A dual-modality cardiac fibrosis localization system based on magnetic resonance imaging and electrophysiology

Abstract

The present invention discloses a dual-modality cardiac fibrosis localization system using magnetic resonance imaging (CMR) and electrophysiology. The system comprises an image post-processing module, an individualized information entry module, an individualized relative density ratio threshold calculation module, a cardiac model construction module, and a matching and localization module. The system generates a CSV file from a CMR and electrophysiology fusion system, and then derives an individualized CMR relative density ratio threshold based on the CSV file. The determination of the IIR threshold in the present invention fully considers the comparison between CMR and electrophysiology. The fibrosis area defined by this threshold is more consistent with the low-voltage zone, enabling better target identification of cardiac fibrosis areas. This threshold-based CMR-guided ablation is therefore more effective.

Description

Technical Field

[0001] The present invention relates to the technical field of medical image processing, and in particular to a magnetic resonance and electrophysiological dual-modality cardiac fibrosis positioning system. Background Art

[0002] Cardiovascular Magnetic Resonance (CMR) is a non-invasive, radiation-free imaging method. Numerous studies and clinical practices have demonstrated its potential as a noninvasive tool for visualizing and quantifying cardiac fibrosis. CMR has been widely adopted and promoted worldwide. Histological changes in left atrial fibrosis are a characteristic of persistent atrial fibrillation and correlate well with the low voltage zone (LVZ) detected by electrophysiological voltage mapping.

[0003] Given that multiple previous studies have shown that there is no significant additional benefit from adding CMR-guided fibrosis ablation. As the results of the currently famous DECAAFII (Comparison of the efficacy of CMR-guided ablation and conventional catheter ablation for the treatment of atrial fibrillation) trial showed: for persistent atrial fibrillation, targeted cardiac fibrosis detected by CMR did not reduce the recurrence of atrial arrhythmias compared with simple pulmonary vein isolation (PVI). Given that CMR has been proven to be a valuable non-invasive assessment of cardiac fibrosis and a useful diagnostic, prognostic and therapeutic tool, however, the currently used CMR-guided ablation has not met the expected research results, how to improve the effectiveness of CMR-guided ablation has become a technical problem that needs to be solved urgently. Summary of the Invention

[0004] The purpose of the present invention is to provide a dual-modality cardiac fibrosis positioning system of magnetic resonance and electrophysiology to improve the effect of CMR-guided ablation.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A dual-modality cardiac fibrosis positioning system of magnetic resonance and electrophysiology, comprising: an image post-processing module, an individualized information input module, an individualized relative density ratio threshold calculation module, a cardiac model construction module, and a matching positioning module;

[0007] The image post-processing module is connected to the individualized relative density ratio threshold calculation module and the heart model construction module respectively, and the image post-processing module is used to perform point-to-point fusion of CMR image information and electrophysiological data information to obtain a CSV file and a VTK file, and send the CSV file to the individualized relative density ratio threshold calculation module and send the VTK file to the heart model construction module;

[0008] The individualized information input module is connected to the individualized relative density ratio threshold calculation module, and is used to input individualized information and send the individualized information to the individualized relative density ratio threshold calculation module; the individualized information includes: eGFR, LAD, BNP, BMI, CHA2DS2-VASc, and age;

[0009] The individualized relative density ratio threshold calculation module is connected to the heart model construction module, and is used to calculate the individualized relative density ratio threshold according to the CSV file and the individualized information, and send the individualized relative density ratio threshold to the heart model construction module;

[0010] The heart model construction module is connected to the matching and positioning module, and is used to extract the heart region from the VTK file according to the individualized relative density ratio threshold to obtain a heart model, and send the heart model to the matching and positioning module;

[0011] The matching and positioning module is used to match the electrophysiological data information with the heart model, obtain and output a cardiac fibrosis positioning result.

