DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This communication is in response to the Application No. 18/779,742 filed 07/22/2024. Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 07/22/2024 has been entered and considered. Initialed copies of the PTO-1449 by the examiner are attached.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Regarding independent claim 1 and its dependent claim(s) 2-15:
Step 1 analysis: Claim 1 is directed to a system which is a machine that falls within one of the four statutory categories.
Step 2A prong 1 analysis: Claim 1 recites, in part:
“analyze the one or more phase images to determine values for one or more properties of the tissue surrounding the implant; and predict, based at least in part on the analyzed one or more phase images, a temperature increase of the medical implant that will occur during a subsequent imaging scan of the patient”
The limitations as shown above, as drafted, are processes that, under the broadest reasonable interpretation, cover the performance of the limitations in the mind which fall within the “Mental Process” grouping of abstract ideas. The limitations of:
“analyze one or more phase images to determine values for one or more properties... and predict... a temperature increase of the medical implant that will occur during a subsequent imaging scan of the patient” recite steps that the human mind can perform through an observation and evaluation, such as the human mind can analyze a phase image and determine a particular property based on the observed image and infer/predict that such property will likely lead to a temperature increase, using, for example, a chart with specific characteristics determined based on the properties of the image. Accordingly, the claim recites an abstract idea.
Step 2A prong 2 analysis: this judicial exception is not integrated into a practical application. In particular, the claim recites the following element(s) –
“one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient”
“a processor operatively coupled to the memory”
The steps of “one or more phase images of a medical implant” merely constitute pre-solution activities involving data gathering such as acquiring data, and thus are insignificant extra-solution activities. Similarly, limitations of “a processor operatively coupled to the memory” are recited as being performed by generic computer components at a high level of generality and amount to no more than instructions to apply the exception using a generic computer.
In view of the foregoing, the additional elements do not integrate the abstract idea into a practical application.
Step 2B analysis: there are no additional elements that amount to significantly more than the judicial exception. Moreover, the additional element(s) as mentioned above do not amount to significantly more for the claim as a whole. Please see MPEP §2106.05. The claim is directed to an abstract idea.
For all the foregoing reasons, claim 1 does not comply with the requirements of 35 USC 101.
Dependent claims 2-3 do not provide elements that overcome the deficiencies of the independent claim. Specifically, the claims recite limitations in the form of additional elements involving data gathering. Such limitations include “imaging pre-scan is conducted for 30 seconds or less” and “a first amount of power used for the pre-scan is less than a second amount of power used for the subsequent imaging scan” which recite insignificant extra-solution activity.
Dependent claims 4-6 do not provide elements and/or limitations that overcome the deficiencies of the independent claim. Specifically:
Claim 4 recites, in part, “the processor predicts the temperature increase of the medical implant based at least in part on a desired power to be used during the subsequent imaging scan”. As described above in claim 1, the inclusion of a processor is recited at such a high level of generality and amount to no more than mere instructions to apply the exception using a generic computer. Similarly, predicting based on a desired power in which will likely lead to a temperature increase, using, for example, a chart with specific characteristics determined recites a mental process of observation and evaluation.
Claim 5 recites, in part, “the processor predicts the temperature increase of the medical implant based at least in part on a desired duration of the subsequent imaging scan” which similarly includes the same analysis performed in claim 4 with the substitution of a “desired duration” instead of a “desired power”.
Claim 6 recites, in part, “the processor analyzes the one or more phase images to determine a specific absorption rate (SAR) of the medical implant, and wherein the processor predicts the temperature increase based at least in part on the determined SAR”. As mentioned in claim 4, the inclusion of a processor is recited at such a high level of generality and amount to no more than mere instructions to apply the exception using a generic computer. Additionally, the analyzing of one or more phase images to determine a specific absorption rate (SAR) of the medical implant and predicting a temperature increase involve a mental process. Such as, a human mind can, through observation and evaluation, of phase image(s) can determine a SAR based on a chart indicating characteristics and/or properties of a tissue and predict an estimate of a temperature increase based on such information.
Dependent claims 7-11 do not provide elements and/or limitations that overcome the deficiencies of the independent claim. Specifically, the claims recite specific properties of the tissue in the form of additional elements involving data gathering and thus provide nothing more than insignificant extra-solution activities.
Dependent claim 12-15 similarly do not provide elements and/or limitations that overcome the deficiencies of the independent claim. Specifically:
Claim 12 recites, in part, “the processor utilizes a neural network to analyze the one or more phase images, and wherein the neural network includes a first hidden layer and a hidden second layer, wherein the first hidden layer includes 11 hidden neurons and the second hidden layer includes 9 hidden neurons”. The claim recites analyzing one or more phase images by a neural network but the claim does not provide any details about how the neural network operates or how the analyzing is made, and the plain meaning of “analyzing” encompasses mental observations or evaluations, e.g., a radiologist mental identification of properties in a phase image. Similarly, the “processor” is recited at a high level of generality, i.e., as generic computer performing generic computer functions.
