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Liu Y, Yin Z, Li X, Zhang Y, Yuan Y, Wei L, Wang S. The diagnostic accuracy of intravoxel incoherent motion and diffusion kurtosis imaging in the differentiation of malignant and benign soft-tissue masses: which is better? Acta Radiol 2022; 63:785-793. [PMID: 34000824 DOI: 10.1177/02841851211017511] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND It is difficult for conventional magnetic resonance imaging (MRI) to distinguish benign soft-tissue masses (STMs) from malignant masses. PURPOSE To quantitatively compare the diagnostic value of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in STMs. MATERIAL AND METHODS The data from 58 patients with STMs were retrospectively analyzed. The GE Discovery 3.0-T MRI scanner was used to acquire conventional MRI sequences, IVIM, and DKI images. The chi-square test, independent sample t-test, and Mann-Whitney U tests were used to compare the differences between conventional MRI features, IVIM, and DKI parameters (Dslow, Dfast, f, mean kurtosis [MK], and mean diffusivity [MD]) between the benign and malignant groups. Receiver-operating characteristic (ROC) curve analysis was also performed. RESULTS Tumor size and depth are statistically different in STTs. Dslow, MK, and MD values in the malignant groups are significantly lower than the benign groups (P < 0.05). However, Dfast and f values are not statistically different between the two groups. The area under the curve (AUC) of Dslow value (0.859) is higher than MD (0.765) and MK (0.676) values for identifying benign and malignant STMs. The Dslow value showed the best specificity (82.93%). The sensitivity and specificity of IVIM and DKI parameters are higher than that of conventional MRI sequences. CONCLUSION IVIM and DKI can be used to distinguish between benign and malignant STMs, with Dslow as the most meaningful parameter.
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Affiliation(s)
- Yajie Liu
- Department of Radiology, The Second Hospital, Dalian Medical University, Shahekou, Dalian, PR China
| | - Zhenzhen Yin
- Department of Radiology, The Second Hospital, Dalian Medical University, Shahekou, Dalian, PR China
| | - Xiangwen Li
- Department of Radiology, The Second Hospital, Dalian Medical University, Shahekou, Dalian, PR China
| | - Yu Zhang
- Department of Radiology, The Second Hospital, Dalian Medical University, Shahekou, Dalian, PR China
| | - Yuan Yuan
- Department of Radiology, The Second Hospital, Dalian Medical University, Shahekou, Dalian, PR China
| | - Lai Wei
- Department of Radiology, The Second Hospital, Dalian Medical University, Shahekou, Dalian, PR China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, Shahekou, Dalian, PR China
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Ueno Y, Tamada T, Sofue K, Murakami T. Diffusion and quantification of diffusion of prostate cancer. Br J Radiol 2022; 95:20210653. [PMID: 34538094 PMCID: PMC8978232 DOI: 10.1259/bjr.20210653] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
For assessing a cancer treatment, and for detecting and characterizing cancer, Diffusion-weighted imaging (DWI) is commonly used. The key in DWI's use extracranially has been due to the emergence of of high-gradient amplitude and multichannel coils, parallelimaging, and echo-planar imaging. The benefit has been fewer motion artefacts and high-quality prostate images.Recently, new techniques have been developed to improve the signal-to-noise ratio of DWI with fewer artefacts, allowing an increase in spatial resolution. For apparent diffusion coefficient quantification, non-Gaussian diffusion models have been proposed as additional tools for prostate cancer detection and evaluation of its aggressiveness. More recently, radiomics and machine learning for prostate magnetic resonance imaging have emerged as novel techniques for the non-invasive characterisation of prostate cancer. This review presents recent developments in prostate DWI and discusses its potential use in clinical practice.
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Affiliation(s)
- Yoshiko Ueno
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Tsutomu Tamada
- Departmentof Radiology, Kawasaki Medical School, Kurashiki, Japan
| | - Keitaro Sofue
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Takamichi Murakami
- Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
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Symmetry Analysis and Conservation Laws for a Time-Fractional Generalized Porous Media Equation. MATHEMATICS 2022. [DOI: 10.3390/math10050687] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The symmetry group method is applied to study a class of time-fractional generalized porous media equations with Riemann–Liouville fractional derivatives. All point symmetry groups and the corresponding optimal subgroups are determined. Then, the similarity reduction is performed to the given equation and some explicit solutions are derived. The asymptotic behaviours for the solutions are also discussed. Through the concept of nonlinear self-adjointness, the conservation laws arising from the admitted point symmetries are listed.
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Papoutsaki MV, Sidhu HS, Dikaios N, Singh S, Atkinson D, Kanber B, Beale T, Morley S, Forster M, Carnell D, Mendes R, Punwani S. Utility of diffusion MRI characteristics of cervical lymph nodes as disease classifier between patients with head and neck squamous cell carcinoma and healthy volunteers. NMR IN BIOMEDICINE 2021; 34:e4587. [PMID: 34240782 DOI: 10.1002/nbm.4587] [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: 02/04/2021] [Revised: 06/10/2021] [Accepted: 06/11/2021] [Indexed: 06/13/2023]
Abstract
Diffusion MRI characteristics assessed by apparent diffusion coefficient (ADC) histogram analysis in head and neck squamous cell carcinoma (HNSCC) have been reported as helpful in classifying tumours based on diffusion characteristics. There is little reported on HNSCC lymph nodes classification by diffusion characteristics. The aim of this study was to determine whether pretreatment nodal microstructural diffusion MRI characteristics can classify diseased nodes of patients with HNSCC from normal nodes of healthy volunteers. Seventy-nine patients with histologically confirmed HNSCC prior to chemoradiotherapy, and eight healthy volunteers, underwent diffusion-weighted (DW) MRI at a 1.5-T MR scanner. Two radiologists contoured lymph nodes on DW (b = 300 s/m2 ) images. ADC, distributed diffusion coefficient (DDC) and alpha (α) values were calculated by monoexponential and stretched exponential models. Histogram analysis metrics of drawn volume were compared between patients and volunteers using a Mann-Whitney test. The classification performance of each metric between the normal and diseased nodes was determined by receiver operating characteristic (ROC) analysis. Intraclass correlation coefficients determined interobserver reproducibility of each metric based on differently drawn ROIs by two radiologists. Sixty cancerous and 40 normal nodes were analysed. ADC histogram analysis revealed significant differences between patients and volunteers (p ≤0.0001 to 0.0046), presenting ADC distributions that were more skewed (1.49 for patients, 1.03 for volunteers; p = 0.0114) and 'peaked' (6.82 for patients, 4.20 for volunteers; p = 0.0021) in patients. Maximum ADC values exhibited the highest area under the curve ([AUC] 0.892). Significant differences were revealed between patients and volunteers for DDC and α value histogram metrics (p ≤0.0001 to 0.0044); the highest AUC were exhibited by maximum DDC (0.772) and the 25th percentile α value (0.761). Interobserver repeatability was excellent for mean ADC (ICC = 0.88) and the 25th percentile α value (ICC = 0.78), but poor for all other metrics. These results suggest that pretreatment microstructural diffusion MRI characteristics in lymph nodes, assessed by ADC and α value histogram analysis, can identify nodal disease.
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Affiliation(s)
| | | | - Nikolaos Dikaios
- Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, UK
| | - Saurabh Singh
- Centre for Medical Imaging, University College London, London, UK
| | - David Atkinson
- Centre for Medical Imaging, University College London, London, UK
| | - Baris Kanber
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Timothy Beale
- Department of Radiology, University College London Hospital, London, UK
| | - Simon Morley
- Department of Radiology, University College London Hospital, London, UK
| | - Martin Forster
- Department of Oncology, University College London, Cancer Institute, London, UK
- Department of Oncology, University College London Hospital, London, UK
| | - Dawn Carnell
- Department of Oncology, University College London Hospital, London, UK
| | - Ruheena Mendes
- Department of Oncology, University College London Hospital, London, UK
| | - Shonit Punwani
- Centre for Medical Imaging, University College London, London, UK
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Value of multiple models of diffusion-weighted imaging for improving the nodal staging of preoperatively node-negative rectal cancer. Abdom Radiol (NY) 2021; 46:4548-4555. [PMID: 34125271 DOI: 10.1007/s00261-021-03125-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 05/10/2021] [Accepted: 05/19/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVE To investigate the parameters of multiple diffusion-weighted imaging (DWI) models for improving nodal staging of preoperatively node-negative rectal cancer. MATERIALS AND METHODS A total of 74 rectal cancer patients without suspected metastatic lymph nodes on conventional MRI who underwent direct surgical resection between November 2018 and January 2020 were enrolled in this prospective study. DWI parameters of mono-exponential model (ADC), intravoxel incoherent motion (D, D* and f), stretched exponential model (DDC and α), and diffusion kurtosis imaging (MD and MK) within the whole tumor were measured to predict the nodal staging in rectal cancer patients. RESULTS The D*, DDC, and MK values were significantly different in patients with pN0 and pN1-2 (all P < 0.001). The D*, DDC, and MK showed good diagnostic performance with the area under the receiver operating characteristic (AUC) of 0.788, 0.827 and 0.799. Multivariate analysis indicated D* (odds ratio, OR = 1.163, P = 0.003) and DDC (OR = 0.007, P = 0.019) as significant predictors of nodal staging. The combination of DDC and D* demonstrated superior diagnostic performance with the AUC, sensitivity, specificity and accuracy of 0.872, 0.800, 0.932 and 0.878, respectively. CONCLUSION Multiple functional DWI parameters were potential to identify the rectal cancer patients with micro-nodal involvement for accurate treatment.
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Shi YJ, Li XT, Zhang XY, Zhu HT, Liu YL, Wei YY, Sun YS. Non-gaussian models of 3-Tesla diffusion-weighted MRI for the differentiation of pancreatic ductal adenocarcinomas from neuroendocrine tumors and solid pseudopapillary neoplasms. Magn Reson Imaging 2021; 83:68-76. [PMID: 34314825 DOI: 10.1016/j.mri.2021.07.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/23/2021] [Accepted: 07/20/2021] [Indexed: 10/20/2022]
Abstract
PURPOSE To assess the MRI performance in differentiating pancreatic ductal adenocarcinomas (PDACs), from solid pseudopapillary neoplasms (SPNs) and pancreatic neuroendocrine tumors (PNETs) using non-gaussian diffusion-weighted imaging models. METHODS This was a retrospective study of patients diagnosed with PDACs (01/2015-06/2019) or with PNETs or SPNs diagnosed (01/2011-12/2019) at our hospital. The lesions were randomized 1:1 to the primary and validation cohorts. The regions of interest (ROIs) were manually drawn on each slice at DWI (b = 1500 s/mm2) from 3 T MRI. D (diffusion coefficient), D* (pseudodiffusion coefficient), f (perfusion fraction), distributed diffusion coefficient (DDC), α (diffusion heterogeneity index), mean diffusivity (MD) and mean kurtosis (MK) were obtained. The parameters with largest performance for differentiation were used to establish a diagnostic model. RESULTS There were 148, 56, and 60 patients with PDAC, PNET, and SPN, respectively. For differentiating PDACs from SPNs, f and MK values were used to establish a diagnostic model with areas under the receiver operating characteristic curves (AUCs) of 0.92 and 0.89 in the primary and validation groups, respectively. For distinguishing PDACs from PNETs, α and MK values were used to establish a diagnostic model with AUCs of 0.87 and 0.86 in the primary and validation groups, respectively. The accuracy rate of the subjective evaluation with the assistance of non-gaussian DWI models for differentiating PDAC from SPNs and PNETs were higher than that of subjective diagnosis alone (P < 0.05). CONCLUSIONS The non-gaussian DWI models could assist radiologists in accurately differentiating PDACs from PNETs and SPNs.