[0012] Optionally, the individualized relative density ratio threshold calculation module includes: an information extraction unit and a threshold calculation unit;

[0013] The information extraction unit is used to extract the voltage value and signal strength of the heart reference anatomical position from the CSV file;

[0014] The threshold calculation unit is used to calculate the individualized relative density ratio threshold according to the voltage value and signal strength of the heart reference anatomical position and the individualized information.

[0015] Optionally, calculating an individualized relative density ratio threshold according to the CSV file and the individualized information specifically includes:

[0016] Calculating a signal strength threshold at any position of the heart according to the CSV file and the individualized information;

[0017] Based on the signal intensity threshold, an individualized relative density ratio threshold is calculated.

[0018] Optionally, the formula for calculating the signal strength threshold at any position of the heart is:

[0019] SI=-SRVI*I R+k2*eGFR+k3*age+k4*LAD+k5*BNP+k6*BMI+k7*CHA2DS2-VASc-b;

[0020] Among them, SI is the signal strength threshold, I R is the signal intensity at the reference anatomical position of the heart, SRVI is the cardiac relative voltage index, ranging from 0.05 to 0.90, k2, k3, k4, k5, k6 and k7 are fusion coefficients, and b is a constant.

[0021] Optionally, the formula for calculating the individualized relative density ratio threshold is:

[0022] SIIR=(SI-I R ) / I R ;

[0023] Or SIIR=(SI-I R ) / SD;

[0024] Or SIIR=SI / I R ;

[0025] Or SIIR = SI / SD;

[0026] Or SIIR=ln[(SI-I R ) / I R +1];

[0027] Or SIIR=ln[(SI-I R ) / SD+1];

[0028] Or SIIR=ln(SI / I R +1);

[0029] Or SIIR = ln(SI / SD+1)

[0030] Among them, SIIR is the individual relative density ratio threshold, SI is the signal intensity threshold, I R is the signal intensity at the reference anatomical position of the heart, and SD is the standard deviation of the magnetic resonance signal intensity.

[0031] Optionally, the image post-processing module, the individualized information entry module, the individualized relative density ratio threshold calculation module, the heart model construction module and the matching and positioning module run on at least one terminal device.

[0032] Optionally, the terminal device is equipped with a central processing unit, a display, an interface for inputting CMR image information, an interface for inputting electrophysiological data information, and a memory.

[0033] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0034] The present invention discloses a dual-modality cardiac fibrosis localization system using magnetic resonance imaging (CMR) and electrophysiology. The system comprises an image post-processing module, an individualized information input module, an individualized relative density ratio threshold calculation module, a cardiac model construction module, and a matching and localization module. The system generates a CSV file from a CMR and electrophysiology fusion system, and then derives a CMR IIR (Individualized Relative Density Ratio) threshold based on the CSV file. The determination of the IIR threshold in the present invention fully considers the comparison between CMR and electrophysiology. The fibrosis area defined by this threshold is more consistent with the low-voltage zone, enabling better target identification of cardiac fibrosis areas. This threshold improves the effectiveness of CMR-guided ablation procedures. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 A schematic structural diagram of a magnetic resonance and electrophysiological dual-modality cardiac fibrosis localization system provided in an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of a heart model provided by an embodiment of the present invention;

[0038] Figure 3 This is an individualized voltage map provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0040] The purpose of the present invention is to provide a dual-modality cardiac fibrosis positioning system of magnetic resonance and electrophysiology to improve the effect of CMR-guided ablation.

[0041] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0042] Example 1

[0043] The embodiment of the present invention provides a dual-modality cardiac fibrosis positioning system of magnetic resonance and electrophysiology, characterized in that: Figure 1 As shown, the system includes: an image post-processing module, an individualized information input module, an individualized relative density ratio threshold calculation module, a heart model construction module and a matching positioning module.

[0044] The image post-processing module is connected to the individualized relative density ratio threshold calculation module and the heart model construction module respectively. The image post-processing module is used to perform point-to-point fusion of CMR image information and electrophysiological data information to obtain a CSV file and a VTK file, and send the CSV file to the individualized relative density ratio threshold calculation module and send the VTK file to the heart model construction module.

