scholarly journals ICG Clearance Test and 99mTc-GSA SPECT/CT Fusion Images

2017 ◽  
Vol 33 (6) ◽  
pp. 449-454 ◽  
Author(s):  
Yuji Iimuro
Keyword(s):  
Fusion Images ◽  
Icg Clearance ◽  
Icg Clearance Test ◽  
Clearance Test

scholarly journals The technique of 3D reconstruction combining with biochemistry to build an equivalent formula of indocyanine green (ICG) clearance test to assess the liver reserve function

2020 ◽  
Author(s):  
JinLi Zheng ◽  
Wei Xie ◽  
Yang Huang ◽  
Yunfeng Zhu ◽  
Li Jiang
Keyword(s):  
Risk Factors ◽  
Indocyanine Green ◽  
Retention Rate ◽  
Liver Volume ◽  
Volume Ratio ◽  
Factors Affecting ◽  
Icg Clearance ◽  
Icg R15 ◽  
Icg Clearance Test ◽  
Clearance Test

Abstract Background: The indocyanine green(ICG) clearance test is the main method of evaluating the liver reserve function before hepatectomy. However, some patients may be allergic to ICG or the equipment of ICG clearance test was lack, leading to be difficult to evaluate liver reserve function. We aim to find an alternative tool to assist the clinicians to evaluate the liver reserve function for those who were allergic to the ICG or lack of equipment before hepatectomy.Methods: We retrospected 300 patients to investigate the risk factors affecting the liver reserve function and to build an equivalent formula to predict ICG 15 minutes retention rate (ICG-R15) value. Results: We found that the independent risk factors affecting ICG clearance test were total bilirubin, albumin, and spleen-to-non-neoplastic liver volume ratio (SNLR). The equivalent formula of the serological index combining with SNLR was: ICG-R15=0.36×TB (umol/L)- 0.78 × ALB(g/L) + 7.783×SNLR + 0.794×PT (s) - 0.016×PLT(/109) - 0.039× ALT (IU/L) + 0.043 × AST (IU/L) + 23.846. The equivalent formula of serum index was: ICG-R152=24.6650.382×TB (umol/L) - 0.799 × ALB(g/L) - 0.025 × PLT(/109) + 0.048 × AST(IU/L) - 0.045 × ALT(IU/L). And the area under the ROC curve (AUC) of predicting ICG-R15≥10% was 0.861 and 0.857, respectively. Conclusion: We found that SNLR was an independent risk factor affecting liver reserve function. Combining with SNLR to evaluate the liver reserve function was better than just basing on serology.

scholarly journals Child-Pugh Parameters and Platelet Count as an Alternative to ICG Test for Assessing Liver Function for Major Hepatectomy

HPB Surgery ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Kin-Pan Au ◽  
See-Ching Chan ◽  
Kenneth Siu-Ho Chok ◽  
Albert Chi-Yan Chan ◽  
Tan-To Cheung ◽  
...  
Keyword(s):  
Platelet Count ◽  
Liver Function ◽  
Hospital Mortality ◽  
Major Hepatectomy ◽  
Retention Rate ◽  
Disease Free Survival ◽  
Term Survival ◽  
Icg Clearance ◽  
Icg Clearance Test ◽  
Clearance Test

Objective. To study the correlations and discrepancies between Child-Pugh system and indocyanine green (ICG) clearance test in assessing liver function reserve and explore the possibility of combining two systems to gain an overall liver function assessment. Design. Retrospective analysis of 2832 hepatocellular carcinoma (HCC) patients graded as Child-Pugh A and Child-Pugh B with ICG clearance test being performed was conducted. Results. ICG retention rate at 15 minutes (ICG15) correlates with Child-Pugh score, however, with a large variance. Platelet count improves the correlation between Child-Pugh score and ICG15. ICG15 can be estimated using the following regression formula: estimated ICG15 (eICG15) = 45.1 + 0.435 × bilirubin − 0.917 × albumin + 0.491 × prothrombin time − 0.0283 × platelet (R2=0.455). Patients with eICG15 >20.0% who underwent major hepatectomy had a tendency towards more posthepatectomy liver failure (4.1% versus 8.0%, p=0.09) and higher in-hospital mortality (3.7% versus 8.0%, p=0.052). They also had shorter median overall survival (5.10±0.553 versus 3.01±0.878 years, p=0.015) and disease-free survival (1.37±0.215 versus 0.707±0.183 years, p=0.018). Conclusion. eICG15 can be predicted from Child-Pugh parameters and platelet count. eICG15 correlates with in-hospital mortality after major hepatectomy and predicts long-term survival.

