WO2018154138A1

WO2018154138A1 - Sequences for wireless charging of batteries in coils and implants

Info

Publication number: WO2018154138A1
Application number: PCT/EP2018/054801
Authority: WO
Inventors: Aasrith GANTI; Timothy ORTIZ; George Randall DUENSING; Gregory Thomas DOWLING
Original assignee: Koninklijke Philips N.V.
Priority date: 2017-02-27
Filing date: 2018-02-27
Publication date: 2018-08-30

Abstract

Systems and methods are disclosed that facilitate providing magnetic resonance (MR) charging pulse sequences for charging batteries or supercapacitors present in wireless MR surface coils or patient implants. The charging pulse sequences deliver signal to the power management circuit in the implant or coil, and the power management circuit converts the signal to energy used to power the device or for storage for later use.

Description

SEQUENCES FOR WIRELESS CHARGING OF BATTERIES ΓΝ COILS AND IMPLANTS

FIELD

[0001] The present invention finds application in wireless battery charging systems and methods for batteries in medical coils and implants. However, it will be appreciated that the described techniques may also find application in other wireless charging systems, other battery charging techniques, and the like.

BACKGROUND

[0002] Wireless medical devices an important technology in the medical market. However, with the capabilities of wireless medical devices comes the need to charge the batteries located inside the medical device or implant in a patient. By 2020 it is estimated that there will be over 21 million implants in the United States. Currently these implants are powered using heavy batteries or capacitors that are many times larger than the implant. The limitation on the battery size is set by the need to energize the implant for up to 10 years. Patients need to undergo multiple operations over their lifetime to replenish their batteries. Higher charge capacity increases risk of impact due to a battery malfunction.

[0003] In conventional implants, the battery is the largest part of the device. In such devices, conventional batteries need to be able to operate for extended periods of time and need to be implanted in anatomical locations that permit the implants to be accessible for multiple replacements. Due to these constraints, long cables are implanted in the patient and run inside the patient's body, which prevents the patient undergoing an MR scan.

[0004] In implants like Deep Brain Stimulation (DBS) and cardiac defibrillators, the implant and battery are far away from one another because of the size of the battery and the need for easy access during replacement. The cables connecting the battery to the implant are long and prevent users from getting advanced imaging care like MRI scans.

[0005] Conventionally, if a patient is administered an implant in his late fifties, for instance, said patient typically would have to undergo at least eight surgeries and spend tens of thousands for maintaining the batteries in his implant. As with DBS implants, patients with cardiac defibrillators cannot undergo MRI scans due to the long current-carrying cables that are present in conventional implants to carry the charge from the battery to the electrode.

[0006] The present application provides new and improved systems and methods that facilitate providing specialized MR sequences for charging and maintaining energy storage devices within MR compatible products such as surface coils or patient implantable products, thereby overcoming the above-referenced problems and others.

BRIEF SUMMARY

[0007] In accordance with one aspect, a system that facilitates wirelessly charging a rechargeable medical device using magnetic resonance (MR) charging pulse sequences, comprises a processor configured to perform a handshake protocol with one or more power management circuits in respective one or more rechargeable medical devices, determine an amount of charge required to recharge the one or more rechargeable medical devices to a predetermined level of charge, and generate at least one MR charging pulse sequence. The system further comprises a transceiver configured to transmit at least one MR charging pulse sequence to an MR device for execution in order to recharge the one or more rechargeable medical devices.

[0008] In accordance with another aspect, method of wirelessly charging a rechargeable medical device using magnetic resonance (MR) charging pulse sequences, comprises performing a handshake protocol with one or more power management circuits in respective one or more rechargeable medical devices, determining an amount of charge required to recharge the one or more rechargeable medical devices to a predetermined level of charge, and generating at least one MR charging pulse sequence. The method further comprises transmitting the at least one MR charging pulse sequence to an MR device for execution in order to recharge the one or more rechargeable medical devices.

[0009] In accordance with another aspect, a wireless and wirelessly-rechargeable medical implant device comprises at least one rechargeable element, and a power management circuit that further comprises: a charge sensor configured to monitor a state of charge of the at least one rechargeable element; a digital processor configured to generate health data describing the state of charge of the at least one rechargeable element; and a transceiver configured to transmit the health data to a base station for generating magnetic resonance (MR) charging pulse sequences. [0010] One advantage is that patient time spent in the operating room is reduced.

