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Verdan S, Torri GB, Marcos VN, Moreira MHS, Defante MLR, Fagundes MDC, de Barros EMJ, Dias AB, Shen L, Altmayer S. Ultrasound-derived fat fraction for diagnosing hepatic steatosis: a systematic review and meta-analysis. Eur Radiol 2025:10.1007/s00330-025-11652-8. [PMID: 40346257 DOI: 10.1007/s00330-025-11652-8] [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: 01/27/2025] [Revised: 03/06/2025] [Accepted: 04/05/2025] [Indexed: 05/11/2025]
Abstract
OBJECTIVE To perform a systematic review and meta-analysis to evaluate the diagnostic performance of Ultrasound-Derived Fat Fraction (UDFF) in detecting hepatic steatosis using Magnetic Resonance Imaging-Proton Density Fat Fraction (MRI-PDFF) as the reference standard. MATERIALS AND METHODS Relevant databases were searched through November 2024. Studies that evaluated the UDFF to detect hepatic steatosis using MRI-PDFF as the reference standard met the inclusion criteria. Our primary outcome was the sensitivity and specificity of UDFF compared to MRI-PDFF in distinguishing steatosis from non-steatosis. Analyses were performed using a bivariate random-effects approach, and heterogeneity was considered substantial if I2 > 50%. A sensitivity analysis was performed to detect potential studies that contribute to heterogeneity. RESULTS Nine studies comprising 1150 patients (mean age range, 14-62 years; 51.2% women) were included. Eight studies were performed using the same vendor platform. The pooled sensitivity of UDFF for detecting hepatic steatosis was 90.4% (95% CI: 84.0%, 94.4%), and the pooled specificity was 83.8% (95% CI: 75.1%, 89.8%). The AUC for the summary receiver-operating characteristic curve was 0.93 (95% CI: 0.83, 0.95). Heterogeneity among the studies was low (I² = 22.2%). CONCLUSION UDFF demonstrates high sensitivity and specificity for detecting hepatic steatosis, supporting its value as a noninvasive tool for screening. KEY POINTS Question Small individual studies suggest that US-Derived Fat Fraction (UDFF) may effectively detect hepatic steatosis compared to MRI, but no meta-analysis has been performed. Findings In nine studies including 1150 patients, UDFF demonstrated high pooled sensitivity (90.4%) and specificity (83.8%) relative to MRI with low between-study heterogeneity. Clinical relevance UDFF demonstrates high diagnostic accuracy compared with MRI, supporting its use as a noninvasive tool with potentially lower cost and wider availability for large-scale screening of hepatic steatosis.
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Affiliation(s)
- Sarah Verdan
- Department of Radiology and Diagnostic Imaging, University Hospital of Juiz de Fora - UFJF, Juiz de Fora, Brazil.
| | - Giovanni B Torri
- Department of Radiology and Diagnostic Imaging, Hospital Universitário de Santa Maria, Universidade Federal de Santa Maria, Santa Maria, Brazil
| | - Vinícius Neves Marcos
- Department of Radiology and Diagnostic Imaging, University Hospital of Juiz de Fora - UFJF, Juiz de Fora, Brazil
| | - Maria Helena Silva Moreira
- Department of Radiology and Diagnostic Imaging, University Hospital of Juiz de Fora - UFJF, Juiz de Fora, Brazil
| | | | | | | | - Adriano B Dias
- University Medical Imaging Toronto, Joint Department of Medical Imaging, University Health Network-Sinai Health System-Women's College Hospital, University of Toronto, Toronto, ON, Canada
| | - Luyao Shen
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Stephan Altmayer
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
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Jin X, Yip TCF, Wong GLH, Wong VWS, Lai JCT. The new definition of metabolic dysfunction-associated steatotic liver disease: the role of ultrasound and elastography. Ultrasonography 2025; 44:189-201. [PMID: 40211108 PMCID: PMC12081130 DOI: 10.14366/usg.24219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2024] [Revised: 03/13/2025] [Accepted: 03/18/2025] [Indexed: 04/12/2025] Open
Abstract
In 2023, nonalcoholic fatty liver disease was renamed metabolic dysfunction-associated steatotic liver disease by the American and European liver associations. This new nomenclature recognizes metabolic dysfunction as the central driver of the disease, and the diagnostic criteria now require the presence of hepatic steatosis plus at least one of five cardiometabolic risk factors. B-mode ultrasonography remains the most common and practical method for detecting hepatic steatosis, although newer ultrasound techniques based on attenuation, backscatter, and speed of sound have gained traction as tools to diagnose and quantify hepatic steatosis. Additionally, ultrasound elastography is increasingly used in routine clinical practice to assess liver fibrosis, diagnose cirrhosis, and identify clinically significant portal hypertension.
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Affiliation(s)
- Xinrui Jin
- Department of Medicine and Therapeutics, Medical Data Analytics Center, The Chinese University of Hong Kong, Hong Kong, China
- State Key Laboratory of Digestive Disease, Institute of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Terry Cheuk-Fung Yip
- Department of Medicine and Therapeutics, Medical Data Analytics Center, The Chinese University of Hong Kong, Hong Kong, China
- State Key Laboratory of Digestive Disease, Institute of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Grace Lai-Hung Wong
- Department of Medicine and Therapeutics, Medical Data Analytics Center, The Chinese University of Hong Kong, Hong Kong, China
- State Key Laboratory of Digestive Disease, Institute of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Vincent Wai-Sun Wong
- Department of Medicine and Therapeutics, Medical Data Analytics Center, The Chinese University of Hong Kong, Hong Kong, China
- State Key Laboratory of Digestive Disease, Institute of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Jimmy Che-To Lai
- Department of Medicine and Therapeutics, Medical Data Analytics Center, The Chinese University of Hong Kong, Hong Kong, China
- State Key Laboratory of Digestive Disease, Institute of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
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Qi R, Lu L, He T, Zhang L, Lin Y, Bao L. Comparing ultrasound-derived fat fraction and MRI-PDFF for quantifying hepatic steatosis: a real-world prospective study. Eur Radiol 2025; 35:2580-2588. [PMID: 39414658 DOI: 10.1007/s00330-024-11119-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Revised: 07/24/2024] [Accepted: 09/10/2024] [Indexed: 10/18/2024]
Abstract
OBJECTIVE To compare the agreement between ultrasound-derived fat fraction (UDFF) with magnetic resonance proton density fat fraction (MRI-PDFF) for quantification of hepatic steatosis and verify its reliability and diagnostic performance by comparing with MRI-PDFF as the reference standard. METHODS This prospective study included a primary analysis of 191 patients who underwent MRI-PDFF and UDFF from February 2023 to February 2024. MRI-PDFF were derived from three liver segment measurements with calculation of an overall median PDFF. UDFF was performed by two different sonographers for each of the six measurements, and the median was taken. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were used to assess agreement. Receiver operating characteristics (ROC) curves were used to evaluate the diagnostic performance of UDFF in detecting different degrees of hepatic steatosis. RESULTS A total of 176 participants were enrolled in the final cohort of this study (median age, 36.0 years; 82 men, 94 women). The median MRI-PDFF value was 11.3% (interquartile range (IQR) 7.5-18.9); 84.7% patients had a median MRI-PDFF value ≥ 6.4%. The median UDFF measured by different sonographers were 9.5% (IQR: 5.0-18.0) and 9.0% (IQR: 5.0-18.0), respectively. The interobserver agreement of UDFF measurement was excellent agreement (ICC = 0.951 [95% CI: 0.934-0.964], p < 0.001). UDFF was positively strongly correlated with MRI-PDFF with ICC of 0.899 (95% CI: 0.852-0.930). The Bland-Altman analysis showed high agreement between UDFF and MRI-PDFF measurements, with a mean bias of 1.7% (95% LOA, -8.7 to 12.2%). The optimal UDFF cutoff values were 5.5%, 15.5% and 17.5% for detecting MRI-PDFF at historic thresholds of 6.4%, 17.4%, and 22.1%, with AUC of 0.851, 0.952, and 0.948, respectively. The sensitivity was 79.2%, 87.5%, 88.9%, and specificity was 81.5%, 90.6%, 90.0%, respectively. CONCLUSIONS UDFF is a reliable and accurate method for quantification and classification of hepatic steatosis, with strong agreement to MRI-PDFF. The UDFF cutoff values of 5.5%, 15.5%, and 17.5% provide high sensitivity and specificity for the detection of mild, moderate, and severe hepatic steatosis, respectively. KEY POINTS Question Is ultrasound-derived fat fraction (UDFF) reliable for the quantitative detection of hepatic steatosis compared to MRI proton density fat fraction (MRI-PDFF)? Findings UDFF cutoff values of 5.5%, 15.5%, and 17.5% provided high sensitivity and specificity for the detection of mild, moderate, and severe hepatic steatosis, respectively. Clinical relevance UDFF is a reliable and accurate method for quantification and classification of hepatic steatosis, with strong agreement to MRI-PDFF and high reproducibility of liver fat content by different sonographers.
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Affiliation(s)
- Ruixiang Qi
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Liren Lu
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Ting He
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Liqing Zhang
- Department of Radiology, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Yiting Lin
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China
| | - Lingyun Bao
- Department of Ultrasound, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, P.R. China.
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Davis LM, Martinez-Correa S, Freeman CW, Adams C, Sultan LR, Le DQ, Lemessa N, Darge K, Hwang M. Ultrasound innovations in abdominal radiology: techniques and clinical applications in pediatric imaging. Abdom Radiol (NY) 2025; 50:1744-1762. [PMID: 39406993 PMCID: PMC11947074 DOI: 10.1007/s00261-024-04616-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Revised: 09/17/2024] [Accepted: 09/24/2024] [Indexed: 01/03/2025]
Abstract
Contrast-enhanced ultrasound, microvascular imaging, elastography, and fat quantification have varying degrees of utility, with some applications in the pediatric setting mirroring that in adults and having unique uses when applied to children in others. This review will present novel ultrasound technologies and the clinical context in which they are applied to the pediatric abdomen. New ultrasound technologies have a broad range of applications in clinical practice and represent a powerful diagnostic tool with the potential to replace other imaging modalities, such as magnetic resonance imaging and computed tomography, in specific cases.
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Affiliation(s)
| | | | | | | | - Laith R Sultan
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - David Q Le
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Natae Lemessa
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kassa Darge
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | - Misun Hwang
- Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- University of Pennsylvania, Philadelphia, PA, USA.
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Pan Z, Chen Q, Lin H, Huang W, Li J, Meng F, Zhong Z, Liu W, Li Z, Qin H, Huang B, Chen Y. Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning. Abdom Radiol (NY) 2025:10.1007/s00261-025-04804-3. [PMID: 39841227 DOI: 10.1007/s00261-025-04804-3] [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: 09/11/2024] [Revised: 01/08/2025] [Accepted: 01/08/2025] [Indexed: 01/23/2025]
Abstract
PURPOSE Intra-pancreatic fat deposition (IPFD) is closely associated with the onset and progression of type 2 diabetes mellitus (T2DM). We aimed to develop an accurate and automated method for assessing IPFD on multi-echo Dixon MRI. MATERIALS AND METHODS In this retrospective study, 534 patients from two centers who underwent upper abdomen MRI and completed multi-echo and double-echo Dixon MRI were included. A pancreatic segmentation model was trained on double-echo Dixon water images using nnU-Net. Predicted masks were registered to the proton density fat fraction (PDFF) maps of the multi-echo Dixon sequence. Deep semantic segmentation feature-based radiomics (DSFR) and radiomics features were separately extracted on the PDFF maps and modeled using the support vector machine method with 5-fold cross-validation. The first deep learning radiomics (DLR) model was constructed to distinguish T2DM from non-diabetes and pre-diabetes by averaging the output scores of the DSFR and radiomics models. The second DLR model was then developed to distinguish pre-diabetes from non-diabetes. Two radiologist models were constructed based on the mean PDFF of three pancreatic regions of interest. RESULTS The mean Dice similarity coefficient for pancreas segmentation was 0.958 in the total test cohort. The AUCs of the DLR and two radiologist models in distinguishing T2DM from non-diabetes and pre-diabetes were 0.868, 0.760, and 0.782 in the training cohort, and 0.741, 0.724, and 0.653 in the external test cohort, respectively. For distinguishing pre-diabetes from non-diabetes, the AUCs were 0.881, 0.688, and 0.688 in the training cohort, which included data combined from both centers. Testing was not conducted due to limited pre-diabetic patients. Intraclass correlation coefficients between radiologists' pancreatic PDFF measurements were 0.800 and 0.699 at two centers, suggesting good and moderate reproducibility, respectively. CONCLUSION The DLR model demonstrated superior performance over radiologists, providing a more efficient, accurate and stable method for monitoring IPFD and predicting the risk of T2DM and pre-diabetes. This enables IPFD assessment to potentially serve as an early biomarker for T2DM, providing richer clinical information for disease progression and management.
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Affiliation(s)
- Zhongxian Pan
- Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital (The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine), Shenzhen, China
| | - Qiuyi Chen
- Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital (The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine), Shenzhen, China
| | - Haiwei Lin
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, China
| | - Wensheng Huang
- Department of Radiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Junfeng Li
- Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital (The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine), Shenzhen, China
| | - Fanqi Meng
- Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital (The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine), Shenzhen, China
| | - Zhangnan Zhong
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, China
| | - Wenxi Liu
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, China
| | - Zhujing Li
- Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital (The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine), Shenzhen, China
| | - Haodong Qin
- MR Research Collaboration, Siemens Healthineers, Shanghai, China
| | - Bingsheng Huang
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, China.
| | - Yueyao Chen
- Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital (The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine), Shenzhen, China.
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Chen F, An J, Deng L, Wang J, He R. Consistency analysis of two US techniques for evaluating hepatic steatosis in patients with metabolic dysfunction-associated steatotic liver disease. BMC Med Imaging 2025; 25:10. [PMID: 39773394 PMCID: PMC11708176 DOI: 10.1186/s12880-024-01549-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2024] [Accepted: 12/30/2024] [Indexed: 01/11/2025] Open
Abstract
BACKGROUND US tools to quantify hepatic steatosis have recently been made clinically available by different manufacturers, but comparative data on their consistency are lacking. OBJECTIVE US tools to quantify hepatic steatosis have recently been made clinically available by different manufacturers, but comparative data on their consistency are lacking. The aim of our study was to compare the diagnostic consistency for evaluating hepatic steatosis by two different US techniques, hepatorenal index by B-mode Ratio and attenuation coefficient by attenuation imaging (ATI). METHODS Patients with suspicion or previously diagnosed of metabolic dysfunction-associated steatotic liver disease (MASLD) who attended fatty liver consulting room from June 2023 to September 2023 were prospectively recruited. Patients underwent two different US techniques of B-mode Ratio and ATI, and laboratory test were collected. According to previously proposed cut-off values, B-mode Ratio ≥ 1.22, 1.42, 1.54, and ATI ≥ 0.62, 0.70, and 0.78 dB/cm/MH were used for assessing of mild, moderate, and severe hepatic steatosis, respectively. Kappa consistency test was used to evaluate the consistency of hepatic steatosis. RESULTS A total of 62 patients were enrolled, including 44 males (71.0%) with an age of (41 ± 13) years and a body mass index of (27.0 ± 3.5) kg/m2. In the hyperlipidemia group, the B-mode Ratio and ATI were significantly higher than those in the non-hyperlipidemia group, with values of 1.68 ± 0.39 vs. 1.28 ± 0.35 (p = 0.001) and 0.74 ± 0.12 dB/cm/MH vs. 0.64 ± 0.11 dB/cm/MH (p = 0.005), respectively. The correlation coefficient between B-mode Ratio and ATI was 0.732 (p < 0.001). Using B-mode Ratio and ATI as diagnostic criteria for MASLD, the proportion of patients with MASLD was 79% and 82%, respectively. The Kappa coefficient for assessing MASLD was 0.90 (p < 0.001). Furthermore, these two different US techniques were used for grading hepatic steatosis, with no, mild, moderate, and severe steatosis accounting for 21%, 18%, 13%, and 48%, as well as 18%, 29%, 22%, and 31%, respectively. The linear weighted Kappa coefficient for staging hepatic steatosis was 0.78 (95% confidence interval: 0.68-0.87, p < 0.001). CONCLUSION The non-invasive methods of two different US techniques based on B-mode Ratio and ATI have good consistency for evaluating hepatic steatosis, and can be used for large-scale community screening.