Claim 13 recites, in part, “an imaging device in communication with the processor, wherein the imaging pre-scan is performed using the imaging device, and wherein the one or more phase images are generated by the imaging device”. The claim recites an “imaging device” however, does not provide specifics as to what constitutes such imaging device and provides nothing more than a data gathering element in the form of extra-solution activity.
Claim 14 recites, in part, “the processor compares the predicted temperature increase of the medical implant to a temperature increase threshold, and wherein the processor issues an alert in response to a determination that the predicted temperature increase exceeds the temperature increase threshold”. As mentioned above, the “processor” is recited at a high level of generality, i.e., as generic computer performing generic computer functions. Additionally, the comparison of a predicted temperature increase to a threshold and an alert in response to exceeding the temperature increase involve mental observations or evaluations, e.g., a radiologist may compare the estimation of future temperatures to a chart and determine when a prediction may exceed a safety measure to issue an alert.
Claim 15 recites, in part, “the processor is configured to determine, based on the analysis of the one or more phase images and a desired duration of the subsequent imaging scan, a maximum power that can be used during the subsequent imaging scan such that the temperature increase does not exceed a temperature increase threshold”. As mentioned above, the “processor” is recited at a high level of generality, i.e., as generic computer performing generic computer functions. Moreover, the plain meaning of “determine” and “analysis” encompasses mental observations or evaluations, e.g., a radiologist may determine based on the observed characteristics of the phase images, a maximum power to be used to remain in a “safe” operation when performing subsequent scans using, for example, a chart indicating a power distribution safety based on observations and evaluation previously performed.
Independent claim 16 and its dependent claims 16-20:
Independent claim 16 recites similar limitations as described in claim 1 and does not comply with the requirements of 35 USC 101. More specifically:
Step 1 analysis: Claim 16 is directed to a method which is a process that falls within one of the four statutory categories.
Step 2A prong 1 analysis: Claim 16 recites, in part:
“analyzing, by a processor of the computing device, the one or more phase images to determine values for one or more properties of the tissue surrounding the implant; and predicting, based at least in part on the analyzed one or more phase images, a temperature increase of the medical implant that will occur during a subsequent imaging scan of the patient”
The limitations as shown above, as drafted, are processes that, under the broadest reasonable interpretation, cover the performance of the limitations in the mind which fall within the “Mental Process” grouping of abstract ideas. The limitations of:
“analyze one or more phase images to determine values for one or more properties... and predict... a temperature increase of the medical implant that will occur during a subsequent imaging scan of the patient” recite steps that the human mind can perform through an observation and evaluation, such as the human mind can analyze a phase image and determine a particular property based on the observed image and infer/predict that such property will likely lead to a temperature increase, using, for example, a chart with specific characteristics determined based on the properties of the image. Accordingly, the claim recites an abstract idea.
Step 2A prong 2 analysis: this judicial exception is not integrated into a practical application. In particular, the claim recites the following element(s) –
“an imaging device”
“one or more phase images of the medical implant that is implanted within the patient, wherein the one or more phase images include tissue surrounding the medical implant, and wherein the one or more phase images result from the pre-scan of the patient”
“a processor of the computing device”
The steps of “one or more phase images of a medical implant” merely constitute pre-solution activities involving data gathering such as acquiring data, and thus are insignificant extra-solution activities. Similarly, limitations of “an imaging device” and “a processor of the computing device” are recited as being performed by generic computer components at a high level of generality and amount to no more than instructions to apply the exception using a generic computer.
In view of the foregoing, the additional elements do not integrate the abstract idea into a practical application.
Step 2B analysis: there are no additional elements that amount to significantly more than the judicial exception. Moreover, the additional element(s) as mentioned above do not amount to significantly more for the claim as a whole. Please see MPEP §2106.05. The claim is directed to an abstract idea.
Dependent claims 17-20 do not provide elements and/or limitations that overcome the deficiencies of the independent claim. Specifically:
Claim 17 recites limitations in the form of additional elements involving data gathering. Such limitations include “imaging pre-scan is conducted for 30 seconds or less” and “a first amount of power used for the pre-scan is less than a second amount of power used for the subsequent imaging scan” which recite insignificant extra-solution activity.
Claim 18 recites, in part, “receiving at least one of a desired power and a desired duration for the subsequent imaging scan, wherein the predicted temperature increase is based on one or more of the desired power and the desired duration”. As described above in claim 4, predicting based on a desired power in which will likely lead to a temperature increase, using, for example, a chart with specific characteristics determined recites a mental process of observation and evaluation. Similarly, the receiving is conducting a data gathering step and as such recite extra-solution activities.
Claim 19 does not provide elements and/or limitations that overcome the deficiencies of the independent claim. Specifically, the claim recites specific properties of the tissue in the form of additional elements involving data gathering and thus provide nothing more than insignificant extra-solution activities.
