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Yuan K, Liu Q, Luo P, Wang C, Zhou Y, Qi F, Zhang Q, Huang X, Qiu B. Association of proton-density fat fraction with osteoporosis: a systematic review and meta-analysis. Osteoporos Int 2024:10.1007/s00198-024-07220-3. [PMID: 39129009 DOI: 10.1007/s00198-024-07220-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 07/29/2024] [Indexed: 08/13/2024]
Abstract
This study aimed to evaluate the correlation between measuring proton-density fat fraction (PDFF) in bone marrow using multi-echo chemical shift-encoded MRI and osteoporosis, assessing its effectiveness as a biomarker for osteoporosis. A systematic review was conducted by two independent researchers using Cochrane, PubMed, EMBASE, and Web of Science databases up to December 2023. Quality assessments were evaluated using the Cochrane risk of bias tool and the Agency for Healthcare Research and Quality (AHRQ) checklist. Fourteen studies involving 1495 patients were analyzed. The meta-analysis revealed a significant difference in PDFF values between the osteoporosis/osteopenia group and the normal control group, with a mean difference of 11.04 (95% CI: 9.17 to 12.92, Z=11.52, P < 0.00001). Measuring PDFF via MRI shows potential as an osteoporosis biomarker and may serve as a risk factor for osteoporosis. This insight opens new avenues for future diagnostic and therapeutic strategies, potentially improving osteoporosis management and patient care. OBJECTIVE This study aims to assess the correlation between measuring proton-density fat fraction (PDFF) in bone marrow using multi-echo chemical shift-encoded MRI and osteoporosis, evaluating its effectiveness as a biomarker for osteoporosis. MATERIALS AND METHODS This systematic review was carried out by two independent researchers using Cochrane, PubMed, EMBASE, and Web of Science databases up to December 2023. Quality assessments were evaluated using the Cochrane risk of bias tool and the Agency for Healthcare Research and Quality (AHRQ) checklist. RESULTS Fourteen studies involving 1495 patients were analyzed. The meta-analysis revealed a significant difference in PDFF values between the osteoporosis/osteopenia group and the normal control group, with a (MD = 11.04, 95% CI: 9.17 to 12.92, Z = 11.52, P < 0.00001). Subgroup analyses indicated that diagnostic methods, gender, and echo length did not significantly impact the PDFF-osteoporosis association. CONCLUSION PDFF measurement via MRI shows potential as an osteoporosis biomarker and may serve as a risk factor for osteoporosis. This insight opens new avenues for future diagnostic and therapeutic strategies, potentially improving osteoporosis management and patient care.
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Affiliation(s)
- Kecheng Yuan
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Qingyun Liu
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Penghui Luo
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Changliang Wang
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Yufu Zhou
- Anhui Fuqing Medical Equipment Co., Ltd., Hefei, China
| | - Fulang Qi
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Qing Zhang
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China
| | - Xiaoyan Huang
- Anhui Fuqing Medical Equipment Co., Ltd., Hefei, China
| | - Bensheng Qiu
- Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China.
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Yoon H, Kim J, Lim HJ, Lee MJ. Quantitative Liver Imaging in Children. Invest Radiol 2024:00004424-990000000-00238. [PMID: 39047265 DOI: 10.1097/rli.0000000000001101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [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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Fortier V, Mohamed A, McNabb E, Dana J, Zakarian R, Levesque IR, Reinhold C. R 2* Impact on Hepatic Fat Quantification With a Commercial Single Voxel Technique at 1.5 and 3.0 T. Can Assoc Radiol J 2024:8465371241255896. [PMID: 38832642 DOI: 10.1177/08465371241255896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024] Open
Abstract
Rationale and Objectives: Fat quantification accuracy using a commercial single-voxel high speed T2-corrected multi-echo (HISTO) technique and its robustness to R2* variations at 3.0 T, such as those introduced by iron in liver, has not been fully established. This study evaluated HISTO at 3.0 T and sought to reproduce results at 1.5 T. Methods: Phantoms were prepared with a range of fat content and R2*. Data were acquired at 1.5 T and 3.0 T, using HISTO and a Dixon technique. Fat quantification accuracy was evaluated as a function of R2*. The patient study included 239 consecutive patients. Data were acquired at 1.5 T or 3.0 T, using HISTO and Dixon techniques. The techniques were compared using Bland-Altman plots. Bias significance was evaluated using a one-sample t-test. Results: In phantoms, HISTO was accurate within 10% up to a R2* of 100 s-1 at both field strengths, while Dixon was accurate within 10% where R2* was accurately quantified (up to 350 s-1 at 1.5 T, and 550 s-1 at 3.0 T). In patients, where R2* was <100 s-1, fat quantification from both techniques agreed at 1.5 T (P = .71), but not at 3.0 T (P = .007), with a bias <1%. Conclusion: Results suggest that HISTO is reliable when R2* is <100 s-1, corresponding to patients with at most mild liver iron overload, and that it should be used with caution when R2* is >100 s-1. Dixon should be preferred for hepatic fat quantification due to its robustness to R2* variations.
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Affiliation(s)
- Véronique Fortier
- Department of Medical Imaging, McGill University Health Centre, Montreal, QC, Canada
- Diagnostic Radiology, McGill University, Montreal, QC, Canada
- Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada
- Medical Physics Unit, McGill University, Montreal, QC, Canada
| | - Ahmed Mohamed
- Radiology Department, National Cancer Institute, Cairo University, Cairo, Egypt
| | - Evan McNabb
- Department of Medical Imaging, McGill University Health Centre, Montreal, QC, Canada
| | - Jérémy Dana
- Department of Medical Imaging, McGill University Health Centre, Montreal, QC, Canada
| | - Rita Zakarian
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Ives R Levesque
- Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, Canada
- Medical Physics Unit, McGill University, Montreal, QC, Canada
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Caroline Reinhold
- Department of Medical Imaging, McGill University Health Centre, Montreal, QC, Canada
- Diagnostic Radiology, McGill University, Montreal, QC, Canada
- Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Montreal Imaging Experts Inc., Montreal, QC, Canada
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Yao S, Wei Y, Ye Z, Chen J, Duan T, Zhang Z, Song B. Hepatic Steatosis Has No Effect in Diagnosis Accuracy of LI-RADS v2018 Categorization of Hepatocellular Carcinoma in MR Imaging. J Magn Reson Imaging 2024; 59:2060-2070. [PMID: 34121266 DOI: 10.1002/jmri.27783] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 06/04/2021] [Accepted: 06/04/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND In clinical practice, hepatocellular carcinoma (HCC) is widely diagnosed by using MRI, however, whether the imaging features are affected by hepatic steatosis (HS) is still unknown. PURPOSE To investigate and compare the differences in HCC related imaging features between with- and without-HS groups, and to further determine whether HS affects the diagnosis accuracy of Liver Imaging Reporting and Data System (LI-RADS) v2018 of HCC in MRI. STUDY TYPE Prospective. SUBJECTS One hundred and seventy-one patients (mean age, 52 ± 11 years; range, 26-83 years) including 137 men and 34 women. FIELD STRENGTH/SEQUENCE 3.0 T, gradient echo (GRE). ASSESSMENT Subjects were classified as HS and non-HS groups according to MRI-proton density fat-fraction (PDFF). HS was defined as MRI-PDFF >5.6%. Three radiologists accessed HCC features and assigned LI-RADS categories in MRI independently based on LI-RADS v2018. Frequencies of HCC major features and LR categorization assignment between the two groups as well as interobserver agreement between the two radiologists were assessed. STATISTICAL TESTS Unpaired t-test, Chi-square test, Fisher's exact test, kappa statistic, intraclass correlation coefficient (ICC). A two-sided P value <0.05 was considered as statistically significant. RESULTS Major features including arterial hyperenhancement (APHE), enhancing "capsule" and nonperipheral "washout" observed between HS and non-HS groups were not significantly different (78.95% vs.78.62%, P = 0.866; 57.89% vs.52.98%, P = 0.483; and 75% vs.81.46%, P = 0.257, respectively), and the assessment of observation size showed a borderline difference (P = 0.059). No significant difference in LR-5 assignment between the two groups (69.74% vs. 72.85% for reader 1, P = 0.641; 71.05% vs. 72.19% for reader 2, P = 0.877). Interobserver agreement between the two radiologists showed almost perfect in LR-5 assignment (κ = 0.869) and size observation (ICC = 0.997). DATA CONCLUSION The diagnosis of HCC based on LI-RADS v2018 in MRI is of comparable performance regardless of HS, in which there is no significant difference in either the major imaging features or LR categorization. LEVEL OF EVIDENCE 2 Technical Efficacy Stage: 2.
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Affiliation(s)
- Shan Yao
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Wei
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Zheng Ye
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Jie Chen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Ting Duan
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Zhen Zhang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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Demondion E, Ernst O, Louvet A, Robert B, Kafri G, Langzam E, Vermersch M. Hepatic fat quantification in dual-layer computed tomography using a three-material decomposition algorithm. Eur Radiol 2024; 34:3708-3718. [PMID: 37955671 DOI: 10.1007/s00330-023-10382-z] [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: 03/02/2023] [Revised: 08/30/2023] [Accepted: 09/07/2023] [Indexed: 11/14/2023]
Abstract
OBJECTIVES The purpose of this study was to evaluate a three-material decomposition algorithm for hepatic fat quantification using a dual-layer computed tomography (DL-CT) and MRI as reference standard on a large patient cohort. METHOD A total of 104 patients were retrospectively included in our study, i.e., each patient had an MRI exam and a DL-CT exam in our institution within a maximum of 31 days. Four regions of interest (ROIs) were positioned blindly and similarly in the liver, by two independent readers on DL-CT and MRI images. For DL-CT exams, all imaging phases were included. Fat fraction agreement between CT and MRI was performed using intraclass correlation coefficients (ICC), determination coefficients R2, and Bland-Altman plots. Diagnostic performance was determined using sensitivity, specificity, and positive and negative predictive values. The cutoff for steatosis was 5%. RESULTS Correlation between MRI and CT data was excellent for all perfusion phases with ICC calculated at 0.99 for each phase. Determination coefficients R2 were also good for all perfusion phases (about 0.95 for all phases). Performance of DL-CT in the diagnosis of hepatic steatosis was good with sensitivity between 89 and 91% and specificity ranging from 75 to 80%, depending on the perfusion phase. The positive predictive value was ranging from 78 to 93% and the negative predictive value from 82 to 86%. CONCLUSION Multi-material decomposition in DL-CT allows quantification of hepatic fat fraction with a good correlation to MRI data. CLINICAL RELEVANCE STATEMENT The use of DL-CT allows for detection of hepatic steatosis. This is especially interesting as an opportunistic finding CT performed for other reasons, as early detection can help prevent or slowdown the development of liver metabolic disease. KEY POINTS • Hepatic fat fractions provided by the dual-layer CT algorithm is strongly correlated with that measured on MRI. • Dual-layer CT is accurate to detect hepatic steatosis ≥ 5%. • Dual-layer CT allows opportunistic detection of steatosis, on CT scan performed for various indications.
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Affiliation(s)
- Emilie Demondion
- Medical Imaging Department, Lille University Hospital, 2 Avenue Oscar-Lambret, Lille, France.
| | - Olivier Ernst
- Medical Imaging Department, Lille University Hospital, 2 Avenue Oscar-Lambret, Lille, France
| | - Alexandre Louvet
- Department of Gastroenterology and Hepatology, Lille University Hospital, 2 Avenue Oscar-Lambret, Lille, France
| | | | - Galit Kafri
- CT Clinical Science, Philips Healthcare, Haifa, Israel
| | - Eran Langzam
- CT Clinical Science, Philips Healthcare, Haifa, Israel
| | - Mathilde Vermersch
- Medical Imaging Department, Lille University Hospital, 2 Avenue Oscar-Lambret, Lille, France
- Medical Imaging Department, Valenciennes Hospital Center, 114 Avenue Desandrouin, Valenciennes, France
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Wang X, Zhang S, Huang Z, Tian G, Liu X, Chen L, An L, Li X, Liu N, Ji Y, Han Y. Influence of Gadoxetate disodium to the hepatic proton density fat fraction quantified with the Dixon sequences in a rabbit model. Abdom Radiol (NY) 2024:10.1007/s00261-024-04320-w. [PMID: 38683216 DOI: 10.1007/s00261-024-04320-w] [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: 01/17/2024] [Revised: 03/28/2024] [Accepted: 03/29/2024] [Indexed: 05/01/2024]
Abstract
OBJECTIVE To study the impact of Gx on quantification of hepatic fat contents under metabolic dysfunction-associated steatotic liver disease (MASLD) imaged on VIBE Dixon in hepatobiliary specific phase. METHODS Forty-two rabbits were randomly divided into control group (n = 10) and high-fat diet group (n = 32). Imaging was performed before enhancement (Pre-Gx) and at the 13th (Post-Gx13) and 17th (Post-Gx17) min after Gx enhancement with 2E- and 6E-VIBE Dixon to determine hepatic proton density fat fractions (PDFF). PDFFs were compared with vacuole percentage (VP) measured under histopathology. RESULTS 33 animals were evaluated and including control group (n = 11) and MASLD group (n = 22). Pre-Gx, Post-Gx13, Post-Gx17 PDFFs under 6E-VIBE Dixon had strong correlations with VPs (r2 = 0.8208-0.8536). PDFFs under 2E-VIBE Dixon were reduced significantly (P < 0.001) after enhancement (r2 = 0.7991/0.8014) compared with that before enhancement (r2 = 0.7643). There was no significant difference between PDFFs of Post-Gx13 and Post-Gx17 (P = 0.123) for which the highest consistency being found with 6E-VIBE Dixon before enhancement (r2 = 0.8536). The signal intensity of the precontrast compared with the postcontrast, water image under 2E-VIBE Dixon increased significantly (P < 0.001), fat image showed no significant difference (P = 0.754). CONCLUSION 2E- and 6E-VIBE Dixon can obtain accurate PDFFs in the hepatobiliary specific phase from 13 to 17th min after Gx enhancement. On 2E-VIBE Dixon (FA = 10°), effective minimization of T1 Bias by the Gx administration markedly improved the accuracy of the hepatic PDFF quantification.
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Affiliation(s)
- Xia Wang
- Department of Radiology, Xi'an GaoXin Hospital, Xi'an Jiao Tong University, South Tuanjie Rd 16, Xi'an, 710075, Shaanxi, China
| | - Sheng Zhang
- Department of Radiology, Xi'an GaoXin Hospital, Xi'an Jiao Tong University, South Tuanjie Rd 16, Xi'an, 710075, Shaanxi, China
| | - Zhe Huang
- Department of Radiology, Xi'an GaoXin Hospital, Xi'an Jiao Tong University, South Tuanjie Rd 16, Xi'an, 710075, Shaanxi, China
| | - Gang Tian
- Department of Radiology, Xi'an GaoXin Hospital, Xi'an Jiao Tong University, South Tuanjie Rd 16, Xi'an, 710075, Shaanxi, China
| | - Xiaofan Liu
- Department of Radiology, Xi'an GaoXin Hospital, Xi'an Jiao Tong University, South Tuanjie Rd 16, Xi'an, 710075, Shaanxi, China
| | - Lijun Chen
- Department of Radiology, Xi'an GaoXin Hospital, Xi'an Jiao Tong University, South Tuanjie Rd 16, Xi'an, 710075, Shaanxi, China
| | - Liang An
- Department of Clinical Laboratory, Xi'an GaoXin Hospital, Xi'an, China
| | - Xumiao Li
- Department of Pathology, Xi'an GaoXin Hospital, Xi'an, China
| | - Ningna Liu
- Department of Pathology, Xi'an GaoXin Hospital, Xi'an, China
| | - Yang Ji
- Department of Imaging Center, First Affiliated Hospital, Xi'an Medical University, Shaanxi, China.
| | - Yuedong Han
- Department of Radiology, Xi'an GaoXin Hospital, Xi'an Jiao Tong University, South Tuanjie Rd 16, Xi'an, 710075, Shaanxi, China.
