Rural gastric cancer primary screening system and method based on oral ultrasound contrast examination

Abstract

The invention discloses a rural gastric cancer primary screening system and method based on oral ultrasound contrast examination, and the system comprises a data collection module, a model building module, and a risk prediction module, the data collection module is used for collecting stomach imaging data and health condition investigation results of the oral ultrasound contrast examination of asymptomatic people in rural areas; the model building module is used for building a gastric cancer risk prediction model, comparing each parameter result of the subject with each parameter threshold value in the gastric cancer risk prediction model to obtain each parameter score, and adding total scores to obtain a subject risk prediction score; and the risk prediction module is used for obtaining a gastric cancer risk prediction result of the subject according to the scoring condition of the subject in the gastric cancer risk prediction model. The method can effectively determine the gastric cancer high-risk population in the asymptomatic population in the rural area, improves the gastric cancer detection rate, and can further improve the current gastric cancer screening situation in the rural area in China as a suitable technology.

Description

Technical Field

[0001] The present invention relates to the field of gastric cancer screening, and in particular to a primary screening system and method for rural gastric cancer based on oral ultrasound contrast examination. Background Art

[0002] Early screening of gastric cancer is of great significance for improving the cure rate of gastric cancer and improving the prognosis of patients. At present, gastroscopy is the standard method for gastric cancer screening and diagnosis, but its application as a general screening method for gastric cancer is limited by factors such as high examination costs, insufficient professional and technical personnel, and patients' concerns about invasive examinations, especially in remote and backward rural areas. The primary screening combined with diagnostic examination strategy can identify high-risk groups for gastric cancer through pre-screening methods and carry out targeted diagnostic gastroscopy examinations, which can reduce the demand for gastroscopy in low-risk groups, improve the efficiency of gastric cancer screening, and reduce medical costs. Oral ultrasound angiography is an easy-to-operate clinical examination technology with the characteristics of non-invasiveness, low cost, simplicity and ease of use. It has been proven to have good gastric lesion detection capabilities. By combining with health questionnaires, a rural gastric cancer primary screening system based on oral ultrasound angiography can be constructed, which can be used as a primary screening method for gastric cancer that is suitable for my country's national conditions, has wide coverage, is low-cost, and is highly efficient, and can improve the efficiency of gastric cancer screening in rural areas. Summary of the invention

[0003] The object of the present invention is to provide a primary screening system and method for rural gastric cancer based on oral ultrasound contrast examination to solve the problems raised in the above background technology.

[0004] To achieve the above-mentioned purpose, one aspect of the present invention provides a rural gastric cancer primary screening system based on oral ultrasound contrast examination, including a data acquisition module, a model building module, and a risk prediction module, wherein:

[0005] The data collection module is used to collect gastric imaging data and health status survey results of asymptomatic people in rural areas through oral ultrasound contrast examination;

[0006] A model building module is used to build a gastric cancer risk prediction model, compare the results of each parameter of the subject with the threshold of each parameter in the gastric cancer risk prediction model, obtain the score of each parameter, and add up the total score to obtain the risk prediction score of the subject;

[0007] The risk prediction module is used to obtain the subject's gastric cancer risk prediction result based on the subject's score in the gastric cancer risk prediction model.

[0008] Furthermore, the gastric imaging data include gastric wall thickness, changes in gastric wall hierarchical structure, gastric wall niche shadows, low-echo space-occupying lesions, etc.; the health status survey includes personal situation, health status, lifestyle, and diet.

[0009] Furthermore, the gastric cancer prediction model incorporates six risk factors: positive oral ultrasound contrast diagnosis, maximum gastric wall thickness ≥ 7 mm, age ≥ 67 years, chronic diarrhea, occasional consumption of fish and frequent consumption of red meat.