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Affiliation(s)
- Fei Chen
- Department of Ultrasound, The First Hospital of Lanzhou University, Lanzhou, 730000, China
| | - Jingjing An
- Department of Ultrasound, The First Hospital of Lanzhou University, Lanzhou, 730000, China
| | - Long Deng
- Department of Ultrasound, The First Hospital of Lanzhou University, Lanzhou, 730000, China
| | - Jing Wang
- Department of Ultrasound, The First Hospital of Lanzhou University, Lanzhou, 730000, China
| | - Ruiling He
- Department of Ultrasound, Donggang Branch the First Hospital of Lanzhou University, Lanzhou, 730000, China.
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Yoon H, Kim J, Lim HJ, Lee MJ. Quantitative Liver Imaging in Children. Invest Radiol 2025; 60:60-71. [PMID: 39047265 DOI: 10.1097/rli.0000000000001101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2024]
Abstract
ABSTRACT In children and adults, quantitative imaging examinations determine the effectiveness of treatment for liver disease. However, pediatric liver disease differs in presentation from liver disease in adults. Children also needed to be followed for a longer period from onset and have less control of their bodies, showing more movement than adults during imaging examinations, which leads to a greater need for sedation. Thus, it is essential to appropriately tailor and accurately perform noninvasive imaging tests in these younger patients. This article is an overview of updated imaging techniques used to assess liver disease quantitatively in children. The common initial imaging study for diffuse liver disease in pediatric patients is ultrasound. In addition to preexisting echo analysis, newly developed attenuation imaging techniques have been introduced to evaluate fatty liver. Ultrasound elastography is also now actively used to evaluate liver conditions, and the broad age spectrum of the pediatric population requires caution to be taken even in the selection of probes. Magnetic resonance imaging (MRI) is another important imaging tool used to evaluate liver disease despite requiring sedation or anesthesia in young children because it allows quantitative analysis with sequences such as fat analysis and MR elastography. In addition to ultrasound and MRI, we review quantitative imaging methods specifically for fatty liver, Wilson disease, biliary atresia, hepatic fibrosis, Fontan-associated liver disease, autoimmune hepatitis, sinusoidal obstruction syndrome, and the transplanted liver. Lastly, concerns such as growth and motion that need to be addressed specifically for children are summarized.
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Affiliation(s)
- Haesung Yoon
- From the Department of Radiology, Gangnam Severance Hospital, Seoul, South Korea (H.Y.); Department of Radiology and Research Institute of Radiological Science, Yonsei University, College of Medicine, Seoul, South Korea (H.Y., J.K., H.J.L., M.-J.L.); and Department of Pediatric Radiology, Severance Children's Hospital, Seoul, South Korea (J.K., H.J.L., M.-J.L.)
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Coskun M, Sendur HN, Babayeva A, Cerit MN, Cerit ET, Yalcin MM, Altinova AE, Akturk M, Karakoc MA, Toruner FB. Quantitative ultrasound techniques and biochemical markers to assess liver steatosis and fibrosis in newly diagnosed acromegaly. J Endocrinol Invest 2024; 47:2823-2833. [PMID: 38709454 PMCID: PMC11473633 DOI: 10.1007/s40618-024-02384-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 04/25/2024] [Indexed: 05/07/2024]
Abstract
PURPOSE The liver is known to be protected from steatosis under the influence of high GH/IGF-1. Cytokeratin 18 (CK18) and insulin-like growth factor binding protein 7 (IGFBP7) increase in liver steatosis and fibrosis. The aim of this study was to use quantitative ultrasound techniques and biochemical markers to assess liver steatosis and liver fibrosis in newly diagnosed acromegaly. METHODS This single-center, cross-sectional study included 23 patients with newly diagnosed acromegaly and 46 age, sex, body mass index (BMI) and waist circumference (WC)-matched controls. Liver steatosis was assessed using tissue attenuation imaging (TAI), and stiffness, indicative of fibrosis, was assessed by shear wave elastography (SWE). Serum IGFBP7 and CK18 were studied by ELISA. RESULTS The acromegaly group had significantly lower liver steatosis (p = 0.006) and higher liver stiffness (p = 0.004), serum IGFBP7 (p = 0.048) and CK18 (p = 0.005) levels than the control group. The presence of fibrosis (p = 0.012) was significantly higher in the acromegaly group than in the control group. Moreover, CK18 was positively correlated with liver stiffness, WC, HOMA-IR, HbA1c, and triglyceride. In the acromegaly group, liver steatosis was negatively correlated with GH level. Stepwise multiple linear regression analysis revealed that BMI (p = 0.008) and CK18 (p = 0.015) were independent risk factors for increased liver stiffness. CONCLUSION This study showed that there was an increased presence of liver fibrosis independent of liver steatosis in newly diagnosed acromegaly. Serum CK18 appears to be a potential marker of increased liver fibrosis in acromegaly.
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Affiliation(s)
- M Coskun
- Department of Endocrinology and Metabolism, Faculty of Medicine, Gazi University, Ankara, Turkey.
| | - H N Sendur
- Department of Radiology, Faculty of Medicine, Gazi University, 06100, Ankara, Turkey
| | - A Babayeva
- Department of Endocrinology and Metabolism, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - M N Cerit
- Department of Radiology, Faculty of Medicine, Gazi University, 06100, Ankara, Turkey
| | - E T Cerit
- Department of Endocrinology and Metabolism, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - M M Yalcin
- Department of Endocrinology and Metabolism, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - A E Altinova
- Department of Endocrinology and Metabolism, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - M Akturk
- Department of Endocrinology and Metabolism, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - M A Karakoc
- Department of Endocrinology and Metabolism, Faculty of Medicine, Gazi University, Ankara, Turkey
| | - F B Toruner
- Department of Endocrinology and Metabolism, Faculty of Medicine, Gazi University, Ankara, Turkey
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Gbande P, Tchaou M, Djoko Makamto HD, Dagbe M, Sonhaye L, Agoda-Koussema LK, Adjenou K. Correlation between qualitative and semi-quantitative ultrasound assessment of diffuse fatty liver disease: A case-control study. ULTRASOUND (LEEDS, ENGLAND) 2024; 32:253-259. [PMID: 39493915 PMCID: PMC11528735 DOI: 10.1177/1742271x241241779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 01/08/2024] [Indexed: 11/05/2024]
Abstract
Objective To study the relationship between qualitative and semi-quantitative assessment of diffuse liver steatosis in ultrasound. Patients and Methods This was a case-control study, conducted in the Campus University Hospital Centre of Lome (Togo) over a 3-month period. It included 40 patients showing ultrasonographic signs of diffuse hepatic steatosis and 40 volunteers (healthy) whose echostructure and echogenicity of the hepatic parenchyma were normal. The B-mode sonographic grade of steatosis was compared with the hepatorenal echogenicity gradient and the ultrasound attenuation coefficient. Results The average body mass index in patients was 30.87 ± 4.65 kg/m2 versus 24.25 ± 4.30 kg/m2 in the healthy group (p < 0.00001). Hepatomegaly was observed in 57.5% of the patients versus 17.5% in the healthy group (p = 0.0005). The average hepatorenal echogenicity ratio was 1.18 ± 0.07 in patients versus 1.01 ± 0.03 in the healthy group (p < 0.00001). The average difference in hepatorenal echogenicity was 9.30 ± 3.41 dB in patients versus 1.52 ± 1.07 dB in the healthy group (p < 0.00001). The attenuation of ultrasound waves increased with the grade of steatosis, averaging 0.08 ± 0.23 dB/cm/MHz (ranging from -0.33 to 0.61 dB/cm/MHz) in patients versus -0.24 ± 0.21 (ranging from -0.69 to 0.19 dB/cm/MHz) in the healthy group (p < 0.00001). Conclusion Despite the advancements in new ultrasound technologies today, qualitative methods continue to be effective for the detection of hepatic steatosis and could prove useful in monitoring the effectiveness of hepatic steatosis treatment.
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Affiliation(s)
- Pihou Gbande
- Department of Radiology and Medical Imaging, Sokodé Regional Hospital Centre, Sokodé, Togo
| | - Mazamaesso Tchaou
- Department of Radiology and Medical Imaging, Sokodé Regional Hospital Centre, Sokodé, Togo
| | | | - Massaga Dagbe
- Department of Radiology and Medical Imaging, Kara University Hospital Centre, Kara, Togo
| | - Lantam Sonhaye
- Department of Radiology and Medical Imaging, Campus University Hospital Centre, Lomé, Togo
| | | | - Komlanvi Adjenou
- Department of Radiology and Medical Imaging, Campus University Hospital Centre, Lomé, Togo
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Wang M, Ma Y, Lan Y, Bai R, Yang L, Hou Y. Association of liver multi-parameter quantitative metrics determined by dual-layer spectral detector computed tomography (SDCT) with coronary plaque scores. Quant Imaging Med Surg 2024; 14:7392-7405. [PMID: 39429605 PMCID: PMC11485365 DOI: 10.21037/qims-24-53] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 08/15/2024] [Indexed: 10/22/2024]
Abstract
Background Hepatic steatosis is closely related to the occurrence and development of coronary plaques. Spectral detector computed tomography (SDCT) can provide more precise multiparameter quantitative parameters for hepatic steatosis. Hence, the purpose of this cross-sectional study was to explore the effect of quantitative liver metrics measured using SDCT on the extent and severity of coronary plaques. Methods In patients who underwent upper abdomen unenhanced SDCT and coronary computed tomography angiography, plaque extent and severity were assessed using segmental involvement score (SIS) and segmental stenosis score (SSS). Liver fat quantification was evaluated by polychromatic and virtual mono-energetic images at 40 and 70 kev, spectral attenuation curve slope, and effective atomic number (CT40 keV, CT70 kev, λHU, and Zeff, respectively). A logistic regression model evaluated the factors influencing high SIS and SSS. Results Enrolled patients (n=644) were divided into groups: low SIS (<5) (n=451), high SIS (≥5) (n=193), low SSS (<5) (n=461), and high SSS (≥5) (n=183). Zeff was more closely correlated with SIS (standard partial regression coefficient =-0.422, P<0.001) and SSS (standard partial regression coefficient =-0.346, P<0.001). Zeff was divided into four groups using interquartile intervals. Compared with the patients in the lowest quartile, those in the second [odds ratio (OR) =2.116, 95% confidence interval (CI): 1.134-3.949, P=0.018], third (OR =2.832, 95% CI: 1.461-5.491, P=0.002), and fourth (OR =3.584, 95% CI: 1.857-6.918, P<0.001) quartiles showed higher risk for high SIS. And correspondingly, the second (OR =1.933, 95% CI: 1.040-3.592, P=0.037), third (OR =2.900, 95% CI: 1.499-5.609, P=0.002), and fourth (OR =3.368, 95% CI: 1.743-6.510, P<0.001) quartiles showed higher risk for high SSS, especially in those who were <60 years old, male and had visceral adipose tissue/subcutaneous adipose tissue <1.18. Conclusions The SDCT-Zeff was an independent factor associated with high SIS and SSS. The quantification of liver fat may be useful for evaluating the risk and prognosis of coronary atherosclerosis.
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Affiliation(s)
- Min Wang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yue Ma
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu Lan
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ruobing Bai
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Linlin Yang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yang Hou
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
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11
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Hajibonabi F, Riedesel EL, Taylor SD, Linam LE, Alazraki AL, Zhang C, Khanna G. Ultrasound-estimated hepatorenal index: diagnostic performance and interobserver agreement for pediatric liver fat quantification. Pediatr Radiol 2024; 54:1653-1660. [PMID: 39136769 DOI: 10.1007/s00247-024-06021-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 07/30/2024] [Accepted: 07/31/2024] [Indexed: 09/07/2024]
Abstract
BACKGROUND Semiquantitative and quantitative sonographic techniques have the potential for screening and surveillance of children at risk of nonalcoholic fatty liver disease. OBJECTIVE To determine diagnostic performance and interobserver agreement of hepatorenal index (HRI) for pediatric ultrasound-based liver fat quantification. MATERIALS AND METHODS In an institutional review board (IRB)-approved retrospective study (April 2014 to April 2023), children (< 18 years) with clinically performed magnetic resonance imaging (MRI) scans for liver fat quantification were assessed. Inclusion criteria required availability of abdominal ultrasound within 3 months of quantitative MRI. Three blinded readers subjectively assessed for sonographic hepatic steatosis and calculated HRI. MRI proton density fat fraction (PDFF) was the reference standard. Interobserver agreement, correlation with PDFF, and optimal HRI (using ROC analysis) values were analyzed. The significance level was set at p < 0.05. RESULTS A total of 41 patients (25 male) with median (interquartile range (IQR)) age of 13 (10-15) years were included. Median (IQR) MRI PDFF was 11.30% (2.70-17.95%). Hepatic steatosis distribution by MRI PDFF included grade 0 (34%), grade 1 (15%), grade 2 (22%), and grade 3 (29%) patients. Intraclass correlation coefficient for HRI among the three readers was 0.61 (95% CI 0.43-0.75) (p < 0.001). Moderate correlation was observed between manually estimated HRI and PDFF for each reader (r = 0.62, 0.67, and 0.67; p < 0.001). Optimal HRI cutoff was found to be 1.99 to diagnose hepatic steatosis (sensitivity 89%, specificity 93%). Median (IQR) HRI for each MRI grade of hepatic steatosis (0-4) was as follows: 1.2 (1.1-1.5), 2.6 (1.1-3.3), 3.6 (2.6-5.4), 5.6 (2.6-10.9), respectively (p < 0.001). CONCLUSION Ultrasound-estimated HRI has moderate interobserver agreement and moderate correlation with MRI-derived PDFF. HRI of 1.99 maximizes accuracy for identifying pediatric liver fat.
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Affiliation(s)
- Farid Hajibonabi
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA.
| | - Erica L Riedesel
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Susan D Taylor
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Leann E Linam
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Adina L Alazraki
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
| | - Chao Zhang
- Biostatistics Shared Resource, Winship Cancer Institute of Emory University, Atlanta, USA
| | - Geetika Khanna
- Department of Radiology & Imaging Sciences, Emory University and Children's Healthcare of Atlanta, 1405 Clifton Road NE, Atlanta, GA, 30322, USA
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12
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Naganuma H, Ishida H, Nagai H, Uno A. Contrast-Enhanced Sonography of the Liver: How to Avoid Artifacts. Diagnostics (Basel) 2024; 14:1817. [PMID: 39202305 PMCID: PMC11353835 DOI: 10.3390/diagnostics14161817] [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: 06/24/2024] [Revised: 08/17/2024] [Accepted: 08/19/2024] [Indexed: 09/03/2024] Open
Abstract
Contrast-enhanced sonography (CEUS) is a very important diagnostic imaging tool in clinical settings. However, it is associated with possible artifacts, such as B-mode US-related artifacts. Sufficient knowledge of US physics and these artifacts is indispensable to avoid the misinterpretation of CEUS images. This review aims to explain the basic physics of CEUS and the associated artifacts and to provide some examples to avoid them. This review includes problems related to the frame rate, scanning modes, and various artifacts encountered in daily CEUS examinations. Artifacts in CEUS can be divided into two groups: (1) B-mode US-related artifacts, which form the background of the CEUS image, and (2) artifacts that are specifically related to the CEUS method. The former includes refraction, reflection, reverberation (multiple reflections), attenuation, mirror image, and range-ambiguity artifacts. In the former case, the knowledge of B-mode US is sufficient to read the displayed artifactual image. Thus, in this group, the most useful artifact avoidance strategy is to use the reference B-mode image, which allows for a simultaneous comparison between the CEUS and B-mode images. In the latter case, CEUS-specific artifacts include microbubble destruction artifacts, prolonged heterogeneous accumulation artifacts, and CEUS-related posterior echo enhancement; these require an understanding of the mechanism of their appearance in CEUS images for correct image interpretation. Thus, in this group, the most useful artifact avoidance strategy is to confirm the phenomenon's instability by changing the examination conditions, including the frequency, depth, and other parameters.