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Byenfeldt M, Kihlberg J, Nasr P, Grönlund C, Lindam A, Bartholomä WC, Lundberg P, Ekstedt M. Altered probe pressure and body position increase diagnostic accuracy for men and women in detecting hepatic steatosis using quantitative ultrasound. Eur Radiol 2024:10.1007/s00330-024-10655-1. [PMID: 38459346 DOI: 10.1007/s00330-024-10655-1] [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: 11/14/2023] [Revised: 12/14/2023] [Accepted: 01/16/2024] [Indexed: 03/10/2024]
Abstract
OBJECTIVES To evaluate the diagnostic performance of ultrasound guided attenuation parameter (UGAP) for evaluating liver fat content with different probe forces and body positions, in relation to sex, and compared with proton density fat fraction (PDFF). METHODS We prospectively enrolled a metabolic dysfunction-associated steatotic liver disease (MASLD) cohort that underwent UGAP and PDFF in the autumn of 2022. Mean UGAP values were obtained in supine and 30° left decubitus body position with normal 4 N and increased 30 N probe force. The diagnostic performance was evaluated by the area under the receiver operating characteristic curve (AUC). RESULTS Among 60 individuals (mean age 52.9 years, SD 12.9; 30 men), we found the best diagnostic performance with increased probe force in 30° left decubitus position (AUC 0.90; 95% CI 0.82-0.98) with a cut-off of 0.58 dB/cm/MHz. For men, the best performance was in supine (AUC 0.91; 95% CI 0.81-1.00) with a cut-off of 0.60 dB/cm/MHz, and for women, 30° left decubitus position (AUC 0.93; 95% CI 0.83-1.00), with a cut-off 0.56 dB/cm/MHz, and increased 30 N probe force for both genders. No difference was in the mean UGAP value when altering body position. UGAP showed good to excellent intra-reproducibility (Intra-class correlation 0.872; 95% CI 0.794-0.921). CONCLUSION UGAP provides excellent diagnostic performance to detect liver fat content in metabolic dysfunction-associated steatotic liver diseases, with good to excellent intra-reproducibility. Regardless of sex, the highest diagnostic accuracy is achieved with increased probe force with men in supine and women in 30° left decubitus position, yielding different cut-offs. CLINICAL RELEVANCE STATEMENT The ultrasound method ultrasound-guided attenuation parameter shows excellent diagnostic accuracy and performs with good to excellent reproducibility. There is a possibility to alter body position and increase probe pressure, and different performances for men and women should be considered for the highest accuracy. KEY POINTS • There is a possibility to alter body position when performing the ultrasound method ultrasound-guided attenuation parameter. • Increase probe pressure for the highest accuracy. • Different performances for men and women should be considered.
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Affiliation(s)
- Marie Byenfeldt
- Department of Radiology in Östersund, Östersund, Sweden.
- Department of Radiation Science, Umeå University, Umeå, Sweden.
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
| | - Johan Kihlberg
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
- Department of Radiology in Linköping, Linköping, Sweden
| | - Patrik Nasr
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
- Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | | | - Anna Lindam
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Wolf C Bartholomä
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
- Department of Radiology in Linköping, Linköping, Sweden
| | - Peter Lundberg
- Department of Radiation Physics, Linköping University, Linköping, Sweden
- Department of Medical and Health Science in Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
| | - Mattias Ekstedt
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
- Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
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Gupta A, Dixit R, Prakash A. Non-invasive hepatic fat quantification: Can multi-echo Dixon help? Radiol Bras 2024; 57:e20230125. [PMID: 38993969 PMCID: PMC11235074 DOI: 10.1590/0100-3984.2023.0125] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 12/12/2023] [Accepted: 01/24/2024] [Indexed: 07/13/2024] Open
Abstract
Objective To evaluate the diagnostic accuracy of multi-echo Dixon magnetic resonance imaging (MRI) in hepatic fat quantification, in comparison with that of magnetic resonance spectroscopy (MRS), on 3.0-T MRI. Materials and Methods Fifty-five adults with no known liver disease underwent MRI in a 3.0-T scanner for determination of the hepatic fat fraction, with two techniques: multi-echo Dixon, in a manually drawn region of interest (ROI) and in the entire liver parenchyma (automated segmentation); and MRS. The diagnostic accuracy and cutoff value for multi-echo Dixon were determined, with MRS being used as the reference standard. Results The mean fat fraction obtained by multi-echo Dixon in the manually drawn ROI and in the entire liver was 5.2 ± 5.8% and 6.6 ± 5.2%, respectively, whereas the mean hepatic fat fraction obtained by MRS was 5.7 ± 6.4%. A very strong positive correlation and good agreement were observed between MRS and multi-echo Dixon, for the ROI (r = 0.988, r2 = 0.978, p < 0.001) and for the entire liver parenchyma (r = 0.960, r2 = 0.922, p < 0.001). A moderate positive correlation was observed between the hepatic fat fraction and body mass index of the participants, regardless of the fat estimation technique employed. Conclusion For hepatic fat quantification, multi-echo Dixon MRI demonstrated a very strong positive correlation and good agreement with MRS (often considered the gold-standard noninvasive technique). Because multi-echo Dixon MRI is more readily available than is MRS, it can be used as a rapid tool for hepatic fat quantification, especially when the hepatic fat distribution is not homogeneous.
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Affiliation(s)
- Akarshi Gupta
- Department of Radiodiagnosis, Lok Nayak Hospital - Maulana Azad
Medical College, New Delhi, India
| | - Rashmi Dixit
- Department of Radiodiagnosis, Lok Nayak Hospital - Maulana Azad
Medical College, New Delhi, India
| | - Anjali Prakash
- Department of Radiodiagnosis, Lok Nayak Hospital - Maulana Azad
Medical College, New Delhi, India
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Kupczyk PA, Kurt D, Endler C, Luetkens JA, Kukuk GM, Fronhoffs F, Fischer HP, Attenberger UI, Pieper CC. MRI proton density fat fraction for estimation of tumor grade in steatotic hepatocellular carcinoma. Eur Radiol 2023; 33:8974-8985. [PMID: 37368108 PMCID: PMC10667464 DOI: 10.1007/s00330-023-09864-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: 02/12/2023] [Revised: 04/03/2023] [Accepted: 05/15/2023] [Indexed: 06/28/2023]
Abstract
OBJECTIVES Image-based detection of intralesional fat in focal liver lesions has been established in diagnostic guidelines as a feature indicative of hepatocellular carcinoma (HCC) and associated with a favorable prognosis. Given recent advances in MRI-based fat quantification techniques, we investigated a possible relationship between intralesional fat content and histologic tumor grade in steatotic HCCs. METHODS Patients with histopathologically confirmed HCC and prior MRI with proton density fat fraction (PDFF) mapping were retrospectively identified. Intralesional fat of HCCs was assessed using an ROI-based analysis and the median fat fraction of steatotic HCCs was compared between tumor grades G1-3 with non-parametric testing. ROC analysis was performed in case of statistically significant differences (p < 0.05). Subgroup analyses were conducted for patients with/without liver steatosis and with/without liver cirrhosis. RESULTS A total of 57 patients with steatotic HCCs (62 lesions) were eligible for analysis. The median fat fraction was significantly higher for G1 lesions (median [interquartile range], 7.9% [6.0─10.7%]) than for G2 (4.4% [3.2─6.6%]; p = .001) and G3 lesions (4.7% [2.8─7.8%]; p = .036). PDFF was a good discriminator between G1 and G2/3 lesions (AUC .81; cut-off 5.8%, sensitivity 83%, specificity 68%) with comparable results in patients with liver cirrhosis. In patients with liver steatosis, intralesional fat content was higher than in the overall sample, with PDFF performing better in distinguishing between G1 and G2/3 lesions (AUC .92; cut-off 8.8%, sensitivity 83%, specificity 91%). CONCLUSIONS Quantification of intralesional fat using MRI PDFF mapping allows distinction between well- and less-differentiated steatotic HCCs. CLINICAL RELEVANCE PDFF mapping may help optimize precision medicine as a tool for tumor grade assessment in steatotic HCCs. Further investigation of intratumoral fat content as a potential prognostic indicator of treatment response is encouraged. KEY POINTS • MRI proton density fat fraction mapping enables distinction between well- (G1) and less- (G2 and G3) differentiated steatotic hepatocellular carcinomas. • In a retrospective single-center study with 62 histologically proven steatotic hepatocellular carcinomas, G1 tumors showed a higher intralesional fat content than G2 and G3 tumors (7.9% vs. 4.4% and 4.7%; p = .004). • In liver steatosis, MRI proton density fat fraction mapping was an even better discriminator between G1 and G2/G3 steatotic hepatocellular carcinomas.
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Affiliation(s)
- Patrick Arthur Kupczyk
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
- Quantitative Imaging Lab Bonn (QILaB), Bonn, Germany.
| | - Darius Kurt
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Christoph Endler
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Quantitative Imaging Lab Bonn (QILaB), Bonn, Germany
| | - Julian Alexander Luetkens
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Quantitative Imaging Lab Bonn (QILaB), Bonn, Germany
| | - Guido Matthias Kukuk
- Department of Radiology, Kantonsspital Graubünden, Loestrasse 170, 7000, Chur, Switzerland
| | - Florian Fronhoffs
- Institute of Pathology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Hans-Peter Fischer
- Institute of Pathology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Ulrike Irmgard Attenberger
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Claus Christian Pieper
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
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Fujita S, Sano K, Cruz G, Velasco C, Kawasaki H, Fukumura Y, Yoneyama M, Suzuki A, Yamamoto K, Morita Y, Arai T, Fukunaga I, Uchida W, Kamagata K, Abe O, Kuwatsuru R, Saiura A, Ikejima K, Botnar R, Prieto C, Aoki S. MR Fingerprinting for Contrast Agent-free and Quantitative Characterization of Focal Liver Lesions. Radiol Imaging Cancer 2023; 5:e230036. [PMID: 37999629 DOI: 10.1148/rycan.230036] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2023]
Abstract
Purpose To evaluate the feasibility of liver MR fingerprinting (MRF) for quantitative characterization and diagnosis of focal liver lesions. Materials and Methods This single-site, prospective study included 89 participants (mean age, 62 years ± 15 [SD]; 45 women, 44 men) with various focal liver lesions who underwent MRI between October 2021 and August 2022. The participants underwent routine clinical MRI, non-contrast-enhanced liver MRF, and reference quantitative MRI with a 1.5-T MRI scanner. The bias and repeatability of the MRF measurements were assessed using linear regression, Bland-Altman plots, and coefficients of variation. The diagnostic capability of MRF-derived T1, T2, T2*, proton density fat fraction (PDFF), and a combination of these metrics to distinguish benign from malignant lesions was analyzed according to the area under the receiver operating characteristic curve (AUC). Results Liver MRF measurements showed moderate to high agreement with reference measurements (intraclass correlation = 0.94, 0.77, 0.45, and 0.61 for T1, T2, T2*, and PDFF, respectively), with underestimation of T2 values (mean bias in lesion = -0.5%, -29%, 5.8%, and -8.2% for T1, T2, T2*, and PDFF, respectively). The median coefficients of variation for repeatability of T1, T2, and T2* values were 2.5% (IQR, 3.6%), 3.1% (IQR, 5.6%), and 6.6% (IQR, 13.9%), respectively. After considering multicollinearity, a combination of MRF measurements showed a high diagnostic performance in differentiating benign from malignant lesions (AUC = 0.92 [95% CI: 0.86, 0.98]). Conclusion Liver MRF enabled the quantitative characterization of various focal liver lesions in a single breath-hold acquisition. Keywords: MR Imaging, Abdomen/GI, Liver, Imaging Sequences, Technical Aspects, Tissue Characterization, Technology Assessment, Diagnosis, Liver Lesions, MR Fingerprinting, Quantitative Characterization Supplemental material is available for this article. © RSNA, 2023.
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Affiliation(s)
- Shohei Fujita
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Katsuhiro Sano
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Gastao Cruz
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Carlos Velasco
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Hideo Kawasaki
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Yuki Fukumura
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Masami Yoneyama
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Akiyoshi Suzuki
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Kotaro Yamamoto
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Yuichi Morita
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Takashi Arai
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Issei Fukunaga
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Wataru Uchida
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Koji Kamagata
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Osamu Abe
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Ryohei Kuwatsuru
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Akio Saiura
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Kenichi Ikejima
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - René Botnar
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Claudia Prieto
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
| | - Shigeki Aoki
- From the Departments of Radiology (S.F., K.S., H.K., A. Suzuki, K.Y., Y.M., T.A., I.F., W.U., K.K., R.K., S.A.), Human Pathology (Y.F.), Hepatobiliary-Pancreatic Surgery (A. Saiura), and Gastroenterology (K.I.), Juntendo University School of Medicine, 1-2-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, The University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, England (G.C., C.V., R.B., C.P.); Department of Radiology, University of Michigan, Ann Arbor, Mich (G.C.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.B., C.P.); and Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile (R.B., C.P.)
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Fellinger P, Beiglböck H, Semmler G, Pfleger L, Smajis S, Baumgartner C, Gajdosik M, Marculescu R, Vila G, Winhofer Y, Scherer T, Trauner M, Kautzky-Willer A, Krssak M, Krebs M, Wolf P. Increased GH/IGF-I Axis Activity Relates to Lower Hepatic Lipids and Phosphor Metabolism. J Clin Endocrinol Metab 2023; 108:e989-e997. [PMID: 37104943 PMCID: PMC10505545 DOI: 10.1210/clinem/dgad206] [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: 12/30/2022] [Revised: 03/25/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023]
Abstract
CONTEXT Non-alcoholic fatty liver disease (NAFLD) is a leading causes of liver-related morbidity and mortality. While data on acromegaly, a state of chronic growth hormone (GH)/insulin-like growth factor I (IGF-I) excess, suggest an inverse relationship with intrahepatic lipid (IHL) content, less is known about the impact of the GH/IGF-I axis on IHL, lipid composition, and phosphor metabolites in individuals without disorders of GH secretion. OBJECTIVE The aim was to investigate the relation between activity of the GH/IGF-I axis and IHL content and phosphor metabolism. METHODS We performed a cross-sectional study in 59 otherwise metabolically healthy individuals (30 females), of which 16 met the criteria of NAFLD with IHL of ≥5.6%. The GH/IGF-I axis was evaluated in a fasting state and during an oral glucose tolerance test (OGTT). Insulin sensitivity was estimated by validated indices. IHL, lipid composition (unsaturation index), and phosphate metabolites were analyzed by using 1H/31P magnetic resonance spectroscopy. RESULTS In the overall cohort (40.6 ± 15 years; body mass index: 24.5 ± 3 kg/m2; IGF-I: 68.0 ± 17% upper limit of normal), fasting GH (R = -0.31; P = .02), GH during oral glucose tolerance test (R = -0.51; P < .01), and IGF-I (R = -0.28; P = .03) inversely correlated with IHL. GH levels during OGTT were significantly lower in NAFLD than in controls (47.7 [22; 143] ng/mL/min vs 16.8 [7; 32] ng/mL/min; P = .003). GH/IGF-I axis activity correlated with lipid composition and with phosphor metabolites. In multiple regression analysis, the GH/IGF-I axis activity was a strong predictor for IHL and lipid composition independent from insulin sensitivity. CONCLUSION GH/IGF-I axis activity impacts hepatic lipid and phosphate metabolism in individuals without disorders in GH secretion. Lower GH axis activity is associated with higher IHL and an unfavorable lipid composition, probably mediated by changes in hepatic energy metabolism.
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Affiliation(s)
- Paul Fellinger
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Hannes Beiglböck
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Georg Semmler
- Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Lorenz Pfleger
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
- Centre of Excellence-High Field MR, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Sabina Smajis
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Clemens Baumgartner
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Martin Gajdosik
- Centre of Excellence-High Field MR, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Rodrig Marculescu
- Department of Laboratory Medicine, Medical University of Vienna, 1090 Vienna, Austria
| | - Greisa Vila
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Yvonne Winhofer
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Thomas Scherer
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Michael Trauner
- Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Alexandra Kautzky-Willer
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Martin Krssak
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
- Centre of Excellence-High Field MR, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Michael Krebs
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
| | - Peter Wolf
- Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, 1090 Vienna, Austria
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12
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Engelke K, Chaudry O, Gast L, Eldib MAB, Wang L, Laredo JD, Schett G, Nagel AM. Magnetic resonance imaging techniques for the quantitative analysis of skeletal muscle: State of the art. J Orthop Translat 2023; 42:57-72. [PMID: 37654433 PMCID: PMC10465967 DOI: 10.1016/j.jot.2023.07.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 07/04/2023] [Accepted: 07/19/2023] [Indexed: 09/02/2023] Open
Abstract
Background Magnetic resonance imaging (MRI) is the dominant 3D imaging modality to quantify muscle properties in skeletal muscle disorders, in inherited and acquired muscle diseases, and in sarcopenia, in cachexia and frailty. Methods This review covers T1 weighted and Dixon sequences, introduces T2 mapping, diffusion tensor imaging (DTI) and non-proton MRI. Technical concepts, strengths, limitations and translational aspects of these techniques are discussed in detail. Examples of clinical applications are outlined. For comparison 31P-and 13C-MR Spectroscopy are also addressed. Results MRI technology provides a rich toolset to assess muscle deterioration. In addition to classical measures such as muscle atrophy using T1 weighted imaging and fat infiltration using Dixon sequences, parameters characterizing inflammation from T2 maps, tissue sodium using non-proton MRI techniques or concentration or fiber architecture using diffusion tensor imaging may be useful for an even earlier diagnosis of the impairment of muscle quality. Conclusion Quantitative MRI provides new options for muscle research and clinical applications. Current limitations that also impair its more widespread use in clinical trials are lack of standardization, ambiguity of image segmentation and analysis approaches, a multitude of outcome parameters without a clear strategy which ones to use and the lack of normal data.
