• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.2
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• pp.37-43
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• 2013

Purpose: PET/CT scan using the SUV (Standardized Uptake Value) of radiopharmaceutical uptake in organs and tissues as an objective indicator makes it possible to analyze physiological and chemical reactions of human organs. This study analyzes the change of the SUV uptake in accordance with the way how PET/CT patients take a rest after the injection of $^{18}F-FDG$ (Fluororo-deoxyglucose). And also subjective satisfaction is assessed listening to music while taking a rest. Materials and Methods: From April 2011 until February 2013, Among the Primary cancer patients who admitted to the Catholic Medical Center (Seoul & Bucheon St. Mary's Hospital) and scanned $^{18}F-FDG$ PET/CT and also received care through the tracking test (mean age $55.61{\pm}12.41$ years, 108 people, 48 men and 60 women) were selected. The patients were divided into two groups. The first group (A: basal study) is requested to take a rest in bed quietly after the injection. However the second one (B: follow up study) is requested to listen to the music while taking a rest. And then SUV analysis was performed respectively. At the end of the scan, ROI (Region Of Interest) were set from the center of the liver (right lobe) and 3 spots of the brain (frontal, temporal, and occipital lobes). And the SUV was calculated. To identify the correlation among those ROIs, paired t-test was performed using SPSS software (Version 12.0K for windows, P>0.05). Also, after the PET/CT scan the satisfaction study was conducted of all the patients. 1:1 questionnaire survey was performed, and that questionnaire was made using the Likert 5-point scale. By utilizing those questionnaires, the analysis about simple frequency, percentage, average, and standard deviation was performed. Results: The SUV change of the 4 designated ROIs in accordance with listening to music was not statistically significant. (Frontal lobe P-value=0.611, Occipital lobe P-value=0.499, Temporal lobe P-value=0.717, Liver P-value=0.334: P-value>0.05) And the satisfaction study indicated that group B was appear to be 0.42 points (5 basis points) higher than group A. It showed that patients are more satisfied in group B than group A. Conclusion: when performing PET/CT scan using $^{18}F-FDG$, listening to music after the injection of the radiopharmaceuticals does not affect the SUV but given the state of the psychological comfort that may increase the patient's satisfaction.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.122-126
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• 2010

Purpose: F-18-FPCIT that shows strong familiarity with DAT located at a neural terminal site offers diagnostic information about DAT density state in the region of the striatum especially Parkinson's disease. In this study, we altered the iteration and subset and measured SUV${\pm}$SD and Contrasts from phantom images which set up to specific iteration and subset. So, we are going to suggest the appropriate range of the iteration and subset. Materials and Methods: This study has been performed with 10 normal volunteers who don't have any history of Parkinson's disease or cerebral disease and Flangeless Esser PET Phantom from Data Spectrum Corporation. $5.3{\pm}0.2$ mCi of F-18-FPCIT was injected to the normal group and PET Phantom was assembled by ACR PET Phantom Instructions and it's actual ratio between hot spheres and background was 2.35 to 1. Brain and Phantom images were acquired after 3 hours from the time of the injection and images were acquired for ten minutes. Basically, SIEMENS Bio graph 40 True-point was used and True-X method was applied for image reconstruction method. The iteration and Subset were set to 2 iterations, 8 subsets, 3 iterations, 16 subsets, 6 iterations, 16 subsets, 8 iterations, 16 subsets and 8 iterations, 21 subsets respectively. To measure SUVs on the brain images, ROIs were drawn on the right Putamen. Also, Coefficient of variance (CV) was calculated to indicate the uniformity at each iteration and subset combinations. On the phantom study, we measured the actual ratio between hot spheres and back ground at each combinations. Same size's ROIs were drawn on the same slide and location. Results: Mean SUVs were 10.60, 12.83, 13.87, 13.98 and 13.5 at each combination. The range of fluctuation by sets were 22.36%, 10.34%, 1.1%, and 4.8% respectively. The range of fluctuation of mean SUV was lowest between 6 iterations 16 subsets and 8 iterations 16 subsets. CV showed 9.07%, 11.46%, 13.56%, 14.91% and 19.47% respectively. This means that the numerical value of the iteration and subset gets higher the image's uniformity gets worse. The range of fluctuation of CV by sets were 2.39, 2.1, 1.35, and 4.56. The range of fluctuation of uniformity was lowest between 6 iterations, 16 subsets and 8 iterations, 16 subsets. In the contrast test, it showed 1.92:1, 2.12:1, 2.10:1, 2.13:1 and 2.11:1 at each iteration and subset combinations. A Setting of 8 iterations and 16 subsets reappeared most close ratio between hot spheres and background. Conclusion: Findings on this study, SUVs and uniformity might be calculated differently caused by variable reconstruction parameters like filter or FWHM. Mean SUV and uniformity showed the lowest range of fluctuation at 6 iterations 16 subsets and 8 iterations 16 subsets. Also, 8 iterations 16 subsets showed the nearest hot sphere to background ratio compared with others. But it can not be concluded that only 6 iterations 16 subsets and 8 iterations 16 subsets can make right images for the clinical diagnosis. There might be more factors that can make better images. For more exact clinical diagnosis through the quantitative analysis of DAT density in the region of striatum we need to secure healthy people's quantitative values.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.111-114
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• 2010