scholarly journals The technique of 3D reconstruction combining with biochemistry to build an equivalent formula of indocyanine green (ICG) clearance test to assess the liver reserve function

BMC Surgery ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jinli Zheng ◽  
Wei Xie ◽  
Yang Huang ◽  
Yunfeng Zhu ◽  
Li Jiang
Keyword(s):  
Risk Factors ◽  
Indocyanine Green ◽  
Retention Rate ◽  
Liver Volume ◽  
Volume Ratio ◽  
Factors Affecting ◽  
Icg Clearance ◽  
Icg R15 ◽  
Icg Clearance Test ◽  
Clearance Test

Abstract Background The indocyanine green (ICG) clearance test is the main method of evaluating the liver reserve function before hepatectomy. However, some patients may be allergic to ICG or the equipment of ICG clearance test was lack, leading to be difficult to evaluate liver reserve function. We aim to find an alternative tool to assist the clinicians to evaluate the liver reserve function for those who were allergic to the ICG or lack of equipment before hepatectomy. Methods We retrospected 300 patients to investigate the risk factors affecting the liver reserve function and to build an equivalent formula to predict ICG 15 min retention rate (ICG-R15) value. Results We found that the independent risk factors affecting ICG clearance test were total bilirubin, albumin, and spleen-to-non-neoplastic liver volume ratio (SNLR). The equivalent formula of the serological index combining with SNLR was: ICG-R15 = 0.36 × TB (umol/L) − 0.78 × ALB(g/L) + 7.783 × SNLR + 0.794 × PT (s) − 0.016 × PLT(/109) − 0.039 × ALT (IU/L) + 0.043 × AST (IU/L) + 23.846. The equivalent formula of serum index was: ICG-R152 = 24.665 + 0.382 × TB (umol/L) − 0.799 × ALB(g/L) − 0.025 × PLT(/109) + 0.048 × AST(IU/L) − 0.045 × ALT(IU/L). And the area under the ROC curve (AUC) of predicting ICG-R15 ≥ 10% was 0.861 and 0.857, respectively. Conclusion We found that SNLR was an independent risk factor affecting liver reserve function. Combining with SNLR to evaluate the liver reserve function was better than just basing on serology.

scholarly journals The technique of 3D reconstruction combining with biochemistry to build an equivalent formula of indocyanine green (ICG) clearance test to assess the liver reserve function

2020 ◽  
Author(s):  
JinLi Zheng ◽  
Wei Xie ◽  
Yang Huang ◽  
Yunfeng Zhu ◽  
Li Jiang
Keyword(s):  
Risk Factors ◽  
Indocyanine Green ◽  
Retention Rate ◽  
Liver Volume ◽  
Volume Ratio ◽  
Factors Affecting ◽  
Icg Clearance ◽  
Icg R15 ◽  
Icg Clearance Test ◽  
Clearance Test

Abstract Background: The indocyanine green(ICG) clearance test is the main method of evaluating the liver reserve function before hepatectomy. However, some patients may be allergic to ICG or the equipment of ICG clearance test was lack, leading to be difficult to evaluate liver reserve function. We aim to find an alternative tool to assist the clinicians to evaluate the liver reserve function for those who were allergic to the ICG or lack of equipment before hepatectomy.Methods: We retrospected 300 patients to investigate the risk factors affecting the liver reserve function and to build an equivalent formula to predict ICG 15 minutes retention rate (ICG-R15) value.Results: We found that the independent risk factors affecting ICG clearance test were total bilirubin, albumin, and spleen-to-non-neoplastic liver volume ratio (SNLR). The equivalent formula of the serological index combining with SNLR was: ICG-R15 = 0.36 × TB (umol/L)- 0.78 × ALB(g/L) + 7.783 × SNLR + 0.794 × PT (s) − 0.016 × PLT(/109) − 0.039 × ALT (IU/L) + 0.043 × AST (IU/L) + 23.846. The equivalent formula of serum index was: ICG-R152 = 24.6650.382 × TB (umol/L) − 0.799 × ALB(g/L) − 0.025 × PLT(/109) + 0.048 × AST(IU/L) − 0.045 × ALT(IU/L). And the area under the ROC curve (AUC) of predicting ICG-R15 ≥ 10% was 0.861 and 0.857, respectively.Conclusion: We found that SNLR was an independent risk factor affecting liver reserve function. Combining with SNLR to evaluate the liver reserve function was better than just basing on serology.

scholarly journals The technique of 3D reconstruction combining with biochemistry to build an equivalent formula of indocyanine green (ICG) clearance test to assess the liver reserve function