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Affiliation(s)
- Klaus Engelke
- Department of Medicine III, Friedrich-Alexander University of Erlangen-Nürnberg, University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
- Institute of Medical Physics (IMP), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Henkestr. 91, 91052, Erlangen, Germany
- Clario Inc, Germany
| | - Oliver Chaudry
- Department of Medicine III, Friedrich-Alexander University of Erlangen-Nürnberg, University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
| | - Lena Gast
- Institute of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Maximiliansplatz 3, 91054, Erlangen, Germany
| | | | - Ling Wang
- Department of Radiology, Beijing Jishuitan Hospital, Beijing, China
| | - Jean-Denis Laredo
- Service d’Imagerie Médicale, Institut Mutualiste Montsouris & B3OA, UMR CNRS 7052, Inserm U1271 Université de Paris-Cité, Paris, France
| | - Georg Schett
- Department of Medicine III, Friedrich-Alexander University of Erlangen-Nürnberg, University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
| | - Armin M. Nagel
- Institute of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Maximiliansplatz 3, 91054, Erlangen, Germany
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
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13
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Jiang Y, Zou J, Fan F, Yang P, Ma L, Gan T, Wang S, Zhang J. Application of multi-echo Dixon and MRS in quantifying hepatic fat content and staging liver fibrosis. Sci Rep 2023; 13:12555. [PMID: 37532757 PMCID: PMC10397311 DOI: 10.1038/s41598-023-39361-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 07/24/2023] [Indexed: 08/04/2023] Open
Abstract
This study associated the liver proton density fat fraction (PDFF), measured by multi-echo Dixon (ME-Dixon) and breath-hold single-voxel high-speed T2-corrected multi-echo 1H magnetic resonance spectroscopy (HISTO) at 1.5 T, with serum biomarkers and liver fibrosis stages. This prospective study enrolled 75 patients suspected of liver fibrosis and scheduled for liver biopsy and 23 healthy participants with normal liver function. The participant underwent ME-Dixon and HISTO scanning. The agreement of PDFF measured by ME-Dixon (PDFF-D) and HISTO (PDFF-H) were compared. Correlations between PDFF and serum fat biomarkers (total cholesterol, triglyceride, and high- and low-density lipoproteins) and the liver fibrosis stages were assessed. PDFF were compared among the liver fibrosis stages (F0-F4) based on clinical liver biopsies. The Bland-Altman plot showed agreement between PDFF-D and PDFF-H(LoA, - 4.44 to 6.75), which have high consistency (ICC 0.752, P < 0.001). The correlations with the blood serum markers were mild to moderate (PDFF-H: r = 0.261-0.410, P < 0.01; PDFF-D: r = 0.265-0.367, P < 0.01). PDFF-D, PDFF-H, and steatosis were distributed similarly among the liver fibrosis stages. PDFF-H showed a slight negative correlation with the liver fibrosis stages (r = - 0.220, P = 0.04). Both ME-Dixon and HISTO sequences measured liver fat content noninvasively. Liver fat content was not directly associated with liver fibrosis stages.
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Affiliation(s)
- Yanli Jiang
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, People's Republic of China
| | - Jie Zou
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, People's Republic of China
| | - Fengxian Fan
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, People's Republic of China
| | - Pin Yang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, People's Republic of China
| | - Laiyang Ma
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, People's Republic of China
| | - Tiejun Gan
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, People's Republic of China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, Shanghai, People's Republic of China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China.
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, People's Republic of China.
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14
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Huang Y, Stinson SE, Juel HB, Lund MAV, Holm LA, Fonvig CE, Nielsen T, Grarup N, Pedersen O, Christiansen M, Chabanova E, Thomsen HS, Krag A, Stender S, Holm JC, Hansen T. An adult-based genetic risk score for liver fat associates with liver and plasma lipid traits in children and adolescents. Liver Int 2023; 43:1772-1782. [PMID: 37208954 DOI: 10.1111/liv.15613] [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: 10/14/2022] [Revised: 04/27/2023] [Accepted: 05/05/2023] [Indexed: 05/21/2023]
Abstract
BACKGROUND & AIMS Genome-wide association studies have identified steatogenic variants that also showed pleiotropic effects on cardiometabolic traits in adults. We investigated the effect of eight previously reported genome-wide significant steatogenic variants, individually and combined in a weighted genetic risk score (GRS), on liver and cardiometabolic traits, and the predictive ability of the GRS for hepatic steatosis in children and adolescents. APPROACH & RESULTS Children and adolescents with overweight (including obesity) from an obesity clinic group (n = 1768) and a population-based group (n = 1890) were included. Cardiometabolic risk outcomes and genotypes were obtained. Liver fat was quantified using 1 H-MRS in a subset of 727 participants. Variants in PNPLA3, TM6SF2, GPAM and TRIB1 were associated with higher liver fat (p < .05) and with distinct patterns of plasma lipids. The GRS was associated with higher liver fat content, plasma concentrations of alanine transaminase (ALT), aspartate aminotransferase (AST) and favourable plasma lipid levels. The GRS was associated with higher prevalence of hepatic steatosis (defined as liver fat ≥5.0%) (odds ratio per 1-SD unit: 2.17, p = 9.7E-10). A prediction model for hepatic steatosis including GRS alone yielded an area under the curve (AUC) of 0.78 (95% CI 0.76-0.81). Combining the GRS with clinical measures (waist-to-height ratio [WHtR] SDS, ALT, and HOMA-IR) increased the AUC up to 0.86 (95% CI 0.84-0.88). CONCLUSIONS The genetic predisposition for liver fat accumulation conferred risk of hepatic steatosis in children and adolescents. The liver fat GRS has potential clinical utility for risk stratification.
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Affiliation(s)
- Yun Huang
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sara E Stinson
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Helene Baek Juel
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Morten A V Lund
- The Children's Obesity Clinic, accredited European Centre for Obesity Management, Department of Pediatrics, Copenhagen University Hospital Holbaek, Copenhagen, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Louise Aas Holm
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Children's Obesity Clinic, accredited European Centre for Obesity Management, Department of Pediatrics, Copenhagen University Hospital Holbaek, Copenhagen, Denmark
| | - Cilius E Fonvig
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Children's Obesity Clinic, accredited European Centre for Obesity Management, Department of Pediatrics, Copenhagen University Hospital Holbaek, Copenhagen, Denmark
- Department of Pediatrics, Kolding Hospital a Part of Lillebaelt Hospital, Kolding, Denmark
| | - Trine Nielsen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Copenhagen University Hospital Herlev Gentofte, Copenhagen, Denmark
| | - Michael Christiansen
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department for Congenital Disorders, Statens Serum Institute, Copenhagen, Denmark
| | - Elizaveta Chabanova
- Department of Diagnostic Radiology, Copenhagen University Hospital Herlev Gentofte, Copenhagen, Denmark
| | - Henrik S Thomsen
- Department of Diagnostic Radiology, Copenhagen University Hospital Herlev Gentofte, Copenhagen, Denmark
| | - Aleksander Krag
- Center for Liver Research, Department of Gastroenterology and Hepatology, Odense University Hospital, Odense, Denmark
- Institute of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Stefan Stender
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
| | - Jens-Christian Holm
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Children's Obesity Clinic, accredited European Centre for Obesity Management, Department of Pediatrics, Copenhagen University Hospital Holbaek, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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15
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Cadenas-Sanchez C, Medrano M, Villanueva A, Cabeza R, Idoate F, Osés M, Rodríguez-Vigil B, Álvarez de Eulate N, Alberdi Aldasoro N, Ortega FB, Labayen I. Differences in specific abdominal fat depots between metabolically healthy and unhealthy children with overweight/obesity: The role of cardiorespiratory fitness. Scand J Med Sci Sports 2023. [PMID: 37081735 DOI: 10.1111/sms.14372] [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: 11/17/2022] [Revised: 03/11/2023] [Accepted: 04/03/2023] [Indexed: 04/22/2023]
Abstract
OBJECTIVES Fat depots localization has a critical role in the metabolic health status of adults. Nevertheless, whether that is also the case in children remains under-studied. Therefore, the aims of this study were: (i) to examine the differences between metabolically healthy (MHO) and unhealthy (MUO) overweight/obesity phenotypes on specific abdominal fat depots, and (ii) to further explore whether cardiorespiratory fitness plays a major role in the differences between metabolic phenotypes among children with overweight/obesity. METHODS A total of 114 children with overweight/obesity (10.6 ± 1.1 years, 62 girls) were included. Children were classified as MHO (n = 68) or MUO. visceral (VAT), abdominal subcutaneous (ASAT), intermuscular abdominal (IMAAT), psoas, hepatic, pancreatic, and lumbar bone marrow adipose tissues were measured by magnetic resonance imaging. Cardiorespiratory fitness was assessed using the 20 m shuttle run test. RESULTS MHO children had lower VAT and ASAT contents and psoas fat fraction compared to MUO children (difference = 12.4%-25.8%, all p < 0.035). MUO-unfit had more VAT and ASAT content than those MUO-fit and MHO-fit (difference = 34.8%-45.3%, all p < 0.044). MUO-unfit shows also greater IMAAT fat fraction than those MUO-fit and MHO-fit peers (difference = 16.4%-13.9% respectively, all p ≤ 0.001). In addition, MHO-unfit presented higher IMAAT fat fraction than MHO-fit (difference = 13.4%, p < 0.001). MUO-unfit presented higher psoas fat fraction than MHO-fit (difference = 29.1%, p = 0.008). CONCLUSIONS VAT together with ASAT and psoas fat fraction, were lower in MHO than in MUO children. Further, we also observed that being fit, regardless of metabolic phenotype, has a protective role over the specific abdominal fat depots among children with overweight/obesity.
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Affiliation(s)
- Cristina Cadenas-Sanchez
- Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain
- Research Institute for Innovation & Sustainable Food Chain Development (IS-FOOD), Public University of Navarre. Department of Health Sciences, Public University of Navarre, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
| | - María Medrano
- Research Institute for Innovation & Sustainable Food Chain Development (IS-FOOD), Public University of Navarre. Department of Health Sciences, Public University of Navarre, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
| | - Arantxa Villanueva
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Smart Cities Institute, Public University of Navarre, Pamplona, Spain
- Department of Electrical, Electronic and Communications Engineering, Public University of Navarre Pamplona, Pamplona, Spain
| | - Rafael Cabeza
- Department of Electrical, Electronic and Communications Engineering, Public University of Navarre Pamplona, Pamplona, Spain
| | - Fernando Idoate
- Radiology Department, Mutua Navarra, Pamplona, Spain
- Department of Health Sciences, Public University of Navarre, Pamplona, Spain
| | - Maddi Osés
- Research Institute for Innovation & Sustainable Food Chain Development (IS-FOOD), Public University of Navarre. Department of Health Sciences, Public University of Navarre, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Beatriz Rodríguez-Vigil
- Osakidetza Basque Health Service, Osatek, Bioaraba Health Research Institute, Vitoria-Gasteiz, Spain
| | - Natalia Álvarez de Eulate
- Sección de Radiología Musculoesquelética, Servicio de Radiología, Hospital Universitario de Navarra, Pamplona, Spain
| | - Nerea Alberdi Aldasoro
- Sección de Radiología Musculoesquelética, Servicio de Radiología, Hospital Universitario de Navarra, Pamplona, Spain
| | - Francisco B Ortega
- Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Idoia Labayen
- Research Institute for Innovation & Sustainable Food Chain Development (IS-FOOD), Public University of Navarre. Department of Health Sciences, Public University of Navarre, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain
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Low G, Ferguson C, Locas S, Tu W, Manolea F, Sam M, Wilson MP. Multiparametric MR assessment of liver fat, iron, and fibrosis: a concise overview of the liver "Triple Screen". Abdom Radiol (NY) 2023; 48:2060-2073. [PMID: 37041393 DOI: 10.1007/s00261-023-03887-0] [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: 02/05/2023] [Revised: 03/12/2023] [Accepted: 03/13/2023] [Indexed: 04/13/2023]
Abstract
Chronic liver disease (CLD) is a common source of morbidity and mortality worldwide. Non-alcoholic fatty liver disease (NAFLD) serves as a major cause of CLD with a rising annual prevalence. Additionally, iron overload can be both a cause and effect of CLD with a negative synergistic effect when combined with NAFLD. The development of state-of-the-art multiparametric MR solutions has led to a change in the diagnostic paradigm in CLD, shifting from traditional liver biopsy to innovative non-invasive methods for providing accurate and reliable detection and quantification of the disease burden. Novel imaging biomarkers such as MRI-PDFF for fat, R2 and R2* for iron, and liver stiffness for fibrosis provide important information for diagnosis, surveillance, risk stratification, and treatment. In this article, we provide a concise overview of the MR concepts and techniques involved in the detection and quantification of liver fat, iron, and fibrosis including their relative strengths and limitations and discuss a practical abbreviated MR protocol for clinical use that integrates these three MR biomarkers into a single simplified MR assessment. Multiparametric MR techniques provide accurate and reliable non-invasive detection and quantification of liver fat, iron, and fibrosis. These techniques can be combined in a single abbreviated MR "Triple Screen" assessment to offer a more complete metabolic imaging profile of CLD.
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Affiliation(s)
- Gavin Low
- Department of Radiology and Diagnostic Imaging, University of Alberta Hospital, WMC 2B2.41 8440-112 ST, Edmonton, AB, T6G2B7, Canada
| | - Craig Ferguson
- Department of Radiology and Diagnostic Imaging, University of Alberta Hospital, WMC 2B2.41 8440-112 ST, Edmonton, AB, T6G2B7, Canada
| | - Stephanie Locas
- Department of Radiology and Diagnostic Imaging, University of Alberta Hospital, WMC 2B2.41 8440-112 ST, Edmonton, AB, T6G2B7, Canada
| | - Wendy Tu
- Department of Radiology and Diagnostic Imaging, University of Alberta Hospital, WMC 2B2.41 8440-112 ST, Edmonton, AB, T6G2B7, Canada
| | - Florin Manolea
- Department of Radiology and Diagnostic Imaging, University of Alberta Hospital, WMC 2B2.41 8440-112 ST, Edmonton, AB, T6G2B7, Canada
| | - Medica Sam
- Department of Radiology and Diagnostic Imaging, University of Alberta Hospital, WMC 2B2.41 8440-112 ST, Edmonton, AB, T6G2B7, Canada
| | - Mitchell P Wilson
- Department of Radiology and Diagnostic Imaging, University of Alberta Hospital, WMC 2B2.41 8440-112 ST, Edmonton, AB, T6G2B7, Canada.
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Levakov G, Kaplan A, Yaskolka Meir A, Rinott E, Tsaban G, Zelicha H, Blüher M, Ceglarek U, Stumvoll M, Shelef I, Avidan G, Shai I. The effect of weight loss following 18 months of lifestyle intervention on brain age assessed with resting-state functional connectivity. eLife 2023; 12:e83604. [PMID: 37022140 PMCID: PMC10174688 DOI: 10.7554/elife.83604] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 03/31/2023] [Indexed: 04/07/2023] Open
Abstract
Background Obesity negatively impacts multiple bodily systems, including the central nervous system. Retrospective studies that estimated chronological age from neuroimaging have found accelerated brain aging in obesity, but it is unclear how this estimation would be affected by weight loss following a lifestyle intervention. Methods In a sub-study of 102 participants of the Dietary Intervention Randomized Controlled Trial Polyphenols Unprocessed Study (DIRECT-PLUS) trial, we tested the effect of weight loss following 18 months of lifestyle intervention on predicted brain age based on magnetic resonance imaging (MRI)-assessed resting-state functional connectivity (RSFC). We further examined how dynamics in multiple health factors, including anthropometric measurements, blood biomarkers, and fat deposition, can account for changes in brain age. Results To establish our method, we first demonstrated that our model could successfully predict chronological age from RSFC in three cohorts (n=291;358;102). We then found that among the DIRECT-PLUS participants, 1% of body weight loss resulted in an 8.9 months' attenuation of brain age. Attenuation of brain age was significantly associated with improved liver biomarkers, decreased liver fat, and visceral and deep subcutaneous adipose tissues after 18 months of intervention. Finally, we showed that lower consumption of processed food, sweets and beverages were associated with attenuated brain age. Conclusions Successful weight loss following lifestyle intervention might have a beneficial effect on the trajectory of brain aging. Funding The German Research Foundation (DFG), German Research Foundation - project number 209933838 - SFB 1052; B11, Israel Ministry of Health grant 87472511 (to I Shai); Israel Ministry of Science and Technology grant 3-13604 (to I Shai); and the California Walnuts Commission 09933838 SFB 105 (to I Shai).
