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Sun K, Dan G, Zhong Z, Zhou XJ. Multi-readout DWI with a reduced FOV for studying the coupling between diffusion and T 2 * relaxation in the prostate. Magn Reson Med 2023; 90:250-258. [PMID: 36932652 DOI: 10.1002/mrm.29636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/16/2023] [Accepted: 02/23/2023] [Indexed: 03/19/2023]
Abstract
PURPOSE To develop a DWI sequence with multiple readout echo-trains in a single shot (multi-readout DWI) over a reduced FOV, and to demonstrate its ability to achieve high data acquisition efficiency in the study of coupling between diffusion and relaxation in the human prostate. METHODS The proposed multi-readout DWI sequence plays out multiple EPI readout echo-trains after a Stejskal-Tanner diffusion preparation module. Each EPI readout echo-train corresponded to a distinct effective TE. To maintain a high spatial resolution with a relatively short echo-train for each readout, a 2D RF pulse was used to limit the FOV. Experiments were performed on the prostate of six healthy subjects to acquire a set of images with three b values (0, 500, and 1000 s/mm2 ) and three TEs (63.0, 78.8, and 94.6 ms), producing three ADC maps at different TEs and three T 2 * $$ {T}_2^{\ast } $$ maps at different b values. RESULTS Multi-readout DWI enabled a threefold acceleration without compromising the spatial resolution when compared with a conventional single-readout sequence. Images with three b values and three TEs were obtained in 3 min 40 s with an adequate SNR (≥ 26.9). The ADC values (1.45 ± 0.13, 1.52 ± 0.14, and 1.58 ± 0.15 μm 2 / ms $$ {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ; P < 0.01) exhibited an increasing trend as TEs increased (63.0 ms, 78.8 ms, and 94.6 ms), whereas T 2 * $$ {T}_2^{\ast } $$ values (74.78 ± 13.21, 63.21 ± 7.84, and 56.61 ± 5.05 ms; P < 0.01) decreases as the b values increased (0, 500, and 1000 s/mm2 ). CONCLUSION The multi-readout DWI sequence over a reduced FOV provides a time-efficient technique to study the coupling between diffusion and relaxation times.
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Affiliation(s)
- Kaibao Sun
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Guangyu Dan
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA.,Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Zheng Zhong
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA.,Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Xiaohong Joe Zhou
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA.,Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois, USA.,Departments of Radiology and Neurosurgery, University of Illinois College of Medicine at Chicago, Chicago, Illinois, USA
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Diffusion in Sephadex Gel Structures: Time Dependency Revealed by Multi-Sequence Acquisition over a Broad Diffusion Time Range. MATHEMATICS 2021; 9. [PMID: 34386373 PMCID: PMC8356480 DOI: 10.3390/math9141688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
It has been increasingly reported that in biological tissues diffusion-weighted MRI signal attenuation deviates from mono-exponential decay, especially at high b-values. A number of diffusion models have been proposed to characterize this non-Gaussian diffusion behavior. One of these models is the continuous-time random-walk (CTRW) model, which introduces two new parameters: a fractional order time derivative α and a fractional order spatial derivative β. These new parameters have been linked to intravoxel diffusion heterogeneities in time and space, respectively, and are believed to depend on diffusion times. Studies on this time dependency are limited, largely because the diffusion time cannot vary over a board range in a conventional spin-echo echo-planar imaging sequence due to the accompanying T2 decays. In this study, we investigated the time-dependency of the CTRW model in Sephadex gel phantoms across a broad diffusion time range by employing oscillating-gradient spin-echo, pulsed-gradient spin-echo, and pulsed-gradient stimulated echo sequences. We also performed Monte Carlo simulations to help understand our experimental results. It was observed that the diffusion process fell into the Gaussian regime at extremely short diffusion times whereas it exhibited a strong time dependency in the CTRW parameters at longer diffusion times.
