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Su Y, Cheng R, Guo J, Zhang M, Wang J, Ji H, Wang C, Hao L, He Y, Xu C. Differentiation of glioma and solitary brain metastasis: a multi-parameter magnetic resonance imaging study using histogram analysis. BMC Cancer 2024; 24:805. [PMID: 38969990 PMCID: PMC11225204 DOI: 10.1186/s12885-024-12571-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 06/27/2024] [Indexed: 07/07/2024] Open
Abstract
BACKGROUND Differentiation of glioma and solitary brain metastasis (SBM), which requires biopsy or multi-disciplinary diagnosis, remains sophisticated clinically. Histogram analysis of MR diffusion or molecular imaging hasn't been fully investigated for the differentiation and may have the potential to improve it. METHODS A total of 65 patients with newly diagnosed glioma or metastases were enrolled. All patients underwent DWI, IVIM, and APTW, as well as the T1W, T2W, T2FLAIR, and contrast-enhanced T1W imaging. The histogram features of apparent diffusion coefficient (ADC) from DWI, slow diffusion coefficient (Dslow), perfusion fraction (frac), fast diffusion coefficient (Dfast) from IVIM, and MTRasym@3.5ppm from APTWI were extracted from the tumor parenchyma and compared between glioma and SBM. Parameters with significant differences were analyzed with the logistics regression and receiver operator curves to explore the optimal model and compare the differentiation performance. RESULTS Higher ADCkurtosis (P = 0.022), frackurtosis (P<0.001),and fracskewness (P<0.001) were found for glioma, while higher (MTRasym@3.5ppm)10 (P = 0.045), frac10 (P<0.001),frac90 (P = 0.001), fracmean (P<0.001), and fracentropy (P<0.001) were observed for SBM. frackurtosis (OR = 0.431, 95%CI 0.256-0.723, P = 0.002) was independent factor for SBM differentiation. The model combining (MTRasym@3.5ppm)10, frac10, and frackurtosis showed an AUC of 0.857 (sensitivity: 0.857, specificity: 0.750), while the model combined with frac10 and frackurtosis had an AUC of 0.824 (sensitivity: 0.952, specificity: 0.591). There was no statistically significant difference between AUCs from the two models. (Z = -1.14, P = 0.25). CONCLUSIONS The frac10 and frackurtosis in enhanced tumor region could be used to differentiate glioma and SBM and (MTRasym@3.5ppm)10 helps improving the differentiation specificity.
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Affiliation(s)
- Yifei Su
- The Neurosurgery Department of Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, Shanxi, 030012, PR China
- Provincial Key Cultivation Laboratory of Intelligent Big Data Digital Neurosurgery of Shanxi Province, Taiyuan, Shanxi, PR China
| | - Rui Cheng
- The Neurosurgery Department of Shanxi Provincial People's Hospital, Taiyuan, Shanxi, 030012, PR China
- Provincial Key Cultivation Laboratory of Intelligent Big Data Digital Neurosurgery of Shanxi Province, Taiyuan, Shanxi, PR China
| | | | | | - Junhao Wang
- The Neurosurgery Department of Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, Shanxi, 030012, PR China
- Provincial Key Cultivation Laboratory of Intelligent Big Data Digital Neurosurgery of Shanxi Province, Taiyuan, Shanxi, PR China
| | - Hongming Ji
- The Neurosurgery Department of Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, Shanxi, 030012, PR China.
- Provincial Key Cultivation Laboratory of Intelligent Big Data Digital Neurosurgery of Shanxi Province, Taiyuan, Shanxi, PR China.
| | - Chunhong Wang
- The Neurosurgery Department of Shanxi Provincial People's Hospital, Taiyuan, Shanxi, 030012, PR China
- Provincial Key Cultivation Laboratory of Intelligent Big Data Digital Neurosurgery of Shanxi Province, Taiyuan, Shanxi, PR China
| | - Liangliang Hao
- The Radiology Department of Shanxi Provincial People's Hospital, Taiyuan, Shanxi, 030012, PR China
| | - Yexin He
- The Radiology Department of Shanxi Provincial People's Hospital, Taiyuan, Shanxi, 030012, PR China
| | - Cheng Xu
- The Radiology Department of Shanxi Provincial People's Hospital, Taiyuan, Shanxi, 030012, PR China.