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Affiliation(s)
- Gidon Levakov
- Department of Brain and Cognitive Sciences, Ben-Gurion University of the NegevBeer ShevaIsrael
| | - Alon Kaplan
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the NegevBeer ShevaIsrael
- Department of Internal Medicine D, Chaim Sheba Medical CenterRamat-GanIsrael
| | - Anat Yaskolka Meir
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the NegevBeer ShevaIsrael
| | - Ehud Rinott
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the NegevBeer ShevaIsrael
| | - Gal Tsaban
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the NegevBeer ShevaIsrael
| | - Hila Zelicha
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the NegevBeer ShevaIsrael
| | | | - Uta Ceglarek
- Department of Medicine, University of LeipzigLeipzigGermany
| | | | - Ilan Shelef
- Department of Diagnostic Imaging, Soroka Medical CenterBeer ShevaIsrael
| | - Galia Avidan
- Department of Psychology, Ben-Gurion University of the NegevBeer ShevaIsrael
| | - Iris Shai
- The Health & Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the NegevBeer ShevaIsrael
- Department of Medicine, University of LeipzigLeipzigGermany
- Department of Nutrition, Harvard T.H. Chan School of Public HealthBostonUnited States
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18
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Wei X, Lin B, Huang Y, Yang S, Huang C, Shi L, Liu D, Zhang P, Lin J, Xu B, Guo D, Li C, He H, Liu S, Xue Y, Xu Y, Zhang H. Effects of Time-Restricted Eating on Nonalcoholic Fatty Liver Disease: The TREATY-FLD Randomized Clinical Trial. JAMA Netw Open 2023; 6:e233513. [PMID: 36930148 PMCID: PMC10024204 DOI: 10.1001/jamanetworkopen.2023.3513] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
IMPORTANCE The efficacy and safety of time-restricted eating (TRE) on nonalcoholic fatty liver disease (NAFLD) remain uncertain. OBJECTIVE To compare the effects of TRE vs daily calorie restriction (DCR) on intrahepatic triglyceride (IHTG) content and metabolic risk factors among patients with obesity and NAFLD. DESIGN, SETTING, AND PARTICIPANTS This 12-month randomized clinical trial including participants with obesity and NAFLD was conducted at the Nanfang Hospital in Guangzhou, China, between April 9, 2019, and August 28, 2021. INTERVENTIONS Participants with obesity and NAFLD were randomly assigned to TRE (eating only between 8:00 am and 4:00 pm) or DCR (habitual meal timing). All participants were instructed to maintain a diet of 1500 to 1800 kcal/d for men and 1200 to 1500 kcal/d for women for 12 months. MAIN OUTCOMES AND MEASURES The primary outcome was change in IHTG content measured by magnetic resonance imaging; secondary outcomes were changes in body weight, waist circumference, body fat, and metabolic risk factors. Intention-to-treat analysis was used. RESULTS A total of 88 eligible patients with obesity and NAFLD (mean [SD] age, 32.0 [9.5] years; 49 men [56%]; and mean [SD] body mass index, 32.2 [3.3]) were randomly assigned to the TRE (n = 45) or DCR (n = 43) group. The IHTG content was reduced by 8.3% (95% CI, -10.0% to -6.6%) in the TRE group and 8.1% (95% CI, -9.8% to -6.4%) in the DCR group at the 6-month assessment. The IHTG content was reduced by 6.9% (95% CI, -8.8% to -5.1%) in the TRE group and 7.9% (95% CI, -9.7% to -6.2%) in the DCR group at the 12-month assessment. Changes in IHTG content were comparable between the 2 groups at 6 months (percentage point difference: -0.2; 95% CI, -2.7 to 2.2; P = .86) and 12 months (percentage point difference: 1.0; 95% CI, -1.6 to 3.5; P = .45). In addition, liver stiffness, body weight, and metabolic risk factors were significantly and comparably reduced in both groups. CONCLUSIONS AND RELEVANCE Among adults with obesity and NAFLD, TRE did not produce additional benefits for reducing IHTG content, body fat, and metabolic risk factors compared with DCR. These findings support the importance of caloric intake restriction when adhering to a regimen of TRE for the management of NAFLD. TRIAL REGISTRATION ClinicalTrials.gov Identifiers: NCT03786523 and NCT04988230.
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Affiliation(s)
- Xueyun Wei
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Bingquan Lin
- Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yan Huang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
- Department of Food Safety and Health Research Center, School of Public Health, Southern Medical University, Guangzhou, China
| | - Shunyu Yang
- Department of Nutrition, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Chensihan Huang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Linna Shi
- Department of Nutrition, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Deying Liu
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Peizhen Zhang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jiayang Lin
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Bingyan Xu
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Dan Guo
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Hua He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Shiqun Liu
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yaoming Xue
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yikai Xu
- Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Huijie Zhang
- Department of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, China
- Department of Food Safety and Health Research Center, School of Public Health, Southern Medical University, Guangzhou, China
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19
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Tang R, Tang G, Hua T, Tu Y, Ji R, Zhu J. mDIXON-Quant technique diagnostic accuracy for assessing bone mineral density in male adult population. BMC Musculoskelet Disord 2023; 24:125. [PMID: 36788513 PMCID: PMC9926741 DOI: 10.1186/s12891-023-06225-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 02/06/2023] [Indexed: 02/16/2023] Open
Abstract
BACKGROUND To investigate the diagnostic efficacy of mDIXON-Quant technique for prediction of bone loss in male adults. METHODS One hundred thirty-eight male adults were divided into normal, osteopenia, and osteoporosis groups based on DXA and QCT for the lumbar spine. Differences in mDIXON-Quant parameters [fat fraction (FF) and T2* value] among three groups, as well as the correlation of mDIXON-Quant parameters and bone mineral density (BMD) were analyzed. The areas under the curves (AUCs) for mDIXON-Quant parameters for prediction of low bone mass were calculated. RESULTS According to DXA standard, FF and T2* value were significantly increased in osteoporosis group compared with normal group (P = 0.012 and P < 0.001). According to QCT standard, FF was significantly increased in osteopenia and osteoporosis groups compared with normal group (both P < 0.001). T2* values were significantly different among three groups (all P < 0.05). After correction for age and body mass index, FF was negatively correlated with areal BMD and volumetric BMD (r = -0.205 and -0.604, respectively; both P < 0.05), and so was T2* value (r = -0.324 and -0.444, respectively; both P < 0.05). The AUCs for predicting low bone mass according to DXA and QCT standards were 0.642 and 0.898 for FF, 0.648 and 0.740 for T2* value, and 0.677 and 0.920 for both combined, respectively. CONCLUSIONS FF combined with T2* value has a better diagnostic efficacy than FF or T2* value alone in prediction of low bone mass in male adults, which is expected to be a promising MRI method for the screening of bone quality. TRIAL REGISTRATION ChiCTR1900024511 (Registered 13-07-2019).
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Affiliation(s)
- Rui Tang
- grid.412538.90000 0004 0527 0050Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, 301 Middle Yanchang Road, Shanghai, 200072 China
| | - Guangyu Tang
- grid.412538.90000 0004 0527 0050Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, 301 Middle Yanchang Road, Shanghai, 200072 China
| | - Ting Hua
- grid.412538.90000 0004 0527 0050Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, 301 Middle Yanchang Road, Shanghai, 200072 China
| | - Yun Tu
- grid.412538.90000 0004 0527 0050Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, 301 Middle Yanchang Road, Shanghai, 200072 China
| | - Rui Ji
- grid.412538.90000 0004 0527 0050Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, 301 Middle Yanchang Road, Shanghai, 200072 China
| | - Jingqi Zhu
- Department of Radiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Middle Yanchang Road, Shanghai, 200072, China.
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20
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Fujita S, Sano K, Cruz G, Fukumura Y, Kawasaki H, Fukunaga I, Morita Y, Yoneyama M, Kamagata K, Abe O, Ikejima K, Botnar RM, Prieto C, Aoki S. MR Fingerprinting for Liver Tissue Characterization: A Histopathologic Correlation Study. Radiology 2023; 306:150-159. [PMID: 36040337 DOI: 10.1148/radiol.220736] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Liver MR fingerprinting (MRF) enables simultaneous quantification of T1, T2, T2*, and proton density fat fraction (PDFF) maps in single breath-hold acquisitions. Histopathologic correlation studies are desired for its clinical use. Purpose To compare liver MRF-derived metrics with separate reference quantitative MRI in participants with diffuse liver disease, evaluate scan-rescan repeatability of liver MRF, and validate MRF-derived measurements for histologic grading of liver biopsies. Materials and Methods This prospective study included participants with diffuse liver disease undergoing MRI from July 2021 to January 2022. Participants underwent two-dimensional single-section liver MRF and separate reference quantitative MRI. Linear regression, Bland-Altman plots, and coefficients of variation were used to assess the bias and repeatability of liver MRF measurements. For participants undergoing liver biopsy, the association between mapping and histologic grading was evaluated by using the Spearman correlation coefficient. Results Fifty-six participants (mean age, 59 years ± 15 [SD]; 32 women) were included to compare mapping techniques and 23 participants were evaluated with liver biopsy (mean age, 52.7 years ± 12.7; 14 women). The linearity of MRF with reference measurements in participants with diffuse liver disease (R2 value) for T1, T2, T2*, and PDFF maps was 0.86, 0.88, 0.54, and 0.99, respectively. The overall coefficients of variation for repeatability in the liver were 3.2%, 5.5%, 7.1%, and 4.6% for T1, T2, T2*, and PDFF maps, respectively. MRF-derived metrics showed high diagnostic performance in differentiating moderate or severe changes from mild or no changes (area under the receiver operating characteristic curve for fibrosis, inflammation, steatosis, and siderosis: 0.62 [95% CI: 0.52, 0.62], 0.92 [95% CI: 0.88, 0.92], 0.97 [95% CI: 0.96, 0.97], and 0.74 [95% CI: 0.57, 0.74], respectively). Conclusion Liver MR fingerprinting provided repeatable T1, T2, T2*, and proton density fat fraction maps in high agreement with reference quantitative mapping and may correlate with pathologic grades in participants with diffuse liver disease. © RSNA, 2022 Online supplemental material is available for this article.
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Affiliation(s)
- Shohei Fujita
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Katsuhiro Sano
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Gastao Cruz
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Yuki Fukumura
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Hideo Kawasaki
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Issei Fukunaga
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Yuichi Morita
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Masami Yoneyama
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Koji Kamagata
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Osamu Abe
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Kenichi Ikejima
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - René M Botnar
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Claudia Prieto
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
| | - Shigeki Aoki
- From the Departments of Radiology (S.F., K.S., H.K., I.F., Y.M., K.K., S.A.), Human Pathology (Y.F.), and Gastroenterology (K.I.), Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo, Tokyo 113-8421, Japan; Department of Radiology, University of Tokyo, Tokyo, Japan (S.F., Y.M., O.A.); Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom (G.C., R.M.B., C.P.); Department of MR Clinical Science, Philips Japan, Tokyo, Japan (M.Y.); School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile (R.M.B., C.P.)
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21
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Kim JW, Lee CH, Yang Z, Kim BH, Lee YS, Kim KA. The spectrum of magnetic resonance imaging proton density fat fraction (MRI-PDFF), magnetic resonance spectroscopy (MRS), and two different histopathologic methods (artificial intelligence vs. pathologist) in quantifying hepatic steatosis. Quant Imaging Med Surg 2022; 12:5251-5262. [PMID: 36330193 PMCID: PMC9622443 DOI: 10.21037/qims-22-393] [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: 04/20/2022] [Accepted: 08/05/2022] [Indexed: 07/26/2023]
Abstract
BACKGROUND The grade of hepatic steatosis is assessed semi-quantitatively and graded as a discrete value. However, the proton density fat fraction (PDFF) measured by magnetic resonance imaging (MRI) and FF measured by MR spectroscopy (FFMRS) are continuous values. Therefore, a quantitative histopathologic method may be needed. This study aimed to (I) provide a spectrum of values of MRI-PDFF, FFMRS, and FFs measured by two different histopathologic methods [artificial intelligence (AI) and pathologist], (II) to evaluate the correlation among them, and (III) to evaluate the diagnostic performance of MRI-PDFF and MRS for grading hepatic steatosis. METHODS Forty-seven patients who underwent liver biopsy and MRI for nonalcoholic steatohepatitis (NASH) evaluation were included. The agreement between MRI-PDFF and MRS was evaluated through Bland-Altman analysis. Correlations among MRI-PDFF, MRS, and two different histopathologic methods were assessed using Pearson correlation coefficient (r). The diagnostic performance of MRI-PDFF and MRS was assessed using receiver operating characteristic curve analyses and the area under the curve (AUC) were obtained. RESULTS The means±standard deviation of MRI-PDFF, FFMRS, FF measured by pathologist (FFpathologist), and FF measured by AI (FFAI) were 12.04±6.37, 14.01±6.16, 34.26±19.69, and 6.79±4.37 (%), respectively. Bland-Altman bias [mean of MRS - (MRI-PDFF) differences] was 2.06%. MRI-PDFF and MRS had a very strong correlation (r=0.983, P<0.001). The two different histopathologic methods also showed a very strong correlation (r=0.872, P<0.001). Both MRI-PDFF and MRS demonstrated a strong correlation with FFpathologist (r=0.701, P<0.001 and r=0.709, P<0.001, respectively) and with FFAI (r=0.700, P<0.001 and r=0.690, P<0.001, respectively). The AUCs of MRI-PDFF for grading ≥S2 and ≥S3 were 0.846 and 0.855, respectively. The AUCs of MRS for grading ≥S2 and ≥S3 were 0.860 and 0.878, respectively. CONCLUSIONS Since MRS and MRI-PDFF demonstrated a strong correlation with each other and with the two different histopathologic methods, they can be used as an alternative noninvasive reference standard in nonalcoholic fatty liver disease (NAFLD) patients. However, these preliminary results should be interpreted with caution until they are validated in further studies.
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Affiliation(s)
- Jeong Woo Kim
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Chang Hee Lee
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Zepa Yang
- Biomedical Research Center, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Baek-Hui Kim
- Department of Pathology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Young-Sun Lee
- Department of Internal Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Kyeong Ah Kim
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
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22
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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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23
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Cadenas-Sanchez C, Idoate F, Cabeza R, Villanueva A, Rodríguez-Vigil B, Medrano M, Osés M, Ortega FB, Ruiz JR, Labayen I. Effect of a Multicomponent Intervention on Hepatic Steatosis Is Partially Mediated by the Reduction of Intermuscular Abdominal Adipose Tissue in Children With Overweight or Obesity: The EFIGRO Project. Diabetes Care 2022; 45:1953-1960. [PMID: 36044664 DOI: 10.2337/dc21-2440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 06/13/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE In adults, there is evidence that improvement of metabolic-associated fatty liver disease (MAFLD) depends on the reduction of myosteatosis. In children, in whom the prevalence of MAFLD is alarming, this muscle-liver crosstalk has not been tested. Therefore, we aimed to explore whether the effects of a multicomponent intervention on hepatic fat is mediated by changes in intermuscular abdominal adipose tissue (IMAAT) in children with overweight/obesity. RESEARCH DESIGN AND METHODS A total of 116 children with overweight/obesity were allocated to a 22-week family-based lifestyle and psychoeducational intervention (control group, n = 57) or the same intervention plus supervised exercise (exercise group, n = 59). Hepatic fat percentage and IMAAT were acquired by MRI at baseline and at the end of the intervention. RESULTS Changes in IMAAT explained 20.7% of the improvements in hepatic steatosis (P < 0.05). Only children who meaningfully reduced their IMAAT (i.e., responders) had improved hepatic steatosis at the end of the intervention (within-group analysis: responders -20% [P = 0.005] vs. nonresponders -1.5% [P = 0.803]). Between-group analysis showed greater reductions in favor of IMAAT responders compared with nonresponders (18.3% vs. 0.6%, P = 0.018), regardless of overall abdominal fat loss. CONCLUSIONS The reduction of IMAAT plays a relevant role in the improvement of hepatic steatosis after a multicomponent intervention in children with overweight/obesity. Indeed, only children who achieved a meaningful reduction in IMAAT at the end of the intervention had a reduced percentage of hepatic fat independent of abdominal fat loss. Our findings suggest that abdominal muscle fat infiltration could be a therapeutic target for the treatment of MAFLD in childhood.
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Affiliation(s)
- Cristina Cadenas-Sanchez
- Institute for Innovation & Sustainable Food Chain Development (ISFOOD), Department of Health Sciences, Public University of Navarre, Pamplona, Navarre, Spain.,Healthcare Research Institute of Navarre (IdiSNA), Pamplona, Spain.,Promoting Fitness and Health Through Physical Activity (PROFITH) Research Group, Sport and Health University Research Institute (iMUDS), Faculty of Sport Sciences, Department of Physical and Sports Education, University of Granada, Granada, Spain
| | - Fernando Idoate
- Radiology Department, Mutua Navarra, Department of Health Sciences, Public University of Navarre, Pamplona, Spain
| | - Rafael Cabeza
- Department of Electrical, Electronic and Communications Engineering, Public University of Navarre, Pamplona, Spain
| | - Arantxa Villanueva
- Healthcare Research Institute of Navarre (IdiSNA), Pamplona, Spain.,Department of Electrical, Electronic and Communications Engineering, Public University of Navarre, Pamplona, Spain.,Smart Cities Institute, Public University of Navarre, Pamplona, Spain
| | - Beatriz Rodríguez-Vigil
- Department of Magnetic Resonance Imaging, Osatek, University Hospital of Alava (HUA), Vitoria-Gasteiz, Spain
| | - María Medrano
- Promoting Fitness and Health Through Physical Activity (PROFITH) Research Group, Sport and Health University Research Institute (iMUDS), Faculty of Sport Sciences, Department of Physical and Sports Education, University of Granada, Granada, Spain
| | - Maddi Osés
- Institute for Innovation & Sustainable Food Chain Development (ISFOOD), Department of Health Sciences, Public University of Navarre, Pamplona, Navarre, Spain.,Healthcare Research Institute of Navarre (IdiSNA), Pamplona, Spain
| | - Francisco B Ortega
- Promoting Fitness and Health Through Physical Activity (PROFITH) Research Group, Sport and Health University Research Institute (iMUDS), Faculty of Sport Sciences, Department of Physical and Sports Education, University of Granada, Granada, Spain.,Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Jonatan R Ruiz
- Promoting Fitness and Health Through Physical Activity (PROFITH) Research Group, Sport and Health University Research Institute (iMUDS), Faculty of Sport Sciences, Department of Physical and Sports Education, University of Granada, Granada, Spain.,Instituto de Investigación Biosanitaria (ibs.Granada), Granada, Spain
| | - Idoia Labayen
- Institute for Innovation & Sustainable Food Chain Development (ISFOOD), Department of Health Sciences, Public University of Navarre, Pamplona, Navarre, Spain.,Healthcare Research Institute of Navarre (IdiSNA), Pamplona, Spain
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24
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Wagner R, Eckstein SS, Yamazaki H, Gerst F, Machann J, Jaghutriz BA, Schürmann A, Solimena M, Singer S, Königsrainer A, Birkenfeld AL, Häring HU, Fritsche A, Ullrich S, Heni M. Metabolic implications of pancreatic fat accumulation. Nat Rev Endocrinol 2022; 18:43-54. [PMID: 34671102 DOI: 10.1038/s41574-021-00573-3] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/13/2021] [Indexed: 12/15/2022]
Abstract
Fat accumulation outside subcutaneous adipose tissue often has unfavourable effects on systemic metabolism. In addition to non-alcoholic fatty liver disease, which has received considerable attention, pancreatic fat has become an important area of research throughout the past 10 years. While a number of diagnostic approaches are available to quantify pancreatic fat, multi-echo Dixon MRI is currently the most developed method. Initial studies have shown associations between pancreatic fat and the metabolic syndrome, impaired glucose metabolism and type 2 diabetes mellitus. Pancreatic fat is linked to reduced insulin secretion, at least under specific circumstances such as prediabetes, low BMI and increased genetic risk of type 2 diabetes mellitus. This Review summarizes the possible causes and metabolic consequences of pancreatic fat accumulation. In addition, potential therapeutic approaches for addressing pancreatic fat accumulation are discussed.
