The disclosure relates generally to magnetic resonance imaging (MRI) systems and, more particularly, to parallel transmission RF pulses for use in MRI systems.
Magnetic resonance imaging (MRI) is a medical imaging technique in widespread use for viewing the structure and function of the human body. MRI systems provide soft-tissue contrast, such as for diagnosing many soft-tissue disorders. MRI systems generally implement a two-phase method. The first phase is the excitation phase, in which a magnetic resonance signal is created in the subject with a main, polarizing magnetic field, B0, and a radio frequency (RF) excitation pulse, B1+. The second phase is the acquisition phase, in which the system receives an electromagnetic signal emitted as the excited nuclei relax back into alignment with the main magnetic field after the excitation pulse B1 is terminated. These two phases are repeated pair-wise to acquire enough data to construct an image.
Higher magnetic field strength scanners have been recently used to improve image signal-to-noise ratio and contrast. However, a spatial variation in the magnitude of the RF excitation magnetic field, B1+, occurs with main magnetic field strengths of, for example, 7 Tesla. This undesirable non-uniformity in the excitation across the region of interest is commonly referred to as “center brightening,” “B1+ inhomogeneity” or “flip angle inhomogeneity.”
Newer-generation MRI systems have generated RF pulses with a spatially tailored excitation pattern to mitigate B1+ inhomogeneity by exciting a spatial inverse of the inhomogeneity. In these systems, multiple radio-frequency pulse trains are transmitted in parallel over independent radio-frequency transmit channels, e.g., the individual rods of a whole-body antenna. This method, referred to as “parallel transmission” or “parallel excitation,” exploits variations among the different spatial profiles of a multi-element RF coil array. Parallel excitation has enabled several important applications beyond the mitigation of B1+ inhomogeneity, including flexibly shaped excitation volumes.
Unfortunately, parallel transmission techniques generally increase peak pulse power, giving rise to concerns regarding excessive exposure to RF energy. A typical measure of the physiological absorption of the RF energy is the specific absorption rate, or SAR, which specifies the deposited power per unit weight (watts/kg) due to the RF pulse. Maximum values for SAR are specified by safety regulations and should be met both globally (e.g., power absorbed by the whole head or whole body) and locally (e.g., power absorbed per 10 grams of tissue). For example, a standardized limit of 4 watts/kg applies to the global SAR of a patient according to an IEC (International Electrotechnical Commission) standard.
When multiple transmit channels are simultaneously employed, the local electric fields generated by each channel undergo local superposition, and local extremes in electric field magnitude may arise, leading to spikes in local SAR. Recent studies have confirmed the presence of “hot spots” and found that parallel transmitted pulses produce relatively high ratios of local to whole-head average SAR, as is described by, for example, F. Seifert et al., in “Patient Safety Concept for Multichannel Transmit Coils,” J. Magn. Reson. Imag., 26:1315-1321 (2007). These relatively-high ratios of local to whole-head average SAR make local SAR the limiting factor of parallel transmission MRI. Concerns regarding elevated SAR levels are also set forth in U. Katscher and P. Bornert in “Parallel RF Transmission in MRI.” NMR Biomed, 19:393-400 (2006).
One technique for SAR reduction involves placing constraints on global and local SAR. In this method, SAR constraints are explicitly built into the pulse design process. Because both whole-head mean SAR and local N-gram SAR at any location can be expressed quadratically in terms of pulse sample values, constraints on both whole-head and local SAR can be incorporated simply by adding quadratic constraints to the design method. For example, the method described by I. Graesslin, et al., in “A Minimum SAR RF Pulse Design Approach for Parallel Tx with Local Hot Spot Suppression and Exact Fidelity Constraint,” Proc. Intl. Soc. Magn. Reson. Med., 2008; 612, explicitly accounts for global SAR as well as local SAR at several spatial locations by incorporating several quadratic constraints into the design. However, this approach presents a computationally intractable problem of solving a system of equations with tens of thousands (or millions) of quadratic constraints.
Parallel transmission pulses are designed based on spatial sensitivity to local specific absorption rate (SAR) and a minimized weighted average of local SAR values. The spatial sensitivity to local SAR is used to compress a model into a set of virtual observation points. The minimized weighted average of local SAR is then calculated over the virtual observation points in an iterative procedure to optimize a set of weighting factors.
