Patent Application
20250221771
This disclosure relates generally to computer-aided identification of ablation sites to manage ventricular tachycardia.
In general, patients with structural heart disease are prone to develop reentrant ventricular tachycardia, which could lead to sudden cardiac death. Current therapeutic interventions are anti-arrhythmic drugs, implantable cardioverter-defibrillators, and radiofrequency catheter ablation. Anti-arrhythmic drugs can decrease the recurrence of arrhythmia, but may cause severe side-effects and are not effective in reducing mortality. Moreover, anti-arrhythmic drugs have a worse efficacy in protecting patients from sudden cardiac death in comparison to implantable cardiovascular defibrillators. While implantable cardioverter defibrillators may normalize cardiac rhythm as soon as the potentially lethal arrhythmia has occurred, they are often associated with inappropriate shocks, component malfunction, and other complications.
Radiofrequency catheter ablation by direct administration of radiofrequency energy to regions of conduction delay is an effective treatment that results in ventricular tachycardia termination and/or reduction of recurrent ventricular tachycardia. Radiofrequency catheter ablation has an overall success rate of 56-77% in patients with post-myocardial infarction ventricular tachycardias. Precise localization of the perpetrator regions in the heart is paramount in the effectiveness of radiofrequency catheter ablation treatment, however, it is difficult to achieve.
Currently, activation mapping of the tachycardia or electro-anatomical mapping during pacing is the clinical practice to identify myocardial regions to be targeted by ablation. These invasive procedures require multiple ventricular tachycardia inductions that are potentially hazardous to patients. Also, ventricular tachycardia induction may not be possible in sedated patients. If the ventricular tachycardia is inducible, the ventricular tachycardia may be short-lasting or hemodynamically not tolerated. Thus, accurate identification of the regions where re-entrant arrhythmias perpetuate by non-invasive techniques is desirable.
The reentry vulnerability index (RVI) provides a directional quantitative activation-repolarization metric relative to two points that can be used to detect potential entry and exit sites of a re-entrant arrhythmia during one paced rhythm. The reentry vulnerability index is determined based on the spatial relation between activation and repolarization times of a premature beat.
Gene therapy may facilitate non-destructive treatment replacing or supplementing present therapeutic approaches such as radiofrequency catheter ablation. Gene therapy has been shown to be safe and effective in animal models post-myocardial infarction.
Various features of the embodiments can be more fully appreciated, as the same become better understood with reference to the following detailed description of the embodiments when considered in connection with the accompanying figures, in which:
Reference will now be made in detail to example implementations, illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. In the following description, reference is made to the accompanying drawings that form a part thereof, and in which is shown by way of illustration specific exemplary embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the invention. The following description is, therefore, merely exemplary.
Life threatening ventricular tachycardia is often a precursor to sudden cardiac death. Ventricular tachycardia may occur in patients with weakened heart muscle (myocardiopathy) and/or chronic myocardial infarction. Radiofrequency catheter ablation at regions of conduction delay is the standard treatment to prevent the recurrence of these arrhythmias. However, the ventricular-tachycardia induction that is required in this procedure is not always possible in patients with hemodynamic instability. Further, substrate changing may occur under anesthesia, which hampers accurate localization of reentry. Moreover, there may be more than one potential site of reentry, thus several ventricular-tachycardia inductions may be required, which may be difficult for the patient.
Some embodiments solve the aforementioned problems and identify one or more ventricular tachycardia ablation sites non-invasively, without requiring ventricular-tachycardia induction in the patient. Some embodiments utilize a reentry susceptibility map on a personalized 3D left ventricular image-based computer-implemented model to identify such ablation sites. More particularly, some embodiments simulate a premature heartbeat or ventricular tachycardia in the model to gather data used to identify such ablation sites in the patient. Further, some embodiments validate the identified ablation sites by simulating ablation and then attempting to simulate induction of a premature heartbeat or ventricular tachycardia in the model. If the simulated induction is unsuccessful at producing simulated ventricular tachycardia or a premature heartbeat, then the identified ablation site is likely correct.
This disclosure further presents a study of five patients (mean age 67.2±11.7 years, two female, three male) with post myocardial infarction ventricular tachycardia. Each patient underwent pre-ablation cardiac late gadolinium enhanced magnetic resonance imaging and subsequent clinical catheter radiofrequency ablation. Personalized reentry susceptibility maps were produced for the patients, and candidate ablation sites were identified according to various embodiments. Simulated ablations were performed to confirm effectiveness. Further, the identified ablation sites were compared with the patients' clinical ablation sites, which were identified using traditional invasive prior art techniques. Results of this study, which provide proof of the utility of embodiments, are presented herein.