[0045] The individualized information entry module is connected to the individualized relative density ratio threshold calculation module, and is used to enter individualized information and send the individualized information to the individualized relative density ratio threshold calculation module; the individualized information includes: glomerular filtration rate eGFR, left atrial diameter LAD, brain natriuretic peptide BNP, body mass index BMI, stroke index CHA2DS2-VASc and age.

[0046] The individualized relative density ratio threshold calculation module is connected to the heart model construction module. The individualized relative density ratio threshold calculation module is used to calculate the individualized relative density ratio threshold according to the CSV file and the individualized information, and send the individualized relative density ratio threshold to the heart model construction module.

[0047] The heart model construction module is connected to the matching and positioning module. The heart model construction module is used to extract the heart area from the VTK file according to the individualized relative density ratio threshold, obtain the heart model, and send the heart model to the matching and positioning module.

[0048] The matching and positioning module is used to match the electrophysiological data information with the heart model, obtain and output a cardiac fibrosis positioning result.

[0049] Among them, the specific execution steps of the image post-processing module are:

[0050] 1. Outline the inner and outer membranes;

[0051] 2. Set reference points;

[0052] 3. Import electrophysiological data;

[0053] 4. Adjust electrophysiological data;

[0054] 5. Generate result files: CSV and VTK files;

[0055] 6. Export VTK file;

[0056] 7. Use specialized software to browse VTK files.

[0057] The specific implementation of the individualized relative density ratio threshold calculation module is as follows:

[0058] The CSV file obtained by the image post-processing module is processed and analyzed to obtain the threshold value of the individual relative density ratio (IIR) for target identification of fibrosis.

[0059] In the initial experiment of the present invention, the correlation between the individualized voltage and IIR can be obtained through the CVS file, so that the threshold SIIR of the individualized IIR can be fitted, specifically:

[0060] The embodiment of the present invention is based on the signal intensity I of a certain reference part (R) of the heart (not the blood pool). R As a reference, the relative density ratio (IIR) is calculated.

[0061] The formula of IIR can be, but is not limited to, the following forms:

[0062] ①IIR=(II R ) / I R

[0063] ②IIR=(II R ) / SD

[0064] ③IIR=I / I R

[0065] ④IIR=I / SD

[0066] ⑤IIR=ln[(II R ) / I R +1]

[0067] ⑥IIR=ln[(II R ) / SD+1]

[0068] ⑦IIR=ln(I / I R +1)

[0069] ⑧IIR=ln(I / SD+1)

[0070] Note: R is a reference part of the heart, that is, the reference anatomical position of the heart, that is, R can be the left atrium, left ventricle, right atrium, right ventricle, great blood vessels, arteries, etc. (excluding the blood pool).

[0071] The corresponding formula for calculating the individualized relative density ratio threshold may also be, but is not limited to, the following form:

[0072] ①SIIR=(SI-I R ) / I R ;

[0073] ②SIIR=(SI-I R ) / SD;

[0074] ③SIIR=SI / I R ;

[0075] ④SIIR=SI / SD;

[0076] ⑤SIIR=ln[(SI-I R ) / I R +1];

[0077] ⑥SIIR=ln[(SI-I R ) / SD+1];

[0078] ⑦SIIR=ln(SI / I R +1);

[0079] ⑧SIIR=ln(SI / SD+1)

[0080] Among them, SIIR is the individual relative density ratio threshold, SI is the signal intensity threshold, I R is the signal intensity at the reference anatomical position of the heart, and SD is the standard deviation of the magnetic resonance signal intensity.

[0081] The calculation formula of SI is:

[0082] SI=-SRVI*I R +k2*eGFR+k3*age+k4*LAD+k5*BNP+k6*BMI+k7*CHA2DS2-VASc-b.