[0010] Furthermore, the scoring criteria for each parameter are:

[0011] A positive oral ultrasound contrast diagnosis was defined as 3 points and a negative one as 0 points;

[0012] The maximum gastric wall thickness was defined as ≥7 mm as 2 points and <7 mm as 0 points;

[0013] The subjects’ age was defined as 1 point if they were ≥67 years old and 0 point if they were <67 years old;

[0014] The definition was that the presence of chronic diarrhea was 1 point, and the absence was 0 points;

[0015] Frequent consumption of fish was defined as 0 points, and occasional consumption of fish was defined as 1 point;

[0016] Frequent consumption of red meat was defined as 1 point, and occasional consumption of red meat was defined as 0 point;

[0017] After adding up the total score, a score between 0 and 3 indicates a low risk of gastric cancer, and a score greater than 3 indicates a high risk of gastric cancer.

[0018] Another aspect of the present invention provides a primary screening method for rural gastric cancer based on oral ultrasound contrast examination, comprising the following steps:

[0019] Step S1, collecting gastric imaging data and health status survey results of oral ultrasound contrast examination of asymptomatic people in rural areas;

[0020] Step S2, constructing a gastric cancer risk prediction model, comparing the results of each parameter of the subject with the threshold of each parameter in the gastric cancer risk prediction model, obtaining a score for each parameter, and adding up the total score to obtain a risk prediction score for the subject;

[0021] Step S3, obtaining a gastric cancer risk prediction result for the subject according to the subject's score in the gastric cancer risk prediction model.

[0022] Furthermore, the gastric imaging data include gastric wall thickness, changes in gastric wall hierarchical structure, gastric wall niche shadows, low-echo space-occupying lesions, etc.; the health status survey includes personal situation, health status, lifestyle, and diet.

[0023] Furthermore, the gastric cancer prediction model incorporates six risk factors: positive oral ultrasound contrast diagnosis, maximum gastric wall thickness ≥ 7 mm, age ≥ 67 years, chronic diarrhea, occasional consumption of fish and frequent consumption of red meat.

[0024] Furthermore, the scoring criteria for each parameter are:

[0025] A positive oral ultrasound contrast diagnosis was defined as 3 points and a negative one as 0 points;

[0026] The maximum gastric wall thickness was defined as ≥7 mm as 2 points and <7 mm as 0 points;

[0027] The subjects’ age was defined as 1 point if they were ≥67 years old and 0 point if they were <67 years old;

[0028] The definition was that the presence of chronic diarrhea was 1 point, and the absence was 0 points;

[0029] Frequent consumption of fish was defined as 0 points, and occasional consumption of fish was defined as 1 point;

[0030] Frequent consumption of red meat was defined as 1 point, and occasional consumption of red meat was defined as 0 point;

[0031] After adding up the total score, a score between 0 and 3 indicates a low risk of gastric cancer, and a score greater than 3 indicates a high risk of gastric cancer.

[0032] Compared with the prior art, the present system and method have the following advantages:

[0033] This method can effectively identify high-risk groups for gastric cancer in asymptomatic groups in rural areas. The results showed that the observed incidence of gastric cancer in people defined as high-risk for gastric cancer by the risk prediction model was 601.85 / 100 000, while the observed incidence of gastric cancer in people with low risk for gastric cancer was 4.56 / 100 000. The risk prediction model had a sensitivity of 72.2%, a specificity of 98.2%, a positive predictive value of 6.0%, and a negative predictive value of 100.0% for predicting gastric cancer. The high-risk group for gastric cancer predicted by this method had a significantly increased incidence of gastric cancer, which strongly suggested the necessity of diagnostic gastroscopy, effectively improved the detection rate of gastric cancer, and could be used as an appropriate technology to improve the current status of gastric cancer screening in rural areas of China. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flow chart of the system and method for primary screening of gastric cancer in rural areas based on oral contrast-enhanced ultrasound examination. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] like Figure 1 The flowchart of the method of the present invention is shown. The embodiment of the present invention provides a primary screening system and method for rural gastric cancer based on oral ultrasound contrast examination. The specific steps are as follows:

[0037] Step S1, asymptomatic residents of a rural community in a town in Chongming District, Shanghai were selected as subjects to undergo a gastric cancer pre-screening program including oral ultrasound contrast examination and health questionnaire survey. Subjects were required to meet the following inclusion criteria: age > 40 years old; male or female; permanent residents of the community and living for more than 6 months; voluntary participation in the program. The main exclusion criteria included: previous diagnosis of gastric cancer; conditions that affect swallowing function; severe mental illness; migrant population.