In accordance with one aspect, a method of designing a parallel transmission radio frequency (RF) pulse for a magnetic resonance imaging (MRI) system includes compressing a model for a subject to be scanned by the MRI system into a plurality of virtual observation points within the model based on comparisons of peak sensitivity to local specific absorption rate (SAR), and defining, with a processor, the parallel transmission RF pulse for antenna of the MRI system that minimizes a weighted average of local SAR values with an iterative procedure that optimizes a set of weighting factors for the plurality of virtual observation points to maximize the minimized weighted average.
In accordance with another aspect, a method of imaging with a parallel transmission RF pulse for an MRI system. The parallel transmission RF pulse is transmitted. The parallel transmission RF pulse corresponds a design using a spatial matrix for each voxel of a model for a subject to be scanned by the MRI system where the spatial matrix is indicative of absorption sensitivity, designating a subset of the voxels as a plurality of virtual observation points for the model by iteratively evaluating the spatial matrices of the voxels to determine whether the absorption sensitivity of a respective one of the voxels is upper bounded by a global SAR-based overestimation of the absorption sensitivity of at least one previously evaluated voxel, and defining the parallel transmission RF pulse that minimizes a weighted average of local SAR over the virtual observation points with an iterative procedure that optimizes a set of weighting factors for the weighted average to maximize the minimized weighted average of local SAR over the virtual observation points.
In accordance with yet another aspect, an MRI system includes a data storage unit to store calibration data for a model for a subject to be scanned, the model having a number of voxels, a coil array for transmitting a parallel transmission RF pulse to the subject, and a control system in communication with the data storage unit and the coil array. The control system is configured to design the parallel transmission RF pulse to control local SAR based on the model, a model compression in which the model is compressed into a plurality of virtual observation points within the model based on comparisons of peak sensitivity to SAR, and an iterative procedure applied to pulses configured to minimize a weighted average of local SAR values, the iterative procedure being configured to optimize a set of weighting factors for the plurality of virtual observation points to maximize the minimized weighted average.
The disclosed methods and systems are directed to designing, applying, and storing parallel transmission RF pulses for magnetic resonance imaging (MRI) scans. The disclosed methods and systems are configured for fast RF pulse design while minimizing or controlling local specific absorption rate (SAR) levels resulting from the application of parallel transmission RF pulses. With the disclosed systems and methods, local-SAR constrained, parallel transmission RF pulses can be designed, stored, and/or used on-the-fly in a time frame suitable for clinical use while remaining capable of achieving flexibly shaped excitation volumes for mitigating spatial inhomogeneities and other purposes. The RF pulses designed by the disclosed systems and methods may be specific or tailored to each subject.
Parallel transmission (pTx) systems provide increased flexibility to generate a variety of magnetization profiles in magnetic resonance imaging (MRI) relative to conventional single-channel RF systems. Parallel transmission (pTx) systems are generally limited by SAR constraints. While global or average SAR values are readily measured and easily amenable to incorporation as constraints in the pTx RF pulse design, local SAR minimization during the design of pTx RF pulses poses a challenging problem. That local SAR is generally not measurable is only part of the problem. The significant challenge is that local SAR estimation resolution in segmented tissue models constitutes an optimization problem with a heavy computational burden. An exhaustive search for the single RF pulse design that minimizes local SAR for a given patient is not feasible given the length of time that the patient would be forced to wait during a scan sequence. Calculating local SAR for every voxel for every possible pTx RF pulse may preclude the real-time, or on-the-fly, design of the pTx RF pulse.
In contrast, the disclosed systems and methods enable the RF pulses to be designed in real-time, or on-the-fly, for a specific subject, in the sense that the RF pulses can be defined in a time frame reasonable for a subject remaining in the scanner after one or more preparation or calibration scans. A reasonable time frame may, for instance, be on the order of tens of seconds or perhaps one or two minutes. In this way, the disclosed systems and methods do not introduce overly burdensome delays for the subject.
The disclosed pulse design systems and methods address the challenge presented by the varied distribution of the parallel transmission signals superimposing inside the body. As a result of the multiple (N) channels in the transmission system, many potentially important locations are to be considered for local SAR evaluation rather than just one fixed hot spot. These challenges notwithstanding, the disclosed systems and methods efficiently and effectively incorporate local SAR constraints into the pTx RF pulse design, while remaining capable of mitigating spatial flip angle inhomogeneities. The local-SAR-constrained design may decrease local SAR considerably relative to conventional pTx design with only an average SAR constraint.