Claim 20 recites, in part, “comparing, by the processor, the predicted temperature increase of the medical implant to a temperature increase threshold; and issuing, by the processor, an alert in response to a determination that the predicted temperature increase exceeds the temperature increase threshold”. As mentioned above, the “processor” is recited at a high level of generality, i.e., as generic computer performing generic computer functions. Additionally, the comparison of a predicted temperature increase to a threshold and an alert in response to exceeding the temperature increase involve mental observations or evaluations, e.g., a radiologist may compare the estimation of future temperatures to a chart and determine when a prediction may exceed a safety measure to issue an alert.
Therefore, claims 1-20 are not 35 USC 101 eligible under 101 analysis.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-11, 13-14 and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Griffin et al. (CA 2805580 A1, English Translation hereafter referred to as “Griffin”) in view of Jiang et al. (WO 2018113518 A1, hereafter referred to as “Jiang”).
Regarding claim 1, Griffin teaches a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient (“Images reconstructed by the data processing server 414 are conveyed back to the operator workstation 402 where they are stored. Real-time images are stored in a data base memory cache” Griffin, [0058]; wherein the images are “MRI system is operated to acquire data from a volume-of-interest that contains at least a portion of a conductive structure using a pulse sequence that includes generating a radio frequency ("RF") field that induces a current in the conductive structure. An image that depicts the portion of the conductive structure is reconstructed from the acquired data, and a phase image is produced from the reconstructed image by extracting phase information from the reconstructed image” Griffin, [0012]), wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient (“An image that depicts the portion of the conductive structure is reconstructed from the acquired data, and a phase image is produced from the reconstructed image by extracting phase information from the reconstructed image” Griffin, [0012]; wherein the conductive structure is that of “artificial heart valves; and implantable medical devices, such as implantable cardiac devices” Griffin, [0020]; wherein the scanning is performed in a pre-scan manner, “allows for several different device configurations to be rapidly tested. The flexibility of the technique also confers the ability to quickly test device compatibility and predict a particular device's behavior under any desired MRI pulse sequence” Griffin, [0022]- [0023]);
a processor operatively coupled to the memory and configured to (Griffin, Fig. 4 processor 408):
predict (“capable of safely and quickly assessing the RF heating potential of a certain device, and predicting heating behavior under application of other sequences” Griffin, [0047]), based at least in part on the analyzed one or more phase images (“allows RF currents induced on conductive structures positioned within the bore of an MRI scanner to be quantified quickly by performing analysis on a single phase image” Griffin, [0048]), a temperature increase of the medical implant that will occur during a subsequent imaging scan of the patient (“predict the heating behavior of a certain configuration using safely acquired measurements. The ability of the method of the present invention to achieve this goal is illustrated in FIGS. 3A and 3B, which display measured temperature rise in different wires during the performance of an MRI pulse sequence... The theory used to predict heating given a RF current distribution, namely Maxwell's equations and Pennes' bioheat equation, is well established; thus, agreement between measured and predicted RF heating, as seen in FIGS. 3A and 3B, is sufficient to conclude that accurate current measurements can be obtained. It has thus been demonstrated through experiment that the method of the present invention is capable of safely and quickly assessing the RF heating potential of a certain device, and predicting heating behavior under application of other sequences” Griffin, [0046]-[0047]).
Griffin fails to explicitly teach analyze the one or more phase images to determine values for one or more properties of the tissue surrounding the implant.
However, Jiang teaches analyze the one or more phase images to determine values for one or more properties of the tissue surrounding the implant (“The tissue heating caused by the RF induced electric field can be characterized by the bioheat transfer formula... Where T is the tissue temperature, Q is the energy of RF induction deposition, S is the heat generated by metabolism, ρ is the density, C is the specific heat capacity, ω is the blood perfusion rate, and subscript b is the nature of the blood, such as T b is the local blood. temperature. The electric field induced by the RF magnetic field causes the tissue to heat up and change in accordance with the laws of biological heat transfer” Jiang, bottom of pg. 3; Eq (1)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Jiang of having analyze the one or more phase images to determine values for one or more properties of the tissue surrounding the implant.
Wherein having Griffin’s system of predicting heating in implants analyze the one or more phase images to determine values for one or more properties of the tissue surrounding the implant.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 2, Griffin in view of Jiang teach the system of claim 1, Griffin fails to explicitly teach wherein the imaging pre-scan is conducted for 30 seconds or less.
However, Jiang teaches wherein the imaging pre-scan is conducted for 30 seconds or less (“the time interval of the sequence 3 scan should be controlled within 3 minutes and the duration controlled within 30 seconds” Jiang, pg. 8 ¶3; “In general, when a patient carrying a deep brain electrical stimulator 10 scans in a 3T environment, Δt selects a value in the range of 10 seconds to 6 minutes because the temperature rise of the electrode contact 18 is fast, in order to improve the measurement result. Accuracy is typically measured at short intervals, for example 10 seconds” Jiang, pg. 8 ¶4).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Jiang of having wherein the imaging pre-scan is conducted for 30 seconds or less.
