Myocardial ischemia diagnosis and analysis system

Abstract

The invention discloses a myocardial ischemia diagnosis and analysis system, which comprises a physiological data module, an electrocardiogram monitoring module and a radiography module, and is used for acquiring related sign data of a patient by using various detection devices; the preliminary illness state analysis module is used for analyzing the patient symptoms obtained through detection; the myocardial ischemia qualitative judgment module is used for deeply analyzing data of patients with myocardial ischemia symptoms and qualitatively judging whether the patients are myocardial ischemia or not; the myocardial ischemia trend judgment module is used for comparing and analyzing data obtained by multiple times of detection of the patient qualitative to myocardial ischemia and judging whether the patient has the probability of myocardial infarction or other follow-up lesions or not; the diagnosis and treatment suggestion module is used for giving different diagnosis and treatment suggestions based on myocardial ischemia trend judgment of the patient; the myocardial ischemia diagnosis efficiency is improved, the workload of doctors is reduced, timely and accurate diagnosis service is provided for patients, and it is ensured that the illness state of the patients can be rapidly recognized and processed.

Description

Technical Field

[0001] The present application relates to the technical field of myocardial ischemia diagnosis and analysis, and in particular to a myocardial ischemia diagnosis and analysis system. Background Art

[0002] Myocardial ischemia is a pathophysiological state in which the heart is not supplied with enough blood and oxygen due to coronary artery stenosis, spasm or embolism. People at high risk of myocardial ischemia include patients with coronary heart disease, arrhythmias and other diseases. If not intervened in time, myocardial ischemia may further develop into severe ischemic heart disease. According to the severity of coronary heart disease, ischemic heart disease can be divided into multiple stages such as latent coronary heart disease, angina pectoris, myocardial infarction, ischemic cardiomyopathy and sudden death. The clinical symptoms of myocardial ischemia usually manifest as discomfort or pain in the precordial area. In severe cases, it may be accompanied by arrhythmias, heart failure, and even cause systemic symptoms such as dyspnea and impaired consciousness.

[0003] Early identification and timely treatment of myocardial ischemia are crucial to the patient's prognosis, especially when suspected myocardial ischemia is found during a physical examination or electrocardiogram. Patients should seek medical attention as soon as possible. However, existing myocardial ischemia diagnosis and analysis systems usually require doctors to study and analyze the examination data of each patient one by one to confirm whether myocardial ischemia exists and make diagnostic recommendations based on the patient's specific situation. This process is cumbersome and time-consuming, which not only wastes the doctor's precious time, but may also result in the patient's condition not being treated in a timely manner, delaying treatment.

[0004] Therefore, there is an urgent need for a system that can improve the efficiency of myocardial ischemia diagnosis to reduce the workload of doctors and provide patients with more timely and accurate diagnostic services to ensure that the patient's condition can be quickly identified and treated. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention aims to provide a myocardial ischemia diagnosis and analysis system to solve the problems raised in the above-mentioned background technology.

[0006] According to one aspect of the present application, a myocardial ischemia diagnosis and analysis system includes a physiological data module, an electrocardiogram monitoring module, an angiography module, a central control module, a preliminary condition analysis module, a myocardial ischemia qualitative determination module, a myocardial ischemia trend determination module, a diagnosis and treatment suggestion module, and a condition data storage module;

[0007] The physiological data module is connected to the central control module and is used to obtain patient-related physiological data using various detection devices;

[0008] The ECG monitoring module is connected to the central control module and is used to collect the patient's dynamic ECG signal in real time;

[0009] The imaging module is connected to the central control module and is used to obtain the patient's radionuclide imaging data using radionuclide ventriculography technology and radionuclide myocardial perfusion imaging technology;

[0010] The central control module is connected with the physiological data acquisition module, the electrocardiogram monitoring module, the angiography module, the preliminary condition analysis module, the myocardial ischemia qualitative determination module, the myocardial ischemia trend determination module, the diagnosis and treatment suggestion module, and the condition data storage module, and is used to control the normal operation of each module through the host;