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Affiliation(s)
- Yan-Jie Shi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No.52 Fu Cheng Road, Hai Dian District, Beijing 100142, China
| | - Xiao-Ting Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No.52 Fu Cheng Road, Hai Dian District, Beijing 100142, China
| | - Xiao-Yan Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No.52 Fu Cheng Road, Hai Dian District, Beijing 100142, China
| | - Hai-Tao Zhu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No.52 Fu Cheng Road, Hai Dian District, Beijing 100142, China
| | - Yu-Liang Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No.52 Fu Cheng Road, Hai Dian District, Beijing 100142, China
| | - Yi-Yuan Wei
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No.52 Fu Cheng Road, Hai Dian District, Beijing 100142, China
| | - Ying-Shi Sun
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No.52 Fu Cheng Road, Hai Dian District, Beijing 100142, China.
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Noninvasive DW-MRI metrics for staging hepatic fibrosis and grading inflammatory activity in patients with chronic hepatitis B. Abdom Radiol (NY) 2021; 46:1864-1875. [PMID: 33074424 DOI: 10.1007/s00261-020-02801-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 09/21/2020] [Accepted: 09/29/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE To assess the value of various diffusion parameters obtained from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging (DWI) models for staging hepatic fibrosis (HF) and grading inflammatory activity in patients with chronic hepatitis B (CHB). METHODS 82 patients with CHB and 30 healthy volunteers underwent DWI with 13 b-values on a 3T MRI unit. The standard apparent diffusion coefficient (ADCst) was calculated using a monoexponential model. The true diffusion coefficient (Dt), pseudo-diffusion coefficient (Dp), and perfusion fraction (f) were calculated using a biexponential model. The distributed diffusion coefficient (DDC) and water-molecule diffusion heterogeneity index (α) were calculated using a stretched-exponential model. Receiver operating characteristic (ROC) curves were performed for diffusion parameters to compare the diagnosis performance. RESULTS The distributions of hepatic fibrosis stages and the inflammatory activity grades (METAVIR scoring system) were as follows: F0, n = 1; F1, n = 16; F2, n = 31; F3, n = 19; and F4, n = 15. A0, n = 1; A1, n = 14; A2, n = 46; and A3, n = 21. ADCst, Dt and DDC values showed negative correlation with the fibrosis stage (r = - 0.418, - 0.717 and - 0.630, all P < 0.001) and the inflammatory activity grade (r = - 0.514, - 0.626 and - 0.550, all P < 0.001). The area under the ROC curve (AUC) of Dt (AUC = 0.854, 0.881) and DDC (AUC = 0.794, 0.834) were significantly higher than that of ADCst (AUC = 0.637, 0.717) in discriminating significant fibrosis (≥ F2) and advanced fibrosis (≥ F3) (all P < 0.05). Although Dt (AUC = 0.867, 0.836) and DDC (AUC = 0.810, 0.808) showed higher AUCs than ADCst (AUC = 0.767, 0.803), there was no significant difference in their ability in detecting inflammatory activity grade ≥ A2/A3 (P > 0.05). CONCLUSIONS Dt and DDC are promising indicators and outperform ADCst for staging HF. While both Dt and DDC have similar diagnostic performance compared with ADCst for grading inflammatory activity.
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Zhao L, Liang M, Yang Y, Zhang H, Zhao X. Prediction of false-negative extramural venous invasion in patients with rectal cancer using multiple mathematical models of diffusion-weighted imaging. Eur J Radiol 2021; 139:109731. [PMID: 33905979 DOI: 10.1016/j.ejrad.2021.109731] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/10/2021] [Accepted: 04/16/2021] [Indexed: 01/12/2023]
Abstract
PURPOSE To investigate the parameters from mono-exponential, stretched-exponential, and intravoxel incoherent motion diffusion-weighted imaging (DWI) models for evaluating false-negative extramural venous invasion (EMVI) on conventional magnetic resonance imaging (MRI) in rectal cancer patients. MATERIAL AND METHODS Seventy-two rectal cancer patients with negative EMVI on conventional MRI who underwent direct surgical resection were enrolled in this prospective study. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and water molecular diffusion heterogeneity index (α) values within the whole tumor were obtained to identify the patients with false-negative EMVI. Receiver operating characteristic (ROC) curves were applied to evaluate the diagnostic performance. Multivariate binary logistic regression analysis was conducted to determine the independent risk factors. RESULTS The DDC, D*, f, and α values were significantly different in the EMVI-positive and EMVI-negative groups (P = 0.018, and P < 0.001, respectively). The D*, f, and α values demonstrated good diagnostic performance with area under the ROC curve (AUC) of 0.861, 0.824, and 0.854, respectively. The combined model, including D*, α, and tumor location, proved superior diagnostic performance with the AUC, sensitivity, specificity, and accuracy of 0.971, 0.917, 0.967, and 0.931, respectively. The AUC of the combined model was significantly higher than that of the D*, f, and DDC (P = 0.004, 0.045, and 0.002, respectively). CONCLUSION Multi-b-value DWI may be a potential tool for identifying micro-EMVI in rectal cancer. The combination of DWI parameters and tumor location leads to superior diagnostic performance.
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Affiliation(s)
- Li Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| | - Meng Liang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| | - Yang Yang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| | - Hongmei Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College. No.17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, China.
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Damen FC, Scotti A, Damen FW, Saran N, Valyi-Nagy T, Vukelich M, Cai K. Multimodal apparent diffusion (MAD) weighted magnetic resonance imaging. Magn Reson Imaging 2020; 77:213-233. [PMID: 33309925 DOI: 10.1016/j.mri.2020.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 11/17/2020] [Accepted: 12/08/2020] [Indexed: 10/22/2022]
Affiliation(s)
- Frederick C Damen
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA.
| | - Alessandro Scotti
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA.
| | - Frederick W Damen
- Department of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.
| | - Nitu Saran
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA.
| | - Tibor Valyi-Nagy
- Department of Pathology, University of Illinois at Chicago, Chicago, IL, USA.
| | - Mirko Vukelich
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA.
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA.
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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: 1.0] [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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Zhang Q, Ouyang H, Ye F, Chen S, Xie L, Zhao X, Yu X. Multiple mathematical models of diffusion-weighted imaging for endometrial cancer characterization: Correlation with prognosis-related risk factors. Eur J Radiol 2020; 130:109102. [PMID: 32673928 DOI: 10.1016/j.ejrad.2020.109102] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Revised: 05/18/2020] [Accepted: 05/26/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE To investigate mono-exponential, bi-exponential, and stretched-exponential models of diffusion-weighted imaging (DWI) for evaluation of prognosis-related risk factors of endometrial cancer (EC). METHOD Sixty-one consecutive patients with EC who preoperatively underwent pelvic MRI with multiple b value DWI between September 2016 and May 2018 were enrolled. The apparent-diffusion-coefficient (ADC), bi-exponential model parameters (D, D* and f) and stretched-exponential model parameters (DDC and α) were measured and compared to analyze the following prognosis-related risk factors confirmed by pathology: histological grade, depth of myometrial invasion, cervical stromal infiltration (CSI) and lymphovascular invasion (LVSI). A stepwise multilvariate logistic regression and the receiver operating characteristic (ROC) curves were performed for further statistical analysis. RESULTS Lower ADC, D, f, and DDC were observed in tumor with high grade compared with a low-grade group, and the largest area under curve (AUC) was obtained when combining f and DDC values. ADC, D, f, DDC, and α were significantly different in patients with deep myometrial invasion (DMI) compared to those without DMI; the combination of f, DDC and α showed the highest AUC. Significantly different ADC and f were found between patients' presence and absence CSI; the f values showed the highest diagnostic performance with an AUC of 0.825. Regarding the LVSI, ADC, D*, f, and DDC were significantly lower in tumors with LVSI compared to those without LVSI; the combination of f and DDC showed the largest AUC. CONCLUSION Multiple mathematical DWI models are a useful approach for the prediction of prognosis-related risk factors in EC.
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Affiliation(s)
- Qi Zhang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Han Ouyang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Feng Ye
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Shuang Chen
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Lizhi Xie
- GE Healthcare, MR Research China, Beijing, China
| | - Xinming Zhao
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Xiaoduo Yu
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Lyu J, Yang G, Mei Y, Guo L, Guo Y, Zhang X, Xu Y, Feng Y. Non-Gaussian Diffusion Models and T 1 rho Quantification in the Assessment of Hepatic Sinusoidal Obstruction Syndrome in Rats. J Magn Reson Imaging 2020; 52:1110-1121. [PMID: 32246796 DOI: 10.1002/jmri.27156] [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: 01/03/2020] [Revised: 03/18/2020] [Accepted: 03/18/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Non-Gaussian diffusion models and T1 rho quantification may reflect the changes in tissue heterogeneity in hepatic sinusoidal obstruction syndrome (SOS). PURPOSE To investigate the feasibility of diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and T1 rho quantification in detecting and staging SOS in a monocrotaline (MCT)-induced rat model. STUDY TYPE Animal study. POPULATION Thirty male Sprague-Dawley rats gavaged with MCT to induce hepatic SOS and six male rats without any intervention. FIELD STRENGTH/SEQUENCE 3.0T, DWI with five b-values (0-2000 s/mm2 ) and T1 rho with five spin lock times (1-60 msec). ASSESSMENT MRI was performed 1 day before and 1, 3, 5, 7, and 10 days after MCT administration. The corrected apparent diffusion coefficient (Dapp ), kurtosis coefficient (Kapp ), distributed diffusion coefficient (DDC), and intravoxel water molecular diffusion heterogeneity (α) were calculated from the corresponding non-Gaussian diffusion model. The T1 rho value was calculated using a monoexponential model. Specimens obtained from the six timepoints were categorized into normal liver (n = 6), early-stage (n = 16), and late-stage (n = 14) SOS in accordance with the pathological score. STATISTICAL TESTS Parametric statistical methods and receiver operating characteristic (ROC) curves were employed to determine diagnostic accuracy. RESULTS The Dapp , Kapp , DDC, α, and T1 rho values were correlated with pathological score with r values of -0.821, 0.726, -0.828, -0.739, and 0.714 (all P < 0.001), respectively. DKI (combined Dapp and Kapp ) and SEM (combined DDC and α) were better than T1 rho for staging SOS. The areas under the ROC curve of DKI, SEM, and T1 rho for differentiating normal liver and early-stage SOS were 0.97, 1.00, and 0.79, whereas those of DKI, SEM, and T1 rho for differentiating early-stage and late-stage SOS were 1.00, 0.97, and 0.92, respectively. DATA CONCLUSION DKI, SEM, and T1 rho may be helpful in staging SOS. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1110-1121.