Wherein having Griffin’s system of predicting heating in implants wherein the imaging pre-scan is conducted for 30 seconds or less.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 3, Griffin in view of Jiang teach the system of claim 2, Griffin further teaches wherein a first amount of power used for the pre-scan is less than a second amount of power used for the subsequent imaging scan (“measurement can be obtained automatically using a single, relatively low-power image” Griffin, [0062]; wherein subsequent imaging scans may be performed, “several different device configurations to be rapidly tested. The flexibility of the technique also confers the ability to quickly test device compatibility and predict a particular device's behavior under any desired MRI pulse sequence... This assessment of RF heating could be interleaved with clinically relevant scans. For instance, RF heating could be periodically assessed in advance of each new imaging scan. In this way, RF heating of every imaging sequence can be safely evaluated.” Griffin, [0022]-[0023]).
Regarding claim 4, Griffin in view of Jiang teach the system of claim 1, Griffin further teaches wherein the processor predicts the temperature increase of the medical implant based at least in part on a desired power to be used during the subsequent imaging scan (“The flexibility of the technique also confers the ability to quickly test device compatibility and predict a particular device's behavior under any desired MRI pulse sequence” Griffin, [0022]; wherein the MRI pulse sequence includes a variety of desired power sequences; “The RF transmitter is responsive to the scan prescription and direction from the pulse sequence server 410 to produce RF pulses of the desired frequency, phase, and pulse amplitude waveform” Griffin, [0051]).
Regarding claim 5, Griffin in view of Jiang teach the system of claim 1, Griffin further teaches wherein the processor predicts the temperature increase of the medical implant based at least in part on a desired duration of the subsequent imaging scan (“The flexibility of the technique also confers the ability to quickly test device compatibility and predict a particular device's behavior under any desired MRI pulse sequence” Griffin, [0022]; wherein the MRI pulse sequence includes a variety of desired duration sequences, see Fig. 3A and 3B; “The RF transmitter is responsive to the scan prescription and direction from the pulse sequence server 410 to produce RF pulses of the desired frequency, phase, and pulse amplitude waveform” Griffin, [0051]).
Regarding claim 6, Griffin in view of Jiang teach the system of claim 1, Griffin further teaches wherein the processor analyzes the one or more phase images to determine a specific absorption rate (SAR) of the medical implant, and wherein the processor predicts the temperature increase based at least in part on the determined SAR (“To address the measurement duration and inapplicability in vivo, induced current can be measured, enabling a prediction of the specific absorption rate ("SAR") distribution near the conductor and subsequently the local heating behavior” Griffin, [0004]).
Regarding claim 7, Griffin in view of Jiang teach the system of claim 1, Griffin fails to explicitly teach wherein the one or more properties of the tissue include a thermal conductivity of the tissue.
However, Jiang teaches wherein the one or more properties of the tissue include a thermal conductivity of the tissue (“The tissue heating caused by the RF induced electric field can be characterized by the bioheat transfer formula” Jiang, bottom of pg. 3, Eq. (1) shows Penne’s bioheat equation with the term “k” which indicates thermal conductivity).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Jiang of having wherein the one or more properties of the tissue include a thermal conductivity of the tissue.
Wherein having Griffin’s system of predicting heating in implants wherein the one or more properties of the tissue include a thermal conductivity of the tissue.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 8, Griffin in view of Jiang teach the system of claim 1, Griffin fails to explicitly teach wherein the one or more properties of the tissue include a heat capacity of the tissue.
However, Jiang teaches wherein the one or more properties of the tissue include a heat capacity of the tissue (“The tissue heating caused by the RF induced electric field can be characterized by the bioheat transfer formula... Where T is the tissue temperature, Q is the energy of RF induction deposition, S is the heat generated by metabolism, ρ is the density, C is the specific heat capacity, ω is the blood perfusion rate, and subscript b is the nature of the blood, such as T b is the local blood. temperature. The electric field induced by the RF magnetic field causes the tissue to heat up and change in accordance with the laws of biological heat transfer” Jiang, bottom of pg. 3; Eq (1)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Jiang of having wherein the one or more properties of the tissue include a heat capacity of the tissue.
Wherein having Griffin’s system of predicting heating in implants wherein the one or more properties of the tissue include a heat capacity of the tissue.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 9, Griffin in view of Jiang teach the system of claim 1, Griffin fails to explicitly teach wherein the one or more properties of the tissue include a density of the tissue.
However, Jiang teaches wherein the one or more properties of the tissue include a density of the tissue (“The tissue heating caused by the RF induced electric field can be characterized by the bioheat transfer formula... Where T is the tissue temperature, Q is the energy of RF induction deposition, S is the heat generated by metabolism, ρ is the density, C is the specific heat capacity, ω is the blood perfusion rate, and subscript b is the nature of the blood, such as T b is the local blood. temperature. The electric field induced by the RF magnetic field causes the tissue to heat up and change in accordance with the laws of biological heat transfer” Jiang, bottom of pg. 3; Eq (1)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Jiang of having wherein the one or more properties of the tissue include a density of the tissue.
