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Stabinska J, Wittsack HJ, Lerman LO, Ljimani A, Sigmund EE. Probing Renal Microstructure and Function with Advanced Diffusion MRI: Concepts, Applications, Challenges, and Future Directions. J Magn Reson Imaging 2024; 60:1259-1277. [PMID: 37991093 PMCID: PMC11117411 DOI: 10.1002/jmri.29127] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/23/2023] Open
Abstract
Diffusion measurements in the kidney are affected not only by renal microstructure but also by physiological processes (i.e., glomerular filtration, water reabsorption, and urine formation). Because of the superposition of passive tissue diffusion, blood perfusion, and tubular pre-urine flow, the limitations of the monoexponential apparent diffusion coefficient (ADC) model in assessing pathophysiological changes in renal tissue are becoming apparent and motivate the development of more advanced diffusion-weighted imaging (DWI) variants. These approaches take advantage of the fact that the length scale probed in DWI measurements can be adjusted by experimental parameters, including diffusion-weighting, diffusion gradient directions and diffusion time. This forms the basis by which advanced DWI models can be used to capture not only passive diffusion effects, but also microcirculation, compartmentalization, tissue anisotropy. In this review, we provide a comprehensive overview of the recent advancements in the field of renal DWI. Following a short introduction on renal structure and physiology, we present the key methodological approaches for the acquisition and analysis of renal DWI data, including intravoxel incoherent motion (IVIM), diffusion tensor imaging (DTI), non-Gaussian diffusion, and hybrid IVIM-DTI. We then briefly summarize the applications of these methods in chronic kidney disease and renal allograft dysfunction. Finally, we discuss the challenges and potential avenues for further development of renal DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Julia Stabinska
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hans-Jörg Wittsack
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Dusseldorf, Germany
| | - Lilach O. Lerman
- Division of Nephrology and Hypertension and Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Alexandra Ljimani
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Dusseldorf, Germany
| | - Eric E. Sigmund
- Bernard and Irene Schwartz Center for Biomedical Imaging Center for Advanced Imaging Innovation and Research (CAI2R), New York University Langone Health, New York City, New York, USA
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Englund EK, Reiter DA, Shahidi B, Sigmund EE. Intravoxel Incoherent Motion Magnetic Resonance Imaging in Skeletal Muscle: Review and Future Directions. J Magn Reson Imaging 2022; 55:988-1012. [PMID: 34390617 PMCID: PMC8841570 DOI: 10.1002/jmri.27875] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/23/2021] [Accepted: 07/26/2021] [Indexed: 12/29/2022] Open
Abstract
Throughout the body, muscle structure and function can be interrogated using a variety of noninvasive magnetic resonance imaging (MRI) methods. Recently, intravoxel incoherent motion (IVIM) MRI has gained momentum as a method to evaluate components of blood flow and tissue diffusion simultaneously. Much of the prior research has focused on highly vascularized organs, including the brain, kidney, and liver. Unique aspects of skeletal muscle, including the relatively low perfusion at rest and large dynamic range of perfusion between resting and maximal hyperemic states, may influence the acquisition, postprocessing, and interpretation of IVIM data. Here, we introduce several of those unique features of skeletal muscle; review existing studies of IVIM in skeletal muscle at rest, in response to exercise, and in disease states; and consider possible confounds that should be addressed for muscle-specific evaluations. Most studies used segmented nonlinear least squares fitting with a b-value threshold of 200 sec/mm2 to obtain IVIM parameters of perfusion fraction (f), pseudo-diffusion coefficient (D*), and diffusion coefficient (D). In healthy individuals, across all muscles, the average ± standard deviation of D was 1.46 ± 0.30 × 10-3 mm2 /sec, D* was 29.7 ± 38.1 × 10-3 mm2 /sec, and f was 11.1 ± 6.7%. Comparisons of reported IVIM parameters in muscles of the back, thigh, and leg of healthy individuals showed no significant difference between anatomic locations. Throughout the body, exercise elicited a positive change of all IVIM parameters. Future directions including advanced postprocessing models and potential sequence modifications are discussed. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Erin K. Englund