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Affiliation(s)
- Robert Wagner
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Sabine S Eckstein
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Hajime Yamazaki
- Section of Clinical Epidemiology, Department of Community Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Felicia Gerst
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Jürgen Machann
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Section of Experimental Radiology, Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Benjamin Assad Jaghutriz
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Annette Schürmann
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Experimental Diabetology, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke, Germany
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Michele Solimena
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Molecular Diabetology, University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany
- Paul Langerhans Institute Dresden (PLID), Helmholtz Center Munich, University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - Stephan Singer
- Institute of Pathology, University of Tübingen, Tübingen, Germany
| | - Alfred Königsrainer
- Department of General, Visceral, and Transplant Surgery, University Hospital Tübingen, Tübingen, Germany
| | - Andreas L Birkenfeld
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Hans-Ulrich Häring
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Andreas Fritsche
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Susanne Ullrich
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Martin Heni
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany.
- German Center for Diabetes Research (DZD), Tübingen, Germany.
- Department of Internal Medicine, Division of Diabetology, Endocrinology, and Nephrology, Eberhard Karls University Tübingen, Tübingen, Germany.
- Institute for Clinical Chemistry and Pathobiochemistry, Department for Diagnostic Laboratory Medicine, University Hospital Tübingen, Tübingen, Germany.
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25
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Martí-Aguado D, Jiménez-Pastor A, Alberich-Bayarri Á, Rodríguez-Ortega A, Alfaro-Cervello C, Mestre-Alagarda C, Bauza M, Gallén-Peris A, Valero-Pérez E, Ballester MP, Gimeno-Torres M, Pérez-Girbés A, Benlloch S, Pérez-Rojas J, Puglia V, Ferrández A, Aguilera V, Escudero-García D, Serra MA, Martí-Bonmatí L. Automated Whole-Liver MRI Segmentation to Assess Steatosis and Iron Quantification in Chronic Liver Disease. Radiology 2021; 302:345-354. [PMID: 34783592 DOI: 10.1148/radiol.2021211027] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background Standardized manual region of interest (ROI) sampling strategies for hepatic MRI steatosis and iron quantification are time consuming, with variable results. Purpose To evaluate the performance of automatic MRI whole-liver segmentation (WLS) for proton density fat fraction (PDFF) and iron estimation (transverse relaxometry [R2*]) versus manual ROI, with liver biopsy as the reference standard. Materials and Methods This prospective, cross-sectional, multicenter study recruited participants with chronic liver disease who underwent liver biopsy and chemical shift-encoded 3.0-T MRI between January 2017 and January 2021. Biopsy evaluation included histologic grading and digital pathology. MRI liver sampling strategies included manual ROI (two observers) and automatic whole-liver (deep learning algorithm) segmentation for PDFF- and R2*-derived measurements. Agreements between segmentation methods were measured using intraclass correlation coefficients (ICCs), and biases were evaluated using Bland-Altman analyses. Linear regression analyses were performed to determine the correlation between measurements and digital pathology. Results A total of 165 participants were included (mean age ± standard deviation, 55 years ± 12; 96 women; 101 of 165 participants [61%] with nonalcoholic fatty liver disease). Agreements between mean measurements were excellent, with ICCs of 0.98 for both PDFF and R2*. The median bias was 0.5% (interquartile range, -0.4% to 1.2%) for PDFF and 2.7 sec-1 (interquartile range, 0.2-5.3 sec-1) for R2* (P < .001 for both). Margins of error were lower for WLS than ROI-derived parameters (-0.03% for PDFF and -0.3 sec-1 for R2*). ROI and WLS showed similar performance for steatosis (ROI AUC, 0.96; WLS AUC, 0.97; P = .53) and iron overload (ROI AUC, 0.85; WLS AUC, 0.83; P = .09). Correlations with digital pathology were high (P < .001) between the fat ratio and PDFF (ROI r = 0.89; WLS r = 0.90) and moderate (P < .001) between the iron ratio and R2* (ROI r = 0.65; WLS r = 0.64). Conclusion Proton density fat fraction and transverse relaxometry measurements derived from MRI automatic whole-liver segmentation (WLS) were accurate for steatosis and iron grading in chronic liver disease and correlated with digital pathology. Automated WLS estimations were higher, with a lower margin of error than manual region of interest estimations. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Moura Cunha and Fowler in this issue.
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Affiliation(s)
- David Martí-Aguado
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Ana Jiménez-Pastor
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Ángel Alberich-Bayarri
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Alejandro Rodríguez-Ortega
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Clara Alfaro-Cervello
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Claudia Mestre-Alagarda
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Mónica Bauza
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Ana Gallén-Peris
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Elena Valero-Pérez
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - María Pilar Ballester
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Marta Gimeno-Torres
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Alexandre Pérez-Girbés
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Salvador Benlloch
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Judith Pérez-Rojas
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Víctor Puglia
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Antonio Ferrández
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Victoria Aguilera
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Desamparados Escudero-García
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Miguel A Serra
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
| | - Luis Martí-Bonmatí
- From the Departments of Digestive Diseases (D.M.A., M.P.B., D.E.G.), Pathology (C.A.C., C.M.A., A.F.), and Gastroenterology and Hepatology (D.M.A.), Clinic University Hospital, INCLIVA Health Research Institute, Avenida Blasco Ibáñez 17, 46010 Valencia, Spain; Biomedical Imaging Research Group (GIBI2), La Fe Health Research Institute, Valencia, Spain (D.M.A., A.R.O., L.M.B.); Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain (A.J.P., Á.A.B.); University of Valencia, Faculty of Medicine, Valencia, Spain (C.A.C., A.F., D.E.G., M.A.S.); Departments of Pathology (M.B., J.P.R.), Digestive Diseases (E.V.P., M.G.T.), and Radiology (A.P.G., L.M.B.) and the Hepatology and Liver Transplantation Unit (V.A.), La Fe University and Polytechnic Hospital, Valencia, Spain; Departments of Digestive Diseases (A.G.P., S.B.) and Pathology (V.P.), Hospital Arnau de Vilanova, Valencia, Spain; CIBERehd (Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas), Instituto de Salud Carlos III, Madrid, Spain (S.B., V.A.); and Río Hortega, Instituto Salud Carlos III, Madrid, Spain (D.M.A.)
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Henze Bancroft LC, Strigel RM, Macdonald EB, Longhurst C, Johnson J, Hernando D, Reeder SB. Proton density water fraction as a reproducible MR-based measurement of breast density. Magn Reson Med 2021; 87:1742-1757. [PMID: 34775638 DOI: 10.1002/mrm.29076] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Revised: 10/06/2021] [Accepted: 10/19/2021] [Indexed: 01/12/2023]
Abstract
PURPOSE To introduce proton density water fraction (PDWF) as a confounder-corrected (CC) MR-based biomarker of mammographic breast density, a known risk factor for breast cancer. METHODS Chemical shift encoded (CSE) MR images were acquired using a low flip angle to provide proton density contrast from multiple echo times. Fat and water images, corrected for known biases, were produced by a six-echo CC CSE-MRI algorithm. Fibroglandular tissue (FGT) volume was calculated from whole-breast segmented PDWF maps at 1.5T and 3T. The method was evaluated in (1) a physical fat-water phantom and (2) normal volunteers. Results from two- and three-echo CSE-MRI methods were included for comparison. RESULTS Six-echo CC-CSE-MRI produced unbiased estimates of the total water volume in the phantom (mean bias 3.3%) and was reproducible across protocol changes (repeatability coefficient [RC] = 14.8 cm3 and 13.97 cm3 at 1.5T and 3.0T, respectively) and field strengths (RC = 51.7 cm3 ) in volunteers, while the two- and three-echo CSE-MRI approaches produced biased results in phantoms (mean bias 30.7% and 10.4%) that was less reproducible across field strengths in volunteers (RC = 82.3 cm3 and 126.3 cm3 ). Significant differences in measured FGT volume were found between the six-echo CC-CSE-MRI and the two- and three-echo CSE-MRI approaches (p = 0.002 and p = 0.001, respectively). CONCLUSION The use of six-echo CC-CSE-MRI to create unbiased PDWF maps that reproducibly quantify FGT in the breast is demonstrated. Further studies are needed to correlate this quantitative MR biomarker for breast density with mammography and overall risk for breast cancer.
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Affiliation(s)
| | - Roberta M Strigel
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Erin B Macdonald
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Clinical Imaging Physics Group, Duke University Medical Center, Durham, North Carolina, USA
| | - Colin Longhurst
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jacob Johnson
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Scott B Reeder
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Emergency Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Yaskolka Meir A, Rinott E, Tsaban G, Zelicha H, Kaplan A, Rosen P, Shelef I, Youngster I, Shalev A, Blüher M, Ceglarek U, Stumvoll M, Tuohy K, Diotallevi C, Vrhovsek U, Hu F, Stampfer M, Shai I. Effect of green-Mediterranean diet on intrahepatic fat: the DIRECT PLUS randomised controlled trial. Gut 2021; 70:2085-2095. [PMID: 33461965 PMCID: PMC8515100 DOI: 10.1136/gutjnl-2020-323106] [Citation(s) in RCA: 124] [Impact Index Per Article: 41.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 11/23/2020] [Accepted: 11/28/2020] [Indexed: 01/08/2023]
Abstract
OBJECTIVE To examine the effectiveness of green-Mediterranean (MED) diet, further restricted in red/processed meat, and enriched with green plants and polyphenols on non-alcoholic fatty liver disease (NAFLD), reflected by intrahepatic fat (IHF) loss. DESIGN For the DIRECT-PLUS 18-month randomized clinical trial, we assigned 294 participants with abdominal obesity/dyslipidaemia into healthy dietary guidelines (HDG), MED and green-MED weight-loss diet groups, all accompanied by physical activity. Both isocaloric MED groups consumed 28 g/day walnuts (+440 mg/day polyphenols provided). The green-MED group further consumed green tea (3-4 cups/day) and Mankai (a Wolffia globosa aquatic plant strain; 100 g/day frozen cubes) green shake (+1240 mg/day total polyphenols provided). IHF% 18-month changes were quantified continuously by proton magnetic resonance spectroscopy (MRS). RESULTS Participants (age=51 years; 88% men; body mass index=31.3 kg/m2; median IHF%=6.6%; mean=10.2%; 62% with NAFLD) had 89.8% 18-month retention-rate, and 78% had eligible follow-up MRS. Overall, NAFLD prevalence declined to: 54.8% (HDG), 47.9% (MED) and 31.5% (green-MED), p=0.012 between groups. Despite similar moderate weight-loss in both MED groups, green-MED group achieved almost double IHF% loss (-38.9% proportionally), as compared with MED (-19.6% proportionally; p=0.035 weight loss adjusted) and HDG (-12.2% proportionally; p<0.001). After 18 months, both MED groups had significantly higher total plasma polyphenol levels versus HDG, with higher detection of Naringenin and 2-5-dihydroxybenzoic-acid in green-MED. Greater IHF% loss was independently associated with increased Mankai and walnuts intake, decreased red/processed meat consumption, improved serum folate and adipokines/lipids biomarkers, changes in microbiome composition (beta-diversity) and specific bacteria (p<0.05 for all). CONCLUSION The new suggested strategy of green-Mediterranean diet, amplified with green plant-based proteins/polyphenols as Mankai, green tea, and walnuts, and restricted in red/processed meat can double IHF loss than other healthy nutritional strategies and reduce NAFLD in half. TRIAL REGISTRATION NUMBER NCT03020186.
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Affiliation(s)
- Anat Yaskolka Meir
- Department of Public Health, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ehud Rinott
- Department of Public Health, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Gal Tsaban
- Department of Public Health, Ben-Gurion University of the Negev, Beer-Sheva, Israel,Division of Cardiology, Soroka Medical Center, Beer Sheva, Israel
| | - Hila Zelicha
- Department of Public Health, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Alon Kaplan
- Department of Public Health, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Philip Rosen
- Division of Diagnostic and Interventional Imaging, Soroka University Medical Center, Beer Sheva, Israel
| | - Ilan Shelef
- Division of Diagnostic and Interventional Imaging, Soroka University Medical Center, Beer Sheva, Israel
| | - Ilan Youngster
- Pediatric Division and Center for Microbiome Research, Shamir Medical Center, Be’er Ya’akov, Israel
| | - Aryeh Shalev
- Division of Cardiology, Soroka Medical Center, Beer Sheva, Israel
| | - Matthias Blüher
- Medical Department III – Endocrinology, Nephrology, Rheumatology, Leipzig University, Leipzig, Germany
| | - Uta Ceglarek
- Institute for Laboratory Medicine, Leipzig University, Leipzig, Germany
| | - Michael Stumvoll
- Medical Department III – Endocrinology, Nephrology, Rheumatology, Leipzig University, Leipzig, Germany
| | - Kieran Tuohy
- Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach, San Michelle All'Adige, Italy
| | - Camilla Diotallevi
- Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach, San Michelle All'Adige, Italy,Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy
| | - Urska Vrhovsek
- Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy
| | - Frank Hu
- Department of Nutrition, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA,Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Meir Stampfer
- Department of Nutrition, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA,Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Iris Shai
- Department of Public Health, Ben-Gurion University of the Negev, Beer-Sheva, Israel .,Department of Nutrition, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
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Schick F, Pieper CC, Kupczyk P, Almansour H, Keller G, Springer F, Mürtz P, Endler C, Sprinkart AM, Kaufmann S, Herrmann J, Attenberger UI. 1.5 vs 3 Tesla Magnetic Resonance Imaging: A Review of Favorite Clinical Applications for Both Field Strengths-Part 1. Invest Radiol 2021; 56:680-691. [PMID: 34324464 DOI: 10.1097/rli.0000000000000812] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
ABSTRACT Whole-body magnetic resonance imaging (MRI) systems with a field strength of 3 T have been offered by all leading manufacturers for approximately 2 decades and are increasingly used in clinical diagnostics despite higher costs. Technologically, MRI systems operating at 3 T have reached a high standard in recent years, as well as the 1.5-T devices that have been in use for a longer time. For modern MRI systems with 3 T, more complexity is required, especially for the magnet and the radiofrequency (RF) system (with multichannel transmission). Many clinical applications benefit greatly from the higher field strength due to the higher signal yield (eg, imaging of the brain or extremities), but there are also applications where the disadvantages of 3 T might outweigh the advantages (eg, lung imaging or examinations in the presence of implants). This review describes some technical features of modern 1.5-T and 3-T whole-body MRI systems, and reports on the experience of using both types of devices in different clinical settings, with all sections written by specialist radiologists in the respective fields.This first part of the review includes an overview of the general physicotechnical aspects of both field strengths and elaborates the special conditions of diffusion imaging. Many relevant aspects in the application areas of musculoskeletal imaging, abdominal imaging, and prostate diagnostics are discussed.