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Affiliation(s)
- Hiroko Naganuma
- Department of Gastroenterology, Yokote Municipal Hospital, Yokote 013-8602, Japan
| | - Hideaki Ishida
- Department of Gastroenterology, Akita Red Cross Hospital, Akita 010-1495, Japan;
| | - Hiroshi Nagai
- New Generation Imaging Laboratory, Tokyo 168-0065, Japan;
| | - Atushi Uno
- Department of Gastroenterology, Ohmori Municipal Hospital, Yokote 013-0525, Japan;
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13
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Pan Y, Wang X, Qiang Y, Wang N, Liu R, Yang G, Zhang Z, He X, Yu Y, Zheng H, Qiu W. A New Method of Plane-Wave Ultrasound Imaging Based on Reverse Time Migration. IEEE Trans Biomed Eng 2024; 71:1628-1639. [PMID: 38133968 DOI: 10.1109/tbme.2023.3346194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2023]
Abstract
Coherent plane-wave compounding technique enables rapid ultrasound imaging with comparable image quality to traditional B-mode imaging that relies on focused beam transmission. However, existing methods assume homogeneity in the imaged medium, neglecting the heterogeneity in sound velocities and densities present in real tissues, resulting in noise reverberation. This study introduces the Reverse Time Migration (RTM) method for ultrasound plane-wave imaging to overcome this limitation, which is combined with a method for estimating the speed of sound in layered media. Simulation results in a homogeneous background demonstrate that RTM reduces side lobes and grating lobes by approximately 30 dB, enhancing the contrast-to-noise ratio by 20% compared to conventional delay and sum (DAS) beamforming. Moreover, RTM achieves superior imaging outcomes with fewer compounding angles. The lateral resolution of the RTM with 5-9 angle compounding is able to achieve the effectiveness of the DAS method with 15-19 angle compounding, and the CNR of the RTM with 11-angle compounding is almost the same as that of the DAS with 21-angle compounding. In a heterogeneous background, experimental simulations and in vitro wire phantom experiments confirm RTM's capability to correct depth imaging, focusing reflected waves on point targets. In vitro porcine tissue experiments enable accurate imaging of layer interfaces by estimating the velocities of multiple layers containing muscle and fat. The proposed imaging procedure optimizes velocity estimation in complex media, compensates for the impact of velocity differences, provides more reliable imaging results.
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14
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Hänni O, Ruby L, Paverd C, Frauenfelder T, Rominger MB, Martin A. Comparison of Ultrasound Attenuation Imaging Using a Linear versus a Conventional Convex Probe: A Volunteer Study. Diagnostics (Basel) 2024; 14:886. [PMID: 38732301 PMCID: PMC11083206 DOI: 10.3390/diagnostics14090886] [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: 03/14/2024] [Revised: 04/15/2024] [Accepted: 04/20/2024] [Indexed: 05/13/2024] Open
Abstract
The study aimed to investigate the feasibility of attenuation imaging (ATI) measurements using a linear probe on healthy volunteers and compare measurements with the conventional convex probe. Attenuation imaging measurements of the liver tissue were taken using ultrasound with a convex and a linear probe in 33 volunteers by two examining doctors, and the measurements were repeated 4-5 weeks later by one of them. The ATI values for the linear probe were in the range of the values for the convex probe for both examiners. Measurements did not change significantly for 32 out of 33 volunteers after 4-5 weeks when using the linear probe. The size of the region of interest (ROI) only impacted the ATI values for the convex probe; it did not affect the values taken with the linear probe. Healthy volunteers were measured, and their attenuation values were compared to those from a convex probe, commonly used in steatosis evaluation. When both probes were positioned in the same liver area, they showed good agreement in attenuation values, though depth significantly affected the measurements, with both probes providing different values at different depths. The study's results aligned with previous research using the same system. Operator A and B's results were compared, demonstrating similar ranges of values for both probes. The linear probe has been demonstrated to allow for superficial measurements and attain ATI values in line with that of the convex probe in the liver.
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Affiliation(s)
- Olivia Hänni
- Faculty of Medicine, University of Zurich, Dekanat Pestalozzistrasse 3, 8032 Zurich, Switzerland
| | - Lisa Ruby
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA (T.F.)
| | - Catherine Paverd
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA (T.F.)
| | - Thomas Frauenfelder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA (T.F.)
| | - Marga B. Rominger
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA (T.F.)
| | - Alexander Martin
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA (T.F.)
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15
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Baek J, Qin SS, Prieto PA, Parker KJ. H-Scan Discrimination for Tumor Microenvironmental Heterogeneity in Melanoma. ULTRASOUND IN MEDICINE & BIOLOGY 2024; 50:268-276. [PMID: 37993356 PMCID: PMC10794040 DOI: 10.1016/j.ultrasmedbio.2023.10.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 10/24/2023] [Accepted: 10/28/2023] [Indexed: 11/24/2023]
Abstract
OBJECTIVE Melanoma is a form of malignant skin cancer that exhibits significant inter-tumoral differences in the tumor microenvironment (TME) secondary to genetic mutations. The heterogeneity may be subtle but can complicate the treatment of metastatic melanoma, contributing to a high mortality rate. Therefore, developing an accurate and non-invasive procedure to discriminate microenvironmental heterogeneity to facilitate therapy selection is an important goal. METHODS In vivo murine melanoma models that recapitulate human disease using synchronous implanted YUMM 1.7 (Yale University Mouse Melanoma) and YUMMER 1.7 (Yale University Mouse Melanoma Exposed to Radiation) murine melanoma lines were investigated. Mice were treated with antibodies to modulate the immune response and longitudinally scanned with ultrasound (US). US radiofrequency data were processed using the H-scan analysis, attenuation estimation and B-mode processing to extract five US features. The measures were used to compare different TMEs (YUMMER vs. YUMM) and responses to immunomodulatory therapies with CD8 depletion or programmed cell death protein 1 (PD-1) inhibition. RESULTS Multiparametric analysis produced a combined H-scan parameter, resolving significant differences (i) between untreated YUMMER and YUMM and (ii) between untreated, PD-1-treated and CD8-treated YUMMER. However, more importantly, the B-mode and attenuation measures failed to differentiate YUMMER and YUMM and to monitor treatment responses, indicating that H-scan is required to differentiate subtle differences within the TME. CONCLUSION We anticipate that the H-scan analysis could discriminate heterogeneous melanoma metastases and guide diagnosis and treatment selection, potentially reducing the need for invasive biopsies or immunologic procedures.
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Affiliation(s)
- Jihye Baek
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA
| | - Shuyang S Qin
- Department of Microbiology & Immunology, University of Rochester School of Medicine & Dentistry, Rochester, NY, USA
| | - Peter A Prieto
- Department of Surgery, University of Rochester Medical Center, Rochester, NY, USA
| | - Kevin J Parker
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA.
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16
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Hänni O, Ruby L, Paverd C, Frauenfelder T, Rominger MB, Martin A. Confounders of Ultrasound Attenuation Imaging in a Linear Probe Using the Canon Aplio i800 System: A Phantom Study. Diagnostics (Basel) 2024; 14:271. [PMID: 38337786 PMCID: PMC10855333 DOI: 10.3390/diagnostics14030271] [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: 12/07/2023] [Revised: 01/17/2024] [Accepted: 01/19/2024] [Indexed: 02/12/2024] Open
Abstract
There have been studies showing attenuation imaging (ATI) with ultrasound as an approach to diagnose liver diseases such as steatosis or cirrhosis. So far, this technique has only been used on a convex probe. The goal of the study was to investigate the feasibility of ATI measurements using the linear array on a canon Aplio i800 scanner on certified phantoms. Three certified liver tissue attenuation phantoms were measured in five different positions using a linear probe. The effects of positioning and depth were explored and compared. The values were compared to the certified expected value for each phantom as well as the different measurement values for each measurement position. The ATI measurements on phantoms showed significant effect for the different probe positions and region of interest (ROI) depths. Values taken in the center with the probe perpendicular to the phantom were closest to certified values. Median values at 2.5-4.5 cm depth for phantoms 1 and 2 and 0.5-2.5 cm for phantom 3 were comparable with certified values. Measurements taken at a depth greater than 6 cm in any position were the least representative of the certified values (p-value < 0.01) and had the widest range throughout the different sessions. ATI measurements can be performed with the linear probe in phantoms; however, careful consideration should be given to depth dependency, as it can significantly affect measurement values. Remaining measurements at various depths within the 0.5-6.0 cm range showed deviation from the certified values of approximately 25%.
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Affiliation(s)
- Olivia Hänni
- Faculty of Medicine, University of Zurich, Dekanat Pestalozzistrasse 3, 8032 Zurich, Switzerland
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland (M.B.R.)
| | - Lisa Ruby
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland (M.B.R.)
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Catherine Paverd
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland (M.B.R.)
| | - Thomas Frauenfelder
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland (M.B.R.)
| | - Marga B. Rominger
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland (M.B.R.)
| | - Alexander Martin
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland (M.B.R.)
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17
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Chen B, Lu Q, Hu B, Sun D, Ying T. Protocol of quantitative ultrasound techniques for noninvasive assessing of hepatic steatosis after bariatric surgery. Front Surg 2024; 10:1244199. [PMID: 38239667 PMCID: PMC10794322 DOI: 10.3389/fsurg.2023.1244199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 11/27/2023] [Indexed: 01/22/2024] Open
Abstract
Introduction Roux-en-Y gastric bypass surgery can effectively improve steatosis, necroinflammatory activity, and hepatic fibrosis in individuals diagnosed with morbid obesity or nonalcoholic steatohepatitis (NASH). Common methods such as body mass index (BMI) to evaluate the postoperative effect of clinical bariatric surgery cannot differentiate subcutaneous fats from visceral fats and muscles. Several Quantitative ultrasound (QUS)-based approaches have been developed to quantify hepatic steatosis. QUS techniques (tissue attenuation imaging (TAI), tissue scatter distribution imaging (TSI)) from radio frequency (RF) data analysis as a means for the detection and grading of hepatic steatosis has been posited as an objective and noninvasive approach. The implementation and standardization of QUS techniques (TAI, TSI) in assessing hepatic steatosis quantitatively after bariatric surgery is of high-priority. Our study is aimed to assess hepatic steatosis with QUS techniques (TAI, TSI) in morbidly obese individuals before and after bariatric surgery, and to compare with anthropometric measurements, laboratory assessments and other imaging methods. Methods and analysis The present investigation, a self-discipline examination of navigational capacity devoid of visual cues, is designed as a single-site, forward-looking evaluation of efficacy with the imprimatur of the institutional review board. The duration of the study has been provisionally determined to span from 1 January 2023 through 31 December 2025. Our cohort shall encompass one hundred participants, who was scheduled to undergo Roux-en-Y gastric bypass (RYGB) at Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. All patients will undergo anthropometric measurements, blood-based biochemical analyses, ultrasonic examination and magnetic resonance imaging proton density fat fraction (MRI-PDFF). The primary endpoint is the analysis of evaluating the efficacy of QUS techniques assessing hepatic steatosis compared to other methods before and after bariatric surgery. Results Prior to the fomal study, we recruited 21 obese Chinese participants who received ultrasonic examination (TAI, TSI) and MRI-PDFF. AC-TAI showed moderate correlations with MRI-PDFF (adjusted r = 0.632; P < 0.05). For MRI-PDFF ≥10%, SC-TSI showed moderate correlations with MRI-PDFF (adjusted r = 0.677; P < 0.05). Conclusion Our pre-experiment results signified that using QUS techniques for postoperative evaluation of bariatric surgery is promising. QUS techniques will be signed a widespread availability, real-time functionality, and low-cost approach for assessing hepatic steatosis before and after bariatric surgery in obese individuals, thus is capable for subsequent scale-up liver fat quantification. Ethics and dissemination The present research endeavor has been bestowed with the imprimatur of the Ethics Committee of the Hospital, as indicated by its Approval Number: 2023-KY-015. In due course, upon completion of the study, we intend to disseminate our findings by publishing them in a suitable academic journal, thereby facilitating their widespread utilization. Registration The trial is duly registered with the Chinese Clinical Trial Registry, and with a unique Trial Registration Number, ChiCTR2300069892, approved on March 28, 2023.
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Affiliation(s)
- Bin Chen
- Department of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Institute of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qijie Lu
- Department of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Institute of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bing Hu
- Department of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Institute of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Di Sun
- Department of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Institute of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tao Ying
- Department of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Institute of Ultrasound in Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Boeriu A, Dobru D, Fofiu C. Non-Invasive Diagnostic of NAFLD in Type 2 Diabetes Mellitus and Risk Stratification: Strengths and Limitations. Life (Basel) 2023; 13:2262. [PMID: 38137863 PMCID: PMC10744403 DOI: 10.3390/life13122262] [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: 10/07/2023] [Revised: 10/26/2023] [Accepted: 11/25/2023] [Indexed: 12/24/2023] Open
Abstract
The progressive potential of liver damage in type 2 diabetes mellitus (T2DM) towards advanced fibrosis, end-stage liver disease, and hepatocarcinoma has led to increased concern for quantifying liver injury and individual risk assessment. The combination of blood-based markers and imaging techniques is recommended for the initial evaluation in NAFLD and for regular monitoring to evaluate disease progression. Continued development of ultrasonographic and magnetic resonance imaging methods for accurate quantification of liver steatosis and fibrosis, as well as promising tools for the detection of high-risk NASH, have been noted. In this review, we aim to summarize available evidence regarding the usefulness of non-invasive methods for the assessment of NAFLD in T2DM. We focus on the power and limitations of various methods for diagnosis, risk stratification, and patient monitoring that support their implementation in clinical setting or in research field.
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Affiliation(s)
- Alina Boeriu
- Gastroenterology Department, University of Medicine Pharmacy, Sciences, and Technology “George Emil Palade” Targu Mures, 540142 Targu Mures, Romania;
- Gastroenterology Department, Mures County Clinical Hospital, 540103 Targu Mures, Romania
| | - Daniela Dobru
- Gastroenterology Department, University of Medicine Pharmacy, Sciences, and Technology “George Emil Palade” Targu Mures, 540142 Targu Mures, Romania;
- Gastroenterology Department, Mures County Clinical Hospital, 540103 Targu Mures, Romania
| | - Crina Fofiu
- Gastroenterology Department, University of Medicine Pharmacy, Sciences, and Technology “George Emil Palade” Targu Mures, 540142 Targu Mures, Romania;
- Internal Medicine Department, Bistrita County Clinical Hospital, 420094 Bistrita, Romania
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Huang X, Lian YE, Qiu L, Yu X, Miao J, Zhang S, Zhang Z, Zhang X, Chen J, Bai Y, Li L. Quantitative Assessment of Hepatic Steatosis Using Label-Free Multiphoton Imaging and Customized Image Processing Program. J Transl Med 2023; 103:100223. [PMID: 37517702 DOI: 10.1016/j.labinv.2023.100223] [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: 05/07/2023] [Revised: 07/17/2023] [Accepted: 07/24/2023] [Indexed: 08/01/2023] Open
Abstract
Nonalcoholic fatty liver disease is rapidly becoming one of the most common causes of chronic liver disease worldwide and is the leading cause of liver-related morbidity and mortality. A quantitative assessment of the degree of steatosis would be more advantageous for diagnostic evaluation and exploring the patterns of disease progression. Here, multiphoton microscopy, based on the second harmonic generation and 2-photon excited fluorescence, was used to label-free image the samples of nonalcoholic fatty liver. Imaging results confirm that multiphoton microscopy is capable of directly visualizing important pathologic features such as normal hepatocytes, hepatic steatosis, Mallory bodies, necrosis, inflammation, collagen deposition, microvessel, and so on and is a reliable auxiliary tool for the diagnosis of nonalcoholic fatty liver disease. Furthermore, we developed an image segmentation algorithm to simultaneously assess hepatic steatosis and fibrotic changes, and quantitative results reveal that there is a correlation between the degree of steatosis and collagen content. We also developed a feature extraction program to precisely display the spatial distribution of hepatocyte steatosis in tissues. These studies may be beneficial for a better clinical understanding of the process of steatosis as well as for exploring possible therapeutic targets.