Wherein having Griffin’s system of predicting heating in implants wherein the one or more properties of the tissue include a density of the tissue.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 10, Griffin in view of Jiang teach the system of claim 1, Griffin fails to explicitly teach wherein the one or more properties of the tissue include an amount of metabolic heat generation of the tissue.
However, Jiang teaches wherein the one or more properties of the tissue include an amount of metabolic heat generation of the tissue (“The tissue heating caused by the RF induced electric field can be characterized by the bioheat transfer formula... Where T is the tissue temperature, Q is the energy of RF induction deposition, S is the heat generated by metabolism, ρ is the density, C is the specific heat capacity, ω is the blood perfusion rate, and subscript b is the nature of the blood, such as T b is the local blood. temperature. The electric field induced by the RF magnetic field causes the tissue to heat up and change in accordance with the laws of biological heat transfer” Jiang, bottom of pg. 3; Eq (1)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Jiang of having wherein the one or more properties of the tissue include an amount of metabolic heat generation of the tissue.
Wherein having Griffin’s system of predicting heating in implants wherein the one or more properties of the tissue include an amount of metabolic heat generation of the tissue.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 11, Griffin in view of Jiang teach the system of claim 1, Griffin fails to explicitly teach wherein the one or more properties of the tissue include an amount of perfusion through the tissue.
However, Jiang teaches wherein the one or more properties of the tissue include an amount of perfusion through the tissue (“The tissue heating caused by the RF induced electric field can be characterized by the bioheat transfer formula... Where T is the tissue temperature, Q is the energy of RF induction deposition, S is the heat generated by metabolism, ρ is the density, C is the specific heat capacity, ω is the blood perfusion rate, and subscript b is the nature of the blood, such as T b is the local blood. temperature. The electric field induced by the RF magnetic field causes the tissue to heat up and change in accordance with the laws of biological heat transfer” Jiang, bottom of pg. 3; Eq (1)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Jiang of having wherein the one or more properties of the tissue include an amount of perfusion through the tissue.
Wherein having Griffin’s system of predicting heating in implants wherein the one or more properties of the tissue include an amount of perfusion through the tissue.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 13, Griffin in view of Jiang teach the system of claim 1, Griffin further teaches further comprising an imaging device in communication with the processor, wherein the imaging pre-scan is performed using the imaging device, and wherein the one or more phase images are generated by the imaging device (“during prescans, magnetic resonance data is acquired” Griffin, [0056]; wherein the MR data is obtained using a magnetic resonance imaging (MRI) scanner, see Griffin abstract and Fig. 4 processor 408).
Regarding claim 14, Griffin in view of Jiang teach the system of claim 1, Griffin further teaches wherein the processor issues an alert in response to a determination that the predicted temperature increase exceeds (“This RF heating assessment could be carried out automatically, with a dedicated system including both hardware and software designed to automatically assess RF heating potential... this device could also be used to halt scanning when a dangerous situation arises, or at least to provide an alert to the clinician” Griffin, [0024]).
Griffin fails to explicitly teach compares the predicted temperature increase of the medical implant to a temperature increase threshold.
However, Jiang teaches compares the predicted temperature increase of the medical implant to a temperature increase threshold (“comparing the calculated heat accumulation amount with a preset threshold value, and comparing the highest temperature rise with the preset maximum temperature rise. Threshold, in between When any one exceeds the threshold, the data processing unit issues a danger warning to the MR control unit in time to automatically stop scanning of the MR scanning device” Jiang, bottom of pg. 6).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Jiang of having compares the predicted temperature increase of the medical implant to a temperature increase threshold.