[0011] The preliminary condition analysis module is connected to the central control module and is used to analyze the patient's symptoms obtained through the preliminary analysis program and summarize and generate a preliminary diagnosis table of symptom manifestations;

[0012] The myocardial ischemia qualitative determination module is connected to the central control module and is used to perform in-depth analysis on the electrocardiogram data and radionuclide angiography data of patients with myocardial ischemia symptoms through a qualitative analysis program, extract key information, and qualitatively determine whether it is myocardial ischemia;

[0013] The myocardial ischemia trend determination module is connected to the central control module and is used to compare and analyze the real-time dynamic electrocardiogram signals of patients identified as myocardial ischemia and the radionuclide angiography data obtained through multiple tests through a trend analysis program to determine whether the patient has a probability of myocardial infarction or other subsequent lesions;

[0014] The diagnosis and treatment suggestion module is connected to the central control module and is used to give different diagnosis and treatment suggestions based on the patient's myocardial ischemia trend determination;

[0015] The condition data storage module is connected to the central control module and is used to store the patient's physiological data, electrocardiogram data, radionuclide angiography data, preliminary diagnosis table of symptom manifestations, qualitative determination results and trends of myocardial ischemia, and diagnosis and treatment recommendations through the memory.

[0016] Preferably, the physiological data module includes:

[0017] A heart rate detection unit, used for detecting the patient's heart rate data through a heart rate detector;

[0018] A blood pressure detection unit, used to detect the patient's blood pressure data through a sphygmomanometer;

[0019] The respiratory rate detection unit is used to detect the patient's respiratory rate through a respiratory detector.

[0020] Preferably, the ECG monitoring module is used to collect the patient's real-time dynamic ECG signal through the ECG monitoring electrodes of the ECG monitor.

[0021] A myocardial ischemia diagnosis and analysis method of a myocardial ischemia diagnosis and analysis system, the myocardial ischemia diagnosis and analysis method comprising:

[0022] Step 1: Detect the patient's heart rate data through a heart rate detector; detect the patient's blood pressure data through a sphygmomanometer; detect the patient's respiratory rate through a respiratory detector; and collect the patient's real-time dynamic ECG signal through the ECG monitoring electrode of the ECG monitor;

[0023] Step 2, using radionuclide ventriculography and radionuclide myocardial perfusion imaging to obtain radionuclide angiography data of the patient;

[0024] Step 3: Analyze the patient's heart rate data, blood pressure data, respiratory rate, dynamic electrocardiogram and radionuclide angiography data obtained through the preliminary analysis program, and summarize and generate a preliminary diagnosis table of symptom manifestations;

[0025] Step 4: Conduct in-depth analysis of the ECG data and radionuclide angiography data of patients with symptoms of myocardial ischemia through a qualitative analysis program to extract key information and qualitatively determine whether it is myocardial ischemia;

[0026] Step 5: Compare and analyze the real-time dynamic electrocardiogram signals of patients diagnosed with myocardial ischemia and the radionuclide angiography data obtained through multiple tests through a trend analysis program to determine the probability of myocardial infarction or other subsequent lesions in the patients;

[0027] Step six, giving different diagnosis and treatment suggestions based on the patient's myocardial ischemia trend; storing the patient's physiological data, ECG signal data, radionuclide angiography data, preliminary diagnosis table of symptom manifestations, qualitative judgment results and trends of myocardial ischemia, and diagnosis and treatment suggestions in the memory.

