CN111297474A - Individualized positioning and mapping system for auricular fibrillation focus - Google Patents

Individualized positioning and mapping system for auricular fibrillation focus Download PDF

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CN111297474A
CN111297474A CN201911315008.6A CN201911315008A CN111297474A CN 111297474 A CN111297474 A CN 111297474A CN 201911315008 A CN201911315008 A CN 201911315008A CN 111297474 A CN111297474 A CN 111297474A
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CN111297474B (en
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刘汉雄
蔡琳
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Chengdu Megan Technology Co ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • A61B2034/101—Computer-aided simulation of surgical operations
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
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Abstract

The invention relates to an individualized positioning and mapping system for atrial fibrillation focuses, which comprises a data collection module: the system is used for collecting data, establishing a database by using the collected data, and carrying out data coding and label establishment on the collected data; an analysis module: obtaining healthy atrial voltage data when atrial fibrillation does not occur, and obtaining a healthy atrial model; a verification module: the method is used for data quality control, and the established model is corrected to obtain a corrected and matched healthy atrium model; a calculation module: establishing a multiple regression estimation model by using relative voltage; identifying and mapping module: outputting a visual focus area map; a feedback module: and receiving a follow-up database, and further judging the accuracy of modeling (R, Rc model) during the operation according to the standard of the operation result and giving a correction suggestion. The invention can effectively realize the positioning and the mapping of the atrial fibrillation focus and improve the curative effect of the atrial fibrillation radio frequency ablation.

Description

Individualized positioning and mapping system for auricular fibrillation focus
Technical Field
The invention relates to a positioning and mapping system, in particular to an individualized positioning and mapping system for atrial fibrillation focuses, and belongs to the technical field of atrial fibrillation positioning.
Background
Transcatheter ablation therapy can be used as an effective treatment for the recovery and maintenance of sinus rhythm in patients with atrial fibrillation. In recent studies, transcatheter ablation therapy has been shown to be advantageous in terms of efficacy and improvement in the quality of life of patients compared to antiarrhythmic drug therapy.
Currently, transcatheter rf ablation is mainly non-individualized cpvi (cyclic Pulmonary nerve ablation), linear ablation, progressive ablation, vagal nerve ablation, and individualized ablation such as fractionated potential ablation, eavm (electrokinetic Voltage mapping) guided ablation, ROTOR (trochanter) ablation, and the like.
In a recent STAR-AF II study, ablation methods of persistent atrial fibrillation were compared: non-individualized ablation (CPVI alone, PVI + left Atrial apical line and mitral isthmus line), and individualized ablation (PVI + cfae (complexframed attached electrical ablation). The STAR-AF study concluded that non-individualized CPVI ablation success was highest (< 60%), with all other approaches being low due to the lack of accurate and effective techniques for individualized localization of atrial fibrillation lesions.
In general, a quantifiable mapping technique for individualized localization of atrial fibrillation lesions is currently lacking. In the current individuation method, the standard on which the EAVM ablation depends is non-individuation and is not unified at present, the mechanism of the ROTOR ablation is not clear at present, the unified standard is not available, the success rate is not repeatable, and the dispute is large.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide an individualized positioning and mapping system for atrial fibrillation focuses, which can effectively realize the positioning and mapping of the atrial fibrillation focuses and improve the curative effect of atrial fibrillation radio frequency ablation.
According to the technical scheme provided by the invention, the system for individually positioning and mapping the auricular fibrillation focus comprises
A data collection module: the system is used for collecting data, establishing a database by using the collected data, and carrying out data coding and label establishment on the collected data;
an analysis module: the method comprises the steps of simulating an individualized healthy atrial voltage state to obtain healthy atrial voltage data when atrial fibrillation does not occur, and obtaining a healthy atrial model;
a verification module: the method is used for data quality control, and the established model is corrected to obtain a corrected and matched healthy atrium model;
a calculation module: establishing a multiple regression estimation model by using relative voltage;
identifying and mapping module: outputting a visual focus area graph, and drawing a focus area boundary with a certain tolerance;
a feedback module: and receiving a follow-up database, and further judging the accuracy of modeling (R, Rc model) during the operation according to the standard of the operation result and giving a correction suggestion.
The data encoded in the data collection module includes individual health data, individual anatomical data, and individual electrophysiological data.