Wherein having Griffin’s system of predicting heating in implants compares the predicted temperature increase of the medical implant to a temperature increase threshold.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 16, Griffin teaches a method of predicting heating in implants, the method comprising: performing, by an imaging device, an imaging pre-scan of a patient with a medical implant (“during prescans, magnetic resonance data is acquired” Griffin, [0056]; wherein the MR data is obtained using a magnetic resonance imaging (MRI) scanner, see Griffin abstract);
storing, in a memory of a computing device in communication with the imaging device, one or more phase images of the medical implant that is implanted within the patient (“Images reconstructed by the data processing server 414 are conveyed back to the operator workstation 402 where they are stored. Real-time images are stored in a data base memory cache” Griffin, [0058]; wherein the images are “MRI system is operated to acquire data from a volume-of-interest that contains at least a portion of a conductive structure using a pulse sequence that includes generating a radio frequency ("RF") field that induces a current in the conductive structure. An image that depicts the portion of the conductive structure is reconstructed from the acquired data, and a phase image is produced from the reconstructed image by extracting phase information from the reconstructed image” Griffin, [0012]), wherein the one or more phase images include tissue surrounding the medical implant, and wherein the one or more phase images result from the pre-scan of the patient (“An image that depicts the portion of the conductive structure is reconstructed from the acquired data, and a phase image is produced from the reconstructed image by extracting phase information from the reconstructed image” Griffin, [0012]; wherein the conductive structure is that of “artificial heart valves; and implantable medical devices, such as implantable cardiac devices” Griffin, [0020]; wherein the scanning is performed in a pre-scan manner, “allows for several different device configurations to be rapidly tested. The flexibility of the technique also confers the ability to quickly test device compatibility and predict a particular device's behavior under any desired MRI pulse sequence” Griffin, [0022]- [0023]); and
predicting (“capable of safely and quickly assessing the RF heating potential of a certain device, and predicting heating behavior under application of other sequences” Griffin, [0047]), based at least in part on the analyzed one or more phase images (“allows RF currents induced on conductive structures positioned within the bore of an MRI scanner to be quantified quickly by performing analysis on a single phase image” Griffin, [0048]), a temperature increase of the medical implant that will occur during a subsequent imaging scan of the patient (“predict the heating behavior of a certain configuration using safely acquired measurements. The ability of the method of the present invention to achieve this goal is illustrated in FIGS. 3A and 3B, which display measured temperature rise in different wires during the performance of an MRI pulse sequence... The theory used to predict heating given a RF current distribution, namely Maxwell's equations and Pennes' bioheat equation, is well established; thus, agreement between measured and predicted RF heating, as seen in FIGS. 3A and 3B, is sufficient to conclude that accurate current measurements can be obtained. It has thus been demonstrated through experiment that the method of the present invention is capable of safely and quickly assessing the RF heating potential of a certain device, and predicting heating behavior under application of other sequences” Griffin, [0046]-[0047]).
Griffin fails to explicitly teach analyzing the one or more phase images to determine values for one or more properties of the tissue surrounding the implant.
However, Jiang teaches analyzing the one or more phase images to determine values for one or more properties of the tissue surrounding the implant (“The tissue heating caused by the RF induced electric field can be characterized by the bioheat transfer formula... Where T is the tissue temperature, Q is the energy of RF induction deposition, S is the heat generated by metabolism, ρ is the density, C is the specific heat capacity, ω is the blood perfusion rate, and subscript b is the nature of the blood, such as T b is the local blood. temperature. The electric field induced by the RF magnetic field causes the tissue to heat up and change in accordance with the laws of biological heat transfer” Jiang, bottom of pg. 3; Eq (1)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a method of predicting heating in implants, the method comprising: performing, by an imaging device, an imaging pre-scan of a patient with a medical implant; storing, in a memory of a computing device in communication with the imaging device, one or more phase images of the medical implant that is implanted within the patient, wherein the one or more phase images include tissue surrounding the medical implant, and wherein the one or more phase images result from the pre-scan of the patient, with the teachings of Jiang of having analyzing the one or more phase images to determine values for one or more properties of the tissue surrounding the implant.
Wherein having Griffin’s system of predicting heating in implants analyzing the one or more phase images to determine values for one or more properties of the tissue surrounding the implant.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 17, Griffin in view of Jiang teach the method of claim 16, Griffin further teaches wherein the pre-scan is conducted using a first amount of power, wherein the first amount of power is lower than a second amount of power used to conduct the subsequent imaging scan (“measurement can be obtained automatically using a single, relatively low-power image” Griffin, [0062]; wherein subsequent imaging scans may be performed, “several different device configurations to be rapidly tested. The flexibility of the technique also confers the ability to quickly test device compatibility and predict a particular device's behavior under any desired MRI pulse sequence... This assessment of RF heating could be interleaved with clinically relevant scans.For instance, RF heating could be periodically assessed in advance of each new imaging scan. In this way, RF heating of every imaging sequence can be safely evaluated.” Griffin, [0022]-[0023]).
Griffin fails to explicitly teach wherein the pre-scan is conducted for 30 seconds or less.
However, Jiang teaches wherein the pre-scan is conducted for 30 seconds or less (“the time interval of the sequence 3 scan should be controlled within 3 minutes and the duration controlled within 30 seconds” Jiang, pg. 8 ¶3; “In general, when a patient carrying a deep brain electrical stimulator 10 scans in a 3T environment, Δt selects a value in the range of 10 seconds to 6 minutes because the temperature rise of the electrode contact 18 is fast, in order to improve the measurement result. Accuracy is typically measured at short intervals, for example 10 seconds” Jiang, pg. 8 ¶4).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a method of predicting heating in implants, the method comprising: performing, by an imaging device, an imaging pre-scan of a patient with a medical implant; storing, in a memory of a computing device in communication with the imaging device, one or more phase images of the medical implant that is implanted within the patient, wherein the one or more phase images include tissue surrounding the medical implant, and wherein the one or more phase images result from the pre-scan of the patient, with the teachings of Jiang of having wherein the pre-scan is conducted for 30 seconds or less.