- Department of Radiology, University of Colorado Anschutz Medical Campus
| | | | | | - Eric E. Sigmund
- Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health
- Center for Advanced Imaging and Innovation (CAIR), Bernard and Irene Schwarz Center for Biomedical Imaging (CBI), NYU Langone Health
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3
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Zhou X, Wang X, Liu E, Zhang L, Zhang H, Zhang X, Zhu Y, Kuai Z. An Unsupervised Deep Learning Approach for
Dynamic‐Exponential
Intravoxel Incoherent Motion
MRI
Modeling and Parameter Estimation in the Liver. J Magn Reson Imaging 2022; 56:848-859. [PMID: 35064945 DOI: 10.1002/jmri.28074] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 01/09/2022] [Accepted: 01/10/2022] [Indexed: 12/18/2022] Open
Affiliation(s)
- Xin‐Xiang Zhou
- Imaging Center Harbin Medical University Cancer Hospital Harbin China
| | - Xin‐Yu Wang
- Imaging Center Harbin Medical University Cancer Hospital Harbin China
| | - En‐Hui Liu
- Imaging Center Harbin Medical University Cancer Hospital Harbin China
| | - Lan Zhang
- Imaging Center Harbin Medical University Cancer Hospital Harbin China
| | - Hong‐Xia Zhang
- Imaging Center Harbin Medical University Cancer Hospital Harbin China
| | - Xiu‐Shi Zhang
- Imaging Center Harbin Medical University Cancer Hospital Harbin China
| | - Yue‐Min Zhu
- CREATIS CNRS UMR 5220‐INSERM U1206‐University Lyon 1‐INSA Lyon‐University Jean Monnet Saint‐Etienne Lyon France
| | - Zi‐Xiang Kuai
- Imaging Center Harbin Medical University Cancer Hospital Harbin China
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Zhang XS, Liu EH, Wang XY, Zhou XX, Zhang HX, Zhu YM, Sang XQ, Kuai ZX. Short-Term Repeatability of in Vivo Cardiac Intravoxel Incoherent Motion Tensor Imaging in Healthy Human Volunteers. J Magn Reson Imaging 2021; 55:854-865. [PMID: 34296813 DOI: 10.1002/jmri.27847] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 07/10/2021] [Accepted: 07/12/2021] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Intravoxel incoherent motion (IVIM) tensor imaging is a promising technique for diagnosis and monitoring of cardiovascular diseases. Knowledge about measurement repeatability, however, remains limited. PURPOSE To evaluate short-term repeatability of IVIM tensor imaging in normal in vivo human hearts. STUDY TYPE Prospective. POPULATION Ten healthy subjects without history of heart diseases. FIELD STRENGTH/SEQUENCE Balanced steady-state free-precession cine sequence and single-shot spin-echo echo planar IVIM tensor imaging sequence (9 b-values, 0-400 seconds/mm2 and six diffusion-encoding directions) at 3.0 T. ASSESSMENT Subjects were scanned twice with an interval of 15 minutes, leaving the scanner between studies. The signal-to-noise ratio (SNR) was evaluated in anterior, lateral, septal, and inferior segments of the left ventricle wall. Fractional anisotropy (FA), mean diffusivity (MD), mean fraction (MF), and helix angle (HA) in the four segments were independently measured by five radiologists. STATISTICAL TESTS IVIM tensor indexes were compared between observers using a one-way analysis of variance or between scans using a paired t-test (normal data) or a Wilcoxon rank-sum test (non-normal data). Interobserver agreement and test-retest repeatability were assessed using the intraclass correlation coefficient (ICC), within-subject coefficient of variation (WCV), and Bland-Altman limits of agreements. RESULTS SNR of inferior segment was significantly lower than the other three segments, and inferior segment was therefore excluded from repeatability analysis. Interobserver repeatability was excellent for all IVIM tensor indexes (ICC: 0.886-0.972; WCV: 0.62%-4.22%). Test-retest repeatability was excellent for MD of the self-diffusion tensor (D) and MF of the perfusion fraction tensor (fp ) (ICC: 0.803-0.888; WCV: 1.42%-9.51%) and moderate for FA and MD of the pseudo-diffusion tensor (D* ) (ICC: 0.487-0.532; WCV: 6.98%-10.89%). FA of D and fp and HA of D presented good test-retest repeatability (ICC: 0.732-0.788; WCV: 3.28%-8.71%). DATA CONCLUSION The D and fp indexes exhibited satisfactory repeatability, but further efforts were needed to improve repeatability of D* indexes. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Xiu-Shi Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - En-Hui Liu
