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Jeanne B Ackman - One of the best experts on this subject based on the ideXlab platform.
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reply to quantitative mri of the thymus chemical shift ratio signal intensity index and apparent diffusion Coefficient Value
American Journal of Roentgenology, 2016Co-Authors: Jeanne B AckmanAbstract:AJR 2016; 206:W98 0361–803X/16/2066–W98 © American Roentgen Ray Society Reply to “Quantitative MRI of the Thymus: Chemical-Shift Ratio, Signal Intensity Index, and Apparent Diffusion Coefficient Value” My coauthors and I are grateful to Dr. Karabulut for his interest in our Structured Review article titled “Pitfalls in the Imaging and Interpretation of Benign Thymic Lesions: How Thymic MRI Can Help” [1] and his excellent comments. We agree with most of the comments and would like to add the following. First, Dr. Karabulut is correct that the initially electronically published article very unfortunately had a mistyped equation for the calculation of the chemical-shift ratio (CSR), with the denominators exchanged. This error was rapidly discovered and corrected within a few days, so the CSR equation is now correctly displayed as follows:
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Reply to “Quantitative MRI of the Thymus: Chemical-Shift Ratio, Signal Intensity Index, and Apparent Diffusion Coefficient Value”
American Journal of Roentgenology, 2016Co-Authors: Jeanne B AckmanAbstract:AJR 2016; 206:W98 0361–803X/16/2066–W98 © American Roentgen Ray Society Reply to “Quantitative MRI of the Thymus: Chemical-Shift Ratio, Signal Intensity Index, and Apparent Diffusion Coefficient Value” My coauthors and I are grateful to Dr. Karabulut for his interest in our Structured Review article titled “Pitfalls in the Imaging and Interpretation of Benign Thymic Lesions: How Thymic MRI Can Help” [1] and his excellent comments. We agree with most of the comments and would like to add the following. First, Dr. Karabulut is correct that the initially electronically published article very unfortunately had a mistyped equation for the calculation of the chemical-shift ratio (CSR), with the denominators exchanged. This error was rapidly discovered and corrected within a few days, so the CSR equation is now correctly displayed as follows:
Angela Lignelli - One of the best experts on this subject based on the ideXlab platform.
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predicting glioblastoma recurrence by early changes in the apparent diffusion Coefficient Value and signal intensity on flair images
American Journal of Roentgenology, 2017Co-Authors: Peter Chang, Daniel S Chow, Peter H Yang, Christopher G Filippi, Angela LignelliAbstract:OBJECTIVE. Recurrence of glioblastoma multiforme (GBM) arises from areas of microscopic tumor infiltration that have yet to disrupt the blood-brain barrier. We hypothesize that these microscopic foci of invasion cause subtle variations in the apparent diffusion Coefficient (ADC) and FLAIR signal detectable with the use of computational big-data modeling. MATERIALS AND METHODS. Twenty-six patients with native GBM were studied immediately after undergoing gross total tumor resection. Within the peritumoral region, areas of future GBM recurrence were identified through coregistration of follow-up MRI examinations. The likelihood of tumor recurrence at each individual voxel was assessed as a function of signal intensity on ADC maps and FLAIR images. Both single and combined multivariable logistic regression models were created. RESULTS. A total of 419,473 voxels of data (105,477 voxels of data within tumor recurrence and 313,996 voxels of data on surrounding peritumoral edema) were analyzed. For future areas ...
Hua Chen - One of the best experts on this subject based on the ideXlab platform.
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Influence of Surface Roughness and Temperature on Wheel / Rail Adhesion in Wet Conditions
Quarterly Report of RTRI, 2015Co-Authors: Hiraku Tanimoto, Hua ChenAbstract:A series of experiments on the wheel/rail traction Coefficient were carried out with a twin disc rolling contact machine by varying the surface roughness and the temperature of the wheel and rail discs, and using sprayed water, for the purpose of obtaining fundamental knowledge about how to prevent wheels slipping during driving and wheel sliding during braking. The results showed that the maximum traction Coefficient Value occurred in the range of 1 to 3 μm of the combined roughness under any temperature conditions, and its Value increased to 0.4 with increases in temperature.
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influence of surface roughness and temperature on wheel rail adhesion in wet conditions
Quarterly Report of Rtri, 2015Co-Authors: Hiraku Tanimoto, Hua ChenAbstract:A series of experiments on the wheel/rail traction Coefficient were carried out with a twin disc rolling contact machine by varying the surface roughness and the temperature of the wheel and rail discs, and using sprayed water, for the purpose of obtaining fundamental knowledge about how to prevent wheels slipping during driving and wheel sliding during braking. The results showed that the maximum traction Coefficient Value occurred in the range of 1 to 3 μm of the combined roughness under any temperature conditions, and its Value increased to 0.4 with increases in temperature.
