Description:FORM 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of invention:

SYSTEM AND METHOD FOR ESTIMATING ABLATION VOLUME OF TISSUE USING IRREVERSIBLE ELECTROPORATION

Applicant

Tata Consultancy Services Limited
A company Incorporated in India under the Companies Act, 1956
Having address:
Nirmal Building, 9th floor,
Nariman point, Mumbai 400021,
Maharashtra, India

Preamble to the description:

The following specification particularly describes the invention and the manner in which it is to be performed.
TECHNICAL FIELD
The disclosure herein relates to electroporation therapy, and, more particularly, to a method and system for estimating ablation volume of tissue using irreversible electroporation (IRE).
BACKGROUND
Irreversible electroporation (IRE) based minimally invasive tissue ablation technique uses electric pulses to cause permanent damage to the cells in the tissue. This technique stimulates the tissue with the short pulsed electric field of short duration through the inserted electrodes. The IRE treatment causes a rise in the temperature of the tissue, often in the vicinity of the electrodes, and limits the usability of the technique for some instances. Instead, high-frequency irreversible electroporation (H-FIRE), which uses a burst of an ultra-short pulsed high-intensity electric field, often bipolar symmetric and asymmetric, alleviates the temperature rise. The high-intensity electric field in H-FIRE causes an electric field-dependent conductivity tensor. Further, the shape and size of the tissue incorporate additional complexity to the problem.
Globally, IRE technique emerges as a promising technique as it overcomes Radio-Frequency technique limitations. However, achieving the desired and the safe ablation volume, i.e., the volume covered by electroporated tissue, depends on multiple factors like a) pulse profile, shape and number of electrodes, besides the IRE treatment parameters, i.e., field strength, pulse type, number of pulses, pulse length, and frequency, and b) the tissue electrical conductivity is often a function of electric field intensity in that range. Hence predicting the proper tissue ablation volume that aids in optimizing the IRE procedure using electroporation is a challenge for the existing techniques.
SUMMARY
Embodiments of the present disclosure present technological improvements as solutions to one or more of the above-mentioned technical problems recognized by the inventors in conventional systems.
For example, in one embodiment, a method for estimating ablation volume of tissue using irreversible electroporation (IRE) is provided. The method includes receiving via biopsy modalities, a standard radiology stain image corresponding to a tissue, wherein the standard stain radiology image provides a plurality of tissue properties of the tissue. The method estimates via an irreversible electroporation (IRE) model, an ablation volume of the tissue from the standard radiology stain image. Further the method builds a three dimensional (3D) IRE computational model, wherein the 3D IRE computational model of the tissue and the estimated ablation volume in response to an electrical pulse applied on to the tissue via a plurality of electrodes, wherein the 3D IRE computational model comprising a temperature profile, an electric field profile and a cell death profile is built based on a first scenario when status of a pulse field electrical stimulation is in pulse a ON-period and a second scenario when the status of the pulse field stimulation is in a pulse OFF-period, and wherein the 3D IRE computational model further comprises a plurality of IRE parameters comprising a plurality of electrode parameters, a plurality of pulse parameters, a plurality of blood parameters, and a plurality of cell death estimation parameters. Further the method obtains a local temperature of the tissue, a tissue electric field, temperature dependent electrical conductivity of the tissue, electric field dependent electrical conductivity of the tissue, and cell death of the tissue, from the built 3D IRE computational model, wherein an optimized pulsed electric field over iterations is obtained from the obtained tissue temperature, the electric field, and the cell death. The method estimates via a statistical cell death model comprising a plurality of electric pulses, duration of an electric pulse, the tissue electric field, and a plurality of tissue parameters, an optimized ablation volume of the tissue, by applying a predefined pulsed electric field on the tissue.
In another aspect, a system for estimating ablation volume of tissue using irreversible electroporation (IRE) is provided is provided. The system comprises a memory storing instructions; one or more communication interfaces; and one or more hardware processors coupled to the memory via the one or more communication interfaces (106), wherein the one or more hardware processors are configured by the instructions to receive, via biopsy modalities, a standard radiology stain image corresponding to a tissue, wherein the standard stain radiology image provides a plurality of tissue properties of the tissue. Further the system estimates, via an irreversible electroporation (IRE) model, an ablation volume of the tissue from the standard radiology stain image. The system further builds a three dimensional (3D) IRE computational model, wherein the 3D IRE computational model of the tissue and the estimated ablation volume in response to an electrical pulse applied on to the tissue via a plurality of electrodes, wherein the 3D IRE computational model comprising a temperature profile, an electric field profile and a cell death profile is built based on a first scenario when status of a pulse field electrical stimulation is in a pulse ON-period and a second scenario when the status of the pulse field stimulation is in a pulse OFF-period, and wherein the 3D IRE computational model further comprises a plurality of IRE parameters comprising a plurality of electrode parameters, a plurality of pulse parameters, a plurality of blood parameters, and a plurality of cell death estimation parameters. Further the system obtains a local temperature of the tissue, a tissue electric field, temperature dependent electrical conductivity of the tissue, electric field dependent electrical conductivity of the tissue, cell death of the tissue, from the built 3D IRE computational model, wherein an optimized pulsed electric field over iterations is obtained from the obtained tissue temperature, the electric field, and the cell death. The method estimates, via a statistical cell death model comprising a plurality of electric pulses, duration of an electric pulse, the tissue electric field, and a plurality of tissue parameters, an optimized ablation volume of the tissue, by applying a predefined pulsed electric field on the tissue.
In yet another aspect, there are provided one or more non-transitory machine-readable information storage mediums comprising one or more instructions, which when executed by one or more hardware processors causes a method for estimating ablation volume of tissue using irreversible electroporation (IRE) is provided. The method includes receiving via biopsy modalities, a standard radiology stain image corresponding to a tissue, wherein the standard stain radiology image provides a plurality of tissue properties of the tissue. The method estimates via an irreversible electroporation (IRE) model, an ablation volume of the tissue from the standard radiology stain image. Further the method builds a three dimensional (3D) IRE computational model, wherein the 3D IRE computational model of the tissue and the estimated ablation volume in response to an electrical pulse applied on to the tissue via a plurality of electrodes, wherein the 3D IRE computational model comprising a temperature profile, an electric field profile and a cell death profile is built based on a first scenario when status of a pulse field stimulation is in a pulse ON-period and a second scenario when the status of the pulse field stimulation is in a pulse OFF-period, and wherein the 3D IRE computational model further comprises a plurality of IRE parameters comprising a plurality of electrode parameters, a plurality of pulse parameters, a plurality of blood parameters, and a plurality of cell death estimation parameters. Further the method obtains a local temperature of the tissue, a tissue electric field, temperature dependent electrical conductivity of the tissue, electric field dependent electrical conductivity of the tissue, and cell death of the tissue, from the built 3D IRE computational model, wherein an optimized pulsed electric field over iterations is obtained from the obtained tissue temperature, the electric field, and the cell death. The method estimates via a statistical cell death model comprising a plurality of electric pulses, duration of an electric pulse, the tissue electric field, and a plurality of tissue parameters, an optimized ablation volume of the tissue, by applying a predefined pulsed electric field on the tissue.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles:
FIG. 1 is a functional block diagram of a system, for estimating the ablation volume of tissue using Irreversible electroporation (IRE), in accordance with some embodiments of the present disclosure.
FIGS. 2 is a flow diagram illustrating the method for estimating the ablation volume of tissue using Irreversible electroporation (IRE), in accordance with some embodiments of the present disclosure.
FIG. 3 illustrates IRE computational model-based tissue ablation application, in accordance with some embodiments of the present disclosure.
FIG. 4 illustrates simulation result for an electric potential at the end of eighth electric pulse and corresponding electric field lines, in accordance with some embodiments of the present disclosure.
FIGS. 5A, 5B, 5C and 5D illustrates stimulating electric pulse pattern, temperature profile validation in the tissue under pulsed IRE treatment with plate-type electrodes and needle-type electrodes, in accordance with some embodiments of the present disclosure.
FIG. 6 illustrates the temperature profile at the end of each pulse, in accordance with some embodiments of the present disclosure.
FIG. 7 illustrates an electrical conductivity profile at the end of each pulse, in accordance with some embodiments of the present disclosure.
FIGS. 8A and 8B illustrate solutions for electric field profiles and cell survival profiles reproduced for the validation of Two-Dimensional (2D) IRE computational model, in accordance with some embodiments of the present disclosure.
FIG. 9 illustrates comparison of ablation zone using statistical cell death model and Electric Field Theory (EFT) model reproduced for the validation of the model, in accordance with some embodiments of the present disclosure.
FIG. 10 illustrates validation of the 2D IRE computational model reproducing survival profile, in accordance with some embodiments of the present disclosure.
FIG. 11 illustrates survival profiles in the IRE treatment with a pair of plate-type electrodes at a fixed pulse length in 2D, in accordance with some embodiments of the present disclosure.
FIG. 12 illustrates the survival profiles in the IRE treatment with the pair of plate-type electrodes in Three-Dimensional (3D) setup, in accordance with some embodiments of the present disclosure.
FIG. 13 illustrates the survival profiles in the IRE model with the pair of plate-type electrodes at a fixed electrode potential in 2D, in accordance with some embodiments of the present disclosure.
FIG. 14 illustrates the survival profiles in the IRE computational model with two pairs a pair of plate-type electrodes at the fixed electrode potential in 2D, in accordance with some embodiments of the present disclosure.
FIG. 15 illustrates the survival profiles of the tissue with two pairs of needle-type electrodes at the fixed pulse length in 3D, in accordance with some embodiments of the present disclosure.
FIG. 16 illustrates changes in survival profiles with pulse length in the tissue with the two pairs of needle-type electrodes in 2D, in accordance with some embodiments of the present disclosure.
FIGS.17A and 17B illustrate temperature in tissue in the IRE treatment with the pulsed electric field with the pair of plate-type electrodes and the two pairs of needle-type electrodes, in accordance with some embodiments of the present disclosure.
It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems and devices embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DETAILED DESCRIPTION OF EMBODIMENTS
Exemplary embodiments are described with reference to the accompanying drawings. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the scope of the disclosed embodiments.