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xin-Yu Wang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xin-Xiang Zhou
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - Hong-Xia Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yue-Min Zhu
- CREATIS, CNRS UMR 5220-INSERM U1206-University Lyon 1-INSA Lyon-University Jean Monnet Saint-Etienne, Lyon, France
| | - Xi-Qiao Sang
- Division of Respiratory Disease, The Fourth Hospital of Harbin Medical University, Harbin, China
| | - Zi-Xiang Kuai
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
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Chevallier O, Wáng YXJ, Guillen K, Pellegrinelli J, Cercueil JP, Loffroy R. Evidence of Tri-Exponential Decay for Liver Intravoxel Incoherent Motion MRI: A Review of Published Results and Limitations. Diagnostics (Basel) 2021; 11:diagnostics11020379. [PMID: 33672277 PMCID: PMC7926368 DOI: 10.3390/diagnostics11020379] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 02/14/2021] [Accepted: 02/20/2021] [Indexed: 12/11/2022] Open
Abstract
Diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) have been explored to assess liver tumors and diffused liver diseases. IVIM reflects the microscopic translational motions that occur in voxels in magnetic resonance (MR) DWI. In biologic tissues, molecular diffusion of water and microcirculation of blood in the capillary network can be assessed using IVIM DWI. The most commonly applied model to describe the DWI signal is a bi-exponential model, with a slow compartment of diffusion linked to pure molecular diffusion (represented by the coefficient Dslow), and a fast compartment of diffusion, related to microperfusion (represented by the coefficient Dfast). However, high variance in Dfast estimates has been consistently shown in literature for liver IVIM, restricting its application in clinical practice. This variation could be explained by the presence of another very fast compartment of diffusion in the liver. Therefore, a tri-exponential model would be more suitable to describe the DWI signal. This article reviews the published evidence of the existence of this additional very fast diffusion compartment and discusses the performance and limitations of the tri-exponential model for liver IVIM in current clinical settings.
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Affiliation(s)
- Olivier Chevallier
- Image-Guided Therapy Center, Department of Vascular and Interventional Radiology, François-Mitterrand University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France; (O.C.); (K.G.); (J.P.); (J.-P.C.)
| | - Yì Xiáng J. Wáng
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, New Territories, Hong Kong, China;
| | - Kévin Guillen
- Image-Guided Therapy Center, Department of Vascular and Interventional Radiology, François-Mitterrand University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France; (O.C.); (K.G.); (J.P.); (J.-P.C.)
| | - Julie Pellegrinelli
- Image-Guided Therapy Center, Department of Vascular and Interventional Radiology, François-Mitterrand University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France; (O.C.); (K.G.); (J.P.); (J.-P.C.)
| | - Jean-Pierre Cercueil
- Image-Guided Therapy Center, Department of Vascular and Interventional Radiology, François-Mitterrand University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France; (O.C.); (K.G.); (J.P.); (J.-P.C.)
| | - Romaric Loffroy
- Image-Guided Therapy Center, Department of Vascular and Interventional Radiology, François-Mitterrand University Hospital, 14 Rue Paul Gaffarel, BP 77908, 21079 Dijon, France; (O.C.); (K.G.); (J.P.); (J.-P.C.)