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Affiliation(s)
- Jian Lyu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
| | - Guixiang Yang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.,Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, Guangdong, China
| | - Yingjie Mei
- Philips Healthcare, Guangzhou, Guangdong, China
| | - Li Guo
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China.,Department of MRI, The First People's Hospital of Foshan (Affiliated Foshan Hospital of Sun Yat-sen University), Foshan, Guangdong, China
| | - Yihao Guo
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
| | - Xinyuan Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
| | - Yikai Xu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.,Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou, Guangdong, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
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Liao X, Zheng S, Lin G. Pulsed field gradient signal attenuation of restricted anomalous diffusions in plate, sphere, and cylinder with wall relaxation. Phys Rev E 2020; 101:012128. [PMID: 32069550 DOI: 10.1103/physreve.101.012128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Indexed: 11/07/2022]
Abstract
The effect of boundary relaxation on pulsed field gradient (PFG) anomalous restricted diffusion is investigated in this paper. The PFG signal attenuation expressions of anomalous diffusion in plate, sphere, and cylinder are derived based on fractional calculus. In addition, approximate expressions for boundary relaxation induced short time signal attenuation under zero gradient field and boundary relaxation affected short time apparent diffusion coefficients are given in this paper. Unlike the exponential signal attenuation in normal diffusion, the PFG signal attenuation in anomalous diffusion with boundary relaxation is either a Mittag-Leffler-function-based attenuation or a stretched-exponential-function-based attenuation. The stretched exponential attenuations of all three structures clearly show the diffractive pattern. In contrast, only in the plate structure does the Mittag-Leffler-function-based attenuation display an obvious diffractive pattern. Additionally, anomalous diffusion with smaller time derivative order α has a weaker diffractive pattern and less signal attenuation. Moreover, the results demonstrate that boundary relaxation induced signal attenuation is significantly affected by the anomalous diffusion when no gradient field is applied. Meanwhile, the boundary relaxation significantly affects PFG signal attenuation of anomalous diffusion in the following ways: The boundary relaxation results in reduced radius from the minimum of the diffractive patterns, and it results in an increased apparent diffusion coefficient and decreased surfaces to volume ratio in varying the diffusion time experiment; the boundary relaxation also substantially affects the apparent diffusion coefficient of sphere structure in the variation of gradient experiment.
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Affiliation(s)
- Xinli Liao
- Chemistry Department, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China
| | - Shaokuan Zheng
- Department of Radiology, UMASS Medical School, Worcester, Massachusetts 01655, USA
| | - Guoxing Lin
- Carlson School of Chemistry and Biochemistry, Clark University, Worcester, Massachusetts 01610, USA
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Kim E, Kim CK, Kim HS, Jang DP, Kim IY, Hwang J. Histogram analysis from stretched exponential model on diffusion-weighted imaging: evaluation of clinically significant prostate cancer. Br J Radiol 2020; 93:20190757. [PMID: 31899654 DOI: 10.1259/bjr.20190757] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVE To evaluate the usefulness of histogram analysis of stretched exponential model (SEM) on diffusion-weighted imaging in evaluating clinically significant prostate cancer (CSC). METHODS A total of 85 patients with prostate cancer underwent 3 T multiparametric MRI, followed by radical prostatectomy. Histogram parameters of the tumor from the SEM [distributed diffusion coefficient (DDC) and α] and the monoexponential model [MEM; apparent diffusion coefficient (ADC)] were evaluated. The associations between parameters and Gleason score or Prostate Imaging Reporting and Data System v. 2 were evaluated. The area under the receiver operating characteristics curve was calculated to evaluate diagnostic performance of parameters in predicting CSC. RESULTS The values of histogram parameters of DDC and ADC were significantly lower in patients with CSC than in patients without CSC (p < 0.05), except for skewness and kurtosis. The value of the 25th percentile of α was significantly lower in patients with CSC than in patients without CSC (p = 0.014). Histogram parameters of ADC and DDC had significant weak to moderate negative associations with Gleason score or Prostate Imaging Reporting and Data System v. 2 (p < 0.001), except for skewness and kurtosis. For predicting CSC, the area under the curves of mean ADC (0.856), 50th percentile DDC (0.852), and 25th percentile α (0.707) yielded the highest values compared to other histogram parameters from each group. CONCLUSION Histogram analysis of the SEM on diffusion-weighted imaging may be a useful quantitative tool for evaluating CSC. However, the SEM did not outperform the MEM. ADVANCES IN KNOWLEDGE Histogram parameters of SEM may be useful for evaluating CSC.
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Affiliation(s)
- EunJu Kim
- Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea.,Philips Healthcare, Seoul, Republic of Korea
| | - Chan Kyo Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Department of Medical Device Management and Research, SAIHST Sungkyunkwan University, Seoul, Republic of Korea.,Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hyun Soo Kim
- Department of Medicine, Graduate School, Kyung Hee University, Seoul, Republic of Korea
| | - Dong Pyo Jang
- Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea
| | - In Young Kim
- Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea
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Lin L, Xue Y, Duan Q, Chen X, Chen H, Jiang R, Zhong T, Xu G, Geng D, Zhang J. Grading meningiomas using mono-exponential, bi-exponential and stretched exponential model-based diffusion-weighted MR imaging. Clin Radiol 2019; 74:651.e15-651.e23. [DOI: 10.1016/j.crad.2019.04.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 04/03/2019] [Indexed: 02/07/2023]
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16
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Jin YN, Zhang Y, Cheng JL, Zheng DD, Hu Y. Monoexponential, Biexponential, and stretched-exponential models using diffusion-weighted imaging: A quantitative differentiation of breast lesions at 3.0T. J Magn Reson Imaging 2019; 50:1461-1467. [PMID: 30919518 DOI: 10.1002/jmri.26729] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2018] [Revised: 03/11/2019] [Accepted: 03/12/2019] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Diffusion-weighted imaging (DWI) plays an important role in the differentiation of malignant and benign breast lesions. PURPOSE To investigate the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched-exponential DWI models in the differential diagnosis of breast lesions. STUDY TYPE Prospective. POPULATION Sixty-one patients (age range: 25-68 years old; mean age: 46 years old) with 31 malignant lesions, 42 benign lesions, and 28 normal breast tissues diagnosed initially by clinical palpation, ultrasonography, or conventional mammography were enrolled in the study from January to September 2016. FIELD STRENGTH 3.0T MR scanner, T1 WI, T2 WI, DWI (conventional and multi-b values), dynamic contrast-enhanced. ASSESSMENT The apparent diffusion coefficient (ADC) was calculated by monoexponential analysis. The diffusion coefficient (ADCslow ), pseudodiffusion coefficient (ADCfast ), and perfusion fraction (f) were calculated using the biexponential model. The distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) were obtained using a stretched-exponential model. All parameters were compared for malignant tumors, benign tumors, and normal breast tissues. A receiver operating characteristic curve was used to compare the ability of these parameters, in order to differentiate benign and malignant breast lesions. STATISTICAL TESTS All statistical analyses were performed using statistical software (SPSS). RESULTS ADC, ADCslow , f, DDC, and α values were significantly lower in malignant tumors when compared with normal breast tissues and benign tumors (P < 0.05). However, ADC and f had higher area under the receiver operating characteristic curve (AUC) values (0.889 and 0.919, respectively). DATA CONCLUSION The parameters derived from the biexponential and stretched-exponential DWI could provide additional information for differentiating between benign and malignant breast tumors when compared with conventional diffusion parameters. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;50:1461-1467.
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Affiliation(s)
- Ya-Nan Jin
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yan Zhang
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jing-Liang Cheng
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | | | - Ying Hu
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Zhang J, Chen X, Chen D, Wang Z, Li S, Zhu W. Grading and proliferation assessment of diffuse astrocytic tumors with monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging and diffusion kurtosis imaging. Eur J Radiol 2018; 109:188-195. [PMID: 30527302 DOI: 10.1016/j.ejrad.2018.11.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 09/26/2018] [Accepted: 11/04/2018] [Indexed: 12/11/2022]
Abstract
PURPOSE To compare the main parameters derived from monoexponential, biexponential and stretched-exponential diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) with respect to diagnostic performance for tumor grading and proliferation assessment in diffuse astrocytic tumors (DATs). MATERIALS AND METHODS Fifty-eight pathologically confirmed DAT patients who underwent DWI and DKI on a 3-T scanner were prospectively collected and retrospectively reviewed. Measurements including the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), fractional anisotropy (FA), and mean kurtosis (MK) were compared between tumor grades (Ⅱ, Ⅲ, and Ⅳ) by using a Jonckheere-Terpstra test. Receiver operating characteristic (ROC) curves were used to assess the diagnostic efficacy of these parameters. Spearman's rho with the Ki-67 labeling index (LI) was calculated for each parameter. RESULTS MK values differed significantly between all DAT subtypes and increased with grade. The ADC, D, f, DDC, α and MD values were significantly higher in grade Ⅱ tumors than in grade Ⅲ/Ⅳ tumors. D* values were significantly lower in grade Ⅱ tumors than in grade Ⅳ tumors (all P < 0.05). In discriminating between grade Ⅱ and Ⅲ tumors, α, MK, MD, D and f had significantly greater area under the ROC curve (AUC) values than D* and FA (0.927, 0.901, 0.896, 0.895, and 0.889, respectively vs 0.659 and 0.598, respectively, P < 0.05). In discriminating between grade Ⅲ and Ⅳ tumors, only MK demonstrated acceptable discrimination (AUC = 0.711). MK and D showed a strong correlation with the Ki-67 LI (ρ = 0.791 and -0.789, respectively, P < 0.001). D*, f, MD, ADC, DDC and α showed a moderate correlation (|ρ| ranged from 0.415 to 0.698, P < 0.05). CONCLUSION MK and D have considerable potential to predict the degree of proliferation of DATs. MK could effectively characterize microstructural changes throughout the malignant transformation of DATs and provided useful complementary information for grading.