Purpose: There has been recent interest in the radioactivity uptake and image acquisition of radioactivity concentration. The degree of uptake is strongly affected by many factors containing $^{18}F$-FDG injection volume, tumor size and the density of blood glucose. Therefore, we investigated how radioactivity uptake in target influences 2D or 3D image analysis and elucidate radioactivity concentration that mediate this effect. This study will show the relationship between the radioactivity uptake and 2D,3D image acquisition on radioactivity concentration. Materials and Methods: We got image with 2D and 3D using 1994 NEMA PET phantom and GE Discovery(GE, U.S.A) STe 16 PET/CT setting the ratio of background and hot sphere's radioactivity concentration as being a standard of 1:2, 1:4, 1:8, 1:10, 1:20, and 1:30 respectively. And we set 10 minutes for CT attenuation correction and acquisition time. For the reconstruction method, we applied iteration method with twice of the iterative and twenty times subset to both 2D and 3D respectively. For analyzing the images, We set the same ROI at the center of hot sphere and the background radioactivity. We measured the radioactivity count of each part of hot sphere and background, and it was comparative analyzed. Results: The ratio of hot sphere's radioactivity density and the background radioactivity with setting ROI was 1:1.93, 1:3.86, 1:7.79, 1:8.04, 1:18.72, and 1:26.90 in 2D, and 1:1.95, 1:3.71, 1:7.10, 1:7.49, 1:15.10, and 1:23.24 in 3D. The differences of percentage were 3.50%, 3.47%, 8.12%, 8.02%, 10.58%, and 11.06% in 2D, the minimum differentiation was 3.47%, and the maximum one was 11.06%. In 3D, the difference of percentage was 3.66%, 4.80%, 8.38%, 23.92%, 23.86%, and 22.69%. Conclusion: The difference of accumulated concentrations is significantly increased following enhancement of radioactivity concentration. The change of radioactivity density in 2D image is affected by less than 3D. For those reasons, when patient is examined as follow up scan with changing the acquisition mode, scan should be conducted considering those things may affect to the quantitative analysis result and take into account these differences at reading.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.1
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• pp.60-64
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• 2017

Purpose Westgard multi-rules application based on test quality improvement and commercialized international standard has been widely used in quality control. However, it is difficult to applicate the Westgard multi-rules in nuclear medicine in vitro tests due to the larger sample sizes and the simultaneous measurement of quality control material and patient sample. This study investigated the usefulness of Westgard multi-rules application in nuclear medicine in vitro tests. Materials and Methods A total of 282 systematic error multi-rules (22s, 101s) recorded in the samsung medical center computer system from January 2013 to June 2016 along with 117 cases of corrective measure record was analyzed. The Quality control implementation is recorded in Hospital information system were divided into 4 high-level areas including quality control material error, experimental procedural error, Kit lot number management error, and others. To prevent quality control material error, the existing method that each staff used their own method was changed. The staff who in charge of managing the quality control material was designated and daily consumption amount of every test was strictly controlled by one person. To prevent other errors, every test step was standardized so that the entire test procedures are identically implemented. Results The total quality control implementation was 117 cases; As a result, 62 quality control material errors were 62 cases, experimental process errors were 24 cases, Kit lot number control errors were 18 cases, and other errors were 13 cases. The quality control material error was corrected and could be used fresh materials within 2 days after thawing. The cases of systemic error were decreased to causes as quality control material error. The quality control materials were reduced above 10 vials to a monthly average. In addition, these errors of experimental processing and Kit lot number were improved by test standardization. Consequently, the cases of 101s and 22s in systematic error rules decreased at least 2 cases to a monthly average. Conclusion To confirm of systematic error through multi-rules application quickly, it is necessary to base on management of the QC material, target values and standard deviation. Moreover, in the event of a systematic error, it was found important to record measures based on test cause analysis. The experiment results are expected to contribute to internal quality control improvement and prompt and accurate result reporting through error recording and causal analysis based on Westgard multi-rules analysis.