- Correspondence: ; Tel.: +33-380-293-677
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Zhang XS, Sang XQ, Kuai ZX, Zhang HX, Lou J, Lu Q, Zhu YM. Investigation of intravoxel incoherent motion tensor imaging for the characterization of the in vivo human heart. Magn Reson Med 2020; 85:1414-1426. [PMID: 32989786 DOI: 10.1002/mrm.28523] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 08/24/2020] [Accepted: 08/26/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To investigate intravoxel incoherent motion (IVIM) tensor imaging of the in vivo human heart and elucidate whether the estimation of IVIM tensors is affected by the complexity of pseudo-diffusion components in myocardium. METHODS The cardiac IVIM data of 10 healthy subjects were acquired using a diffusion weighted spin-echo echo-planar imaging sequence along 6 gradient directions with 10 b values (0~400 s/mm2 ). The IVIM data of left ventricle myocardium were fitted to the IVIM tensor model. The complexity of myocardial pseudo-diffusion components was reduced through exclusion of low b values (0 and 5 s/mm2 ) from the IVIM curve-fitting analysis. The fractional anisotropy, mean fraction/mean diffusivity, and Westin measurements of pseudo-diffusion tensors (fp and D*) and self-diffusion tensor (D), as well as the angle between the main eigenvector of fp (or D*) and that of D, were computed and compared before and after excluding low b values. RESULTS The fractional anisotropy values of fp and D* without low b value participation were significantly higher (P < .001) than those with low b value participation, but an opposite trend was found for the mean fraction/diffusivity values. Besides, after removing low b values, the angle between the main eigenvector of fp (or D*) and that of D became small, and both fp and D* tensors presented significant decrease of spherical components and significant increase of linear components. CONCLUSION The presence of multiple pseudo-diffusion components in myocardium indeed influences the estimation of IVIM tensors. The IVIM tensor model needs to be further improved to account for the complexity of myocardial microcirculatory network and blood flow.
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Affiliation(s)
- Xiu-Shi Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China
| | - Xi-Qiao Sang
- Division of Respiratory Disease, The Fourth Hospital of Harbin Medical University, Harbin, People's Republic of China
| | - Zi-Xiang Kuai
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China
| | - Hong-Xia Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China
| | - Jie Lou
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China
| | - Qing Lu
- Department of Radiology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yue-Min Zhu
- Univ Lyon, INSA Lyon, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, Lyon, France
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Ye C, Xu D, Qin Y, Wang L, Wang R, Li W, Kuai Z, Zhu Y. Accurate intravoxel incoherent motion parameter estimation using Bayesian fitting and reduced number of low b-values. Med Phys 2020; 47:4372-4385. [PMID: 32403175 DOI: 10.1002/mp.14233] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 03/02/2020] [Accepted: 04/15/2020] [Indexed: 12/28/2022] Open
Abstract
PURPOSE Intravoxel incoherent motion (IVIM) magnetic resonance imaging is a potential noninvasive technique for the diagnosis of brain tumors. However, perfusion-related parameter mapping is a persistent problem. The purpose of this paper is to investigate the IVIM parameter mapping of brain tumors using Bayesian fitting and low b-values. METHODS Bayesian shrinkage prior (BSP) fitting method and different low b-value distributions were used to estimate IVIM parameters (diffusion D, pseudo-diffusion D*, and perfusion fraction F). The results were compared to those obtained by least squares (LSQ) on both simulated and in vivo brain data. Relative error (RE) and reproducibility were used to evaluate the results. The differences of IVIM parameters between brain tumor and normal regions were compared and used to assess the performance of Bayesian fitting in the IVIM application of brain tumor. RESULTS In tumor regions, the value of D* tended to be decreased when the number of low b-values was insufficient, especially with LSQ. BSP required less low b-values than LSQ for the correct estimation of perfusion parameters of brain tumors. The IVIM parameter maps of brain tumors yielded by BSP had smaller variability, lower RE, and higher reproducibility with respect to those obtained by LSQ. Obvious differences were observed between tumor and normal regions in parameters D (P < 0.05) and F (P < 0.001), especially F. BSP generated fewer outliers than LSQ, and distinguished better tumors from normal regions in parameter F. CONCLUSIONS Intravoxel incoherent motion parameters clearly allow brain tumors to be differentiated from normal regions. Bayesian fitting yields robust IVIM parameter mapping with fewer outliers and requires less low b-values than LSQ for the parameter estimation.