[0011] Another advantage is rechargeable medical devices can be recharged during an MR imaging scan.

[0012] Another advantage is that, by including energy efficient transfer MR sequences before, between or after the imaging sequences, battery replacement cycle and size is reduced.

[0013] Still further advantages of the subject innovation will be appreciated by those of ordinary skill in the art upon reading and understand the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings are only for purposes of illustrating various aspects and are not to be construed as limiting.

[0015] FIGURE 1 illustrates a system 10 that facilitates providing wireless charging of medical devices, in accordance with one or more features described herein.

[0016] FIGURE 2 illustrates a method for wirelessly charging an MR surface coil battery using charging pulse sequences, in accordance with various aspects described herein.

[0017] FIGURE 3 illustrates a method for wirelessly charging a medical implant device before and during implantation in a patient, in accordance with one or more aspects described herein.

[0018] FIGURES 4 and 5 collectively illustrate a method for wirelessly charging a medical implant device after implantation in a patient, in accordance with one or more aspects described herein.

DETAILED DESCRIPTION

[0019] The foregoing problems in the conventional art are overcome by the herein described systems and methods, which facilitate providing efficient energy transfer pulse sequences for wirelessly charging rechargeable medical devices (e.g., wireless surface coil loop elements, rechargeable medical implant devices, etc.) as described herein. The described charging pulse sequences effectively reduce the size of implants that need to be placed inside the human body and reduce or eliminate the need for repeating surgical procedures. The described MR pulse sequences facilitate a new way of working in the field of medicine.

[0020] In one embodiment, an MR imaging sequence is modified to produce an MR charging pulse sequence having optimal energy transfer characteristics for charging rechargeable elements of a medical device using an MR imaging device. For instance, MR imaging sequences can be reprogrammed to charge a rechargeable medical device during an MR scan or the like, without increasing specific absorption rate (SAR) specifications for the MR device. In one embodiment, the flip angle of an MR imaging sequence is reduced when modifying the sequence to produce the charging pulse sequence.

[0021] FIGURE 1 illustrates a system 10 that facilitates providing wireless charging of medical devices, in accordance with one or more features described herein. The following examples relate to charging magnetic resonance (MR) surface coils, implant devices, and the like (collectively referred to herein as "rechargeable medical devices"). However, it will be appreciated by those of skill in the art that any rechargeable devices can be charged using the herein-described systems and methods.

[0022] The system 10 comprises an MR imaging device 12 comprising one or more MR surface coils 14. Each loop element 16 of the surface coil comprises a wireless transceiver 18 and a power management circuit or ship (PMC) 20 that communicates with a base station 22. The PMC 20 comprises hardware such as a charge sensor for monitoring or sensing a state of charge (i.e., a percentage of full charge or the like) in chargeable devices (batteries, supercapacitors, etc., collectively referred to herein as "rechargeable elements") monitored by the PMC, a digital processor for processing information, and a transceiver for communicating with the base station. During the pre- or post-scan stage of an MR scan, when e.g. the patient is being setup or during the downtime of the system, the power management circuit 20 shares the information of the charge present in each of the batteries 24 or supercapacitors 26 in the surface coil 14.

[0023] As used herein, "state of charge" refers to any measurable condition of the charging element in a standalone mode or integrated mode. For example the battery impedance should change over a given charge % for a healthy battery. That is, the impedance of the battery changes over time based on the amount of charge stored by the battery. When impedance is low, then the rate at which the batteries charge will be much higher than when the battery is full. Additionally, impedance changes over the lifetime of the battery. A new battery may be capable of holding full capacity, but as time goes on, it will only be able to hold 90-95% of its charge, which can also be detected as a parameter from by the herein-described processing unit.

[0024] In high field MRI system, a wave behavior phenomenon occurs that causes constructive and destructive interference patterns, which in turn cause localized heat patterns that have potential to cause tissue damage. The interference also causes an inhomogeneous RF field that, although not ideal for normal imaging, can be used for charging implant batteries or surface coils. According to one embodiment, the herein-described MR transmit sequences can be programmed such that the constructive interference patterns deliver energy that can be used to charge batteries in implants or surface coils.