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Affiliation(s)
- Xingxin Huang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Yuan-E Lian
- Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Lida Qiu
- College of Physics and Electronic Information Engineering, Minjiang University, Fuzhou, China
| | - XunBin Yu
- Department of Pathology, Fujian Provincial Hospital, Fuzhou, China
| | - Jikui Miao
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Shichao Zhang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Zheng Zhang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Xiong Zhang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Jianxin Chen
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Yannan Bai
- Department of Hepatobiliary and Pancreatic Surgery, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.
| | - Lianhuang Li
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China.
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20
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Şendur HN, Cerit MN, Fatullayeva T, Erdal ZS, Karabörk Kılıç AC, Özhan Oktar S. Do Ultrasound Based Quantitative Hepatic Fat Content Measurements Have Differences Between Respiratory Phases? Acad Radiol 2023; 30:1832-1837. [PMID: 36628802 DOI: 10.1016/j.acra.2022.12.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/10/2022] [Accepted: 12/13/2022] [Indexed: 01/11/2023]
Abstract
RATIONALE AND OBJECTIVES The recently developed ultrasound based tools using attenuation coefficient (AC) and scatter distribution coefficient (SDC) values can be used to quantify hepatic fat content in patients with non-alcoholic fatty liver disease (NAFLD). However, currently the impact of respiratory phase on these measurements is not known. The purpose of this study is to compare AC and SDC measurements acquired at peak inspiration and end expiration phases. MATERIALS AND METHODS AC and SDC measurements were obtained in 50 patients with NAFLD. Tissue Attenuation Imaging (TAI) and Tissue Scatter Distribution Imaging (TSI) tools were utilized to measure AC and SDC values, respectively. Five measurements were performed at respiratory phases using TAI and TSI tools and the median values were noted. Subgroup analyses were performed and Wilcoxon signed rank test was used for comparison of the measurements. RESULTS The median values of the AC measurements at peak inspiration and end expiration phases were 0.87 dB/cm/MHz and 0.89 dB/cm/MHz, respectively. The median values of the SDC measurements at peak inspiration and end expiration phases were 97.91 and 96.62, respectively. There were no statistically significant differences in AC and SDC measurements between the respiratory phases except for AC measurements in BMI <30 kg/m2 subgroup. CONCLUSION Our results revealed that respiratory phases have no impact on SDC measurements. However, while the AC measurements in BMI ≥30 kg/m2 subgroup showed no significant difference, there was a significant difference in AC measurements in BMI <30 kg/m2 subgroup between the respiratory phases.
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Affiliation(s)
- Halit Nahit Şendur
- Department of Radiology, Gazi University Faculty of Medicine, Yenimahalle, Ankara, Turkey.
| | - Mahi N Cerit
- Department of Radiology, Gazi University Faculty of Medicine, Yenimahalle, Ankara, Turkey
| | - Turkana Fatullayeva
- Department of Radiology, Gazi University Faculty of Medicine, Yenimahalle, Ankara, Turkey
| | - Zeynep S Erdal
- Department of Radiology, Gazi University Faculty of Medicine, Yenimahalle, Ankara, Turkey
| | | | - Suna Özhan Oktar
- Department of Radiology, Gazi University Faculty of Medicine, Yenimahalle, Ankara, Turkey
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21
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Fetzer DT, Pierce TT, Robbin ML, Cloutier G, Mufti A, Hall TJ, Chauhan A, Kubale R, Tang A. US Quantification of Liver Fat: Past, Present, and Future. Radiographics 2023; 43:e220178. [PMID: 37289646 DOI: 10.1148/rg.220178] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Fatty liver disease has a high and increasing prevalence worldwide, is associated with adverse cardiovascular events and higher long-term medical costs, and may lead to liver-related morbidity and mortality. There is an urgent need for accurate, reproducible, accessible, and noninvasive techniques appropriate for detecting and quantifying liver fat in the general population and for monitoring treatment response in at-risk patients. CT may play a potential role in opportunistic screening, and MRI proton-density fat fraction provides high accuracy for liver fat quantification; however, these imaging modalities may not be suited for widespread screening and surveillance, given the high global prevalence. US, a safe and widely available modality, is well positioned as a screening and surveillance tool. Although well-established qualitative signs of liver fat perform well in moderate and severe steatosis, these signs are less reliable for grading mild steatosis and are likely unreliable for detecting subtle changes over time. New and emerging quantitative biomarkers of liver fat, such as those based on standardized measurements of attenuation, backscatter, and speed of sound, hold promise. Evolving techniques such as multiparametric modeling, radiofrequency envelope analysis, and artificial intelligence-based tools are also on the horizon. The authors discuss the societal impact of fatty liver disease, summarize the current state of liver fat quantification with CT and MRI, and describe past, currently available, and potential future US-based techniques for evaluating liver fat. For each US-based technique, they describe the concept, measurement method, advantages, and limitations. © RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.
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Affiliation(s)
- David T Fetzer
- From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.)
| | - Theodore T Pierce
- From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.)
| | - Michelle L Robbin
- From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.)
| | - Guy Cloutier
- From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.)
| | - Arjmand Mufti
- From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.)
| | - Timothy J Hall
- From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.)
| | - Anil Chauhan
- From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.)
| | - Reinhard Kubale
- From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.)
| | - An Tang
- From the Department of Radiology (D.T.F.) and Department of Internal Medicine, Division of Digestive and Liver Diseases (A.M.), UT Southwestern Medical Center, 5323 Harry Hines Blvd, E6-230-BF, Dallas, TX 75390-9316; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (T.T.P.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (M.L.R.); Departments of Radiology and Biomedical Engineering, Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center, Montréal, Quebec, Canada (G.C.); Department of Medical Physics, University of Wisconsin, Madison, Wis (T.J.H.); Department of Radiology, University of Kansas Medical Center, Kansas City, Kan (A.C.); Department of Diagnostic and Interventional Radiology, University Hospital Homburg/Saar, Homburg, Germany (R.K.); and Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM) and Université de Montréal, Montréal, Quebec, Canada (A.T.)
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22
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Guglielmo FF, Barr RG, Yokoo T, Ferraioli G, Lee JT, Dillman JR, Horowitz JM, Jhaveri KS, Miller FH, Modi RY, Mojtahed A, Ohliger MA, Pirasteh A, Reeder SB, Shanbhogue K, Silva AC, Smith EN, Surabhi VR, Taouli B, Welle CL, Yeh BM, Venkatesh SK. Liver Fibrosis, Fat, and Iron Evaluation with MRI and Fibrosis and Fat Evaluation with US: A Practical Guide for Radiologists. Radiographics 2023; 43:e220181. [PMID: 37227944 DOI: 10.1148/rg.220181] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Quantitative imaging biomarkers of liver disease measured by using MRI and US are emerging as important clinical tools in the management of patients with chronic liver disease (CLD). Because of their high accuracy and noninvasive nature, in many cases, these techniques have replaced liver biopsy for the diagnosis, quantitative staging, and treatment monitoring of patients with CLD. The most commonly evaluated imaging biomarkers are surrogates for liver fibrosis, fat, and iron. MR elastography is now routinely performed to evaluate for liver fibrosis and typically combined with MRI-based liver fat and iron quantification to exclude or grade hepatic steatosis and iron overload, respectively. US elastography is also widely performed to evaluate for liver fibrosis and has the advantage of lower equipment cost and greater availability compared with those of MRI. Emerging US fat quantification methods can be performed along with US elastography. The author group, consisting of members of the Society of Abdominal Radiology (SAR) Liver Fibrosis Disease-Focused Panel (DFP), the SAR Hepatic Iron Overload DFP, and the European Society of Radiology, review the basics of liver fibrosis, fat, and iron quantification with MRI and liver fibrosis and fat quantification with US. The authors cover technical requirements, typical case display, quality control and proper measurement technique and case interpretation guidelines, pitfalls, and confounding factors. The authors aim to provide a practical guide for radiologists interpreting these examinations. © RSNA, 2023 See the invited commentary by Ronot in this issue. Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
- Flavius F Guglielmo
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Richard G Barr
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Takeshi Yokoo
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Giovanna Ferraioli
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - James T Lee
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Jonathan R Dillman
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Jeanne M Horowitz
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Kartik S Jhaveri
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Frank H Miller
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Roshan Y Modi
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Amirkasra Mojtahed
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Michael A Ohliger
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Ali Pirasteh
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Scott B Reeder
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Krishna Shanbhogue
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Alvin C Silva
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Elainea N Smith
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Venkateswar R Surabhi
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Bachir Taouli
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Christopher L Welle
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Benjamin M Yeh
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
| | - Sudhakar K Venkatesh
- From the Department of Radiology, Thomas Jefferson University, 132 S 10th St, Philadelphia, PA 19107 (F.F.G.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); Department of Radiology and Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Tex (T.Y.); Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy (G.F.); Department of Radiology, University of Kentucky, Lexington, Ky (J.T.L.); Department of Radiology, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio (J.R.D.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (J.M.H., F.H.M.); Joint Department of Medical Imaging, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.S.J.); Department of Radiology, ChristianaCare, Newark, Del (R.Y.M.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (A.M.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, Calif (M.A.O., B.M.Y.); Departments of Radiology and Medical Physics (A.P.) and Departments of Radiology, Medical Physics, Biomedical Engineering, Medicine, and Emergency Medicine (S.B.R.), University of Wisconsin, Madison, Wis; Department of Radiology, NYU Langone Health, New York, NY (K.S.); Department of Radiology, Mayo Clinic, Phoenix, Ariz (A.C.S.); Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (E.N.S.); Department of Radiology, University of Texas MD Anderson Cancer Center, Houston, Tex (V.R.S.); Department of Diagnostic, Molecular and Interventional Radiology, BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY (B.T.); and Department of Radiology, Mayo Clinic, Rochester, Minn (C.L.W., S.K.V.)
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Timaná J, Chahuara H, Basavarajappa L, Basarab A, Hoyt K, Lavarello R. Simultaneous imaging of ultrasonic relative backscatter and attenuation coefficients for quantitative liver steatosis assessment. Sci Rep 2023; 13:8898. [PMID: 37264043 DOI: 10.1038/s41598-023-33964-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 04/21/2023] [Indexed: 06/03/2023] Open
Abstract
Prevalence of liver disease is continuously increasing and nonalcoholic fatty liver disease (NAFLD) is the most common etiology. We present an approach to detect the progression of liver steatosis based on quantitative ultrasound (QUS) imaging. This study was performed on a group of 55 rats that were subjected to a control or methionine and choline deficient (MCD) diet known to induce NAFLD. Ultrasound (US) measurements were performed at 2 and 6 weeks. Thereafter, animals were humanely euthanized and livers excised for histological analysis. Relative backscatter and attenuation coefficients were simultaneously estimated from the US data and envelope signal-to-noise ratio was calculated to train a regression model for: (1) fat fraction percentage estimation and (2) performing classification according to Brunt's criteria in grades (0 <5%; 1, 5-33%; 2, >33-66%; 3, >66%) of liver steatosis. The trained regression model achieved an [Formula: see text] of 0.97 (p-value < 0.01) and a RMSE of 3.64. Moreover, the classification task reached an accuracy of 94.55%. Our results suggest that in vivo QUS is a promising noninvasive imaging modality for the early assessment of NAFLD.
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Affiliation(s)
- José Timaná
- Laboratorio de Imágenes Médicas, Pontificia Universidad Católica del Perú, Lima, Peru
| | - Hector Chahuara
- Laboratorio de Imágenes Médicas, Pontificia Universidad Católica del Perú, Lima, Peru
| | - Lokesh Basavarajappa
- Department of Bioengineering, University of Texas at Dallas, Richardson, TX, USA
| | - Adrian Basarab
- INSA-Lyon, UCBL, CNRS, Inserm, CREATIS UMR 5220 U1294, Université de Lyon, Villeurbanne, France
| | - Kenneth Hoyt
- Department of Bioengineering, University of Texas at Dallas, Richardson, TX, USA
| | - Roberto Lavarello
- Laboratorio de Imágenes Médicas, Pontificia Universidad Católica del Perú, Lima, Peru.
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Jang W, Song JS. Non-Invasive Imaging Methods to Evaluate Non-Alcoholic Fatty Liver Disease with Fat Quantification: A Review. Diagnostics (Basel) 2023; 13:diagnostics13111852. [PMID: 37296703 DOI: 10.3390/diagnostics13111852] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 05/17/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023] Open
Abstract
Hepatic steatosis without specific causes (e.g., viral infection, alcohol abuse, etc.) is called non-alcoholic fatty liver disease (NAFLD), which ranges from non-alcoholic fatty liver (NAFL) to non-alcoholic steatohepatitis (NASH), fibrosis, and NASH-related cirrhosis. Despite the usefulness of the standard grading system, liver biopsy has several limitations. In addition, patient acceptability and intra- and inter-observer reproducibility are also concerns. Due to the prevalence of NAFLD and limitations of liver biopsies, non-invasive imaging methods such as ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) that can reliably diagnose hepatic steatosis have developed rapidly. US is widely available and radiation-free but cannot examine the entire liver. CT is readily available and helpful for detection and risk classification, significantly when analyzed using artificial intelligence; however, it exposes users to radiation. Although expensive and time-consuming, MRI can measure liver fat percentage with magnetic resonance imaging proton density fat fraction (MRI-PDFF). Specifically, chemical shift-encoded (CSE)-MRI is the best imaging indicator for early liver fat detection. The purpose of this review is to provide an overview of each imaging modality with an emphasis on the recent progress and current status of liver fat quantification.
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Affiliation(s)
- Weon Jang
- Department of Radiology, Jeonbuk National University Medical School and Hospital, 20 Geonji-ro, Deokjin-gu, Jeonju 54907, Jeonbuk, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju 54907, Jeonbuk, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju 54907, Jeonbuk, Republic of Korea
| | - Ji Soo Song
- Department of Radiology, Jeonbuk National University Medical School and Hospital, 20 Geonji-ro, Deokjin-gu, Jeonju 54907, Jeonbuk, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju 54907, Jeonbuk, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju 54907, Jeonbuk, Republic of Korea
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25
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Yan SY, Yang YW, Jiang XY, Hu S, Su YY, Yao H, Hu CH. Fat quantification: Imaging methods and clinical applications in cancer. Eur J Radiol 2023; 164:110851. [PMID: 37148843 DOI: 10.1016/j.ejrad.2023.110851] [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: 02/24/2023] [Revised: 04/19/2023] [Accepted: 04/24/2023] [Indexed: 05/08/2023]
Abstract
Recently, the study of the relationship between lipid metabolism and cancer has evolved. The characteristics of intratumoral and peritumoral fat are distinct and changeable during cancer development. Subcutaneous and visceral adipose tissue are also associated with cancer prognosis. In non-invasive imaging, fat quantification parameters such as controlled attenuation parameter, fat volume fraction, and proton density fat fraction from different imaging methods complement conventional images by providing concrete fat information. Therefore, measuring the changes of fat content for further understanding of cancer characteristics has been applied in both research and clinical settings. In this review, the authors summarize imaging advances in fat quantification and highlight their clinical applications in cancer precaution, auxiliary diagnosis and classification, therapy response monitoring, and prognosis.