The disclosed systems and methods implement a model compression technique to determine virtual observation points for the model to decrease the complexity of the prediction of the local SAR calculations. The designation of virtual observation points is based on spatial absorption sensitivity to local SAR. Rather than assign each voxel to a respective cluster of voxels, the disclosed systems and methods iteratively evaluate the spatial sensitivities of the voxels to determine whether the absorption sensitivity of a respective one of the voxels is upper bounded by a global SAR-based overestimation of the absorption sensitivity of at least one previously evaluated voxel. The resulting set of virtual observation points may then be used to reasonably predict and control the maximum local SAR, despite the small size of the set relative to the total number of voxels in the model.
The disclosed systems and methods also implement an iterative procedure to design the pulses based on the local SAR levels reached at the virtual observation points. The iterative procedure uses a set of weighting factors for the virtual observation points to represent the local SAR component to convert the design procedure into a computationally feasible condition. Pulses that minimize a weighted average of local SAR are processed by the iterative procedure to update the set of weighting factors to maximize the minimum weighted average. In some embodiments, the pulse design process may include approximating a peak local SAR as a weighted average of the local SAR. In each iterative step of the pulse design process, weighting factors may be fixed and the RF pulse is designed to minimize the weighted average of the local SAR. For a better approximation of the peak local SAR, i.e. to minimize the gap between the weighted average of the local SAR and peak local, the weighting factors are updated. The pulse design process may, in some cases, increase the weighted average of the local SAR.
The disclosed pulse design methods and systems may capture the spatial distribution of local SAR in numerical tissue models in a compressed parameterization in order to incorporate local SAR constraints within a design process having a computation time that accommodates design during an in vivo MRI scan. The design methods and systems provide a protocol-specific peak local SAR, which bounds the achievable peak local SAR for a given excitation profile fidelity. The disclosed methods and systems may reduce peak local 10 g SAR by 14-66% for slice-selective pTx excitations and 2D selective pTx excitations compared to a pTx pulse design constrained only by global SAR. While the improvement may lead to an increase in global SAR (e.g., up to 34%), the increase may be favorable in cases where local SAR constraints dominate the pulse applications.
The disclosed methods and systems are well-suited for use with a variety of different design algorithms or pulse types, including, for example, RF shimming, spoke design, spiral trajectory excitation, spatially selective excitation, uniform volume excitation, spatial-domain design for small flip angle approximation, linear class of large tip angle pulses, and optimal control methods.
The disclosed methods and systems may include or use one or more iterative procedures during the pulse design to optimize a set of weighting factors for a set of virtual observation points. Further information regarding the use of optimizers in connection with virtual observation points in pulse design is set forth in U.S. patent application Ser. No. 13/083,342 (which was filed on Apr. 8, 2011, and entitled “Parallel Transmission RF Pulse Design with Local SAR Constraints”), the entire disclosure of which is hereby incorporated by reference, and Gebhardt M, et al., “Evaluation of Maximum Local SAR for Parallel Transmission (PTx) Pulses Based on Pre-Calculated Field Data Using a Selected Subset of ‘Virtual Observation Points’,” Proc. Intl. Soc. Mag. Reson. Med., Stockholm, Sweden, p 1441 (2010). The disclosed methods and systems may include one or more features of the methods and systems described in the above-referenced documents in some embodiments.
Turning now to the drawing figures,
The control system 104 includes a workstation 110 having one or more output interfaces (e.g., display) 112 and one or more input interfaces (e.g., keyboard) 114. The workstation 110 includes a processor 116, which may be a commercially available, programmable machine running a commercially available operating system. The workstation 110 provides an operator interface that enables scan sequences to be entered into or otherwise defined for the control system 104 and the MRI system 100. The workstation 110 may be coupled to a number of servers, including, in this example, a pulse sequence server 118, a data acquisition server 120, a data processing server 122, and a data store server 124. The workstation 110 and the servers 118, 120, 122 and 124 may communicate with each other via any desired communication technique, protocol, or standard. The servers 118, 120, 122, and 124 may correspond with respective services provided by a single workstation, such as the workstation 110. The components of the control system 104 may be coupled to one another via a data bus or network (not shown) and need not be connected via respective, dedicated communication lines as shown. Any one or more of the components of the control system 104 may be implemented as a service unit, module, or other unit implemented by a common physical machine or other device. Additional, different, or fewer components may be provided, such as combining two or more servers or providing the workstation functionality on a server or vice versa.
