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This work focuses on the in silico evaluation of the energy deposed by MRI switched gradient fields in bulk metallic implants and the consequent temperature increase in the surrounding tissues. An original computational strategy, based on the subdivision of the gradient coil switching sequences into sub-signals and on the time-harmonic electromagne...
Citations
... Simulations were performed in two steps, following the computational scheme discussed in Arduino et al (2019). The implementation of the electromagnetic problem complies with the one described in Bottauscio et al (2015). ...
Objective: To quantify the effects of different levels of realism in the description of the anatomy around hip, knee or shoulder implants when simulating, numerically, radiofrequency and gradient-induced heating in MRI. This quantification is needed to define how precise the digital human model modified with the implant should be to get realistic dosimetric assessments. Approach: The analysis is based on a large number of numerical simulations where four “levels of realism” have been adopted in modelling human bodies carrying orthopaedic implants. Main results: Results show that the quantification of the heating due to switched gradient fields does not strictly require a detailed local anatomical description when preparing the digital human model carrying an implant. In this case, a simple overlapping of the implant CAD with the body anatomy is sufficient to provide a quite good and conservative estimation of the heating. On the contrary, the evaluation of the electromagnetic field distribution and heating caused by the radiofrequency field requires an accurate description of the tissues around the prosthesis. Significance: The results of this paper provide hints for selecting the “level of realism” in the definition of the anatomical models with embedded passive implants when performing simulations that should reproduce, as closely as possible, the in vivo scenarios of patients carrying orthopaedic implants.
... The induced heat then diffuses in the surrounding tissues. The highest heating is found when the implant experiences higher GC fields amplitudes, namely relatively far from the imaging region [24]. ...
... The following computational procedure allowed us to minimize the number of simulations required. For a given implant, three electromagnetic simulations, performed with a validated homemade finite element solver [24], provided the current density distribution inside the implant,Ĵ i (x), induced at 1 Hz by a 1-T spatially uniform magnetic flux density directed along the i-th Cartesian axis. Denoted by B k,i the i-th component of the magnetic flux density generated by the k-th GC in the implant barycentre, the actual distribution J k (x) was: ...
... In order to produce conservative results, all the metallic components were simulated as a CoCrMo alloy. Indeed, such an alloy produces higher temperature increases than those generated in titanium-based alloys (e.g., about 140% when a total hip implant is involved [24]) when exposed to the GC excitation. The implants were positioned within the phantom complying with the realistic location and orientation inside a human body. ...
Due to the large variety of possible clinical scenarios, a reliable heating-risk assessment is not straightforward when patients with arthroplasty undergo MRI scans. This paper proposes a simple procedure to estimate the thermal effects induced in patients with hip, knee, or shoulder arthroplasty during MRI exams. The most representative clinical scenarios were identified by a preliminary frequency analysis, based on clinical service databases, collecting MRI exams of 11,658 implant carrier patients. The thermal effects produced by radiofrequency and switching gradient fields were investigated through 588 numerical simulations performed on an ASTM-like phantom, considering four prostheses, two static field values, seven MR sequences, and seven regions of imaging. The risk assessment was inspired by standards for radiofrequency fields and by scientific studies for gradient fields. Three risk tiers were defined for the radiofrequency, in terms of whole-body and local SAR averages, and for GC fields, in terms of temperature elevation. Only 50 out of 588 scenarios require some caution to be managed. Results showed that the whole-body SAR is not a self-reliant safety parameter for patients with metallic implants. The proposed numerical procedure can be easily extended to any other scenario, including the use of detailed anatomical models.
... It is often assumed implicitly that the MR-induced heating in presence of implants is because of the RF field, [19][20][21] but recently an additional hazard caused in bulky passive implants (like joint replacements) by the exposure to MRI gradient fields has been shown. [22][23][24][25][26][27][28] The RF heating is induced directly in the biological tissues by the electromagnetic field, whose spatial distribution can be severely affected by the presence of metallic implants. On the other hand, the gradient field may induce significant eddy currents and Joule losses only within the implant, which heats up and successively diffuses the heat toward the biological tissues. ...