• Journal of Sericultural and Entomological Science
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• v.8
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• pp.11-25
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• 1968

Various formulae for estimation of leaf production in mulberry trees were investigated and obtained. Four varieties of mulberry trees were used as the materials, and seven characters namely branch length. branch diameter, node number per branch, total branch weight, branch weight except leaves, leaf weight and leaf area, were studied. The formulae to estimate the leaf yield of mulberry trees are as follows: 1. Varietal differences were appeared in means, variances, standard devitations and standard errors of seven characters studied as shown in table 1. 2. Y$_1$=a$_1$X$_1$${\times}$P$_1$......(l) where Y$_1$ means yield per l0a by branch number and leaf weight determination. a$_1$.........leaf weight per branch. X$_1$.......branch number per plant. P$_1$........plant number per l0a. 3. Y$_2$=(a$_2$${\pm}$S. E.${\times}$X$_2$)+P$_1$.......(2) where Y$_2$ means leaf yield per l0a by branch length and leaf weight determination. a$_2$......leaf weight per meter of branch length. S. E. ......standard error. X$_2$....total branch length per plant. P$_1$........plant number per l0a as written above. 4. Y$_3$=(a$_3$${\pm}$S. E${\times}$X$_3$)${\times}$P$_1$.....(3) where Y$_3$ means of yield per l0a by branch diameter measurement. a$_3$.......leaf weight per 1cm of branch diameter. X$_3$......total branch diameter per plant. 5. Y$_4$=(a$_4$${\pm}$S. E.${\times}$X$_4$)P$_1$......(4) where Y$_4$ means leaf yield per 10a by node number determination. a$_4$.......leaf weight per node X$_4$.....total node number per plant. 6. Y$\sub$5/= {(a$\sub$5/${\pm}$S. E.${\times}$X$_2$)Kv}${\times}$P$_1$.......(5) where Y$\sub$5/ means leaf yield per l0a by branch length and leaf area measurement. a$\sub$5/......leaf area per 1 meter of branch length. K$\sub$v/......leaf weight per 100$\textrm{cm}^2$ of leaf area. 7. Y$\sub$6/={(X$_2$$\div$a$\sub$6/${\pm}$S. E.)}${\times}$K$\sub$v/${\times}$P$_1$......(6) where Y$\sub$6/ means leaf yield estimated by leaf area and branch length measurement. a$\sub$6/......branch length per l00$\textrm{cm}^2$ of leaf area. X$_2$, K$\sub$v/ and P$_1$ are written above. 8. Y$\sub$7/= {(a$\sub$7/${\pm}$S. E. ${\times}$X$_3$)}${\times}$K$\sub$v/${\times}$P$_1$.......(7) where Y$\sub$7/ means leaf yield estimates by branch diameter and leaf area measurement. a$\sub$7/......leaf area per lcm of branch diameter. X$_3$, K$\sub$v/ and P$_1$ are written above. 9. Y$\sub$8/= {(X$_3$$\div$a$\sub$8/${\pm}$S. E.)}${\times}$K$\sub$v/${\times}$P$_1$.......(8) where Y$\sub$8/ means leaf yield estimates by leaf area branch diameter. a$\sub$8/......branch diameter per l00$\textrm{cm}^2$ of leaf area. X$_3$, K$\sub$v/, P$_1$ are written above. 10. Y$\sub$9/= {(a$\sub$9/${\pm}$S. E.${\times}$X$_4$)${\times}$K$\sub$v/}${\times}$P$_1$......(9) where Y$\sub$7/ means leaf yield estimates by node number and leaf measurement. a$\sub$9/......leaf area per node of branch. X$_4$, K$\sub$v/, P$_1$ are written above. 11. Y$\sub$10/= {(X$_4$$\div$a$\sub$10/$\div$S. E.)${\times}$K$\sub$v/}${\times}$P$_1$.......(10) where Y$\sub$10/ means leaf yield estimates by leaf area and node number determination. a$\sub$10/.....node number per l00$\textrm{cm}^2$ of leaf area. X$_4$, K$\sub$v/, P$_1$ are written above. Among many estimation methods. estimation method by the branch is the better than the methods by the measurement of node number and branch diameter. Estimation method, by branch length and leaf area determination, by formulae (6), could be the best method to determine the leaf yield of mulberry trees without destroying the leaves and without weighting the leaves of mulberry trees.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.3-8
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• 2016

