• Investigative Magnetic Resonance Imaging
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• v.12 no.1
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• pp.8-19
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• 2008

Purpose : To investigate the 3-bond and spatial connectivity of human brain metabolites by scalar coupling and dipolar nuclear Overhauser effect/enhancement (NOE) interaction through 2D- correlation spectroscopy (COSY) and 2D- NOE spectroscopy (NOESY) techniques. Materials and Methods : All 2D experiments were performed on Bruker Avance 500 (11.8 T) with the zshield gradient triple resonance cryoprobe at 298 K. Human brain metabolites were prepared with 10% $D_2O$. Two-dimensional spectra with 2048 data points contains 320 free induction decay (FID) averaging. Repetition delay was 2 sec. The Top Spin 2.0 software was used for post-processing. Total 7 metabolites such as N-acetyl aspartate (NAA), creatine (Cr), choline (Cho), lutamine (Gln), glutamate (Glu), myo-inositol (Ins), and lactate (Lac) were included for major target metabolites. Results : Symmetrical 2D-COSY and 2D-NOESY pectra were successfully acquired: COSY cross peaks were observed in the only 1.0-4.5 ppm, however, NOESY cross peaks were observed in the 1.0-4.5 ppm and 7.9 ppm. From the result of the 2-D COSY data, cross peaks between the methyl protons ($CH_3$(3)) at 1.33 ppm and methine proton (CH(2)) at 4.11 ppm were observed in Lac. Cross peaks between the methylene protons (CH2(3,$H{\alpha}$)) at 2.50ppm and methylene protons ($CH_2$,(3,$H_B$)) at 2.70 ppm were observed in NAA. Cross peaks between the methine proton (CH(5)) at 3.27 ppm and the methine proton (CH(4,6)) at 3.59 ppm, between the methine proton (CH(1,3)) at 3.53 ppm and methine proton (CH(4,6)) at 3.59 ppm, and between the methine proton (CH(1,3)) at 3.53 ppm and methine proton (CH(2)) at 4.05 ppm were observed in Ins. From the result of 2-D NOESY data, cross peaks between the NH proton at 8.00 ppm and methyl protons ($CH_3$) were observed in NAA. Cross peaks between the methyl protons ($CH_3$(3)) at 1.33 ppm and methine proton (CH(2)) at 4.11 ppm were observed in Lac. Cross peaks between the methyl protons (CH3) at 3.03 ppm and methylene protons (CH2) at 3.93 ppm were observed in Cr. Cross peaks between the methylene protons ($CH_2$(3)) at 2.11 ppm and methylene protons ($CH_2$(4)) at 2.35 ppm, and between the methylene protons($CH_2$ (3)) at 2.11 ppm and methine proton (CH(2)) at 3.76 ppm were observed in Glu. Cross peaks between the methylene protons (CH2 (3)) at 2.14 ppm and methine proton (CH(2)) at 3.79 ppm were observed in Gln. Cross peaks between the methine proton (CH(5)) at 3.27 ppm and the methine proton (CH(4,6)) at 3.59 ppm, and between the methine proton (CH(1,3)) at 3.53 ppm and methine proton (CH(2)) at 4.05 ppm were observed in Ins. Conclusion : The present study demonstrated that in vitro 2D-COSY and NOESY represented the 3-bond and spatial connectivity of human brain metabolites by scalar coupling and dipolar NOE interaction. This study could aid in better understanding the interactions between human brain metabolites in vivo 2DCOSY study.

• Investigative Magnetic Resonance Imaging
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• v.8 no.1
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• pp.32-41
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• 2004