... where T is the period, or the repetition time, of the pulse sequence. This averaging is justified by the different time-scales of the electromagnetic and thermal phenomena 28,34 and it is consistent with the use of the root mean square of the time derivative of the magnetic field as a reference test value in ISO/TS 10974. Therefore, if B(x,t) is the magnetic field generated by the GCs during the execution of a given pulse sequence of length T, the quantity I(x) is an index of the thermal stress that the metallic implant experiences if located in x. ...
... In this paper, as a proof of concept, laboratory experiments are replaced by virtual experiments, where simulations are performed using computational tools. 28 The adopted virtual model consists of the studied implant (hip, knee, or shoulder), with metallic parts made of CoCrMo alloy and without porous or ceramic coating, placed inside the phantom. All the models, presented in Table 1, are discretized with a uniform voxel mesh of 2 mm. ...
Purpose
To theoretically investigate the feasibility of a novel procedure for testing the MRI gradient‐induced heating of medical devices and translating the results into clinical practice.
Methods
The concept of index of stress is introduced by decoupling the time waveform characteristics of the gradient field signals from the field spatial distribution within an MRI scanner. This index is also extended to consider the anisotropy of complex bulky metallic implants. Merits and drawbacks of the proposed index of stress are investigated through virtual experiments. In particular, the values of the index of stress evaluated for realistic orthopedic implants placed within an ASTM phantom are compared with accurate heating simulations performed with 2 anatomic body models (a man and a woman) implanted through a virtual surgery procedure.
Results
The manipulation of the proposed index of stress allows to identify regions within the MRI bore where the implant could affect the safety of the examinations. Furthermore, the conducted analysis shows that the power dissipated into the implant by the induced eddy currents is a dosimetric quantity that estimates well the maximum temperature increase in the tissues surrounding the implant.
Conclusion
The results support the adoption of an anisotropic index of stress to regulate the gradient‐induced heating of geometrically complex implants. They also pave the way for a laboratory characterization of the implants based on electrical measurements, rather than on thermal measurements. The next step will be to set up a standardized experimental procedure to evaluate the index of stress associated with an implant.
... 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t For step (a), the electromagnetic problem was conveniently limited to the region of the metallic objects, assuming that induced currents and related power deposition are confined within the implant at the low frequencies of the GC field. In order to account for the complex time evolution of realistic sequences, the approach proposed and validated in [12] was adopted. The time waveforms of the magnetic field signals were decomposed into truncated Fourier series. ...
... For all the simulations reported in the paper, the GC field was assumed to be spatially uniform in the region of the implant. This assumption makes the results more general, freeing them from the complex spatial distribution of GC fields, which are specific to the scanner model [12]. Thanks to the linearity of the electromagnetic and thermal problems, the results can be adapted to any GC field amplitude B GC , by rescaling the total deposited power and the peak temperature elevation by the factor B 2 GC . ...
Patients with implanted orthopaedic devices represent a growing number of subjects undergoing magnetic resonance imaging (MRI) scans each year. MRI safety labelling is required for all implants under the EU Medical Device Regulations to ensure regulatory compliance, with each device assessed through standardised testing procedures. In this paper, we employ parametric studies to assess a range of clinically relevant factors that cause tissue heating, performing simulations with both radiofrequency (RF) and gradient coil (GC) switching fields, the latter of which is often overlooked in the literature. A series of worst case scenarios for both types of excitation field are discussed. In the case of GC fields large volume implants and large plate areas with the field oriented perpendicular to the plane cause the highest heating levels, along with sequences with high rates of field switching. Implant heating from RF fields is driven primarily from the antenna effect, with thin, linear implants of resonant length resulting in the highest temperature rises. In this work, we show that simplifications may be made to the field sequence and device geometry without significantly comprising the accuracy of the simulation results, opening up the possibility for generic estimates of the implant heating for orthopaedic device manufacturers and opportunities to simplify the safety compliance process.