Wherein having Griffin’s system of predicting heating in implants wherein the pre-scan is conducted for 30 seconds or less.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 18, Griffin in view of Jiang teach the method of claim 16, Griffin further teaches further comprising receiving at least one of a desired power and a desired duration for the subsequent imaging scan, wherein the predicted temperature increase is based on one or more of the desired power and the desired duration (“The flexibility of the technique also confers the ability to quickly test device compatibility and predict a particular device's behavior under any desired MRI pulse sequence” Griffin, [0022]; wherein the MRI pulse sequence includes a variety of desired power and duration sequences; “The RF transmitter is responsive to the scan prescription and direction from the pulse sequence server 410 to produce RF pulses of the desired frequency, phase, and pulse amplitude waveform” Griffin, [0051]).
Regarding claim 19, Griffin in view of Jiang teach the method of claim 16, Griffin fails to explicitly teach wherein the one or more properties of the tissue include a thermal conductivity of the tissue.
However, Jiang teaches wherein the one or more properties of the tissue include a thermal conductivity of the tissue (“The tissue heating caused by the RF induced electric field can be characterized by the bioheat transfer formula” Jiang, bottom of pg. 3, Eq. (1) shows Penne’s bioheat equation with the term “k” which indicates thermal conductivity).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a method of predicting heating in implants, the method comprising: performing, by an imaging device, an imaging pre-scan of a patient with a medical implant; storing, in a memory of a computing device in communication with the imaging device, one or more phase images of the medical implant that is implanted within the patient, wherein the one or more phase images include tissue surrounding the medical implant, and wherein the one or more phase images result from the pre-scan of the patient, with the teachings of Jiang of having wherein the one or more properties of the tissue include a thermal conductivity of the tissue.
Wherein having Griffin’s system of predicting heating in implants wherein the one or more properties of the tissue include a thermal conductivity of the tissue.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Regarding claim 20, Griffin in view of Jiang teach the method of claim 16, Griffin further teaches further comprising: by the processor, the predicted temperature and issuing, by the processor, an alert in response to a determination that the predicted temperature increase exceeds (“This RF heating assessment could be carried out automatically, with a dedicated system including both hardware and software designed to automatically assess RF heating potential... this device could also be used to halt scanning when a dangerous situation arises, or at least to provide an alert to the clinician” Griffin, [0024]).
Griffin fails to explicitly teach comparing the predicted temperature increase of the medical implant to a temperature increase threshold.
However, Jiang teaches comparing the predicted temperature increase of the medical implant to a temperature increase threshold (“comparing the calculated heat accumulation amount with a preset threshold value, and comparing the highest temperature rise with the preset maximum temperature rise. Threshold, in between When any one exceeds the threshold, the data processing unit issues a danger warning to the MR control unit in time to automatically stop scanning of the MR scanning device” Jiang, bottom of pg. 6).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin of having a method of predicting heating in implants, the method comprising: performing, by an imaging device, an imaging pre-scan of a patient with a medical implant; storing, in a memory of a computing device in communication with the imaging device, one or more phase images of the medical implant that is implanted within the patient, wherein the one or more phase images include tissue surrounding the medical implant, and wherein the one or more phase images result from the pre-scan of the patient, with the teachings of Jiang of having comparing the predicted temperature increase of the medical implant to a temperature increase threshold.
Wherein having Griffin’s system of predicting heating in implants comparing the predicted temperature increase of the medical implant to a temperature increase threshold.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Jiang relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses image analysis, while Jiang is for monitoring of tissue temperature around an active implant under MR based on MR measurements with high resolution to soft tissue. Please see Griffin et al. paragraph [0004] and Jiang et al. top of pg. 3.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Griffin et al. in view of Jiang et al. and in further view of Guidon et al. (US 20220026516 A1, hereinafter referred to as “Guidon”).
Regarding claim 12, Griffin in view of Jiang teach the system of claim 1, Griffin in view of Jiang fail to explicitly teach wherein the processor utilizes a neural network to analyze the one or more phase images, and wherein the neural network includes a first hidden layer and a hidden second layer, wherein the first hidden layer includes 11 hidden neurons and the second hidden layer includes 9 hidden neurons.
However, Guidon teaches wherein the processor utilizes a neural network to analyze the one or more phase images (“a neural network model for analyzing MR images” Guidon, abstract), and wherein the neural network includes a first hidden layer and a hidden second layer, wherein the first hidden layer includes 11 hidden neurons and the second hidden layer includes 9 hidden neurons (“The exemplary neural network model 204 includes layers of neurons 502, 504-1 to 504-n, and 506, including an input layer 502, one or more hidden layers 504-1 through 504-n, and an output layer 506. Each layer may include any number of neurons” Guidon, [0074]; “each neuron in hidden layer(s) 504-1 through 504-n processes one or more inputs from the input layer 502, and/or one or more outputs from neurons in one of the previous hidden layers” Guidon, [0076]. Therefore, it would have been obvious to one of ordinary sill in the art before the effective filing date of the claimed invention was made to have wherein the first hidden layer includes 11 hidden neurons and the second hidden layer includes 9 hidden neurons, since Guidon discloses a neural network model for analyzing phase images with one or more hidden layers and each layer may include any number of neurons wherein is just a designer’s choice of having a different number of neurons. Thus, efficiently enhancing the value of each pixel which includes a magnitude and a phase in MRI data)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin in view of Jiang of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Guidon of having wherein the processor utilizes a neural network to analyze the one or more phase images, and wherein the neural network includes a first hidden layer and a hidden second layer, wherein the first hidden layer includes 11 hidden neurons and the second hidden layer includes 9 hidden neurons.