Thus, some embodiments provide novel, non-invasive techniques that use reentry susceptibility maps overlayed on patient-specific 3D computational models to enhance the guidance of clinical ablation, e.g., catheter radiofrequency ablation.
Thus, system 100 includes catheter ablation device 108. Catheter ablation device 108 may be communicatively coupled to computer 106, to a different computer, or may be a standalone device. Catheter ablation device 108 may utilize radiofrequency energy to scar cardiac tissue to prevent or reduce electrical signals from passing using known techniques. Alternately, catheter ablation device 108 may use a different technique to produce scarring, such as cold temperatures, e.g., cryoablation.
System 100 may further, or alternatively, include genetic ablation material 110 for ablation based on localized gene modification. Localized gene modification may be accomplished by conveying genetic ablation material 110 to the ablation site using known techniques.
System 100 also includes magnetic resonance imaging device (MRI) 104. MRI 104 is communicatively coupled to computer 106, e.g., directly or by way of a computer network such as the internet. MRI 104 may be used to obtain tissue characterization of the myocardium of patient 102. More particularly, MRI 104 may be used with a gadolinium-based contrast agent to identify different regions of cardiac tissue, e.g., undamaged tissue versus scar tissue.
Computer 106 may generate and store an electroanatomical geometric model of the left ventricle of patient 102 based on late gadolinium enhanced MRI data produced by MRI 104 from patient 102. The model may be as shown and described in U.S. Pat. No. 10,765,336, entitled “System and Method for Planning a Patient-Specific Cardiac Procedure,” which is hereby incorporated by reference in its entirety. The model may be constructed as follows, by way of non-limiting example. Computer 106 may segment the left ventricle, using a semi-automatic approach, into regions of non-infarcted tissue, gray zone, and core scar. Computer 106 may do so by applying signal intensity thresholding to the late gadolinium enhanced MRI data. An example segmented left ventricle depiction is shown in
Computer 106 may be further configured to generate and store a reentry susceptibility map based on the model, introduced presently and described in detail elsewhere herein, e.g., in reference to
The rapid pacing protocol may utilize multiple pacing locations evenly distributed in the model. In the study of five patients, seven pacing locations were used: three basal, three mid-myocardial, and one apical. The pacing locations may be projected to the nearest region of gray zone. The pacing protocol may include multiple steady state stimuli (these stimuli may be referred to as “S1” herein) followed by a premature stimuli (referred to as “S2” herein) at each pacing site. In the study of five patients discussed herein, S1 pacing at a cycle length of 600 ms was delivered for six beats to achieve a steady-state, followed by a premature stimulus S2 initially given at 300 ms. The S1-S2 timing may be progressively shortened from 300 ms until a premature heartbeat or ventricular tachycardia reentry is induced. If reentry cannot be induced with the first premature stimulus, determined by electrical quiescence, additional successive premature stimuli (S3, S4, S5) may be delivered at 250 ms after the previous stimulus, until ventricular tachycardia is induced. Sustained reentry may be simulated in the model for five seconds, for example. For each ventricular tachycardia morphology induced in the model, the reentrant circuit may identified through visual analysis of the 3D reentrant wave propagation depicted in the model. If reentry does not occur following S5, the model heart may be considered non-inducible from that pacing site.
Computer 106 may compute and record the activation times and repolarization times produced by the simulated ventricular tachycardia induced by the rapid pacing protocol. More particularly, the time-series transmembrane potential may be recorded for a plurality of nodes (e.g., every node) in the model for the duration of each simulated rapid pacing and ventricular tachycardia at each pacing location. For each pacing location, a time of activation (e.g., a time of maximum derivative of the simulated transmembrane potential, dV/dt) and a time of repolarization (e.g., a time of a −70 mV crossing) following the shortest S2 stimulus may be determined for a plurality of nodes (e.g., every node) in the model. Computer 106 may extract and store surface meshes, containing the S2 activation and repolarization times, for each reentry-inducing pacing site. The meshes may be based on (e.g., overlayed on) the tetrahedral meshes of the model. The activation and repolarization time data may be subsequently used to generate a reentry susceptibility map as described further herein, e.g., in reference to
Action potential tracings 408, 410, 412 show repolarization curves for the proximal regions and activation time curves for the distal regions. The widths of the bands between the repolarization times and the activation times provide indications of reentry susceptibility due to wavefronts travelling from the proximal regions to the distal regions. In particular, the narrower the band, the more susceptible the region is to reentry due to the particular wavefront travelling from the proximal to the distal regions.
The width of the bands may be quantified according to various embodiments toward producing a reentry susceptibility map. More particularly, using the recorded repolarization and activation times obtained from the simulated pacing in the model, some embodiments calculate one or more a directional quantitative activation-repolarization metrics, e.g., in the form of reentry vulnerability indices. Such a directional quantitative activation-repolarization metric indicates reentry susceptibility due to wavefronts travelling between the respective proximal and distal region.