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Affiliation(s)
- Ju Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Xiaowei Chen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Dong Chen
- Department of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Zhenxiong Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Shihui Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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18
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Li C, Chen M, Wan B, Yu J, Liu M, Zhang W, Wang J. A comparative study of Gaussian and non-Gaussian diffusion models for differential diagnosis of prostate cancer with in-bore transrectal MR-guided biopsy as a pathological reference. Acta Radiol 2018; 59:1395-1402. [PMID: 29486596 DOI: 10.1177/0284185118760961] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Although several studies have been reported on evaluating the performance of Gaussian and different non-Gaussian diffusion models on prostate cancer, few studies have been reported on the comparison of different models on differential diagnosis for prostate cancer. Purpose To compare the utility of various metrics derived from monoexponential model (MEM), biexponential model (BEM), stretched-exponential model (SEM) based diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differential diagnosis of prostate cancer. Material and Methods Thirty-three patients underwent magnetic resonance imaging (MRI) examination. Multi-b value and multi-direction DWIs were performed. In-bore MR-guided biopsy was performed. Apparent diffusion coefficient (ADC), pure molecular diffusion (ADCslow), pseudo-diffusion coefficient (ADCfast), perfusion fraction (f), water molecular diffusion heterogeneity index (α), distributed diffusion coefficient (DDC), non-Gaussian diffusion coefficient (MD), and mean kurtosis (MK) values were calculated and compared between cancerous and non-cancerous groups. Receiver operating characteristic (ROC) analysis was performed for all parameters and models. Results ADC, ADCslow, DDC, and MD values were significantly lower while MK value was significantly higher in prostate cancer than those of prostatitis and benign prostatic hyperplasia. ADC, ADCslow, DDC, MD, and MK could discriminate between tumor and non-tumorous lesions (area under the curve, 0.856, 0.835, 0.866, 0.918, and 0.937, respectively). MK was superior to ADC in the discrimination of prostate cancer. DKI was superior to MEM in the discrimination of prostate cancer. Conclusions Parameters derived from both Gaussian and non-Gaussian models could characterize prostate cancer. DKI may be advantageous than DWI for detection of prostate cancer.
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Affiliation(s)
- Chunmei Li
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, PR China
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, PR China
| | - Ben Wan
- Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, PR China
| | - Jingying Yu
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, PR China
| | - Ming Liu
- Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, PR China
| | - Wei Zhang
- Department of Pathology, Beijing Hospital, National Center of Gerontology, Beijing, PR China
| | - Jianye Wang
- Department of Urology, Beijing Hospital, National Center of Gerontology, Beijing, PR China
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Hu Y, Tang H, Li H, Li A, Li J, Hu D, Li Z, Kamel IR. Assessment of different mathematical models for diffusion-weighted imaging as quantitative biomarkers for differentiating benign from malignant solid hepatic lesions. Cancer Med 2018; 7:3501-3509. [PMID: 29733515 PMCID: PMC6051139 DOI: 10.1002/cam4.1535] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2018] [Revised: 04/09/2018] [Accepted: 04/10/2018] [Indexed: 01/25/2023] Open
Abstract
To quantitatively compare the monoexponential, biexponential, and stretched‐exponential diffusion‐weighted imaging (DWI) models in differentiating benign from malignant solid hepatic lesions. The institutional review board approved this retrospective study and waived the informed consent requirement. A total of 188 patients with 288 hepatic lesions included 202 malignant lesions and 86 benign lesions were assessed (confirmed by pathology or clinical follow‐up for 6 months). All patients underwent hepatic 3.0‐T MRI, including multi‐b DWI that used 12 b values. The ADC, Dp, Dt, perfusion fraction (fp), α, and DDC values for normal liver, benign liver lesions, and malignant liver lesions were calculated. Independent sample t tests were used for comparisons. The diagnostic performance of the parameters was evaluated using ROC analysis. The AUC value for each model was also calculated. The value of Dp was significantly lower in benign lesions than in normal hepatic parenchyma while others were significantly higher (P < .001). Whereas Values of Dt and α in malignant hepatic lesions were significantly higher than in normal hepatic parenchyma (P < .001), and the Dp value was significantly lower (P < .001). Values of ADC, fp, DDC, and α for malignant hepatic lesions were significantly lower than those for benign hepatic lesions (P < .001). ROC analysis showed that the diagnostic value of the biexponential model of normal hepatic parenchyma vs benign hepatic lesions and normal hepatic parenchyma vs malignant hepatic lesions was high (0.946 and 0.876, respectively). In the differential diagnosis of benign and malignant hepatic lesions, DDC had the highest AUC value (0.819). The biexponential and stretched‐exponential DWI may provide additional information and improve the differential diagnosis of benign and malignant hepatic lesions compared with the monoexponential DWI.
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Affiliation(s)
- Yao Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hao Tang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Haojie Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Anqin Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jiali Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ihab R Kamel
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Medical Institutions, Baltimore, MD, USA
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Zeng Q, Shi F, Zhang J, Ling C, Dong F, Jiang B. A Modified Tri-Exponential Model for Multi- b-value Diffusion-Weighted Imaging: A Method to Detect the Strictly Diffusion-Limited Compartment in Brain. Front Neurosci 2018. [PMID: 29535599 PMCID: PMC5834430 DOI: 10.3389/fnins.2018.00102] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Purpose: To present a new modified tri-exponential model for diffusion-weighted imaging (DWI) to detect the strictly diffusion-limited compartment, and to compare it with the conventional bi- and tri-exponential models. Methods: Multi-b-value diffusion-weighted imaging (DWI) with 17 b-values up to 8,000 s/mm2 were performed on six volunteers. The corrected Akaike information criterions (AICc) and squared predicted errors (SPE) were calculated to compare these three models. Results: The mean f0 values were ranging 11.9–18.7% in white matter ROIs and 1.2–2.7% in gray matter ROIs. In all white matter ROIs: the AICcs of the modified tri-exponential model were the lowest (p < 0.05 for five ROIs), indicating the new model has the best fit among these models; the SPEs of the bi-exponential model were the highest (p < 0.05), suggesting the bi-exponential model is unable to predict the signal intensity at ultra-high b-value. The mean ADCvery−slow values were extremely low in white matter (1–7 × 10−6 mm2/s), but not in gray matter (251–445 × 10−6 mm2/s), indicating that the conventional tri-exponential model fails to represent a special compartment. Conclusions: The strictly diffusion-limited compartment may be an important component in white matter. The new model fits better than the other two models, and may provide additional information.
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Affiliation(s)
- Qiang Zeng
- Department of Neurosurgery, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Feina Shi
- Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jianmin Zhang
- Department of Neurosurgery, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Chenhan Ling
- Department of Neurosurgery, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Fei Dong
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Biao Jiang
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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21
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Analysis of PFG Anomalous Diffusion via Real-Space and Phase-Space Approaches. MATHEMATICS 2018. [DOI: 10.3390/math6020017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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22
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López-Sánchez EJ, Romero JM, Yépez-Martínez H. Fractional cable equation for general geometry: A model of axons with swellings and anomalous diffusion. Phys Rev E 2018; 96:032411. [PMID: 29346980 DOI: 10.1103/physreve.96.032411] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Indexed: 11/07/2022]
Abstract
Different experimental studies have reported anomalous diffusion in brain tissues and notably this anomalous diffusion is expressed through fractional derivatives. Axons are important to understand neurodegenerative diseases such as multiple sclerosis, Alzheimer's disease, and Parkinson's disease. Indeed, abnormal accumulation of proteins and organelles in axons is a hallmark of these diseases. The diffusion in the axons can become anomalous as a result of this abnormality. In this case the voltage propagation in axons is affected. Another hallmark of different neurodegenerative diseases is given by discrete swellings along the axon. In order to model the voltage propagation in axons with anomalous diffusion and swellings, in this paper we propose a fractional cable equation for a general geometry. This generalized equation depends on fractional parameters and geometric quantities such as the curvature and torsion of the cable. For a cable with a constant radius we show that the voltage decreases when the fractional effect increases. In cables with swellings we find that when the fractional effect or the swelling radius increases, the voltage decreases. Similar behavior is obtained when the number of swellings and the fractional effect increase. Moreover, we find that when the radius swelling (or the number of swellings) and the fractional effect increase at the same time, the voltage dramatically decreases.
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Affiliation(s)
- Erick J López-Sánchez
- Posgrado en Ciencias Naturales e Ingeniería, Universidad Autónoma Metropolitana, Cuajimalpa and Vasco de Quiroga 4871, Santa Fe Cuajimalpa, Ciudad de México 05300, Mexico
| | - Juan M Romero
- Departamento de Matemáticas Aplicadas y Sistemas, Universidad Autónoma Metropolitana-Cuajimalpa, Vasco de Quiroga 4871, Santa Fe Cuajimalpa, Ciudad de México 05300, Mexico
| | - Huitzilin Yépez-Martínez
- Universidad Autónoma de la Ciudad de México, Prolongación San Isidro 151, San Lorenzo Tezonco, Iztapalapa, Ciudad de México 09790, Mexico
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23
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Hyde JS. Autobiography of James S. Hyde. APPLIED MAGNETIC RESONANCE 2017; 48:1103-1147. [PMID: 29962662 PMCID: PMC6022859 DOI: 10.1007/s00723-017-0950-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The papers, book chapters, reviews, and patents by James S. Hyde in the bibliography of this document have been separated into EPR and MRI sections, and within each section by topics. Within each topic, publications are listed chronologically. A brief summary is provided for each patent listed. A few publications and patents that do not fit this schema have been omitted. This list of publications is preceded by a scientific autobiography that focuses on selected topics that are judged to have been of most scientific importance. References to many of the publications and patents in the bibliography are made in the autobiography.