Within the verification module, according to [ Hc]＝[SI]*[SM]Correcting the healthy atrial model by using Hv matrix algorithm to obtain a corrected matched healthy atrial model (H)CA model); wherein, [ SI ]]For the data quality scoring matrix, [ SM]The model quality score matrix, Hv is the healthy atrial model.
The determination of the relative voltage in the calculation module is:
Tv＝βD*D*(Fv*SRVI*(1-βS*S)+∑βtm*Xm)，
wherein, TvCritical value of voltage of lesion region, D is atrial anatomical partition, βDCoefficient of D, βSIs a coefficient of the relative model R, S is a heart rhythm state parameter, βtmCoefficient of personal health factor, anatomical factor and electrophysiological factor to be investigated in a multiple regression estimation model with the voltage value of the sampling point position as a dependent variable, FvFor the reference voltage collected, SRVI is the standard relative voltage index.
The calculation module specifically determines the lesion as:
when q × hc (min)/av (k) >1, mv (k) ═ 1, the position is estimated to be a lesion;
when Q × hc (min)/av (k) ≦ 1, and p × hc (k) -av (k) > Q, mv (k) ═ 1, the position is estimated to be a lesion; otherwise, mv (k) is 0, denying the location as a lesion;
therefore, under the M model, each sampling point of the heart tissue shows two values of 0 and 1, which respectively represent that the heart tissue is estimated to be not a focus and is estimated to be a focus; wherein A isv(k) The voltage value obtained for the sampling point at the actual position, Hc (k) is the voltage value estimated in the non-atrial fibrillation population according to the position after matching, Mv (k) is according to { Av }kAnd { Hc }kThe obtained k position is a possible characteristic value of the focus; that is, mv (k) is a quantitative value indicating whether the sampling point has a lesion feature in a health matching manner; min represents the minimum value; q and p are correction values of a judging program for judging whether a certain sampling point position is a focus or not, and the initial value is set to be 1; the Q initial value is the variation width of the voltage of the non-atrial fibrillation population obtained according to the current research and is set to be 7;
rvi (k) denotes the relative voltage index at the k position; satisfies Av(k)＝βD*D*(Fv*RVI(k)+∑βkm*Xm)；
Rv (k) according to RVI (k) and SRVI, obtaining k position as possible characteristic value of the focus; under the R model, a relative voltage index RVI (k) of a k position is provided, and meanwhile, the voltage state of the position is estimated by comparing the relation between the RVI (k) and the SRVI to judge whether the focus is the focus;
when rvi ≦ SRVI, rv (k) ≦ 1, the location is estimated to be a lesion;
when rvi (k) > SRVI, rv (k) ═ 0, deny the location a lesion;
rc (k) obtaining k position as possible characteristic value of the focus according to the matched label quality obtained by Hc (k) and Rv (k) and Mv (k); and the correction according to the matching accuracy by Ca (correct by acclimatess) and the correction according to the consistency by Cc (correct by consistence);
Ca＝g(N,ns,nd,L)
n represents the size of the current non-atrial fibrillation human group database; n issIndicating the amount of sample included after matching the tag; l represents the label grade; n isdThe number of matched labels of d level is represented;
when only one tag combination is considered for matching; when a plurality of label combinations (w types) exist in Ca for matching, and the Ca value of each combination is calculated;
1)N≥104
Figure BDA0002325608400000031
2)N<104
Figure BDA0002325608400000032
for Cc, when rv (k) m (k), Cc is 0; rc (k) ═ rv (k) ═ m (k);
when rv (k) ≠ m (k), Cc ═ 1; rc (k) [ (Ca-0.5) × (m (k) -r (k)) ]
Rc (k) is a characteristic value of possible lesion, which is obtained according to the matched label quality obtained by Hc (k) and the obtained k positions of Rv (k) and Mv (k); the value range of Rc (k) is {0,1} according to the formula;
when rc (k) is 1, the estimated location is a lesion;
when rc (k) is 0, deny the location as a lesion;
therefore, the judgment of the focus characteristics at each position can have three model states;
mv (k), rv (k), rc (k), mv (k), health match; rv (k), self-associated; rc (k), weight synthesis;
correspondingly, when the k position is judged as a focus, Av (k) can be obtained; for all v (k) ═ 1 (estimated as the location of the lesion), the maximum av (k) value can be used as the basis for the threshold voltage value under each model.