Purpose SUV is one of the parameters that assist diagnosis in origin, metastasis and staging of cancer. Specially, it is important to compare SUV before and after chemo or radiation therapy to find out effectiveness of treatment. Storing PET data which has no quantitative change is needed for SUV comparison. However, there is a possibility to loss the data in external hard drive or MINIpacs that are managed by department of nuclear medicine. The aim of this study is to evaluate SUV and metabolic tumor volume (MTV) among reconstructed data (R-D) in workstation, R-D and re-sliced data (S-D) in PACS. Materials and Methods Data of 20 patients (aged $60.5{\pm}8.3y$) underwent $^{18}F-FDG$ PET (Biograph truepoint 40, mCT 40, mCT 64, mMR, Siemens) study were analysed. $SUV_{max}$, $SUV_{peak}$ and MTV were measured in liver, aorta and tumor after sending R-D in workstation, R-D and S-D in PACS to syngo.via software. Results R-D of workstation and PACS showed the same value as mean $SUV_{max}$ in liver, aorta and tumor were $2.95{\pm}0.59$, $2.35{\pm}0.61$, $10.36{\pm}6.15$ and $SUV_{peak}$ were $2.70{\pm}0.51$, $2.07{\pm}0.43$, $7.67{\pm}3.73$(p>0.05) respectively. Mean $SUV_{max}$ of S-D in PACS were decreased by 5.18%, 7.22%, 12.11% and $SUV_{peak}$ 2.61%, 3.63%, 10.07%(p<0.05). Correlation between R-D and S-D were $SUV_{max}$ 0.99, 0.96, 0.99 and $SUV_{peak}$ 0.99, 0.99, 0.99. And 2SD in balnd-altman analysis were $SUV_{max}$ 0.125, 0.290, 1.864 and $SUV_{peak}$ 0.053, 0.103, 0.826. MTV of R-D in workstation and PACS show the same value as $14.21{\pm}12.72cm^3$(p>0.05). MTV in PACS was decreased by 0.12% compared to R-D(p>0.05). Correlation and 2SD between R-D and S-D were 0.99 and 2.243. Conclusion $SUV_{max}$, $SUV_{peak}$, MTV showed the same value in both of R-D in workstation and PACS. However, there was statistically difference in $SUV_{max}$, $SUV_{peak}$ of S-D compare to R-D despite of high correlation. It is possible to analyse reliable pre and post SUV if storing R-D in main hospital PACS system.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.115-118
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• 2012

Purpose: The Levey-Jennings chart controlled measurement values that deviated from the tolerance value (mean ${\pm}2SD$ or ${\pm}3SD$). On the other hand, the upgraded Westgard Multi-Rules are actively recommended as a more efficient, specialized form of hospital certification in relation to Internal Quality Control. To apply Westgard Multi-Rules in quality control, credible quality control substance and target value are required. However, as physical examinations commonly use quality control substances provided within the test kit, there are many difficulties presented in the calculation of target value in relation to frequent changes in concentration value and insufficient credibility of quality control substance. This study attempts to improve the professionalism and credibility of quality control by applying Westgard Multi-Rules and calculating credible target value by using a commercialized quality control substance. Materials and Methods : This study used Immunoassay Plus Control Level 1, 2, 3 of Company B as the quality control substance of Total T3, which is the thyroid test implemented at the relevant hospital. Target value was established as the mean value of 295 cases collected for 1 month, excluding values that deviated from ${\pm}2SD$. The hospital quality control calculation program was used to enter target value. 12s, 22s, 13s, 2 of 32s, R4s, 41s, $10\bar{x}$, 7T of Westgard Multi-Rules were applied in the Total T3 experiment, which was conducted 194 times for 20 days in August. Based on the applied rules, this study classified data into random error and systemic error for analysis. Results: Quality control substances 1, 2, and 3 were each established as 84.2 ng/$dl$, 156.7 ng/$dl$, 242.4 ng/$dl$ for target values of Total T3, with the standard deviation established as 11.22 ng/$dl$, 14.52 ng/$dl$, 14.52 ng/$dl$ respectively. According to error type analysis achieved after applying Westgard Multi-Rules based on established target values, the following results were obtained for Random error, 12s was analyzed 48 times, 13s was analyzed 13 times, R4s was analyzed 6 times, for Systemic error, 22s was analyzed 10 times, 41s was analyzed 11 times, 2 of 32s was analyzed 17 times, $10\bar{x}$ was analyzed 10 times, and 7T was not applied. For uncontrollable Random error types, the entire experimental process was rechecked and greater emphasis was placed on re-testing. For controllable Systemic error types, this study searched the cause of error, recorded the relevant cause in the action form and reported the information to the Internal Quality Control committee if necessary. Conclusions : This study applied Westgard Multi-Rules by using commercialized substance as quality control substance and establishing target values. In result, precise analysis of Random error and Systemic error was achieved through the analysis of 12s, 22s, 13s, 2 of 32s, R4s, 41s, $10\bar{x}$, 7T rules. Furthermore, ideal quality control was achieved through analysis conducted on all data presented within the range of ${\pm}3SD$. In this regard, it can be said that the quality control method formed based on the systematic application of Westgard Multi-Rules is more effective than the Levey-Jennings chart and can maximize error detection.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.45-49
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• 2010