The pulse sequence server 118 functions in response to instructions downloaded from the workstation 110 to operate a gradient system 126 and a radio frequency (“RF”) system 128. Scan sequences containing data indicative of the RF pulses and gradients may be stored in a library or other memory of the pulse sequence server 118 or other component of the control system 104. Gradient waveforms to perform the prescribed scan are produced and applied to the gradient system 126 that excites gradient coils in a gradient coil assembly 130 to produce the magnetic field gradients Gx, Gy, and Gz used for position-encoding MR signals. The gradient coil assembly 130 forms part of a magnet assembly 132 that includes an annular or other polarizing magnet 134 and a whole-body RF coil array 136. In some cases, the whole-body RF coil array 136 is constructed in the form of a so-called birdcage antenna and has a number of individual antenna rods which run parallel to the patient tunnel and uniformly distributed in a circumferential arrangement around the patient tunnel. The individual antenna rods may be capacitively coupled to one another in a ring shape at one end of the birdcage antenna. A depiction of an exemplary birdcage antenna is shown in connection with the SAR calculation technique described in U.S. Patent Publication No. 2010/0327868 (“SAR Calculation for Multichannel MR Transmission Systems”), the entire disclosure of which is incorporated by reference.
RF excitation waveforms are applied to the RF coil 136 by the RF system 128 to perform a selected magnetic resonance pulse sequence. Responsive MR signals detected by the RF coil 136 or a separate local coil (not shown) are received by the RF system 128, amplified, demodulated, filtered and digitized under direction of the pulse sequence server 118. The RF system 128 includes an RF transmitter for producing a wide variety of RF pulses used in MR pulse sequences. The RF transmitter is responsive to the selected scan sequence and direction from the pulse sequence server 118 to produce RF pulses of the desired frequency, phase and pulse amplitude waveform. The generated RF pulses may be applied to the whole body RF coil 136 or to one or more local coils or coil arrays. As described below, the RF transmitter includes a plurality of transmission channels to produce RF pulses formed via the superimposition of the RF pulses generated by each transmission channel.
The RF system 128 also includes one or more RF receiver channels. Each RF receiver channel includes an RF amplifier that amplifies the MR signal received by the coil to which it is connected. Each receiver may also include a detector that collects and digitizes in-phase (I) and quadrature (Q) components of the received MR signal.
The pulse sequence server 118 may receive patient data from a physiological acquisition controller 138. The controller 138 receives signals from a number of different sensors connected to the patient, such as ECG signals from electrodes or respiratory signals from a bellows. Such signals are typically used by the pulse sequence server 118 to synchronize, or “gate”, the implementation of the scan sequence with the subject's respiration or heart beat.
The pulse sequence server 118 also connects to a scan room interface circuit 140 that receives signals from various sensors associated with the condition of the patient or subject and the magnet system. It is also through the scan room interface circuit 140 that a subject positioning system 142 receives commands to move the subject to desired positions during the scan sequence. The subject positioning system 142 may direct one or more motors (not shown) that drive a bed and, thus, the subject, to a desired position.
The digitized MR signal samples produced by the RF system 128 are received by the data acquisition server 120. The data acquisition server 120 operates in response to instructions downloaded from the workstation 110 to receive the real-time MR data and provide buffer storage such that no data is lost by data overrun. In some scan sequences, the data acquisition server 120 does little more than pass the acquired MR data to the data processor server 122. However, in scans that require information derived from acquired MR data to control the further performance of the scan, the data acquisition server 120 is programmed to produce such information and convey it to the pulse sequence server 118. For example, during calibration or other pre-scans, MR data is acquired and used to calibrate the pulse sequence performed by the pulse sequence server 118. The calibration data may be stored in a memory or storage device or other unit of, associated with, or in communication with, any of the aforementioned servers or other devices. Also, navigator signals may be acquired during a scan and used to adjust RF or gradient system operating parameters or to control the view order in which k-space is sampled. The data acquisition server 120 may be employed to process MR signals used to detect the arrival of contrast agent in a magnetic resonance angiography (MRA) scan. In all these examples, the data acquisition server 120 acquires MR data and processes it in real-time to produce information that is used to control the scan.
The data processing server 122 receives MR data from the data acquisition server 120 and processes it in accordance with instructions downloaded from the workstation 110. Such processing may include, for example, Fourier transformation of raw k-space MR data to produce two or three-dimensional images, the application of filters to a reconstructed image, the performance of back-projection image reconstruction of acquired MR data, the calculation of functional MR images, the calculation of motion or flow images, segmentation, rendering, or other visualization processes.
