Indexed: 01/11/2023]
Abstract
Background Early detection of liver cirrhosis is of great significance to the formulation of treatment plans and improving prognosis. Computed tomography (CT) is commonly used in the assessment of patients with chronic liver disease. In this study, we proposed a new distance ratio method for accurate diagnosis of cirrhosis using CT images. Methods This was a retrospective study of a consecutive series of patients in Guangdong Provincial People's Hospital. Sixty-two patients with pathologically diagnosed cirrhosis but whose morphologic changes were insufficient to diagnose cirrhosis were included in the cirrhosis group. Those who were pathologically confirmed to be free of cirrhosis and fibrosis and without a history of chronic hepatic were classified as the control group. A total of 124 patients underwent abdominal dynamic enhanced CT. Both the L-distance ratio-the ratio of the distance from the right portal vein bifurcation point to the anterior and posterior edges of the liver-and the caudate-right lobe ratio were measured by two independent radiologists. Intraclass correlation coefficients (ICCs) were used to assess the agreement between the radiologists. Binary logistic regression was performed for univariate analysis, and the odds ratio (OR) was also calculated. The discrimination ability of the two methods was evaluated by the area under the receiver operating characteristic curve (AUC). Results For both the L-distance ratio and the caudate-right lobe ratio, high agreement was observed between the two radiologists, although the ICC value of the L-distance ratio was slightly higher than that of the caudate-right lobe ratio (0.916 vs. 0.907). Binary logistic regression suggested that higher ratios were correlated with cirrhosis [the L-distance ratio, high vs. low OR =4.41, 95% confidence interval (CI): 2.08-9.36, P<0.001; the caudate-right lobe ratio, high vs. low OR =2.19, 95% CI: 1.07-4.49, P=0.031]. The AUCs of the L-distance ratio and the caudate-right lobe ratio were 0.823 (95% CI: 0.752-0.894) and 0.663 (95% CI: 0.569-0.757), respectively. Conclusions The L-distance ratio method proposed in this paper is more simple, accurate, and reliable than the caudate-right lobe ratio method in the diagnosis of cirrhosis.
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Affiliation(s)
- Huifen Ye
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.,Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Qiushi Wang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Haitao Huang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China.,School of Medicine, South China University of Technology, Guangzhou, China
| | - Ke Zhao
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Pinxiong Li
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.,Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Zaiyi Liu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.,Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
| | - Guangyi Wang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Changhong Liang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.,Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China
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Abstract
Early diagnosis of hepatic fibrosis (HF) is pivotal for management to cease progression to cirrhosis and hepatocellular carcinoma. HF is the telltale sign of chronic liver disease, and confirmed by liver biopsy, which is an invasive technique and inclined to sampling errors. The morphologic parameters of cirrhosis are assessed on conventional imaging such as on ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI). Newer imaging modalities such as magnetic resonance elastography and US elastography are reliable and accurate. More research studies on novel imaging modalities such as MRI with diffusion weighted imaging, enhancement by hepatobiliary contrast agents, and CT using perfusion are essential for earlier diagnosis, surveillance and accurate management. The purpose of this article is to discuss non-invasive CT, MRI, and US imaging modalities for diagnosis and stratify HF.
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Affiliation(s)
- Mayur Virarkar
- Department of Neuroradiology, The University of Texas Health Science Center, Houston, TX.