Electroporation is permeabilizing cell membranes via a locally induced electrical field. Cell membrane or tissue membrane permeabilization can be either reversible, allowing molecular interaction such as in electrochemotherapy, gene electro-transfer, transdermal drug delivery and electrofusion of cell or irreversible, causing cell death. Irreversible electroporation (IRE) has overcome the ideal benchmark treatment such as thermal, e.g., radiofrequency ablation, microwave ablation, laser ablation, and chemical ablation techniques.
Though the topic of electric field effect on living cells is more than a few centuries old, the systematic analysis of cell death in pulsed electric field treatment was reported a few decades ago in the literature (“Sale AJH, Hamilton WA. Effects of high electric fields on microorganisms: I. Killing of bacteria and yeasts. Biochimica et Biophysica Acta (BBA) – General Subjects. 1967;148(3):781-788.”). This work mentioned that the rapid cell death can be observed with increasing number of electric pulses and the likelihood of survival of a few microorganisms when exposed to squared electric pulses. Further, this study states that the electric field with shorter pulses requires the more electric pulses to achieve a certain degree of the cell death. Additionally, the cell death increases sharply with the increase in an electric field strength when pulse length and the number of electric pulses remain unaltered. This sensitivity on the electric field strength is microorganism specific. It also reports that an increase in temperature for 20oC to 40oC does not influence the lethal damage of a cell, suggesting non-thermal cell damage.
Later in literature (“Canatella PJ, Karr JF, Petros JA, Prausnitz MR. Quantitative study of electroporation-mediated molecular uptake and cell viability. Biophysical journal. 2001;80(2):755{764.”) experimentally studied the cellular uptake and the cell viability in the pulsed electric field. This study claims that previously used parameters, i.e., charge delivered, and energy supplied, are inappropriate for modelling cellular uptake and viability. Instead, a complex dependency on the electrical parameters is presented as the viability and uptake depend upon the intricate mechanism of pore creation, growth, and resealing; transport through electrophoresis, electroosmosis, and diffusion, and associated effects. This study suggests a decrease in the cell viability with increasing in the electric field strength at a particular pulse length and number of pulses. This study also claims that at a specific electroporation condition, the uptake and loss of the cell viability decrease as cell density increases.
The findings of these studies concerning the effects of the electric field on the microorganisms and cells attracted scientific community with a greater interest in several applications, including tumor cell ablation. One of the existing studies (“Davalos RV, Mir L, Rubinsky B. Tissue ablation with irreversible electroporation. Annals of biomedical engineering. 2005; 33: 223-231.”) reported a theoretical analysis to delineate the achievable ablation volume in an undesired tissue through IRE. According to this study, resultant local electric field, due to stimulation with the pulsed electric field, beyond a threshold value can cause the tissue ablation. The strength of the stimulating electric field is determined such that temperature rise in the tissue remains below 50oC to avoid thermal damage. The model used in this study consists of estimating the electric field distribution and temperature profile in the tissue in pulsed field stimulation. The results infer that the ablation volume achievable through IRE before the onset of the thermal effects is comparable to the other techniques, such as cryosurgery. Additionally, this work suggests various IRE control parameters, such as field strength, pulse length, electrode dimensions, number of electrodes, etc. Several significant experimental and theoretical studies have been since reported in literature dealing with the Electric Field Theory (EFT) based tissue-ablation for clinical treatment planning without causing thermal damage.
To understand and estimate the ablation volume in literature (“Peleg M. A model of microbial survival after exposure to pulsed electric fields. Journal of the Science of Food and Agriculture. 1995;67(1):93-99.”) proposed a statistical cell death model. Further in literature (“Golberg A, Rubinsky B. A statistical model for multidimensional irreversible electroporation cell death in tissue. Biomedical engineering online. 2010;9(1):1-13.”), with the computed electric field, the ablation volume is predicted using Fermi equation-based Peleg model, often called as Peleg-Fermi model. Several other studies consider this statistical cell death model to study the IRE-based tissue ablation and demonstrate better usability of the model in explaining the behavior of the tissue ablation volume for the treatment parameters, such as field strength, pulse length, and the number of pulses. This statistical cell death model suggests a broad transitional zone instead of a sharp boundary between the regions of killed and survived cells. It also predicts that fractional cell death occurs in the tissue treated with the pulsed electric field even below the defined threshold field strength in the EFT.
The EFT and statistical cell death model-based estimations of the tissue ablation volume in IRE suggest that the electrode number and configuration are critical parameters in clinical planning using IRE for different scenarios. Several studies reported efficient IRE treatment for the large ablation volume using multiple electrodes and varied configurations. Sometimes, the location of the undesired tissue in an organ requires electrodes of different shapes, such as plate-type electrodes for electroporation in the liver.
Despite wide acceptance of the IRE technique in medical ablation therapy, little is known about the mechanistic insight of the cell or tissue death, the relationship between pulse parameters, electrode configuration and the tissue ablation process in the cell membrane. Further a few probing techniques, like fluorescent dyes, cell impedance monitoring, and transmembrane potential visualization, provide electroporation insights. Still, there is a need for a better understanding of the cell death pathway and their systemic response regarding the abscopal effects of tissue or tumor cell and cell death mechanisms after exposure to the electric pulse. However, a gap exists in explaining the dynamics of the tissue ablation and its mechanisms, such as necrosis, apoptosis, necroptosis and pyroptosis, led by the electroporation. Moreover, the advancement in computational power and modelling techniques enables personalization and provides insight into the dynamic electroporation process, which clinicians and regulatory bodies have widely acknowledged as digital evidence.
Achieving the desired and the safe ablation volume, i.e., the volume covered by electroporated tissue, depends on multiple factors like a) pulse profile, shape and number of electrodes, besides the IRE treatment parameters, i.e., field strength, pulse type, number of pulses, pulse length, and frequency, and b) the tissue electrical conductivity is often a function of electric field intensity in that range. Hence without considering the above-mentioned multiple factors, predicting the proper ablation volume of the tissue that aids in optimizing the IRE procedure using the electroporation is a challenge for conventional methods.
To overcome the challenges of the conventional methods, embodiments of the present disclosure provide a method and system for estimating ablation volume of the tissue using irreversible electroporation (IRE). The disclosed method estimates the ablation volume of the tissue by building a 3D IRE computational model through an electrical stimulation. Further local temperature of the tissue, tissue electric field, temperature dependent electrical conductivity of the tissue, electric field dependent electrical conductivity of the tissue, and cell death of the tissue, are calculated using the 3D IRE computational model. The electrical conductivity of the tissue varies with either the electric field or the temperature based on a relative sensitivity of the tissue. An optimized pulsed electric field over iterations is obtained from the obtained tissue temperature, the electric field, and the cell death. Further an optimized ablation volume of the tissue is estimated using a statistical cell death model comprising a plurality of electric pulses, duration of an electric pulse, the tissue electric field, and a plurality of tissue parameters, by applying a predefined pulsed electric field on the tissue. The 3D IRE computational model with different types and geometrical configurations of electrodes, besides estimating the optimized pulsed electric field comprising of optimal electric field properties, and the optimized ablation volume aids a surgeon in clinical treatment planning.
Referring now to the drawings, and more particularly to FIG. 1 through FIG. 17B, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments and these embodiments are described in the context of the following exemplary system and/or method.
FIG. 1 is a functional block diagram of a system 100, for estimating the ablation volume of the tissue using IRE, in accordance with some embodiments of the present disclosure. In an embodiment, the system 100 includes a processor(s) 104, communication interface device(s), alternatively referred as input/output (I/O) interface(s) 106, and one or more data storage devices or a memory 102 operatively coupled to the processor(s) 104. The system 100 with one or more hardware processors is configured to execute functions of one or more functional blocks of the system 100. The one or more processors 104 may be one or more software processing components and/or hardware processors.
Referring to the components of system 100, in an embodiment, the processor(s) 104, can be one or more hardware processors 104. In an embodiment, the one or more hardware processors 104 can be implemented as one or more microprocessors, GPU, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the one or more hardware processors 104 are configured to fetch and execute computer-readable instructions stored in the memory 102. In an embodiment, the system 100 can be implemented in a variety of computing systems including laptop computers, notebooks, hand-held devices such as mobile phones, workstations, mainframe computers, servers, and the like.
The I/O interface(s) 106 can include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface to display the generated target images and the like and can facilitate multiple communications within a wide variety of networks N/W and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as WLAN, cellular and the like. In an embodiment, the I/O interface (s) 106 can include one or more ports for connecting to number of external devices or to another server or devices.
The memory 102 may include any computer-readable medium known in the art including, for example, volatile memory, such as static random-access memory (SRAM) and dynamic random-access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.
In an embodiment, database 108 is comprised in the memory 102, wherein the database 108 comprises information on biopsy modalities, standard radiology stain image, and a plurality of IRE parameters. The memory 102 further comprises a plurality of modules (not shown) for various technique(s) such as the IRE technique, and the like. The memory 102 further comprises modules (not shown) implementing techniques such as, the 3D IRE computational model, the statistical cell death model, an electric field model, and a thermal model. The above-mentioned technique(s) are implemented as at least one of a logically self-contained part of a software program, a self-contained hardware component, and/or, a self-contained hardware component with a logically self-contained part of a software program embedded into each of the hardware component (e.g., hardware processor 104 or memory 102) that when executed perform the method described herein. The memory 102 further comprises (or may further comprise) information pertaining to input(s)/output(s) of each step performed by the systems and methods of the present disclosure. In other words, input(s) fed at each step and output(s) generated at each step are comprised in the memory 102 and can be utilized in further processing and analysis.