[0038] In the first phase, a total of 14,969 subjects completed the pre-screening program, of which 14,800 had negative oral ultrasound contrast examinations and entered follow-up. Oral ultrasound contrast examinations of 169 subjects were positive, and 145 subjects underwent further gastroscopy, and a total of 16 cases of gastric cancer were diagnosed. During the 1-year follow-up period, a total of 6 cases of gastric cancer were diagnosed in the follow-up population. Therefore, the subjects can be divided into a gastric cancer group (22 cases) and a non-gastric cancer group (14,947 cases). The above population was used as a training set for the construction of a gastric cancer risk model. The R statistical software was used to analyze the correlation between the parameters obtained in oral ultrasound contrast examinations and health questionnaires and gastric cancer, and to screen for gastric cancer-related risk factors. The post-screening characteristics include six risk factors: oral ultrasound contrast diagnosis, maximum gastric wall thickness, age, chronic diarrhea, frequency of fish consumption, and frequency of red meat consumption.

[0039] Through oral contrast-enhanced ultrasound examination, parameters obtained include oral contrast-enhanced ultrasound diagnosis, maximum gastric wall thickness and gastric space-occupying lesions.

[0040] A total of 375 parameters including patient demographics, smoking and drinking history, dietary habits, exercise status, past medical history, and family history were obtained through a health questionnaire.

[0041] Step S2, use univariate and multivariate analysis to screen and obtain gastric cancer risk factors, give corresponding scores to risk factors through regression analysis, build a gastric cancer risk prediction model, compare the corresponding risk factor results of the subjects with the parameter cutoff values ​​in the gastric cancer prediction model, obtain the risk scores of each subject, and divide the subjects into a high-risk group for gastric cancer and a low-risk group for gastric cancer.

[0042] Before step S2, it is necessary to obtain a training data set, and use univariate and multivariate analysis to screen and obtain gastric cancer risk factors. Six gastric cancer-related risk factors (see Table 1) including oral ultrasound contrast diagnosis, maximum gastric wall thickness, age, chronic diarrhea, frequency of fish consumption, and frequency of red meat consumption were obtained to construct a clinical prediction model and determine the cutoff value of the clinical risk prediction model.

[0043] Table 1 Univariate and multivariate regression analysis to determine risk factors associated with gastric cancer

[0044]

[0045]

[0046]

[0047] where CI is confidence interval; OCTU is oral contrast transabdominal ultrasonography; and OR is odds ratio.

[0048] The scores of each parameter were determined by regression analysis as follows (see Table 2): 1) Positive oral ultrasound contrast diagnosis: defined as any positive finding in oral ultrasound contrast examination, including but not limited to thickening of the gastric wall, unclear gastric wall layers, niches, hypoechoic masses, etc.; positive oral ultrasound contrast diagnosis was 3 points and negative was 0 points; 2) Maximum gastric wall thickness ≥7 mm: defined as the maximum thickness of the gastric wall at any position ≥7 mm during oral ultrasound contrast examination; ≥7 mm was 2 points and <7 mm was 0 points; 3) Age: defined as the subject's age ≥67 years; ≥67 years was 1 point and <67 years was 0 points; 4) Chronic diarrhea: defined as "yes" or "no"; "yes" was 1 point and "no" was 0 points; 5) Fish consumption: defined as "frequent" or "occasionally" consumed; "frequent" was 0 points and "occasionally" was 1 point; 6) Red meat consumption: defined as "frequent" or "occasionally" consumed; "frequent" was 1 point and "occasionally" was 0 points.