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Affiliation(s)
- Suo Yu Yan
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Yi Wen Yang
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Xin Yu Jiang
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Su Hu
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China
| | - Yun Yan Su
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China.
| | - Hui Yao
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China; Department of General Surgery, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China.
| | - Chun Hong Hu
- Department of Radiology, The First Affiliated Hospital to Soochow University, Suzhou 215006, PR China.
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Şendur HN, Cerit MN, Ibrahimkhanli N, Şendur AB, Özhan Oktar S. Interobserver Variability in Ultrasound-Based Liver Fat Quantification. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2023; 42:833-841. [PMID: 35778902 DOI: 10.1002/jum.16048] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/28/2022] [Accepted: 06/10/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES To assess interobserver variability in ultrasound-based quantitative liver fat content measurements and to determine how much time these quantitative ultrasound (QUS) techniques require. METHODS One hundred patients with known or suspected of having nonalcoholic fatty liver disease were included in this prospective study. Two observers who were blinded to each other measurements performed tissue attenuation imaging (TAI) and tissue scatter distribution imaging (TSI) techniques independently. Both observers assessed hepatic steatosis visually and obtained 5 measurements for each QUS technique and the median values of the measurements were recorded. Spearman's correlation test was used to assess the correlation between QUS measurements and visual hepatic stetaosis grades. Intraclass correlation coefficient (ICC) test was used to assess interobserver variability in QUS measurements. RESULTS The median values of TAI measurements for the observers 1 and 2 were 0.75 and 0.74 dB/cm/MHz, respectively. The median values of TSI measurements for the observers 1 and 2 were 93.53 and 92.58, respectively. The interobserver agreement in TAI (ICC: 0.970) and TSI (ICC: 0.938) measurements were excellent. The mean of the required time period for TAI technique were 55.1 ± 7.8 and 59.9 ± 6.6 seconds for the observers 1 and 2, respectively. The mean of the required time period for TSI technique were 49.1 ± 5.8 and 54.1 ± 5.4 seconds for the observers 1 and 2, respectively. CONCLUSION The current study revealed that both TAI and TSI techniques are highly reproducible and can be implemented into daily practice with little additional time requirement.
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Affiliation(s)
- Halit Nahit Şendur
- Department of Radiology, Gazi University Faculty of Medicine, Mevlana Bulvarı No:29 06560 Yenimahalle, Ankara, Turkey
| | - Mahi Nur Cerit
- Department of Radiology, Gazi University Faculty of Medicine, Mevlana Bulvarı No:29 06560 Yenimahalle, Ankara, Turkey
| | - Nemat Ibrahimkhanli
- Department of Radiology, Gazi University Faculty of Medicine, Mevlana Bulvarı No:29 06560 Yenimahalle, Ankara, Turkey
| | | | - Suna Özhan Oktar
- Department of Radiology, Gazi University Faculty of Medicine, Mevlana Bulvarı No:29 06560 Yenimahalle, Ankara, Turkey
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Platz Batista da Silva N, Scharf G, Lürken L, Verloh N, Schleder S, Stroszczynski C, Jung EM, Haimerl M. Different Ultrasound Shear Wave Elastography Techniques as Novel Imaging-Based Approaches for Quantitative Evaluation of Hepatic Steatosis-Preliminary Findings. Tomography 2023; 9:681-692. [PMID: 36961013 PMCID: PMC10037607 DOI: 10.3390/tomography9020054] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 03/10/2023] [Accepted: 03/14/2023] [Indexed: 03/19/2023] Open
Abstract
BACKGROUND Modern ultrasound (US) shear-wave dispersion (SWD) and attenuation imaging (ATI) can be used to quantify changes in the viscosity and signal attenuation of the liver parenchyma, which are altered in hepatic steatosis. We aimed to evaluate modern shear-wave elastography (SWE), SWD and ATI for the assessment of hepatic steatosis. METHODS We retrospectively analyzed the US data of 15 patients who underwent liver USs and MRIs for the evaluation of parenchymal disease/liver lesions. The USs were performed using a multifrequency convex probe (1-8 MHz). The quantitative US measurements for the SWE (m/s/kPa), the SWD (kPa-m/s/kHz) and the ATI (dB/cm/MHz) were acquired after the mean value of five regions of interest (ROIs) was calculated. The liver MRI (3T) quantification of hepatic steatosis was performed by acquiring proton density fat fraction (PDFF) mapping sequences and placing five ROIs in artifact-free areas of the PDFF scan, measuring the fat-signal fraction. We correlated the SWE, SWD and ATI measurements to the PDFF results. RESULTS Three patients showed mild steatosis, one showed moderate steatosis and eleven showed no steatosis in the PDFF sequences. The calculated SWE cut-off (2.5 m/s, 20.4 kPa) value identified 3/4 of patients correctly (AUC = 0.73, p > 0.05). The SWD cut-off of 18.5 m/s/kHz, which had a significant correlation (r = 0.55, p = 0.034) with the PDFF results (AUC = 0.73), identified four patients correctly (p < 0.001). The ideal ATI (AUC = 0.53 (p < 0.05)) cut-off was 0.59 dB/cm/MHz, which showed a significantly good correlation with the PDFF results (p = 0.024). CONCLUSION Hepatic steatosis can be accurately detected using all the US-elastography techniques applied in this study, although the SWD and the SWE showed to be more sensitive than the PDFF.
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Affiliation(s)
| | - Gregor Scharf
- Department of Radiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Lukas Lürken
- Department of Radiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Niklas Verloh
- Department of Diagnostic and Interventional Radiology, Medical Center University of Freiburg, Hugstetter Straße 55, 79106 Freiburg im Breisgau, Germany
| | - Stephan Schleder
- Department of Diagnostic and Interventional Radiology, Merciful Brothers Hospital St. Elisabeth, 94315 Straubing, Germany
| | - Christian Stroszczynski
- Department of Radiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Ernst Michael Jung
- Department of Radiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
| | - Michael Haimerl
- Department of Radiology, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany
- Department of Diagnostic and Interventional Radiology, Hospital Wuerzburg Mitte, 97074 Wuerzburg, Germany
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28
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Solberg S, Amini N, Zaza Y, Angelsen BAJ, Hansen R. Estimation of fat content in soft tissues using dual frequency ultrasound-A phantom study. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2023; 153:1766. [PMID: 37002069 DOI: 10.1121/10.0017601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 02/25/2023] [Indexed: 05/18/2023]
Abstract
This paper presents an initial investigation into the use of dual frequency pulse-echo ultrasound, second order ultrasound field (SURF) imaging, to measure the fat content of soft tissues. The SURF imaging method was used to measure the non-linear bulk elasticity (NBE) of several fatty phantoms that were created by mixing different mass fractions of soybean oil uniformly into agar phantoms. The median of the measured NBE within the estimation region was found to increase linearly with fat mass fraction (R2 = 0.99), from 1.7 GPa-1 at 9.6% fat to 2.52 GPa-1 at 63.6% fat, thus, showing promise as a sensitive parameter for fat content measurement. Comparisons to mixture laws in earlier literature are made, and the most important error sources that need to be considered for the in vivo applications of the method are discussed.
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Affiliation(s)
| | | | - Yamen Zaza
- SURF Technology AS, 7491 Trondheim, Norway
| | - Bjørn A J Angelsen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Rune Hansen
- Department of Health Research, SINTEF Digital, 7465 Trondheim, Norway
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29
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Tahmasebi A, Wang S, Wessner CE, Vu T, Liu JB, Forsberg F, Civan J, Guglielmo FF, Eisenbrey JR. Ultrasound-Based Machine Learning Approach for Detection of Nonalcoholic Fatty Liver Disease. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2023. [PMID: 36807314 DOI: 10.1002/jum.16194] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/05/2022] [Accepted: 01/25/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVES Current diagnosis of nonalcoholic fatty liver disease (NAFLD) relies on biopsy or MR-based fat quantification. This prospective study explored the use of ultrasound with artificial intelligence for the detection of NAFLD. METHODS One hundred and twenty subjects with clinical suspicion of NAFLD and 10 healthy volunteers consented to participate in this institutional review board-approved study. Subjects were categorized as NAFLD and non-NAFLD according to MR proton density fat fraction (PDFF) findings. Ultrasound images from 10 different locations in the right and left hepatic lobes were collected following a standard protocol. MRI-based liver fat quantification was used as the reference standard with >6.4% indicative of NAFLD. A supervised machine learning model was developed for assessment of NAFLD. To validate model performance, a balanced testing dataset of 24 subjects was used. Sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy with 95% confidence interval were calculated. RESULTS A total of 1119 images from 106 participants was used for model development. The internal evaluation achieved an average precision of 0.941, recall of 88.2%, and precision of 89.0%. In the testing set AutoML achieved a sensitivity of 72.2% (63.1%-80.1%), specificity of 94.6% (88.7%-98.0%), positive predictive value (PPV) of 93.1% (86.0%-96.7%), negative predictive value of 77.3% (71.6%-82.1%), and accuracy of 83.4% (77.9%-88.0%). The average agreement for an individual subject was 92%. CONCLUSIONS An ultrasound-based machine learning model for identification of NAFLD showed high specificity and PPV in this prospective trial. This approach may in the future be used as an inexpensive and noninvasive screening tool for identifying NAFLD in high-risk patients.
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Affiliation(s)
- Aylin Tahmasebi
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Shuo Wang
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Corinne E Wessner
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Trang Vu
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Ji-Bin Liu
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Flemming Forsberg
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Jesse Civan
- Department of Medicine, Division of Gastroenterology and Hepatology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Flavius F Guglielmo
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - John R Eisenbrey
- Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
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30
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Welman CJ, Saunders J, Zelesco M, Abbott S, Boardman G, Ayonrinde OT. Hepatic steatosis: Ultrasound assessment using attenuation imaging (ATI) with liver biopsy correlation. J Med Imaging Radiat Oncol 2023; 67:45-53. [PMID: 35466506 DOI: 10.1111/1754-9485.13412] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 03/10/2022] [Accepted: 03/30/2022] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Hepatic steatosis duration and severity are risk factors for liver fibrosis and cardiometabolic disease. We assessed the diagnostic accuracy of attenuation imaging (ATI), compared with histologic hepatosteatosis grading in adults with varied suspected liver pathologies. METHODS Liver biopsy was performed on 76 patients (51 women, 25 men) with non-malignant diffuse parenchymal liver disease, within 4 weeks of multiparametric liver ultrasound including attenuation imaging (ATI). Skin-liver capsule distance (SCD) and body mass index (BMI) were measured. Histologic steatosis was graded none (S0), mild (S1), moderate (S2) or severe (S3). We compared histology and sonographic parameters. RESULTS The median patient age was 50.5 (range 18-83) years and BMI 28.9 kg/m2 (interquartile range 24.0-33.3). The distribution of histologic steatosis grade was S0 (44%), S1(17%), S2(30%) and S3(9%). Median ATI value for each biopsy steatosis grade was 0.60 (IQR: 0.52-0.65), 0.65 (IQR: 0.6-0.71), 0.83 (IQR: 0.74-0.90) and 0.90 (IQR: 0.82-1.01) dB/cm/MHz for S0, S1, S2 and S3, respectively. The AUC of ATI for detection of any steatosis (S1-S3) and moderate to severe steatosis (S2-S3) was 0.85 (95% CI: 0.75-0.91) and 0.91 (95% CI: 0.83-0.99) with cut-offs of 0.55 and 0.62 dB/cm/MHz. ATI threshold of 0.74 dB/cm/MHz was able to discriminate between S0-S1 and S2-3 with accuracy, CI and kappa statistic of 0.8889, 0.65-0.98 and 0.7534. CONCLUSION We found a good correlation between ATI and steatosis grade. The most accurate discrimination was between none to mild (S0-1) and moderate to severe (S2-3) steatosis.
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Affiliation(s)
- Christopher J Welman
- Department of Medical Imaging, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
| | - Jacqualine Saunders
- Department of Medical Imaging, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
| | - Marilyn Zelesco
- Department of Medical Imaging, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
| | - Steven Abbott
- Department of Medical Imaging, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
| | - Glenn Boardman
- Data Analyst, Clinical Service Planning & Population Health, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
| | - Oyekoya T Ayonrinde
- Department of Gastroenterology, Fiona Stanley Hospital, Murdoch, Western Australia, Australia
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Lu R, Jiang X, Zhang J, Hu J, Chen X, Wu Z, Qian Z, Luo H, Ni Z, Yi H. A Novel Portable Unilateral Magnetic Resonance Magnet for Noninvasive Quantification of Human Liver Fat. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023; 72:1-8. [DOI: 10.1109/tim.2023.3268480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2025]
Affiliation(s)
- Rongsheng Lu
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, the School of Mechanical Engineering, and the National Key Laboratory of Bioelectronics, Southeast University, Nanjing, China
| | - Xiaowen Jiang
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments and the School of Mechanical Engineering, Southeast University, Nanjing, China
| | - Jinxiang Zhang
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments and the School of Mechanical Engineering, Southeast University, Nanjing, China
| | - Jianxiong Hu
- Wuxi Marvel Stone Healthcare Company Ltd., Wuxi, China
| | - Xiao Chen
- Wuxi Marvel Stone Healthcare Company Ltd., Wuxi, China
| | - Ziyue Wu
- Wuxi Marvel Stone Healthcare Company Ltd., Wuxi, China
| | - Zhiyong Qian
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments and the School of Mechanical Engineering, Southeast University, Nanjing, China
| | - Hai Luo
- Wuxi Marvel Stone Healthcare Company Ltd., Wuxi, China
| | - Zhonghua Ni
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments and the School of Mechanical Engineering, Southeast University, Nanjing, China
| | - Hong Yi
- Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments and the School of Mechanical Engineering, Southeast University, Nanjing, China
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Zheng Y, Yang S, Chen X, Lv J, Su J, Yu S. The Correlation between Type 2 Diabetes and Fat Fraction in Liver and Pancreas: A Study using MR Dixon Technique. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:7073647. [PMID: 36685051 PMCID: PMC9822734 DOI: 10.1155/2022/7073647] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 12/05/2022] [Accepted: 12/08/2022] [Indexed: 01/01/2023]
Abstract
Objective The increased obesity results in ectopic fat deposits in liver and pancreas, which will affect insulin resistance and elevated plasma glucose with type 2 diabetes. To assess the relationship between obesity and ectopic fat deposits and diabetes, this study used the MR Dixon method for the quantification of liver and pancreas fat fraction (FF) in type 2 diabetes mellitus (T2DM) patients and healthy controls. Methods The FF of whole liver (FFWL) and pancreas (FFWP), the maximum diameters of the pancreas, the abdominal subcutaneous adipose area (SAT), the visceral adipose tissue area (VAT), and the total abdominal adipose tissue area (TAT) were measured for 157 subjects using the MR Dixon data. Four groups were established on the basis of BMI value. For statistics, intra- and intergroup comparisons were made by employing independent sample t-test. Results FFWL, FFWP, and VAT varied significantly between T2DM (BMI < 25) and control group (BMI < 25), T2DM (BMI ≥ 25) and control group (BMI ≥ 25), T2DM (BMI < 25) and T2DM (BMI ≥ 25) (all P < 0.05). The FF of pancreas tail, SAT, and TAT varied significantly between control group (BMI < 25) and control group (BMI ≥ 25) (P < 0.05). FFWP and the FF of pancreas tail varied significantly between T2DM and normal volunteers (P < 0.05), with normal or mild liver fat content. Conclusion The tissue FF, which has a close relationship with T2DM, can be assessed by the MR Dixon technique. T2DM patients should pay attention to tissue fat content regardless of BMI values.