2020 ◽  
Author(s):  
JinLi Zheng ◽  
Wei Xie ◽  
Yang Huang ◽  
Yunfeng Zhu ◽  
Li Jiang
Keyword(s):  
Risk Factors ◽  
Indocyanine Green ◽  
Retention Rate ◽  
Liver Volume ◽  
Volume Ratio ◽  
Factors Affecting ◽  
Icg Clearance ◽  
Icg R15 ◽  
Icg Clearance Test ◽  
Clearance Test

Abstract Background: The indocyanine green(ICG) clearance test is the main method of evaluating the liver reserve function before hepatectomy. However, some patients may be allergic to ICG or the equipment of ICG clearance test was lack, leading to be difficult to evaluate liver reserve function. We aim to find an alternative tool to assist the clinicians to evaluate the liver reserve function for those who were allergic to the ICG or lack of equipment before hepatectomy.Methods: We retrospected 300 patients to investigate the risk factors affecting the liver reserve function and to build an equivalent formula to predict ICG 15 minutes retention rate (ICG-R15) value. Results：We found that the independent risk factors affecting ICG clearance test were total bilirubin, albumin, and spleen-to-non-neoplastic liver volume ratio (SNLR). The equivalent formula of the serological index combining with SNLR was: ICG-R15=0.36×TB (umol/L) - 0.78 × ALB(g/L) + 7.783×SNLR + 0.794×PT (s) - 0.016×PLT(/109) - 0.039× ALT (IU/L) + 0.043 × AST (IU/L) + 23.846. The equivalent formula of serum index was: ICG-R152=24.665 + 0.382×TB (umol/L) - 0.799 × ALB(g/L) - 0.025 × PLT(/109) + 0.048 × AST(IU/L) - 0.045 × ALT(IU/L). And the area under the ROC curve (AUC) of predicting ICG-R15≥10% was 0.861 and 0.857, respectively. Conclusion: We found that SNLR was an independent risk factor affecting liver reserve function. Combining with SNLR to evaluate the liver reserve function was better than just basing on serology.

scholarly journals P-L02 Machine learning to evaluate liver reserve function based on venous blood biochemistry

2021 ◽  
Vol 108 (Supplement_9) ◽  
Author(s):  
Zhengfeng Wang ◽  
zhi long shi ◽  
jnxing zheng ◽  
shaozhen rui ◽  
hui zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Venous Blood ◽  
Retention Rates ◽  
Gradient Boosting ◽  
Test Results ◽  
Biochemical Indicators ◽  
Extreme Gradient Boosting ◽  
Icg Clearance ◽  
Icg Clearance Test ◽  
Clearance Test

Abstract Background The accurate and comprehensive evaluation of liver reserve function is crucial for daily follow-up and medical treatment of patients with liver disease. However, existing techniques are too complex and costly for universal implementation.To develop a convenient, reliable method to evaluate liver reserve function based on eight biochemical indicators measured from venous blood.  Methods Blood test results (albumin (Alb), total bilirubin (TBIL), prothrombin time (PT), international normalized ratio (INR), total cholesterol (TC), cholinesterase (ChE), aspartate amino transferase (AST), and alanine transaminase (ALT)) were collected retrospectively from 660 patients treated at the first hospital of Ianzhou University from 2016 to 2018. As the reference standard for liver reserve function, indocyanine green (ICG) clearance test results were also collected from the same patients at the same times. The patient data were processed and analyzed to construct a machine learning model, eXtreme Gradient Boosting (XGBoost), and a generalized linear model (GLM) to predict liver reserve function based on the eight biochemical indicators. Results Results showed that the predicted XGBoost values were closely correlated with the actual ICG 15-minute retention rates (R = 0.969, R2 = 0.939), while the GLM values had a relatively low correlation (R = 0.566, R2 = 0.320). These findings indicate that the developed model can be used to evaluate liver reserve function with comparable performance to the ICG clearance test. Furthermore, the XGBoost model exhibited superior prediction compared with the GLM. Hence, the XGBoost model developed using machine learning can be utilized to evaluate liver reserve function from eight biochemical indicators that are closely related to liver function, commonly used clinically, and easier to obtain than ICG clearance measures. Conclusions The results predicted by the XGBoost model were highly accurate when compared with the results of the actual ICG test, demonstrating the strong practical clinical value of the model.

P1302 : Evidence for the ICG-clearance-test as a relevant predictor of post hepatectomy liver failure

2015 ◽  
Vol 62 ◽  
pp. S327-S328
Author(s):  
S. Haegele ◽  
F. Offensperger ◽  
E. Lahner ◽  
A. Assinger ◽  
E. Fleischmann ◽  
...  
Keyword(s):  
Liver Failure ◽  
Icg Clearance ◽  
Icg Clearance Test ◽  
Clearance Test
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