• Journal of Hospice and Palliative Care
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• v.5 no.2
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• pp.111-124
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• 2002

Purpose : Although the average life expectancy has increased due to advances in medicine, mortality due to cancer is on an increasing trend. Consequently, the number of terminally ill cancer patients is also on the rise. Predicting the survival period is an important issue in the treatment of terminally ill cancer patients since the choice of treatment would vary significantly by the patents, their families, and physicians according to the expected survival. Therefore, we investigated the prognostic factors for increased mortality risk in terminally ill cancer patients to help treat these patients by predicting the survival period. Methods : We investigated 31 clinical parameters in 157 terminally ill cancer patients admitted to in the Department of Family Medicine, National Health Insurance Corporation Ilsan Hospital between July 1, 2000 and August 31, 2001. We confirmed the patients' survival as of October 31, 2001 based on medical records and personal data. The survival rates and median survival times were estimated by the Kaplan-Meier method and Log-rank test was used to compare the differences between the survival rates according to each clinical parameter. Cox's proportional hazard model was used to determine the most predictive subset from the prognostic factors among many clinical parameters which affect the risk of death. We predicted the mean, median, the first quartile value and third quartile value of the expected lifetimes by Weibull proportional hazard regression model. Results : Out of 157 patients, 79 were male (50.3%). The mean age was $65.1{\pm}13.0$ years in males and was $64.3{\pm}13.7$ years in females. The most prevalent cancer was gastric cancer (36 patients, 22.9%), followed by lung cancer (27, 17.2%), and cervical cancer (20, 12.7%). The survival time decreased with to the following factors; mental change, anorexia, hypotension, poor performance status, leukocytosis, neutrophilia, elevated serum creatinine level, hypoalbuminemia, hyperbilirubinemia, elevated SGPT, prolonged prothrombin time (PT), prolonged activated partial thromboplastin time (aPTT), hyponatremia, and hyperkalemia. Among these factors, poor performance status, neutrophilia, prolonged PT and aPTT were significant prognostic factors of death risk in these patients according to the results of Cox's proportional hazard model. We predicted that the median life expectancy was 3.0 days when all of the above 4 factors were present, $5.7{\sim}8.2$ days when 3 of these 4 factors were present, $11.4{\sim}20.0$ days when 2 of the 4 were present, and $27.9{\sim}40.0$ when 1 of the 4 was present, and 77 days when none of these 4 factors were present. Conclusions : In terminally ill cancer patients, we found that the prognostic factors related to reduced survival time were poor performance status, neutrophilia, prolonged PT and prolonged am. The four prognostic factors enabled the prediction of life expectancy in terminally ill cancer patients.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.94-100
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• 2010