| | - Ajaykumar C Morani
- Department of Abdominal Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Melissa W Taggart
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Priya Bhosale
- Department of Abdominal Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX
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Noninvasive Assessment of Liver Parenchyma Using Gray-Scale Ultrasound-Based Histogram Analysis in Patients With Chronic Hepatitis B Infection. Ultrasound Q 2020; 36:69-73. [PMID: 30855417 DOI: 10.1097/ruq.0000000000000438] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The aims of this study were to examine the alterations of liver echo-intensity histogram parameters in chronic hepatitis B (CHB) patients and to assess the potential role of histogram parameters in the evaluation of hepatic fibrosis. A total of 52 patients with CHB who underwent liver biopsies were included in the study. The control group consisted of 30 healthy individuals. Histogram parameters were obtained from histogram analysis of gray-scale ultrasound images of both groups. The histogram parameters of the groups were compared. The association of histogram parameters with the grading and staging of histological activity index (HAI) in patients with CHB were evaluated. The patient group had statistically significant lower skewness, kurtosis, and higher variance, mean, 50th, and 90th percentile values compared with control group. When patients with CHB were divided into subgroups according to HAI stage, there was the increasing trend in skewness values and decreasing trend in kurtosis values across subgroups. The first percentile values showed negative correlation with HAI staging in patients with CHB. Ultrasound is a fast, inexpensive, and reproducible imaging method; histogram analysis of gray-scale ultrasound images may provide useful information for evaluation of hepatic fibrosis in CHB patients.
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Wang Q, Liu H, Zhu Z, Sheng Y, Du Y, Li Y, Liu J, Zhang J, Xing W. Feasibility of T1 mapping with histogram analysis for the diagnosis and staging of liver fibrosis: Preclinical results. Magn Reson Imaging 2020; 76:79-86. [PMID: 33242591 DOI: 10.1016/j.mri.2020.11.006] [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: 08/19/2020] [Revised: 10/10/2020] [Accepted: 11/14/2020] [Indexed: 02/07/2023]
Abstract
PURPOSE To compare the diagnostic accuracy of parameters derived from the histogram analysis of precontrast, 10-min hepatobiliary phase (HBP) and 20-min HBP T1 maps for staging liver fibrosis (LF). METHODS LF was induced in New Zealand white rabbits by subcutaneous injections of carbon tetrachloride for 4-16 weeks (n = 120), and 20 rabbits injected with saline served as controls. Precontrast, 10-min and 20-min HBP modified Look-Locker inversion recovery (MOLLI) T1 mapping was performed. Histogram analysis of T1 maps was performed, and the mean, median, skewness, kurtosis, entropy, inhomogeneity and 10th/25th/75th/90th percentiles of T1native, T110min and T120min were derived. Quantitative histogram parameters were compared. For significant parameters, further receiver operating characteristic (ROC) analyses were performed to evaluate the potential diagnostic performance in differentiating LF stages. RESULTS Finally, 17, 20, 21, 21 and 20 rabbits were included for the F0, F1, F2, F3, and F4 pathological grades of fibrosis, respectively. The mean/75th of T1native, entropy of T110min and entropy/mean/median/10th of T120min demonstrated a significant good correlation with the LF stage (|r| = 0.543-0.866, all P < 0.05). The 75th of T1native, entropy10min, and entropy20min were the three most reliable imaging markers in reflecting the stage of LF. The area under the ROC curve of entropy20min was larger than that of entropy10min (P < 0.05 for LF ≥ F2, ≥F3, and ≥ F4) and the 75th of T1native (P < 0.05 for LF ≥ F2 and ≥ F3) for staging LF. CONCLUSION Magnetic resonance histogram analysis of T1 maps, particularly the entropy derived from 20-min HBP T1 mapping, is promising for predicting the LF stage.
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Affiliation(s)
- Qing Wang
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou & Changzhou First People's Hospital, Jiangsu 213200, China.
| | - HaiFeng Liu
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou & Changzhou First People's Hospital, Jiangsu 213200, China
| | - ZuHui Zhu
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou & Changzhou First People's Hospital, Jiangsu 213200, China
| | - Ye Sheng
- Department of Interventional Radiology, Third Affiliated Hospital of Soochow University & Changzhou First People's Hospital, Changzhou, Jiangsu 213200, China
| | - YaNan Du
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou & Changzhou First People's Hospital, Jiangsu 213200, China
| | - YuFeng Li
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou & Changzhou First People's Hospital, Jiangsu 213200, China
| | - JianHong Liu
- Department of Pathology, The Third People's Hospital of Changzhou, Changzhou, Jiangsu 213200, China
| | | | - Wei Xing
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou & Changzhou First People's Hospital, Jiangsu 213200, China.