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Affiliation(s)
- Fritz Schick
- From the Section of Experimental Radiology, Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen
| | | | - Patrick Kupczyk
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Haidara Almansour
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Gabriel Keller
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Fabian Springer
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Petra Mürtz
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Christoph Endler
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Alois M Sprinkart
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Sascha Kaufmann
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Judith Herrmann
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Ulrike I Attenberger
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
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Hupfeld S, Pischel D, Jechorek D, Janicová A, Pech M, Fischbach F. MRI-based fat quantification of the liver: Is it time for commercially available products? Eur J Radiol 2021; 144:109993. [PMID: 34656047 DOI: 10.1016/j.ejrad.2021.109993] [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: 06/24/2021] [Revised: 09/24/2021] [Accepted: 09/29/2021] [Indexed: 11/28/2022]
Abstract
PURPOSE (1) To assess the clinical applicability of commercially available solutions for MR-based quantification of the hepatic fat fraction (HFF) and (2) to compare their results with clinically established in-phase/oppose-phase (IP/OP) imaging as proposed by Dixon. METHODS Twenty-eight patients underwent MRI examinations using multigradient-echo sequences including multi-peak modeling and T2∗ correction, IP/OP imaging and multi-echo spectroscopy with successive HFF evaluation. Histopathological examination yielded the fraction of adipose hepatocytes (fAH) and the presence of increased liver iron concentration (LIC). We correlated HFF with fAH, and assessed concordance correlations among the MR-based methods with the presence of increased LIC as a control parameter. We investigated the liver segmentation quality and overall workflow of the postprocessing solutions (Philips LiverHealth and Siemens LiverLab). RESULTS IP/OP imaging yielded a very strong correlation (r=0.88) with fAH when excluding three cases with increased LIC. Multigradient echo imaging and multiecho spectroscopy quantifications yielded similar correlations (r=0.87…0.93) as IP/OP imaging but were insensitive to increased LIC. Visceral fat, kidney tissue and major vessels were included regularly in the segmentation. Spectroscopic fat quantification was sensitive to the inclusion of visceral fat. CONCLUSIONS IP/OP imaging allows HFF quantification when ruling out hepatic siderosis, whereas dedicated multi-echo imaging sequences and spectroscopy show no bias for increased iron concentration. The segmentation quality and workflow of both postprocessing solutions need to be improved. Nevertheless, all solutions are able to bring MRI-based hepatic fat quantification into the clinical application. We therefore recommend commercial hepatic fat quantification tools for institutions specialised to abdominal imaging.
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Affiliation(s)
- Sebastian Hupfeld
- Department of Radiology and Nuclear Medicine, Otto von Guericke University, Medical School, Leipziger Str. 44, 39120 Magdeburg, Germany.
| | - Dennis Pischel
- Department of Radiology and Nuclear Medicine, Otto von Guericke University, Medical School, Leipziger Str. 44, 39120 Magdeburg, Germany
| | - Dörthe Jechorek
- Institute for Pathology, Otto von Guericke University, Medical School, Leipziger Str. 44, 39120 Magdeburg, Germany
| | - Andrea Janicová
- Experimental Radiology, Department of Radiology and Nuclear Medicine, Otto von Guericke University, Medical School, Leipziger Str. 44, 39120 Magdeburg, Germany
| | - Maciej Pech
- Department of Radiology and Nuclear Medicine, Otto von Guericke University, Medical School, Leipziger Str. 44, 39120 Magdeburg, Germany
| | - Frank Fischbach
- Department of Radiology and Nuclear Medicine, Otto von Guericke University, Medical School, Leipziger Str. 44, 39120 Magdeburg, Germany
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30
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Yaskolka Meir A, Keller M, Müller L, Bernhart SH, Tsaban G, Zelicha H, Rinott E, Kaplan A, Gepner Y, Shelef I, Schwarzfuchs D, Ceglarek U, Stadler P, Blüher M, Stumvoll M, Kovacs P, Shai I. Effects of lifestyle interventions on epigenetic signatures of liver fat: Central randomized controlled trial. Liver Int 2021; 41:2101-2111. [PMID: 33938135 DOI: 10.1111/liv.14916] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 04/13/2021] [Accepted: 04/24/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND AIMS In the CENTRAL trial context, we found diverse liver fat dynamics in response to different dietary interventions. Epigenetic mechanisms may contribute to the intraindividual variation. Moreover, genetic factors are involved in developing nonalcoholic fatty-liver disease (NAFLD), a disease reflected by an increase in intrahepatic fat (IHF). In this exploratory analysis, we primarily aimed to examine the effect of lifestyle interventions on DNA-methylation of NAFLD related genes associated with IHF. METHODS For 120 participants from the CENTRAL trial, an 18-month regimen of either low-fat (LF) or Mediterranean-low carbohydrate (MED/LC) diets, with or without physical activity (PA+/PA-), was instructed. Magnetic resonance imaging was used to measure IHF%, which was analysed for association with CpG specific DNA-methylation levels of 41 selected candidate genes. Single-nucleotide polymorphisms known to be associated with NAFLD within the studied genes were genotyped by TaqMan assays. RESULTS At baseline, participants (92% men; body mass index = 30.2 kg/m2 ) had mean IHF of 10.7% (59% NAFLD). Baseline-IHF% was inversely correlated with DNA-methylation at individual CpGs within AC074286.1, CRACR2A, A2MP1, FARP1 (P < .05 for all multivariate models). FARP1 rs9584805 showed association with IHF, with the prevalence of NAFLD and baseline methylation level of the CpG site (cg00071727) associated with IHF%. Following 18-month lifestyle intervention, differential DNA-methylation patterns were observed between diets at cg14335324 annotated to A2MP1 (P = .04, LF vs. MED/LC), and differential DNA-methylation between PA groups within AC074286.1, CRACR2A, and FARP1 CpGs (P < .05 for all, PA-vs. PA+). CONCLUSIONS This study suggests epigenetic markers for IHF and potential epigenetic remodeling after long-term lifestyle interventions.
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Affiliation(s)
- Anat Yaskolka Meir
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Maria Keller
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany.,Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Luise Müller
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Stephan H Bernhart
- Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.,Bioinformatics Group, Department of Computer Science, University of Leipzig, Leipzig, Germany.,Transcriptome Bioinformatics, LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Gal Tsaban
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Hila Zelicha
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ehud Rinott
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Alon Kaplan
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Yftach Gepner
- Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Sylvan Adams Sports Institute, Tel Aviv University, Tel Aviv, Israel
| | - Ilan Shelef
- Soroka University Medical Center, Beer-Sheva, Israel
| | | | - Uta Ceglarek
- Institute for Laboratory Medicine, University of Leipzig Medical Center, Leipzig, Germany
| | - Peter Stadler
- Bioinformatics Group, Department of Computer Science, University of Leipzig, Leipzig, Germany.,Competence Center for Scalable Data Services and Solutions Dresden/Leipzig, German Centre for Integrative Biodiversity Research (iDiv), Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.,Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany.,Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.,Department of Theoretical Chemistry, University of Vienna, Vienna, Austria.,Center for RNA in Technology and Health, University of Copenhagen, Frederiksberg, Denmark.,Santa Fe Institute, Santa Fe, NM, USA
| | - Matthias Blüher
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany.,Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Michael Stumvoll
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany.,Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany.,Deutsches Zentrum für Diabetesforschung, Neuherberg, Germany
| | - Peter Kovacs
- Medical Department III-Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
| | - Iris Shai
- Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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31
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Choi MH, Lee YJ, Choi YJ, Pak S. Dual-energy CT of the liver: True noncontrast vs. virtual noncontrast images derived from multiple phases for the diagnosis of fatty liver. Eur J Radiol 2021; 140:109741. [PMID: 33991971 DOI: 10.1016/j.ejrad.2021.109741] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 04/03/2021] [Accepted: 04/22/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE To evaluate the difference in liver density and to compare the performance to diagnose fatty liver between true noncontrast (TNC) images and virtual noncontrast (VNC) images generated from dual-energy CT (DECT). MATERIALS AND METHODS Patients who underwent liver dynamic DECT and MRI were included (n = 49). Two observers measured the liver and spleen densities on TNC images and three VNC images from the arterial, portal and delayed phases of DECT (VNCa, VNCp and VNCd, respectively). The liver-minus-spleen density (density L-S) and liver-to-spleen ratio (density L/S) were calculated. The CT parameters were compared between normal liver patients and fatty liver patients by using the independent t-test. Differences and agreements between measurements on TNC images and VNC images were evaluated by using the paired t-test and Bland-Altman analysis. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of CT parameters for diagnosing fatty liver. RESULTS All CT parameters measured on TNC and VNC images were significantly higher in normal liver patients than in fatty liver patients. Although the mean liver densities on VNC images were significantly lower than those on TNC images, all CT parameters showed good agreement between TNC images and VNC images. The diagnostic performances of CT parameters on VNC images were not significantly different from those on TNC images. CONCLUSION Although the liver and spleen density on VNC images was significantly lower than that on TNC images, the diagnostic performances of CT parameters on three VNC images from multiple phases were similar to those on TNC images for diagnosing fatty liver.
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Affiliation(s)
- Moon Hyung Choi
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 1021, Tongil-ro, Eunpyeong-gu, Seoul, 03312, Republic of Korea
| | - Young Joon Lee
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 1021, Tongil-ro, Eunpyeong-gu, Seoul, 03312, Republic of Korea.
| | - Yun Jeong Choi
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 1021, Tongil-ro, Eunpyeong-gu, Seoul, 03312, Republic of Korea
| | - SeongYong Pak
- Siemens Healthineers Ltd., 23 Chungjeong-ro, Seoul, 03737, Republic of Korea
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32
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Winfield JM, Blackledge MD, Tunariu N, Koh DM, Messiou C. Whole-body MRI: a practical guide for imaging patients with malignant bone disease. Clin Radiol 2021; 76:715-727. [PMID: 33934876 DOI: 10.1016/j.crad.2021.04.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 04/08/2021] [Indexed: 01/09/2023]
Abstract
Whole-body magnetic resonance imaging (MRI) is now a crucial tool for the assessment of the extent of systemic malignant bone disease and response to treatment, and forms part of national and international recommendations for imaging patients with myeloma or metastatic prostate cancer. Recent developments in scanners have enabled acquisition of good-quality whole-body MRI data within 45 minutes on modern MRI systems from all main manufacturers. This provides complimentary morphological and functional whole-body imaging; however, lack of prior experience and acquisition times required can act as a barrier to adoption in busy radiology departments. This article aims to tackle the former by reviewing the indications and providing guidance for technical delivery and clinical interpretation of whole-body MRI for patients with malignant bone disease.
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Affiliation(s)
- J M Winfield
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK; MRI Unit, Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, SM2 5PT, UK
| | - M D Blackledge
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK; MRI Unit, Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, SM2 5PT, UK
| | - N Tunariu
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK; MRI Unit, Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, SM2 5PT, UK
| | - D-M Koh
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK; MRI Unit, Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, SM2 5PT, UK
| | - C Messiou
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, 123 Old Brompton Road, London, SW7 3RP, UK; MRI Unit, Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, SM2 5PT, UK.
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33
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Corrias G, Erta M, Sini M, Sardu C, Saba L, Mahmood U, Castellanos SH, Bates D, Mondanelli N, Thomsen B, Carollo G, Sawan P, Mannelli L. Comparison of Multimaterial Decomposition Fat Fraction with DECT and Proton Density Fat Fraction with IDEAL IQ MRI for Quantification of Liver Steatosis in a Population Exposed to Chemotherapy. Dose Response 2021; 19:1559325820984938. [PMID: 33958978 PMCID: PMC8060765 DOI: 10.1177/1559325820984938] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 11/20/2020] [Accepted: 12/07/2020] [Indexed: 12/25/2022] Open
Abstract
Introduction: Oncologic patients who develop chemotherapy-associated liver injury (CALI) secondary to chemotherapy treatment tend to have worse outcomes. Biopsy remains the gold standard for the diagnosis of hepatic steatosis. The purpose of this article is to compare 2 alternatives: Proton-Density-Fat-Fraction (PDFF) MRI and MultiMaterial-Decomposition (MMD) DECT. Materials and Methods: 49 consecutive oncologic patients treated with Chemotherapy underwent abdominal DECT and abdominal MRI within 2 weeks of each other. Two radiologists tracked Regions of Interest independently both in the PDFF fat maps and in the MMD DECT fat maps. Non-parametric exact Wilcoxon signed rank test and Cohen’s K were used to compare the 2 sequences and to evaluate the agreement. Results: There was no statistically significant difference in the fat fraction measured as a continuous value between PDFF and DECT between 2 readers. Within the same imaging method (PDFF) the degree of agreement based on the k coefficient between reader 1 and reader 2 is 0.88 (p-value < 0.05). Similarly, for single-source DECT(ssDECT) the degree of agreement based on the k coefficient between reader 1 and reader 2 is 0.97 (p-value < 0.05). Conclusions: The results of this study demonstrate that the hepatic fat fraction of ssDECT with MMD are not significantly different from PDFF. This could be an advantage in an oncological population that undergoes serial CT scans for follow up of chemotherapy response.
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Affiliation(s)
- Giuseppe Corrias
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Radiology, University of Cagliari, Italy
| | - Marco Erta
- Department of Radiology, University of Cagliari, Italy
| | - Marcello Sini
- Department of Radiology, University of Cagliari, Italy
| | - Claudia Sardu
- Department of Medical Science, University of Cagliari, Italy
| | - Luca Saba
- Department of Radiology, University of Cagliari, Italy
| | - Usman Mahmood
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - David Bates
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | | | | | - Peter Sawan
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Peter Sawan and Lorenzo Mannelli have contributed equally
| | - Lorenzo Mannelli
- IRCCS SDN, Napoli, Italy., Peter Sawan and Lorenzo Mannelli have contributed equally
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34
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Virarkar M, Szklaruk J, Jensen CT, Taggart MW, Bhosale P. What's New in Hepatic Steatosis. Semin Ultrasound CT MR 2021; 42:405-415. [PMID: 34130852 DOI: 10.1053/j.sult.2021.03.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Hepatic steatosis can lead to liver cancer, cirrhosis, and portal hypertension. There are two main types, non-alcoholic fatty liver disease (NAFLD) and alcoholic liver disease. The detection and quantification of hepatic steatosis with lifestyle changes can slow the evolution from NAFLD to steatohepatitis. Currently, the gold standard for the quantification of fat in the liver is biopsy, has some limitations. Hepatic steatosis is frequently detected during cross sectional imaging. Ultrasound (US), Computed Tomography (CT), and Magnetic Resonance Imaging (MRI) provide noninvasive assessment of liver parenchyma and can detect fat infiltration in the liver. However, the non-invasive quantification of hepatic steatosis by imaging has been challenging. Recent MRI techniques show great promise in the detection and quantification of liver fat. The aim of this article is to review the utilization of non-invasive imaging modalities for the detection and quantification of hepatic steatosis, to evaluate their advantages and limitations.
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Affiliation(s)
- Mayur Virarkar
- Department of Neuroradiology, The University of Texas Health Science Center, Houston, TX.
| | - Janio Szklaruk
- Department of Abdominal Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Corey T Jensen
- Department of Abdominal Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Melissa W Taggart
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Priya Bhosale
- Department of Abdominal Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX
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35
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Tada T, Kumada T, Toyoda H, Nakamura S, Shibata Y, Yasuda S, Watanuki Y, Tsujii K, Fukuda N, Fujioka M, Takeshima K, Niwa F, Ogawa S, Hashinokuchi S, Kataoka S, Ichikawa H, Iijima H. Attenuation imaging based on ultrasound technology for assessment of hepatic steatosis: A comparison with magnetic resonance imaging-determined proton density fat fraction. Hepatol Res 2020; 50:1319-1327. [PMID: 32876367 DOI: 10.1111/hepr.13563] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/02/2020] [Accepted: 08/16/2020] [Indexed: 02/06/2023]
Abstract
AIM A new method has recently been developed for diagnosing hepatic steatosis based on attenuation measurement using ultrasound. We investigated the ability of attenuation imaging (ATI) to detect steatosis that was identified by proton density fat fraction (PDFF) on magnetic resonance imaging (MRI) in patients with chronic liver disease. METHODS A total of 119 patients with chronic liver disease (non-B, non-C) were analyzed. The relationship between ATI values and steatosis grades determined by PDFF was evaluated. Additionally, the diagnostic ability of ATI was evaluated using receiver operating characteristic curve analysis, and the correlation between ATI values and PDFF values was determined. RESULTS The ATI values of steatosis grades 0, 1, 2, and 3 were 0.55, 0.61, 0.74, and 0.84 dB/cm/MHz, respectively (P < 0.001). There was a statistically significant trend of higher ATI values with higher steatosis grades (P < 0.001). The correlation coefficient (r) between PDFF values and ATI values was 0.70 (95% confidence interval [CI] 0.59-0.78; P < 0.001), corresponding to a strong relationship. The diagnostic ability of ATI for steatosis grades ≥1, ≥2, and 3, as determined by PDFF, were 0.81 (95% CI 0.73-0.89), 0.87 (95% CI 0.79-0.96), and 0.94 (95% CI 0.89-0.98), respectively. The r between PDFF values and ATI values was 0.49 (95% CI 0.31-0.63; P < 0.001) for patients with mild or no steatosis (grade ≤1), and 0.75 (95% CI 0.57-0.86; P < 0.001) for obese patients (body mass index ≥25 kg/m2 ). CONCLUSION ATI values had an excellent diagnostic ability to detect hepatic steatosis.
