KR101894098B1 - Method for predicting risk of onset of cardio-metabolic disease - Google Patents
Method for predicting risk of onset of cardio-metabolic disease Download PDFInfo
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Abstract
The present invention relates to a method of providing information for predicting the risk of cardio-metabolic disease of a subject by measuring intestinal 18 F-FDG uptake.
Description
The present invention relates to a method for providing information for predicting a subject having a high risk of developing a cardiovascular disease.
As dietary habits and lifestyle changes and aging, diabetes related diseases are increasing steadily every year. Heart disease is consistently high in the cause of death in Korea, and according to the National Statistical Office (NSO) survey, it ranked second after cancer.
Cardio-metabolic risk (CMR) is a factor that increases the risk of developing atherosclerosis-related diseases. Coronary risk factors include factors such as abdominal obesity, body mass index (BMI), age, sex, hypertension, insulin resistance, cholesterol, triglycerides, LDL, HDL, dyslipidemia and smoking as measured by waist circumference.
On the other hand, positron emission tomography (PET) is a method of detecting radioactive isotopes that emit positron to various basic metabolites and detecting extinction radiation generated by interaction between positron and substance after administration to human body It means a technique to create a tomographic image.
Radioisotopes used for PET is 18 F-FDG (Fluorodeoxy glucose) , 18F-FLT (Fluorothymidine), 18 F-FP-CIT (Fluoropropyl carbomethoxy-3b- (4-iodophenyltropane)), 11 C- methionine, 11 C -Acetate, 11 C-PIB (Pittsburgh compound B), 13 N-ammonia, and 82 Rb, among which 18 F-FDG is the most widely used.
PET was originally developed for the visualization of tumors because tumor cells absorb more 18 F-FDG than normal cells. However, the application of PET is gradually expanding and is now being used in non-tumor pathology physiology. Accordingly, there is a growing interest in the diversity of absorption of 18 F-FDG in general subjects.
In view of this background, the present inventors have for the first time discovered that there is a correlation between intestinal intake of 18 F-FDG and cardiovascular risk factors, and completed the present invention.
It is an object of the present invention to provide an information providing method for predicting a subject having a high risk of developing a cardio-metabolic disease.
In one aspect of the present invention, when the intake of 18 F-FDG (Fluorodeoxy glucose) in a subject's PET (Positron emission tomography) data is higher than the intake of 18 F-FDG in the liver, And determining that the risk of developing cardio-metabolic disease is high, comprising the step of determining the risk of developing cardio-metabolic disease.
In the information providing method of the present invention, 18 F-FDG refers to a compound having a structure represented by the following general formula (1) wherein oxygen at the 2-position of glucose is substituted with 18 F.
[Chemical Formula 1]
In the information providing method of the present invention, PET (positron emission tomography) examination can be used for the measurement of 18 F-FDG in the intestines or liver, and preferably PET / CT (computed tomography) Can be used.
The PET test is a nuclear medicine testing method that can display physiological, chemical, and functional images of the human body in three dimensions using a radioactive material that emits positron. Specifically, PET uses radioactive isotope-labeled compounds such as 18 F, 11 C, 13 N, and 15 O as radioactive isotopes to trace the biochemical changes of the body using compounds such as glucose, amino acid, fatty acid, It is an invasive diagnostic technique. This PET test is mainly used for evaluating cancer test, brain disease and the like, but the present invention is used to provide information for predicting the risk of developing a deep vein disease in a subject.
In addition, the PET / CT inspection is an inspection method for obtaining a more accurate image by attenuating and correcting a PET image by CT. The CT scan is an inspection method for constructing a cross-sectional image by exposing a subject to a trace amount of X-rays and then calculating a relative X-ray absorption coefficient of each tissue using a computer.
In the information providing method of the present invention, the subject refers to all animals including humans, preferably a breast cancer patient, more preferably a female breast cancer patient, most preferably suffering from a deep vein disease It can be a female breast cancer patient who is not.