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Crossed cerebellar diaschisis after acute ischemic stroke detected by intravoxel incoherent motion magnetic resonance imaging. Neurol Sci 2021; 43:1135-1141. [PMID: 34213697 DOI: 10.1007/s10072-021-05425-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 06/21/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE To study the value of 3.0 T magnetic resonance imaging with intravoxel incoherent motion (IVIM) in the diagnosis of the crossed cerebellar diaschisis (CCD) after the unilateral supratentorial acute ischemic stroke. METHODS Seventy-four patients with acute ischemic stroke who underwent intravoxel incoherent motion (IVIM), arterial spin labeling (ASL), and conventional magnetic resonance imaging (MRI) scanning were enrolled. Intravoxel incoherent motion-derived perfusion-related parameters including fast diffusion coefficient (D*), slow diffusion coefficient (D), vascular volume fraction (f), and arterial spin-labeling-derived cerebral blood flow (CBF) of bilateral cerebellum were measured. RESULTS In the CCD-positive group, D*, D, and CBF values of the contralateral cerebellum decreased compared with those of the ipsilesional cerebellum (P < 0.05), whereas f significantly increased (P < 0.05). A positive correlation was detected between the slow diffusion coefficient-based asymmetry index (AI-D) and the cerebral blood flow-based asymmetry index (AI-CBF) (r = 0.515, P < 0.01), whereas the vascular volume fraction-based asymmetry index (AI-f) had a negative correlation with the cerebral blood flow-based asymmetry index (AI-CBF) (r = - 0.485, P < 0.01). Furthermore, the area under the receiver operating characteristic (ROC) curve value of AI-D and AI-f was 0.81 and 0.76, respectively. CONCLUSIONS The IVIM is feasible for the detection of CCD. This technique might provide opportunities to further investigate the pathophysiology of CCD.
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Huang HM. Reliable estimation of brain intravoxel incoherent motion parameters using denoised diffusion-weighted MRI. NMR IN BIOMEDICINE 2020; 33:e4249. [PMID: 31922646 DOI: 10.1002/nbm.4249] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 12/03/2019] [Accepted: 12/04/2019] [Indexed: 06/10/2023]
Abstract
In this study, we evaluate whether diffusion-weighted magnetic resonance imaging (DW-MRI) data after denoising can provide a reliable estimation of brain intravoxel incoherent motion (IVIM) perfusion parameters. Brain DW-MRI was performed in five healthy volunteers on a 3 T clinical scanner with 12 different b-values ranging from 0 to 1000 s/mm2 . DW-MRI data denoised using the proposed method were fitted with a biexponential model to extract perfusion fraction (PF), diffusion coefficient (D) and pseudo-diffusion coefficient (D*). To further evaluate the accuracy and precision of parameter estimation, IVIM parametric images obtained from one volunteer were used to resimulate the DW-MRI data using the biexponential model with the same b-values. Rician noise was added to generate DW-MRI data with various signal-to-noise ratio (SNR) levels. The experimental results showed that the denoised DW-MRI data yielded precise estimates for all IVIM parameters. We also found that IVIM parameters were significantly different between gray matter and white matter (P < 0.05), except for D* (P = 0.6). Our simulation results show that the proposed image denoising method displays good performance in estimating IVIM parameters (both bias and coefficient of variation were <12% for PF, D and D*) in the presence of different levels of simulated Rician noise (SNRb=0 = 20-40). Simulations and experiments show that brain DW-MRI data after denoising can provide a reliable estimation of IVIM parameters.
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Affiliation(s)
- Hsuan-Ming Huang
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei City, Taiwan
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Lévy S, Rapacchi S, Massire A, Troalen T, Feiweier T, Guye M, Callot V. Intravoxel Incoherent Motion at 7 Tesla to quantify human spinal cord perfusion: limitations and promises. Magn Reson Med 2020; 84:1198-1217. [DOI: 10.1002/mrm.28195] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 12/16/2019] [Accepted: 01/10/2020] [Indexed: 12/15/2022]
Affiliation(s)
- Simon Lévy
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
- Aix‐Marseille Univ, IFSTTAR, LBA Marseille France
- iLab‐Spine International Associated Laboratory Marseille‐Montreal France‐Canada
| | - Stanislas Rapacchi
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
| | - Aurélien Massire
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
- iLab‐Spine International Associated Laboratory Marseille‐Montreal France‐Canada
| | | | | | - Maxime Guye
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
| | - Virginie Callot
- Aix‐Marseille Univ, CNRS, CRMBM Marseille France
- APHM, Hopital Universitaire Timone, CEMEREM Marseille France
- iLab‐Spine International Associated Laboratory Marseille‐Montreal France‐Canada