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Xu X, Zhu H, Li R, Lin H, Grimm R, Fu C, Yan F. Whole-liver histogram and texture analysis on T1 maps improves the risk stratification of advanced fibrosis in NAFLD. Eur Radiol 2020; 31:1748-1759. [PMID: 32897416 PMCID: PMC7880972 DOI: 10.1007/s00330-020-07235-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 06/04/2020] [Accepted: 08/27/2020] [Indexed: 12/16/2022]
Abstract
Objectives To assess whole-liver texture analysis on T1 maps for risk stratification of advanced fibrosis in patients with suspected nonalcoholic fatty liver disease (NAFLD). Methods This retrospective study included 53 patients. Histogram and texture parameters (volume, mean, SD, median, 5th percentile, 95th percentile, skewness, kurtosis, diff-entropy, diff-variance, contrast, and entropy) of T1 maps were calculated based on the semi-automatically segmented whole-liver volume. A two-step approach combining the Nonalcoholic Fatty Liver Disease Fibrosis Score (NFS) and Fibrosis-4 Index (FIB-4) with the liver stiffness measurement (LSM) for the risk stratification was used. Univariate analysis was performed to identify significant parameters. Logistic regression models were then run on the significant features. Diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis. Results In total, 33 (62%) subjects had a low risk and 20 (38%) subjects had an intermediate-to-high risk of advanced fibrosis. The following significantly different parameters with the best performance were diff-entropy, entropy, and diff-variance, with AUROC 0.837 (95% CI 0.73–0.95), 0.821 (95% CI 0.71–0.94), and 0.807 (95% CI 0.69–0.93). The optimal combination of median, 5th percentile, and diff-entropy as a multivariate model improved the diagnostic performance to diagnose an intermediate-to-high risk of advanced fibrosis with AUROC 0.902(95% CI 0.79–0.97). Conclusions Parameters obtained by histogram and texture analysis of T1 maps may be a noninvasive analytical approach for stratifying the risk of advanced fibrosis in NAFLD. Key Points • Variable flip angle (VFA) T1 mapping can be used to acquire 3D T1 maps within a clinically acceptable duration. • Whole-liver histogram and texture parameters on T1 maps in patients with NAFLD can distinguish those with an intermediate-to-high risk of advanced fibrosis. • The multivariate model of combination of texture parameters improved the diagnostic performance for a high risk of advanced fibrosis and clinical parameters offer no added value to the multivariate model. Electronic supplementary material The online version of this article (10.1007/s00330-020-07235-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xinxin Xu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai, 200025, China
| | - Hong Zhu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai, 200025, China
| | - Ruokun Li
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai, 200025, China
| | - Huimin Lin
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai, 200025, China
| | - Robert Grimm
- MR Applications Predevelopment, Siemens Healthcare, Erlangen, Germany
| | - Caixia Fu
- MR Applications Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, People's Republic of China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai, 200025, China.