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Slices of the Anomalous Phase Cube Depict Regions of Sub- and Super-Diffusion in the Fractional Diffusion Equation. MATHEMATICS 2021. [DOI: 10.3390/math9131481] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Fractional-order time and space derivatives are one way to augment the classical diffusion equation so that it accounts for the non-Gaussian processes often observed in heterogeneous materials. Two-dimensional phase diagrams—plots whose axes represent the fractional derivative order—typically display: (i) points corresponding to distinct diffusion propagators (Gaussian, Cauchy), (ii) lines along which specific stochastic models apply (Lévy process, subordinated Brownian motion), and (iii) regions of super- and sub-diffusion where the mean squared displacement grows faster or slower than a linear function of diffusion time (i.e., anomalous diffusion). Three-dimensional phase cubes are a convenient way to classify models of anomalous diffusion (continuous time random walk, fractional motion, fractal derivative). Specifically, each type of fractional derivative when combined with an assumed power law behavior in the diffusion coefficient renders a characteristic picture of the underlying particle motion. The corresponding phase diagrams, like pages in a sketch book, provide a portfolio of representations of anomalous diffusion. The anomalous diffusion phase cube employs lines of super-diffusion (Lévy process), sub-diffusion (subordinated Brownian motion), and quasi-Gaussian behavior to stitch together equivalent regions.
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Karaman MM, Zhang J, Xie KL, Zhu W, Zhou XJ. Quartile histogram assessment of glioma malignancy using high b-value diffusion MRI with a continuous-time random-walk model. NMR IN BIOMEDICINE 2021; 34:e4485. [PMID: 33543512 DOI: 10.1002/nbm.4485] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 01/15/2021] [Indexed: 06/12/2023]
Abstract
The purpose of this study is to investigate the feasibility of using a continuous-time random-walk (CTRW) diffusion model, together with a quartile histogram analysis, for assessing glioma malignancy by probing tissue heterogeneity as well as cellularity. In this prospective study, 91 patients (40 females, 51 males) with histopathologically proven gliomas underwent MRI at 3 T. The cohort included 42 grade II (GrII), 19 grade III (GrIII) and 29 grade IV (GrIV) gliomas. Echo-planar diffusion-weighted imaging was conducted using 17 b-values (0-4000 s/mm2 ). Three CTRW model parameters, including an anomalous diffusion coefficient Dm , and two parameters related to temporal and spatial diffusion heterogeneity α and β, respectively, were obtained. The mean parameter values within the tumor regions of interest (ROIs) were computed by utilizing the first quartile of the histograms as well as the full ROI for comparison. A Bonferroni-Holm-corrected Mann-Whitney U-test was used for the group comparisons. Individual and combinations of the CTRW parameters were evaluated for the characterization of gliomas with a receiver operating characteristic analysis. All first-quartile mean CTRW parameters yielded significant differences (p-values < 0.05) between pair-wise comparisons of GrII (Dm : 1.14 ± 0.37 μm2 /ms; α: 0.904 ± 0.03, β: 0.913 ± 0.06), GrIII (Dm : 0.88 ± 0.21 μm2 /ms; α: 0.888 ± 0.01, β: 0.857 ± 0.06) and GrIV gliomas (Dm : 0.73 ± 0.22 μm2 /ms; α: 0.878 ± 0.01; β: 0.791 ± 0.07). The highest sensitivity, specificity, accuracy and area-under-the-curve of using the combinations of the first-quartile parameters were 84.2%, 78.5%, 75.4% and 0.76 for GrII and GrIII classification; 86.2%, 89.4%, 75% and 0.76 for GrIII and GrIV classification; and 86.2%, 85.7%, 84.5% and 0.90 for GrII and GrIV classification, respectively. Quartile-based analysis produced higher accuracy and area-under-the-curve than the full ROI-based analysis in all classifications. The CTRW diffusion model, together with a quartile-based histogram analysis, offers a new way for probing tumor structural heterogeneity at a subvoxel level, and has potential for in vivo assessment of glioma malignancy to complement histopathology.