Images reconstructed by the data processing server 122 are conveyed back to the workstation 110 for storage and/or display. Real-time images may be stored in a database memory cache (not shown) from which they may be output to the display 112 or an auxiliary terminal or console 144, which may be located near the magnet assembly 132 for use by attending physicians or other operators. Batch mode images or selected real time images are stored in a database on mass storage device 146, which may include any desired storage medium. When such images have been reconstructed and transferred to storage, the data processing server 122 notifies the data store server 124 on the workstation 110. The workstation 110 may be used by an operator to archive the images, produce films, or send the images via a network to other facilities.
Referring now to
The RF system 126 includes a set of transmitters 200, each of which produces an individual, selected RF excitation field. The base, or carrier, frequency of this RF excitation field is produced under control of a frequency synthesizer 204, which receives a set of digital control signals from the pulse sequence server 118. These control signals may include data representative of the frequency and phase of the RF carrier signal, which may be produced at an output 206. The RF carrier is applied to a modulator and up converter 208 in each transmitter 200, where its amplitude is modulated in response to a signal also received from the pulse sequence server 118. The signal defines the envelope of the RF excitation pulse to be produced and is generated by sequentially reading out a series of stored digital values. These stored digital values may be changed to enable any desired RF pulse envelope to be produced by each transmitter 200.
The magnitude of the RF excitation pulse produced at an output 210 is attenuated by an exciter attenuator circuit 212 in each transmitter 200. Each attenuator circuit 212 receives a digital command from the pulse sequence server 118. The attenuated RF excitation pulses are applied to a power amplifier 214 in each transmitter 200. The power amplifiers 214 are current source devices that connect to respective transmit inputs on a set of transmit/receive switches 216. In this example, a desired number N of the transmitters 200 are employed and connected through a corresponding number N of the transmit/receive switches 216 to a corresponding number N of the coil elements in the RF coil array 136. Other transmitter arrangements may be used.
The signal produced by the subject is picked up by the coil array 200 and applied to the inputs of the set of receive channels 202. A pre-amplifier 218 in each receiver channel 202 amplifies the signal by an amount determined by a digital attenuation signal received from the pulse sequence server 118 (
The transmit/receive switches 216 are controlled and directed by the pulse sequence server 118 (
When the B1 field is not produced, the pulse sequence server 118 directs the transmit/receive switches 216 to connect each of the N receive channels to the respective N coil elements. Signals produced by the excited spins in the subject are picked up and separately processed as described above.
In this example, the method includes an act 302 in which a preliminary scan sequence is selected from a library of predetermined scan sequences made available by the control system 104 (
A calibration act 304 may be implemented after selection of the numerical model and the scan sequence (or scan type). The calibration act 304 is generally directed to adjusting the selected numerical model before the model is used for electric field calculations that support the RF pulse design. Generally speaking, each calibration scan provides feedback regarding the electric and magnetic fields produced in a tissue segment by the respective array elements of the system for a given pTx pulse. The calibration act 304 may include any number of scans, as desired, and may involve standard calibration techniques used with commercially available scanners used in typical clinical contexts. The calibration act 304 may be implemented before the selection of the scan sequence.
The calibration scan(s) are used to adjust the numerical model of the body based on the transverse magnetization resulting from the RF pulses applied during the calibration scan(s). Each calibration scan may involve any desired combination of the parallel transmit channels 200. The magnetization resulting from each scan is captured and processed by the RF system 128, the data acquisition server 120, and other components of the control system 104 in much the same manner as an RF pulse designed for clinical purposes. However, the data is instead used to improve the model's ability to predict the magnetic field generated in the subject's body resulting from a given RF pulse by incorporating or adjusting tissue properties, such as conductivity, dielectricity, density, etc. In this way, the model may be adjusted to reflect anatomical or other differences of the specific subject relative to the numerical model that should be taken into account during RF pulse design. Calibration data, which may be indicative of, for instance, the calibration scan results or the adjustments to the model, may be stored in any server, device, component, or other unit of the control system 104 (
After completion of the calibration scans, and once the numerical model has been adjusted for the specific subject and scan sequence, an RF pulse design act 306 is implemented to define and select an RF pulse with one or more local SAR-based constraints. The RF pulse design act 306 may be performed on, for instance, the workstation 110 (
Once the RF pulse is defined and selected, an operator may use the workstation 110 (
Further details regarding the pTx RF pulse design method are provided in connection with an example shown in
In view of the foregoing relationship, the spatial matrix, S, is indicative of the sensitivity of a particular voxel to electric field absorption. The spatial matrix, S, does not incorporate the details of the RF excitation or any other temporal information. Instead, the spatial matrix, S, reflects the anatomy of the subject, the positioning of the RF coil(s), and other non-temporal, spatial parameters.