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Affiliation(s)
- Toshifumi Tada
- Department of Internal Medicine, Himeji Red Cross Hospital, Himeji, Hyogo, Japan
| | - Takashi Kumada
- Faculty of Nursing, Gifu Kyoritsu University, Ogaki, Gifu, Japan
| | - Hidenori Toyoda
- Department of Gastroenterology and Hepatology, Ogaki Municipal Hospital, Ogaki, Gifu, Japan
| | - Shinichiro Nakamura
- Department of Internal Medicine, Himeji Red Cross Hospital, Himeji, Hyogo, Japan
| | - Yusuke Shibata
- Department of Internal Medicine, Himeji Red Cross Hospital, Himeji, Hyogo, Japan
| | - Satoshi Yasuda
- Department of Gastroenterology and Hepatology, Ogaki Municipal Hospital, Ogaki, Gifu, Japan
| | - Yutaka Watanuki
- Department of Clinical Laboratory, Himeji Red Cross Hospital, Himeji, Hyogo, Japan
| | - Kazuyuki Tsujii
- Department of Clinical Laboratory, Himeji Red Cross Hospital, Himeji, Hyogo, Japan
| | - Naoya Fukuda
- Department of Radiology Engineering, Himeji Red Cross Hospital, Himeji, Hyogo, Japan
| | - Mamoru Fujioka
- Department of Radiology Engineering, Himeji Red Cross Hospital, Himeji, Hyogo, Japan
| | - Kenji Takeshima
- Department of Clinical Research, Ogaki Municipal Hospital, Ogaki, Gifu, Japan
| | - Fumihiko Niwa
- Department of Clinical Research, Ogaki Municipal Hospital, Ogaki, Gifu, Japan
| | - Sadanobu Ogawa
- Department of Clinical Research, Ogaki Municipal Hospital, Ogaki, Gifu, Japan
| | | | - Saki Kataoka
- Department of Clinical Research, Ogaki Municipal Hospital, Ogaki, Gifu, Japan
| | - Hironori Ichikawa
- Department of Clinical Research, Ogaki Municipal Hospital, Ogaki, Gifu, Japan
| | - Hiroko Iijima
- Ultrasound Imaging Center, Hyogo College of Medicine, Nishinomiya, Hyogo, Japan
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36
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Liver fat quantification: where do we stand? Abdom Radiol (NY) 2020; 45:3386-3399. [PMID: 33025153 DOI: 10.1007/s00261-020-02783-1] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 09/09/2020] [Accepted: 09/21/2020] [Indexed: 12/14/2022]
Abstract
Excessive intracellular accumulation of triglycerides in the liver, or hepatic steatosis, is a highly prevalent condition affecting approximately one billion people worldwide. In the absence of secondary cause, the term nonalcoholic fatty liver disease (NAFLD) is used. Hepatic steatosis may progress into nonalcoholic steatohepatitis, the more aggressive form of NAFLD, associated with hepatic complications such as fibrosis, liver failure and hepatocellular carcinoma. Hepatic steatosis is associated with metabolic syndrome, cardiovascular disease and represents an independent risk factor for type 2 diabetes, cardiovascular disease and malignancy. Percutaneous liver biopsy is the current reference standard for NAFLD assessment; however, it is an invasive procedure associated with complications and suffers from high sampling variability, impractical for clinical routine and drug efficiency studies. Therefore, noninvasive imaging methods are increasingly used for the diagnosis and monitoring of NAFLD. Among the methods quantifying liver fat, chemical-shift-encoded MRI (CSE-MRI)-based proton density fat-fraction (PDFF) has shown the most promise. MRI-PDFF is increasingly accepted as quantitative imaging biomarker of liver fat that is transforming daily clinical practice and influencing the development of new treatments for NAFLD. Furthermore, CT is an important imaging method for detection of incidental steatosis, and the practical advantages of quantitative ultrasound hold great promise for the future. Understanding the disease burden of NAFLD and the role of imaging may initiate important interventions aimed at avoiding the hepatic and extrahepatic complications of NAFLD. This article reviews clinical burden of NAFLD, and the role of noninvasive imaging techniques for quantification of liver fat.
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37
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Langner T, Strand R, Ahlström H, Kullberg J. Large-scale biometry with interpretable neural network regression on UK Biobank body MRI. Sci Rep 2020; 10:17752. [PMID: 33082454 PMCID: PMC7576214 DOI: 10.1038/s41598-020-74633-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 10/05/2020] [Indexed: 11/14/2022] Open
Abstract
In a large-scale medical examination, the UK Biobank study has successfully imaged more than 32,000 volunteer participants with magnetic resonance imaging (MRI). Each scan is linked to extensive metadata, providing a comprehensive medical survey of imaged anatomy and related health states. Despite its potential for research, this vast amount of data presents a challenge to established methods of evaluation, which often rely on manual input. To date, the range of reference values for cardiovascular and metabolic risk factors is therefore incomplete. In this work, neural networks were trained for image-based regression to infer various biological metrics from the neck-to-knee body MRI automatically. The approach requires no manual intervention or direct access to reference segmentations for training. The examined fields span 64 variables derived from anthropometric measurements, dual-energy X-ray absorptiometry (DXA), atlas-based segmentations, and dedicated liver scans. With the ResNet50, the standardized framework achieves a close fit to the target values (median R\documentclass[12pt]{minimal}
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\begin{document}$$^2 > 0.97$$\end{document}2>0.97) in cross-validation. Interpretation of aggregated saliency maps suggests that the network correctly targets specific body regions and limbs, and learned to emulate different modalities. On several body composition metrics, the quality of the predictions is within the range of variability observed between established gold standard techniques.
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Affiliation(s)
- Taro Langner
- Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.
| | - Robin Strand
- Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.,Department of Information Technology, Uppsala University, 751 85, Uppsala, Sweden
| | - Håkan Ahlström
- Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.,Antaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden
| | - Joel Kullberg
- Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden.,Antaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden
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38
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Steger GL, Salesov E, Richter H, Reusch CE, Kircher PR, Del Chicca F. Evaluation of the changes in hepatic apparent diffusion coefficient and hepatic fat fraction in healthy cats during body weight gain. Am J Vet Res 2020; 81:796-803. [PMID: 32969732 DOI: 10.2460/ajvr.81.10.796] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To determine the change in mean hepatic apparent diffusion coefficient (ADC) and hepatic fat fraction (HFF) during body weight gain in cats by use of MRI. ANIMALS 12 purpose-bred adult neutered male cats. PROCEDURES The cats underwent general health and MRI examination at time 0 (before dietary intervention) and time 1 (after 40 weeks of being fed high-energy food ad libitum). Sequences included multiple-echo gradient-recalled echo MRI and diffusion-weighted MRI with 3 b values (0, 400, and 800 s/mm2). Variables (body weight and the HFF and ADC in selected regions of interest in the liver parenchyma) were compared between time points by Wilcoxon paired-sample tests. Relationships among variables were assessed with generalized mixed-effects models. RESULTS Median body weight was 4.5 and 6.5 kg, mean ± SD HFF was 3.39 ± 0.89% and 5.37 ± 1.92%, and mean ± SD hepatic ADC was 1.21 ± 0.08 × 10-3 mm2/s and 1.01 ± 0.2 × 10-3 mm2/s at times 0 and 1, respectively. Significant differences between time points were found for body weight, HFF, and ADC. The HFF was positively associated with body weight and ADC was negatively associated with HFF. CONCLUSIONS AND CLINICAL RELEVANCE Similar to findings in people, cats had decreasing hepatic ADC as HFF increased. Protons associated with fat tissue in the liver may reduce diffusivity, resulting in a lower ADC than in liver with lower HFF. Longer studies and evaluation of cats with different nutritional states are necessary to further investigate these findings.
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Parmar KL, O'Reilly D, Valle JW, Braun M, Naish JH, Williams SR, Lloyd WK, Malcomson L, Cresswell K, Bamford C, Renehan AG. Prospective study of change in liver function and fat in patients with colorectal liver metastases undergoing preoperative chemotherapy: protocol for the CLiFF Study. BMJ Open 2020; 10:e027630. [PMID: 32967864 PMCID: PMC7513559 DOI: 10.1136/bmjopen-2018-027630] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION Preoperative chemotherapy in patients undergoing resection for colorectal liver metastases (CLM) improves oncological outcomes. However, chemotherapy-associated liver injury (occurring in two patterns: vascular and fat deposition) is a real clinical concern prior to hepatic resection. After major liver resection, regeneration of the residual liver is a prerequisite for recovery and avoidance of liver failure, but this regenerative capacity may be hindered by chemotherapy. Thus, there is a need to predict for this serious complication. Over the past two decades, several tests and derived indices have been developed, which have failed to achieve clinical utility, mainly as they were indirect measurements of liver function. Here, we will use a novel test of liver function (the liver maximum capacity (LiMAx) test), and measure liver fat using MRI. METHODS AND ANALYSIS This prospective study will assess changes in liver function longitudinally, measured by the LiMAx test, and liver fat, measured by advanced MRI using both MR spectroscopy and the modified Dixon method, in up to 35 patients undergoing preoperative chemotherapy for CLM. The primary outcomes will be the changes in liver function and fat compared with baseline prechemotherapy measurements. Secondary outcome measures include: routinely measured liver function blood tests, anthropometric measurements, postoperative histology and digital quantification of fat, postoperative complications and mortality and quality of life. ETHICS AND DISSEMINATION The study was approved by a National Health Service Research Ethics Committee and registered with the Health Research Authority. Dissemination will be via international and national conferences and the National Institute for Health Research network. Manuscripts will be published. TRIAL REGISTRATION NUMBER This study is registered online at www.clinicaltrials.gov (registration number NCT03562234).
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Affiliation(s)
- Kat L Parmar
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Manchester Cancer Research Centre, Manchester, UK
| | - Derek O'Reilly
- Hepatobiliary Surgery, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Juan W Valle
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Oncology, Christie NHS Foundation Trust, Manchester, UK
| | - Michael Braun
- Oncology, Christie NHS Foundation Trust, Manchester, UK
| | - Jo H Naish
- Institute of Cardiovascular Sciences, University of Manchester, Manchester, UK
| | - Steve R Williams
- Centre for Imaging Sciences, University of Manchester, Manchester, UK
| | - William K Lloyd
- Centre for Imaging Sciences, University of Manchester, Manchester, UK
| | - Lee Malcomson
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Surgery, Christie NHS Foundation Trust, Manchester, UK
| | - Katharine Cresswell
- Public Programmes Team, Research and Innovation Division, Manchester University NHS Foundation Trust, Manchester, UK
| | - Colin Bamford
- Cancer Patient and Public Advisory Group, NIHR Manchester Biomedical Research Centre, Manchester, UK
| | - Andrew G Renehan
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Surgery, Christie NHS Foundation Trust, Manchester, UK
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Differences in multi-echo chemical shift encoded MRI proton density fat fraction estimation based on multifrequency fat peaks selection in non-alcoholic fatty liver disease patients. Clin Radiol 2020; 75:880.e5-880.e12. [PMID: 32888653 DOI: 10.1016/j.crad.2020.07.031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 07/28/2020] [Indexed: 11/20/2022]
Abstract
AIM To compare the performance of multi-echo chemical-shift-encoded (MECSE) magnetic resonance imaging (MRI) proton density fat fraction (PDFF) estimation, considering three different fat frequency peak combinations, for the quantification of steatosis in patients with non-alcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS The present study was a prospective cross-sectional research of 121 patients with metabolic syndrome and evidence of hepatic steatosis on ultrasound, who underwent a 3 T MRI examination. All patients were studied with a multifrequency MECSE sequence. The PDFF was calculated using six peaks (MECSEp123456), three peaks (MECSEp456), and a single peak (MECSEp5) model. The two simpler fat peak models were compared to the six peaks model, which was considered the reference standard. Linearity was evaluated using linear regression while agreement was described using Bland-Altman analysis. RESULTS The mean age was 47 (±9) years and BMI was 29.9 (±2.9) kg/m2. Steatosis distribution was 15%/31%/54% (S1/S2/S3, respectively). Compared to MECSEp123456, both models provided linear PDFF measurements (R2= 0.99 and 0.97, MECSEp456 and MECSEp5 respectively). Regression slope (0.92; p<0.001) and mean Bland-Altman bias (-1.5%; 95% limits of agreement: -3.19%, 0.22%) indicated minimal underestimation by using PDFF-MECSEp456. Nonetheless, mean differences in PDFF estimations varied from -1.5% (MECSEp456,p=0.006) to -2.2% (MECSEp5,p<0.001) when compared to full six fat frequencies model. CONCLUSION Although simpler spectral fat MECSE analysis shows a linear relationship with the standard six peaks model, their variation in estimated PDFF values introduces a low but clinically significant bias in fat quantification and steatosis grading in NAFLD patients.
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Abstract
There are >1.5 billion people with chronic liver disease worldwide, causing liver diseases to be a significant global health issue. Diffuse parenchymal liver diseases, including hepatic steatosis, fibrosis, metabolic diseases, and hepatitis cause chronic liver injury and may progress to fibrosis and eventually hepatocellular carcinoma. As early diagnosis and treatment of these diseases impact the progression and outcome, the need for assessment of the liver parenchyma has increased. While the current gold standard for evaluation of the hepatic parenchymal tissue, biopsy has disadvantages and limitations. Consequently, noninvasive methods have been developed based on serum biomarkers and imaging techniques. Conventional imaging modalities such as ultrasound, computed tomography scan, and magnetic resonance imaging provide noninvasive options for assessment of liver tissue. However, several recent advances in liver imaging techniques have been introduced. This review article focuses on the current status of imaging methods for diffuse parenchymal liver diseases assessment including their diagnostic accuracy, advantages and disadvantages, and comparison between different techniques.
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Liu Q, Nie H, Xu H, Wang P, Lei P. Noninvasive Imaging for the Evaluation of Non-Alcoholic Fatty Liver Disease Spectrum. Korean J Radiol 2020; 22:155-158. [PMID: 32767866 PMCID: PMC7772382 DOI: 10.3348/kjr.2020.0492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 04/18/2020] [Accepted: 04/24/2020] [Indexed: 11/23/2022] Open
Affiliation(s)
- Qianjiao Liu
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Hongfang Nie
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Hengtian Xu
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Pingxian Wang
- Department of Medical Insurance, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Pinggui Lei
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
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Jacobsen MC, Thrower SL. Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement. Med Phys 2020; 47:3752-3771. [PMID: 32453879 PMCID: PMC8495770 DOI: 10.1002/mp.14241] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 04/20/2020] [Accepted: 05/07/2020] [Indexed: 12/21/2022] Open
Abstract
Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual-energy CT (DECT) and photon-counting detector CT (PCD-CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD-CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi-energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image-guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.
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Affiliation(s)
- Megan C. Jacobsen
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sara L. Thrower
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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Kuetting D, Luetkens J, Fimmers R, Sprinkart AM, Attenberger U, Pieper CC. MRI Assessment of Chylous and Nonchylous Effusions: Use of Multipoint Dixon Fat Quantification. Radiology 2020; 296:698-705. [PMID: 32662762 DOI: 10.1148/radiol.2020200089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Diagnosis of chylous effusions normally requires invasive paracentesis. Purpose To assess whether MRI with multipoint Dixon fat quantification allows for noninvasive differentiation of chylous and nonchylous ascites and pleural effusions. Materials and Methods Phantom, ex vivo, and in vivo MRI examinations were performed by using a commercially available multipoint Dixon pulse sequence with a 1.5-T MRI system. Fat fraction values were measured with a region of interest-based approach on reconstructed maps. For phantom evaluation, eight titrated fatty fluid solutions (nonhuman samples) with varying triglyceride content (145-19 000 mg/dL [1.64-214.7 mmol/L]) were examined. For ex vivo evaluation, 15 chylous and five nonchylous study participant fluid samples were examined. In a prospective study performed from June 2016 to February 2018, 29 study participants with known chylous (n = 17) and nonchylous (n = 12) effusions were evaluated with MRI. All clinical samples underwent laboratory testing for triglyceride level, total protein level, white blood cells, and red blood cells. Laboratory values were correlated with fat fraction values; the optimal fat fraction threshold was determined to differentiate chylous and nonchylous fluids. Results Phantom analysis showed that fat fraction values correlated with triglyceride content (r = 0.99, P < .001). In ex vivo studies, multipoint Dixon-derived fat fraction was higher in chylous versus nonchylous fluids (mean, 2.5% ± 1.2 [standard deviation] vs 0.8% ± 0.2; P = .001). Fat fraction was correlated with triglyceride content (r = 0.96, P < .001). For in vivo studies, fat fraction was greater for chylous versus nonchylous fluids (mean, 6.2% ± 4.3 vs 0.6% ± 0.6; P < .001). In vivo fat fraction was correlated with triglyceride content (r = 0.96, P < .001). Use of a fat fraction cutoff value greater than 1.8% yielded a sensitivity of 14 of 17 (82% [95% confidence interval (CI): 57%, 97%]) and a specificity of 12 of 12 (100% [95% CI: 74%, 100%]) for differentiation of chylous and nonchylous effusions. Conclusion MRI can help identify chylous versus nonchylous ascites and pleural effusions through use of multipoint Dixon fat quantification. © RSNA, 2020 Online supplemental material is available for this article.