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Zheng Y, Xu YS, Liu Z, Liu HF, Zhai YN, Mao XR, Lei JQ. Whole-Liver Apparent Diffusion Coefficient Histogram Analysis for the Diagnosis and Staging of Liver Fibrosis. J Magn Reson Imaging 2019; 51:1745-1754. [PMID: 31729811 DOI: 10.1002/jmri.26987] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 10/17/2019] [Accepted: 10/18/2019] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Conventional diffusion-weighted imaging is limited in the quantitative evaluation of liver fibrosis, and whole-liver apparent diffusion coefficient (ADC) histogram analysis might contribute to the diagnosis and staging of liver fibrosis. PURPOSE To explore the value of whole-liver ADC histogram parameters in the diagnosis and staging of liver fibrosis. STUDY TYPE Retrospective. POPULATION Twenty individuals with no liver disease and 86 patients with liver fibrosis, including 30 with chronic viral hepatitis, 29 with autoimmune hepatitis, and 27 with unexplained liver fibrosis patients. FIELD STRENGTH/SEQUENCE 3.0T/T1 -weighted, T2 -weighted, and diffusion-weighted images. ASSESSMENT A region of interest (ROI) was drawn in each slice of the diffusion-weighted images. Whole-liver histogram parameters were obtained with dedicated software by accumulating all ROIs. The effectiveness of the parameters in differentiating stage 1 or greater (≥F1), stage 2 or greater (≥F2), and stage 3 or greater (≥F3) liver fibrosis was assessed. STATISTICAL TESTS Mann-Whitney U-test and receiver operating characteristic curve analysis. RESULTS Kurtosis, entropy, skewness, mode, and 90th and 75th percentiles exhibited significant differences among the pathological fibrosis stages (P < 0.05). Kurtosis was found to be the most meaningful parameter in differentiating fibrosis stages of the viral hepatitis, autoimmune hepatitis, and unexplained liver fibrosis group (area under the curve) (AUC = 0.793, 0.771, 0.798, respectively). In the combined liver fibrosis group, kurtosis achieved the highest AUC (0.801; 95% confidence interval [CI]: 0.702-0.900; sensitivity: 0.750; specificity: 0.850; positive likelihood ratio: 4.953; negative likelihood ratio: 0.302; positive predictive value: 0.946; negative predictive value: 0.486), with a cutoff value of 1.817, in differentiating fibrosis stage ≥F1. DATA CONCLUSION Kurtosis, entropy, skewness, mode, and 90th and 75th percentiles may contribute to the diagnosis and staging of liver fibrosis, especially kurtosis. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:1745-1754.
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Affiliation(s)
- You Zheng
- First Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China.,Department of Radiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Yong-Sheng Xu
- First Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China
| | - Zhao Liu
- First Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China
| | - Hai-Feng Liu
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Ya-Nan Zhai
- First Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China
| | - Xiao-Rong Mao
- Department of Infectious Diseases, First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Jun-Qiang Lei
- First Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China
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Li S, Sun X, Chen M, Ying Z, Wan Y, Pi L, Ren B, Cao Q. Liver Fibrosis Conventional and Molecular Imaging Diagnosis Update. JOURNAL OF LIVER 2019; 8:236. [PMID: 31341723 PMCID: PMC6653681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Liver fibrosis is a serious, life-threatening disease with high morbidity and mortality that result from diverse causes. Liver biopsy, considered the "gold standard" to diagnose, grade, and stage liver fibrosis, has limitations in terms of invasiveness, cost, sampling variability, inter-observer variability, and the dynamic process of fibrosis. Compelling evidence has demonstrated that all stages of fibrosis are reversible if the injury is removed. There is a clear need for safe, effective, and reliable non-invasive assessment modalities to determine liver fibrosis in order to manage it precisely in personalized medicine. However, conventional imaging methods used to assess morphological and structural changes related to liver fibrosis, including ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), are only useful in assessing advanced liver disease, including cirrhosis. Functional imaging techniques, including MR elastography (MRE), US elastography, and CT perfusion are useful for assessing moderate to advanced liver fibrosis. MRE is considered the most accurate noninvasive imaging technique, and US elastography is currently the most widely used noninvasive means. However, these modalities are less accurate in early-stage liver fibrosis and some factors affect the accuracy of these techniques. Molecular imaging is a target-specific imaging mechanism that has the potential to accurately diagnose early-stage liver fibrosis. We provide an overview of recent advances in molecular imaging for the diagnosis and staging of liver fibrosis which will enable clinicians to monitor the progression of disease and potentially reverse liver fibrosis. We compare the promising technologies with conventional and functional imaging and assess the utility of molecular imaging in precision and personalized clinical medicine in the early stages of liver fibrosis.