The invention has the advantages that: the quantitative mapping technology for individualized positioning of atrial fibrillation focuses is provided, the mechanism is clear, the standard is unified, the quantification and the repeatability can be realized, the success rate of the ablation guided by a module and a system supporting the technology through clinical verification is over 80 percent, and the curative effect of the current atrial fibrillation radio frequency ablation can be obviously improved.
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FIG. 1 is a block diagram of the system of the present invention.
FIG. 2 is a schematic diagram of the present invention.
Detailed Description
The invention is further illustrated by the following specific figures and examples.
As shown in fig. 1 and 2: in order to effectively realize the positioning and mapping of the atrial fibrillation focus and improve the curative effect of the atrial fibrillation radio frequency ablation, the invention comprises the following steps:
a data collection module: the system is used for collecting data, establishing a database by using the collected data, and carrying out data coding and label establishment on the collected data;
specifically, data from device output and manual input can be accepted through the data collection module, and the input data is coded and labeled according to the internal requirement format of the system. Information codes (caseNO. + info No.) and labels (labelNo.) of individual characteristics of cases are established. The data of the information coding is mainly divided into three large blocks including individual health data, individual anatomical data and individual electrophysiological data.
See in particular the data collection module description below:
and (3) encoding content: 1) case number, 2) data encoding, 3) tag definition
And (3) an encoding mode:
the symbols of the case numbers indicate: caseno. XX, XX is a serial number, and the specific serial number is NNNNNYYYYMMDDHHMMSS; NNNNNNN is the serial number (different serial numbers are distributed under the same date and time); YYYY is the year of three-dimensional electroanatomical mapping; MM is the month of three-dimensional point anatomical mapping; DD is the date of performing three-dimensional electroanatomical mapping; HH is the hour of performing three-dimensional electroanatomical mapping; MM is the minutes for performing three-dimensional electrodissection mapping; SS is the number of seconds for three-dimensional electroanatomical mapping.
Noxx:
data is divided into three large blocks: 1) individual health data, 2) individual anatomical data, 3) individual electrophysiological data; and (3) encoding format: position coding + value coding; position coding is block + item; wherein, the plate block is: 01-individual health data; 02-individual anatomical data; 03-individual electrophysiological data
2) Items and corresponding codes under each version block: example (c):
Figure BDA0002325608400000041
value encoding:
and (3) label definition: labelNo. XX; the label meaning is as follows: dividing the input information into classes according to the information value and giving the labels; setting label grade:
when the main value to be considered is the atrial voltage, different grades are given to the magnitude of the effect of the factors on the atrial voltage according to the theory at present. Example (c):
Figure BDA0002325608400000042
and (3) label coding: tag rank-tag item-tag value; example (c): a demarcation criterion is defined for the value of the data, for example: the BMI (body Mass index) tag encodes 0201; the complete encoding of individual BMI tag is obtained by data encoding (01-01-13)/(01-01-12)2。
The BMI was 30 when 25 was used as a cutoff for obesity. The individual's BMI tag is encoded as labelno.020103.
An analysis module: the method comprises the steps of simulating an individualized healthy atrial voltage state to obtain healthy atrial voltage data when atrial fibrillation does not occur, and obtaining a healthy atrial model;
in particular for individualized simulation of healthy atrial voltage states. And matching the existing database of the crowd without atrial fibrillation in the system (the database is established as above, but the crowd is different and is a non-atrial fibrillation crowd) according to the obtained individual characteristic information number and label. According to the formula Hv ═ fhv(labelNo.((βi*Xi),Wj) (Hv, which is the matched simulated healthy atrial voltage, fhvIs a simulation model established according to a system database), and obtains the healthy atrial voltage data of the atrial fibrillation patient under simulation when the atrial fibrillation patient does not have atrial fibrillation. I.e. to establish an individual matched healthy atrial model (H-model).
Description of model H:
1) and the principle is as follows: there are several major factors (e.g., age, left atrial size, cardiac function, BMI) that affect changes in atrial voltage, and several factors are currently considered to have clinically meaningful voltage values based on previous studies. However, as the database is improved, the judgment of influencing factors, such as genotype, is expected to be improved, and when the research factors are not included in the original research and the database is planned to be built, the parameters are included, and the weight values of the parameters are variable at the beginning and are gradually fixed as the database is imported. The development of low voltage in atrial fibrillation lesions is gradual.