In this example, the pre-calculation of the fields and, thus, the spatial matrices Sv for local SAR sensitivity representation, are generated and averaged for a volume of the numerical model surrounding each voxel v, i.e., an N-gram volume such as a 10 g volume. For N-gram SAR calculation, the fields in the N-gram region around the voxel v are pre-calculated using the FDTD technique, and the local SAR in the region may be averaged as follows:
Further details regarding exemplary procedures for the pre-calculation of the spatial matrix S as an indication of SAR sensitivity are set forth in U.S. Patent Publication No. 2010/0308825 (“Method and Device for Selecting Body Model Positions for SAR Monitoring of a Magnetic Resonance Transmit Array”), and U.S. application Ser. No. 13/045,832 (“Method for Determining Sensitivity Matrices for Hotspots”), the entire disclosures of which are hereby incorporated by reference.
Upon completion of the pre-calculation of the spatial matrix for the absorption sensitivity of each voxel, the selected (and calibrated) model is compressed in act 402 into a set of virtual observation points (VOPs). The model compression is based on comparisons of peak sensitivity to local specific absorption rate (SAR). The set of VOPs is determined or designated by evaluating the absorption sensitivity of each voxel relative to a global SAR-based overestimation of SAR spatial sensitivity. The global SAR-based overestimation may define or establish an upper bound matrix for finding the virtual observation points via an iterative process. The overestimation may be calculated as a sum of the spatial matrix of the virtual observation point and a global SAR matrix scaled by an overestimation factor. The model may then be compressed by iteratively evaluating the voxels to determine whether the absorption sensitivity of a respective one of the voxels is upper bounded by the absorption sensitivity of at least one previously evaluated voxel. If the absorption sensitivity is not upper bounded, then the voxel is added to the set of VOPs. As described below, the upper bound may be established via an overestimation factor, which, in some embodiments, may be used to scale a global SAR term. For example, an upper and lower bound for the VOP determination may be as follows:
The VOPs are the subset, Vsub, of the voxels that satisfy the above expression for any pulse, b(t). Because Vsub is a subset of all of the voxels, the lower bound is satisfied. The upper bound determination may be implemented via an iterative procedure that allows each voxel in the model to be jointly upper bounded by all of the VOPs within the overestimating term. For any voxel v, there exists a set of voxel-dependent nonnegative coefficients cw,v whose sum is unity over the VOPs, such that
As a result, several VOPs may contribute to bound a particular voxel. Which particular VOP ultimately upper bounds the voxel is allowed to depend on the pulse waveform b(t). Thus, the compression method captures more dependencies among the voxels in the model than in an compression method in which each voxel is only represented by a single VOP. The compression method may thus decrease the number of voxels in Vsub required to estimate local SAR. Further details regarding the model compression method are set forth below in connection with the examples of
which is true if all the eigenvalues of the matrix,
are nonnegative.
The overestimation factor ∈ may be considered a tuning factor of the compression procedure and pTx pulse design methods disclosed herein. By decreasing the overestimation factor ∈, the approximation of the maximum local SAR within the model is tighter, and the number of virtual observation points is increased. Conversely, by increasing the overestimation factor E, the approximation of the maximum local SAR within the model is less tight, and the number of virtual observation points is decreased.
Other model compression techniques involving a spatial matrix indicative of absorption sensitivity may be used to determine or designate the VOPs. While some embodiments of the model compression method may use a greedy algorithm, other techniques may be used to determine an optimal or near optimal solution.
Upon completion of the model compression act 402, the spatial sensitivity of the model and coil design to local SAR peaks or hotspots is captured via the virtual observation points (VOPs). Up through this point in the method, the processing is not limited to any particular type of pulse or pulse design. The processing is pulse-generic, as the set of VOPs may be used to design a variety of different parallel transmission pulses. The VOPs may thus be pre-computed once for a given model and array configuration, and then later applied in subsequent computations directed to efficiently estimating peak local SAR due to a given pTx RF pulse. By capturing peaks in the local SAR distribution with VOPs, it becomes feasible to incorporate peak local SAR constraints in pTx RF designs.