[0025] In one embodiment, the PMC also relays geographic location information to provide its location for charging. In another embodiment, an initial gradient is applied at the beginning of an MR scan to determine coil locations for charging parameters. Additionally or alternatively, coil locations can be landmarked prior to feeding a patient into the bore of the MR imaging device.

[0026] The system 10 also comprises a processor 28 that executes, and a memory 30 that stores, computer-executable instructions or "modules" for performing the various functions, acts, methods, etc. described herein. The memory 30 may be a computer-readable medium on which a control program is stored, such as a disk, hard drive, or the like. Common forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tape, or any other magnetic storage medium, CD-ROM, DVD, or any other optical medium, RAM, ROM, PROM, EPROM, FLASH-EPROM, flash memory, variants thereof, other memory chip or cartridge, or any other tangible medium from which the processor 28 can read and execute. In this context, the described systems may be implemented on or as one or more general purpose computers, special purpose computer(s), a programmed microprocessor or microcontroller and peripheral integrated circuit elements, an ASIC or other integrated circuit, a digital signal processor, a hardwired electronic or logic circuit such as a discrete element circuit, a programmable logic device such as a PLD, PLA, FPGA, Graphics processing unit (GPU), or PAL, or the like.

[0027] According to an embodiment, based on the charge information obtained from the PMC 20, the processor 28 determines an amplitude, duty cycle, plane of orientation, and/or flip angle for a charging pulse sequence 32 that is transmitted via a transceiver 33 to the MR device 12, where it is executed to charge the batteries 24 and/or supercapacitors 26 of the surface coil. The processor 28 generates and transmits the charging pulse sequence 32 to charge the surface coil battery or supercapacitor. In one embodiment, all surface coils connected to the MR imaging system are periodically or continuously evaluated, and a surface coil having the lowest charge relative to other surface coils is wirelessly recharged using the described pulse sequence technique. The charging procedure is then reiterated until all surface coils have a desired or predetermined level of charge (e.g., 90%, 95%, or so other predetermined desired level of charge). The pulse sequence charging process is monitored by the processor and repeated as necessary based on the type of surface coil being used. Such "self-charge" scans are of low specific absorption rate (SAR) and need not be gradient-intensive, for the protection of the implant and patient. In one example, SAR is set based on the patient weight and the anatomy of interest. The IEC and FCC have regulations for SAR, and a "low" SAR scan as discussed herein means that a selected SAR lies e.g. below 50% of regulation limits. Similarly, medium SAR typically means 50 to 80% of the limit, and SAR over e.g., 80% of the limit is considered high.

[0028] During the charging pulse sequence, information describing the number of charges performed, the rate of charge and the total time taken to charge each of the storage devices (batteries, supercapacitors, etc.) is recorded. If a storage device is near end-of-life or if the recorded information indicates a situation where the battery is taking too long to charge, the serial number of the surface coil is transmitted to a local Field Service Engineer (FSE) for a proactive battery exchange in order to reduce the downtime experienced by the customer. Based on the type of energy harvesting technique applied, the health of the loop elements can be studied based on the charge information obtained from the power management circuit 20.

[0029] According to an embodiment, the charging pulse sequences comprise three phases: a handshaking phase; a load determining phase; and an energy transfer phase. Accordingly, the memory has stored thereon a handshaking module 34 that, when executed by the processor, establishes communication with loop elements 16 in the MR coils 14. A load determination module 36 is executed by the processor to identify coils having batteries 24 that need charging. Once the load is determined (i.e., the amount of charge needed to charge the identified batteries), the processor generates one or more charge pulse sequences 32 and executes an energy transfer module 38 to deliver the charge pulse sequences to the identified batteries via the MR device 12. The charge pulse sequence(s) 32 is optimized to deliver the power required to charge the battery or device (load). In one embodiment, the pulse sequence is determined by a machine learning algorithm 40 that also monitors the health of the charged device (batteries, supercapacitors, etc.) in the MR coil and the health of each of the elements. MR rechargeable element health data 42 is stored in the memory 30 and can be fed back to "Big-data" centers for analysis and preventative maintenance of the coils.