[0049] Table 2 Risk factors and scores related to gastric cancer

[0050]

[0051]

[0052] where CI is confidence interval; OCTU is oral contrast transabdominal ultrasonography; and OR is odds ratio.

[0053] According to the cutoff value of the clinical prediction model, the subjects' gastric cancer risk was divided into two groups:

[0054] Low-risk group: clinical prediction model cutoff value 0-3 points

[0055] High-risk group: clinical prediction model cutoff value >3 points

[0056] The subjects in the high-risk group had a higher risk of gastric cancer. The high-risk group predicted by the model was recommended to undergo further diagnostic gastroscopy. The accuracy of this clinical prediction model in predicting gastric cancer was 85.2%, the AUC value was 0.884, the sensitivity was 72.2%, the specificity was 98.2%, the positive predictive value was 6.0%, and the negative predictive value was 100.0%.

[0057] Another 5488 subjects were included as a validation set, 250 subjects had positive oral ultrasound contrast examination, 145 of whom underwent gastroscopy, and a total of 8 cases of gastric cancer were diagnosed. By comparing the above parameters of the subjects with the cutoff values ​​of the clinical prediction model, the subjects were assigned to low-risk and high-risk groups and compared with the diagnosis of gastric cancer in the subjects. The accuracy of this clinical prediction model in predicting gastric cancer in the validation set was 97.8%, the AUC value was 0.992, the sensitivity was 100.0%, the specificity was 95.7%, the positive predictive value was 3.3%, and the negative predictive value was 100.0% (see Table 3).

[0058] Table 3 Gastric cancer risk assessment of training set and validation set

[0059]

[0060] Among them, EGC is early gastric cancer.

[0061] Step S3, obtaining the predicted risk of gastric cancer for the subject according to the grouping of the subject in the clinical prediction model, and recommending a diagnostic gastroscopy.

[0062] For the subjects in the validation set, among the 129 subjects with a score of 4, 1 case of gastric cancer was diagnosed; among the 27 subjects with a score of 6, 9 cases of gastric cancer were diagnosed; among the 10 subjects with a score of 7, 2 cases of gastric cancer were diagnosed; and among the 1 subject with a score of 9, 1 case of gastric cancer was diagnosed (see Table 3);

[0063] For the test machine subjects, among the 79 subjects with a score of 5, 2 cases of gastric cancer were diagnosed; among the 18 subjects with a score of 6, 1 case of gastric cancer was diagnosed; among the 20 subjects with a score of 7, 4 cases of gastric cancer were diagnosed; and among the 2 subjects with a score of 8, 1 case of gastric cancer was diagnosed (see Table 3).

[0064] The observed incidence of gastric cancer in the high-risk group defined by the risk prediction model was 601.85 / 100 000, while that in the low-risk group was 4.56 / 100 000. The risk prediction model had a sensitivity of 72.2%, a specificity of 98.2%, a positive predictive value of 6.0%, and a negative predictive value of 100.0% for predicting gastric cancer. The high-risk group predicted by this method had a significantly increased incidence of gastric cancer, which strongly suggested the necessity of diagnostic gastroscopy, effectively improved the detection rate of gastric cancer, and could be used as an appropriate technology to improve the current status of gastric cancer screening in rural areas of China.

[0065] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A primary screening system for gastric cancer in rural areas based on oral ultrasound contrast examination, characterized by: It includes data collection module, model building module and risk prediction module, among which: The data collection module is used to collect gastric imaging data and health status survey results of asymptomatic people in rural areas through oral ultrasound contrast examination; A model building module is used to build a gastric cancer risk prediction model, compare the results of each parameter of the subject with the threshold of each parameter in the gastric cancer risk prediction model, obtain the score of each parameter, and add up the total score to obtain the risk prediction score of the subject; The risk prediction module is used to obtain the subject's gastric cancer risk prediction result based on the subject's score in the gastric cancer risk prediction model.