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Affiliation(s)
- M Muge Karaman
- Center for MR Research, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Jiaxuan Zhang
- Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Karen L Xie
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaohong Joe Zhou
- Center for MR Research, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Neurosurgery, University of Illinois at Chicago, Chicago, Illinois, USA
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Shan Y, Xu BY, Li S, Fan Y, Liu YB, Zhang M, Ma QF, Gao JH, Lu J. Assessment of MRI-based anomalous diffusion changes in brain ischemic stroke with a fractional motion model. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2020; 317:106795. [PMID: 32712547 DOI: 10.1016/j.jmr.2020.106795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/12/2020] [Accepted: 07/15/2020] [Indexed: 06/11/2023]
Abstract
The actual diffusion process in human brain has been shown to be anomalous comparing to that predicted with traditional diffusion MRI (dMRI) theory. Recently, dMRI based on fractional motion (FM) model has demonstrated the potential to accurately describe anomalous diffusion in vivo. In this work, we explored the potential value of FM model-based dMRI in quantificational identification of ischemic stroke and compared that with the traditional apparent diffusion coefficient (ADC). We included 23 acute stroke patients, 8 of whom finished a follow-up scan, and 22 matched healthy controls. The dMRI images were acquired by using a Stejskal-Tanner single-shot spin-echo echo-planar-imaging sequence (diffusion gradients were applied in three orthogonal directions with 25 non-zero b values ranging from 248 to 4474 s/mm2) at 3.0 T MRI. We calculated the coefficient of variation (CV) for FM-related parameters in stroke lesions, and compared the mean values for FM-related parameters and ADC by using two-sample t-tests. Correlation analysis was achieved using Pearson correlation coefficient test. In acute stroke lesions, CV for FM-related parameters showed significant increase compared with normal tissues (P < 0.01), while those of ADC didn't appear statistical difference. Mean values for FM-related parameters showed significant decrease in acute lesion (P < 0.01) and their changing pattern during follow-up was positively correlated with ADC (P < 0.005). Our results initially verified the utility of the FM-model in detecting ischemic stroke compared with traditional dMRI.
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Affiliation(s)
- Yi Shan
- Department of Radiology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Bo-Yan Xu
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, No. 5 Yiheyuan Road, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, No. 5 Yiheyuan Road, Beijing 100871, China
| | - Shuang Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yang Fan
- Beijing Intelligent Brain Cloud, Inc., Integrated Science Building, No. 5 Yiheyuan Road, Beijing 100871, China
| | - Yi-Bing Liu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Miao Zhang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Qing-Feng Ma
- Department of Neurology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing 100053, China
| | - Jia-Hong Gao
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, No. 5 Yiheyuan Road, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, No. 5 Yiheyuan Road, Beijing 100871, China; McGovern Institute for Brain Research, Peking University, No. 5 Yiheyuan Road, Beijing 100871, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China; Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing 100053, China.
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Zhong Z, Merkitch D, Karaman MM, Zhang J, Sui Y, Goldman JG, Zhou XJ. High-Spatial-Resolution Diffusion MRI in Parkinson Disease: Lateral Asymmetry of the Substantia Nigra. Radiology 2019; 291:149-157. [PMID: 30777809 DOI: 10.1148/radiol.2019181042] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Motor symptoms in Parkinson disease (PD) have exhibited lateral asymmetry, suggesting asymmetric neuronal loss in the substantia nigra (SN). Diffusion MRI may be able to help confirm tissue microstructural alterations in the substantia nigra to probe for the presence of asymmetry. Purpose To investigate lateral asymmetry in the SN of patients with PD by using diffusion MRI with both Gaussian and non-Gaussian models. Materials and Methods In this cross-sectional study conducted from March 2015 to March 2017, 27 participants with PD and 27 age-matched healthy control (HC) participants, all right handed, underwent MRI at 3.0 T. High-spatial-resolution diffusion images were acquired with a reduced field of view by using seven b values up to 3000 sec/mm2. A continuous-time random-walk (CTRW) non-Gaussian diffusion model was used to produce anomalous diffusion coefficient (Dm) and temporal (α) and spatial (β) diffusion heterogeneity indexes followed by a Gaussian diffusion model to yield an apparent diffusion coefficient (ADC). Individual or linear combinations of diffusion parameters in the SN were unilaterally and bilaterally compared between the PD and HC groups. Results In the bilateral comparison between the PD and HC groups, differences were observed in β (0.67 ± 0.06 [standard deviation] vs 0.64 ± 0.04, respectively; P = .016), ADC (0.48 μm2/msec ± 0.08 vs 0.53 μm2/msec ± 0.06, respectively; P = .03), and the combination of CTRW parameters (P = .02). In the unilateral comparison, differences were observed in all diffusion parameters on the left SN (P < .03), but not on the right (P > .20). In a receiver operating characteristic (ROC) analysis to delineate left SN abnormality in PD, the combination of Dm, α, and β produced the best sensitivity (sensitivity, 0.78); the combination of Dm and β produced the best specificity (specificity, 0.85); and the combination of α and β produced the largest area under the ROC curve (area under the ROC curve, 0.73). Conclusion These results suggest that quantitative diffusion MRI is sensitive to brain tissue changes in participants with Parkinson disease and provide evidence of substantia nigra lateral asymmetry in this disease. © RSNA, 2019 Online supplemental material is available for this article.