Keigo Endo - One of the best experts on this subject based on the ideXlab platform.
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diagnostic utility of diffusion weighted mr imaging and apparent diffusion Coefficient Value for the diagnosis of adrenal tumors
Journal of Magnetic Resonance Imaging, 2009Co-Authors: Yoshito Tsushima, Ayako Takahashitaketomi, Keigo EndoAbstract:Purpose To determine the utility of diffusion-weighted MR imaging (DWI) for the diagnosis of adrenal tumors. Materials and Methods Forty-two patients (24 men and 18 women; age, 61.5 ± 12.7 years old; range, 34–86 years) with 43 adrenal tumors (11 functioning cortical adenomas, 20 nonfunctioning cortical adenomas, 7 metastatic tumors, and 5 pheochromocytomas) were retrospectively investigated. DWIs were obtained by single-shot spin-echo type echo-planar imaging sequence (1.5 Tesla [T]; TR = 8000 ms, TE = 72, b-factor = 0 and 1000 s/mm2), and apparent diffusion Coefficient (ADC) Value was calculated. Chemical shift images were obtained by gradient echo sequence (TR = 161, TE = 2.38 [out-of-phase, OP] and 4.76 [in-phase, IP], FA = 60), and the signal intensity index (SII; [IP-OP]/IP *100%) was calculated. Results There was no difference in ADC Values between adenomas (1.09 ± 0.29*10−3 mm2/s; range, 0.52–1.64) and metastatic tumors (0.85 ± 0.26*10−3; 0.51–1.23; p = 0.14). Pheochromocytomas showed the higher mean ADC Value (1.59 ± 0.34*10−3; 1.04–1.96) compared with those of adenomas or metastatic tumors (P < 0.05 and P < 0.005, respectively). The mean SII of adenomas (62.1 ± 17.9%; 14.5–88.4) was significantly higher than those of pheochromocytomas (4.0 ± 10.0%; −19.6–3.3; P < 0.005) or metastatic tumors (−1.5 ± 11.7%; −18.3–8.2; P < 0.01). There was no correlation between ADC Values and SII. Conclusion Although pheochromocytomas showed higher ADC Values, we did not find that ADC Value had diagnostic utility for differentiating adenomas and metastatic tumors. J. Magn. Reson. Imaging 2009;29:112–117. © 2008 Wiley-Liss, Inc.
Harriet C Thoeny - One of the best experts on this subject based on the ideXlab platform.
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diffusion weighted imaging of the parotid gland influence of the choice of b Values on the apparent diffusion Coefficient Value
Journal of Magnetic Resonance Imaging, 2004Co-Authors: Harriet C Thoeny, Frederik De Keyzer, Chris Boesch, Robert HermansAbstract:PURPOSE: To determine how the ADC Value of parotid glands is influenced by the choice of b-Values. MATERIALS AND METHODS: In eight healthy volunteers, diffusion-weighted echo-planar imaging (DW-EPI) was performed on a 1.5 T system, with b-Values (in seconds/mm2) of 0, 50, 100, 150, 200, 250, 300, 500, 750, and 1000. ADC Values were calculated by two alternative methods (exponential vs. logarithmic fit) from five different sets of b-Values: (A) all b-Values; (B) b=0, 50, and 100; (C) b=0 and 750; (D) b=0, 500, and 1000; and (E) b=500, 750, and 1000. RESULTS: The mean ADC Values for the different settings were (in 10(-3) mm2/second, exponential fit): (A) 0.732+/-0.019, (B) 2.074+/-0.084, (C) 0.947+/-0.020, (D) 0.890+/-0.023, and (E) 0.581+/-0.021. ADC Values were significantly (P <0.001) different for all pairwise comparisons of settings (A-E) of b-Values, except for A vs. D (P=0.172) and C vs. D (P=0.380). The ADC(B) was significantly higher than ADC(C) or ADC(D), which was significantly higher than ADC(E). ADC Values from exponential vs. logarithmic fit (P=0.542), as well as left vs. right parotid gland (P=0.962), were indistinguishable. CONCLUSION: The ADC Values calculated from low b-Value settings were significantly higher than those calculated from high b-Value settings. These results suggest that not only true diffusion but also perfusion and saliva flow may contribute to the ADC.