FIG. 2 is a flow diagram illustrating the method for estimating the ablation volume of tissue using Irreversible electroporation (IRE), in accordance with some embodiments of the present disclosure. In an embodiment, the system 100 comprises one or more data storage devices or the memory 102 operatively coupled to the processor(s) 104 and is configured to store instructions for execution of steps of the method 200 by the processor(s) or one or more hardware processors 104. The steps of method 200 of the present disclosure will now be explained with reference to the components or blocks of the system 100 as depicted in FIG. 1, and the steps of flow diagram as depicted in FIG. 2. Although process steps, method steps, techniques or the like may be described in a sequential order, such processes, methods, and techniques may be configured to work in alternate orders. In other words, any sequence or order of steps that may be described does not necessarily indicate a requirement that the steps to be performed in that order. The steps of processes described herein may be performed in any order practical. Further, some steps may be performed simultaneously.
Referring to the steps of the method 200, at step 202 of the method 200, the one or more hardware processors 104 receive, via biopsy modalities, the standard radiology stain image corresponding to the tissue, wherein the standard stain radiology image provides the plurality of tissue properties of the tissue. Configuration setup of the IRE model comprises initializing electrode parameters (electrode, type of electrode, shape, and dimension, the distance between electrodes, mono pulse, bipolar pulse, mono/bipolar pulse, heat capacity, electrical conductivity, thermal conductivity), electrode configuration, pulse parameters (shape, amplitude, on-time and off-time, frequency), tissue parameters (pre-specified organ, tissue density), cell death estimation parameters, and tissue boundary conditions.
At step 204 of the method 200, the one or more hardware processors 104 estimate, by using the IRE model, an ablation volume of the tissue from the standard radiology stain image.
At step 206 of the method 200, the one or more hardware processors 104 build, the 3D IRE computational model, wherein the 3D IRE computational model corresponds to the standard radiology stain image of the tissue and the estimated ablation volume in response to an electrical field applied on to the tissue via the plurality of electrodes. The 3D IRE computational model comprising a temperature profile, an electric field profile and a cell death profile is built based on a first scenario when status of a pulse field stimulation is in a pulse ON-period and a second scenario when the status of the pulse field stimulation is in a pulse OFF-period. The 3D IRE computational model further comprises the plurality of IRE parameters comprising a plurality of electrode parameters, a plurality of pulse parameters, a plurality of blood parameters, and a plurality of cell death estimation parameters. Type of the plurality of electrodes comprises one of (i) a pair of needle type electrodes, (ii) a couple of pair of needle type electrodes, and (iii) a pair of plate type electrodes.
In simulation phase of the electrical stimulation, for a defined pulse wave, the 3D IRE computational model identifies the pulse ON-period, or the pulse OFF-period based on supply of electrode potential. During the pulse field stimulation when the status of the pulse field stimulation is in the pulse ON-period, based on the relative sensitivity of the tissue of the electrical conductivity on the temperature and the electric field. The pulse field stimulation steps comprise:
Calculating the electric field in the tissue using the electric field model.
Calculating current density(J), electric current (I), charge density (Q).
Calculating the temperature of the tissue based on the electric field using a thermal model.
Estimating the cell death of the tissue using the statistical cell-death model.
The electrical conductivity of the tissue is the function of one of (i) the temperature and (ii) the electric field, based on the relative sensitivity of the tissue.
During the pulse field stimulation when the status of the pulse field stimulation is in the pulse OFF-period, the temperature in the tissue is calculated using the thermal model and the electrical conductivity of the tissue is calculated based on the temperature.
During the pulse field stimulation if the relative sensitivity of the tissue of the electrical conductivity is comparatively higher on the temperature, the electrical conductivity is calculated based on the temperature. The pulse field stimulation is iteratively performed for a predefined pulse length. For high frequency IRE, the electrical conductivity is calculated based on the temperature. If the relative sensitivity of the tissue of the electrical conductivity is higher on the electric field, the electrical conductivity is calculated based on the electric field. At the end of the pulse ON-period, data corresponding to the temperature, the electrical conductivity and the cell death are stored, and time is updated for further time-steps and interpretation. In this pulse field simulation, the calculation of the temperature, the electric field, and the cell death is a time-marching process that continues until the pulse count reaches its pre-defined maximum pulse.
An electric potential (Ø) due to the applied pulse field stimulation through the inserted plurality of electrodes to the tissue is modelled by a Laplace's equation, mathematically represented as:
?.( s?Ø) = 0 (1)
The electric field is calculated as the negative of the spatial gradient of electric potential in the tissue.
s is the electrical conductivity of the tissue. The electrical conductivity of the tissue can be a function of local temperature or the magnitude of the local electric field. The temperature dependent electrical conductivity of the tissue can be modelled as:
s = s_0(1+ a(T-T_0)) (2)
where s_0 is the baseline electrical conductivity corresponding to initial tissue temperature T_0 and a is a is a scalar coefficient.
The temperature (T) in the tissue can be determined using thermal equation:
?C ?T/?t = ?·(k?T) -? ??_b ?_b C_b (T - T_b) + s|??|^2 + q^m (3)
where ? is density, C is heat capacity, k is thermal conductivity of the tissue, ? is blood perfusion rate, and q^m is rate of metabolic heat generation, Tb is blood temperature, subscript b distinguishes properties of blood.
At surfaces of the tissue exposed to an ambient, zero flux boundary conditions can be considered for solution of the electric field and the temperature. The electric field and the temperature with the surface of the tissue exposed to the ambient is given by:
s?Ø. n ^ = 0 (4a)
k?T .n ^ = 0 (4b)
where n ^ is normal to surface of the tissue.
In case of Two-Dimensional (2D) simulation and Three-Dimensional (3D) simulation with a pair of plate-type electrodes and the 3D simulation with multiple needle-type electrodes, electrode surfaces exposed to the ambient i.e., undergo convective heat transfer. With a heat transfer coefficient h for the tissue and air interface, the convective flux boundary condition is given by:
k?T.n ^=h(T-T_a ) (5)
where T_a is air temperature.
For the 3D IRE computational model, temperature variation is generally insufficient to alter the electrical conductivity of the tissue. Hence, the electrical conductivity depends upon intensity of the electric field due to increase in tissue membrane's permeability at a stronger field intensity. A symmetric sigmoid function model can be used to express the electric field of the electrical conductivity as:
s = s_0 + s_(m-s_0 )/(1+A.exp(-(E-B)/C) ) (6)
where s_m is the maximum attainable electrical conductivity, A, B, and C are the tissue-specific constants that define shape of the sigmoid, E is the magnitude of the local electric field strength in V\/cm.
Symmetrical sigmoid Gompertz curve function is an alternative model for the electric field dependent electrical conductivity of the tissue, given as:
s = s_0+ (s_m- s_0) ?e^(-ae )?^(-b|E| ) (7)
where a and b are pulse length-dependent coefficients defining displacement and growth rate for the Symmetrical sigmoid Gompertz curve function, respectively.
The expressions for the pulse length-dependent coefficients are given as:
a=-5 X 10^(-6) t^2 + 0.04t +2.803 (8a)
b=-7 X 10^(-9) t^2 + 5 X 10^(-6) t + 0.002 (8b)
where t is the pulse length in µs, and these expressions are valid for the pulse length of up to 400 µs.
Moreover, for the time-varying pulse field stimulation through the electrodes, the time-dependent field solution is obtained, irrespective of the type of dependency of s.
The cell death in the tissue is estimated by using the statistical cell death model as:
S(E,n) = 1/(1+exp(-(E-E_C)/A) ) (9)
where E_C is the critical electric field strength at which the fractional survival level is 0.5, A is a parameter defining steepness of the survival curve around this critical field strength. The cell death is quantitatively represented by survival, zero survival corresponds to complete cell death and unit fractional survival corresponds to the living cells.
Parameters E_c (n) and A(n) are dependent upon the number of pulses, and the dependency can be expressed as Algebraic relationships.
E_c (n) = E_c0 exp?(-K_1 n) (10a)
A(n) = A_0 exp?(-K_2 n) (10b)
where E_c0 and = A_0 are curve-fitting constants.
In another approach, E_c (n,t) and A (n, t) can be functions of the number of pulses and the pulse length and can be estimated by experimental analysis. At a constant pulse length, E_c (n) and A (n) can be expressed as:
E_c (n)= E_c1 exp(-K_1 n) +E_c2 exp(-K_2 n) (11a)
A(n) = A_1 exp(-K_3 n) +A_2 exp(-K_4 n) (11b)
At a constant number of pulses, E_c (t) and A(t) is expressed as:
E_c (t)= E_c3 exp(-K_5 t) +E_c4 exp(-K_6 t) (12a)
A(t) = A_3 exp (?-K?_7 t) +A_4 exp (?-K?_8 t) (12b)
In every successive pulse, a certain fraction of cell death occurs, accumulating into a total cell death due to the application of a certain number of pulses.
The pseudocode of building the 3D IRE computational model for obtaining the electric field in the tissue, temperature in the tissue, and the cell death is as follows:
Input: Pulse Parameters; Electrode Parameters; Tissue Parameters; Blood Parameters; Cell Death Estimation Parameters
0: Output: temperature, electric field, Cell death
0: System Initialization:
t ? 0 : t_end (t_end = number of pulse × pulse frequency);
S_v ? 1, when pulse ON period; or S_v ? 0, when pulse OFF period;
s_T ? s(T), for the temperature dependent electrical conductivity of the tissue; or
s_E ? s(E), for electric field dependent electrical conductivity of the tissue;
P ? 1 (monopulse) or 2 (H - FIRE)
1: for t ? 0 : t_end do
2: if S_v = 1 then
3: E = -??; from Electric field solver (eq. 1)
4: T ? update from Temperature solver (eq. 2)
5: J,I,Q ? from corresponding modules
6: if s = s(T) and P = 2 then
s ? update from s_T
7: else
s ? update from s_E;
8: end if
9: if S_v (t) = 1 and S_v (t+?t) = 0 then
10: Estimate the cell death from the statistical cell death model
11: Save : Output;
12: end if
13: else if S_v = 0 then
14: T ? update from Temperature solver (eq. 2)
15: s ? update from s_T
16: end if
The pulse field stimulation is iteratively performed for the predefined pulse length, to predict the ablation volume of the tissue for the predefined pulsed electric field comprising an electric pulse sequence, and wherein for a predefined ablation volume, the electrical stimulation is iteratively performed to predict the optimized pulsed electric field comprising the electric pulse sequence, until the predefined ablation volume is achieved.
At step 208 of the method 200, the one or more hardware processors 104 obtain, via the one or more hardware processors, the tissue electric field, local temperature of the tissue, the temperature dependent electrical conductivity of the tissue, the electric field dependent electrical conductivity of the tissue, from the built 3D IRE computational model, wherein the optimized pulsed electric field over iterations is obtained from the obtained temperature, the electric field, and the cell death. The optimized pulsed electric field comprises a plurality of optimal electric field properties comprising an optimal electric pulse sequence, an optimal voltage supplied to the electrodes, an optimal number of electric pulses, an optimal electric pulse length, an optimal electric pulse frequency, an optimal number of electrodes, and selection of type of electrodes.
At step 210 of the method 200, the one or more hardware processors 104 estimate, via a statistical cell death model comprising a plurality of electric pulses, duration of an electric pulse, the tissue electric field, and a plurality of tissue parameters, the optimized ablation volume of the tissue, by applying the pre-defined pulsed electric field on the tissue.
Experimental Results
A mono-polar rectangular electrical pulse protocol of 1 Hz frequency with a train of eight pulses is adapted for investigation. As a process of validation, the simulations of the 3D IRE computational model were performed using the pair of needle-type and the pair of plate-type electrodes. For the validation, a set of parameters considered is shown in Table 1. The 3D IRE computational model and mechanism of the cell death are investigated for various electrode configurations: i) the pair of plate-type electrodes and ii) two pairs of needle-type electrodes.