[0028] The myocardial ischemia diagnosis and analysis system of the present application improves the efficiency of myocardial ischemia diagnosis, reduces the workload of doctors, and provides patients with more timely and accurate diagnosis services, ensuring that the patient's condition can be quickly identified and treated. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic diagram of the structure of a myocardial ischemia diagnosis and analysis system according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the contents of the present application easier to understand, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0031] like Figure 1As shown, a myocardial ischemia diagnosis and analysis system is characterized in that it includes a physiological data module, an electrocardiogram monitoring module, an angiography module, a central control module, a preliminary condition analysis module, a myocardial ischemia qualitative determination module, a myocardial ischemia trend determination module, a diagnosis and treatment suggestion module and a condition data storage module; the physiological data module is connected to the central control module, and is used to obtain patient-related physiological data using various detection equipment; specifically, the physiological data module includes: a heart rate detection unit, which is used to detect the patient's heart rate data through a heart rate detector; a blood pressure detection unit, which is used to detect the patient's blood pressure data through a sphygmomanometer; and a respiratory rate detection unit, which is used to detect the patient's respiratory rate through a respiratory detector.

[0032] The ECG monitoring module is connected to the central control module, and collects the patient's real-time dynamic ECG signals through the ECG monitoring electrodes of the ECG monitor. The way to judge myocardial ischemia through ECG is that if there is myocardial ischemia, the ST segment of each lead is depressed or arched, and the T wave is inverted or high-peaked. The above manifestations generally belong to myocardial ischemia.

[0033] The angiography module is connected to the central control module and is used to obtain the patient's radionuclide angiography data using radionuclide ventriculography technology and radionuclide myocardial perfusion imaging technology. Coronary angiography is a standard for diagnosing myocardial ischemia. In the case of myocardial ischemia, when doing coronary angiography, the lesions of the coronary vessels can be clearly seen, and the degree of stenosis of the coronary vessels can be understood, which plays a role in determining the diagnosis of myocardial ischemia.

[0034] The central control module is connected to the physiological data acquisition module, the ECG monitoring module, the angiography module, the preliminary condition analysis module, the myocardial ischemia qualitative determination module, the myocardial ischemia trend determination module, the diagnosis and treatment suggestion module, and the condition data storage module, and is used to control the normal operation of each module through the host.

[0035] The preliminary condition analysis module is connected to the central control module and is used to analyze the patient symptoms obtained through the test through a preliminary analysis program, and summarize and generate a preliminary diagnosis table of the symptom manifestations.

[0036] The myocardial ischemia qualitative determination module is connected to the central control module and is used to conduct in-depth analysis of the ECG data and radionuclide angiography data of patients with myocardial ischemia symptoms through a qualitative analysis program, extract key information, and qualitatively determine whether it is myocardial ischemia; the myocardial ischemia qualitative determination module includes a qualitative data demand module, a qualitative image splitting module, a qualitative model creation module, a qualitative model training module and a qualitative image qualitative recognition module, among which:

[0037] Qualitative data requirement module is used to classify, quantity and size of images.

[0038] The qualitative model creation module is used to correspond the feature information in the graph with the classification of the graph, so that when the training results of the model are subsequently applied, images with the same features and their generalized types can be correctly classified; creating a convolutional neural network model involves the selection of various parameters and hyperparameters; setting the model output after creating the model to the abstract variable M.

[0039] The qualitative model training module is used to perform convolution calculations of the neural network with R and M as parameters to extract graphic features. The output is Features. The image set that needs to be prepared for training should contain at least an equal number of myocardial ischemia images and normal myocardial images. Normal myocardial images are classified as Normal, and ischemic myocardial images are classified as Defect.

[0040] Qualitative image qualitative recognition module, let the entire recognition process be an abstract function: I, I has been implemented in TensorFlow; let the normal myocardial blood supply image be Np, let the ischemic myocardial blood supply image be Pp, and get the result: I(Features,Pp)=Normal,I(Features,Np)=Defect.

[0041] The myocardial ischemia trend determination module is connected to the central control module and is used to compare and analyze the real-time dynamic electrocardiogram signals of patients with myocardial ischemia and the radionuclide angiography data obtained through multiple tests through a trend analysis program to determine the probability of myocardial infarction or other subsequent lesions in the patients. The myocardial ischemia trend determination module includes a trend data demand module, a trend model creation module, a trend model training module, and a trend determination classification module, wherein:

[0042] The trend data requirement module is used to classify, count and size images.

