Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Model for predicating lung cancer risks for people suffering from pulmonary nodules among China urban population on basis of CT (computed tomography) images and biomarker spectrums

A biomarker and biomarker technology, applied in the field of lung cancer risk prediction model, can solve the problem of no reports in the Chinese population, and achieve the effect of simple expression level

Active Publication Date: 2016-06-29
ZHONGSHAN HOSPITAL FUDAN UNIV
View PDF2 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, a pulmonary nodule malignant risk prediction model for European and American populations has been invented internationally, but a pulmonary nodule malignant risk model for Chinese populations has not been reported

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Model for predicating lung cancer risks for people suffering from pulmonary nodules among China urban population on basis of CT (computed tomography) images and biomarker spectrums
  • Model for predicating lung cancer risks for people suffering from pulmonary nodules among China urban population on basis of CT (computed tomography) images and biomarker spectrums
  • Model for predicating lung cancer risks for people suffering from pulmonary nodules among China urban population on basis of CT (computed tomography) images and biomarker spectrums

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0041] A lung cancer risk prediction model based on CT images and biomarker profiles for Chinese urban population with pulmonary nodules, consisting of biomarkers and their enzyme-labeled antibodies, carbonate buffer solution with a pH value of 9.6, and pH value of 7.4 Phosphate buffer, serum protein diluent, stop solution, tetramethylbenzidine substrate solution, normal human serum and positive control serum;

[0042] The biomarkers include gastrin releasing propeptide, carcinoembryonic antigen, fragment of cytokeratin 19 and squamous cell carcinoma antigen.

[0043] The carbonate buffer solution with a pH value of 9.6 was obtained by adding 1.59 g of sodium carbonate and 2.93 g of sodium bicarbonate to 1 L of distilled water. The phosphate buffer solution with the pH value of 7.4 is 0.2 gram potassium dihydrogen phosphate, 2.9 gram sodium hydrogen phosphate dodecahydrate, 8.0 gram sodium chloride, 0.2 gram potassium chloride, 0.5 mL Tween-20 to 1L distilled water derived. Th...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a model for predicating lung cancer risks for people suffering from pulmonary nodules among the China urban population on the basis of CT (computed tomography) images and biomarker spectrums. The model comprises biomarkers, enzyme-labeled antibodies of the biomarkers, a carbonate buffer solution with the pH value being 9.6, a phosphate buffer solution with a pH value being 7.4, a serum protein diluent, a stop solution, a tetramethyl benzidine substrate solution, serum of normal people and positive control serum; the biomarkers are four biomarkers including pro-gastrin-releasing peptides, carcino-embryonic antigens, fragments of cytokeratin 19 and squamous-cell carcinoma antigens and are combined with CT imageology parameters and other clinical indexes. The model can assist in screening of lung cancer.

Description

technical field [0001] The invention relates to the field of biotechnology, in particular to a lung cancer risk prediction model for Chinese urban population with pulmonary nodules based on CT images and biomarker spectrum. Background technique [0002] Lung cancer is the most common and deadly cancer worldwide. The morbidity and mortality of lung cancer rank first among all malignant tumors in my country. According to the statistics of The International Agency for Research on Cancer (IARC) of the World Health Organization, the incidence of lung cancer in my country in 2008 was 35 per 100,000 people, and the agency estimated that by 2025, there will be 1 million new cases of lung cancer in my country every year. According to the 2010 Health Statistical Yearbook of the Ministry of Health, as of 2009, the national lung cancer mortality rate was 30.83 / 100,000 people, which was higher than the second highest mortality rate of liver cancer by more than 4 / 100,000 people. Althoug...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G01N23/04G01N33/68G01N33/574
CPCG01N23/04G01N33/57423G01N33/68
Inventor 白春学杨达伟周建
Owner ZHONGSHAN HOSPITAL FUDAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com