[0030] The system 10 also facilitates charging batteries and/or supercapacitors (collectively referred to herein as "rechargeable elements") in a medical device 44, also referred to herein as an "implant" 44, which is implanted in a patient, or which is wirelessly charged using the described charging pulse sequences just prior to implantation in the patient or after implantation. The described MR sequences can be employed to charge medical implant device batteries 46 wirelessly, which facilitates reducing implant battery size so that the implant battery is located proximately or integrally to the implant. The implant device 40 includes one or more batteries 46 and a PMC 47 that operates in a fashion similar or identical to the PMC 20 described above. This, in turn, mitigates or eliminates a need for metallic wiring between the battery and implant device, which means that patients in whom such implant devices are implanted can undergo MR scans without the detrimental effects associated with the extensive wiring required by conventional implant batteries.

[0031] In one embodiment, the phases for charging implant batteries also comprise: a handshaking phase; a load determining phase; and an energy transfer phase. Accordingly, the processor executes the handshaking module 34, load determination module 36, and energy transfer module 38 in a manner similar to that described above for charging MR coils in order to establish communication with the medical device, determine an amount of charge required by the battery 46, and deliver a charging pulse sequence 32 to charge the battery 46. After the hand-shaking phase, the system acquires information on the implant's health and battery strength. Medical device health data 48 is stored to the memory 30 and can be transmitted to a remote data center for engineering analysis to facilitate making a decision on proactive device maintenance or replacement. With this information, the MR system's machine learning algorithm 40 creates a charging pulse sequence 32 to supply the amount of energy to charge the battery 46. Implantable products will enable a new workflow in MR imaging.

[0032] According to an example, if a rechargeable element has a low charge as determined by the processor from the data received from the PMC, then a charging pulse sequence is executed prior to a subsequent imaging sequence. In this manner, the charging pulse sequence 32 is interleaved into an imaging sequence during an MR imaging scan. Charging of the rechargeable elements described herein may be performed using a quick charge, a trickle charge, or any other suitable charging approach.

[0033] In another embodiment, energy efficient transfer sequences with defined Magnetic Resonance Fingerprinting (MRF) are employed to support simultaneous charging and material detection using multiple parameters that include, without being limited to: flip angle, echo time, pulse phase, repetition time, etc. Predefined pattern recognition provides a feedback method to determine the amount charge or device activation of the implant.

[0034] In one example, the medical device 44 is a Deep Brain Stimulation (DBS) implant for patients with Parkinson's disease. DBS implants have enabled symptom improvements in patients suffering from Parkinson's. However, the procedure to place an implant is both expensive and tedious. MR scans are used to determine the precise position and implants are placed based off of the MR scan data. Conventionally, once the electrodes are placed, wires are run near the collar bone of the patient to connect the electrode to the battery. This long cable prevents the user from having MR scans as these wires could cause heating issues. Functional MRI (fMRI) scans, which can be very beneficial to the patient, also cannot be performed because of the large wires of the conventional implant.

[0035] The herein-described wirelessly charged implants are smaller in size relative to that of conventional implants due reduction of the implant battery size. This feature enables a doctor to place the implant directly near the targeted area without the need for long wires or multiple surgeries to replace the batteries in the implants. Since the implants are smaller and without cables, the patient has access to MR imaging. Based on the program administered, an MR pulsing sequence can be used to charge the implant battery 46 and measure the health thereof.

[0036] In another example, the medical device 44 is a cardiac defibrillator. Cardiac defibrillator implants represent one of the most commonly implanted devices. By using the herein- described wirelessly-capable implant charging techniques, a need for long conventional wires is mitigated, and thereby patients can be administered better care using MRI. The MR charging pulse sequence 32 charges the battery 46 inside the implant 44 and facilitates evaluation of the health of the implant 44 during each visit. Using MR techniques, the abnormalities or asynchronous behavior of the heart can be visually seen while the implant is operating. A need for surgery to place implants is mitigated as MR guided implant placement techniques can be used to place these implants in the right place in real time due to the herein-described wireless charging techniques.

