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Bastati N, Perkonigg M, Sobotka D, Poetter-Lang S, Fragner R, Beer A, Messner A, Watzenboeck M, Pochepnia S, Kittinger J, Herold A, Kristic A, Hodge JC, Traussnig S, Trauner M, Ba-Ssalamah A, Langs G. Correlation of histologic, imaging, and artificial intelligence features in NAFLD patients, derived from Gd-EOB-DTPA-enhanced MRI: a proof-of-concept study. Eur Radiol 2023; 33:7729-7743. [PMID: 37358613 PMCID: PMC10598123 DOI: 10.1007/s00330-023-09735-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 03/25/2023] [Accepted: 04/14/2023] [Indexed: 06/27/2023]
Abstract
OBJECTIVE To compare unsupervised deep clustering (UDC) to fat fraction (FF) and relative liver enhancement (RLE) on Gd-EOB-DTPA-enhanced MRI to distinguish simple steatosis from non-alcoholic steatohepatitis (NASH), using histology as the gold standard. MATERIALS AND METHODS A derivation group of 46 non-alcoholic fatty liver disease (NAFLD) patients underwent 3-T MRI. Histology assessed steatosis, inflammation, ballooning, and fibrosis. UDC was trained to group different texture patterns from MR data into 10 distinct clusters per sequence on unenhanced T1- and Gd-EOB-DTPA-enhanced T1-weighted hepatobiliary phase (T1-Gd-EOB-DTPA-HBP), then on T1 in- and opposed-phase images. RLE and FF were quantified on identical sequences. Differences of these parameters between NASH and simple steatosis were evaluated with χ2- and t-tests, respectively. Linear regression and Random Forest classifier were performed to identify associations between histological NAFLD features, RLE, FF, and UDC patterns, and then determine predictors able to distinguish simple steatosis from NASH. ROC curves assessed diagnostic performance of UDC, RLE, and FF. Finally, we tested these parameters on 30 validation cohorts. RESULTS For the derivation group, UDC-derived features from unenhanced and T1-Gd-EOB-DTPA-HBP, plus from T1 in- and opposed-phase, distinguished NASH from simple steatosis (p ≤ 0.001 and p = 0.02, respectively) with 85% and 80% accuracy, respectively, while RLE and FF distinguished NASH from simple steatosis (p ≤ 0.001 and p = 0.004, respectively), with 83% and 78% accuracy, respectively. On multivariate regression analysis, RLE and FF correlated only with fibrosis (p = 0.040) and steatosis (p ≤ 0.001), respectively. Conversely, UDC features, using Random Forest classifier predictors, correlated with all histologic NAFLD components. The validation group confirmed these results for both approaches. CONCLUSION UDC, RLE, and FF could independently separate NASH from simple steatosis. UDC may predict all histologic NAFLD components. CLINICAL RELEVANCE STATEMENT Using gadoxetic acid-enhanced MR, fat fraction (FF > 5%) can diagnose NAFLD, and relative liver enhancement can distinguish NASH from simple steatosis. Adding AI may let us non-invasively estimate the histologic components, i.e., fat, ballooning, inflammation, and fibrosis, the latter the main prognosticator. KEY POINTS • Unsupervised deep clustering (UDC) and MR-based parameters (FF and RLE) could independently distinguish simple steatosis from NASH in the derivation group. • On multivariate analysis, RLE could predict only fibrosis, and FF could predict only steatosis; however, UDC could predict all histologic NAFLD components in the derivation group. • The validation cohort confirmed the findings for the derivation group.