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Affiliation(s)
- Zheng Zhong
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Douglas Merkitch
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - M Muge Karaman
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Jiaxuan Zhang
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Yi Sui
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Jennifer G Goldman
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Xiaohong Joe Zhou
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
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Guerreri M, Palombo M, Caporale A, Fasano F, Macaluso E, Bozzali M, Capuani S. Age-related microstructural and physiological changes in normal brain measured by MRI γ-metrics derived from anomalous diffusion signal representation. Neuroimage 2018; 188:654-667. [PMID: 30583064 DOI: 10.1016/j.neuroimage.2018.12.044] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 12/11/2018] [Accepted: 12/20/2018] [Indexed: 12/29/2022] Open
Abstract
Nowadays, increasing longevity associated with declining cerebral nervous system functions, suggests the need for continued development of new imaging contrast mechanisms to support the differential diagnosis of age-related decline. In our previous papers, we developed a new imaging contrast metrics derived from anomalous diffusion signal representation and obtained from diffusion-weighted (DW) data collected by varying diffusion gradient strengths. Recently, we highlighted that the new metrics, named γ-metrics, depended on the local inhomogeneity due to differences in magnetic susceptibility between tissues and diffusion compartments in young healthy subjects, thus providing information about myelin orientation and iron content within cerebral regions. The major structural modifications occurring in brain aging are myelinated fibers damage in nerve fibers and iron accumulation in gray matter nuclei. Therefore, we investigated the potential of γ-metrics in relation to other conventional diffusion metrics such as DTI, DKI and NODDI in detecting age-related structural changes in white matter (WM) and subcortical gray matter (scGM). DW-images were acquired in 32 healthy subjects, adults and elderly (age range 20-77 years) using 3.0T and 12 b-values up to 5000 s/mm2. Association between diffusion metrics and subjects' age was assessed using linear regression. A decline in mean γ (Mγ) in the scGM and a complementary increase in radial γ (γ⊥) in frontal WM, genu of corpus callosum and anterior corona radiata with advancing age were found. We suggested that the increase in γ⊥ might reflect declined myelin density, and Mγ decrease might mirror iron accumulation. An increase in D// and a decrease in the orientation dispersion index (ODI) were associated with axonal loss in the pyramidal tracts, while their inverted trends within the thalamus were thought to be linked to reduced architectural complexity of nerve fibers. γ-metrics together with conventional diffusion-metrics can more comprehensively characterize the complex mechanisms underlining age-related changes than conventional diffusion techniques alone.
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Affiliation(s)
- Michele Guerreri
- SAIMLAL Department, Sapienza, Piazzale Aldo Moro, 5, 00185, Roma, RM, Italy; Institute for Complex Systems, CNR, Rome, Italy.
| | - Marco Palombo
- Institute for Complex Systems, CNR, Rome, Italy; Department of Computer Science & Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Alessandra Caporale
- Institute for Complex Systems, CNR, Rome, Italy; Laboratory for Structural, Physiologic and Functional Imaging, Perelman School of Medicine University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Marco Bozzali
- Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy
| | - Silvia Capuani
- Institute for Complex Systems, CNR, Rome, Italy; Neuroimaging Laboratory, Santa Lucia Foundation, Rome, Italy
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Tang L, Zhou XJ. Diffusion MRI of cancer: From low to high b-values. J Magn Reson Imaging 2018; 49:23-40. [PMID: 30311988 DOI: 10.1002/jmri.26293] [Citation(s) in RCA: 118] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 07/20/2018] [Accepted: 07/23/2018] [Indexed: 12/14/2022] Open
Abstract
Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models to extract biologically valuable information from diffusion-weighted MR signals, and significant advances in MR hardware that has enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections. First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in relation to three tissue properties-cellularity, vascularity, and microstructures. An emphasis is placed on characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate diffusion MR clinical applications in each of the following three categories: 1) cancer detection and diagnosis; 2) cancer grading, staging, and classification; and 3) cancer treatment response prediction and evaluation. Third, we discuss several practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via well-organized multicenter clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care on a large scale. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:23-40.
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Affiliation(s)
- Lei Tang
- Department of Radiology, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research, Beijing, China
| | - Xiaohong Joe Zhou
- Center for MR Research and Departments of Radiology, Neurosurgery, and Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA
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