An iterative procedure to design a specific parallel transmission pulse with peak local SAR constraints based on the set of VOPs is implemented in act 404. The iterative procedure is configured to design the pulse by optimizing a set of weighting factors for the VOPs. The pulse is configured to minimize a weighted average of local SAR. The iterative procedure is configured to determine values for the weighting factors that maximize a minimum weighted average of local SAR. Use of the weighting factors allows one or more pulse design constraints to be solved or otherwise incorporated into the pulse design through the use of commercially available optimizers.
The pTx pulse design methods disclosed herein may be based on one or more local SAR-based constraints. Instead of minimizing the maximum local SAR of the entire model, the lower bound in the above-described VOP condition is minimized, which is a tight lower bound for the small overestimating factor, ∈G, and which may also equal the maximum local SAR of the entire model if the voxel of the maximum local SAR belongs to one of the VOPs. The performance of this pTx pulse design may be evaluated for pulses with a fixed excitation performance target, which may be the root mean square error (RMSE) relative to the desired transverse magnetization profile, md, inside the region of interest (ROI). The transverse magnetization, m(b), by transmitting pTx RF pulse b(t), may be calculated using Bloch equation simulations. The disclosed methods and systems may be applied for excitation targets defined in terms of either least-squares or magnitude-least-squares.
The iterative procedure may be configured to determine a lower bound, SARlow, of the peak local SAR in the subset Vsub that can be achieved with the fixed RMSE. The pTx RF pulse, b(t), to reach the lower bound may then be determined as follows:
Notwithstanding the advantages of the model compression technique described above, minimizing the design criterion may be difficult within the time constraints of the MRI scan. To decrease the computational time involved, an approximation involving a set of weighting factors is employed. The approximation determination is generally implemented in the act 404 once the set of VOPs are determined.
The act 404 may consider pTx RF pulses that minimize the weighted average of the local SAR. Among the pTx RF pulses designed, the lower bound of the peak local SAR over VOPs and a pTx RF pulse that minimizes the peak local SAR over VOPs are determined. Given nonnegative weighting factors, wv, whose sum is equal to one, let bw(t) be a pTx RF pulse, with a fixed RMSE performance, c, that minimizes the weighted average of the local SAR:
where wv are non-negative weighting factors whose sum is equal to one. Each weighting factor is applied to a respective one of the VOP spatial matrices.
The approximation effectively converts the local SAR-based design constraint into a problem for which a solution is computationally feasible using one of several available or known optimizers, such as those utilizing a conjugate gradient method or other codes. Please see, for example, Setsompop, K., et al., “Magnitude least squares optimization for parallel radio frequency excitation design demonstrated at 7 Tesla with eight channel,” Magn Reson Med, Vol. 59(4), p. 908-15 (2008), Setsompop, K., et al., “Parallel RF transmission with eight channels at 3 Tesla,” Magn Reson Med, Vol. 56(5), p. 1163-71 (2006), Grissom, W., et al., “Spatial domain method for the design of RF pulses in multicoil parallel excitation,” Magn Reson Med, Vol. 56(3), p. 620-9 (2006), and Gumbrecht R., et al., “Fast high-flip pTx pulse design to mitigate B1+ inhomogeneity using composite pulses at 7 T,” 18th Annual Meeting of ISMRM (2010). Using these pulse design methods to resolve the approximation constraint, the approximation is updated via the iterative process to effectively implement the design constraint.
The iterative procedure may be used to find the ultimate peak local SAR (PUPiL SAR), which may correspond with the maximum, among all the weighting factors, of the minimum weighted average of the local SAR, given the VOPs and a fixed mitigation error as follows:
such that
and wv≧0. Further details of the iterative procedure are set forth in connection with the example of
Turning now to
At the outset, in act 502, the maximum eigenvalues of the absorption sensitivity matrices, Sv,10g, are calculated for all the voxels in the model. The voxels may then be reordered in act 504 based on the maximum eigenvalues in a descending order. Selection of the overestimation factor ∈ may then occur in act 506 to tune the complexity or extent of the compression, thereby to trading off the number of voxels in the VOP subset (Vsub) and the tightness of the bound. The selection may alternatively occur at any time before the above-described calculation and ordering acts.