Purpose: Several radiopharmaceuticals were used for cisternography. But recently, due to more short acquisition time, high resolution than other radiopharmaceuticals like In-111 DTPA, we were using Tc-99m DTPA in cisternography. Using of Tc-99m DTPA for intrathecal, was not officially recognised by the FDA. And there are matters of aseptic meningitis, muscular tetany, seizures by inappropriate radiopharmaceuticals handling. So, it is necessary to prevent adverse reactions while handling the radiopharmaceuticals using in cisternography. Therefore, this study aims to evaluation of usefulness and procedures for safety of radiopharmaceuticals in cisternography. Materials and Methods: Subjects were 12radioactive tracer vials using in cisternography in 2008 Dec. 16 - 2009 Dec. 30. (1) Radioactive tracer Vial test - We were measured NaPertechnetate radiation dose and volume, normal saline volume for dilution, source volume and dose activity for patient injection. And then, calculated mass of pure DTPA. (2) Bacterial endotoxin test - We performed pyrogen test using by negative/positive control vials which was added normal saline 0.2 mL and added normal saline 0.1 mL, Tc-99m DTPA 0.1 mL in test control vial. And then, reacted by digital hot plate in $37.5^{\circ}C$ for 1 hour and compared of gel-clot in each control vials. (3) Compliance safety procedure - We were checked safety issues and wrote out a safety procedure exam sheet. Results: (1) Radioactive tracer Vial test - Mass of DTPA per dose for patient injection (mg) was 0.88 (mg) on average, and Mass of DTPA per volume for patient injection (mg) was 0.74 (mg) on average. (2) Bacterial endotoxin test - All control test vials showed negative reactions. (3) Compliance safety procedure - We were checked safety issues and wrote out a safety exam sheet in all the exams. So, there were no adverse reactions. Conclusion: We could examine easier to safety tests using by Techscan - DTPA (Mallinckrodt): CaNa3. Each test results were passed the safety tests and there are no adverse reactions. The use of Tc-99m DTPA for cisternography, always has been become an issue. Since it has occur adverse reaction while examine the cisternography using by Tc-99m DTPA, it needs to set up the 'Standard Operating procedures'.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.1
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• pp.43-48
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• 2014