Category Variable name Value in 2D Value in 3D Unit
Domain setup Length along X-axis 3:3E - 02 3:3E - 02 m
Width along Y-axis 3:3E - 02 3:3E - 02 m
Height along Z-axis - 1:1E - 02 m
Electrode setup Length - 7:0E – 03 m
Width 1:50E – 03 1:50E – 03 m
Thickness 1:50E – 03 1:50E – 03 m
Separation between anode & cathode 8:0E - 03 8:0E - 03 m
IRE parameters Voltage to distance ratio 25000 25000 V/m

Number of periods 8 8
Frequency 1 1 Hz
Pulse length 5:0E – 2
5:0E – 2
s
Pulse shape Rectangular Rectangular
Pulse type Unipolar Unipolar
Tissue parameters Initial temperature 310:15 310:15 K
Thermal conductivity 0:512 0:512 W/m K
Electrical conductivity 0:126 0:126 S/m
Density 1050 1050 Kg/m3
Heat capacity 3600 3600 J kg K

Rate of metabolic heat generation 420 420 W/ m3
Blood parameters Arterial blood temperature 310:15 310:15 K
Density 1060 1060 Kg/ m3
Heat capacity 3600 3600 J/Kg K
Blood profusion rate 0.0044 0.0044 1/s
Electrode parameters Density 1050 1050 Kg/ m3