In the present context, following a premature S1-S2 stimulus, the directional quantitative activation-repolarization metric relative to two points may be in the form of a time interval duration, which determines the spatial relationship between the S2 following/succeeding repolarization time and the S2 distal activation time. Hence, some embodiments calculate the directional quantitative activation-repolarization metrics between each proximal node i and distal node j (activated later than i) using the surface meshes containing the S2 activation and repolarization times recorded as described above in reference to
Thus, the directional quantitative activation-repolarization metric provides a quantitative measure of the activation-repolarization time interval, which predicts whether a premature activation wavefront is capable of inducing reentry. An example non-limiting definition of a directional quantitative activation-repolarization metric is presented here. For two nodes i and j in a mesh of the myocardial surface for which the activation time due to the S2 beat initiated at node p is later in node j than i, the directional quantitative activation-repolarization metric value between i and j due to pacing at node p is denoted herein as DQAPMi,j,p and may be defined as, by way of non-limiting example:
In Equation (1), RTi,p represents the repolarization time of node i due to pacing at node p, and AT,pj represents the activation time of node j due to pacing at node p. Defined this way, the directional quantitative activation-repolarization metric is a metric between two nodes relative to a direction of wavefront propagation.
In order to express the vulnerability at a particular node i irrespective of choice of distal node, the reentry susceptibility localization map value at a node i may be defined as an average of directional quantitative activation-repolarization metrics DQAPMi,j,p over all pacing sites and over all nodes j that are neighboring nodes to i for which ATj>ATi:
In Equation (2), the term P represents the set of pacing nodes, and the term Nj represents the number of neighboring nodes to j that are distal to node i. The neighboring nodes j to a particular node i may be defined in various ways according to various embodiments. According to some embodiments, the neighboring nodes j to a node i are defined as the nodes that are within a specified distance, e.g., 1 mm, to i. According to some embodiments, the neighboring nodes j to a node i are defined as the nodes that are first or second order neighbors to i, as described presently in reference to
Returning to the discussion of the study of five patients, when a pacing site resulted in reentry, a reentry susceptibility localization map was constructed from the S2 activation and repolarization times preceding the reentry. Each patient's reentry susceptibility localization map was used to choose the virtual ablation locations in the patient-specific models. To account for multiple locations of reentry susceptibility, the study virtually ablated up to three nodes with the lowest reentry susceptibility quantification values from each reentry susceptibility localization map for each patient. Due to the high resolution of the surface data, multiple nodes in close proximity were often classified as one highly vulnerable node. If two ablation locations were within 3 mm of each other, the study only performed one ablation to account for clinical reentry susceptibility quantification diameters and included the node with the next lowest reentry susceptibility quantification value for virtual ablation at a cluster of nodes. The virtual lesions were treated as non-conducting tissue and the diameter of the spherical ablations were performed at 3, 5, 7, and 10 mm to account for myocardial wall thickness and heterogeneous fibrotic remodeling. The virtually ablated heart models were then subjected to the rapid pacing protocol described herein and, if reentry did not occur, the ablation was deemed successful. If the virtual ablations with a diameter of 10 mm did not terminate the reentry, virtual ablations were performed by including the second RVI node at 10 mm (and then again including the third at 10 mm if necessary) in the same fashion and subjected to the rapid pacing protocol. If the virtual ablations were successful, the study decreased the diameters to 7, 5, and 3 mm of the virtual ablations until the reentry was not terminated.
The rapid pacing protocol induced eleven sustained ventricular tachycardia events across the five patients, with nine of the sustained ventricular tachycardia events being unique. Reentry susceptibility values were calculated for all surface nodes that sustained simulated electrical activity (non-injured myocardium and GZ) in each patient using S2 activation and repolarization data.
The ventricular tachycardia exit site in Patient 6 occurs in the basal region of fibrotic remodeling (see 704) and the lowest reentry susceptibility value in the respective cluster is first identified by the second lowest reentry susceptibility value in the reentry susceptibility localization map. Virtual ablation at the first location at 10 mm was unsuccessful, as the ablation did not overlap the exit site. Virtual ablation (4 mm) of the lowest 5, 10, and 15 sites successfully terminated the ventricular tachycardia following rapid pacing. Diagram 706 depicts virtual ablation of the five lowest-valued locations. The virtual ablation resulted in 1.49% of additional non-conducting tissue.