[0083] For example, using the formula SIIR=(SI-I R ) / I R The SIIR calculation is as follows:

[0084] SIIR=(SI-I R ) / I R =SI / I R -1=k8(-SRVI*I R+k2*eGFR+k3*age+k4*LAD+k5*BNP+k6*BMI+k7*CHA2DS2-VASc-b) / (k1*I R )-1

[0085] For example, using the formula SIIR=ln(SI / I R +1) The SIIR calculation is specifically as follows:

[0086] SIIR=ln(SI / I R +1)=k8ln(-k1*I R +k2*eGFR+k3*age+k4*LAD+k5*BNP+k6*BMI+k7*CHA2DS2-VASc-b) / ln(I R )-1

[0087] eGFR is glomerular filtration rate (unit: ml / min; its value range is [0, 150]), LAD is left atrial diameter (unit: mm; its value range is [20, 70]), BNP is brain natriuretic peptide (unit: pg / ml; its value range is [0, 5000]), BMI is body mass index (unit: kg / m2; its value range is [12, 40]), CHA2DS2-VASc is stroke index (unit: points; its value range is [0, 7]), I R is the signal strength at a reference anatomical site of the heart (unit: Tesla; range: [0,700]). k1 to k7 are fusion coefficients, which are constant values, and b is a constant value that can be set differently for different systems.

[0088] The value ranges and meanings of the parameters in the former specific form are shown in Table 1.

[0089] Table 1 Parameters of the former form

[0090]

[0091] The value ranges and meanings of the parameters in the latter specific form are shown in Table 2.

[0092] Table 2 Parameters of the latter form

[0093]

[0094] The specific implementation method of the heart model construction module and the matching positioning module is: by browsing the VTK file through special software, the CMR heart model can be obtained by adjusting the IIR threshold, and it can be matched with the heart model reconstructed by the electrophysiological data measured by the electrophysiological system.

[0095] Example 2

[0096] Embodiment 2 of the present invention provides CMR images and data information acquired by the acquisition gating system module (the CMR image information includes CMR images and data information). Next, the image post-processing module performs a point-to-point fusion of the CMR images and data information with the electrophysiological data information mapped by the electrophysiological system to generate CSV and VTK files. Then, the individualized relative density ratio threshold calculation module processes and analyzes the CSV file obtained by the image post-processing module to obtain an individualized relative density ratio (IIR) threshold for target fibrosis identification.

[0097] V of the present invention example R V is the voltage value with a certain point on the anterior wall of the left heart as the anatomical reference point. R =7.8mv, the anatomical point corresponds to a signal intensity of 548t, and the individualized IIR threshold SIIR is calculated according to the above formula as follows (the values ​​of the parameters in the formula are only for example):

[0098] SIIR=2(-0.228*7.8+0.0032*88+0.037*73+0.081*36+0.036*176+0.58*24.8+0.037*4-0.345) / (0.0354*548)-1;

[0099] That is, SIIR = 1.538.

[0100] It can also be expressed as:

[0101] SIIR=5ln(-0.228*7.8+0.0032*88+0.037*73+0.081*36+0.036*176+0.58*24.8+0.037*4-0.345) / ln(548)-1

[0102] That is, SIIR = 1.540.

[0103] The VTK file of the present invention is browsed through the heart model construction module and extracted based on the individual relative density ratio threshold to obtain a three-dimensional reconstructed heart model of the left heart, such as Figure 2 At the same time, the matching and positioning module matches the electrophysiological data with the heart model to obtain the individualized voltage map of the left heart, as shown in Figure 3 shown.

[0104] like Figure 2 and Figure 3 visible, Figure 2 Delay Enhancement Area (Slash Filled Area) with Figure 3The displayed low-voltage areas (areas filled with slashes) have a high degree of matching. In other words, the individualized voltage target identification of cardiac fibrosis by CMR and electrophysiology is highly consistent, that is, the sensitivity and accuracy of the fusion system in identifying fibrosis targets are high.