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Affiliation(s)
- Yonghong Zheng
- Shengli Clinical Medical College of Fujian Medical University, Fujian, Fuzhou, China
- Department of Radiology, Fujian Provincial Hospital, Fujian, Fuzhou, China
| | - Shengsheng Yang
- Shengli Clinical Medical College of Fujian Medical University, Fujian, Fuzhou, China
- Department of Radiology, Fujian Provincial Hospital, Fujian, Fuzhou, China
| | - Xianyuan Chen
- Shengli Clinical Medical College of Fujian Medical University, Fujian, Fuzhou, China
- Department of Radiology, Fujian Provincial Hospital, Fujian, Fuzhou, China
| | - Jieqin Lv
- Shengli Clinical Medical College of Fujian Medical University, Fujian, Fuzhou, China
- Department of Radiology, Fujian Provincial Hospital, Fujian, Fuzhou, China
| | - Jiawei Su
- Shengli Clinical Medical College of Fujian Medical University, Fujian, Fuzhou, China
- Department of Radiology, Fujian Provincial Hospital, Fujian, Fuzhou, China
| | - Shun Yu
- Shengli Clinical Medical College of Fujian Medical University, Fujian, Fuzhou, China
- Department of Radiology, Fujian Provincial Hospital, Fujian, Fuzhou, China
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Şendur AB, Şendur HN. A Standardized Approach for MRI-PDFF is Necessary in the Assessment of Diagnostic Performances of the Ultrasound-Based Hepatic Fat Quantification Tools. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2022; 41:3159-3161. [PMID: 36149356 DOI: 10.1002/jum.16102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 09/07/2022] [Indexed: 06/16/2023]
Abstract
The recently developed ultrasound-based hepatic fat quantification tools have the potential to be implemented in daily practice with wide acceptance due to inherited advantages of ultrasound technology. Researchers intensively focused on this topic and the accumulated evidences that support clinical usefulness of these tools. However, differences in the researcher-dependent factors of the utilized MRI-PDFF technique, the recommended reference standard, may hinder the better understanding of the diagnostic performances of these tools. Therefore, a standardized approach for MRI-PDFF technique, which is established with international consensus may be considered as important.
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Affiliation(s)
| | - Halit Nahit Şendur
- Department of Radiology, Faculty of Medicine, Gazi University, Ankara, Turkey
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Hong SB, Lee NK, Kim S, Um K, Kim K, Kim IJ. Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort. Medicina (B Aires) 2022; 58:medicina58101459. [PMID: 36295617 PMCID: PMC9609129 DOI: 10.3390/medicina58101459] [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: 08/26/2022] [Revised: 10/09/2022] [Accepted: 10/14/2022] [Indexed: 12/04/2022] Open
Abstract
The early diagnosis of hepatic steatosis is important. No study has assessed hepatic fat quantification by using low-dose dual-energy computed tomography (CT). We assessed the accuracy of hepatic fat quantification using the multi-material decomposition (MMD) algorithm with low-dose non-contrast material-enhanced dual-energy CT. We retrospectively reviewed 33 prospectively enrolled patients who had undergone low-dose non-contrast material-enhanced dual-energy CT and magnetic resonance image (MRI) proton density fat fraction (PDFF) on the same day. Percentage fat volume fraction (FVF) images were generated using the MMD algorithm on the low-dose dual-energy CT data. We assessed the correlation between FVFs and MRI-PDFFs by using Spearman's rank correlation. With a 5% cutoff value of MRI-PDFF for fatty liver, a receiver operating characteristic (ROC) curve analysis was performed to identify the optimal criteria of FVF for diagnosing fatty liver. CTDIvol of CT was 2.94 mGy. FVF showed a strong correlation with MRI-PDFF (r = 0.756). The ROC curve analysis demonstrated that FVF ≥ 4.61% was the optimal cutoff for fatty liver. With this cutoff value for diagnosing the fatty liver on low-dose dual-energy CT, the sensitivity, specificity, and area under the curve were 90%, 100%, and 0.987, respectively. The MMD algorithm using low-dose non-contrast material-enhanced dual-energy CT is feasible for quantifying hepatic fat.
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Affiliation(s)
- Seung Baek Hong
- Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Pusan 46241, Korea
| | - Nam Kyung Lee
- Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Pusan 46241, Korea
- Correspondence: (N.K.L.); (K.K.)
| | - Suk Kim
- Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Pusan 46241, Korea
| | - Kyunga Um
- General Electronics (GE) Healthcare Korea, Seoul 04637, Korea
| | - Keunyoung Kim
- Department of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital, Pusan 46241, Korea
- Correspondence: (N.K.L.); (K.K.)
| | - In Joo Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Biomedical Research Institute, Pusan National University Hospital, Pusan 46241, Korea
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Şendur HN, Özdemir Kalkan D, Cerit MN, Kalkan G, Şendur AB, Özhan Oktar S. Hepatic Fat Quantification With Novel Ultrasound Based Techniques: A Diagnostic Performance Study Using Magnetic Resonance Imaging Proton Density Fat Fraction as Reference Standard. Can Assoc Radiol J 2022; 74:362-369. [PMID: 36113064 DOI: 10.1177/08465371221123696] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Purpose: To assess the diagnostic performances of novel Tissue attenuation imaging (TAI) and Tissue scatter distribution imaging (TSI) tools in quantification of liver fat content using magnetic resonance imaging proton density fat fraction (MRI PDFF) as reference standard. Methods: Eighty consecutive patients with known or suspected non-alcoholic fatty liver disease (NAFLD) who volunteered to participate in the study comprised the study cohort. All patients underwent MRI PDFF scan and quantitative ultrasound (QUS) imaging using TAI and TSI tools. The cutoff values of ≥5%, ≥16.3% and ≥21.7% on MRI PDFF were used for mild, moderate and severe steatosis, respectively. Area under the Receiver operating characteristic (AUROC) curves were used to assess the diagnostic performance of TAI and TSI in detecting different grades of hepatic steatosis. Results: The AUROCs of TAI and TSI tools in detecting hepatosteatosis (MRI PDFF ≥5%), were 0.95 [95% Confidence Interval (CI): 0.91–0.99] ( P < 0.001) and 0.96 (95% CI: 0.93–0.99) ( P < 0.001), respectively. In distinguishing between different grades of steatosis, the values of 0.75, 0.86 and 0.96 dB/cm/MHz have 88%, 88% and 100% sensitivity, respectively, for TAI tool; and the values of 92.44, 96.64 and 99.45 have 90%, 92% and 91.7% sensitivity, respectively, for TSI tool. Conclusion: TAI and TSI tools accurately quantify liver fat content and can be used for the assessment and grading of hepatosteatosis in patients with known or suspected NAFLD.
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Affiliation(s)
- Halit Nahit Şendur
- Faculty of Medicine, Department of Radiology, Gazi University, Ankara, Turkey
| | | | - Mahi Nur Cerit
- Faculty of Medicine, Department of Radiology, Gazi University, Ankara, Turkey
| | - Gökalp Kalkan
- Medicana International Ankara Hospital, Radiology Unit, Ankara, Turkey
| | | | - Suna Özhan Oktar
- Faculty of Medicine, Department of Radiology, Gazi University, Ankara, Turkey
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Li YW, Jiao Y, Chen N, Gao Q, Chen YK, Zhang YF, Wen QP, Zhang ZM. How to select the quantitative magnetic resonance technique for subjects with fatty liver: A systematic review. World J Clin Cases 2022; 10:8906-8921. [PMID: 36157636 PMCID: PMC9477046 DOI: 10.12998/wjcc.v10.i25.8906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 05/25/2022] [Accepted: 07/22/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Early quantitative assessment of liver fat content is essential for patients with fatty liver disease. Mounting evidence has shown that magnetic resonance (MR) technique has high accuracy in the quantitative analysis of fatty liver, and is suitable for monitoring the therapeutic effect on fatty liver. However, many packaging methods and postprocessing functions have puzzled radiologists in clinical applications. Therefore, selecting a quantitative MR imaging technique for patients with fatty liver disease remains challenging. AIM To provide information for the proper selection of commonly used quantitative MR techniques to quantify fatty liver. METHODS We completed a systematic literature review of quantitative MR techniques for detecting fatty liver, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Studies were retrieved from PubMed, Embase, and Cochrane Library databases, and their quality was assessed using the Quality Assessment of Diagnostic Studies criteria. The Reference Citation Analysis database (https:// www.referencecitationanalysis.com) was used to analyze citation of articles which were included in this review. RESULTS Forty studies were included for spectroscopy, two-point Dixon imaging, and multiple-point Dixon imaging comparing liver biopsy to other imaging methods. The advantages and disadvantages of each of the three techniques and their clinical diagnostic performances were analyzed. CONCLUSION The proton density fat fraction derived from multiple-point Dixon imaging is a noninvasive method for accurate quantitative measurement of hepatic fat content in the diagnosis and monitoring of fatty liver progression.
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Affiliation(s)
- You-Wei Li
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Yang Jiao
- Department of Rehabilitation Psychology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Na Chen
- Department of Otorhinolaryngology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Qiang Gao
- Department of Gastroenterology and Hepatology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Yu-Kun Chen
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Yuan-Fang Zhang
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Qi-Ping Wen
- Department of Radiology, Beijing Rehabilitation Hospital, Capital Medical University, Beijing 100144, China
| | - Zong-Ming Zhang
- Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China
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Cassinotto C, Jacq T, Anselme S, Ursic-Bedoya J, Blanc P, Faure S, Belgour A, Guiu B. Diagnostic Performance of Attenuation to Stage Liver Steatosis with MRI Proton Density Fat Fraction as Reference: A Prospective Comparison of Three US Machines. Radiology 2022; 305:353-361. [PMID: 35819322 DOI: 10.1148/radiol.212846] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background US tools to quantify liver fat content have recently been made clinically available by different vendors, but comparative data on their accuracy are lacking. Purpose To compare the diagnostic performances of the attenuation parameters of US machines from three different manufacturers (vendors 1, 2, and 3) in participants who underwent liver fat quantification with the MRI-derived proton density fat fraction (PDFF). Materials and Methods From July 2020 to June 2021, consecutive participants with chronic liver disease were enrolled in this prospective single-center study and underwent MRI PDFF quantification (reference standard) and US on the same day. US was performed with two different machines from among three vendors assessed. Areas under the receiver operating characteristic curve (AUCs) for the staging of liver steatosis (MRI PDFF: ≥5.5% for grade ≥S1 and ≥15.5% for grade ≥S2) were calculated in test and validation samples and then compared between vendors in the study sample. Results A total of 534 participants (mean age, 60 years ± 13 [SD]; 320 men) were evaluated. Failure of measurements occurred in less than 1% of participants for all vendors. Correlation coefficients with the MRI PDFF were 0.71, 0.73, and 0.54 for the attenuation coefficients of vendors 1, 2, and 3, respectively. In the test sample, AUCs for diagnosis of steatosis grade S1 and higher and grade S2 and higher were 0.89 and 0.93 for vendor 1 attenuation, 0.88 and 0.92 for vendor 2 attenuation, and 0.79 and 0.79 for vendor 3 attenuation, respectively. In the validation sample, a threshold value of 0.65 for vendor 1 and 0.66 for vendor 2 yielded sensitivity of 77% and 84% and specificity of 78% and 85%, respectively, for diagnosis of grade S1 and higher. Vendor 2 attenuation had greater AUCs than vendor 3 attenuation (P = .001 and P = .003) for diagnosis of grade S1 and higher and grade S2 and higher, respectively, and vender 2 had greater AUCs for attenuation than vendor 1 for diagnosis of grade S2 and higher (P = .04). For all vendors, attenuation was not associated with liver stiffness (correlation coefficients <0.05). Conclusion To stage liver steatosis, attenuation coefficient accuracy varied among US devices across vendors when using MRI proton density fat fraction quantification as the reference standard, with some demonstrating excellent diagnostic performance and similar cutoff values. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Dubinsky in this issue.
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Affiliation(s)
- Christophe Cassinotto
- From the Departments of Diagnostic and Interventional Radiology (C.C., T.J., S.A., A.B., B.G.), Hepatology A (J.U.B., S.F.), and Hepatology B (P.B.), Saint-Eloi Hospital, University Hospital of Montpellier, 80 Avenue Augustin Fliche, 34090 Montpellier, France; and Institut Desbrest d'Epidémiologie et de Santé Publique, IDESP UMR UA11 INSERM, Montpellier University, Montpellier, France (C.C., B.G.)
| | - Tony Jacq
- From the Departments of Diagnostic and Interventional Radiology (C.C., T.J., S.A., A.B., B.G.), Hepatology A (J.U.B., S.F.), and Hepatology B (P.B.), Saint-Eloi Hospital, University Hospital of Montpellier, 80 Avenue Augustin Fliche, 34090 Montpellier, France; and Institut Desbrest d'Epidémiologie et de Santé Publique, IDESP UMR UA11 INSERM, Montpellier University, Montpellier, France (C.C., B.G.)
| | - Sophie Anselme
- From the Departments of Diagnostic and Interventional Radiology (C.C., T.J., S.A., A.B., B.G.), Hepatology A (J.U.B., S.F.), and Hepatology B (P.B.), Saint-Eloi Hospital, University Hospital of Montpellier, 80 Avenue Augustin Fliche, 34090 Montpellier, France; and Institut Desbrest d'Epidémiologie et de Santé Publique, IDESP UMR UA11 INSERM, Montpellier University, Montpellier, France (C.C., B.G.)
| | - José Ursic-Bedoya
- From the Departments of Diagnostic and Interventional Radiology (C.C., T.J., S.A., A.B., B.G.), Hepatology A (J.U.B., S.F.), and Hepatology B (P.B.), Saint-Eloi Hospital, University Hospital of Montpellier, 80 Avenue Augustin Fliche, 34090 Montpellier, France; and Institut Desbrest d'Epidémiologie et de Santé Publique, IDESP UMR UA11 INSERM, Montpellier University, Montpellier, France (C.C., B.G.)
| | - Pierre Blanc
- From the Departments of Diagnostic and Interventional Radiology (C.C., T.J., S.A., A.B., B.G.), Hepatology A (J.U.B., S.F.), and Hepatology B (P.B.), Saint-Eloi Hospital, University Hospital of Montpellier, 80 Avenue Augustin Fliche, 34090 Montpellier, France; and Institut Desbrest d'Epidémiologie et de Santé Publique, IDESP UMR UA11 INSERM, Montpellier University, Montpellier, France (C.C., B.G.)
| | - Stéphanie Faure
- From the Departments of Diagnostic and Interventional Radiology (C.C., T.J., S.A., A.B., B.G.), Hepatology A (J.U.B., S.F.), and Hepatology B (P.B.), Saint-Eloi Hospital, University Hospital of Montpellier, 80 Avenue Augustin Fliche, 34090 Montpellier, France; and Institut Desbrest d'Epidémiologie et de Santé Publique, IDESP UMR UA11 INSERM, Montpellier University, Montpellier, France (C.C., B.G.)
| | - Ali Belgour
- From the Departments of Diagnostic and Interventional Radiology (C.C., T.J., S.A., A.B., B.G.), Hepatology A (J.U.B., S.F.), and Hepatology B (P.B.), Saint-Eloi Hospital, University Hospital of Montpellier, 80 Avenue Augustin Fliche, 34090 Montpellier, France; and Institut Desbrest d'Epidémiologie et de Santé Publique, IDESP UMR UA11 INSERM, Montpellier University, Montpellier, France (C.C., B.G.)
| | - Boris Guiu
- From the Departments of Diagnostic and Interventional Radiology (C.C., T.J., S.A., A.B., B.G.), Hepatology A (J.U.B., S.F.), and Hepatology B (P.B.), Saint-Eloi Hospital, University Hospital of Montpellier, 80 Avenue Augustin Fliche, 34090 Montpellier, France; and Institut Desbrest d'Epidémiologie et de Santé Publique, IDESP UMR UA11 INSERM, Montpellier University, Montpellier, France (C.C., B.G.)