The degree of intestinal 18 F-FDG intake and the level of 18 F-FDG uptake in the liver are preferably determined by measuring the standardized uptake value (SUV) in the PET data of the subject. The measurement of SUV is described, for example, in Med. Phys. 39 (6), June 2012, and the like, but the present invention is not limited thereto.
Specifically, the SUV is a software calculation of the metabolic hypertrophy portion detected in a PET image, which means the radiation emitted per gram of tissue divided by the amount of radioactivity administered per kilogram of body weight.
In the present invention, the cardiovascular disease may be cardiovascular disease or diabetes, and specifically, it may be any one selected from the group consisting of hypertension, ischemic heart disease, atherosclerosis, cerebrovascular disease, dyslipidemia and diabetes.
Prediction in the present invention means predicting a medical result in advance, and means for predicting the onset of a deep vein disease for the purpose of the present invention.
In the present invention, the cardio-metabolic risk (CMR) factor refers to a group of factors that increase the risk of cardiovascular disease and diabetes, including age; gender; BMI (body mass index); Abdominal obesity; Blood sugar testing (BST); Or serum triglycerides, cholesterol, high density lipoprotein (HDL), or low density lipo protein (LDL).
In a specific embodiment of the present invention embodiments, by comparing the 18 F-FDG uptake in the liver and the intestine 18 F-FDG uptake of the subject, classifying the intake of the 18 F-FDG in the entire lowest patients with low-fed groups and he said at least one sheet fraction within the 18 F-FDG uptake is higher than 18 F-FDG uptake in the liver or the equivalent intake patients were divided into groups. Was in the univariate regression results of the analysis, the center metabolic risk factors, BMI (body mass index) and triglycerides are enteric 18 F-FDG uptake and a significant positive correlation (positive correlation) against the shim metabolic risk factors of the subject .
In another embodiment of the present invention, the different lengths of the fractions were placed in a three-dimensional volume of interest (VOI) and the Standardized Uptake Value (SUV) was measured in different long segments. In addition, total bowel (TB) SUVs were measured by averaging different SUVs in different intestinal fractions. Multiple regression analysis showed that BMI and triglycerides were independent predictors of TB maximum SU ( max ) and TB mean SU (SUV).
The maximum standard intake factor (SUV max ) means a maximum value of the standard intake factor, and the average standard intake factor (SUV mean ) means a threshold value limit of 40% SUV max .
The 18 F-FDG uptake pattern of the present invention has a significant positive correlation with cardiovascular risk factors, particularly BMI and triglycerides, and thus can be useful for predicting subjects at high risk for the development of cardiovascular disease.
According to the present invention, it is possible to provide information that can predict a subject having a high risk of developing a deep vein disease.
Fig. 1 (a) is an image of PET / CT images of 18 F-FDG uptake in women with low-dose breast cancer, and (b) PET / CT images of 18 F-FDG uptake in female breast cancer patients .
FIG. 2 is a graph showing correlation between TB SUV max and coronary risk factors. FIG. 2B is a graph showing correlation between a, b, B, c, triglyceride, cholesterol, LDL and f HDL.
Hereinafter, preferred embodiments of the present invention will be described in order to facilitate understanding of the present invention. However, these embodiments are provided only for the purpose of easier understanding of the present invention, and the scope of the present invention is not limited by the following description.
EXAMPLES Thyroid metabolic risk factors and intestinal 18 Correlation between F-FDG uptake
1. Selection of experiment subjects
We retrospectively reviewed the FDG PET / CT database of Ewha Womans University Women's Cancer Center and selected a breast cancer group to obtain a sufficient number of subjects. This experiment was approved by the institutional review board (IRB) of Mokdong Hospital, Ewha Womans University. All the procedures, including human participation, in this experiment followed the IRB Code of Ethics and followed the 1964 Helsinki Declaration and subsequent amendments or equivalent ethical codes. All patients received consent documents via IRB, and all data were anonymized before analysis.