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Affiliation(s)
- Nina Bastati
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Matthias Perkonigg
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Sarah Poetter-Lang
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Romana Fragner
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Andrea Beer
- Department of Pathology, Medical University of Vienna, Vienna, Austria
| | - Alina Messner
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Martin Watzenboeck
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Svitlana Pochepnia
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Jakob Kittinger
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Alexander Herold
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Antonia Kristic
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Jacqueline C Hodge
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Stefan Traussnig
- Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria
| | - Michael Trauner
- Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria
| | - Ahmed Ba-Ssalamah
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
- Department of Biomedical Imaging and Image-Guided Therapy, General Hospital of Vienna (AKH), Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
| | - Georg Langs
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
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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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Accuracy of Liver Fat Quantification With Advanced CT, MRI, and Ultrasound Techniques: Prospective Comparison With MR Spectroscopy. AJR Am J Roentgenol 2016; 208:92-100. [PMID: 27726414 DOI: 10.2214/ajr.16.16565] [Citation(s) in RCA: 163] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVE The purpose of this study was to prospectively evaluate the accuracy of proton-density fat-fraction, single- and dual-energy CT (SECT and DECT), gray-scale ultrasound (US), and US shear-wave elastography (US-SWE) in the quantification of hepatic steatosis with MR spectroscopy (MRS) as the reference standard. SUBJECTS AND METHODS Fifty adults who did not have symptoms (23 men, 27 women; mean age, 57 ± 5 years; body mass index, 27 ± 5) underwent liver imaging with un-enhanced SECT, DECT, gray-scale US, US-SWE, proton-density fat-fraction MRI, and MRS for this prospective trial. MRS voxels for the reference standard were colocalized with all other modalities under investigation. For SECT (120 kVp), attenuation values were recorded. For rapid-switching DECT (80/140 kVp), monochromatic images (70-140 keV) and fat density-derived material decomposition images were reconstructed. For proton-density fat fraction MRI, a quantitative chemical shift-encoded method was used. For US, echogenicity was evaluated on a qualitative 0-3 scale. Quantitative US shear-wave velocities were also recorded. Data were analyzed by linear regression for each technique compared with MRS. RESULTS There was excellent correlation between MRS and both proton-density fat-fraction MRI (r2 = 0.992; slope, 0.974; intercept, -0.943) and SECT (r2 = 0.856; slope, -0.559; intercept, 35.418). DECT fat attenuation had moderate correlation with MRS measurements (r2 = 0.423; slope, 0.034; intercept, 8.459). There was good correlation between qualitative US echogenicity and MRS measurements with a weighted kappa value of 0.82. US-SWE velocity did not have reliable correlation with MRS measurements (r2 = 0.004; slope, 0.069; intercept, 6.168). CONCLUSION Quantitative MRI proton-density fat fraction and SECT fat attenuation have excellent linear correlation with MRS measurements and can serve as accurate noninvasive biomarkers for quantifying steatosis. Material decomposition with DECT does not improve the accuracy of fat quantification over conventional SECT attenuation. US-SWE has poor accuracy for liver fat quantification.
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Goceri E, Shah ZK, Layman R, Jiang X, Gurcan MN. Quantification of liver fat: A comprehensive review. Comput Biol Med 2016; 71:174-89. [PMID: 26945465 DOI: 10.1016/j.compbiomed.2016.02.013] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Revised: 02/18/2016] [Accepted: 02/19/2016] [Indexed: 12/19/2022]
Abstract
Fat accumulation in the liver causes metabolic diseases such as obesity, hypertension, diabetes or dyslipidemia by affecting insulin resistance, and increasing the risk of cardiac complications and cardiovascular disease mortality. Fatty liver diseases are often reversible in their early stage; therefore, there is a recognized need to detect their presence and to assess its severity to recognize fat-related functional abnormalities in the liver. This is crucial in evaluating living liver donors prior to transplantation because fat content in the liver can change liver regeneration in the recipient and donor. There are several methods to diagnose fatty liver, measure the amount of fat, and to classify and stage liver diseases (e.g. hepatic steatosis, steatohepatitis, fibrosis and cirrhosis): biopsy (the gold-standard procedure), clinical (medical physics based) and image analysis (semi or fully automated approaches). Liver biopsy has many drawbacks: it is invasive, inappropriate for monitoring (i.e., repeated evaluation), and assessment of steatosis is somewhat subjective. Qualitative biomarkers are mostly insufficient for accurate detection since fat has to be quantified by a varying threshold to measure disease severity. Therefore, a quantitative biomarker is required for detection of steatosis, accurate measurement of severity of diseases, clinical decision-making, prognosis and longitudinal monitoring of therapy. This study presents a comprehensive review of both clinical and automated image analysis based approaches to quantify liver fat and evaluate fatty liver diseases from different medical imaging modalities.