The study of five patients compared the ablation locations determined according to the reentry susceptibility localization map with the ablation locations determined using clinical invasive prior art techniques. That is, the study of five patients evaluated the efficacy and efficiency of the virtual ablations determined according to the reentry susceptibility localization map approach of various embodiments. Virtual ablations were deemed successful if the ventricular tachycardia could not be induced by the rapid pacing protocol. The study compared the fraction of total heart surface and location of each patient's virtual ablations to the clinical lesions. The virtual ablation fraction was calculated using the number of tetrahedra in each ablation of the left ventricular meshes as compared with the total number of tetrahedra in the mesh. The location of the virtual ablations was visually compared to that of the clinical lesions using the same anatomical orientation. Table 1 below depicts parameters relating to the clinical ablations.
Properties of the reentry susceptibility localization maps and the virtual ablation results are summarized in Table 2 below. The overall sensitivity and specificity of using the reentry susceptibility localization map to identify susceptible regions to reentry followed by guided virtual ablation was 100%.
At 902, method 900 includes generating an at least partial electroanatomical geometry model of a left ventricle of a patient. The actions of 902 may include generating an electroanatomical model as shown and described herein, e.g., in reference to
At 904, method 900 includes simulating pacing, in the model, in the left ventricle of the patient in order to induce a simulated premature heartbeat in the model. The actions of 904 may include simulating pacing using a rapid pacing protocol, e.g., as shown and described herein in reference to
At 906, method 900 includes recording an activation time and a repolarization time resulting from the simulating pacing at each of a plurality of nodes in the model. The actions of 906 may include recording the activation times and repolarization times in a surface mesh of the model, e.g., as shown and described herein in reference to
At 908, method 900 includes determining, based on the plurality of activation times and repolarization times recorded per 906, a reentry susceptibility quantification at each of a plurality of nodes in the model. The actions of 908 may include generating a reentry susceptibility localization map, e.g., as shown and described herein in reference to
At 910, method 900 includes identifying a candidate ablation site based on the plurality of reentry susceptibility quantifications. For example, the candidate ablation site may include a location of minimal reentry susceptibility quantification value, e.g., as shown and described herein in reference to
At 912, method 900 includes simulating, in the model, an ablation at the candidate ablation site. The actions of 912 may be as described herein, e.g., in reference to
At 914, method 900 determines whether the simulated ablation prevented a simulated rapid pacing protocol from inducing a simulated reentry ventricular tachycardia in the model. The actions of 914 may be as described herein, e.g., in reference to
At 916, method 900 includes ablating a location in the patient's left ventricle corresponding to the candidate ablation site. Any of a variety of ablation techniques may be utilized, such as by way of non-limiting example, radiofrequency ablation, genetic ablation by localized gene modification, cryoablation, or cardiac radioablation, e.g., based on stereotactic ionizing radiation.
Note that, in general, embodiments are not limited to determining the directional quantitative activation-repolarization metrics, and hence the reentry susceptibility localization map values, based on activation and repolarization times generated by the model disclosed herein. Electrocardiogramaging (ECGI) uses the body surface electrocardiograms and the patient's heart-torso geometry using either MRI or computed tomography (CT). The equivalent dipole layer (EDL) inverse model reconstructs endo-epicardial surface map of activation and repolarization times. The EDL model assumes the current source distribution within the heart is equivalent to a dipole layer at the surface of the myocardium. Accordingly, some embodiments may determine the directional quantitative activation-repolarization metrics, and hence the reentry susceptibility localization map values, based on the activation-repolarization times determined by the ECGI, facilitating a minimally invasive approach to identify the region(s) susceptible to reentry.
Certain embodiments can be performed using a computer program or set of programs. The computer programs can exist in a variety of forms both active and inactive. For example, the computer programs can exist as software program(s) comprised of program instructions in source code, object code, executable code or other formats; firmware program(s), or hardware description language (HDL) files. Any of the above can be embodied on a transitory or non-transitory computer readable medium, which include storage devices and signals, in compressed or uncompressed form. Exemplary computer readable storage devices include conventional computer system RAM (random access memory), ROM (read-only memory), EPROM (erasable, programmable ROM), EEPROM (electrically erasable, programmable ROM), and magnetic or optical disks or tapes.
While the invention has been described with reference to the exemplary embodiments thereof, those skilled in the art will be able to make various modifications to the described embodiments without departing from the true spirit and scope. The terms and descriptions used herein are set forth by way of illustration only and are not meant as limitations. In particular, although the method has been described by examples, the steps of the method can be performed in a different order than illustrated or simultaneously. Those skilled in the art will recognize that these and other variations are possible within the spirit and scope as defined in the following claims and their equivalents.
This application is the national stage entry of International Patent Application No. PCT/US2022/039382, filed on Aug. 4, 2022, and published as WO 2023/018593 A1 on Feb. 16, 2023, which claims the benefit of U.S. Provisional Patent Application Ser. No. 63/231,466, filed Aug. 10, 2021, which are hereby incorporated by reference herein in their entireties.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2022/039382 | 8/4/2022 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 63231466 | Aug 2021 | US |