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Affiliation(s)
- Chen Ye
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Daoyun Xu
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Yongbin Qin
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Lihui Wang
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Rongpin Wang
- Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China
| | - Wuchao Li
- Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China
| | - Zixiang Kuai
- Harbin Medical University Cancer Hospital, Harbin, China
| | - Yuemin Zhu
- Univ Lyon, INSA Lyon, CNRS, INSERM, CREATIS UMR 5220, U1206, Lyon, F-69621, France
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Li C, Ye J, Prince M, Peng Y, Dou W, Shang S, Wu J, Luo X. Comparing mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted MR imaging for stratifying non-alcoholic fatty liver disease in a rabbit model. Eur Radiol 2020; 30:6022-6032. [PMID: 32591883 DOI: 10.1007/s00330-020-07005-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 04/17/2020] [Accepted: 06/04/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVES To compare diffusion parameters obtained from mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) in stratifying non-alcoholic fatty liver disease (NAFLD). METHODS Thirty-two New Zealand rabbits were fed a high-fat/cholesterol or standard diet to obtain different stages of NAFLD before 12 b-values (0-800 s/mm2) DWI. The apparent diffusion coefficient (ADC) from the mono-exponential model; pure water diffusion (D), pseudo-diffusion (D*), and perfusion fraction (f) from bi-exponential DWI; and distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) from stretched-exponential DWI were calculated for hepatic parenchyma. The goodness of fit of the three models was compared. NAFLD severity was pathologically graded as normal, simple steatosis, borderline, and non-alcoholic steatohepatitis (NASH). Spearman rank correlation analysis and receiver operating characteristic curves were used to assess NAFLD severity. RESULTS Upon comparison, the goodness of fit chi-square from stretched-exponential fitting (0.077 ± 0.012) was significantly lower than that for the bi-exponential (0.110 ± 0.090) and mono-exponential (0.181 ± 0.131) models (p < 0.05). Seven normal, 8 simple steatosis, 6 borderline, and 11 NASH livers were pathologically confirmed from 32 rabbits. Both α and D increased with increasing NAFLD severity (r = 0.811 and 0.373, respectively; p < 0.05). ADC, f, and DDC decreased as NAFLD severity increased (r = - 0.529, - 0.717, and - 0.541, respectively; p < 0.05). Both α (area under the curve [AUC] = 0.952) and f (AUC = 0.931) had significantly greater AUCs than ADC (AUC = 0.727) in the differentiation of NASH from borderline or less severe groups (p < 0.05). CONCLUSIONS Stretched-exponential DWI with higher fitting efficiency performed, as well as bi-exponential DWI, better than mono-exponential DWI in the stratification of NAFLD severity. KEY POINTS • Stretched-exponential diffusion model fitting was more reliable than the bi-exponential and mono-exponential diffusion models (p = 0.039 and p < 0.001, respectively). • As NAFLD severity increased, the diffusion heterogeneity index (α) increased, while the perfusion fraction (f) decreased (r = 0.811, - 0.717, p < 0.05). • Both α and f showed superior NASH diagnostic performance (AUC = 0.952, 0.931) compared with ADC (AUC = 0.727, p < 0.05).
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Affiliation(s)
- Chang Li
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou, 225001, People's Republic of China.,Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yan Jiang West Road, Guangzhou, 510120, People's Republic of China
| | - Jing Ye
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou, 225001, People's Republic of China
| | - Martin Prince
- Department of Radiology, Weill Medical College of Cornell University, 407 E 61st Street, New York, NY, 10065, USA
| | - Yun Peng
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou, 225001, People's Republic of China
| | - Weiqiang Dou
- GE Healthcare, MR Research China, Bejing, 100176, China
| | - Songan Shang
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou, 225001, People's Republic of China
| | - Jingtao Wu
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou, 225001, People's Republic of China
| | - Xianfu Luo
- Department of Radiology, Northern Jiangsu People's Hospital, Clinical Medical School of Yangzhou University, No. 98 Nantong West Road, Yangzhou, 225001, People's Republic of China.