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Affiliation(s)
- Evgin Goceri
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, USA.
| | - Zarine K Shah
- Department of Radiology, Wexner Medical Center, The Ohio State University, Columbus, USA
| | - Rick Layman
- Department of Radiology, Wexner Medical Center, The Ohio State University, Columbus, USA
| | - Xia Jiang
- Department of Radiology, Wexner Medical Center, The Ohio State University, Columbus, USA
| | - Metin N Gurcan
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, USA
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Tan C, Cai S, Huang Y. Spatially Localized Two-Dimensional J-Resolved NMR Spectroscopy via Intermolecular Double-Quantum Coherences for Biological Samples at 7 T. PLoS One 2015. [PMID: 26207739 PMCID: PMC4514627 DOI: 10.1371/journal.pone.0134109] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Background and Purpose Magnetic resonance spectroscopy (MRS) constitutes a mainstream technique for characterizing biological samples. Benefiting from the separation of chemical shifts and J couplings, spatially localized two-dimensional (2D) J-resolved spectroscopy (JPRESS) shows better identification of complex metabolite resonances than one-dimensional MRS does and facilitates the extraction of J coupling information. However, due to variations of macroscopic magnetic susceptibility in biological samples, conventional JPRESS spectra generally suffer from the influence of field inhomogeneity. In this paper, we investigated the implementation of the localized 2D J-resolved spectroscopy based on intermolecular double-quantum coherences (iDQCs) on a 7 T MRI scanner. Materials and Methods A γ-aminobutyric acid (GABA) aqueous solution, an intact pig brain tissue, and a whole fish (Harpadon nehereus) were explored by using the localized iDQC J-resolved spectroscopy (iDQCJRES) method, and the results were compared to those obtained by using the conventional 2D JPRESS method. Results Inhomogeneous line broadening, caused by the variations of macroscopic magnetic susceptibility in the detected biological samples (the intact pig brain tissue and the whole fish), degrades the quality of 2D JPRESS spectra, particularly when a large voxel is selected and some strongly structured components are included (such as the fish spinal cord). By contrast, high-resolution 2D J-resolved information satisfactory for metabolite analyses can be obtained from localized 2D iDQCJRES spectra without voxel size limitation and field shimming. From the contrastive experiments, it is obvious that the spectral information observed in the localized iDQCJRES spectra acquired from large voxels without field shimming procedure (i.e. in inhomogeneous fields) is similar to that provided by the JPRESS spectra acquired from small voxels after field shimming procedure (i.e. in relatively homogeneous fields). Conclusion The localized iDQCJRES method holds advantage for recovering high-resolution 2D J-resolved information from inhomogeneous fields caused by external non-ideal field condition or internal macroscopic magnetic susceptibility variations in biological samples, and it is free of voxel size limitation and time-consuming field shimming procedure. This method presents a complementary way to the conventional JPRESS method for MRS measurements on MRI systems equipped with broad inner bores, and may provide a promising tool for in vivo MRS applications.