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Affiliation(s)
- Shujing Li
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA,Department of Radiology, The first affiliated Hospital of Hebei Medical University, Shijiazhuang, Hebei province, P.R.China
| | - Xicui Sun
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Minjie Chen
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Zhekang Ying
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Yamin Wan
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA,Department of Radiology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan province, P.R.China
| | - Liya Pi
- Department of Pediatrics in the College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Bin Ren
- Department of Surgery, University of Alabama at Birmingham School of Medicine, Alabama, USA
| | - Qi Cao
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA,Corresponding author: Qi Cao, MD. Ph.D, Department of Diagnostic Radiology and Nuclear Medicine University of Maryland School of Medicine, West Baltimore, Street Baltimore, Maryland, USA, Tel: +1 410-706-6432;,
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Cai Y, Huang MP, Wang XF, Lu X, Luo L, Shu J. Quantitative analysis of susceptibility-weighted magnetic resonance imaging in chronic hepatitis in rats. Magn Reson Imaging 2018; 54:71-76. [DOI: 10.1016/j.mri.2018.08.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Revised: 08/01/2018] [Accepted: 08/17/2018] [Indexed: 02/07/2023]
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Hu F, Yang R, Huang Z, Wang M, Zhang H, Yan X, Song B. Liver fibrosis: in vivo evaluation using intravoxel incoherent motion-derived histogram metrics with histopathologic findings at 3.0 T. Abdom Radiol (NY) 2017. [PMID: 28624925 DOI: 10.1007/s00261-017-1208-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
PURPOSE To retrospectively determine the feasibility of intravoxel incoherent motion (IVIM) imaging based on histogram analysis for the staging of liver fibrosis (LF) using histopathologic findings as the reference standard. METHODS 56 consecutive patients (14 men, 42 women; age range, 15-76, years) with chronic liver diseases (CLDs) were studied using IVIM-DWI with 9 b-values (0, 25, 50, 75, 100, 150, 200, 500, 800 s/mm2) at 3.0 T. Fibrosis stage was evaluated using the METAVIR scoring system. Histogram metrics including mean, standard deviation (Std), skewness, kurtosis, minimum (Min), maximum (Max), range, interquartile (Iq) range, and percentiles (10, 25, 50, 75, 90th) were extracted from apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) maps. All histogram metrics among different fibrosis groups were compared using one-way analysis of variance or nonparametric Kruskal-Wallis test. For significant parameters, receivers operating characteristic curve (ROC) analyses were further performed for the staging of LF. RESULTS Based on their METAVIR stage, the 56 patients were reclassified into three groups as follows: F0-1 group (n = 25), F2-3 group (n = 21), and F4 group (n = 10). The mean, Iq range, percentiles (50, 75, and 90th) of D* maps between the groups were significant differences (all P < 0.05). Area under the ROC curve (AUC) of the mean, Iq range, 50, 75, and 90th percentile of D* maps for identifying significant LF (≥F2 stage) was 0.901, 0.859, 0.876, 0.943, and 0.886 (all P < 0.0001), respectively; for diagnosing severe fibrosis or cirrhosis (F4), AUC was 0.917, 0.922, 0.943, 0.985, and 0.939 (all P < 0.0001), respectively. The histogram metrics of ADC, D, and f maps demonstrated no significant difference among the groups (all P > 0.05). CONCLUSION Histogram analysis of D* map derived from IVIM can be used to stage liver fibrosis in patients with CLDs and provide more quantitative information beyond the mean value.
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Affiliation(s)
- Fubi Hu
- Department of Radiology, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan, China
- Department of Radiology, The First Affiliated Hospital of Chengdu Medical College, 278# Baoguang Road, Xindu District, Chengdu, Sichuan, China
| | - Ru Yang
- Department of Radiology, The First Affiliated Hospital of Chengdu Medical College, 278# Baoguang Road, Xindu District, Chengdu, Sichuan, China
| | - Zixing Huang
- Department of Radiology, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan, China
| | - Min Wang
- Department of Radiology, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan, China
| | - Hanmei Zhang
- Department of Radiology, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan, China
| | - Xu Yan
- Siemens Healthcare, MR Collaborations NE Asia, Shanghai, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, 37# Guoxue Road, Chengdu, Sichuan, China.
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