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Xiao J, Zhu C, Zhang X, Sun L, Gao C, Liang X, He Q, Liu M. Associations among FT 4 level, FT 3/FT 4 ratio, and non-alcoholic fatty liver disease in Chinese patients with hypopituitarism. Endocr J 2022; 69:659-667. [PMID: 35034938 DOI: 10.1507/endocrj.ej21-0536] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is the most common hepatic metabolic disorder. Thyroid function is associated with NAFLD in different populations; however, little attention has been paid in patients with hypopituitarism. To analyze the association between thyroid function and NAFLD, we included 134 patients with hypopituitarism admitted to the Tianjin Medical University General Hospital between June 2013 and May 2019. Participants were divided into the NAFLD(-) and NAFLD(+) groups based on abdominal ultrasonography findings. We evaluated 68 male and 66 female patients with hypopituitarism. The prevalence of NAFLD was 52.24%. The NAFLD(+) group had a significantly higher free triiodothyronine/free thyroxine (FT3/FT4) ratio than the NAFLD(-) group (p = 0.003). The NAFLD(+) group showed significantly lower levels of FT4 and the growth hormone (GH) than the NAFLD(-) group (p = 0.003 and 0.016, respectively). We observed an association of the FT4 level and FT3/FT4 ratio with NAFLD in the univariate model, which was non-significant after adjustment for metabolic parameters (BMI, HDL-C, triglycerides, serum uric acid, blood pressure, fasting glucose). To better understand the role of each metabolic parameters, we performed additional models for each of those predictors individually after adjustment for age and gender, the association between FT4 level and FT3/FT4 ratio lost significance after adjustment for HDL-C and TG, but not for other predictors. Our findings suggest that thyroid dysfunction may be crucially involved in NAFLD by regulating whole-body metabolism, especially lipid utilization. Therefore, sufficient thyroid hormone replacement therapy for patients with hypopituitarism is recommended from the early stage.
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Affiliation(s)
- Jinfeng Xiao
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Chonggui Zhu
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xinxin Zhang
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Longhao Sun
- Department of General surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Chang Gao
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xiaoyu Liang
- Department of General surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Qing He
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Ming Liu
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, 300052, China
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Computed Tomography Image Analysis of Body Fat Based on Multi-Image Information. BIOMED RESEARCH INTERNATIONAL 2022; 2022:8265211. [PMID: 35769672 PMCID: PMC9236801 DOI: 10.1155/2022/8265211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/14/2022] [Accepted: 05/25/2022] [Indexed: 11/17/2022]
Abstract
Body fat assessment is required as part of an objective health assessment, both for nonobese and obese people. Image-based body fat assessment will enable faster diagnosis. Body fat analysis that accounts for age and sex will help in both diagnosis and correlating diseases and fat distribution. After evaluating computed tomography imaging algorithms to identify and segment human abdominal and subcutaneous fat, we present an improved region growing scale-invariant feature transform algorithm. It applies Naive Bayes image thresholding for key point selection and image matching. This method enables rapid and accurate comparison and matching of images from multiple databases and improves the efficiency of image processing.
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40
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Zeng Y, Cao R, Tao Z, Gao Y. Association between the severity of metabolic dysfunction-associated fatty liver disease and the risk of colorectal neoplasm: a systematic review and meta-analysis. Lipids Health Dis 2022; 21:52. [PMID: 35668493 PMCID: PMC9172084 DOI: 10.1186/s12944-022-01659-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 05/23/2022] [Indexed: 12/03/2022] Open
Abstract
Background The severity of metabolic dysfunction-associated fatty liver disease (MAFLD) reportedly plays a part in the etiology of colorectal tumors. However, there is no consensus. Methods Studies relevant with the impact of MAFLD severity on the risk of colorectal neoplasms published before 24th April 2022 were screened. The pooled odds ratio (OR) with corresponding 95% confidence intervals (95% CI) was obtained using standard and cumulative meta-analyses. Subgroup, meta-regression, and sensitivity analyses were carried out to identify heterogeneity. Results Fourteen studies with data from 37,824 MAFLD patients were included. The prevalence of colorectal neoplasms escalated with the progression of MAFLD compared to simple steatosis (OR = 1.93; 95% CI = 1.42–2.62). The magnitude and direction of the effect on these outcomes remained largely constant over time. Even after limiting the meta-analysis to 8 studies with available adjusted OR (aOR), the findings still suggested that MAFLD severity was positively related to colorectal neoplasms (aOR = 3.03; 95% CI = 2.02–4.53). Severe MAFLD was more likely to cause left colon tumors (OR = 3.86, 95% CI = 2.16–6.91) than right colon neoplasms (OR = 1.94, 95% CI = 1.15–3.28). Conclusion The severity of MAFLD was independently related to colorectal neoplasms and severe MAFLD was more likely to cause left colon tumors. Supplementary Information The online version contains supplementary material available at 10.1186/s12944-022-01659-1.
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Affiliation(s)
- Yunqing Zeng
- Department of Gastroenterology, Qilu Hospital of Shandong University, 107 West Wen Hua Road, Jinan, 250012, Shandong, China
| | - Ruyue Cao
- Department of Gastroenterology, Qilu Hospital of Shandong University, 107 West Wen Hua Road, Jinan, 250012, Shandong, China
| | - Ziwen Tao
- Department of Gastroenterology, Qilu Hospital of Shandong University, 107 West Wen Hua Road, Jinan, 250012, Shandong, China
| | - Yanjing Gao
- Department of Gastroenterology, Qilu Hospital of Shandong University, 107 West Wen Hua Road, Jinan, 250012, Shandong, China.
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Mitrovic B, Gluvic ZM, Obradovic M, Radunovic M, Rizzo M, Banach M, Isenovic ER. Non-alcoholic fatty liver disease, metabolic syndrome, and type 2 diabetes mellitus: where do we stand today? Arch Med Sci 2022; 19:884-894. [PMID: 37560721 PMCID: PMC10408022 DOI: 10.5114/aoms/150639] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 06/02/2022] [Indexed: 08/11/2023] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD), metabolic syndrome (MetS), and type 2 diabetes (T2DM) are metabolic disorders that belong to a highly prevalent disease cluster with a significant impact on public health worldwide. MetS is a complex condition characterized by metabolism perturbations that include glucose intolerance, insulin resistance, dyslipidaemia, associated pro-inflammatory state, and arterial hypertension. Because the components of MetS commonly co-occur, the management of these disorders cannot be considered separate issues. Thus NAFLD, recognized as a hepatic manifestation of MetS, is frequently associated with T2DM. This review analyses the underlying connections between these diseases and the risks associated with their co-occurrence. The effective management of NAFLD associated with MetS and T2DM involves an early diagnosis and optimal treatment of each condition leading to improvement in glycaemic and lipid regulation, liver steatosis, and arterial hypertension. The net effect of such treatment is the prevention of atherosclerotic cardiovascular diseases and liver fibrosis.
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Affiliation(s)
- Bojan Mitrovic
- University Clinical-Hospital Centre Zemun-Belgrade, Clinic of Internal medicine, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Zoran M. Gluvic
- University Clinical-Hospital Centre Zemun-Belgrade, Clinic of Internal medicine, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Milan Obradovic
- Department of Radiobiology and Molecular Genetics, “VINČA” Institute of Nuclear Sciences – National Institute of the Republic of Serbia, University of Belgrade, Belgrade, Serbia
| | - Maja Radunovic
- Faculty of Stomatology, Pancevo, University Business Academy, Novi Sad, Serbia
| | - Manfredi Rizzo
- Department of Internal Medicine and Medical Specialties, University of Palermo, Palermo, Italy
| | - Maciej Banach
- Department of Hypertension, Medical University of Lodz, Lodz, Poland
| | - Esma R. Isenovic
- Department of Radiobiology and Molecular Genetics, “VINČA” Institute of Nuclear Sciences – National Institute of the Republic of Serbia, University of Belgrade, Belgrade, Serbia
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Barahman M, Grunvald E, Prado PJ, Bussandri A, Henderson WC, Wolfson T, Fowler KJ, Sirlin CB. Point-of-care magnetic resonance technology to measure liver fat: Phantom and first-in-human pilot study. Magn Reson Med 2022; 88:1794-1805. [PMID: 35611691 DOI: 10.1002/mrm.29304] [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: 02/10/2022] [Revised: 04/22/2022] [Accepted: 04/25/2022] [Indexed: 11/06/2022]
Abstract
PURPOSE To assess feasibility and accuracy of point-of-care (POC) NMR-proton density fat fraction (PDFF) in phantoms and in a human pilot study in a POC setting. METHODS POC NMR (LiverScope, Livivos, San Diego CA) PDFF measurements were obtained of certified phantoms with known PDFF values (0%-40%). In an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant prospective human study, a convenience sample of participants from an obesity clinic was enrolled (November 2020 to June 2021). The inclusion criteria required body mass index (BMI) = 27-40 kg/m2 and willingness to undergo POC NMR and MRI-PDFF measurements. Liver PDFF was measured by POC NMR and, within 35 days after, by a confounder corrected CSE MRI PDFF acquisition and reconstruction method. The adverse events were documented and linear regression analyses were performed. RESULTS POC NMR-PDFF measurements agreed with known phantom PDFF values (R2 = 0.99). Fourteen participants were enrolled in the pilot human study. MRI-PDFF could not be obtained in 4 participants (claustrophobia reaction, n = 3, exceeded size of MR scanner bore, n = 1). POC NMR was unevaluable in 2 participants (insufficient signal penetration depth, n = 1, failure to comply with instructions, n = 1). Technical success was 11 of 13 (85%) for POC NMR PDFF. In 7 participants (4 female; 31-74 years old; median BMI 35 kg/m2 ), MRI-PDFF (range, 2.8%-18.1%), and POC NMR-PDFF (range, 3%-25.2%), agreed with R2 = 0.94. POC NMR had no adverse events. CONCLUSION POC NMR measures PDFF accurately in phantoms and, in a first-in-human pilot study, is feasible and accurate in adults with obesity. Further testing to determine precision and accuracy across larger and more diverse cohorts is needed.
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Affiliation(s)
- Mark Barahman
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Eduardo Grunvald
- Division of General Internal Medicine, Department of Medicine, University of California San Diego, San Diego, California, USA.,Bariatric and Metabolic Institute, Division of Minimally Invasive Surgery, Department of Surgery, University of California San Diego, San Diego, California, USA
| | | | | | - Walter C Henderson
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Tanya Wolfson
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Kathryn J Fowler
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
| | - Claude B Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, California, USA
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El informe radiológico en paciente con hepatopatía crónica. RADIOLOGIA 2022. [DOI: 10.1016/j.rx.2022.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Zhou H, Zhou Y, Ding J, Chen Y, Wen J, Zhao L, Zhang Q, Jing X. Clinical evaluation of grayscale and linear scale hepatorenal indices for fatty liver quantification: a prospective study of a native Chinese population. Abdom Radiol (NY) 2022; 47:1321-1332. [PMID: 35150314 DOI: 10.1007/s00261-022-03434-3] [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: 10/10/2021] [Revised: 01/26/2022] [Accepted: 01/28/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND AIMS Hepato-renal index (HRI) has been investigated extensively in various clinical studies. New linear scale HRI (LS-HRI) is proposed as an alternative to conventional grayscale HRI (GS-HRI) that suffers from lack of a widely accepted cut-off value for differentiation of fatty from normal livers. To investigate the diagnostic performance of conventional GS-HRI and new LS-HRI for a relatively large Chinese population with NAFLD using a well-established ultrasonographic fatty liver indicator (US-FLI) as the reference standard for steatosis grades. MATERIALS AND METHODS A total of 106 patients with various stages of NAFLD were prospectively enrolled. All ultrasound images for these patients were first acquired by a highly experienced ultrasound doctor and their US-FLI scores then obtained by the same doctor. Both GS-HRI and LS-HRI values were measured off-line by two additional ultrasound doctors. Four steatosis grades were determined from US-FLI scores for steatosis detection and staging. RESULTS Inter-observer agreements for both GS-HRI and LS-HRI were excellent with the respective concordance correlation coefficient (CCC) of 0.900 for GS-HRI and 0.822 for LS-HRI. A linear correlation to US-FLI for LS-HRI (R = 0.74) was substantially superior to that for GS-HRI (R = 0.46). LS-HRI had a sensitivity of 85.9% and a specificity of 96.3% to differentiate steatosis from the normal liver (AUROC: 95.5%) while GS-HRI had a sensitivity of 85.9% and a specificity of 92.6% to distinguish steatosis from the normal liver (AUROC: 94.7%). CONCLUSIONS Both GS-HRI and LS-HRI measurements are reproducible between two ultrasonographic clinicians and are evidently effective for steatosis detection.
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Affiliation(s)
- Hongyu Zhou
- Department of Ultrasound, The Third Central Hospital of Tianjin/Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases/Artificial Cell Engineering Technology Research Center, Tianjin, China/Tianjin Institute of Hepatobiliary Disease, Tianjin, China, 83 Jintang Road, Hedong District, Tianjin, 300170, China
| | - Yan Zhou
- Department of Ultrasound, The Third Central Hospital of Tianjin/Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases/Artificial Cell Engineering Technology Research Center, Tianjin, China/Tianjin Institute of Hepatobiliary Disease, Tianjin, China, 83 Jintang Road, Hedong District, Tianjin, 300170, China
| | - Jianmin Ding
- Department of Ultrasound, The Third Central Hospital of Tianjin/Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases/Artificial Cell Engineering Technology Research Center, Tianjin, China/Tianjin Institute of Hepatobiliary Disease, Tianjin, China, 83 Jintang Road, Hedong District, Tianjin, 300170, China
| | - Ying Chen
- Department of Ultrasound, The Third Central Hospital of Tianjin/Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases/Artificial Cell Engineering Technology Research Center, Tianjin, China/Tianjin Institute of Hepatobiliary Disease, Tianjin, China, 83 Jintang Road, Hedong District, Tianjin, 300170, China
| | - Jing Wen
- Department of Ultrasound, The Third Central Hospital of Tianjin/Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases/Artificial Cell Engineering Technology Research Center, Tianjin, China/Tianjin Institute of Hepatobiliary Disease, Tianjin, China, 83 Jintang Road, Hedong District, Tianjin, 300170, China
| | - Lei Zhao
- Department of Ultrasound, The Third Central Hospital of Tianjin/Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases/Artificial Cell Engineering Technology Research Center, Tianjin, China/Tianjin Institute of Hepatobiliary Disease, Tianjin, China, 83 Jintang Road, Hedong District, Tianjin, 300170, China
| | - Qian Zhang
- The Third Central Clinical College of Tianjin Medical University, Tianjin, 300170, China
| | - Xiang Jing
- Department of Ultrasound, The Third Central Hospital of Tianjin/Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases/Artificial Cell Engineering Technology Research Center, Tianjin, China/Tianjin Institute of Hepatobiliary Disease, Tianjin, China, 83 Jintang Road, Hedong District, Tianjin, 300170, China.
- Department of Ultrasound, The Third Central Hospital of Tianjin, Tianjin, China, 83 Jintang Road, Hedong District, Tianjin, 300170, China.
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45
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Ferraioli G, Kumar V, Ozturk A, Nam K, de Korte CL, Barr RG. US Attenuation for Liver Fat Quantification: An AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative. Radiology 2022; 302:495-506. [PMID: 35076304 DOI: 10.1148/radiol.210736] [Citation(s) in RCA: 98] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an estimated prevalence of up to 30% in the general population and higher in people with type 2 diabetes. The assessment of liver fat content is essential to help identify patients with or who are at risk for NAFLD and to follow their disease over time. The American Institute of Ultrasound in Medicine-RSNA Quantitative Imaging Biomarkers Alliance Pulse-Echo Quantitative Ultrasound Initiative was formed to help develop and standardize acquisition protocols and to better understand confounding factors of US-based fat quantification. The three quantitative US parameters explored by the initiative are attenuation, backscatter coefficient, and speed of sound. The purpose of this review is to present the current state of attenuation imaging for fat quantification and to provide expert opinion on examination performance and interpretation. US attenuation methods that need further study are outlined.