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Chabert S, Verdu J, Huerta G, Montalba C, Cox P, Riveros R, Uribe S, Salas R, Veloz A. Impact of b-Value Sampling Scheme on Brain IVIM Parameter Estimation in Healthy Subjects. Magn Reson Med Sci 2019; 19:216-226. [PMID: 31611542 PMCID: PMC7553810 DOI: 10.2463/mrms.mp.2019-0061] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Purpose: Intravoxel incoherent motion (IVIM) analysis has attracted the interest of the clinical community due to its close relationship with microperfusion. Nevertheless, there is no clear reference protocol for its implementation; one of the questions being which b-value distribution to use. This study aimed to stress the importance of the sampling scheme and to show that an optimized b-value distribution decreases the variance associated with IVIM parameters in the brain with respect to a regular distribution in healthy volunteers. Methods: Ten volunteers were included in this study; images were acquired on a 1.5T MR scanner. Two distributions of 16 b-values were used: one considered ‘regular’ due to its close association with that used in other studies, and the other considered ‘optimized’ according to previous studies. IVIM parameters were adjusted according to the bi-exponential model, using two-step method. Analysis was undertaken in ROI defined using in the Automated Anatomical Labeling atlas, and parameters distributions were compared in a total of 832 ROI. Results: Maps with fewer speckles were obtained with the ‘optimized’ distribution. Coefficients of variation did not change significantly for the estimation of the diffusion coefficient D but decreased by approximately 39% for the pseudo-diffusion coefficient estimation and by 21% for the perfusion fraction. Distributions of adjusted parameters were found significantly different in 50% of the cases for the perfusion fraction, in 80% of the cases for the pseudo-diffusion coefficient and 17% of the cases for the diffusion coefficient. Observations across brain areas show that the range of average values for IVIM parameters is smaller in the ‘optimized’ case. Conclusion: Using an optimized distribution, data are sampled in a way that the IVIM signal decay is better described and less variance is obtained in the fitted parameters. The increased precision gained could help to detect small variations in IVIM parameters.
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Affiliation(s)
- Stéren Chabert
- CINGS Centro de Investigación y Desarrollo de Ingeniería para la Salud, Universidad de Valparaíso.,Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso.,Millennium Nucleus for Cardiovascular Magnetic Resonance
| | - Jorge Verdu
- Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso.,Universidad Politécnica de Valencia
| | - Gamaliel Huerta
- Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso
| | - Cristian Montalba
- Center for Biomedical Imaging, Pontificia Universidad Católica de Chile
| | - Pablo Cox
- Servicio de Imagenología, Hospital Carlos van Buren
| | - Rodrigo Riveros
- Servicio de Imagenología, Hospital Carlos van Buren.,Facultad de Medicina, Universidad de Valparaíso
| | - Sergio Uribe
- Millennium Nucleus for Cardiovascular Magnetic Resonance.,Center for Biomedical Imaging, Pontificia Universidad Católica de Chile.,Radiology Department, Pontificia Universidad Católica de Chile
| | - Rodrigo Salas
- CINGS Centro de Investigación y Desarrollo de Ingeniería para la Salud, Universidad de Valparaíso.,Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso
| | - Alejandro Veloz
- CINGS Centro de Investigación y Desarrollo de Ingeniería para la Salud, Universidad de Valparaíso.,Escuela de Ingenieria Civil Biomedica, Universidad de Valparaíso
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Maehara M. Development of voxel-based optimization diffusion kurtosis imaging (DKI) and comparison with conventional DKI. Radiol Phys Technol 2019; 12:290-298. [PMID: 31278593 DOI: 10.1007/s12194-019-00523-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 06/25/2019] [Accepted: 06/26/2019] [Indexed: 11/29/2022]
Abstract
The aims of this study were to implement voxel-based optimization diffusion kurtosis imaging (DKI) and evaluate the accuracy of the method for the analysis of diffusion imaging data in comparison with conventional DKI. Conventional DKI and voxel-based optimization DKI were tested on a phantom and a human in a 1.5 T whole-body scanner. The differences in the diffusion coefficient (D) and diffusion kurtosis (K) values were analyzed using the Mann-Whitney U test, and the Holm correction was applied to the statistical analyses. In the phantom study, the D value resulting from voxel-based optimization DKI was significantly lower than those from conventional DKI in water and agarose solutions at concentrations of 50 and 100 g/L (all p < 0.01). Moreover, the K value was significantly lower in the water and agarose solutions at concentrations of 50, 100, and 200 g/L (all p < 0.01). In the human study, the D value resulting from voxel-based optimization DKI was significantly lower than that of conventional DKI in both white matter (WM), and gray matter (GM) (all p < 0.01). Moreover, the K value was significantly lower in cerebrospinal fluid, WM, and GM (all p < 0.01). To correctly measure the DKI, the optimized b values for each voxel must be used. Voxel-based optimization DKI is a method that optimizes the b values for each voxel. It appears that voxel-based optimization DKI improves the accuracy of the K value for biological tissues.
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Affiliation(s)
- Masanori Maehara
- Department of Radiology, Nihon University School of Dentistry at Matsudo, 2-870-1, Sakae-nishi, Matsudo, 271-8587, Chiba, Japan.
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