[0105] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0106] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A dual-modality cardiac fibrosis localization system based on magnetic resonance imaging and electrophysiology, characterized in that: The system includes: an image post-processing module, an individualized information input module, an individualized relative density ratio threshold calculation module, a heart model construction module and a matching positioning module; The image post-processing module is connected to the individualized relative density ratio threshold calculation module and the heart model construction module respectively, and the image post-processing module is used to perform point-to-point fusion of CMR image information and electrophysiological data information to obtain a CSV file and a VTK file, and send the CSV file to the individualized relative density ratio threshold calculation module and send the VTK file to the heart model construction module; The individualized information input module is connected to the individualized relative density ratio threshold calculation module, and is used to input individualized information and send the individualized information to the individualized relative density ratio threshold calculation module; the individualized information includes: eGFR, LAD, BNP, BMI, CHA2DS2-VASc, and age; The individualized relative density ratio threshold calculation module is connected to the heart model construction module, and is used to calculate the individualized relative density ratio threshold according to the CSV file and the individualized information, and send the individualized relative density ratio threshold to the heart model construction module; The heart model construction module is connected to the matching and positioning module, and is used to extract the heart region from the VTK file according to the individualized relative density ratio threshold to obtain a heart model, and send the heart model to the matching and positioning module; The matching and positioning module is used to match the electrophysiological data information with the heart model, obtain and output a cardiac fibrosis positioning result.

2. The dual-modality cardiac fibrosis positioning system of magnetic resonance and electrophysiology according to claim 1, characterized in that: The individualized relative density ratio threshold calculation module includes: an information extraction unit and a threshold calculation unit; The information extraction unit is used to extract the voltage value and signal strength of the heart reference anatomical position from the CSV file; The threshold calculation unit is used to calculate the individualized relative density ratio threshold according to the voltage value and signal strength of the heart reference anatomical position and the individualized information.

3. The dual-modality cardiac fibrosis localization system of magnetic resonance and electrophysiology according to claim 2, characterized in that: Calculating an individualized relative density ratio threshold according to the CSV file and the individualized information specifically includes: Calculating a signal strength threshold at any position of the heart according to the CSV file and the individualized information; Based on the signal intensity threshold, an individualized relative density ratio threshold is calculated.

4. The dual-modality cardiac fibrosis localization system of magnetic resonance and electrophysiology according to claim 3, characterized in that: The formula for calculating the signal strength threshold at any position of the heart is: SI=-SRVI*I R +k2*eGFR+k3* age+k4*LAD+k5*BNP+k6*BMI+ k7*CHA2DS2-VASc-b; Among them, SI is the signal strength threshold, I R is the signal intensity at the reference anatomical position of the heart, SRVI is the cardiac relative voltage index, ranging from 0.05 to 0.90, k2, k3, k4, k5, k6 and k7 are fusion coefficients, and b is a constant.

5. The dual-modality cardiac fibrosis positioning system of magnetic resonance and electrophysiology according to claim 3, characterized in that: The formula for calculating the individualized relative density ratio threshold is: SIIR=(SI-I R ) / IS R ; or SIIR = (SI - I R ) / SD; or SIIR = SI / I R ; Or SIIR = SI / SD; or SIIR = ln[(SI - I R ) / I R + 1]; or SIIR = ln[(SI - I R ) / SD + 1]; or SIIR = ln(SI / I R + 1); Or SIIR = ln(SI / SD+1) Among them, SIIR is the individual relative density ratio threshold, SI is the signal intensity threshold, I R is the signal intensity at the reference anatomical position of the heart, and SD is the standard deviation of the magnetic resonance signal intensity.

6. The dual-modality cardiac fibrosis positioning system of magnetic resonance and electrophysiology according to claim 1, characterized in that: The image post-processing module, the individualized information input module, the individualized relative density ratio threshold calculation module, the heart model construction module and the matching and positioning module run on at least one terminal device.

7. The dual-modality cardiac fibrosis positioning system of magnetic resonance and electrophysiology according to claim 6, characterized in that: The terminal device is equipped with a central processing unit, a display, an interface for inputting CMR image information, an interface for inputting electrophysiological data information, and a memory.

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