A database of 425 female breast cancer patients who had undergone 18 F-FDG PET / CT for initial screening between 2012 and 2015 was used as a database and the results were compared with those of 18 F-FDG The purpose of this study was to investigate the association between intestinal intake and cardio-metabolic risk (CMR) factors, so 99 patients with diabetes or hypertension were excluded.
A total of 326 non-diabetic and non-hypertensive patients were included in the final statistical analysis. All of the 326 patients were suffering from inflammatory diseases such as inflammatory bowel disease, infectious colitis, cholangitis, rheumatism, Because of this problem, no medication was administered. In addition, no patients underwent neoadjuvant chemotherapy prior to PET / CT.
2. Measurement of cardiovascular risk factors
On the medical chart, the social viability of smoking or drinking was examined. Body mass data, including height and weight, were used for PET examinations at the PET center. Body mass index (BMI) was calculated using height and weight.
Standard clinical data were reviewed prior to initial treatment and triglyceride, cholesterol high density lipoprotein (HDL) and low density lipoprotein (LDL) were measured from the lipid profile.
3. Intestines 18 Measurement of F-FDG uptake
For 18 F-FDG PET / CT, we fasted for at least 6 hours, and then injected intravenously with 5.18 MBq / kg FDG and taken 1 hour later. Before the administration of FDG, glucose levels were measured and found to be below 140 mg / dL. Non-contrast CT was first taken and PET images were taken from the cranium to the thigh (Siemens Biograph mCT 128 slice CT) (Siemens Medical Solutions, Erlangen, Germany). Low dose CT (CARE Dose system, Siemens Medical Solutions, Erlagen, Germany) was photographed to perform attenuation correction. The spatial resolution of the PET center was 2.0 mm FWHM (full width at half maximum) in the transverse and axial directions. 3D emission scans and 2 min scan / bed position x 5-7 positions were obtained as parameters for PET images. PET images were acquired using a 3.0 ×
Intestinal 18 F-FDG uptake was evaluated in two read self qualitative and quantitative. The analysis was performed by consensus, and the analysts were strictly blocked from the coronary risk factor data.
For qualitative analysis, the patients were divided into intestinal 18 F-FDG uptake of high and low patient patient. Between the uptake of 18 F-FDG in the entire section above or equal to the patient than the cross-classification, and at least one fraction intestinal 18 F-FDG uptake low patients with low intake group compared with the intake of 18 F-FDG in High intake group.
For quantitative analysis, the maximum and average normalized intake values (SUV max and SUV mean ) in different intestinal fractions were measured after placing in a three-dimensional volume of interest (VOI). The SUV mean was measured as the threshold limit of 40% SUV max . Intestinal 18 F-FDG uptake in the small intestine was measured in the duodenum third region, plant and distal ring president. 18 F-FDG uptake in the large intestine was measured in the cecum, right ascending aorta, left colonic and descending colon-S colon junctions. Then, SUVs at different bowel sites were averaged and measured for total bowel (TB SUV max and TB SUV mean ).
4. Coronary risk factors and intestinal 18 Correlation analysis between F-FDG uptake
4-1. Statistical method
Data were expressed as 95% confidence interval (CI), and significance was determined when p value was less than 0.05. All statistical analyzes were performed using SPSS software version 18.0 (SPSS Inc., Chicago, IL, USA). The association between anthropometric data (key, weight and BMI), human data (age), and clinical test data (BST and lipid profiles) and intestinal 18 F-FDG uptake was assessed using an independent t- Pearson correlation was used for continuous SUV. Regression analysis was used to measure the association between each coronary risk factor and intestinal 18 F-FDG uptake. Multivariate regression analysis was then performed to measure the independent effects of each variable on intestinal 18 F-FDG uptake.
4-2. Patient data
None of the 326 patients had smoking or alcohol history. The mean age of the patients was 47.2 ± 9.2 years (range 28-79) and the mean height, weight, and BMI were 158.3 ± 5.4 cm (range 144.0 - 173.0), 57.6 ± 8.2kg 3.2 (range 15.1 - 34.8). The blood sugar testing (BST) values were 99.0 ± 10.9 mg / dl (range 75.0 - 188.0) and the triglyceride and cholesterol levels were 96.9 ± 54.8 mg / dl (range 10.0 - 393.0) and 191.5 ± 36.6 mg / - 345.0). HDL and LDL levels were 53.2 ± 22.6 mg / dl (range 26.0 to 340.0) and 113.4 ± 36. mg / dl (range 37.0 - 237.0).