[0037] In another example, the medical device 44 is a powered targeted drug delivery device implant. Using the described technique, targeted drug delivery can be improved. Conventionally, the amount of drug delivered to the target area is restricted by the size of the battery 46 of the implant. However, using the herein-described MR pulse sequencing to charge an implant battery, the implant battery size can be minimized and localized to the implant thereby mitigating a need for large wires and increasing the amount of drug delivered between implant/battery servicing. That is, once the drug implant device is placed inside the patient using MR guided surgery, it is charged using MR pulse sequences. This energy is then stored for use by the implant to deliver a required dose of drug to the target area. In a related embodiment, using MR fingerprinting, which uses a pseudo-randomized acquisition so that different tissues have a unique signal fingerprint, tissue damage around a region where a drug is administered can be obtained and used in estimating a subsequent dosage.

[0038] In all of the above-mentioned implant examples, a common feature involves reducing battery size using wirelessly chargeable batteries. Using MR and self-learning MR sequencing (e.g., the machine learning algorithm 40), power can be transferred to the battery using either the system 10 itself or a transmit coil 50. Once the device 44 is placed, a physician or the like can administer a drug or change the pulse sequence of the defibrillator or DBS device, not only based on a patient's feedback but also by directly looking at results from fMRI scans of, for instance, the brain and/or high SNR images for other parts of the body. Using the described systems and methods, the system 10 can be programmed to charge a coil or implant battery up to a predetermined level of charge, as well as control how care is being administered.

[0039] FIGURES 2-5 illustrate flowcharts representing wireless charging methods such as can be performed using the system of Figure 1. FIGURE 2 illustrates a method for wirelessly charging an MR surface coil battery using charging pulse sequences, in accordance with various aspects described herein. At 100, the charging procedure or sequence begins. At 102, communication is established with each loop element in each surface coil in the MR system. Communication may be wired or wireless. At 104, data is received from a power management circuit (PMC) coupled to each loop element. At 106, a determination is made based on the received data regarding whether one or more batteries or supercapacitors in each loop element require charging. If not, then at 108, health information is gathered regarding the number of charges received by, overall health of, and discharge history of, each supercapacitor and/or battery. In another embodiment, the health information includes temperature information (historical and/or current) of the monitored rechargeable element. The information collected at 108 is stored to memory and sent to one or more remote "big data" servers for engineering analysis at 110, e.g., to facilitate proactive action regarding battery or supercapacitor maintenance or replacement. At 112, the MR imaging sequence commences.

[0040] If the determination at 106 indicates that one or more batteries or supercapacitors requires charging, then a machine learning algorithm is employed to charge the identified battery or supercapacitor. At 114, a number of channels or elements that require charging is determined. At 116, charging pulse sequence parameters are set and the identified elements are charged wirelessly. The pulse sequence parameters may include, for example, gradient, amplitude, duty cycle, and/or flip angle of the charging pulse sequence. At 118, information is gathered regarding the number of charges received by, overall health of, and discharge history of, each supercapacitor and/or battery. The information collected at 118 is stored to memory and sent to one or more remote "big data" servers for engineering analysis at 120, e.g., to facilitate proactive action regarding battery or supercapacitor maintenance or replacement. At 122, the MR imaging sequence commences.

[0041] According to one example in which a high power signal is employed, the pulse sequence parameters include an amplitude of approximately 900 Hz, duty cycle of approximately 5% with peak power at approximately 30kW. This type of high power can be set by setting a 90 degree flip angle in the pulse sequence. The 90 degree flip angle tips the hydrogen atoms to their highest excitation, which means maximum power is delivered from the amplifiers. In another example in which a low power signal is employed, a lower duty cycle and lower switching frequency are used, thereby delivering only milliwatts to the implants. It will be understood that the foregoing values are provided by way of example only and are not to be construed in a limiting sense.