Purpose : To measure the NMR relaxation properties of MnPC, to observe the characteristics of liver enhancement patterns on MR images in experimentally implanted rabbit VX2 tumor model, and to estimate the possibility of tissue specific contrast agent for MnPC in comparison with the hepatobiliary agent. Materials and Methods : Phthalocyanine (PC) was chelated with paramagnetic ions, manganese (Mn). 2.01 g (5.2 mmol) of phthalocyanine was mixed with 0.37 g (1.4 nlmol) of Mn chloride at $310^{\circ}C$ for 36 hours and then purified by chromatography ($CHCl_3:\;CH_3OH=98:2$, volume ratio) to obtain 1.04 g $(46\%)$ of MnPC (molecular weight = 2000 daltons). The T1/T2 relaxivity (R1/R2) for MnPC were determined at a 1.5 T (64 MHz) MR spectrometer. VX2 tumor model was experimentally implanted in the liver parenchyma of rabbits. All MR studies were performed on 1.5 T. The human extremity radio frequency coil of a bird cage type was employed. MR images were acquired at 17 to 24 days after VX2 carcinoma implantation.4 mmol/kg MnPC and 0.01 mmol/kg Mn-DPDP were injected via the ear vein of rabbits. T1-weighted images were obtained with spin-echo (TR/TE=516/14 msec) and fast multiplanar spoiled gradient recalled (TR/TE : 80/4 msec, $60^{\circ}$ flip angle) pulse sequence. Fast spin-echo (TR/TE=1200/85 msec) was used to obtain the T2-weighted images. Results : The value of T1/T2 relaxivity (R1/R2) of MnPC was $7.28\;mM^{-1}S^{-1}$ and $55.56\;mM^{-1}S^{-1}$ respectively at 1.5 T (64 MHz). Because the T2 relaxivity of MnPC that bonded strongly, covalently manganese with phthalocyanine was very high, the signal intensity of liver parenchyma was decreased on postcontrast T2-weighted images and we could easily distinguish the VX2 carcinoma within the liver parenchyma. When MnPC was administrated intravenously, the tumor margin delineation was more remarkable than Mn-DPDP-enhanced images. The enhancement of liver parenchyma with MnPC persisted at relatively high levels over at least one hour after injection of the contrast agents. Conclusion : The hepatic uptake and biliary excretion of MnPC, which are similar to Mn-DPDP, suggest that this agent is a new liver-specific agent. Also, MnPC seems to be used as a dual contrast agent (T1 and T2) with high T2 relaxivity. However, it is warranted that MnPC needs further investigation as a potential contrast agent for MR imaging of the liver. That is, further characterizations of MnPC are needed in vivo and in vitro before clinical trials. The diagnostic potential of MnPC will also have to be examined more in the animal models of additional types.

• Proceedings of the Korean DIstribution Association Conference
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• 2003.02a
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• pp.123-166
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• 2003

Marketing channel is recognized as one of the society systems which have the character of functional organization. These organizations are related to each other for specialized and cooperative work. Channel members in distribution channel are striving to accomplish exchange through reciprocal action. Thus channel members exercise their power to take better position in exchange. There will be struggling between members about satisfaction and conflict during this power exercise. Now a days, buyers use more harsh power as large retail firms are increasing. This phenomenon is occurring in the distribution channel. However, there will be different phenomenon in case of agricultural products. Not like industrial product suppliers, agricultural product suppliers have various supply channels and many agricultural products are seasonal. It has also unstable amount supplies. There should be differentiated marketing in agricultural products. Relatively weaker powered suppliers have to strengthen comparative factors and also have to be technically specialized through assessed experience in order to establish strong product sales chain. Making a brand of agricultural product would be also a good idea to increase the product comparability. Channel members need to be recognized their specialized functions in order to make balanced distribution channel. There have to be conversion of concept of relation between suppliers and buyers from subordinate relationship to cooperative relationship.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.755-762
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• 2018

The purpose of this study was to compare the FA(faractional anisotropy) and ADC(apparent diffusion coefficient) values, which were derived from diffusion tensor imaging in breast cancer patients. The diffusion gradient used in this study was derived from quantitative diffusion indices using 20 directions(b-value, 0 and $1,000s/mm^2$). Quantitative analysis was analyzed using Pearson's correction and qualitative analysis using for correction coefficients. As a result, $FA_{min}$, $FA_{mean}$ and $FA_{max}$ were $0.098{\pm}0.065$, $0.302{\pm}0.142$ and $0.634{\pm}0.236$, respectively(p > 0.05). The $ADC_{min}$, $ADC_{mean}$ and $ADC_{max}$ were $0.741{\pm}0.403$, $1.095{\pm}0.394$ and $1.530{\pm}0.447$, respectively(p > 0.05). The $FA_{min}$, $FA_{mean}$, and $FA_{max}$ mean values were $0.132{\pm}0.050$, $0.418{\pm}0.094$, and $0.770{\pm}0.164$ for Category 6 and Kinetic Curve Pattern III, respectively. $ADC_{min}$, $ADC_{mean}$, and $ADC_{max}$ were $0.753{\pm}0.189$, $1.120{\pm}0.236$, and $1.615{\pm}0.372$, respectively. Quantitative analysis showed negative correlation between $ADC_{mean}-FA_{mean}$ and $ADC_{max}-FA_{max}$(p = 0.001, 0.003). The qalitative analysis showed ADC 0.628(p = 0.001), FA 0.620(p = 0.001) in the internal evaluations, ADC 0.677(p = 0.001), FA 0.695(p = 0.001) in external evaluations. In conclusion, based on the morphological examination, time to signal intensity graph is the form of wash-out(pattern III) in the dynamic contrast enhance examination, As a result, the $ADC_{mean}$ $1.120{\pm}0.236$ and $FA_{mean}$ values were $0.032{\pm}0.142$ with a negative correlation (Y=1.44-1.12X). Therefore, If we understand the shape of time to signal intensity graph and the relationship between ADC and FA, It will be a criterion for distinguishing malignant diseases in breast cancer.