2) And the meaning is as follows: by regulating the factors (X)i) And rank weight (W)j) I represents each factor, j represents the grade of the weight of each grade, the atrial voltage condition of the patient without atrial fibrillation is simulated as much as possible, the low voltage threshold value of the atrial fibrillation focus estimated in the investigation index is obtained, β is a coefficient, and the value of i is consistent with the number of the factors.
3) And establishing:
matching: matching atrial states of non-atrial fibrillation populations primarily by tags, i.e. representing factor X under consideration by tagiLabel level indicates a level weight Wj. Obtaining the distribution rule of the atrial voltage of people with the same label in the investigation range, namely obtaining the ideal voltage point K of the people without atrial fibrillation matched with the label (K is the area of the atrium/(the electrode spacing)2) Then, the voltage values of all points are used for simulating the voltage value distribution curve of the incorporated atrial fibrillation individual without the occurrence of atrial fibrillation, namely, the f is establishedhvAnd (4) an equation.
The method comprises the following steps of 1, obtaining a non-atrial fibrillation population consistent with labels of individual atrial fibrillation through matching investigated factors, obtaining a voltage distribution state corresponding to ideal voltage points under the label set through parameter estimation, wherein Hv (K) exists, K belongs to [1, K ] ∩ Z, Z represents an integer set of total points, K represents each point, 2, optimizing the investigated factors, performing multiple regression analysis on the voltage corresponding to the (K) through linear regression, correcting inclusion factors, namely, taking Hv (K) as a dependent variable, establishing a regression equation by taking the original heart rhythm state and the inclusion factors as independent variables, judging whether residual errors accord with normal distribution, if so, tentatively adding new factors according to theory to update to match, and repeating the process to obtain an optimal matching model.
Example (c): the labels 010101 and 010202, 020101 are used as matching factors. Meaning that the conditions for inclusion in individuals with atrial fibrillation fit the characteristics indicated in the label. Meanwhile, the crowd with the first-level matching (010101 and 010202) is obtained from the crowd without atrial fibrillation, and the crowd with the simultaneous second-level matching (020101) can be finely divided.
Model Hv ═ fhv(labelNo.((βi*Xi),Wj) Initial form) and its specific parameters include, but are not limited to, the following forms:
Hv＝(β1*X1*LNNORMINV((β2*X2),(2.929+β3*X3+β4*X4+β0),1.296))*W^(-1)
LNNORMINV is the inverse of a lognormal distribution function, where NORMINV is F-1(x) Is the inverse of the normal cumulative distribution function f (x), and f (x) is the standard normal cumulative distribution function.
Other parameters in the formula are as follows:
Figure BDA0002325608400000061
with the improvement of the database, the function form, the parameters and the initial values of the above formula are supplemented continuously.
A verification module: the method is used for data quality control, and the established model is corrected to obtain a corrected and matched healthy atrium model;
specifically, the method is used for data quality control including 1) and data quality control to eliminate bias caused by system errors or error errors, and the content includes (background stability of measured data s, accuracy a of a measuring method, degree of difference upsilon of data measurement times/data measurement times, checking times r of data input, and the like). 2) Quality control of individual built model, content includes program according to s, a, upsilon and rCounting SI (score information matrix), namely a data quality scoring matrix, and SM (score model matrix), namely a model quality scoring matrix, according to [ Hc ]]＝[SI]*[SM]Hv matrix algorithm corrects the model to obtain corrected matched healthy atrial model (H)CA model).
A calculation module: establishing a multiple regression estimation model by adopting relative voltage;
in particular, a personalized mapping strategy for obtaining atrial fibrillation lesions. Conventional EAVM-guided ablation uses a fixed reference value, i.e., an absolute voltage value, for both low-voltage decision thresholds, but this is not a true individualized mapping and has no uniform criteria. In the embodiment of the invention, the atrial voltage is defined and quantified individually again by adopting a Relative Voltage Index (RVI) which is firstly proposed by a preliminary test study, and a Standard Relative Voltage Index (SRVI) is taken as an individual voltage boundary value standard. The voltage-related indicator does not use absolute voltage values (such as, but not limited to, unipolar voltages, bipolar voltage values, voltage cutoff values, average values, etc. in volts) but rather uses relative values.