[0043] The trend model creation module is used to correspond the feature information in the graph with the classification of the graph, so that when the training results of the model are subsequently applied, images with the same features and their generalized types can be correctly classified; creating a convolutional neural network model involves the selection of various parameters and hyperparameters.

[0044] The trend model training module is used to perform convolution calculations of the neural network with R and M as parameters to extract graphic features and output: Features, a set of images that need to be prepared during training, and each image should be correctly classified into the category represented by Cat, which is the actual clinical follow-up lesion.

[0045] The trend determination classification module is used to construct the entire recognition process as an abstract function: C; C has been specifically implemented in TensorFlow. Suppose the image to be recognized is: Ip, and the result is: C(Features, Ip) = (Cat, Ratio), where Cat is the classification of the image, Ratio is the percentage of the possibility that the image is classified as this category, and the possibility that the image Ip is of the Cat category is Ratio.

[0046] The diagnosis and treatment suggestion module is connected to the central control module and is used to give different diagnosis and treatment suggestions based on the patient's myocardial ischemia trend.

[0047] The medical condition data storage module is connected to the central control module and is used to store the patient's physiological data, electrocardiogram signal data, radionuclide angiography data, preliminary diagnosis table of symptom manifestations, qualitative judgment results and trends of myocardial ischemia, and diagnosis and treatment recommendations through the memory.

[0048] A myocardial ischemia diagnosis and analysis method of a myocardial ischemia diagnosis and analysis system, characterized in that the myocardial ischemia diagnosis and analysis method comprises:

[0049] Step 1: Detect the patient's heart rate data through a heart rate detector; detect the patient's blood pressure data through a sphygmomanometer; detect the patient's respiratory rate through a respiratory detector; and collect the patient's real-time dynamic ECG signal through the ECG monitoring electrode of the ECG monitor;

[0050] Step 2, using radionuclide ventriculography and radionuclide myocardial perfusion imaging to obtain radionuclide angiography data of the patient;

[0051] Step 3: Analyze the patient's heart rate data, blood pressure data, respiratory rate, dynamic electrocardiogram and radionuclide angiography data obtained through the preliminary analysis program, and summarize and generate a preliminary diagnosis table of symptom manifestations;

[0052] Step 4: Conduct in-depth analysis of the ECG data and radionuclide angiography data of patients with symptoms of myocardial ischemia through a qualitative analysis program to extract key information and qualitatively determine whether it is myocardial ischemia;

[0053] Step 5: Compare and analyze the real-time dynamic electrocardiogram signals of patients diagnosed with myocardial ischemia and the radionuclide angiography data obtained through multiple tests through a trend analysis program to determine the probability of myocardial infarction or other subsequent lesions in the patients;

[0054] Step six, giving different diagnosis and treatment suggestions based on the patient's myocardial ischemia trend; storing the patient's physiological data, ECG signal data, radionuclide angiography data, preliminary diagnosis table of symptom manifestations, qualitative judgment results and trends of myocardial ischemia, and diagnosis and treatment suggestions in the memory.

[0055] In summary, the myocardial ischemia diagnosis and analysis system improves the efficiency of myocardial ischemia diagnosis, reduces the workload of doctors, and provides patients with more timely and accurate diagnostic services, ensuring that the patient's condition can be quickly identified and treated.

[0056] The above embodiments are only used to illustrate the technical solutions of the embodiments of the present application, rather than to limit them. Although the embodiments of the present application are described in detail with reference to the above embodiments, it should be understood by those skilled in the art that the technical solutions described in the above embodiments can still be modified, or some of the technical features can be replaced by equivalents, without departing from the spirit and scope defined by the claims of the present application.