... Switched gradient-field heating has been investigated to a lesser extent. [22][23][24][25][26][27][28][29][30] Graf et al 22 evaluated the heating of metallic objects, including a titanium hip prosthesis and an aluminum replica, during a 3D true fast imaging sequence with steady precession (TrueFISP) and concluded that, under specific conditions (eg, high duty cycle, long measuring time, metallic components with low resistance), gradient-induced heating of conducting specimens could be expected. These general conclusions were in line with the results of experiments involving metallic components. ...
... The spatial distributions of the two fields are significantly different. The RF B 1 field is oriented primarily along the transverse plane and is as uniform as possible, whereas all three orthogonal components of the GC magnetic field contribute to the heating of metallic implants, 29,30 and the vector addition of the corresponding field distributions is required to predict the heating effects. Typical gradients range from 20 mT/m to 40 mT/m, with slew rates up to 200 T/(m s), 30 and gradient field magnitude may reach several millitesla. ...
... Following the approach described in Arduino et al, 29 the GC simulations were restricted to the region of the metallic implant. This numerical approach is based on time-harmonic electromagnetic solutions. ...
Purpose
To investigate how the simultaneous exposure to gradient and RF fields affects the temperature rise in patients with a metallic hip prosthesis during an MRI session.
Methods
In silico analysis was performed with an anatomically realistic human model with CoCrMo hip implant in 12 imaging positions. The analysis was performed at 1.5 T and 3 T, considering four clinical sequences: turbo spin‐echo, EPI, gradient‐echo, and true fast imaging sequence with steady precession. The exposure to gradient and RF fields was evaluated separately and superposed, by adopting an ad hoc computational algorithm. Temperature increase within the body, rather than specific absorption rate, was used as a safety metric.
Results
With the exception of gradient‐echo, all investigated sequences produced temperature increases higher than 1 K after 360 seconds, at least for one body position. In general, RF‐induced heating dominates the turbo spin‐echo sequence, whereas gradient‐induced heating prevails with EPI; the situation with fast imaging sequence with steady precession is more diversified. The RF effects are enhanced when the implant is within the RF coil, whereas the effects of gradient fields are maximized if the prosthesis is outside the imaging region. Cases for which temperature‐increase thresholds were exceeded were identified, together with the corresponding amount of tissue mass involved and the exposure time needed to reach these limits.
Conclusion
The analysis confirms that risky situations may occur when a patient carrying a hip implant undergoes an MRI exam and that, in some cases, the gradient field heating may be significant. In general, exclusion criteria only based on whole‐body specific absorption rate may not be sufficient to ensure patients’ safety.
... The possible heating of metallic devices implanted in the patient's body is a source of concern in MRI, discussed in many papers and standards. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] Two fields may produce heating in the presence of metallic implants: gradient fields (which may deposit significant Joule losses within bulky metallic objects [16][17][18][19][20] and radiofrequency (RF) fields. In the latter case, thermal effects are commonly evaluated in terms of specific absorption rate (SAR) around the implant and, sometimes, of the consequent heating. ...
Background and Objectives
Electric currents are induced in implanted medical devices with metallic filamentary closed loops (e.g., fixation grids, stents) when exposed to time varying magnetic fields, as those generated during certain diagnostic and therapeutic biomedical treatments. A simplified methodology to efficiently compute these currents, to estimate the altered electromagnetic field distribution in the biological tissues and to assess the consequent biological effects is proposed for low or medium frequency fields.
Methods
The proposed methodology is based on decoupling the handling of the filamentary wire and the anatomical body. To do this, a circuital solution is adopted to study the metallic filamentary implant and this solution is inserted in the electromagnetic field solution involving the biological tissues. The Joule losses computed in the implant are then used as a forcing term for the thermal problem defined by the bioheat Pennes’ equation. The methodology is validated against a model problem, where a reference solution is available.