Description of relative voltages:
1) principle and meaning: the voltage of the heart tissue of an individual follows a general rule that there is a range of normal values. But also individual variability. For the population suffering from atrial fibrillation, the atrial stroma changes, and the accurate identification of the low-voltage focus is particularly important, so that the accurate individual difference has important significance for the population suffering from atrial fibrillation. The critical voltage value is searched to distinguish a focus area from a healthy area, and the focus area and the healthy area can be obtained according to a matched healthy population rule (H model) or can be calculated according to a relation between a healthy tissue and a pathological tissue which are relatively constant based on the critical voltage value (RVI, relative voltage index acquisition).
2) And (3) calculating: the present invention utilizes this rule discovered by preliminary studies. The study was based on analysis of the voltage in each region of the cardiac tissue to obtain a relatively stable voltage region and a representative value Fv(reference voltage, here "voltage representative value of relatively stable voltage region")Including but not limited to a certain percentile value of the voltage of the atrial anatomical partition for reference, such as atrial forewall region, atrial appendage region, etc., which was found in tests to have no statistically significant variation between the non-atrial fibrillation "healthy" population and the atrial fibrillation population, and therefore can be used as a reference voltage, with the database perfected, a more stable reference voltage can be found), and a lesion area voltage threshold (T) valuev: threshold Voltage Threshold value, which should be equal to a certain percentile of the lower value of the clinically normal healthy atrial Voltage, which can distinguish between healthy and diseased), and a more stable relationship between the Threshold value and the representative value of the stable region Voltage, the initial form and its specific parameters include but are not limited to the following forms:
Tv＝βD*D*(Fv*SRVI*(1-βS*S)+∑βtm*Xm)，
the SRVI found in the pilot study was a constant, defined in the examples of the present invention as the "Standard relative Voltage index", which is the value of the "relative value" of the T per casevOr FvWhen the absolute voltage value changes, the change can be used as a unified standard for judging the atrial lesion and the healthy tissue. Based on the RVI, i.e. the concept of "relative voltage index", the RVI corresponding to a certain sampling point is calculated and compared with the SRVI, and the result can be used to judge whether the point is a focus. The RVI satisfies: a. thev(k)＝f(RVI(k)) In the case of a liquid crystal display device, in particular,
Av(k)＝βD*D*(Fv*RVI(k)(1-βS*S)+∑βkm*Xm)，
wherein A isvThe actual absolute voltage value of a certain sampling point position of the Absolute voltage, RVI (relative voltage Index) relative voltage Index value, D is an atrial anatomical partition in the two formulas, βDCoefficient of D S is the rhythm condition parameter, βSIs the coefficient of R. t: critical position, the initial value is the anatomical position corresponding to the 5 th percentile of healthy atrial voltage. k is the position of the sampling point. m: each incorporating a factor. As well as factors affecting atrial voltage. At the very beginning of the databaseIn construction, the factors that need to be considered in theory and the factors that need to be actually considered last are influenced by the completeness of the data of the included population.
As the database is refined, the considerations in the Hc model and the Rc model will tend to be consistent and close to reality. When is treated with Av(k) As dependent variables, Fv and XmCoefficient when setting up regression equation for independent variable βtmAnd βkmThe method is used for estimating coefficients of personal health factors, anatomical factors and electrophysiological factors considered in a multiple regression model taking a voltage value of a sampling point position as a dependent variable, wherein the electrophysiological parameters comprise but are not limited to regional distribution characteristics of various electrophysiological indexes.
As the database is perfected, the m (inclusion factor) and the previous i (i.e. the inclusion factor in the H model) tend to be consistent and close to the real situation; the T value (critical position) corresponds to a critical value point in all k (sampling positions), and the T corresponding to the point is calculated by the formulavThe value can represent the lower critical value of the healthy atrium absolute voltage value matched with the current case, and can be used as the absolute voltage value standard for judging the individuation of the atrium focus and the healthy tissue (the actual measurement A corresponding to a certain sampling positionvValue and TvComparing the values, and judging whether the point is a focus or not according to the result).
The parameters of these two equations are illustrated in the following table:
Figure BDA0002325608400000081
with the improvement of the database, the function form, the parameters and the initial values of the formula are continuously corrected and supplemented.
3) Is characterized in that: that is, any algorithm using relative voltage index instead of absolute voltage value or relative voltage index as parameter, and any algorithm using other electrophysiological parameters proposed by the present invention, and its application and system are within the scope of the present invention.
Relative model (R model) and description of its application:
1) and position voltage value description, k represents a voltage sampling position, and A, Hc, M and R represent model states.