2. The rural gastric cancer primary screening system based on oral ultrasound contrast examination according to claim 1 is characterized in that: The gastric imaging data include gastric wall thickness, changes in gastric wall hierarchical structure, gastric wall niche shadows, and hypoechoic space-occupying lesions; the health status survey includes personal situation, health status, lifestyle, and diet.

3. The rural gastric cancer primary screening system based on oral ultrasound contrast examination according to claim 1 is characterized in that: The gastric cancer risk prediction model included six risk factors: positive oral ultrasound contrast diagnosis, maximum gastric wall thickness ≥ 7 mm, age ≥ 67 years, chronic diarrhea, occasional consumption of fish and frequent consumption of red meat.

4. The rural gastric cancer primary screening system based on oral ultrasound contrast examination according to claim 3 is characterized in that: The scoring criteria for each parameter are: A positive oral ultrasound contrast diagnosis was defined as 3 points and a negative one as 0 points; The maximum gastric wall thickness was defined as ≥7 mm as 2 points and <7 mm as 0 points; The subjects’ age was defined as 1 point if they were ≥67 years old and 0 point if they were <67 years old; The definition was that the presence of chronic diarrhea was 1 point, and the absence was 0 points; Frequent consumption of fish was defined as 0 points, and occasional consumption of fish was defined as 1 point; Frequent consumption of red meat was defined as 1 point, and occasional consumption of red meat was defined as 0 point; The total score was added up to define a low risk of gastric cancer if the score was 0-3, and a score greater than 3 was defined as a high risk of gastric cancer.

5. A primary screening method for gastric cancer in rural areas based on oral ultrasound contrast examination, characterized in that: The following steps are involved: Step S1, collecting gastric imaging data and health status survey results of oral ultrasound contrast examination of asymptomatic people in rural areas; Step S2, constructing a gastric cancer risk prediction model, comparing the results of each parameter of the subject with the threshold of each parameter in the gastric cancer risk prediction model, obtaining a score for each parameter, and adding up the total score to obtain a risk prediction score for the subject; Step S3, obtaining a gastric cancer risk prediction result for the subject according to the subject's score in the gastric cancer risk prediction model.

6. The primary screening method for gastric cancer in rural areas based on oral ultrasound contrast examination according to claim 5, characterized in that: The gastric imaging data include gastric wall thickness, changes in gastric wall hierarchical structure, gastric wall niche shadows, and hypoechoic space-occupying lesions; the health status survey includes personal situation, health status, lifestyle, and diet.

7. The primary screening method for gastric cancer in rural areas based on oral ultrasound contrast examination according to claim 5, characterized in that: The gastric cancer risk prediction model included six risk factors: positive oral ultrasound contrast diagnosis, maximum gastric wall thickness ≥ 7 mm, age ≥ 67 years, chronic diarrhea, occasional consumption of fish and frequent consumption of red meat.

8. The primary screening method for gastric cancer in rural areas based on oral ultrasound contrast examination according to claim 5, characterized in that: The scoring criteria for each parameter are: A positive oral ultrasound contrast diagnosis was defined as 3 points and a negative one as 0 points; The maximum gastric wall thickness was defined as ≥7 mm as 2 points and <7 mm as 0 points; The definition of the subject's age was 1 point if the subject was ≥67 years old and 0 point if the subject was <67 years old; The definition was that the presence of chronic diarrhea was 1 point, and the absence was 0 points; Frequent consumption of fish was defined as 0 points, and occasional consumption of fish was defined as 1 point; Frequent consumption of red meat was defined as 1 point, and occasional consumption of red meat was defined as 0 point; After adding up the total score, a score between 0 and 3 indicates a low risk of gastric cancer, and a score greater than 3 indicates a high risk of gastric cancer.

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