4-3. Qualitative analysis
Intestinal 18 to F-FDG uptake based on a visual rating, were included in the group are low intake of patients 100 (30.7%), a patient of 226 patients (69.3%) and was included in the intake group. In the core metabolic risk factors, age (p = 0.004), when the BMI (p <0.001), and TG (p <0.001), there was a significant difference depending on the visual rating of the intestine 18 F-FDG uptake. Detailed data are shown in Table 1.
Table 1 enteric 18 F-FDG-core metabolic risk factors according to a visual rating of the intake
In univariate regression analysis, high age ( p = 0.009), high BMI ( p <0.001) and high triglyceride ( p = 0.001) were significant factors for the increase of intestinal 18F-FDG uptake in PET. Cholesterol levels showed ambiguous significance ( p = 0.077).
Detailed data are shown in Table 2. BMI and triglycerides were independent predictors of intestinal 18 F-FDG uptake ( p = 0.027, p < 0.05 ), respectively, when multiple regression analysis was performed for three significant variables and univariate analysis was performed for ambiguous variables p = 0.023). A typical example of the core according to the difference in the metabolic risk factors visual rating of the intestine 18 F-FDG uptake in PET are shown in Fig. Fig. 1 (a) is a 18- F-FDG PET / CR image of a 57-year-old female breast cancer patient, and the intake of 18 F-FDG in the intestine was lower than the liver. The BMI of this patient was 20.0 and the triglyceride level was 45 mg / dL. Fig. 1 (b) is a 18- F-FDG PET / CT image of a 64-year-old female breast cancer patient with high 18 F-FDG uptake in the intestine. The patient had a BMI of 27.3 and a triglyceride level of 393 mg / dL.
[Table 2] Univariate and multivariate logistic regression analysis
4-4. Quantitative analysis
The overall TB SUV max is 2.0 ± 0.5 (range 1.2 to 4.0) and the TB SUV mean is 1.7 ± 0.4 (range 1.0 to 3.1). According to Pearson correlation, TB SUV max is age (r = 0.203 and p <0.001, Fig. 2a), BMI (r = 0.373 and p <0.001, Figure 2b), triglycerides (r = 0.338 and p <0.001, Fig. 2c), cholesterol (r = 0.148 and p = 0.008, Fig. 2d) and LDL (r = 0.143 and p = 0.024, Fig. 2e) and exhibited a significant positive correlation, HDL (r = -0.147 p = 0.022 and , Fig. 2f). In addition, the TB SUV mean was significantly lower in the age group (r = 0.175 and p = 0.001), BMI (r = 0.333 and p <0.001), triglyceride (r = 0.321 and p <0.001), cholesterol (r = 0.151 and p = And LDL (r = 0.136 and p = 0.0330), respectively, and showed a significant negative correlation with HDL (r = -0.131 and p = 0.040).
Univariate regression analysis, high age (p <0.001), higher BMI (p <0.001), high triglycerides (p <0.001), high cholesterol (p = 0.008), low HDL (p = 0.022), and high LDL (p = 0.024) was a significant factor in the increase of TB SUV max in PET. Further, in the TB SUV mean, age (p = 0.001), BMI ( p <0.001), TG (p <0.001), cholesterol (p = 0.007), HDL ( p = 0.040), and LDL (p = 0.033) This was a significant factor. BMI and triglycerides were higher in the TB SUV max ( p = 0.006 and p = 0.004) and TB SUV mean ( p = 0.007 and p = 0.004) in PET, respectively, when multiple regression analysis was performed on the six significant variables in the univariate analysis 0.017). Detailed data are shown in Table 3.
[Table 3] Univariate and Multivariate Regression Analysis Results
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