2) M Model, Match Model (healthy) matching Model-lesion determination.
3) R Model, Relative Model-Relative voltage.
4) The Rc Model, the Relative Model after the correction of Relative Model.
Wherein, the position voltage and the model relation:
Av(k) the method comprises the following steps And actually taking the voltage value obtained by the point at the position. (A: absolute value of Absolute voltage).
Hc (k): and according to the estimated voltage value of the matched position in the non-atrial fibrillation crowd.
Mv (k): according to Av(k) And Hc (k), the obtained k position is a possible characteristic value of the focus. That is, mv (k) is a quantitative value indicating whether or not the spot position has lesion features by the health matching method.
min represents the minimum value. q and p are correction values of a judging program for judging whether a certain sampling point position is a focus or not, and the initial value is set to be 1. The Q initial value is 7, which is the variation width of the voltage of the non-atrial fibrillation population obtained according to the current research.
When q × hc (min)/av (k) >1, mv (k) ═ 1, the position is estimated to be a lesion.
When Q × hc (min)/av (k) ≦ 1, and p × hc (k) -av (k) > Q, mv (k) ═ 1, the position was estimated to be a lesion. Otherwise, mv (k) is 0, denying that the location is a lesion.
Thus, in the M model, each sampling point of the cardiac tissue has two values of 0 and 1, which respectively indicate whether the cardiac tissue is estimated to be a lesion or not and whether the cardiac tissue is estimated to be a lesion.
RVI (k): indicating the relative voltage index at the k position. Satisfies Av(k)＝βD*D*(Fv*RVI(k)+∑βkm*Xm)。
Rv (k): according to RVI (k) and SRVI, the k position is obtained as a possible characteristic value of the focus.
Under the R model, the relative voltage index of the k position, RVI (k), is provided, and the voltage state of the position is estimated by comparing the relation between RVI (k) and SRVI to judge whether the focus is present.
When rvi (k) ≦ SRVI, rv (k) ═ 1, the location was estimated to be a lesion.
When rvi (k) > SRVI, rv (k) ═ 0, the location is denied as a lesion.
Rc (k): and obtaining k position as possible characteristic value of the focus according to the matched label quality obtained by Hc (k) and the label quality obtained by Rv (k) and Mv (k). Ca (correct by acuturanss), correction according to matching accuracy. Cc (correct by consistency), correction according to consistency.
Description of Ca:
the principle is as follows: the obtained Hc model is a Hc (k) position-voltage value set obtained by selecting a label, obtaining a non-atrial fibrillation human group database and analyzing the database. The labels are selected based on the characteristics of individuals who incorporate atrial fibrillation. The number and grade of tags selected, as well as the size of the early database, will affect the accuracy of Hc, as represented by the degree of modeling of the state of the heart tissue before atrial fibrillation occurs in individuals who incorporate atrial fibrillation. Therefore, by introducing the Ca value, the lesion judgment provided by Mv (k) is given confidence.
And (3) calculating:
Ca＝g(N,ns,nd,l)
and N represents the size of the current non-atrial fibrillation human group database. n issIndicating the amount of sample included after matching the tag. And l represents the grade of the label. n isdThe number of matching tags representing d levels.
When only one tag combination is considered for matching. Ca is matched with a plurality of label combinations (w types), and the Ca value of each combination is calculated.
1)N≥104
Figure BDA0002325608400000101
2)N<104
Figure BDA0002325608400000102
In the section "Ca description", the purpose of calculating Ca is described. That is, by introducing Ca value, the focus judgment provided by Mv (k) is given confidence.
Cc illustrates:
the principle is that no matter the healthy contrast-matching judgment of Mv (k), the focus critical value is estimated through a non-atrial fibrillation human group database, or the self contrast-correlation judgment of Rv (k), the focus critical value is estimated through the correlation between healthy tissues and pathological tissues with relatively stable self heart tissues, and the early influencing factors are selected (the label is selected and the grade is given and βjParameters), limited by the size of the database, and the recognition limitation, the part to be perfected can be perfected by the expansion of the size of the database. Therefore, the inconsistent components between Mv (k) and Rv (k) are correctly judged and analyzed at an early stage, and the M model and the R model can be optimized. Therefore, the main purpose is to optimize the RVI expression and judge the focus area by adopting a self-contrast mode as far as possible, thereby reducing the calculated amount and ensuring the accuracy.