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Affiliation(s)
- Chunhua Tan
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Yuqing Huang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
- * E-mail:
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Garnov N, Linder N, Schaudinn A, Blüher M, Karlas T, Schütz T, Dietrich A, Kahn T, Busse H. Comparison of T1 relaxation times in adipose tissue of severely obese patients and healthy lean subjects measured by 1.5 T MRI. NMR IN BIOMEDICINE 2014; 27:1123-1128. [PMID: 25066754 DOI: 10.1002/nbm.3166] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2013] [Revised: 06/17/2014] [Accepted: 06/22/2014] [Indexed: 06/03/2023]
Abstract
Subcutaneous (SAT) and visceral adipose tissue (VAT) differ in composition, endocrine function and localization in the body. VAT is considered to play a role in the pathogenesis of insulin resistance, type 2 diabetes, fatty liver disease, and other obesity-related disorders. It has been shown that the amount, distribution, and (cellular) composition of adipose tissue (AT) correlate well with metabolic conditions. In this study, T1 relaxation times of AT were measured in severely obese subjects and compared with those of healthy lean controls. Here, we tested the hypothesis that T1 relaxation times of AT differ between lean and obese individuals, but also between VAT and SAT as well as superficial (sSAT) and deep SAT (dSAT) in the same individual. Twenty severely obese subjects (BMI 41.4 ± 4.8 kg/m(2) ) and ten healthy lean controls matched for age (BMI 21.5 ± 1.9 kg/m(2) ) underwent MRI at 1.5 T using a single-shot fast spin-echo sequence (short-tau inversion recovery) at six different inversion times (TI range 100-1000 ms). T1 relaxation times were computed for all subjects by fitting the TI -dependent MR signal intensities of user-defined regions of interest in both SAT and VAT to a model function. T1 times in sSAT and dSAT were only measured in obese patients. For both obese patients and controls, the T1 times of SAT (275 ± 14 and 301 ± 12 ms) were significantly (p < 0.01) shorter than the respective values in VAT (294 ± 20 and 360 ± 35 ms). Obese subjects also showed significant (p < 0.01) T1 differences between sSAT (268 ± 11 ms) and dSAT (281 ± 19 ms). More important, T1 differences in both SAT and VAT were highly significant (p < 0.001) between obese patients and healthy subjects. The results of our pilot study suggest that T1 relaxation times differ between severely obese patients and lean controls, and may potentially provide an additional means for the non-invasive assessment of AT conditions and dysfunction.
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Affiliation(s)
- Nikita Garnov
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Leipzig, Germany; Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany
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Current Technological Advances in Magnetic Resonance With Critical Impact for Clinical Diagnosis and Therapy. Invest Radiol 2013; 48:869-77. [DOI: 10.1097/01.rli.0000434380.71793.d3] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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MRI-diagnosed nonalcoholic fatty liver disease is correlated to insulin resistance in adolescents. Acad Radiol 2013; 20:1436-42. [PMID: 24119357 DOI: 10.1016/j.acra.2013.08.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2013] [Revised: 08/17/2013] [Accepted: 08/23/2013] [Indexed: 12/16/2022]
Abstract
RATIONALE AND OBJECTIVES To evaluate the presence of nonalcoholic fatty liver disease (NAFLD) in eutrophic and obese adolescents with magnetic resonance imaging (MRI) and its relationship to insulin resistance and other potential biomarkers. MATERIALS AND METHODS A total of 50 adolescents (aged 11-17 years), including 24 obese and 26 eutrophic adolescents, were evaluated using MRI exams for NAFLD diagnosis. Blood analysis was performed to measure glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, triglycerides, fibrinogen, aminotransferases, alkaline phosphatase, gamma-gt, and C-reactive protein. The Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) index was also calculated. Laboratory test results and anthropometric assessment were statistically analyzed to determine potential correlation with NAFLD prevalence. RESULTS The prevalence of NAFLD among the obese was significantly higher (83.3%; CI 95: 64.5-94.5%) than that of the eutrophic group (19.2%; CI 95: 7.4-37.6%). In multivariate analysis, only HOMA-IR was an independent risk factor for diagnosis NAFLD using MRI. Compared to eutrophic adolescents, the obese adolescents had significantly higher levels for all parameters measured except for total and high-density lipoprotein cholesterol, which were significantly lower. CONCLUSION The prevalence of NAFLD was 19.2% among eutrophic patients and 83.3% among obese patients. Only HOMA-IR was determined to be an independent risk factor for NAFLD.