Heat capacity 490 490 J/Kg K
Electrical conductivity 1.4E + 06 1.4E + 06 S/m
Thermal conductivity 16.3 16.3 W/m K
Table 1
FIG. 3 illustrates the 3D IRE computational model-based tissue ablation application, in accordance with some embodiments of the present disclosure. This application allows a user to provide input parameters comprising the electrode parameters, pulse sequence protocol, the tissue parameters, and the cell death parameters through an interface. Computations are executed by the 3D IRE computational model and further the application facilitates visualization of the simulation results in 2D and 3D. The application comprises of three modules: a temperature distribution profile, the electric field distribution profile, and the cell survival profile. This application also allows exporting or saving of the simulation results for further analysis.
The 3D IRE computational model-based tissue ablation application is validated in two phases: (1) the temperature distribution profile, which in turn validates the local electric field solution in the domain; (2) the cell survival profile, as a function of electric field strength, number of pulses, pulse length and type of electrodes, for constant electrical conductivity and the electrical conductivity based on the electric field.
Further the ablation volumes of the tissue are estimated by the 3D IRE computational model for IRE treatment with plate-type electrodes and multiple pairs of needle-type electrodes. In the 3D IRE computational model, involving a pair of electrodes inserted into the tissue, the stimulations are provided through applying the electric potential at one electrode and zero potential is maintained at the other electrode. FIG. 4 illustrates simulation result for an electrical potential at the end of eighth electric pulse and corresponding electric field lines, in accordance with some embodiments of the present disclosure. More specifically FIG. 4 illustrates simulation result of the IRE model at the end of eighth electric pulse and corresponding electric field lines, considering the temperature dependency of the electrical conductivity.
FIGS. 5A, 5B, 5C and 5D illustrates stimulating electric pulse pattern, temperature profile validation in the tissue under pulsed IRE treatment with plate-type electrodes and needle-type electrodes, in accordance with some embodiments of the present disclosure. More specifically FIGS. 5B, 5C and 5D illustrates comparison of the temperature profile validation in the tissue under pulsed IRE treatment with the exist techniques in the literature (“Marino M, Lujan E, Mocskos E, Marshall G. OpenEP: An open-source simulator for electroporation-based tumor treatments. Scientific reports. 2021;11(1):1{15.” – Marino et al.) and (“Lackovic I, Magjarevic R, Miklavcic D. Three-dimensional finite-element analysis of joule heating in electrochemotherapy and in vivo gene electrotransfer. IEEE Transactions on Dielectrics and Electrical Insulation. 2009;16(5):1338{1347.”- Lackovic et al.)
In case of the plate-type electrode-based IRE treatment two locations are selected – location 1 in the middle of two electrodes, and location 2 on the electrode adjacent to the tissue. Whereas, for the needle-type electrode-based IRE treatment, three locations are selected – (1) the middle of two electrodes, (2) a quarter of the gap apart from the anode, and (3) close to the anode. For both the cases, i.e., plate-type electrodes and the needle-type electrodes, the validation is made for two different tissue conductivities of s = 0:126 S/m and s = 0:504 S/m. FIG. 5A specifically illustrates an electric pulse pattern to stimulate the tissue for validation. FIG. 5B illustrates comparison of temperatures for the IRE treatment with a pair of plate-type electrodes at the (1) middle of two electrodes and (2) adjacent to the plate-type electrode for s = 0:126 S/m and s = 0:504 S/m. FIGS. 5C illustrates the IRE treatment with the pair of needle-type electrodes. More specifically FIG. 5C illustrates the IRE treatment with the pair of needle-type electrodes, the temperature profile at (1) the middle of two electrodes, (2) a quarter distance apart from the electrode, and (3) a point close to the electrode for s = 0:126 S/m. More specifically FIG. 5C illustrates the IRE treatment with the pair of needle-type electrodes, the temperature profile at (1) the middle of two electrodes, (2) a quarter distance apart from the electrode, and (3) a point close to the electrode for s = 0.504 S/m. For the reported results, the data points are collected for tip and trough of the curves, and the intermediate points are not collected, therefore, the data points are connected by the dotted straight line in FIGS. 5B, 5C and 5D.
It is observed form FIG. 5B that the simulation results for the IRE treatment with the plate-type electrodes agree very well with results in the literature (“Lackovic I, Magjarevic R, Miklavcic D. Three-dimensional finite-element analysis of joule heating in electrochemotherapy and in vivo gene electrotransfer. IEEE Transactions on Dielectrics and Electrical Insulation. 2009;16(5):1338{1347.”) In the case of a pair of needle-type electrodes-based IRE treatment, as shown in FIGS. 5C and 5D the simulated temperature recordings at locations 1 and location 2 agree very well with the reported results in the literature ((“Marino M, Lujan E, Mocskos E, Marshall G. OpenEP: An open-source simulator for electroporation-based tumor treatments. Scientific reports. 2021;11(1):1-15.”) and (“Lackovic I, Magjarevic R, Miklavcic D. Three-dimensional finite-element analysis of joule heating in electrochemotherapy and in vivo gene electrotransfer. IEEE Transactions on Dielectrics and Electrical Insulation. 2009;16(5):1338{1347.”). However, a small deviation has been observed for location 3, i.e., close to the electrodes, which is possibly due to the difference in geometry, square cross-section in the 3D IRE computational model and the circular cross-section in the reported results, of electrodes and thereby the difference in field line distribution at proximity of the electrodes. Further, it can be observed that this deviation magnifies with the increase in the number of pulses.
FIG. 6 illustrates the temperature profile at the end of each pulse, in accordance with some embodiments of the present disclosure.
FIG. 7 illustrates an electric conductivity profile at the end of each pulse, in accordance with some embodiments of the present disclosure. It is observed from the temperature profile curves in FIGS. 5C and 5D, the results infer that the temperature rise is higher in the vicinity of the electrodes and decreases with the increasing distance from the electrodes, which can also be seen in the temperature profile in FIG. 6 represents the temperature profiles at the end each pulse before the termination of the stimulation. A symmetric temperature profile can be observed with respect to plane perpendicular to a line connecting the electrodes and passing through midline joining the electrode pairs. The minimum temperature rise occurs between the two electrodes at a middle point.
The electrical conductivity of the tissue is often a function of the local temperature, as given by Equation (2). According to the IRE model, the electrical conductivity increases with the temperature. Therefore, electrical conductivity profiles in the domain appear similar to the temperature profile, as shown in FIG. 7.
Further second phase of the validation is carried out by comparing the simulated cell survival profiles with the reported results in the literature (“Golberg A, Rubinsky B. A statistical model for multidimensional irreversible electroporation cell death in tissue. Biomedical engineering online. 2010;9(1):1-13.”) and (“Yang Y, Moser MAJ, Zhang E, Zhang W, Zhang B. Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro. PLOS ONE. 2018;13(4):1-18”). For the estimation of the cell viability using Fermi type model of Peleg in the computational model, existing works in the literature considered a setup with a pair of parallel electrodes of 1 mm diameter and placed at a gap of 1 cm in a tissue domain of constant electrical conductivity of 0:42 S/m. For this reported cell viability study in literature (“Golberg A, Rubinsky B. A statistical model for multidimensional irreversible electroporation cell death in tissue. Biomedical engineering online. 2010;9(1):1-13.”), the electric field is solved in the 2D tissue domain with a constant tissue-electrode boundary potential and insulating boundary condition at the outer edges of the domain.
FIGS. 8A and 8B illustrate solutions for the electric field profiles and the cell survival profiles reproduced for the validation of the 3D IRE computational model, in accordance with some embodiments of the present disclosure. More specifically FIG. 8A illustrates magnitude of the electric field distribution, and FIG. 8B illustrates the cell survival profiles.
Simulated magnitude of the electric field distribution using the IRE model is shown in FIG. 8A. Simulation result findings infer that the magnitude of the electric field distribution is qualitatively similar to the reported profile in the literature (“Golberg A, Rubinsky B. A statistical model for multidimensional irreversible electroporation cell death in tissue. Biomedical engineering online. 2010;9(1):1-13.”) The deviation in the maximum electric field strength is less than 0.5%. This difference could possibly be due to the electrode's shape variation. Based on the simulated electric field distribution, further following the statistical cell death model, the cell survival profiles can be estimated. Further the cell survival profiles obtained from the simulation and those reported in literature (“Golberg A, Rubinsky B. A statistical model for multidimensional irreversible electroporation cell death in tissue. Biomedical engineering online. 2010;9(1):1-13.”) are compared. For the different combinations of the non-dimensional voltages C = V0/E_C0 L, number of pulses, and pulse lengths, the cell death profiles are presented in FIG. 8B The statistical cell death model presents distribution of the cell viability, in contrast to the nature of prediction by the EFT, which draws a sharp boundary between the dead cells and living cells. In the statistical cell death model, the transition zone depends upon the IRE treatment parameters. In FIG. 8B a qualitatively similar cell survival profile is observed as reported in literature (“Golberg A, Rubinsky B. A statistical model for multidimensional irreversible electroporation cell death in tissue. Biomedical engineering online. 2010;9(1):1-13.”).
FIG. 9 illustrates comparison of ablation zone using statistical cell death model and Electric Field Theory (EFT) model reproduced for the validation of the model, in accordance with some embodiments of the present disclosure. FIG. 10 illustrates validation of the 3D IRE computational model reproducing survival profile, in accordance with some embodiments of the present disclosure. Parameters corresponding to part (a) of FIG. 10 is 1000 V, 60 pulses, 50 µs, part (b) of FIG. 10 is (b) 2000 V, 60 pulses, 50 µs, part (c) of FIG. 10 is 3000 V, 60 pulses, 50 µs, part (d) of FIG. 10 is 2000 V, 30 pulses, 50 µs, part (e) of FIG. 10 is 2000 V, 60 pulses, 50 µs, part (f) of FIG. 10 is 2000 V, 90 pulses, 50 µs, part (g) of FIG. 10 is 2000 V, 60 pulses, 10 µs, part (h) of FIG. 10 is 2000 V, 60 pulses, 50 µs, part (i) of FIG. 10 is 2000 V, 60 pulses, 100 µs.
FIG. 11 illustrates survival profiles in the IRE treatment with the pair of plate-type electrodes at a fixed pulse length in in 2D, in accordance with some embodiments of the present disclosure. Panels corresponding to the survival profiles are shown in FIG. 11 at (a) 500 V, (b) 1000 V, (c) 2000 V, and (d) 3000 V electrode potentials for (i) 1, (ii) 8, (iii) 10, (iv) 30, (v) 60; and (vi) 90 pulses at the pulse length of 25 µs.
Further, the 3D IRE computational model is validated by comparing the simulated cell survival profiles with the results in literature (“Yang Y, Moser MAJ, Zhang E, Zhang W, Zhang B. Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro. PLOS ONE. 2018;13(4):1-18.”). Here the simulations are performed with the electric field of the pulse length of 10-100 µs, and the tissue conductivity is considered to be dependent upon the local electric field strength, as expressed equation (7). The electrical conductivity of a healthy cervical tissue is considered as s_0 = 0.22973 S/m and the s_max = 2.8 ? s_0 = 0:64324 S/m 2.8??? ?s_0?=?0.64324?S/m. The other constants for the electric field dependent electrical conductivity of the tissue are the constants for curve fitting of the experimental data reported by study in literature (“Neal II RE, Garcia PA, Robertson JL, Davalos RV. Experimental characterization, and numerical modeling of tissue electrical conductivity during pulsed electric fields for irreversible electroporation treatment planning. IEEE Transactions on Biomedical Engineering. 2012;59(4):1076=1085.”). The electrical stimulation is provided to the electrode with a specific voltage Ø = V_0, and the other electrode is maintained at the voltage Ø = 0. The distance between the centroids of the electrodes is 10 mm, and a squire of 1 mm edge length is considered.
The cell survival profile for the IRE treatment with the stimulation of pulses of 100 µs pulse length at 1 Hz and the electrode potential Ø = 2500 V is shown in FIG. 9, in accordance with some embodiments of the present disclosure. With the solved electric field (in V/cm) in the tissue domain, the survival profiles are drawn using the statistical Peleg-Fermi model. An elliptic ablation volume enclosing the electrodes is obtained in the computations, which is qualitatively inline with the reported cell death profile in literature (“Yang Y, Moser MAJ, Zhang E, Zhang W, Zhang B. Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro. PLOS ONE. 2018;13(4):1-18.”). Also, the electric field magnitude contour lines, and thereby, the predictions for the EFT model from the computation, appear very similar to the reported results in literature in literature (“Yang Y, Moser MAJ, Zhang E, Zhang W, Zhang B. Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro. PLOS ONE. 2018;13(4):1-18.”).
In the same setup, the ablation volumes with the variation of the IRE treatment parameters are reproduced, as reported in literature (“Yang Y, Moser MAJ, Zhang E, Zhang W, Zhang B. Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro. PLOS ONE. 2018;13(4):1-18.”).
In the part (a)-(c) of FIG. 10, shows the changes in the ablation volume of tissue with the change in the applied electrode potential from 1000 V to 3000 V for 60 pulses of 50 µs pulse length. In the part (d)-(f) of FIG. 10, shows the ablation volumes of tissue for 30, 60 and 90 pulses of 50 µs pulse length with the electrode potential of 2000 V. In part (g)-(i) of FIG. 10, shows the ablation volume of the tissue for the stimulation with 2000 V electrode potential for the pulse lengths of 10 µs, 50 µs, and 100 µs for 60 pulses. In all the cases, the obtained cell death profiles qualitatively match with the reported findings in literature (“Yang Y, Moser MAJ, Zhang E, Zhang W, Zhang B. Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro. PLOS ONE. 2018;13(4):1-18.”).
Further the ablation volume of the tissue in the IRE treatment set-up with is extended with the pair of plate-type electrodes in two dimensions and the couple of pairs of needle-type electrodes. In earlier case, the pair of plate-type electrodes of width of 0:5 mm and length of 6 mm were placed at a distance of 4.4 mm, as used in an earlier study in literature (“Lackovic I, Magjarevic R, Miklavcic D. Three-dimensional finite-element analysis of joule heating in electrochemotherapy and in vivo gene electrotransfer. IEEE Transactions on Dielectrics and Electrical Insulation. 2009;16(5):1338-1347.”). The electrodes are attached to the two opposing outer faces of a block of tissue, as shown in FIG. 11. For the IRE treatment, different combinations of the applied potential are considered in the range of 500 V to 3000 V, pulse length ranging from 10 µs to 100 µs, and the number of pulses in the range of 1 to 90. The IRE treatment parameters are selected for estimation of the cell death as the necessary parameters for the statistical cell death model for the healthy cervical tissue.
FIG. 12 illustrates survival profiles in the IRE treatment with the pair of plate-type electrodes in 3D setup, in accordance with some embodiments of the present disclosure.
The changes in ablation volume of the tissue with the variation of the number of pulses ranging from 1 to 90, at the fixed applied potential and pulse width, are shown in panels (i) – (vi) of FIG. 11 respectively, i.e., the rows of FIG. 11. Also, the panels in the columns of FIG. 11, e.g., part (a) of FIG. 11 to part (d) of FIG 11, show the change in the ablation volume of the tissue with the variation of applied electric potential from 500 V to 3000 V at the constant pulse length and the pulse number. In both cases of parameter variations, the considered electric pulse length is 25 µs.