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Affiliation(s)
- Giovanna Ferraioli
- From the Medical School University of Pavia, Viale Brambilla, Pavia, Italy (G.F.); Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, Boston, Mass (V.K., A.O.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (K.N.); Medical UltraSound Imaging Center, Radboud University Medical Center, Nijmegen, the Netherlands (C.L.d.K.); Technical Medical (TechMed) Center, University of Twente, Enschede, the Netherlands (C.L.d.K.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); and Southwoods Imaging, 7623 Market St, Youngstown, OH 44512 (R.G.B.)
| | - Viksit Kumar
- From the Medical School University of Pavia, Viale Brambilla, Pavia, Italy (G.F.); Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, Boston, Mass (V.K., A.O.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (K.N.); Medical UltraSound Imaging Center, Radboud University Medical Center, Nijmegen, the Netherlands (C.L.d.K.); Technical Medical (TechMed) Center, University of Twente, Enschede, the Netherlands (C.L.d.K.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); and Southwoods Imaging, 7623 Market St, Youngstown, OH 44512 (R.G.B.)
| | - Arinc Ozturk
- From the Medical School University of Pavia, Viale Brambilla, Pavia, Italy (G.F.); Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, Boston, Mass (V.K., A.O.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (K.N.); Medical UltraSound Imaging Center, Radboud University Medical Center, Nijmegen, the Netherlands (C.L.d.K.); Technical Medical (TechMed) Center, University of Twente, Enschede, the Netherlands (C.L.d.K.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); and Southwoods Imaging, 7623 Market St, Youngstown, OH 44512 (R.G.B.)
| | - Kibo Nam
- From the Medical School University of Pavia, Viale Brambilla, Pavia, Italy (G.F.); Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, Boston, Mass (V.K., A.O.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (K.N.); Medical UltraSound Imaging Center, Radboud University Medical Center, Nijmegen, the Netherlands (C.L.d.K.); Technical Medical (TechMed) Center, University of Twente, Enschede, the Netherlands (C.L.d.K.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); and Southwoods Imaging, 7623 Market St, Youngstown, OH 44512 (R.G.B.)
| | - Chris L de Korte
- From the Medical School University of Pavia, Viale Brambilla, Pavia, Italy (G.F.); Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, Boston, Mass (V.K., A.O.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (K.N.); Medical UltraSound Imaging Center, Radboud University Medical Center, Nijmegen, the Netherlands (C.L.d.K.); Technical Medical (TechMed) Center, University of Twente, Enschede, the Netherlands (C.L.d.K.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); and Southwoods Imaging, 7623 Market St, Youngstown, OH 44512 (R.G.B.)
| | - Richard G Barr
- From the Medical School University of Pavia, Viale Brambilla, Pavia, Italy (G.F.); Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, Boston, Mass (V.K., A.O.); Department of Radiology, Thomas Jefferson University, Philadelphia, Pa (K.N.); Medical UltraSound Imaging Center, Radboud University Medical Center, Nijmegen, the Netherlands (C.L.d.K.); Technical Medical (TechMed) Center, University of Twente, Enschede, the Netherlands (C.L.d.K.); Department of Radiology, Northeastern Ohio Medical University, Rootstown, Ohio (R.G.B.); and Southwoods Imaging, 7623 Market St, Youngstown, OH 44512 (R.G.B.)
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46
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Kaliaev A, Chavez W, Soto J, Huda F, Xie H, Nguyen M, Shamdasani V, Anderson S. Quantitative Ultrasound Assessment of Hepatic Steatosis. J Clin Exp Hepatol 2022; 12:1091-1101. [PMID: 35814521 PMCID: PMC9257875 DOI: 10.1016/j.jceh.2022.01.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 01/17/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND/AIMS Non-alcoholic fatty liver disease (NAFLD) is widespread chronic disease of the live in humans with the prevalence of 30% of the United States population.1,2 The goal of the study is to validate the performance of quantitative ultrasound algorithms in the assessment of hepatic steatosis in patients with suspected NAFLD. METHODS This prospective study enrolled a total of 31 patients with clinical suspicion of NAFLD to receive liver fat measurements by quantitative ultrasound and reference MRI measurements (proton density fat-fraction, PDFF). The following ultrasound (US) parameters based on both raw ultrasound RF (Radio Frequency) data and 2D B-mode images of the liver were analyzed with subsequent correlation with MRI-PDFF: hepatorenal index, acoustic attenuation coefficient, Nakagami coefficient parameter, shear wave viscosity, shear wave dispersion and shear wave elasticity. Ultrasound parameters were also correlated with the presence of hypertension and diabetes. RESULTS The mean (± SD) age and body mass index of the patients were 49.03 (± 12.49) and 30.12 (± 6.15), respectively. Of the aforementioned ultrasound parameters, the hepatorenal index and acoustic attenuation coefficient showed a strong correlation with MRI-PDFF derivations of hepatic steatosis, with r-values of 0.829 and 0.765, respectively. None of the remaining US parameters showed strong correlations with PDFF. Significant differences in Nakagami parameters and acoustic attenuation coefficients were found in those patients with and without hypertension. CONCLUSIONS Hepatorenal index and acoustic attenuation coefficient correlate well with MRI-PDFF-derived measurements of hepatic steatosis. Quantitative ultrasound is a promising tool for the diagnosis and assessment of patients with NAFLD.
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Key Words
- ALT, alanine aminotransferase
- AST, aspartate aminotransferase
- BMI, body mass index
- DICOM, digital imaging and communications in medicine
- HIPAA, health insurance portability and accountability act
- HRI, hepatorenal index
- Hgb A1C, hemoglobin A1C (glycated hemoglobin)
- IQ, in-phase quadrature
- IR, insulin resistance
- LDL, low-density lipoprotein
- MRI-PDFF, magnetic resonance imaging - proton density fat-fraction
- NAFLD, non-alcoholic fatty liver disease
- NASH, non-alcoholic steatohepatitis
- RF, raw radio frequency
- ROI, regions of interest
- SD, standard deviation
- T2DM, type 2 diabetes mellitus
- US, ultrasound
- liver fat quantification
- non-alcoholic fatty liver disease
- ultrasound
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Affiliation(s)
- Artem Kaliaev
- Boston University Medical Center, Department of Radiology, Boston, MA, USA,Address for correspondence: Artem Kaliaev, Department of Radiology, Boston University Medical Center, 820 Harrison Ave, Boston, MA 02118, USA.
| | - Wilson Chavez
- Boston University Medical Center, Department of Radiology, Boston, MA, USA
| | - Jorge Soto
- Boston University Medical Center, Department of Radiology, Boston, MA, USA
| | - Fahimul Huda
- Boston University Medical Center, Department of Radiology, Boston, MA, USA
| | - Hua Xie
- Ultrasound Imaging and Interventions, Philips Research North America, Cambridge, MA, USA
| | - Man Nguyen
- Ultrasound Imaging and Interventions, Philips Research North America, Cambridge, MA, USA
| | | | - Stephan Anderson
- Boston University Medical Center, Department of Radiology, Boston, MA, USA
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47
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Park J, Lee JM, Lee G, Jeon SK, Joo I. Quantitative Evaluation of Hepatic Steatosis Using Advanced Imaging Techniques: Focusing on New Quantitative Ultrasound Techniques. Korean J Radiol 2022; 23:13-29. [PMID: 34983091 PMCID: PMC8743150 DOI: 10.3348/kjr.2021.0112] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 07/26/2021] [Accepted: 08/31/2021] [Indexed: 12/12/2022] Open
Abstract
Nonalcoholic fatty liver disease, characterized by excessive accumulation of fat in the liver, is the most common chronic liver disease worldwide. The current standard for the detection of hepatic steatosis is liver biopsy; however, it is limited by invasiveness and sampling errors. Accordingly, MR spectroscopy and proton density fat fraction obtained with MRI have been accepted as non-invasive modalities for quantifying hepatic steatosis. Recently, various quantitative ultrasonography techniques have been developed and validated for the quantification of hepatic steatosis. These techniques measure various acoustic parameters, including attenuation coefficient, backscatter coefficient and speckle statistics, speed of sound, and shear wave elastography metrics. In this article, we introduce several representative quantitative ultrasonography techniques and their diagnostic value for the detection of hepatic steatosis.
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Affiliation(s)
- Junghoan Park
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea.
| | - Gunwoo Lee
- Ultrasound R&D 2 Group, Health & Medical Equipment Business, Samsung Electronics Co., Ltd., Seoul, Korea
| | - Sun Kyung Jeon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
| | - Ijin Joo
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
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48
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Offerdahl K, Huber M, Long W, Bottenus N, Nelson R, Trahey G. Occult Regions of Suppressed Coherence in Liver B-Mode Images. ULTRASOUND IN MEDICINE & BIOLOGY 2022; 48:47-58. [PMID: 34702640 PMCID: PMC9969659 DOI: 10.1016/j.ultrasmedbio.2021.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 07/01/2021] [Accepted: 09/06/2021] [Indexed: 05/03/2023]
Abstract
Ultrasound is an essential tool for diagnosing and monitoring diseases, but it can be limited by poor image quality. Lag-one coherence (LOC) is an image quality metric that can be related to signal-to-noise ratio and contrast-to-noise ratio. In this study, we examine matched LOC and B-mode images of the liver to discern patterns of low image quality, as indicated by lower LOC values, occurring beneath the abdominal wall, near out-of-plane vessels and adjacent to hyperechoic targets such the liver capsule. These regions of suppressed coherence are often occult; they present as temporally stable uniform speckle on B-mode images, but the LOC measurements in these regions suggest substantially degraded image quality. Quantitative characterization of the coherence suppression beneath the abdominal wall reveals a consistent pattern both in simulations and in vivo; sharp drops in coherence occurring beneath the abdominal wall asymptotically recover to a stable coherence at depth. Simulation studies suggest that abdominal wall reverberation clutter contributes to the initial drop in coherence but does not influence the asymptotic LOC value. Clinical implications are considered for contrast loss in B-mode imaging and estimation errors for elastography and Doppler imaging.
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Affiliation(s)
- Katelyn Offerdahl
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA.
| | - Matthew Huber
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Will Long
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Nick Bottenus
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA; Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado, USA
| | - Rendon Nelson
- Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Gregg Trahey
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA; Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
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Pirmoazen AM, Khurana A, Loening AM, Liang T, Shamdasani V, Xie H, El Kaffas A, Kamaya A. Diagnostic Performance of 9 Quantitative Ultrasound Parameters for Detection and Classification of Hepatic Steatosis in Nonalcoholic Fatty Liver Disease. Invest Radiol 2022; 57:23-32. [PMID: 34049335 DOI: 10.1097/rli.0000000000000797] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Nonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide. Quantitative ultrasound (QUS) parameters based on radiofrequency raw data show promise in quantifying liver fat. PURPOSE The aim of this study was to evaluate the diagnostic performance of 9 QUS parameters compared with magnetic resonance imaging (MRI)-estimated proton density fat fraction (PDFF) in detecting and staging hepatic steatosis in patients with or suspected of NAFLD. MATERIALS AND METHODS In this Health Insurance Portability and Accountability Act-compliant institutional review board-approved prospective study, 31 participants with or suspected of NAFLD, without other underlying chronic liver diseases (13 men, 18 women; average age, 52 years [range, 26-90 years]), were examined. The following parameters were obtained: acoustic attenuation coefficient (AC); hepatorenal index (HRI); Nakagami parameter; shear wave elastography measures such as shear wave elasticity, viscosity, and dispersion; and spectroscopy-derived parameters including spectral intercept (SI), spectral slope (SS), and midband fit (MBF). The diagnostic ability (area under the receiver operating characteristic curves and accuracy) of QUS parameters was assessed against different MRI-PDFF cutoffs (the reference standard): 6.4%, 17.4%, and 22.1%. Linearity with MRI-PDFF was evaluated with Spearman correlation coefficients (p). RESULTS The AC, SI, Nakagami, SS, HRI, and MBF strongly correlated with MRI-PDFF (P = 0.89, 0.89, 0.88, -0.87, 0.81, and 0.71, respectively [P < 0.01]), with highest area under the receiver operating characteristic curves (ranging from 0.85 to 1) for identifying hepatic steatosis using 6.4%, 17.4%, and 22.1% MRI-PDFF cutoffs. In contrast, shear wave elasticity, shear wave viscosity, and shear wave dispersion did not strongly correlate to MRI-PDFF (P = 0.45, 0.38, and 0.07, respectively) and had poor diagnostic performance. CONCLUSION The AC, Nakagami, SI, SS, MBF, and HRI best correlate with MRI-PDFF and show high diagnostic performance for detecting and classifying hepatic steatosis in our study population. SUMMARY STATEMENT Quantitative ultrasound is an accurate alternative to MRI-based techniques for evaluating hepatic steatosis in patients with or at risk of NAFLD. KEY FINDINGS Our preliminary results show that specific quantitative ultrasound parameters accurately detect different degrees of hepatic steatosis in NAFLD.
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Affiliation(s)
- Amir M Pirmoazen
- From the Department of Radiology, School of Medicine, Stanford University, California
| | - Aman Khurana
- Departments of Radiology and Biomedical Engineering, University of Kentucky, Lexington
| | - Andreas M Loening
- From the Department of Radiology, School of Medicine, Stanford University, California
| | - Tie Liang
- From the Department of Radiology, School of Medicine, Stanford University, California
| | - Vijay Shamdasani
- Strategy & Business Development, Philips Healthcare, Cambridge, Massachusetts
| | - Hua Xie
- Department of Precision Diagnosis and Image Guided Therapy, Philips Research North America, Cambridge, Massachusetts
| | - Ahmed El Kaffas
- Department of Radiology, Molecular Imaging Program at Stanford, School of Medicine, Stanford University, California
| | - Aya Kamaya
- From the Department of Radiology, School of Medicine, Stanford University, California
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50
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Gluvic Z, Tomasevic R, Bojovic K, Obradovic M, Isenovic ER. Non-alcoholic fatty liver disease: a multidisciplinary clinical practice approach—the institutional adaptation to existing Clinical Practice Guidelines. EMERGENCY AND CRITICAL CARE MEDICINE 2021; 2:12-22. [DOI: 10.1097/ec9.0000000000000016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 08/16/2021] [Indexed: 10/13/2023]
Abstract
Abstract
Non-alcoholic fatty liver disease (NAFLD) is among the most frequently encountered chronic liver diseases in everyday clinical practice. It is considered the hepatic manifestation of metabolic syndrome. Today, liver biopsy is still the gold standard for NAFLD confirmation and assessing NAFLD's possible progression to non-alcoholic steatohepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma. Because of the high prevalence of NAFLD and potential associated risks of invasive diagnostic procedures, it is of great interest to recruit the patients for liver biopsy. However, as the presence of liver fibrosis determines the further clinical course, liver biopsy is expectedly reserved for those with increased fibrosis risk. The quality of liver biopsy recruitment and patient monitoring could be significantly improved by using non-invasive tools to assess liver fibrosis presence and interactive collaboration between general practitioners, gastroenterologists, and endocrinologists. As a result, the quality of liver biopsy recruitment and patients monitoring could be significantly improved. Here, we proposed clinical practice guidelines that could be implemented for everyday clinical practice in NAFLD patients.
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Affiliation(s)
- Zoran Gluvic
- University Clinical-Hospital Centre Zemun-Belgrade, Clinic of Internal Medicine, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Ratko Tomasevic
- University Clinical-Hospital Centre Zemun-Belgrade, Clinic of Internal Medicine, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Ksenija Bojovic
- Clinical Centre of Serbia, Clinic of Infectious and Tropical Diseases, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Milan Obradovic
- Department of Radiobiology and Molecular Genetics, “VINČA” Institute of Nuclear Sciences – National Institute of thе Republic of Serbia, University of Belgrade, Belgrade, Serbia
| | - Esma R. Isenovic
- Department of Radiobiology and Molecular Genetics, “VINČA” Institute of Nuclear Sciences – National Institute of thе Republic of Serbia, University of Belgrade, Belgrade, Serbia
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