[0042] FIGURE 3 illustrates a method for wirelessly charging a medical implant device before and during implantation in a patient, in accordance with one or more aspects described herein. At 150, an MR diagnosis is performed and/or analyzed. A determination is made at 152 regarding whether an implant devices is to be implanted in the patient. If not, then the method proceeds to 162, where the procedure is terminated. If an implant is needed by the patient, then at 154, and MR-guided implant device is selected for implanting in the patient. At 156, the implant device battery is wirelessly charged using low power sequences of a few milliwatts of power. At 158, the implant device is implanted in the patient and checked using MR. At 160, the implant is charged to a predetermined level of charge. In one embodiment, the implant device battery is charged to a level that ensures that the implant device has enough charge to last at least until a next scheduled checkup or appointment. At 160, the charging procedure terminates.

[0043] FIGURES 4 and 5 collectively illustrate a method for wirelessly charging a medical implant device after implantation in a patient, in accordance with one or more aspects described herein. In the example of Figures 4 and 5, the implant device is a drug delivery device. However, it will be understood that the same technique is applicable to wirelessly recharge any battery-powered implant device. At 200, the post-implant placement sequence begins. At 202, MRI and/or fMRI scans are performed on the patient or an anatomical portion thereof. At 204, a determination is made regarding whether the problem or condition for which the implant was installed has been resolved of fixed. If so, then at 206, the implant is not charged any further and the method ends.

[0044] If the determination at 204 indicates that the condition has not resolved, then at 208, a determination is made regarding whether additional drug therapy or dosage is required. If so, then at 210, the communication is established with the implant device (e.g., by a base station or processor associated with the MR system). At 212, data is received from a power management circuit of the implant device. The method then proceeds to "A", wherein it resumes in FIGURE 5.

[0045] If the determination at 208 is negative, then at 214 a determination is made regarding whether the implant device requires additional charge. If so, the method proceeds to 210 and on to point "A". If not, then at 216, information is gathered regarding the number of charges received by, overall health of, and discharge history of, the implant device battery. The method then proceeds to "B", wherein it resumes in FIGURE 5.

[0046] In FIGURE 5, proceeding from "A", at 218, a determination is made based on the received PMC data regarding whether one or more batteries or supercapacitors in the implant device require charging. If not, then at 220, information is gathered regarding the number of charges received by, overall health of, and discharge history of, each supercapacitor and/or battery. The information collected at 220 is stored to memory and sent to one or more remote "big data" at 222 servers for engineering analysis, e.g., to facilitate proactive action regarding battery or supercapacitor maintenance or replacement. At 224, MR imaging is performed to evaluate the effectiveness of the implant device.

[0047] If the determination at 218 indicates that one or more batteries or supercapacitors requires charging, then a machine learning algorithm is employed to charge the identified battery or supercapacitor. At 228, a number of channels or elements that require charging is determined. At 230, charging pulse sequence parameters are set and the identified elements are charged wirelessly. The pulse sequence parameters may include, for example, gradient, amplitude, duty cycle, and/or flip angle of the charging pulse sequence. At 232, information is gathered regarding the number of charges received by, overall health of, and discharge history of, each supercapacitor and/or battery. The information collected at 232 is stored to memory and sent to one or more remote "big data" servers at 234 for engineering analysis, e.g., to facilitate proactive action regarding battery or supercapacitor maintenance or replacement. The method then proceeds to 224, where MR imaging is performed to evaluate the effectiveness of the implant device.

[0048] Proceeding from "B", at 226, information is gathered regarding the number of charges received by, overall health of, and discharge history of, each supercapacitor and/or battery. The information collected at 226 is stored to memory and sent to one or more remote "big data" at 234 servers for engineering analysis, e.g., to facilitate proactive action regarding battery or supercapacitor maintenance or replacement. The method then proceeds to 224, where MR imaging is performed to evaluate the effectiveness of the implant device.

[0049] The innovation has been described with reference to several embodiments. Modifications and alterations may occur to others upon reading and understanding the preceding detailed description. It is intended that the innovation be construed as including all such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims

CLAIMS:

1. A system (10) that facilitates wirelessly charging of a rechargeable medical device using magnetic resonance (MR) charging pulse sequences (32), comprising:

a processor (28) configured to:

perform a handshake protocol with one or more power management circuits (20, 47) in respective one or more rechargeable medical devices (16, 44);

determine an amount of charge required to recharge the one or more rechargeable medical devices to a predetermined level of charge;

generate at least one MR charging pulse sequence (32); and

a transceiver (33) configured to transmit the at least one MR charging pulse sequence to an MR device (12) for execution in order to recharge the one or more rechargeable medical devices.