The iterative procedure begins in act 508 with the addition of the first voxel in the model to the VOP subset Vsub. Each successive voxel is then checked in a decision block 510 that determines whether the absorption sensitivity of the voxel is upper-bounded by previously determined VOPs in Vsub. If not upper-bounded, then the voxel is designated as another VOP in act 512 and added to Vsub. If the voxel is upper-bounded, then control passes to another decision block 514 that determines whether all of the voxels in the model have been considered. If not, control returns to the decision block 510 for evaluation of the next voxel. Otherwise, the model compression procedure is complete.
A decision block 520 determines whether all the eigenvalues of the difference matrix are nonnegative, in which case the voxel is upper-bounded by previously determined VOPs. An indication to that effect may be stored in act 522. Otherwise, control passes to act 524, where the eigenvector, b, of P corresponding to the minimum eigenvalue is calculated. A decision block 526 then determines whether, by vector b, the local SAR at the voxel v is greater than the maximum local SAR over the VOPs plus the overestimating term, i.e.
the voxel v cannot be upper-bounded, and the voxel is designated as a VOP in act 528. If not, then control passes to another decision block 530 in which the number of iterations is checked against a maximum. If not, then the coefficients, cw,v, are updated to make b′Pb nonnegative in act 532, and control returns to the decision block 520. If the number of iterations exceeds a pre-selected maximum number of iterations, the voxel is designated a VOP and added to Vsub as shown.
After performing the iterative procedures of
The outer iterative procedure begins in act 602, in which a pulse is found that minimizes the weighted average with the current weighting factors. For example, the RF pulses may be designed with the second order regularization term b′Sb. The act 602 may also include an analysis of the contributions of each VOP to the weighted average to determine a direction to change each weighting factor that increases the minimized weighted average after each iteration of the iterative procedure. For example, the weighting factor of a VOP that has a large contribution may be increased to such an extent that, in an ideal case, its weighting factor approaches 1 (and all other weighting factors thus approach 0).
A decision block 604 may then determine whether the weighted average of the local SAR levels over the VOPs increased. If yes, then control passes to another decision block 606 that checks to see whether a maximum number of iterations has been reached for the inner iterative procedure. If not, then the weighting factors are updated in act 608 in accordance with the directions resulting from the analysis in act 602, and another pulse is designed in act 602. If the weighted average does not increase, then control passes to act 610 to calculate the peak local SAR over the VOPs. If the peak local SAR decreased, then control passes to another decision block 614 to determine whether a maximum number of iterations has been reached for the outer iterative procedure. If not, then control returns to the act 602 for further pulse design via optimization of the weighting factors. Alternatively, control may return to the act 608 (or a similar block) to update the weighting factors, which may be useful to avoid a local minima and/or maxima. Once the peak local SAR does not increase, then the pulse design procedure is complete.
The weighting factors may thus be updated through a gradient descent method. In some embodiments of the pulse design procedure, each iteration includes (1) calculating the local SAR in Vsub deposited by bw(t), (2) predicting the direction of the weighting factors, wv, that increases the weighted average of the local SAR, and (3) updating the weighting factors, wv, to the direction with only a small change in each iterative step. The iterative process is stopped if the weighted average of the local SAR, SARw, does not increase or until it reaches the preselected number of iterations.
The above-described iterative procedure may be used in some embodiments to estimate the global maxima, PUPiL SAR, by searching over many weighting factors. After determining a lower bound, the procedure may design pTx RF pulses whose peak local SAR over the VOPs approaches the lower bound. In determining PUPiL SAR, the maximum lower bound is found. However, the above-described procedure minimizes the peak local SAR over the VOPs. While, in some cases, only the RF pulses, bw(t), that minimize the weighted average of the local SAR are considered, the RF pulse that has the minimum peak local SAR over the VOPs is determined as follows:
In
Various embodiments described herein can be used alone or in combination with one another. The foregoing detailed description has described only a few of the many possible implementations of the present invention. For this reason, this detailed description is intended by way of illustration, and not by way of limitation.
This application claims the benefit of U.S. provisional application entitled “Local SAR in Parallel Transmission Pulse Design,” filed Sep. 1, 2011, and assigned Ser. No. 61/530,266, the entire disclosure of which is hereby expressly incorporated by reference.
This invention was made with government support under Research Grant Program (R01) Contract Nos. EB007942 and EB006847 awarded by the National Institutes of Health (NIH). The government has certain rights in the invention.
Number | Date | Country | |
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61530266 | Sep 2011 | US |