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Qi J, Fong Y, Saltz L, D'Angelica MI, Kemeny NE, Gonen M, Shia J, Shukla-Dave A, Jarnagin WM, Do RKG, Schwartz LH, Koutcher JA, Zakian KL. Serial measurement of hepatic lipids during chemotherapy in patients with colorectal cancer: a 1 H MRS study. NMR IN BIOMEDICINE 2013; 26:204-12. [PMID: 22961714 PMCID: PMC3519948 DOI: 10.1002/nbm.2837] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2012] [Revised: 06/20/2012] [Accepted: 06/21/2012] [Indexed: 05/12/2023]
Abstract
Hepatic steatosis is a hallmark of chemotherapy-induced liver injury. We made serial (1) H MRS measurements of hepatic lipids in patients over the time course of a 24-week chemotherapeutic regimen to determine whether (1) H MRS could be used to monitor the progression of chemotherapy-induced steatosis. Thirty-four patients with stage III or IV colorectal cancer receiving 5-fluorouracil, folinic acid and oxaliplatin (n=21) or hepatic arterial infusion of floxuridine with systemic irinotecan (n=13) were studied prospectively. (1) H MRS studies were performed at baseline and after 6 and 24 weeks of treatment. A (1) H MR spectrum was acquired from the liver during a breath hold and the ratio of fat to fat+water (FFW) was calculated to give a measure of hepatic triglycerides (HTGCs). The methodology was histologically validated in 18 patients and the reproducibility was assessed in 16 normal volunteers. Twenty-seven patients completed baseline, 6-week and 24-week (1) H MRS examinations and one was censored. Thirteen of 26 patients (50%) showed an increase in FFW after completion of treatment. Six patients (23%) developed hepatic steatosis and two patients converted from steatosis to nonsteatotic liver. Patients whose 6-week hepatic lipid levels had increased significantly relative to baseline also had a high probability of lipid elevation relative to baseline at the completion of treatment. Serial (1) H MRS is effective for the monitoring of HTGC changes during chemotherapy and for the detection of chemotherapy-associated steatosis. Six of 26 patients developed steatosis during chemotherapy. Lipid changes were observable at 6 weeks.
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Affiliation(s)
- Jing Qi
- Memorial Sloan-Kettering Cancer Center, New York, New York, USA
| | - Yuman Fong
- Memorial Sloan-Kettering Cancer Center, New York, New York, USA
| | - Leonard Saltz
- Memorial Sloan-Kettering Cancer Center, New York, New York, USA
| | | | - Nancy E. Kemeny
- Memorial Sloan-Kettering Cancer Center, New York, New York, USA
| | - Mithat Gonen
- Memorial Sloan-Kettering Cancer Center, New York, New York, USA
| | - Jinru Shia
- Memorial Sloan-Kettering Cancer Center, New York, New York, USA
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Hepatic fat quantification: a prospective comparison of magnetic resonance spectroscopy and analysis methods for chemical-shift gradient echo magnetic resonance imaging with histologic assessment as the reference standard. Invest Radiol 2012; 47:368-75. [PMID: 22543969 DOI: 10.1097/rli.0b013e31824baff3] [Citation(s) in RCA: 84] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVE The aims of this study were to assess the confounding effects of hepatic iron deposition, inflammation, and fibrosis on hepatic steatosis (HS) evaluation by magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) and to assess the accuracies of MRI and MRS for HS evaluation, using histology as the reference standard. MATERIALS AND METHODS In this institutional review board-approved prospective study, 56 patients gave informed consents and underwent chemical-shift MRI and MRS of the liver on a 1.5-T magnetic resonance scanner. To estimate MRI fat fraction (FF), 4 analysis methods were used (dual-echo, triple-echo, multiecho, and multi-interference), and MRS FF was calculated with T2 correction. Degrees of HS, iron deposition, inflammation, and fibrosis were analyzed in liver resection (n = 37) and biopsy (n = 19) specimens. The confounding effects of histology on fat quantification were assessed by multiple linear regression analysis. Using the histologic degree of HS as the reference standard, the accuracies of each method in estimating HS and diagnosing an HS of 5% or greater were determined by linear regression and receiver operating characteristic analyses. RESULTS Iron deposition significantly confounded estimations of FF by the dual-echo (P < 0.001) and triple-echo (P = 0.033) methods, whereas no histologic feature confounded the multiecho and multi-interference methods or MRS. The MRS (r = 0.95) showed the strongest correlation with histologic degree of HS, followed by the multiecho (r = 0.92), multi-interference (r = 0.91), triple-echo (r = 0.90), and dual-echo (r = 0.85) methods. For diagnosing HS, the areas under the curve tended to be higher for MRS (0.96) and the multiecho (0.95), multi-interference (0.95), and triple-echo (0.95) methods than for the dual-echo method (0.88) (P ≥ 0.13). CONCLUSION The multiecho and multi-interference MRI methods and MRS can accurately quantify hepatic fat, with coexisting histologic abnormalities having no confounding effects.