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Affiliation(s)
- Daniel Kuetting
- From the Department of Radiology (D.K., J.L., A.M.S., U.A., C.C.P.) and Department of Medical Biometry, Informatics, and Epidemiology (R.F.), University of Bonn, Venusberg Campus 1, 53105 Bonn, Germany
| | - Julian Luetkens
- From the Department of Radiology (D.K., J.L., A.M.S., U.A., C.C.P.) and Department of Medical Biometry, Informatics, and Epidemiology (R.F.), University of Bonn, Venusberg Campus 1, 53105 Bonn, Germany
| | - Rolf Fimmers
- From the Department of Radiology (D.K., J.L., A.M.S., U.A., C.C.P.) and Department of Medical Biometry, Informatics, and Epidemiology (R.F.), University of Bonn, Venusberg Campus 1, 53105 Bonn, Germany
| | - Alois M Sprinkart
- From the Department of Radiology (D.K., J.L., A.M.S., U.A., C.C.P.) and Department of Medical Biometry, Informatics, and Epidemiology (R.F.), University of Bonn, Venusberg Campus 1, 53105 Bonn, Germany
| | - Ulrike Attenberger
- From the Department of Radiology (D.K., J.L., A.M.S., U.A., C.C.P.) and Department of Medical Biometry, Informatics, and Epidemiology (R.F.), University of Bonn, Venusberg Campus 1, 53105 Bonn, Germany
| | - Claus C Pieper
- From the Department of Radiology (D.K., J.L., A.M.S., U.A., C.C.P.) and Department of Medical Biometry, Informatics, and Epidemiology (R.F.), University of Bonn, Venusberg Campus 1, 53105 Bonn, Germany
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de Boer A, Harteveld AA, Stemkens B, Blankestijn PJ, Bos C, Franklin SL, Froeling M, Joles JA, Verhaar MC, van den Berg N, Hoogduin H, Leiner T. Multiparametric Renal MRI: An Intrasubject Test-Retest Repeatability Study. J Magn Reson Imaging 2020; 53:859-873. [PMID: 32297700 PMCID: PMC7891585 DOI: 10.1002/jmri.27167] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 03/30/2020] [Accepted: 03/31/2020] [Indexed: 12/13/2022] Open
Abstract
Background Renal multiparametric magnetic resonance imaging (MRI) is a promising tool for diagnosis, prognosis, and treatment monitoring in kidney disease. Purpose To determine intrasubject test–retest repeatability of renal MRI measurements. Study Type Prospective. Population Nineteen healthy subjects aged over 40 years. Field Strength/Sequences T1 and T2 mapping, R2* mapping or blood oxygenation level‐dependent (BOLD) MRI, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM) diffusion‐weighted imaging (DWI), 2D phase contrast, arterial spin labelling (ASL), dynamic contrast enhanced (DCE) MRI, and quantitative Dixon for fat quantification at 3T. Assessment Subjects were scanned twice with ~1 week between visits. Total scan time was ~1 hour. Postprocessing included motion correction, semiautomated segmentation of cortex and medulla, and fitting of the appropriate signal model. Statistical Test To assess the repeatability, a Bland–Altman analysis was performed and coefficients of variation (CoVs), repeatability coefficients, and intraclass correlation coefficients were calculated. Results CoVs for relaxometry (T1, T2, R2*/BOLD) were below 6.1%, with the lowest CoVs for T2 maps and highest for R2*/BOLD. CoVs for all diffusion analyses were below 7.2%, except for perfusion fraction (FP), with CoVs ranging from 18–24%. The CoV for renal sinus fat volume and percentage were both around 9%. Perfusion measurements were most repeatable with ASL (cortical perfusion only) and 2D phase contrast with CoVs of 10% and 13%, respectively. DCE perfusion had a CoV of 16%, while single kidney glomerular filtration rate (GFR) had a CoV of 13%. Repeatability coefficients (RCs) ranged from 7.7–87% (lowest/highest values for medullary mean diffusivity and cortical FP, respectively) and intraclass correlation coefficients (ICCs) ranged from −0.01 to 0.98 (lowest/highest values for cortical FP and renal sinus fat volume, respectively). Data Conclusion CoVs of most MRI measures of renal function and structure (with the exception of FP and perfusion as measured by DCE) were below 13%, which is comparable to standard clinical tests in nephrology. Level of Evidence 2 Technical Efficacy Stage 1
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Affiliation(s)
- Anneloes de Boer
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Anita A Harteveld
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Bjorn Stemkens
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Peter J Blankestijn
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Clemens Bos
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Suzanne L Franklin
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, The Netherlands
| | - Martijn Froeling
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jaap A Joles
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marianne C Verhaar
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Nico van den Berg
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Hans Hoogduin
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Tim Leiner
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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Abstract
Objective Today, a biopsy is the gold standard in the diagnosis of non-alcoholic fatty liver. However, a biopsy is an invasive technique, limited to the sample taken, and it may lead to misdiagnosis. Therefore, novel noninvasive options are needed. The objective of this study was to investigate the accuracy of magnetic resonance (MR) Dixon sequence and elastography using magnetic resonance spectroscopy (MRS) as a reference in the quantification of hepatic steatosis. Methods A total of 60 patients were included in the study. All patients underwent magnetic resonance imaging (MRI), MRS, and elastography in order to quantify hepatosteatosis. MRI and MRS imaging studies were performed using MR Dixon and high-speed T2-corrected multiple-echo 1H-MRS sequence (HISTO) sequences, respectively, in order to calculate proton density fat fraction (PDFF) values. Results The mean MRI-PDFF value with the MRS region of interest (ROI) was found as 9.4% ± 12.1%. The mean MRS-PDFF was found as 8.9% ± 11.3%. No statistically significant difference was found between MRS-PDFF and MRI-PDFF values measured in ROI (p < 0.005). The correlation between MRS-PDFF and MRI-PDFF was examined with Spearman’s correlation analysis. Accordingly, there was an excellent correlation between MRS and MRI values measured in ROI (r ≥ 0.8, p < 0.001). Sensitivity, specificity, positive predictive value, and negative predictive value were calculated as 96%, 100%, 89.5%, and 92.6%, respectively, for MRI-PDFF in predicting hepatic steatosis for the same ROI localization with MRS. The optimum cut-off value of MRS-PDFF in predicting hepatic steatosis was found as 5.3% using the same ROI localization with MRS. Conclusion The results of this study indicated an excellent correlation between MRI-PDFF and MRS-PDFF. The multi-echo Dixon MRI technique seems a promising alternative method in the detection of non-alcoholic fatty liver disease.
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Affiliation(s)
- Isil Yurdaisik
- Radiology, Istinye University Gaziosmanpasa Medical Park Hospital, Istanbul, TUR
| | - Fuad Nurili
- Radiology, Memorial Sloan Kettering Cancer Center, New York, USA
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Labayen I, Medrano M, Arenaza L, Maíz E, Osés M, Martínez-Vizcaíno V, Ruiz JR, Ortega FB. Effects of Exercise in Addition to a Family-Based Lifestyle Intervention Program on Hepatic Fat in Children With Overweight. Diabetes Care 2020; 43:306-313. [PMID: 31227585 DOI: 10.2337/dc19-0351] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 05/17/2019] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Pediatric hepatic steatosis is highly prevalent and closely related to type 2 diabetes. This study aimed to determine whether the addition of supervised exercise to a family-based lifestyle and psycho-educational intervention results in greater reduction of percentage of hepatic fat (HF), adiposity, and cardiometabolic risk factors in children with overweight/obesity. RESEARCH DESIGN AND METHODS The study subjects of this nonrandomized, two-arm, parallel design clinical trial were 116 overweight/obese children (10.6 ± 1.1 years of age, 53.4% girls) living in Vitoria-Gasteiz (Spain). For 22 weeks, they followed either a lifestyle and psycho-education program (control intervention [CInt], N = 57), consisting of two family-based education sessions/month, or the same plus supervised exercise (intensive intervention [II], N = 59) focused mainly on high-intensity aerobic workouts (3 sessions/week, 90 min/session). The primary outcome was the change in percentage of HF (as measured by MRI) between baseline and the end of the intervention period. Secondary outcomes included changes in BMI, fat mass index (FMI), abdominal fat (measured by DEXA), blood pressure, triglycerides, HDL, LDL, γ-glutamyl transferase, glucose, and insulin concentrations. RESULTS A total of 102 children completed the trial (N = 53 and N = 49 in the CInt and II groups, respectively). Percentage of HF decreased only in the II group (-1.20 ± 0.31% vs. 0.04 ± 0.30%, II and CInt groups, respectively), regardless of baseline value and any change in adiposity (P < 0.01). BMI, FMI, abdominal fat (P ≤ 0.001), and insulin (P < 0.05) were reduced in both groups. CONCLUSIONS Multicomponent intervention programs that include exercise training may help to reduce adiposity, insulin resistance, and hepatic steatosis in overweight/obese children.
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Affiliation(s)
- Idoia Labayen
- Institute for Innovation & Sustainable Development in the Food Chain (IS-FOOD), Public University of Navarra, Pamplona, Spain
| | - María Medrano
- Institute for Innovation & Sustainable Development in the Food Chain (IS-FOOD), Public University of Navarra, Pamplona, Spain
| | - Lide Arenaza
- Institute for Innovation & Sustainable Development in the Food Chain (IS-FOOD), Public University of Navarra, Pamplona, Spain
| | - Edurne Maíz
- University of the Basque Country, Donostia, Spain
| | - Maddi Osés
- Institute for Innovation & Sustainable Development in the Food Chain (IS-FOOD), Public University of Navarra, Pamplona, Spain
| | - Vicente Martínez-Vizcaíno
- Health and Social Research Center, Universidad de Castilla-La Mancha, Cuenca, Spain.,Universidad Autónoma de Chile, Talca, Chile
| | - Jonatan R Ruiz
- PROFITH "PROmoting FITness and Health through physical activity" Research Group, Department of Physical and Sports Education, Faculty of Sports Sciences, University of Granada, Granada, Spain
| | - Francisco B Ortega
- PROFITH "PROmoting FITness and Health through physical activity" Research Group, Department of Physical and Sports Education, Faculty of Sports Sciences, University of Granada, Granada, Spain
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Kořínek R, Gajdošík M, Trattnig S, Starčuk Z, Krššák M. Low-level fat fraction quantification at 3 T: comparative study of different tools for water-fat reconstruction and MR spectroscopy. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2020; 33:455-468. [PMID: 31980962 DOI: 10.1007/s10334-020-00825-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 12/12/2019] [Accepted: 01/03/2020] [Indexed: 12/22/2022]
Abstract
OBJECTIVES Chemical Shift Encoded Magnetic Resonance Imaging (CSE-MRI)-based quantification of low-level (< 5% of proton density fat fraction-PDFF) fat infiltration requires highly accurate data reconstruction for the assessment of hepatic or pancreatic fat accumulation in diagnostics and biomedical research. MATERIALS AND METHODS We compare three software tools available for water/fat image reconstruction and PDFF quantification with MRS as the reference method. Based on the algorithm exploited in the tested software, the accuracy of fat fraction quantification varies. We evaluate them in phantom and in vivo MRS and MRI measurements. RESULTS The signal model of Intralipid 20% emulsion used for phantoms was established for 3 T and 9.4 T fields. In all cases, we noticed a high coefficient of determination (R-squared) between MRS and MRI-PDFF measurements: in phantoms <0.9924-0.9990>; and in vivo <0.8069-0.9552>. Bland-Altman analysis was applied to phantom and in vivo measurements. DISCUSSION Multi-echo MRI in combination with an advanced algorithm including multi-peak spectrum modeling appears as a valuable and accurate method for low-level PDFF quantification over large FOV in high resolution, and is much faster than MRS methods. The graph-cut algorithm (GC) showed the fewest water/fat swaps in the PDFF maps, and hence stands out as the most robust method of those tested.
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Affiliation(s)
- Radim Kořínek
- Institute of Scientific Instruments of the CAS, Kralovopolska 147, 612 64, Brno, Czech Republic.
| | - Martin Gajdošík
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Centre, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.,Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, 1210 Amsterdam Ave, New York, NY, 10027, USA
| | - Siegfried Trattnig
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Centre, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular Imaging, MOLIMA, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Zenon Starčuk
- Institute of Scientific Instruments of the CAS, Kralovopolska 147, 612 64, Brno, Czech Republic
| | - Martin Krššák
- Department of Biomedical Imaging and Image-Guided Therapy, High-Field MR Centre, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular Imaging, MOLIMA, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.,Division of Endocrinology and Metabolism, Department of Medicine III, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
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Guo Z, Blake GM, Li K, Liang W, Zhang W, Zhang Y, Xu L, Wang L, Brown JK, Cheng X, Pickhardt PJ. Liver Fat Content Measurement with Quantitative CT Validated against MRI Proton Density Fat Fraction: A Prospective Study of 400 Healthy Volunteers. Radiology 2020; 294:89-97. [PMID: 31687918 DOI: 10.1148/radiol.2019190467] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Background Although chemical shift-encoded (CSE) MRI proton density fat fraction (PDFF) is the current noninvasive reference standard for liver fat quantification, the liver is more frequently imaged with CT. Purpose To validate quantitative CT measurements of liver fat against the MRI PDFF reference standard. Materials and Methods In this prospective study, 400 healthy participants were recruited between August 2015 and July 2016. Each participant underwent same-day abdominal unenhanced quantitative CT with a calibration phantom and CSE 3.0-T MRI. CSE MRI liver fat measurements were used to calibrate an equation to adjust CT fat measurements and put them on the PDFF measurement scale. CT and PDFF liver fat measurements were plotted as histograms, medians, and interquartile ranges compared; scatterplots and Bland-Altman plots obtained; and Pearson correlation coefficients calculated. Receiver operating characteristic curves including areas under the curve were evaluated for mild (PDFF, 5%) and moderate (PDFF, 14%) steatosis thresholds for both raw and adjusted CT measurements. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. Results Four hundred volunteers (mean age, 52.6 years ± 15.2; 227 women) were evaluated. MRI PDFF measurements of liver fat ranged between 0% and 28%, with 41.5% (166 of 400) of participants with PDFF greater than 5%. Both raw and adjusted quantitative CT values correlated well with MRI PDFF (r2 = 0.79; P < .001). Bland-Altman analysis of adjusted CT values showed no slope or bias. Both raw and adjusted CT had areas under the receiver operating characteristic curve of 0.87 and 0.99, respectively, to identify participants with mild (PDFF, >5%) and moderate (PDFF, >14%) steatosis, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for unadjusted CT was 75.9% (126 of 166), 85.0% (199 of 234), 78.3% (126 of 161), and 83.3% (199 of 239), respectively, for PDFF greater than 5%; and 84.8% (28 of 33), 98.4% (361 of 367), 82.4% (28 of 34), and 98.6% (361 of 366), respectively, for PDFF greater than 14%. Results for adjusted CT were mostly identical. Conclusion Quantitative CT liver fat exhibited good correlation and accuracy with proton density fat fraction measured with chemical shift-encoded MRI. © RSNA, 2019 Online supplemental material is available for this article.
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Affiliation(s)
- Zhe Guo
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - Glen M Blake
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - Kai Li
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - Wei Liang
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - Wei Zhang
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - Yong Zhang
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - Li Xu
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - Ling Wang
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - J Keenan Brown
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - Xiaoguang Cheng
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
| | - Perry J Pickhardt
- From the Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing 100035, China (Z.G., K.L., W.L., W.Z., Y.Z., L.X., L.W., X.C.); School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, England (G.M.B.); Mindways Software Inc, Austin, Tex (J.K.B.); and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wis (P.J.P.)
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Shi X, Ye W, Liu F, Zhang R, Hou Q, Shi C, Yu J, Shi Y. Ultrasonic liver steatosis quantification by a learning-based acoustic model from a novel shear wave sequence. Biomed Eng Online 2019; 18:121. [PMID: 31864367 PMCID: PMC6925885 DOI: 10.1186/s12938-019-0742-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 12/10/2019] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND An efficient and accurate approach to quantify the steatosis extent of liver is important for clinical practice. For the purpose, we propose a specific designed ultrasound shear wave sequence to estimate ultrasonic and shear wave physical parameters. The utilization of the estimated quantitative parameters is then studied. RESULTS Shear wave attenuation, shear wave absorption, elasticity, dispersion slope and echo attenuation were simultaneously estimated and quantified from the proposed novel shear wave sequence. Then, a regression tree model was utilized to learn the connection between the space represented by all the physical parameters and the liver fat proportion. MR mDIXON quantification was used as the ground truth for liver fat quantification. Our study included a total of 60 patients. Correlation coefficient (CC) with the ground truth were applied to mainly evaluate different methods for which the corresponding values were - 0.25, - 0.26, 0.028, 0.045, 0.46 and 0.83 for shear wave attenuation, shear wave absorption, elasticity, dispersion slope, echo attenuation and the learning-based model, respectively. The original parameters were extremely outperformed by the learning-based model for which the root mean square error for liver steatosis quantification is only 4.5% that is also state-of-the-art for ultrasound application in the related field. CONCLUSIONS Although individual ultrasonic and shear wave parameters were not perfectly adequate for liver steatosis quantification, a promising result can be achieved by the proposed learning-based acoustic model based on them.
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Affiliation(s)
- Xiudong Shi
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Wen Ye
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Fengjun Liu
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Rengyin Zhang
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Qinguo Hou
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Chunzi Shi
- Department of Pathology, School of Basic Medical Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jinhua Yu
- Department of Electronic Engineering, Fudan University, Shanghai, China. .,Key Laboratory of Medical Imaging, Computing and Computer Assisted Intervention, Shanghai, China.
| | - Yuxin Shi
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
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