Wherein having Griffin’s system of predicting heating in implants wherein the processor utilizes a neural network to analyze the one or more phase images, and wherein the neural network includes a first hidden layer and a hidden second layer, wherein the first hidden layer includes 11 hidden neurons and the second hidden layer includes 9 hidden neurons.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Guidon relate to obtaining data from MRI phase images. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses phase image analysis, while Guidon is for efficiently enhancing the value of each pixel which includes a magnitude and a phase in MRI data in applications for estimating parameters that cannot be used with only the magnitude. Please see Griffin et al. paragraph [0004] and Guidon et al. paragraph [0003].
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Griffin et al. in view of Jiang et al. and in further view of Winter et al. (“MRI‐related heating of implants and devices: a review”, 2021 herein after referred to as “Winter”).
Regarding claim 15, Griffin in view of Jiang teach the system of claim 1, Griffin further teaches wherein the processor is configured to determine, based on the analysis of the one or more phase images and a desired duration of the subsequent imaging scan (“The flexibility of the technique also confers the ability to quickly test device compatibility and predict a particular device's behavior under any desired MRI pulse sequence” Griffin, [0022]; wherein the MRI pulse sequence includes a variety of desired duration sequences, see Fig. 3A and 3B; “The RF transmitter is responsive to the scan prescription and direction from the pulse sequence server 410 to produce RF pulses of the desired frequency, phase, and pulse amplitude waveform” Griffin, [0051]).
Griffin in view of Jiang fail to explicitly teach a maximum power that can be used during the subsequent imaging scan such that the temperature increase does not exceed a temperature increase threshold.
However, Winter teaches a maximum power that can be used during the subsequent imaging scan such that the temperature increase does not exceed a temperature increase threshold (Winter pg. 1660 Figure 13 discloses a diagram with different orientations, length and power (i.e., W/kg) of RF-induced heating of a coronary stent in which “estimate[s] the maximum induced stent SAR values for a given background local SAR in a human body model” for a given power, shown as red in the diagram, i.e., indicating a temperature threshold, for “a risk assessment of implant types
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Griffin in view of Jiang of having a system to predict heating in implants, the system comprising: a memory configured to store one or more phase images of a medical implant that is implanted within a patient, wherein the one or more phase images include the medical implant and tissue surrounding the medical implant, and wherein the one or more phase images are based on an imaging pre-scan of the patient, with the teachings of Winter of having a maximum power that can be used during the subsequent imaging scan such that the temperature increase does not exceed a temperature increase threshold.
Wherein having Griffin’s system of predicting heating in implants a maximum power that can be used during the subsequent imaging scan such that the temperature increase does not exceed a temperature increase threshold.
The motivation behind the modification would have been to obtain a system of predicting heating in implants that enhances the safety of electrically conductive devices undergoing magnetic resonance imaging (MRI) of implants in a human body, since Griffin and Guidon relate to measuring MRI induced radio frequency currents of an implant. Wherein Griffin measures the induced current to enable a prediction of specific absorption rate (“SAR”) distribution near the conductor (e.g., implant) and subsequently the local heating behavior using remote sensing which uses phase image analysis, while Winter is a simulation-based parametrization approach for short implants that give a fast estimation of RF-induced heating and would enable a more generalized risk assessment of implant types. Please see Griffin et al. paragraph [0004] and Winter et al. pg. 1660 Fig. 13 description.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Drown et al. (US 20200273175 A1) – acquires MRI image data including magnitude and phase to be used for various purposes including medical implant and tissue surrounding the implant temperature.
Golestani-Rad et al. (US 20230137794 A1) – predict heating in implants and determine an implant trajectory based on a specific absorption rate of radiofrequency energy associated with the implant using the implant trajectory and the tangential component of the electric field.
Johnson et al. (US 20100168821 A1) – an energy management system that facilitates the transfer of high frequency energy induced on an implant lead including an energy dissipating surface associated with the implant lead.
Vu et al. (“Machine learning-based prediction of MRI-induced power absorption in the tissue in patients with simplified deep brain stimulation lead models”, 2021) – a machine learning model that can predict the local specific absorption rate (SAR) in the tissue around tips of implanted leads from the distribution of the tangential component of the MRI incident electric field.
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/EMMANUEL SILVA-AVINA/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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