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Ye C, Xu D, Qin Y, Wang L, Wang R, Li W, Kuai Z, Zhu Y. Estimation of intravoxel incoherent motion parameters using low b-values. PLoS One 2019; 14:e0211911. [PMID: 30726298 PMCID: PMC6364995 DOI: 10.1371/journal.pone.0211911] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Accepted: 01/22/2019] [Indexed: 02/06/2023] Open
Abstract
Intravoxel incoherent motion (IVIM) imaging is a magnetic resonance imaging (MRI) technique widely used in clinical applications for various organs. However, IVIM imaging at low b-values is a persistent problem. This paper aims to investigate in a systematic and detailed manner how the number of low b-values influences the estimation of IVIM parameters. To this end, diffusion-weighted (DW) data with different low b-values were simulated to get insight into the distributions of subsequent IVIM parameters. Then, in vivo DW data with different numbers of low b-values and different number of excitations (NEX) were acquired. Finally, least-squares (LSQ) and Bayesian shrinkage prior (BSP) fitting methods were implemented to estimate IVIM parameters. The influence of the number of low b-values on IVIM parameters was analyzed in terms of relative error (RE) and structural similarity (SSIM). The results showed that the influence of the number of low b-values on IVIM parameters is variable. LSQ is more dependent on the number of low b-values than BSP, but the latter is more sensitive to noise.
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Affiliation(s)
- Chen Ye
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Daoyun Xu
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
- * E-mail:
| | - Yongbin Qin
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Lihui Wang
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Rongpin Wang
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Wuchao Li
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang, China
| | - Zixiang Kuai
- Harbin Medical University Cancer Hospital, Harbin, China
| | - Yuemin Zhu
- Univ Lyon, INSA Lyon, CNRS, INSERM, CREATIS UMR 5220, U1206, Lyon, France
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10
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Zhang HX, Zhang XS, Kuai ZX, Zhou Y, Sun YF, Ba ZC, He KB, Sang XQ, Yao YF, Chu CY, Zhu YM. Determination of Hepatocellular Carcinoma and Characterization of Hepatic Focal Lesions with Adaptive Multi-Exponential Intravoxel Incoherent Motion Model. Transl Oncol 2018; 11:1370-1378. [PMID: 30216762 PMCID: PMC6139005 DOI: 10.1016/j.tranon.2018.08.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2018] [Revised: 08/27/2018] [Accepted: 08/27/2018] [Indexed: 12/19/2022] Open
Abstract
PURPOSE: To distinguish hepatocellular carcinoma (HCC) from other types of hepatic lesions with the adaptive multi-exponential IVIM model. METHODS: 94 hepatic focal lesions, including 38 HCC, 16 metastasis, 12 focal nodular hyperplasia, 13 cholangiocarcinoma, and 15 hemangioma, were examined in this study. Diffusion-weighted images were acquired with 13 b values (b = 0, 3, …, 500 s/mm2) to measure the adaptive multi-exponential IVIM parameters, namely, pure diffusion coefficient (D), diffusion fraction (fd), pseudo-diffusion coefficient (Di*) and perfusion-related diffusion fraction (fi) of the ith perfusion component. Comparison of the parameters of and their diagnostic performance was determined using Mann-Whitney U test, independent-sample t test, one-way analysis of variance, Z test and receiver-operating characteristic analysis. RESULTS: D, D1* and D2* presented significantly difference between HCCs and other hepatic lesions, whereas fd, f1 and f2 did not show statistical differences. In the differential diagnosis of HCCs from other hepatic lesions, D2* (AUC, 0.927) provided best diagnostic performance among all parameters. Additionally, the number of exponential terms in the model was also an important indicator for distinguishing HCCs from other hepatic lesions. In the benign and malignant analysis, D gave the greatest AUC values, 0.895 or 0.853, for differentiation between malignant and benign lesions with three or two exponential terms. Most parameters were not significantly different between hypovascular and hypervascular lesions. For multiple comparisons, significant differences of D, D1* or D2* were found between certain lesion types. CONCLUSION: The adaptive multi-exponential IVIM model was useful and reliable to distinguish HCC from other hepatic lesions.