2. The system according to claim 1, wherein the handshake protocol is carried out between the processor (28) via the transceiver (33) and a digital processor in each of the one or more power management circuits (16, 44).

3. The system according to claim 1, wherein the processor (28) is further configured to receive from each power management circuit health data (42, 48) describing one or more of:

a state of charge of at least one of a battery and a supercapacitor of the rechargeable medical device (16, 44) in which the power management circuit (20, 47) is employed;

a number of prior charges applied to at least one of the battery and the supercapacitor; and

a number of prior discharges of at least one of the battery and the supercapacitor.

4. The system according to claim 3, wherein the processor (28) is further configured to transmit the health data (42, 48) to a remote server for analysis in identifying proactive maintenance or replacement of at least one of the battery and the supercapacitor.

5. The system according to claim 1, wherein the rechargeable medical device is a loop element (16) in an MR coil (14).

6. The system according to claim 1, wherein the rechargeable medical device is a medical implant device (44).

7. The system according to claim 6, wherein the medical implant device (44) is one of:

a deep brain stimulation (DBS) implant device;

a cardiac defibrillation implant device; and

a powered targeted drug delivery implant device.

8. The system according to claim 1, wherein the MR charging pulse sequence (32) is generated by modifying an MR imaging sequence.

9. The system according to claim 1, wherein the MR charging pulse sequence (32) is interleaved into an MR imaging sequence and executed during an MR imaging scan of a patient.

10. A method of wirelessly charging a rechargeable medical device (16, 44) using magnetic resonance (MR) charging pulse sequences (32), comprising:

performing a handshake protocol with one or more power management circuits (20, 47) in respective one or more rechargeable medical devices;

determining an amount of charge required to recharge the one or more rechargeable medical devices to a predetermined level of charge;

generating at least one MR charging pulse sequence; and

transmitting the at least one MR charging pulse sequence to an MR device for execution in order to recharge the one or more rechargeable medical devices.

1 1. The method according to claim 10, further comprising performing the handshake protocol between a processor (28) in a base station (22) and a digital processor in each of the one or more power management circuits.

12. The method according to claim 10, further comprising receiving, from each power management circuit, health data (42, 48) describing one or more of:

a state of charge of at least one of a battery and a supercapacitor of the rechargeable medical device in which the power management circuit is employed;

13. The method according to claim 12, further comprising transmitting the health data (42, 48) to a remote server for analysis in identifying proactive maintenance or replacement of at least one of the battery and the supercapacitor.

14. The method according to claim 10, wherein the rechargeable medical device is a loop element (16) an MR surface coil (14).

15. The method according to claim 10, wherein the rechargeable medical device is a medical implant device (44).

16. The method according to claim 15, wherein the medical implant device (44) is one of:

a deep brain stimulation (DBS) implant;

a cardiac defibrillation implant; and

a powered targeted drug delivery implant.

17. The method according to claim 10, wherein generating the MR charging pulse sequence (32) further comprises modifying an MR imaging sequence.

18. The method according to claim 10, further comprising interleaving the MR charging pulse sequence (32) into an MR imaging sequence and executing the MR charging pulse sequence during an MR imaging scan of a patient.

19. A wireless and wirelessly-rechargeable medical implant device (44), comprising: at least one rechargeable element;

a power management circuit (20, 47) comprising:

a charge sensor configured to monitor a state of charge of the at least one rechargeable element;

a digital processor configured to generate health data describing the state of charge of the at least one rechargeable element; and

a transceiver configured to transmit the health data to a base station for generating magnetic resonance (MR) charging pulse sequences.

20. The medical implant device (44) of claim 19, wherein the at least one rechargeable element is recharged by the MR charging pulse sequences (32), which are received during an MR imaging scan of a patient in which the medical implant device is implanted.

21. The medical implant device (44) of claim 19, wherein the medical implant device is one of:

a deep brain stimulation (DBS) implant device;

a cardiac defibrillation implant device; and

a powered targeted drug delivery implant device.