Results
The proposed simplified methodology is proved to be in good agreement with solutions provided by alternative approaches. In particular, errors in the amplitude of the currents induced in the wires result to be always lower than 3 %. After the validation, the methodology is applied to check the interactions between the magnetic field generated by different biomedical devices and a skull grid, which represents a complex filamentary wire implant.
Conclusions
The proposed simplified methodology, suitable to be applied to closed loop wires in the low to intermediate frequency range, is found to be sufficiently accurate and easy to apply in realistic exposure scenarios. This modelling tool allows analyzing different types of small implants, from coronary and biliary duct stents to orthopedic grids, under a variety of exposure scenarios.
Background:
Testing MRI gradient-induced heating of implanted medical devices is required by regulatory organizations and others. A gradient heating test of the ISO 10974 Technical Specification (TS) for active implants was adopted for this study of passive hip implants. All but one previous study of hip implants used nonuniform gradient exposure fields in clinical scanners and reported heating of less than 5 °C. This present study adapted methods of the TS, addressing the unmet need for identifying worst-case heating via exposures to uniform gradient fields.
Purpose:
To identify gradient-field parameters affecting maximum heating in vitro for a hip implant and a cylindrical titanium disk.
Study type:
Computational simulations and experimental validation of induced heating.
Phantom:
Tissue-simulating gel.
Field strength:
42 T/s RMS, sinusoidal, continuous B fields with high spatial uniformity ASSESSMENT: Hip implant heating at 1-10 kHz, via computational modeling, validated by limited point measurements. Experimental measurements of exposures of an implant at 42 T/s for 4, 6, and 9 kHz, analyzed at 50, 100, and 150 seconds.
Statistical tests:
One sample student's t-test to assess difference between computational and experimental results. Experimental vs. computational results were not significantly different (p < 0.05).
Results:
Maximum simulated temperature rise (10-minute exposure) was 10 °C at 1 kHz and 0.66 °C at 10 kHz. The ratio of the rise for 21 T/s vs. 42 T/s RMS was 4, after stabilizing at 50 seconds (dB/dt ratio squared).
Data conclusions:
Heating of an implant is proportional to the frequency of the B field and the implant's cross-sectional area and is greater for a thickness on the order of its skin depth. Testing with lower values of dB/dt RMS with lower cost amplifiers enables prediction of heating at higher values for dB/dt squared (per ISO TS) with identical frequency components and waveforms, once thermal equilibrium occurs.
Evidence level:
1 TECHNICAL EFFICACY: Stage 1.
A numerical procedure for analyzing electromagnetic (EM) fields interactions with biological tissues is presented. The proposed approach aims at drastically reducing the computational burden required by the repeated solution of large scale problems involving the interaction of the human body with EM fields, such as in the study of the time evolution of EM fields, uncertainty quantification, and inverse problems. The proposed volume integral equation (VIE), focused on low frequency applications, is a system of integral equations in terms of current density and scalar potential in the biological tissues excited by EM fields and/or electrodes connected to the human body. The proposed formulation requires the voxelization of the human body and takes advantage of the regularity of such discretization by speeding-up the computational procedure. Moreover, it exploits recent advancements in the solution of VIE by means of iterative preconditioned solvers and ad hoc parametric Model Order Reduction techniques. The efficiency of the proposed tool is demonstrated by applying it to a couple of realistic model problems: the assessment of the peripheral nerve stimulation, performed in terms of evaluation of the induced electric field, due to the gradient coils of a magnetic resonance imaging scanner during a clinical examination and the assessment of the exposure to environmental fields at 50 Hz of live-line workers with uncertain properties of the biological tissues. Thanks to the proposed method, uncertainty quantification analyses and time domain simulations are possible even for large scale problems and they can be performed on standard computers and reasonable computation time. Sample implementation of the method is made publicly available at https://github.com/UniPD-DII-ETCOMP/BioMOR.