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Abstract
Excess body adiposity, especially abdominal obesity and ectopic fat accumulation, are key risk factors in the development of a number of chronic diseases. The advent of in vivo imaging methodologies that allow direct assessment of total body fat and its distribution have been pivotal in this process. They have helped to identify a number of sub-phenotypes in the general population whose metabolic risk factors are not commensurate with their BMI. At least two such sub-phenotypes have been identified: subjects with normal BMI, but excess intra-abdominal (visceral) fat (with or without increased ectopic fat) and subjects with elevated BMI (> 25 kg/m(2)) but low visceral and ectopic fat. The former sub-phenotype is associated with adverse metabolic profiles, while the latter is associated with a metabolically normal phenotype, despite a high BMI. Here, examples of these phenotypes are presented and the value of carrying out enhanced phenotypical characterisation of subjects in interventional studies discussed.
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Patel KD, Abeysekera KWM, Marlais M, McPhail MJW, Thomas HC, Fitzpatrick JA, Lim AKP, Taylor-Robinson SD, Thomas EL. Recent advances in imaging hepatic fibrosis and steatosis. Expert Rev Gastroenterol Hepatol 2011; 5:91-104. [PMID: 21309675 DOI: 10.1586/egh.10.85] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Liver disease is an increasing cause of morbidity and mortality worldwide. Currently, the gold standard for diagnosis and assessment of parenchymal disease is histopathological assessment of a percutaneous or transjugular liver biopsy. The risks and limitations of this technique are well recognized and as a result, significant effort has gone into the development of novel noninvasive methods of diagnosis and longitudinal assessment. Imaging techniques have improved significantly over the past decade and new technologies are beginning to enter clinical practice. Ultrasound, computed tomography and MRI are the main modalities currently used, but novel MRI-based techniques will have an increasing role. While there has been extensive research into the imaging of focal liver disease, the evidence base for imaging in diffuse disease has also undergone recent rapid development, particularly in the assessment of fibrosis and steatosis. Both of these abnormalities of the parenchyma can lead to cirrhosis and/or hepatocellular carcinoma and represent an important opportunity for detection of early liver disease. We discuss the recent advances in liver imaging techniques and their role in the diagnosis and monitoring of diffuse liver disease, with a focus on their current and potential clinical relevance and whether they may replace or augment liver biopsy. We also discuss techniques currently under development and their potential clinical applications in the future.
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Affiliation(s)
- Kayur D Patel
- Liver Unit, Division of Diabetes Endocrinology and Metabolism, Department of Medicine, 10th Floor Queen Elizabeth the Queen Mother Wing, St Mary's Hospital Campus, Imperial College London, South Wharf Street, London W2 1NY, UK
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Assessment of relevant hepatic steatosis in obese adolescents by rapid fat-selective GRE imaging with spatial-spectral excitation: a quantitative comparison with spectroscopic findings. Eur Radiol 2010; 21:816-22. [DOI: 10.1007/s00330-010-1975-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2010] [Revised: 08/06/2010] [Accepted: 08/29/2010] [Indexed: 01/01/2023]
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