Purpose: We can evaluate function of kidney by Glomerular Filtration Rate (GFR) test using $^{99m}Tc$-DTPA which is simple. This test is influenced by several parameter such as net syringe count, kidney depth, corrected kidney count, acquisition time and characters of gamma camera. In this study, we evaluated predose count according to matrix size in the GFR test using $^{99m}Tc$-DTPA. Materials and Methods: Gamma camera of Infinia in GE was used, and LEGP collimator, three types of matrix size ($64{\times}64$, $128{\times}128$, $256{\times}256$) and 1.0 of zoom factor were applied. We increased radioactivity concentration from 222 (6), 296 (8), 370 (10), 444 (12) up to 518 MBq (14 mCi) respectively and acquired images according to matrix size at 30 cm distance from detector. Lastly, we evaluated these values and then substituted them for GFR formula. Results: In $64{\times}64$, $128{\times}128$ and $256{\times}256$ of matrix size, counts per second was 26.8, 34.5, 41.5, 49.1 and 55.3 kcps, 25.3, 33.4, 41.0, 48.4 and 54.3 kcps and 25.5, 33.7, 40.8, 48.1 and 54.7 kcps respectively. Total counts for 5 second were 134, 172, 208, 245 and 276 kcounts from $64{\times}64$, 127, 172, 205, 242, 271 kcounts from $128{\times}128$, and 137, 168, 204, 240 and 273 kcounts from $256{\times}256$, and total counts for 60 seconds were 1,503, 1,866, 2,093, 2,280, 2,321 kcounts, 1,511, 1,994, 2,453, 2,890 and 3,244 kcounts, and 1,524, 2,011, 2,439, 2,869 and 3,268 kcounts respectively. It is different from 0 to 30.02 % of percentage difference in $64{\times}64$ of matrix size. But in $128{\times}128$ and $256{\times}256$, it is showed 0.60 and 0.69 % of maximum value each. GFR of percentage difference in $64{\times}64$ represented 6.77% of 222 MBq (6 mCi), 42.89 % of 518 MBq (14 mCi) at 60 seconds respectively. However it is represented 0.60 and 0.63 % each in $128{\times}128$ and $256{\times}256$. Conclusion: There was no big difference in total counts of percentage difference and GFR values acquiring from $128{\times}128$ and $256{\times}256$ of matrix size. But in $64{\times}64$ of matrix size when the total count exceeded 1,500 kcounts, the overflow phenomenon was appeared differently according to predose radioactivity of concentration and acquisition time. Therefore, we must optimize matrix size and net syringe count considering the total count of predose to get accurate GFR results.

• The Korean Journal of Nuclear Medicine Technology
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• v.24 no.1
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• pp.27-32
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• 2020

Purpose Glomerular Filtration Rate(GFR) is an important indicator for evaluating renal function and monitoring the progress of renal disease. Currently, the method of measuring GFR in clinical trials by using serum creatinine value and ^99mTc-DTPA(diethylenetriamine pentaacetic acid) renal dynamic scan is still useful. After the Gates method of formula was announced, when ^99mTc-DTPA Renal dynamic scan is taken, it is applied the GFR is measured using a gamma camera. The purpose of this paper is to measure the GFR by applying the Gates method of formula. It is according to effect activity and matrix size that is related in the GFR. Materials and Methods Data from 5 adult patients (patient age = 62 ± 5, 3 males, 2 females) who had been examined ^99mTc-DTPA Renal dynamic scan were analyzed. A dynamic image was obtained for 21 minutes after instantaneous injection of ^99mTc-DTPA 15 mCi into the patient's vein. To evaluate the glomerular filtration rate according to changes in activity and matrix size, total counts were measured after setting regions of interest in both kidneys and tissues in 2-3 minutes. The distance from detector to the table was maintained at 30cm, and the capacity of the pre-syringe (PR) was set to 15, 20, 25, 30 mCi, and each the capacity of post-syringe (PO) was 1, 5, 10, 15 mCi is set to evaluate the activity change. And then, each matrix size was changed to 32 × 32, 64 × 64, 128 × 128, 256 × 256, 512 × 512, and 1024 × 1024 to compare and to evaluate the values. Results As the activity increased in matrix size, the difference in GFR gradually decreased from 52.95% at the maximum to 16.67% at the minimum. The GFR value according to the change of matrix size was similar to 2.4%, 0.2%, 0.2% of difference when changing from 128 to 256, 256 to 512, and 512 to 1024, but 54.3% of difference when changing from 32 to 64 and 39.43% of difference when changing from 64 to 128. Finally, based on the presently used protocol, 256 × 256, PR 15 mCi and PO 1 mCi, the GFR value was the largest difference with 82% in PR 15 mCi and PO 1 mCi. conditions, and at the least difference is 0.2% in the conditions of PR 30 mCi and PO 15 mCi. Conclusion Through this paper, it was confirmed that when measuring the GFR using the gate method in the ^99mTc-DTPA renal dynamic scan. The GFR was affected by activity and matrix size changes. Therefore, it is considered that when taking the ^99mTc-DTPA renal dynamic scan, is should be careful by applying appropriate parameters when calculating GFR in the every hospital.