And (3) calculating:
when rv (k) is m (k), Cc is 0. Rc (k) ═ rv (k) ═ m (k)
When rv (k) ≠ m (k), Cc ═ 1.
Rc (k) [ (Ca-0.5) × (m (k) — r (k)) ], i.e., rc (k) can be calculated by rounding up.
Description of the correction:
similarly, rc (k) is the possible feature value of the lesion based on the matched label quality obtained from hc (k) and rv (k) and mv (k), and k is the obtained position. The value range of Rc (k) is {0,1} according to the formula.
When rc (k) is 1, the estimated location is a lesion.
When rc (k) is 0, the position is denied as a lesion.
Therefore, the judgment of the focus characteristics at each position can have three model states.
Mv (k), rv (k), rc (k), mv (k), health match; rv (k), self-associated; rc (k), weight synthesis.
Correspondingly, when the k position is judged as a focus, Av (k) can be obtained. For all v (k) ═ 1 (estimated as the position of the lesion), the above-mentioned v (k) ═ 1 means the voltage determination in each mode, and the maximum av (k) value thereof can be used as the basis of the threshold voltage value in each model.
Identifying and mapping module: outputting a visual focus area graph, and drawing a focus area boundary with a certain tolerance;
in particular, an output system. The method is used for guiding the radio frequency ablation operation and visually positioning the atrial lesion area of the patient with atrial fibrillation. Meanwhile, an intuitive focus area map is output (namely, a low-voltage area is drawn by using different colors or textures on an existing heart three-dimensional model), and the focus area boundary is drawn by using the electrode spacing as the tolerance, namely, the maximum range represented by the acquired points is used as the tolerance.
A feedback module: and receiving follow-up database information, judging the operation result, further judging the accuracy of modeling (R, Rc model) during the operation and giving a correction suggestion.
Rc (relative Model correct) is the correction of the R Model. The above corrective instruction explains the model.
Follow-up database description:
the significance is as follows: the individual ablation strategy has better results in preliminary experiments, and can be perfected and accurate in application. Under the current condition that the ablation of the atrial fibrillation patient has low success rate and high recurrence rate, the postoperative heart rhythm state of the atrial fibrillation patient is judged by follow-up visit, the evidence property of an individualized ablation strategy is enhanced on the individual level, possible reasons influencing prognosis and population characteristics are analyzed on the population level, and targeted model optimization is provided when the individualized ablation strategy is customized.
After the atrial fibrillation patient is ablated, a better effect can be achieved in the field. That is, the immediate effect of ablation is successful. However, long-term effects need to be judged by follow-up. If patients with atrial fibrillation relapse after ablation, it is assumed that the population labeled 010203 is likely to relapse, [ i.e., in this example, a population with moderate atrial augmentation ]. The increase in atrial augmentation may be considered as a parameter. As the case may be. The content is as follows: whether atrial fibrillation occurs again after operation or not; if so, how long it takes to occur; the number of arrhythmic events occurring within 3 months, 6 months, 12 months, 3 years, 5 years, and the type. The state of cardiac function. The application comprises the following steps: judging and optimizing the effectiveness of the individual strategy: and (5) inspecting indexes and feeding back opinions.

Claims (5)

1. An individualized positioning and mapping system for auricular fibrillation focuses is characterized in that: comprises that
A data collection module: the system is used for collecting data, establishing a database by using the collected data, and carrying out data coding and label establishment on the collected data;
an analysis module: the method comprises the steps of simulating an individualized healthy atrial voltage state to obtain healthy atrial voltage data when atrial fibrillation does not occur, and obtaining a healthy atrial model;
a verification module: the method is used for data quality control, and the established model is corrected to obtain a corrected and matched healthy atrium model;
a calculation module: establishing a multiple regression estimation model by using relative voltage;
identifying and mapping module: outputting a visual focus area graph, and drawing a focus area boundary with a certain tolerance;
a feedback module: and receiving a follow-up database, and further judging the accuracy of modeling (R, Rc model) during the operation according to the standard of the operation result and giving a correction suggestion.
2. The system of claim 1, wherein the system is configured to perform mapping by: the data encoded in the data collection module includes individual health data, individual anatomical data, and individual electrophysiological data.