Purpose: In the PET/CT images, The SUV (standardized uptake value) enables the quantitative assessment according to the biological changes of organs as the index of distinction whether lesion is malignant or not. Therefore, It is too important to enter parameters correctly that affect to the SUV. The purpose of this study is to evaluate an allowable error range of SUV as measuring the difference of results according to input errors of Activity, Weight, uptake Time among the parameters. Materials and Methods: Three inserts, Hot, Teflon and Air, were situated in the 1994 NEMA Phantom. Phantom was filled with 27.3 MBq/mL of 18F-FDG. The ratio of hotspot area activity to background area activity was regulated as 4:1. After scanning, Image was re-reconstructed after incurring input errors in Activity, Weight, uptake Time parameters as ${\pm}5%$, 10%, 15%, 30%, 50% from original data. ROIs (region of interests) were set one in the each insert areas and four in the background areas. $SUV_{mean}$ and percentage differences were calculated and compared in each areas. Results: $SUV_{mean}$ of Hot. Teflon, Air and BKG (Background) areas of original images were 4.5, 0.02. 0.1 and 1.0. The min and max value of $SUV_{mean}$ according to change of Activity error were 3.0 and 9.0 in Hot, 0.01 and 0.04 in Teflon, 0.1 and 0.3 in Air, 0.6 and 2.0 in BKG areas. And percentage differences were equally from -33% to 100%. In case of Weight error showed $SUV_{mean}$ as 2.2 and 6.7 in Hot, 0.01 and 0.03 in Tefron, 0.09 and 0.28 in Air, 0.5 and 1.5 in BKG areas. And percentage differences were equally from -50% to 50% except Teflon area's percentage deference that was from -50% to 52%. In case of uptake Time error showed $SUV_{mean}$ as 3.8 and 5.3 in Hot, 0.01 and 0.02 in Teflon, 0.1 and 0.2 in Air, 0.8 and 1.2 in BKG areas. And percentage differences were equally from 17% to -14% in Hot and BKG areas. Teflon area's percentage difference was from -50% to 52% and Air area's one was from -12% to 20%. Conclusion: As shown in the results, It was applied within ${\pm}5%$ of Activity and Weight errors if the allowable error range was configured within 5%. So, The calibration of dose calibrator and weighing machine has to conduct within ${\pm}5%$ error range because they can affect to Activity and Weight rates. In case of Time error, it showed separate error ranges according to the type of inserts. It showed within 5% error when Hot and BKG areas error were within ${\pm}15%$. So we have to consider each time errors if we use more than two clocks included scanner's one during the examinations.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.62-68
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• 2016

Purpose In a cyclosporine experiment using a robotic liquid handing system has found a deviation of its standard curve and low reproducibility of patients's results. The difference of the test is that methanol is mixed with samples and the extractions are used for the test. Therefore, we assumed that the abnormal test results came from using methanol and conducted this test. In a manual of a robotic liquid handling system mentions that we can choose several setting parameters depending on the viscosity of the liquids being used, the size of the sampling tips and the motor speeds that you elect to use but there's no exact order. This study was undertaken to confirm pipetting ability depending on types of liquids and investigate proper setting parameters for the optimum dispensing ability. Materials and Methods 4types of liquids(water, serum, methanol, PEG 6000(25%)) and $TSH^{125}I$ tracer(515 kBq) are used to confirm pipetting ability. 29 specimens for Cyclosporine test are used to compare results. Prepare 8 plastic tubes for each of the liquids and with multi pipette $400{\mu}l$ of each liquid is dispensed to 8 tubes and $100{\mu}l$ of $TSH^{125}I$ tracer are dispensed to all of the tubes. From the prepared samples, $100{\mu}l$ of liquids are dispensed using a robotic liquid handing system, counted and calculated its CV(%) depending on types of liquids. And then by adjusting several setting parameters(air gap, dispense time, delay time) the change of the CV(%)are calcutated and finds optimum setting parameters. 29 specimens are tested with 3 methods. The first(A) is manual method and the second(B) is used robotic liquid handling system with existing parameters. The third(C) is used robotic liquid handling system with adjusted parameters. Pipetting ability depending on types of liquids is assessed with CV(%). On the basis of (A), patients's test results are compared (A)and(B), (A)and(C) and they are assessed with %RE(%Relative error) and %Diff(%Difference). Results The CV(%) of the CPM depending on liquid types were water 0.88, serum 0.95, methanol 10.22 and PEG 0.68. As expected dispensing of methanol using a liquid handling system was the problem and others were good. The methanol's dispensing were conducted by adjusting several setting parameters. When transport air gap 0 was adjusted to 2 and 5, CV(%) were 20.16, 12.54 and when system air gap 0 was adjusted to 2 and 5, CV(%) were 8.94, 1.36. When adjusted to system air gap 2, transport air gap 2 was 12.96 and adjusted to system air gap 5, Transport air gap 5 was 1.33. When dispense speed was adjusted 300 to 100, CV(%) was 13.32 and when dispense delay was adjusted 200 to 100 was 13.55. When compared (B) to (A), the result increased 99.44% and %RE was 93.59%. When compared (C-system air gap was adjusted 0 to 5) to (A), the result increased 6.75% and %RE was 5.10%. Conclusion Adjusting speed and delay time of aspiration and dispense was meaningless but changing system air gap was effective. By adjusting several parameters proper value was found and it affected the practical result of the experiment. To optimize the system active efforts are needed through the test and in case of dispensing new types of liquids proper test is required to check the liquid is suitable for using the equipment.