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Affiliation(s)
- Hong-Xia Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China
| | - Xiu-Shi Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China
| | - Zi-Xiang Kuai
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China.
| | - Yang Zhou
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China
| | - Yun-Feng Sun
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China
| | - Zhi-Chang Ba
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China
| | - Kuang-Bang He
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China
| | - Xi-Qiao Sang
- Division of Respiratory Disease, The Fourth Hospital of Harbin Medical University, Harbin, 150001, China
| | - Yuan-Fei Yao
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China
| | - Chun-Yu Chu
- College of engineering, Bohai University, Jinzhou, 121013, China
| | - Yue-Min Zhu
- CREATIS, CNRS UMR 5220-INSERM U1206-University Lyon 1-INSA Lyon-University Jean Monnet Saint-Etienne, Lyon, 69621, France
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11
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Federau C. Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence. NMR IN BIOMEDICINE 2017; 30. [PMID: 28885745 DOI: 10.1002/nbm.3780] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Revised: 06/19/2017] [Accepted: 07/07/2017] [Indexed: 05/07/2023]
Abstract
The idea that in vivo intravoxel incoherent motion magnetic resonance signal is influenced by blood motion in the microvasculature is exciting, because it suggests that local and quantitative perfusion information can be obtained in a simple and elegant way from a few diffusion-weighted images, without contrast injection. When the method was proposed in the late 1980s some doubts appeared as to its feasibility, and, probably because the signal to noise and image quality at the time was not sufficient, no obvious experimental evidence could be produced to alleviate them. Helped by the tremendous improvements seen in the last three decades in MR hardware, pulse design, and post-processing capabilities, an increasing number of encouraging reports on the value of intravoxel incoherent motion perfusion imaging have emerged. The aim of this article is to review the current published evidence on the feasibility of in vivo perfusion imaging with intravoxel incoherent motion MRI.
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Affiliation(s)
- Christian Federau
- Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, Petersgraben, Basle, Switzerland
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12
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Kuai ZX, Liu WY, Zhu YM. Effect of multiple perfusion components on pseudo-diffusion coefficient in intravoxel incoherent motion imaging. ACTA ACUST UNITED AC 2017; 62:8197-8209. [DOI: 10.1088/1361-6560/aa8d0c] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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13
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Ye Q, Chen Z, Zhao Y, Zhang Z, Miao H, Xiao Q, Wang M, Li J. Initial experience of generalized intravoxel incoherent motion imaging and diffusion tensor imaging (GIVIM-DTI) in healthy subjects. J Magn Reson Imaging 2016; 44:732-8. [PMID: 27079733 DOI: 10.1002/jmri.25262] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2016] [Accepted: 03/18/2016] [Indexed: 11/06/2022] Open
Affiliation(s)
- Qiong Ye
- Department of Radiology; The First Affiliated Hospital of Wenzhou Medical University; ZheJiang P.R. China
| | - Zhongwei Chen
- Department of Radiology; The First Affiliated Hospital of Wenzhou Medical University; ZheJiang P.R. China
| | - Youfan Zhao
- Department of Radiology; The First Affiliated Hospital of Wenzhou Medical University; ZheJiang P.R. China
| | - Zhenhua Zhang
- Department of Radiology; The First Affiliated Hospital of Wenzhou Medical University; ZheJiang P.R. China
| | - Haiwei Miao
- Department of Radiology; The First Affiliated Hospital of Wenzhou Medical University; ZheJiang P.R. China
| | - Qinqin Xiao
- Department of Radiology; The First Affiliated Hospital of Wenzhou Medical University; ZheJiang P.R. China
| | - Meihao Wang
- Department of Radiology; The First Affiliated Hospital of Wenzhou Medical University; ZheJiang P.R. China
| | - Jiance Li
- Department of Radiology; The First Affiliated Hospital of Wenzhou Medical University; ZheJiang P.R. China
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