Claims

1. A myocardial ischemia diagnosis and analysis system, characterized in that: It includes physiological data module, ECG monitoring module, angiography module, central control module, preliminary condition analysis module, myocardial ischemia qualitative determination module, myocardial ischemia trend determination module, diagnosis and treatment suggestion module and condition data storage module; The physiological data module is connected to the central control module and is used to obtain patient-related physiological data using various detection devices; The ECG monitoring module is connected to the central control module and is used to collect the patient's dynamic ECG signal in real time; The imaging module is connected to the central control module and is used to obtain the patient's radionuclide imaging data using radionuclide ventriculography technology and radionuclide myocardial perfusion imaging technology; The central control module is connected with the physiological data acquisition module, the electrocardiogram monitoring module, the angiography module, the preliminary condition analysis module, the myocardial ischemia qualitative determination module, the myocardial ischemia trend determination module, the diagnosis and treatment suggestion module, and the condition data storage module, and is used to control the normal operation of each module through the host; The preliminary condition analysis module is connected to the central control module and is used to analyze the patient's symptoms obtained through the preliminary analysis program and summarize and generate a preliminary diagnosis table of symptom manifestations; The myocardial ischemia qualitative determination module is connected to the central control module and is used to perform in-depth analysis on the electrocardiogram data and radionuclide angiography data of patients with myocardial ischemia symptoms through a qualitative analysis program, extract key information, and qualitatively determine whether it is myocardial ischemia; The myocardial ischemia trend determination module is connected to the central control module and is used to compare and analyze the real-time dynamic electrocardiogram signals of patients identified as myocardial ischemia and the radionuclide angiography data obtained through multiple tests through a trend analysis program to determine whether the patient has a probability of myocardial infarction or other subsequent lesions; The diagnosis and treatment suggestion module is connected to the central control module and is used to give different diagnosis and treatment suggestions based on the patient's myocardial ischemia trend determination; The condition data storage module is connected to the central control module and is used to store the patient's physiological data, electrocardiogram data, radionuclide angiography data, preliminary diagnosis table of symptom manifestations, qualitative determination results and trends of myocardial ischemia, and diagnosis and treatment recommendations through the memory.

2. A myocardial ischemia diagnosis and analysis system according to claim 1, characterized in that: The physiological data module includes: A heart rate detection unit, used for detecting the patient's heart rate data through a heart rate detector; A blood pressure detection unit, used to detect the patient's blood pressure data through a sphygmomanometer; The respiratory rate detection unit is used to detect the patient's respiratory rate through a respiratory detector.

3. The myocardial ischemia diagnosis and analysis system according to claim 1, characterized in that: The ECG monitoring module is used to collect the patient's real-time dynamic ECG signal through the ECG monitoring electrodes of the ECG monitor.

4. The myocardial ischemia diagnosis and analysis method of the myocardial ischemia diagnosis and analysis system according to claims 1-3, characterized in that: The myocardial ischemia diagnosis and analysis method comprises: Step 1: Detect the patient's heart rate data through a heart rate detector; detect the patient's blood pressure data through a sphygmomanometer; detect the patient's respiratory rate through a respiratory detector; and collect the patient's real-time dynamic ECG signal through the ECG monitoring electrode of the ECG monitor; Step 2, using radionuclide ventriculography and radionuclide myocardial perfusion imaging to obtain radionuclide angiography data of the patient; Step 3: Analyze the patient's heart rate data, blood pressure data, respiratory rate, dynamic electrocardiogram and radionuclide angiography data obtained through the preliminary analysis program, and summarize and generate a preliminary diagnosis table of symptom manifestations; Step 4: Conduct in-depth analysis of the ECG data and radionuclide angiography data of patients with symptoms of myocardial ischemia through a qualitative analysis program to extract key information and qualitatively determine whether it is myocardial ischemia; Step 5: Compare and analyze the real-time dynamic electrocardiogram signals of patients diagnosed with myocardial ischemia and the radionuclide angiography data obtained through multiple tests through a trend analysis program to determine the probability of myocardial infarction or other subsequent lesions in the patients; Step six, giving different diagnosis and treatment suggestions based on the patient's myocardial ischemia trend; storing the patient's physiological data, ECG signal data, radionuclide angiography data, preliminary diagnosis table of symptom manifestations, qualitative judgment results and trends of myocardial ischemia, and diagnosis and treatment suggestions in the memory.

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