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Affiliation(s)
- James S Hyde
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plan Road, Milwaukee, WI 53226; 414-955-4000; ; ORCID: 0000-0002-3023-1243
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Bedair R, Priest AN, Patterson AJ, McLean MA, Graves MJ, Manavaki R, Gill AB, Abeyakoon O, Griffiths JR, Gilbert FJ. Assessment of early treatment response to neoadjuvant chemotherapy in breast cancer using non-mono-exponential diffusion models: a feasibility study comparing the baseline and mid-treatment MRI examinations. Eur Radiol 2017; 27:2726-2736. [PMID: 27798751 PMCID: PMC5486805 DOI: 10.1007/s00330-016-4630-x] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Revised: 09/29/2016] [Accepted: 10/03/2016] [Indexed: 12/22/2022]
Abstract
OBJECTIVES To assess the feasibility of the mono-exponential, bi-exponential and stretched-exponential models in evaluating response of breast tumours to neoadjuvant chemotherapy (NACT) at 3 T. METHODS Thirty-six female patients (median age 53, range 32-75 years) with invasive breast cancer undergoing NACT were enrolled for diffusion-weighted MRI (DW-MRI) prior to the start of treatment. For assessment of early response, changes in parameters were evaluated on mid-treatment MRI in 22 patients. DW-MRI was performed using eight b values (0, 30, 60, 90, 120, 300, 600, 900 s/mm2). Apparent diffusion coefficient (ADC), tissue diffusion coefficient (D t), vascular fraction (ƒ), distributed diffusion coefficient (DDC) and alpha (α) parameters were derived. Then t tests compared the baseline and changes in parameters between response groups. Repeatability was assessed at inter- and intraobserver levels. RESULTS All patients underwent baseline MRI whereas 22 lesions were available at mid-treatment. At pretreatment, mean diffusion coefficients demonstrated significant differences between groups (p < 0.05). At mid-treatment, percentage increase in ADC and DDC showed significant differences between responders (49 % and 43 %) and non-responders (21 % and 32 %) (p = 0.03, p = 0.04). Overall, stretched-exponential parameters showed excellent repeatability. CONCLUSION DW-MRI is sensitive to baseline and early treatment changes in breast cancer using non-mono-exponential models, and the stretched-exponential model can potentially monitor such changes. KEY POINTS • Baseline diffusion coefficients demonstrated significant differences between complete pathological responders and non-responders. • Increase in ADC and DDC at mid-treatment can discriminate responders and non-responders. • The ƒ fraction at mid-treatment decreased in responders whereas increased in non-responders. • The mono- and stretched-exponential models showed excellent inter- and intrarater repeatability. • Treatment effects can potentially be assessed by non-mono-exponential diffusion models.
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Affiliation(s)
- Reem Bedair
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Andrew N Priest
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge, CB2 0QQ, UK
| | - Andrew J Patterson
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge, CB2 0QQ, UK
| | - Mary A McLean
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge, CB2 0QQ, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Martin J Graves
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge, CB2 0QQ, UK
| | - Roido Manavaki
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Andrew B Gill
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Oshaani Abeyakoon
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - John R Griffiths
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, CB2 0RE, UK
| | - Fiona J Gilbert
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK.
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Fujima N, Yoshida D, Sakashita T, Homma A, Kudo K, Shirato H. Residual tumour detection in post-treatment granulation tissue by using advanced diffusion models in head and neck squamous cell carcinoma patients. Eur J Radiol 2017; 90:14-19. [DOI: 10.1016/j.ejrad.2017.02.025] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2016] [Revised: 02/08/2017] [Accepted: 02/15/2017] [Indexed: 10/20/2022]
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Wang F, Wang Y, Zhou Y, Liu C, Xie L, Zhou Z, Liang D, Shen Y, Yao Z, Liu J. Comparison between types I and II epithelial ovarian cancer using histogram analysis of monoexponential, biexponential, and stretched-exponential diffusion models. J Magn Reson Imaging 2017; 46:1797-1809. [PMID: 28379611 DOI: 10.1002/jmri.25722] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2016] [Accepted: 03/14/2017] [Indexed: 12/23/2022] Open
Abstract
PURPOSE To evaluate the utility of histogram analysis of monoexponential, biexponential, and stretched-exponential models to a dualistic model of epithelial ovarian cancer (EOC). MATERIALS AND METHODS Fifty-two patients with histopathologically proven EOC underwent preoperative magnetic resonance imaging (MRI) (including diffusion-weighted imaging [DWI] with 11 b-values) using a 3.0T system and were divided into two groups: types I and II. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) histograms were obtained based on solid components of the entire tumor. The following metrics of each histogram were compared between two types: 1) mean; 2) median; 3) 10th percentile and 90th percentile. Conventional MRI morphological features were also recorded. RESULTS Significant morphological features for predicting EOC type were maximum diameter (P = 0.007), texture of lesion (P = 0.001), and peritoneal implants (P = 0.001). For ADC, D, f, DDC, and α, all metrics were significantly lower in type II than type I (P < 0.05). Mean, median, 10th, and 90th percentile of D* were not significantly different (P = 0.336, 0.154, 0.779, and 0.203, respectively). Most histogram metrics of ADC, D, and DDC had significantly higher area under the receiver operating characteristic curve values than those of f and α (P < 0.05) CONCLUSION: It is feasible to grade EOC by morphological features and three models with histogram analysis. ADC, D, and DDC have better performance than f and α; f and α may provide additional information. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1797-1809.
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Affiliation(s)
- Feng Wang
- Department of Radiology, Peking University Third Hospital, Haidian District, Beijing, P.R. China
| | - Yuxiang Wang
- Department of Pathology, School of Basic Medical Science, Peking University Third Hospital, Peking University Health Science Center, Beijing, P.R. China
| | - Yan Zhou
- Department of Radiology, Peking University Third Hospital, Haidian District, Beijing, P.R. China
| | - Congrong Liu
- Department of Pathology, School of Basic Medical Science, Peking University Third Hospital, Peking University Health Science Center, Beijing, P.R. China
| | - Lizhi Xie
- GE Healthcare, MR Research China, Beijing, P.R. China
| | - Zhenyu Zhou
- GE Healthcare, MR Research China, Beijing, P.R. China
| | - Dong Liang
- Siemens Ltd., China, Chaoyang District, Beijing, P.R. China
| | - Yang Shen
- Department of Radiology, Peking University Third Hospital, Haidian District, Beijing, P.R. China
| | - Zhihang Yao
- Department of Radiology, Peking University Third Hospital, Haidian District, Beijing, P.R. China
| | - Jianyu Liu
- Department of Radiology, Peking University Third Hospital, Haidian District, Beijing, P.R. China
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Zhu HB, Zhang XY, Zhou XH, Li XT, Liu YL, Wang S, Sun YS. Assessment of pathological complete response to preoperative chemoradiotherapy by means of multiple mathematical models of diffusion-weighted MRI in locally advanced rectal cancer: A prospective single-center study. J Magn Reson Imaging 2016; 46:175-183. [PMID: 27981667 DOI: 10.1002/jmri.25567] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Accepted: 11/10/2016] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To assess stretched-exponential, mono-exponential and intravoxel incoherent motion (IVIM) models of diffusion-weighted MRI(DWI) in predicting pathological complete response (pCR) to neoadjuvant chemoradiotherapy (CRT) in rectal cancer patients. MATERIALS AND METHODS This prospective study recruited 98 consecutive patients with locally advanced rectal cancer who underwent 3 Tesla MR examination before, during and after CRT. The apparent diffusion coefficient (ADC), IVIM-derived parameters (D, f, and D*), and stretched-exponential model-derived parameters (DDC and α) were measured. The parameters and their corresponding changes during and after CRT were compared between pCR and non-pCR. Receiver-operating characteristic curve analysis was performed to evaluate the diagnostic performance. Coefficient of variations and intraclass correlation coefficient were calculated to assess reliability and agreement. RESULTS Nineteen patients achieved pCR while 79 did not. The pCR group had higher ADC and α (ADC2 and α2 ), and their changes (ΔADC2 , and Δα2 ) at the endpoint than non-pCR group. α2 and ADC2 yielded similar AUCs (P = 0.339), Δα2 and ΔADC2 yielded similar AUCs (P = 0.263) ADC and α presented substantial agreement, and α presented the minimum CV (5.0-7.0%). CONCLUSION ADC and α were useful for assessing pCR after CRT. α might be more useful because it demonstrated better diagnostic performance than IVIM-derived parameters and better reliability than ADC. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:175-183.
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Affiliation(s)
- Hai-Bin Zhu
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Beijing, China
| | - Xiao-Yan Zhang
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Beijing, China
| | - Xiao-Hong Zhou
- Center for Magnetic Research, Medical Hospital, University of Illinois Hospital, Chicago, Illinois, USA
| | - Xiao-Ting Li
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Beijing, China
| | - Yu-Liang Liu
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Beijing, China
| | - Shuai Wang
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Beijing, China
| | - Ying-Shi Sun
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, No. 52, Beijing, China
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Lin G. Analyzing signal attenuation in PFG anomalous diffusion via a non-Gaussian phase distribution approximation approach by fractional derivatives. J Chem Phys 2016; 145:194202. [DOI: 10.1063/1.4967403] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
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Contribution of mono-exponential, bi-exponential and stretched exponential model-based diffusion-weighted MR imaging in the diagnosis and differentiation of uterine cervical carcinoma. Eur Radiol 2016; 27:2400-2410. [DOI: 10.1007/s00330-016-4596-8] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2016] [Revised: 08/24/2016] [Accepted: 09/01/2016] [Indexed: 10/20/2022]
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Taouli B, Beer AJ, Chenevert T, Collins D, Lehman C, Matos C, Padhani AR, Rosenkrantz AB, Shukla-Dave A, Sigmund E, Tanenbaum L, Thoeny H, Thomassin-Naggara I, Barbieri S, Corcuera-Solano I, Orton M, Partridge SC, Koh DM. Diffusion-weighted imaging outside the brain: Consensus statement from an ISMRM-sponsored workshop. J Magn Reson Imaging 2016; 44:521-40. [PMID: 26892827 PMCID: PMC4983499 DOI: 10.1002/jmri.25196] [Citation(s) in RCA: 127] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2015] [Revised: 01/28/2016] [Accepted: 01/30/2016] [Indexed: 12/11/2022] Open
Abstract
The significant advances in magnetic resonance imaging (MRI) hardware and software, sequence design, and postprocessing methods have made diffusion-weighted imaging (DWI) an important part of body MRI protocols and have fueled extensive research on quantitative diffusion outside the brain, particularly in the oncologic setting. In this review, we summarize the most up-to-date information on DWI acquisition and clinical applications outside the brain, as discussed in an ISMRM-sponsored symposium held in April 2015. We first introduce recent advances in acquisition, processing, and quality control; then review scientific evidence in major organ systems; and finally describe future directions. J. Magn. Reson. Imaging 2016;44:521-540.