At the constant electric potential and pulse length, i.e., in the rows of FIG. 11, the fractional cell death and the ablation volume of the tissue increase with increasing pulse number. For a weak electric potential, e.g., 500 V in row (a) of the FIG. 11, more than half of the cells survive even when exposed to many electric pulses. At a strong electric potential, e.g., 3000 V in row (d) of FIG. 11, a large fractional cell death is observed even for a few pulses, as shown in panel (d) of FIG. 11 for 8 pulses, though the ablation volume of the is small. This ablation volume of the tissue increases with the increasing pulse number. The panels in the FIG. 11 in a particular row, moving left to right, also suggest a decrease in the transition region of the cell death with the increasing the number of pulses.
The comparison of the panels in the columns of FIG. 11, i.e., increasing the electric potential downward at the constant pulse length and the pulse number, suggests that the ablation volume of the tissue increases with the increasing applied electric potential. The only exception is for a single pulse stimulation, as shown in the first column of the FIG. 11, where cell death is negligible. At a sufficiently large number of pulses, the fractional cell death and the ablation volume of the tissue increase with increasing the electrode potential. At a particular number of pulses, with increasing stimulating the electric potential, e.g., column (iv) of the FIG. 11 for 30 pulses, the shape of the transition region of the cell death changes, while the width of this transition region does not change much.
A low cell death profile can be seen at the combination of weak electrode potential and fewer pulses, i.e., the panels near the top-left corner of FIG. 11. Whereas, at the strong applied electrode potential and many pulses, i.e., the panels near the lower-bottom corner of Fig. 11, produce large ablation volumes. Other combinations of these two parameters result in intermediate fractional cell death and ablation volumes of the tissues.
FIG. 12 shows the sliced 3D simulation results for the ablation volume of the tissue in a block of tissue in the IRE model with the pair of plate-type electrodes. These results are shown for a parameter set of the electrode potential of 2000 V, pulse length of 25 µs and at three different numbers of pulses of 30, 60, and 90 for the three panels, respectively. These results are just the 3D counterparts of the results obtained in 2D simulation, as shown in panels iv-vi of part (c) of FIG. 11. It can be found that the 2D simulation results are very similar to that of the 3D simulation, except for the additional predictions for the depth and the shape of the ablation volume of the tissue in the 3rd direction, which is a very obvious missing component of 2D simulations.
FIG. 13 illustrates survival profiles in the IRE model with a pair of plate-type electrodes at a fixed electrode potential in 2D, in accordance with some embodiments of the present disclosure. Panels correspond to the survival profiles at 1000 V electrode potential for (a) 10, (b) 30, and (c) 60 pulses and pulse length of (i) 15 µs, (ii) 25 µs, (iii) 35 µs, (iv) 50 µs, (v) 75 µs, and (vi) 100 µs.
In this case the ablation volume of the tissue is analyzed by considering the variation in the pulse length and the number of pulses, while the electrode potential is constant at 1000 V, as shown in FIG. 13. In this case, the panels in a row, i.e., from (i) to (vi) of the FIG. 13, show the change in the ablation volume of the tissue with increasing the pulse length, ranging from 15 µs, 25 µs, 35 µs, 50 µs, 75 µs, and 100 µs, respectively, at the constant pulse number (e.g., 10 pulse for row (a) of FIG. 13) and the electrode potential. Whereas the panels in columns (6 columns) of FIG. 13 show the estimated ablation volumes of the tissue with the increasing number of pulses, i.e., (a) 10, (b) 30, and (c) 60 pulses, while the pulse length and the applied electrode potential remain constant.
The panels in a row of FIG. 13, i.e., for the increasing the pulse length from 15 µs to 100 µs, at the constant electric field of 1000 V and number pulses, row (a) of FIG. 13 for 10 pulses as an example, suggest that the fractional cell death and consequently the ablation volume of the tissue increase. It can also be observed that this variation in the pulse length does not cause much change in the thickness of the transition region of the cell death. The column-wise arrangement of panels in FIG. 13 shows the change in the ablation volume of the tissue with the variation of the pulse number from 10 to 30, at the constant electrode potential of 1000 V and the pulse length, for example 15 µs in column (i) of FIG. 13. Similar to the observation in FIG. 11, the column-wise arrangement of panels in FIG. 13 shows that the size of the ablation volume of the tissue increases with the increasing number of pulses, as both cases are the same. From FIG. 13, it can also be observed that for the IRE model with less number of pulses and shorter pulse length, e.g., panels towards the left of row (a) of FIG. 13, the cell survival is quite high. Whereas, for a larger number of pulses, irrespective of pulse length, it is observed from panels in rows (b) and (c) of FIG. 13, significantly higher the cell death and the larger ablation volumes of the tissue are observed. This observation infers that the larger ablation volumes of the tissue can be achievable by applying the large number of pulses of any pulse length.
Further the ablation volume of the tissue is analyzed using the two pairs of needle-type electrodes and the influence of parameters of the IRE model. In this case, two pairs of electrodes are placed at the corners of a square of the edge length equal to the inter-electrode gap of 10mm. The electrodes on the left-hand side are provided with the same type of polarity applying a potential Ø = V_0, and the opposite polarity is maintained at electrodes on the right-hand side with zero potential. The electric potentials are supplied to the electrodes simultaneously according to the pulse protocol.
FIG. 14 illustrates survival profiles in the IRE model with two pairs a pair of plate-type electrodes at a fixed electrode potential in 2D, in accordance with some embodiments of the present disclosure. Panels of FIG. 14 correspond to the survival profile at (a) 1000 V, (b) 2000 V, and (c) 3000 V electrode potentials for the pulse length of 25 µs and (i) 10, (ii) 30, (iii) 60, and (vi) 90 pulses.
FIG. 14 and FIG. 16 shows the cell survival profiles at different conditions in the tissue with two pairs of electrodes in 2D. In FIG. 14, the results are shown at the constant pulse length of 25 µs, and in FIG. 16, both the electrode potential and the number of pulses is maintained at fixed values of 3000 V and 60, respectively.
At the pulse length of 25 µs, the changes in the ablation volume of the tissue with the number of pulses from 10-90 are shown in the panels in rows of FIG. 14 at constant values of the electrode potentials, i.e., in panels (a) i -iv for V_0= 1000 V, panels (b)i-iv for V_0 = 2000 V, and panels (c)i-iv for V_0 = 3000 V, respectively. Simulation results infer that the shape of the ablation volume of the tissue is very much different from the plate-type electrodes. The ablation volume of the tissue increases with the number of pulses at the fixed electrode potential and the pulse length. As observed earlier, the thickness of the transition zone decreases with the increasing the number of pulses.
In FIG. 14, the panels from top to bottom, i.e., (a) to (c), show the change in the ablation volume of the tissue with the increasing applied electrode potentials for the different number of pulses corresponding to the columns, e.g., column (i) for 10 pulses. In a particular column corresponding to a specific pulse number, e.g., column (i) for 10 pulses, the ablation volume of the tissue increases with the increasing applied electrode potential. Also, a significant change in the shape of the ablation volume of the tissue is observed with the change in applied electrode potential.
FIG. 15 illustrates survival profiles of the tissue with two pairs of needle-type electrodes at a fixed pulse length in 3D, in accordance with some embodiments of the present disclosure. Panels of FIG. 15 correspond to the survival profiles at 2000 V electrode potential for (a) 30, (b) 60, and (c) 90 pulses and pulse length of 25 µs. The ablation volumes of the tissue obtained from the 3D simulations for the IRE model of tissue with the two pairs of needle-type electrodes are shown in FIG. 14. These results are obtained for the fixed electrode potential of 2000 V and the pulse length of 25 µs, while the numbers of pulses considered are 30; 60; and 90. These 3D simulation results provide a complete shape of the ablation volume of the tissue, including information in all three directions of the coordinate system. Further, the effect of pulse length on the ablation volume of the tissue is shown in the panels of FIG. 16 by varying the pulse length from 15 µs to 100 µs for the applied electrode potential of 3000 V and 60 pulses. In this case, as the pulse length increases, the ablation volume of the tissue increases, whereas the shape of the ablation volume of the tissue and thickness of the transition zone remain almost unaltered.
FIG. 16 illustrates changes in survival profiles with pulse length I the tissue with two pairs of needle-type electrodes in 2D, in accordance with some embodiments of the present disclosure. Panels of FIG.16 correspond to the survival profile at 60 pulses of (a) 15 µs, (b) 35 µs, (c) 50 µs and (d) 100 µs pulse lengths for 1000 V electrode potential. The IRE process is always associated with the temperature change in the domain. The magnitude of this temperature rise depends upon the pulse length, number of pulses, magnitude of the electric field and other parameters. As the objective of the IRE is to cause the tissue ablation without causing detrimental thermal effects, the selection of IRE parameters should be such that the temperature rise remains under control during the process and establish a controlled cell death. FIGS. 17A and 17B shows relationship between temperature change and pulse duration and, consequently, the number of pulses for different electrode potentials and the pulse lengths. This thermal behavior of the IRE process is studied by recording the temperature responses at a location middle to the electrodes in a set-up with the pair of plate-type electrodes and at a quarter distance apart from the electrode for the two pairs of needle-type electrodes set-up.
FIGS.17A and 17B illustrate temperature in tissue in the IRE treatment with the pulsed electric field with a pair of plate-type electrodes and two pairs of needle-type electrodes. Simulation results shown in FIGS. 17A and 17B, infer a nonlinear temperature rise with the number of pulses for both the plate-type electrode and the two pairs of needle-type electrodes. The IRE treatment with higher electrode potential or larger pulse length causes a higher temperature rise. On the other hand, for lower electrode potential or shorter pulse length, the temperature rise is lower. Therefore, carefully selecting the combinations of IRE parameters can help prevent detrimental thermal effects by maintaining the temperature within the desired level.
In the IRE-based tissue ablation, the 3D IRE computational model estimates the ablation volumes of the tissue as the effect of the electric field and tissue conductivity due to local temperature. Besides the simplest, the pair of needle-type electrode-based treatment strategy, the IRE model can simulate the outcome for the different types of electrodes such as multiple pair of needle-type electrodes and the pair of plate-type electrodes and thereof in 2D and 3D. The IRE model is integrated with the statistical cell death prediction model, which is much more realistic than the EFT model. The simulation suggests the achievable ablation volume of the tissue using the plate-type electrodes is significantly larger than the pair of needle-type electrodes, and the shapes of the tissue ablation zones are significantly different. Further, the cell death probability and the ablation volumes of the tissue are larger for the plate-type electrodes than the two pair of needle-type electrodes for the same inter-electrode separation. However, the larger temperature rise is observed in the IRE treatment with the plate-type electrodes at the same inter-electrode separation and the electrode potential.
The written description describes the subject matter herein to enable any person skilled in the art to make and use the embodiments. The scope of the subject matter embodiments is defined by the claims and may include other modifications that occur to those skilled in the art. Such other modifications are intended to be within the scope of the claims if they have similar elements that do not differ from the literal language of the claims or if they include equivalent elements with insubstantial differences from the literal language of the claims.
Achieving the desired and the safe ablation volume, i.e., the volume covered by electroporated tissue, depends on multiple factors like a) pulse profile, shape and number of electrodes, besides the IRE treatment parameters, i.e., field strength, pulse type, number of pulses, pulse length, and frequency, and b) the tissue electrical conductivity is often a function of electric field intensity in that range. Hence without considering the above-mentioned multiple factors, predicting the proper ablation volume of the tissue that aids in optimizing the IRE procedure using the electroporation is a challenge for conventional methods.
To overcome the challenges of the conventional methods, embodiments of the present disclosure provide a method and system for estimating tissue ablation volume using irreversible electroporation (IRE). The disclosed method estimates the ablation volume of the tissue by building a computational model through simulating IRE model. An electrical conductivity of the tissue varies with the electric field and the temperature based on a relative sensitivity of the tissue. Further the optimized pulsed electric field over iterations is obtained from local temperature of the tissue, the temperature dependent electrical conductivity, and the electric field dependent electrical conductivity, and the cell death. Further an optimized ablation volume of the tissue is estimated using a statistical cell death model, by applying the obtained optimized pulsed electric field on the tissue. The IRE technique with different types and geometrical configurations of electrodes, besides estimating optimized pulsed electric field comprising of optimal electric field properties, and the optimized ablation volume aids a surgeon in customizing the IRE technique for clinical treatment planning.
It is to be understood that the scope of the protection is extended to such a program and in addition to a computer-readable means having a message therein; such computer-readable storage means contain program-code means for implementation of one or more steps of the method, when the program runs on a server or mobile device or any suitable programmable device. The hardware device can be any kind of device which can be programmed including e.g., any kind of computer like a server or a personal computer, or the like, or any combination thereof. The device may also include means which could be e.g., hardware means like e.g., an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination of hardware and software means, e.g., an ASIC and an FPGA, or at least one microprocessor and at least one memory with software processing components located therein. Thus, the means can include both hardware means and software means. The method embodiments described herein could be implemented in hardware and software. The device may also include software means. Alternatively, the embodiments may be implemented on different hardware devices, e.g., using a plurality of CPUs.
The embodiments herein can comprise hardware and software elements. The embodiments that are implemented in software include but are not limited to, firmware, resident software, microcode, etc. The functions performed by various components described herein may be implemented in other components or combinations of other components. For the purposes of this description, a computer-usable or computer readable medium can be any apparatus that can comprise, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope of the disclosed embodiments. Also, the words “comprising,” “having,” “containing,” and “including,” and other similar forms are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include random access memory (RAM), read-only memory (ROM), volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.
It is intended that the disclosure and examples be considered as exemplary only, with a true scope of disclosed embodiments being indicated by the following claims.
, Claims:We Claim:

1. A processor implemented method (200), the method comprising:
receiving (202), via biopsy modalities controlled by one or more hardware processors, a standard radiology stain image corresponding to a tissue, wherein the standard stain radiology image provides a plurality of tissue properties of the tissue;
estimating (204), via an irreversible electroporation (IRE) model controlled by the one or more hardware processors, an ablation volume of the tissue from the standard radiology stain image;
building (206) , a three dimensional (3D) IRE computational model, executed via the one or more hardware processors, wherein the 3D IRE computational model of the tissue and the estimated ablation volume in response to an electrical pulse applied on to the tissue via a plurality of electrodes, wherein the 3D IRE computational model comprising a temperature profile, an electric field profile and a cell death profile is built based on a first scenario when status of a pulse field stimulation is in a pulse ON-period and a second scenario when the status of the pulse field stimulation is in a pulse OFF-period, and wherein the 3D IRE computational model further comprises a plurality of IRE parameters comprising a plurality of electrode parameters, a plurality of pulse parameters, a plurality of blood parameters, and a plurality of cell death estimation parameters;
obtaining (208), via the one or more hardware processors, a local temperature of the tissue, tissue electric field, temperature dependent electrical conductivity of the tissue, electric field dependent electrical conductivity of the tissue, and cell death of the tissue, from the built 3D IRE computational model, wherein an optimized pulsed electric field over iterations is obtained from the obtained tissue temperature, the electric field, and the cell death; and
estimating (210), via a statistical cell death model comprising a plurality of electric pulses, duration of an electric pulse, the tissue electric field, and a plurality of tissue parameters executed by the one or more hardware processors, an optimized ablation volume of the tissue, by applying a predefined pulsed electric field on the tissue.