3. The system of claim 1, wherein the system is configured to perform mapping by: within the verification module, according to [ Hc]＝[SI]*[SM]Correcting the healthy atrial model by using Hv matrix algorithm to obtain a corrected matched healthy atrial model (H)CA model); wherein, [ SI ]]For the data quality scoring matrix, [ SM]The model quality score matrix, Hv is the healthy atrial model.
4. The system of claim 1, wherein the system is configured to perform mapping by: the determination of the relative voltage in the calculation module is:
Tv＝βD*D*(Fv*SRVI*(1-βS*S)+∑βtm*Xm)，
wherein, TvCritical value of voltage of lesion region, D is atrial anatomical partition, βDCoefficient of D, βSIs a coefficient of the relative model R, S is a heart rhythm state parameter, βtmCoefficient of personal health factor, anatomical factor and electrophysiological factor to be investigated in a multiple regression estimation model with the voltage value of the sampling point position as a dependent variable, FvFor the reference voltage collected, SRVI is the standard relative voltage index.
5. The system of claim 4, wherein the system comprises: the calculation module specifically determines the lesion as:
when q × hc (min)/av (k) >1, mv (k) ═ 1, the position is estimated to be a lesion;
when Q × hc (min)/av (k) ≦ 1, and p × hc (k) -av (k) > Q, mv (k) ═ 1, the position is estimated to be a lesion; otherwise, mv (k) is 0, denying the location as a lesion;
therefore, under the M model, each sampling point of the heart tissue shows two values of 0 and 1, which respectively represent that the heart tissue is estimated to be not a focus and is estimated to be a focus; wherein A isv(k) The voltage value obtained for the sampling point at the actual position, Hc (k) is the voltage value estimated in the non-atrial fibrillation population according to the position after matching, Mv (k) is according to { Av }kAnd { Hc }kThe obtained k position is a possible characteristic value of the focus; that is, mv (k) is a quantitative value indicating whether the sampling point has a lesion feature in a health matching manner; min represents the minimum value; q and p are correction values of a judging program for judging whether a certain sampling point position is a focus or not, and the initial value is set to be 1; the Q initial value is the variation width of the voltage of the non-atrial fibrillation population obtained according to the current research and is set to be 7;
rvi (k) denotes the relative voltage index at the k position; satisfies Av(k)＝βD*D*(Fv*RVI(k)+∑βkm*Xm)；
Rv (k) according to RVI (k) and SRVI, obtaining k position as possible characteristic value of the focus; under the R model, a relative voltage index RVI (k) of a k position is provided, and meanwhile, the voltage state of the position is estimated by comparing the relation between the RVI (k) and the SRVI to judge whether the focus is the focus;
when rvi ≦ SRVI, rv (k) ≦ 1, the location is estimated to be a lesion;
when rvi (k) > SRVI, rv (k) ═ 0, deny the location a lesion;
rc (k) obtaining k position as possible characteristic value of the focus according to the matched label quality obtained by Hc (k) and Rv (k) and Mv (k); and correction according to matching accuracy by Ca (correct by acclimatess) and correction according to Cc (correct consistency);
Ca＝g(N,ns,nd,L)
n represents the size of the current non-atrial fibrillation human group database; n issIndicating the amount of sample included after matching the tag; l represents the label grade; n isdThe number of matched labels of d level is represented;
when only one tag combination is considered for matching; when a plurality of label combinations (w types) exist in Ca for matching, and the Ca value of each combination is calculated;
1)N≥104
Figure FDA0002325608390000021
2)N<104
Figure FDA0002325608390000022
for Cc, when rv (k) m (k), Cc is 0; rc (k) ═ rv (k) ═ m (k);
when rv (k) ≠ m (k), Cc ═ 1;
Figure FDA0002325608390000023
rc (k) is a characteristic value of possible lesion, which is obtained according to the matched label quality obtained by Hc (k) and the obtained k positions of Rv (k) and Mv (k); the value range of Rc (k) is {0,1} according to the formula;
when rc (k) is 1, the estimated location is a lesion;
when rc (k) is 0, deny the location as a lesion;
therefore, the judgment of the focus characteristics at each position can have three model states;
mv (k), rv (k), rc (k), mv (k), health match; rv (k), self-associated; rc (k), weight synthesis;
correspondingly, when the k position is judged as a focus, Av (k) can be obtained; for all v (k) ═ 1 (estimated as the location of the lesion), the maximum av (k) value can be used as the basis for the threshold voltage value under each model.
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