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Affiliation(s)
- Bachir Taouli
- Department of Radiology and Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ambros J. Beer
- Department of Nuclear Medicine, University Hospital Ulm, Ulm, Germany
| | - Thomas Chenevert
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - David Collins
- CR UK Cancer Imaging Centre, Institute of Cancer Research and Department of Radiology, Royal Marsden Hospital, London, UK
| | - Constance Lehman
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Celso Matos
- Department of Radiology, Champalimaud Clinical Centre, Lisbon, Portugal
| | | | | | - Amita Shukla-Dave
- Departments of Medical Physics and Radiology, Memorial Sloan-Kettering Cancer Center, New York, New York, USA
| | - Eric Sigmund
- Irene and Bernard Schwartz Center for Biomedical Imaging (CBI) and Center for Advanced Imaging and Innovation (CAIR), Department of Radiology, NYU Langone Medical Center, New York, New York, USA
| | - Lawrence Tanenbaum
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Harriet Thoeny
- Department of Diagnostic Radiology, Inselspital Bern, Bern, Switzerland
| | | | | | - Idoia Corcuera-Solano
- Department of Radiology and Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Matthew Orton
- CR UK Cancer Imaging Centre, Institute of Cancer Research and Department of Radiology, Royal Marsden Hospital, London, UK
| | | | - Dow-Mu Koh
- Institute of Cancer Research and Department of Radiology, Royal Marsden Hospital, London, UK
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Lin G. Instantaneous signal attenuation method for analysis of PFG fractional diffusions. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2016; 269:36-49. [PMID: 27209371 DOI: 10.1016/j.jmr.2016.05.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2016] [Revised: 04/15/2016] [Accepted: 05/12/2016] [Indexed: 06/05/2023]
Abstract
An instantaneous signal attenuation (ISA) method for analyzing pulsed field gradient (PFG) fractional diffusion (FD) has been developed, which is modified from the propagator approach developed in 2001 by Lin et al. for analyzing PFG normal diffusion. Both, the current ISA method and the propagator method have the same fundamental basis that the total signal attenuation (SA) is the accumulation of all the ISA, and the ISA is the average SA of the whole diffusion system at each moment. However, the manner of calculating ISA is different. Unlike the use of the instantaneous propagator in the propagator method, the current method directly calculates ISA as A(K(t'),t'+dt')/A(K(t'),t'), where A(K(t'),t'+dt') and A(K(t'),t') are the SA. This modification makes the current method applicable to PFG FD as the instantaneous propagator may not be obtainable in FD. The ISA method was applied to study PFG SA including the effect of finite gradient pulse widths (FGPW) for free FD, restricted FD and the FD affected by a non-homogeneous gradient field. The SA expressions were successfully obtained for all three types of free FDs while other current methods still have difficulty in obtaining all of them. The results from this method agree with reported results such as that obtained by the effective phase shift diffusion equation (EPSDE) method. The M-Wright phase distribution approximation was also used to derive an SA expression for time FD as a comparison, which agrees with ISA method. Additionally, the continuous-time random walk (CTRW) simulation was performed to simulate the SA of PFG FD, and the simulation results agree with the analytical results. Particularly, the CTRW simulation results give good support to the analytical results including FGPW effect for free FD and restricted time FD based on a fractional derivative model where there have been no corresponding theoretical reports to date. The theoretical SA expressions including FGPW obtained here such as [Formula: see text] may be applied to analyze PFG FD in polymer or biological systems with improved accuracy where SGP approximation cannot be satisfied. The method can perhaps provide new insight to FD MRI and hence benefit the development of diffusion biomarkers based on fractional derivative.
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Affiliation(s)
- Guoxing Lin
- Carlson School of Chemistry and Biochemistry, Clark University, Worcester, MA 01610, United States.
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Ertas G, Onaygil C, Akin Y, Kaya H, Aribal E. Quantitative differentiation of breast lesions at 3T diffusion-weighted imaging (DWI) using the ratio of distributed diffusion coefficient (DDC). J Magn Reson Imaging 2016; 44:1633-1641. [DOI: 10.1002/jmri.25327] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Accepted: 05/16/2016] [Indexed: 12/19/2022] Open
Affiliation(s)
- Gokhan Ertas
- Department of Biomedical Engineering; Yeditepe University; Istanbul Turkey
| | - Can Onaygil
- Institute of Diagnostic and Interventional Radiology; Oberlausitz-Kliniken gGmbH; Bautzen Germany
| | - Yasin Akin
- Department of Radiology; Sanliurfa Mehmet Akif Inan Education and Research Hospital; Sanliurfa Turkey
| | - Handan Kaya
- Department of Pathology; Marmara University School of Medicine; Istanbul Turkey
| | - Erkin Aribal
- Department of Radiology; Marmara University School of Medicine; Istanbul Turkey
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Jiang DZ, Zhong Y, Zhou DY, Wu WQ, Wu GY, Quan H. Application of brain multi-b-value diffusion-weighted imaging (DWI) in adolescent orphans from AIDS families. Br J Radiol 2016; 89:20150732. [PMID: 26892165 DOI: 10.1259/bjr.20150732] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To evaluate the application value of multi-b-value diffusion-weighted imaging (DWI) with mono-exponential model and stretched-exponential model in the diagnosis of HIV-positive patients. METHODS Multi-b-value (0, 50, 150, 200, 400, 600, 800 s mm(-2)) DWI was performed in 23 adolescent orphans from AIDS families, including 15 HIV-positive subjects and 8 HIV-negative healthy subjects. Apparent diffusion coefficient (ADC) values were fitted by mono-exponential model; distribution diffusion coefficient (DDC) values and heterogeneity index (α) values were fitted by stretched-exponential model in bilateral basal ganglia, then non-parametric tests were performed. RESULTS The signal intensity attenuation in multi-b-value DWI could be well described by both mono-exponential model and stretched-exponential model. In the left basal ganglia, mean α-values in HIV-positive subjects (α = 0.848 ± 0.068) were significantly lower than that in healthy subjects (α = 0.923 ± 0.050, p = 0.013). There was no statistical difference of α-values between HIV-positive subjects and healthy control subjects in the right basal ganglia. Apart from these, there were also no statistical differences of DDC values or ADC values between two groups in bilateral basal ganglia (all p > 0.05). In bilateral basal ganglia, DDC values were positively correlated with ADC values in HIV-positive patients (right basal ganglia: r = 0.832, p = 0.000; left basal ganglia: r = 0.770, p = 0.001) as well as in healthy cases (right basal ganglia: r = 0.927, p = 0.001; left basal ganglia: r = 0.878, p = 0.004). Receiver operating characteristic (ROC) curve analysis yielded area under the ROC curve (Az) values of 0.817 (p = 0.014 < 0.05) in the left basal ganglia. The sensitivity and specificity were 62.5% and 86.7%, respectively. CONCLUSION Through the study of asymptomatic HIV-positive subjects when b < 1000 s mm(-2), we can see stretched-exponential model DWI can provide more information than mono-exponential model DWI. ADVANCES IN KNOWLEDGE Multi-b-value DWI was performed in subjects with HIV. DWI measurements could be neuroimaging biomarkers of cerebral injury in the course of HIV infection.
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Affiliation(s)
- Da-Zhen Jiang
- 1 Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, China
| | - Yang Zhong
- 1 Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, China
| | - Ding-Yi Zhou
- 1 Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, China
| | - Wei-Qing Wu
- 1 Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, China
| | - Guang-Yao Wu
- 2 Medical Imaging Department of the Zhongnan Hospital, Wuhan University, Wuhan, China
| | - Hong Quan
- 1 Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan, China
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Shen N, Zhao L, Jiang J, Jiang R, Su C, Zhang S, Tang X, Zhu W. Intravoxel incoherent motion diffusion-weighted imaging analysis of diffusion and microperfusion in grading gliomas and comparison with arterial spin labeling for evaluation of tumor perfusion. J Magn Reson Imaging 2016; 44:620-32. [PMID: 26880230 DOI: 10.1002/jmri.25191] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2015] [Accepted: 01/25/2016] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To determine the utility of intravoxel incoherent motion (IVIM) imaging in grading gliomas and compare IVIM perfusion metrics with arterial spin labeling (ASL)-derived cerebral blood flow (CBF). MATERIALS AND METHODS Fifty-two patients with pathologically confirmed gliomas underwent IVIM and ASL imaging at 3.0T. IVIM perfusion-related diffusivity (D*), perfusion fraction (f), product of f and D*(f×D*), true diffusivity (D), and apparent diffusion coefficient (ADC) were obtained to distinguish glioma grades. The CBF derived from pseudocontinuous ASL within the solid tumor was compared and correlated with IVIM perfusion metrics for grading of gliomas. Values were also normalized to the contralateral normal-appearing white matter. Receiver-operating characteristic was performed to determine diagnostic efficiency. The reliability was estimated with intraclass coefficient, coefficient of variance, and Bland-Altman plots. RESULTS IVIM perfusion metrics and CBF were significantly higher in the high-grade than the low-grade gliomas (P < 0.001), ADC and D were significantly lower in the high-grade than the low-grade gliomas (P < 0.001). f×D* differed significantly between grades II through IV (P < 0.05 for all). The other metrics showed significant difference between grade II and grade III (P < 0.05 for all). Area under the curve (AUC) was largest for f×D* in distinguishing high-grade from low-grade gliomas (AUC = 0.979, P < 0.001) and between grade II and grade III (AUC = 0.957, P < 0.001). f×D* improved diagnostic performance of CBF in grading gliomas and showed strong correlation with CBF (r = 0.696, P < 0.001). CONCLUSION IVIM-derived metrics are promising biomarkers in preoperative grading gliomas. IVIM imaging may be an additive method to ASL and ADC for evaluating tumor perfusion and diffusion. J. Magn. Reson. Imaging 2016;44:620-632.
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Affiliation(s)
- Nanxi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lingyun Zhao
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jingjing Jiang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rifeng Jiang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Changliang Su
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shun Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiangyu Tang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Lin G. An effective phase shift diffusion equation method for analysis of PFG normal and fractional diffusions. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2015; 259:232-240. [PMID: 26384777 DOI: 10.1016/j.jmr.2015.08.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Revised: 08/23/2015] [Accepted: 08/26/2015] [Indexed: 06/05/2023]
Abstract
Pulsed field gradient (PFG) diffusion measurement has a lot of applications in NMR and MRI. Its analysis relies on the ability to obtain the signal attenuation expressions, which can be obtained by averaging over the accumulating phase shift distribution (APSD). However, current theoretical models are not robust or require approximations to get the APSD. Here, a new formalism, an effective phase shift diffusion (EPSD) equation method is presented to calculate the APSD directly. This is based on the idea that the gradient pulse effect on the change of the APSD can be viewed as a diffusion process in the virtual phase space (VPS). The EPSD has a diffusion coefficient, K(β)(t)D rad(β)/s(α), where α is time derivative order and β is a space derivative order, respectively. The EPSD equations of VPS are built based on the diffusion equations of real space by replacing the diffusion coefficients and the coordinate system (from real space coordinate to virtual phase coordinate). Two different models, the fractal derivative model and the fractional derivative model from the literature were used to build the EPSD fractional diffusion equations. The APSD obtained from solving these EPSD equations were used to calculate the PFG signal attenuation. From the fractal derivative model the attenuation is exp(-γ(β)g(β)δ(β)Df1t(α)), a stretched exponential function (SEF) attenuation, while from the fractional derivative model the attenuation is Eα,1(-γ(β)g(β)δ(β)Df2t(α)), a Mittag-Leffler function (MLF) attenuation. The MLF attenuation can be reduced to SEF attenuation when α=1, and can be approximated as a SEF attenuation when the attenuation is small. Additionally, the effect of finite gradient pulse widths (FGPW) is calculated. From the fractal derivative model, the signal attenuation including FGPW effect is exp[ -Df1∫0(τ) K(β)(t)dt(α)]. The results obtained in this study are in good agreement with the results in literature. Several expressions that describe signal attenuation have not been reported and that can be of great importance for the PFG experiments. This EPSD equation method provides a new, simple path to calculate signal attenuation of PFG NMR experiments.