2. The processor implemented method as claimed in claim 1, wherein during the pulse field stimulation when the status of the pulse field stimulation is in the pulse ON-period, based on the relative sensitivity of the tissue of the electrical conductivity on the temperature and the electric field, the pulse field stimulation steps comprises:
calculating the electric field of the tissue using an electric field model;
calculating current density(J), electric current (I), charge density (Q);
calculating the temperature of the tissue based on the electric field using a thermal model; and
estimating the cell death of the tissue using a statistical cell-death model.

3. The processor implemented method as claimed in claim 1, wherein during the pulse field stimulation when the status of the pulse field stimulation is in the pulse OFF-period, the temperature of the electrical conductivity in the tissue is calculated using the thermal model and the electrical conductivity of the tissue is calculated based on the temperature.

4. The processor implemented method as claimed in claim 1, wherein during the pulse field stimulation in the pulse ON-period and the pulse OFF-period the temperature profile, the electric field profile and the cell death profile are generated from the calculated temperature, the electric field, and the cell death.
5. The processor implemented method as claimed in claim 2, wherein if the relative sensitivity of the tissue of the electrical conductivity is comparatively higher on the temperature, the electrical conductivity is calculated based on the temperature, wherein for high frequency IRE, the electrical conductivity is calculated based on the temperature, and wherein if the relative sensitivity of the tissue of the electrical conductivity is comparatively higher on the electric field, the electrical conductivity is calculated based on the electric field.

6. The processor implemented method as claimed in claim 1, wherein the electrical conductivity of the tissue is function of one of (i) the temperature and (ii) the electric field, based on the relative sensitivity of the tissue.

7. The processor implemented method as claimed in claim 1, wherein type of the plurality of electrodes comprises one of (i) a pair of needle type electrodes, (ii) a couple of pairs of needle type electrodes, and (iii) a pair of plate type electrodes (iv) different configurations of two and three pairs of needle type electrodes.

8. The processor implemented method as claimed in claim 1, wherein the optimized pulsed electric field comprises a plurality of an optimal electric pulse sequence, an optimal voltage supplied to the electrodes, an optimal number of electric pulses, an optimal electric pulse length, an optimal electric pulse frequency, an optimal number of electrodes, and selection of type of electrodes.

9. The processor implemented method as claimed in claim 1, wherein the pulse field stimulation is iteratively performed for a predefined pulse length, to predict the ablation volume of the tissue for the predefined pulsed electric field comprising an electric pulse sequence, and wherein for a predefined ablation volume, the electrical stimulation is iteratively performed to predict the optimized pulsed electric field comprising the electric pulse sequence, until the predefined ablation volume is achieved.

10. A system (100) comprising:
a memory (102) storing instructions;
one or more communication interfaces (106); and
one or more hardware processors (104) coupled to the memory (102) via the one or more communication interfaces (106), wherein the one or more hardware processors (104) are configured by the instructions to:
receive, via biopsy modalities, a standard radiology stain image corresponding to a tissue, wherein the standard stain radiology image provides a plurality of tissue properties of the tissue;
estimate, via an irreversible electroporation (IRE) model, an ablation volume of the tissue from the standard radiology stain image;
build a three dimensional (3D) IRE computational model, wherein the 3D IRE computational model of the tissue and the estimated ablation volume in response to an electrical pulse applied on to the tissue via a plurality of electrodes, wherein the 3D IRE computational model comprising a temperature profile, an electric field profile and a cell death profile is built based on a first scenario when status of a pulse field stimulation is in a pulse ON-period and a second scenario when the status of the pulse field stimulation is in a pulse OFF-period, and wherein the 3D IRE computational model further comprises a plurality of IRE parameters comprising a plurality of electrode parameters, a plurality of pulse parameters, a plurality of blood parameters, and a plurality of cell death estimation parameters;
obtain a local temperature of the tissue, a tissue electric field, temperature dependent electrical conductivity of the tissue, electric field dependent electrical conductivity of the tissue, cell death of the tissue, from the built 3D IRE computational model, wherein an optimized pulsed electric field over iterations is obtained from the obtained tissue temperature, the electric field, and the cell death; and
estimate, via a statistical cell death model comprising a plurality of electric pulses, duration of an electric pulse, the tissue electric field, and a plurality of tissue parameters, an optimized ablation volume of the tissue, by applying a predefined pulsed electric field on the tissue.

11. The system as claimed in claim 10, wherein during the pulse field stimulation when the status of the pulse field stimulation is in the pulse ON-period, based on the relative sensitivity of the tissue of the electrical conductivity on the temperature and the electric field, the pulse field stimulation steps comprises:
calculating the electric field of the tissue using an electric field model;
calculating current density(J), electric current (I), charge density (Q);
calculating the temperature of the tissue based on the electric field using a thermal model; and
estimating the cell death of the tissue using a statistical cell-death model.

12. The system as claimed in claim 10, wherein during the pulse field stimulation when the status of the pulse field stimulation is in the pulse OFF-period, the temperature in the tissue is calculated using the thermal model and the electrical conductivity of the tissue is calculated based on the temperature.

13. The system as claimed in claim 10, wherein during the pulse field stimulation in the pulse ON-period and the pulse OFF-period the temperature profile, the electric field profile and the cell death profile are generated from the calculated temperature, the electric field, and the cell death.

14. The system as claimed in claim 11, wherein if the tissue relative sensitivity of the electrical conductivity is comparatively higher on the temperature, the electrical conductivity is calculated based on the temperature, wherein for high frequency IRE, the electrical conductivity is calculated based on the temperature, and wherein if the relative sensitivity of the tissue of the electrical conductivity is comparatively higher on the electric field, the electrical conductivity is calculated based on the electric field.

15. The system as claimed in claim 10, wherein the electrical conductivity of the tissue is function of one of (i) the temperature and (ii) the electric field, based on the relative sensitivity of the tissue.

16. The system as claimed in claim 10, wherein type of the plurality of electrodes comprises one of (i) a pair of needle type electrodes, (ii) a couple of pair of needle type electrodes, and (iii) a pair of plate type electrodes (iv) different configurations for two and three pairs of needle type electrodes.

17. The system as claimed in claim 10, wherein the optimized pulsed electric field comprises an optimal electric pulse sequence, an optimal voltage supplied to the electrodes, an optimal number of electric pulses, an optimal electric pulse length, an optimal electric pulse frequency, an optimal number of electrodes, and selection of type of electrodes.

18. The system as claimed in claim 10, wherein the pulse field stimulation is iteratively performed for a predefined pulse length, to predict the ablation volume of the tissue for the predefined pulsed electric field comprising an electric pulse sequence, and wherein for a predefined ablation volume, the electrical stimulation is iteratively performed to predict the optimized pulsed electric field comprising the electric pulse sequence, until the predefined ablation volume is achieved.

Dated this 29th Day of November 2023

Tata Consultancy Services Limited
By their Agent & Attorney

(Adheesh Nargolkar)
of Khaitan & Co
Reg No IN-PA-1086