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Affiliation(s)
- Guoxing Lin
- Carlson School of Chemistry and Biochemistry, Clark University, Worcester, MA 01610, United States.
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Bai Y, Lin Y, Tian J, Shi D, Cheng J, Haacke EM, Hong X, Ma B, Zhou J, Wang M. Grading of Gliomas by Using Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MR Imaging and Diffusion Kurtosis MR Imaging. Radiology 2015; 278:496-504. [PMID: 26230975 DOI: 10.1148/radiol.2015142173] [Citation(s) in RCA: 167] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
PURPOSE To quantitatively compare the potential of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models and diffusion kurtosis imaging in the grading of gliomas. MATERIALS AND METHODS This study was approved by the local ethics committee, and written informed consent was obtained from all subjects. Both diffusion-weighted imaging and diffusion kurtosis imaging were performed in 69 patients with pathologically proven gliomas by using a 3-T magnetic resonance (MR) imaging unit. An isotropic apparent diffusion coefficient (ADC), true ADC, pseudo-ADC, and perfusion fraction were calculated from diffusion-weighted images by using a biexponential model. A water molecular diffusion heterogeneity index and distributed diffusion coefficient were calculated from diffusion-weighted images by using a stretched exponential model. Mean diffusivity, fractional anisotropy, and mean kurtosis were calculated from diffusion kurtosis images. All values were compared between high-grade and low-grade gliomas by using a Mann-Whitney U test. Receiver operating characteristic and Spearman rank correlation analysis were used for statistical evaluations. RESULTS ADC, true ADC, perfusion fraction, water molecular diffusion heterogeneity index, distributed diffusion coefficient, and mean diffusivity values were significantly lower in high-grade gliomas than in low-grade gliomas (U = 109, 56, 129, 6, 206, and 229, respectively; P < .05). Pseudo-ADC and mean kurtosis values were significantly higher in high-grade gliomas than in low-grade gliomas (U = 98 and 8, respectively; P < .05). Both water molecular diffusion heterogeneity index (area under the receiver operating characteristic curve [AUC] = 0.993) and mean kurtosis (AUC = 0.991) had significantly greater AUC values than ADC (AUC = 0.866), mean diffusivity (AUC = 0.722), and fractional anisotropy (AUC = 0.500) in the differentiation of low-grade and high-grade gliomas (P < .05). CONCLUSION Water molecular diffusion heterogeneity index and mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters.
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Affiliation(s)
- Yan Bai
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
| | - Yusong Lin
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
| | - Jie Tian
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
| | - Dapeng Shi
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
| | - Jingliang Cheng
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
| | - E Mark Haacke
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
| | - Xiaohua Hong
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
| | - Bo Ma
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
| | - Jinyuan Zhou
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
| | - Meiyun Wang
- From the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.)
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Nicolas R, Sibon I, Hiba B. Accuracies and Contrasts of Models of the Diffusion-Weighted-Dependent Attenuation of the MRI Signal at Intermediate b-values. MAGNETIC RESONANCE INSIGHTS 2015; 8:11-21. [PMID: 26106263 PMCID: PMC4468950 DOI: 10.4137/mri.s25301] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Revised: 04/23/2015] [Accepted: 04/26/2015] [Indexed: 11/24/2022]
Abstract
The diffusion-weighted-dependent attenuation of the MRI signal E(b) is extremely sensitive to microstructural features. The aim of this study was to determine which mathematical model of the E(b) signal most accurately describes it in the brain. The models compared were the monoexponential model, the stretched exponential model, the truncated cumulant expansion (TCE) model, the biexponential model, and the triexponential model. Acquisition was performed with nine b-values up to 2500 s/mm2 in 12 healthy volunteers. The goodness-of-fit was studied with F-tests and with the Akaike information criterion. Tissue contrasts were differentiated with a multiple comparison corrected nonparametric analysis of variance. F-test showed that the TCE model was better than the biexponential model in gray and white matter. Corrected Akaike information criterion showed that the TCE model has the best accuracy and produced the most reliable contrasts in white matter among all models studied. In conclusion, the TCE model was found to be the best model to infer the microstructural properties of brain tissue.
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Affiliation(s)
- Renaud Nicolas
- Centre de Résonance Magnétique des Systèmes Biologiques (RMSB), UMR 5536, CNRS-Université Bordeaux, Bordeaux Cedex, France. ; Aquitaine Institute for Cognitive and Integrative Neuroscience (INCIA), UMR 5287, CNRS-Université Bordeaux, Talence, France. ; Ecole Pratique des Hautes Etudes (EPHE), Laboratoire de Neurobiologie Intégrative et Adaptative, Bordeaux Cedex, France
| | - Igor Sibon
- Aquitaine Institute for Cognitive and Integrative Neuroscience (INCIA), UMR 5287, CNRS-Université Bordeaux, Talence, France. ; University Hospital (CHU) Bordeaux Pellegrin, NeuroVascular Unit, Bordeaux Cedex, France
| | - Bassem Hiba
- Centre de Résonance Magnétique des Systèmes Biologiques (RMSB), UMR 5536, CNRS-Université Bordeaux, Bordeaux Cedex, France. ; Aquitaine Institute for Cognitive and Integrative Neuroscience (INCIA), UMR 5287, CNRS-Université Bordeaux, Talence, France
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Abstract
Magnetic resonance imaging is a powerful, noninvasive imaging technique with exquisite sensitivity to soft tissue composition. Magnetic resonance imaging is primary tool for brain tumor diagnosis, evaluation of drug response assessment, and clinical monitoring of the patient during the course of their disease. The flexibility of magnetic resonance imaging pulse sequence design allows for a variety of image contrasts to be acquired, including information about magnetic resonance-specific tissue characteristics, molecular dynamics, microstructural organization, vascular composition, and biochemical status. The current review highlights recent advancements and novel approaches in MR characterization of brain tumors.
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Comparison of Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging and Arterial Spin Labeling MR Imaging in Gliomas. BIOMED RESEARCH INTERNATIONAL 2015; 2015:234245. [PMID: 25945328 PMCID: PMC4402183 DOI: 10.1155/2015/234245] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2014] [Revised: 03/14/2015] [Accepted: 03/21/2015] [Indexed: 11/18/2022]
Abstract
Gliomas grading is important for treatment plan; we aimed to investigate the application of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in gliomas grading, by comparing with the three-dimensional pseudocontinuous arterial spin labeling (3D pCASL). 24 patients (13 high grade gliomas and 11 low grade gliomas) underwent IVIM DWI and 3D pCASL imaging before operation; maps of fast diffusion coefficient (D∗), slow diffusion coefficient (D), fractional perfusion-related volume (f), and apparent diffusion coefficient (ADC) as well as cerebral blood flow (CBF) were calculated and then coregistered to generate the corresponding parameter values. We found CBF and D∗ were higher in the high grade gliomas, whereas ADC, D, and f were lower (all P < 0.05). In differentiating the high from low grade gliomas, the maximum areas under the curves (AUC) of D∗, CBF, and ADC were 0.857, 0.85, and 0.902, respectively. CBF was negatively correlated with f in tumor (r = −0.619, P = 0.001). ADC was positively correlated with D in both tumor and white matter (r = 0.887, P = 0.000 and r = 0.824, P = 0.000, resp.). There was no correlation between CBF and D∗ in both tumor and white matter (P > 0.05). IVIM DWI showed more efficiency than 3D pCASL but less validity than conventional DWI in differentiating the high from low grade gliomas.
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Liu X, Zhou L, Peng W, Wang H, Zhang Y. Comparison of stretched-Exponential and monoexponential model diffusion-Weighted imaging in prostate cancer and normal tissues. J Magn Reson Imaging 2015; 42:1078-85. [PMID: 25727776 DOI: 10.1002/jmri.24872] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2014] [Accepted: 02/04/2015] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND To compare stretched-exponential and monoexponential model diffusion-weighted imaging (DWI) in prostate cancer and normal tissues. METHODS Twenty-seven patients with prostate cancer underwent DWI exam using b-values of 0, 500, 1000, and 2000 s/mm(2) . The distributed diffusion coefficients (DDC) and α values of prostate cancer and normal tissues were obtained with stretched-exponential model and apparent diffusion coefficient (ADC) values using monoexponential model. The ADC, DDC (both in 10(-3) mm(2)/s), and α values (range, 0-1) were compared among different prostate tissues. The ADC and DDC were also compared and correlated in each tissue, and the standardized differences between DDC and ADC were compared among different tissues. RESULTS Data were obtained for 31 cancers, 36 normal peripheral zone (PZ) and 26 normal central gland (CG) tissues. The ADC (0.71 ± 0.12), DDC (0.60 ± 0.18), and α value (0.64 ± 0.05) of tumor were all significantly lower than those of the normal PZ (1.41 ± 0.22, 1.47 ± 0.20, and 0.85 ± 0.09) and CG (1.25 ± 0.14, 1.32 ± 0.13, and 0.82 ± 0.06) (all P < 0.05). ADC was significantly higher than DDC in cancer, but lower than DDC in the PZ and CG (all P < 0.05). The ADC and DDC were strongly correlated (R(2) = 0.99, 0.98, 0.99, respectively, all P < 0.05) in all the tissue, and standardized difference between ADC and DDC of cancer was slight but significantly higher than that in normal tissue. CONCLUSION The stretched-exponential model DWI provides more parameters for distinguishing prostate cancer and normal tissue and reveals slight differences between DDC and ADC values.
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Affiliation(s)
- Xiaohang Liu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liangping Zhou
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Weijun Peng
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - He Wang
- Global Applied Science Laboratory, GE Healthcare, Shanghai, China
| | - Yong Zhang
- Global Applied Science Laboratory, GE Healthcare, Shanghai, China
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Lai V, Lee VHF, Lam KO, Sze HCK, Chan Q, Khong PL. Intravoxel water diffusion heterogeneity MR imaging of nasopharyngeal carcinoma using stretched exponential diffusion model. Eur Radiol 2014; 25:1708-13. [DOI: 10.1007/s00330-014-3535-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Revised: 09/28/2014] [Accepted: 11/20/2014] [Indexed: 11/30/2022]
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Bisdas S, Koh TS, Roder C, Braun C, Schittenhelm J, Ernemann U, Klose U. Intravoxel incoherent motion diffusion-weighted MR imaging of gliomas: feasibility of the method and initial results. Neuroradiology 2013; 55:1189-96. [PMID: 23852430 DOI: 10.1007/s00234-013-1229-7] [Citation(s) in RCA: 82] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2013] [Accepted: 06/26/2013] [Indexed: 11/26/2022]
Abstract
INTRODUCTION The purpose of this study was to evaluate the feasibility of intravoxel incoherent motion (IVIM) imaging and its value in differentiating the histologic grade among human gliomas. METHODS The IVIM model generated parametric images for apparent diffusion coefficient ADC, slow diffusion coefficient D (or D slow), fast diffusion coefficient D* (or D fast), and fractional perfusion-related volume f in 22 patients with gliomas (WHO grade II-IV) using monopolar Stejskal-Tanner diffusion-weighted imaging (DWI) scheme and 14 b values ranging from 0 s/mm2 to a maximum of 1,300 s/mm2. A region-of-interest analysis on the tumor as well as in the white matter was conducted. The parameter values were tested for significant differences. The repeatability of the measurements was tested by coefficient of variation and Bland-Altman plots. RESULTS D, D*, and f in the high-grade gliomas demonstrated significant differences compared to the healthy white matter. D* and f showed a significant difference between low- and high-grade gliomas. D tended to be slightly lower in the WHO grade II compared to WHO grade III-IV tumors. f and D* demonstrated higher coefficients of variation than the ADC and D in tumor. The Bland-Altman plots demonstrated satisfactory results without any outliers outside the mean ± 1.96 standard deviation. CONCLUSION The IVIM-fitted post-processing of DWI-signal decay in human gliomas could show significantly different values of fractional perfusion-related volume and fast diffusion coefficient between low- and high-grade tumors, which might enable a noninvasive WHO grading in vivo.
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Affiliation(s)
- Sotirios Bisdas
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls University, Hoppe Seyler Str. 3, 72076, Tübingen, Germany,
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Kristoffersen A. Optimized quantification of diffusional non-gaussianity in the human brain. J Magn Reson Imaging 2013; 38:1434-44. [PMID: 23559256 DOI: 10.1002/jmri.24102] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2012] [Accepted: 02/11/2013] [Indexed: 11/07/2022] Open
Affiliation(s)
- Anders Kristoffersen
- Clinic of Radiology and Nuclear Medicine; St. Olav's Hospital HF; Trondheim Norway
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Diffusion-weighted magnetic resonance imaging of the prostate: improved robustness with stretched exponential modeling. J Comput Assist Tomogr 2013. [PMID: 23192207 DOI: 10.1097/rct.0b013e31826bdbbd] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE This study aimed to compare the intraclass correlation coefficients of parameters estimated with stretched exponential and biexponential diffusion models of in vivo diffusion-weighted magnetic resonance imaging (MRI) of the prostate. METHODS After the institutional review board issued a waiver of informed consent for this Health Insurance Portability and Accountability Act-compliant study, 25 patients with biopsy-proven prostate cancer underwent 3T endorectal MRI and diffusion-weighted MRI of the prostate at 10 b values (0, 45, 75, 105, 150, 225, 300, 600, 900, and 1200 s/mm). The full set of b values was collected twice within a single acquisition. Intraclass correlation coefficients were calculated for intra-acquisition variability. From the biexponential model, the quantitative parameters diffusion coefficient (D), perfusion coefficient (D*), and perfusion fraction (f) were estimated. From the stretched exponential model, the quantitative parameters Kohlrausch decay constant (DK) and alpha (α) were estimated. RESULTS For the 25 patient data sets, the average intraclass correlation coefficients for DK and α were 95.8%, and 64.1%, respectively, whereas those for D, D*, and f were 84.4%, 25.3%, and 41.3%, respectively. CONCLUSIONS The stretched exponential diffusion model captures the nonlinear effects of intravoxel incoherent motion in the prostate. The parameters derived from this model are more reliable and reproducible than the parameters derived from the standard, widely used biexponential diffusion/perfusion model.
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Hall MG, Barrick TR. Two-step anomalous diffusion tensor imaging. NMR IN BIOMEDICINE 2012; 25:286-294. [PMID: 21812048 DOI: 10.1002/nbm.1747] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2010] [Revised: 04/08/2011] [Accepted: 04/11/2011] [Indexed: 05/31/2023]
Abstract
We extend the formalism of anomalous diffusion imaging to include directional anisotropy of fitted parameters. The resulting technique is termed anomalous diffusion tensor imaging (aDTI), and allows the directional properties of the distributed diffusion coefficient (α) and the anomalous diffusion exponent, (γ) to be analysed using the same analytical techniques as regular diffusion tensor imaging (DTI). Together, these parameters quantify the rate of diffusion (α) and the complexity of the diffusion environment (γ). We generated tensor images for the anomalous exponent tensor (Γ) and distributed diffusivity tensor (A) from in vivo human brain data and present images of eigenvalues, eigenvectors, Trace/3 (Tr), fractional anisotropy (FA) and tensor shape measures. In white matter, A is found to have a median Tr = 0.56 × 10(- 3) mm(2) s(- 1), FA = 0.58 and Γ Tr = 0.69, FA = 0.13. We observed that white matter shows a similar anisotropic geometry for the distributed diffusion tensor as for the regular diffusion tensor, whereas the anomalous exponent tensor exhibits a different shape characteristic which may be informative of tissue microstructure.
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Affiliation(s)
- Matt G Hall
- Centre for Medical Image Computing, Dept of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK
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Magin RL, Akpa BS, Neuberger T, Webb AG. Fractional Order Analysis of Sephadex Gel Structures: NMR Measurements Reflecting Anomalous Diffusion. COMMUNICATIONS IN NONLINEAR SCIENCE & NUMERICAL SIMULATION 2011; 16:4581-4587. [PMID: 21804746 PMCID: PMC3144506 DOI: 10.1016/j.cnsns.2011.04.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
We report the appearance of anomalous water diffusion in hydrophilic Sephadex gels observed using pulse field gradient (PFG) nuclear magnetic resonance (NMR). The NMR diffusion data was collected using a Varian 14.1 Tesla imaging system with a home-built RF saddle coil. A fractional order analysis of the data was used to characterize heterogeneity in the gels for the dynamics of water diffusion in this restricted environment. Several recent studies of anomalous diffusion have used the stretched exponential function to model the decay of the NMR signal, i.e., exp[-(bD)(α)], where D is the apparent diffusion constant, b is determined the experimental conditions (gradient pulse separation, durations and strength), and α is a measure of structural complexity. In this work, we consider a different case where the spatial Laplacian in the Bloch-Torrey equation is generalized to a fractional order model of diffusivity via a complexity parameter, β, a space constant, μ, and a diffusion coefficient, D. This treatment reverts to the classical result for the integer order case. The fractional order decay model was fit to the diffusion-weighted signal attenuation for a range of b-values (0 < b < 4,000 s-mm(-2)). Throughout this range of b values, the parameters β, μ and D, were found to correlate with the porosity and tortuosity of the gel structure.
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Affiliation(s)
- Richard L. Magin
- Department of Bioengineering, University of Illinois at Chicago, Chicago IL 60607 USA
| | - Belinda S. Akpa
- Department of Chemical Engineering, University of Illinois at Chicago, Chicago IL 60607 USA
| | - Thomas Neuberger
- Center for Magnetic Resonance Imaging, Pennsylvania State University, University Park PA 16802 USA
| | - Andrew G. Webb
- C. J. Gorter High Field Magnetic Resonance Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
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Kristoffersen A. Estimating non-gaussian diffusion model parameters in the presence of physiological noise and rician signal bias. J Magn Reson Imaging 2011; 35:181-9. [PMID: 21972173 DOI: 10.1002/jmri.22826] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2011] [Accepted: 09/02/2011] [Indexed: 11/07/2022] Open
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De Santis S, Gabrielli A, Palombo M, Maraviglia B, Capuani S. Non-Gaussian diffusion imaging: a brief practical review. Magn Reson Imaging 2011; 29:1410-6. [PMID: 21601404 DOI: 10.1016/j.mri.2011.04.006] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2010] [Revised: 02/15/2011] [Accepted: 04/03/2011] [Indexed: 11/30/2022]
Abstract
The departure from purely mono-exponential decay of the signal, as observed from brain tissue following a diffusion-sensitized sequence, has prompted the search for alternative models to characterize these unconventional water diffusion dynamics. Several approaches have been proposed in the last few years. While multi-exponential models have been applied to characterize brain tissue, several unresolved controversies about the interpretations of the results have motivated the search for alternative models that do not rely on the Gaussian diffusion hypothesis. In this brief review, diffusional kurtosis imaging (DKI) and anomalous diffusion imaging (ADI) techniques are addressed and compared with diffusion tensor imaging. Theoretical and experimental issues are briefly described to allow readers to understand similarities, differences and limitations of these two non-Gaussian models. However, since the ultimate goal is to improve specificity, sensitivity and spatial localization of diffusion MRI for the detection of brain diseases, special attention will be paid on the clinical feasibility of the proposed techniques as well as on the context of brain pathology investigations.
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Affiliation(s)
- Silvia De Santis
- Physics Department, Sapienza University of Rome, P.le A. Moro 5, 00185 Rome, Italy.
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Kristoffersen A. Statistical assessment of non-Gaussian diffusion models. Magn Reson Med 2011; 66:1639-48. [DOI: 10.1002/mrm.22960] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2010] [Revised: 03/16/2011] [Accepted: 03/20/2011] [Indexed: 12/25/2022]
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Prah DE, Paulson ES, Nencka AS, Schmainda KM. A simple method for rectified noise floor suppression: Phase-corrected real data reconstruction with application to diffusion-weighted imaging. Magn Reson Med 2011; 64:418-29. [PMID: 20665786 DOI: 10.1002/mrm.22407] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Diffusion-weighted MRI is an intrinsically low signal-to-noise ratio application due to the application of diffusion-weighting gradients and the consequent longer echo times. The signal-to-noise ratio worsens with increasing image resolution and diffusion imaging methods that use multiple and higher b-values. At low signal-to-noise ratios, standard magnitude reconstructed diffusion-weighted images are confounded by the existence of a rectified noise floor, producing poor estimates of diffusion metrics. Herein, we present a simple method of rectified noise floor suppression that involves phase correction of the real data. This approach was evaluated for diffusion-weighted imaging data, obtained from ethanol and water phantoms and the brain of a healthy volunteer. The parameter fits from monoexponential, biexponential, and stretched-exponential diffusion models were computed using phase-corrected real data and magnitude data. The results demonstrate that this newly developed simple approach of using phase-corrected real images acts to reduce or even suppress the confounding effects of a rectified noise floor, thereby producing more accurate estimates of diffusion parameters.
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Affiliation(s)
- Douglas E Prah
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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