WO2017132182A1 - Systems and methods for joint reconstruction of quantitative t2 and adc maps - Google Patents

Abstract

Systems and methods for generating apparent diffusion coefficient maps and T2 maps of an object is provided. The method includes (a) performing a pulse sequence, using a magnetic resonance imaging (MRI) system, including a plurality of motion encoding gradients to acquire diffusion weighted imaging (DWI) data at a given echo time (TE) and, (b) during step (a), varying the TE to acquire a combined dataset. The method also includes (c) reconstructing both a T2 map of the object and an apparent diffusion coefficient (ADC) map of the object from the combined dataset.

Description

SYSTEMS AND METHODS FOR JOINT RECONSTRUCTION OF

QUANTITATIVE T2 AND ADC MAPS

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is based on, claims the benefit of, and incorporates herein by reference in its entirety, U.S. Provisional Patent Application Serial No. 62/288,807, filed on January 29, 2016, and entitled "SIMULTANEOUS ESTIMATION OF T2 RELAXATION AND APPARENT DIFFUSION COEFFICIENT MAPS WITH MAGNETIC RESONANCE IMAGING."

BACKGROUND

[0002] The present disclosure relates to systems and methods for medical imaging and, more particularly, to system sand methods for efficiently acquiring data for and producing reports indicating quantitative measures of parameters from a subject.

[0003] When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field BQ), the individual magnetic moments of the nuclear spins in the tissue tend to align with this polarizing field. If they are not initially aligned precisely with the polarizing field, they will precess about the field at their characteristic Larmor frequency as a top precesses about the Earth's gravitational field if the top's spin axis is not initially aligned with the field. Usually the nuclear spins are the nuclei of hydrogen atoms, but NMR active nuclei of other elements are occasionally used. At equilibrium, the individual magnetic moments of all the nuclei combine to produce a net magnetic moment M_z in the direction of the polarizing field, but the randomly oriented magnetic components in the perpendicular, or transverse, plane (x-y plane) cancel one another. If, however, the substance, or tissue, is subjected to a magnetic field (excitation field B-^; also referred to as the radiofrequency (RF) field) which is in the x-y plane and which oscillates near the Larmor frequency, the net aligned moment, M_z, may be rotated, or "tipped", into the x-y plane to produce a net transverse magnetic moment M_t, which precesses (rotates about the

BQ field direction) in the x-y plane at the Larmor frequency. The typically brief application of the B-j_^ field that accomplishes the tipping of the nuclear spins is generally known as an radiofrequency (RF) pulse. The practical value of this phenomenon resides in the signal that is emitted by the excited spins after the excitation field B-^ is terminated. There is a wide variety of measurement pulse sequences ("sequences") in which this nuclear magnetic resonance ("NMR") phenomenon is exploited.

[0004] When utilizing these signals to produce images, the phenomenon is generally known as magnetic resonance imaging ("MRI"), and magnetic field gradients (G_x, Gy, and

G_z) of the polarizing field BQ are employed. Typically, the region to be imaged experiences a sequence of measurement cycles in which these gradients vary according to the particular localization method being used. The emitted MRI signals are detected using a receiver coil. The MRI signals are then digitized and processed to reconstruct the image using one of many well-known reconstruction techniques.

[0005] Diffusion-weighted imaging ("DWI") is an MRI method that uses motion sensitizing magnetic field gradients to elicit contrast related to the diffusion of water or other fluid molecules. By applying the diffusion gradients in selected directions during the MRI measurement cycle, diffusion weighted image data can be acquired from which apparent diffusion coefficients or apparent diffusion tensors can be obtained for each voxel location in the reconstructed image. This information can be particularly useful in a variety of different clinical applications.

[0006] For example, fluid molecules diffuse more readily along the direction of the axonal fiber bundle in the brain, as compared with directions partially or totally orthogonal to the fibers. Hence, the directionality and anisotropy of the apparent diffusion coefficients (or tensor) tend to correlate with the direction of the axonal fibers and fiber bundles. This information of the location of fiber bundles in the brain can be used to perform surgical planning and a variety of other clinical applications.

[0007] An overall measure of diffusivity, referred to as the apparent diffusion coefficient (ADC) is routinely used in neurological MRI to identify acute stroke and infarcts in the brain. Because a hallmark of acute stroke is an immediate decrease in ADC (which occurs earlier than changes in other imaging biomarkers) followed by an increase in ADC (above baseline) in the chronically infarcted brain, DWI has become the gold standard for evaluating strokes.

[0008] Quantitative T2 mapping utilizes differences in the temporal decay of the MRI signal in different tissues to provide information about tissue composition. For example, myocardial tissue can be characterized using T2 mapping to evaluate the presence of myocardial edema or iron overload.

[0009] Thus, T2 mapping and ADC mapping are both used to evaluate microstructural environments and can provide insight into the presence and extent of several pathologies. Unfortunately, acquiring both sets of data is time consuming and exacerbated by the fact that each individual set of data can require extensive acquisition times. That is, currently, T2 and ADC mapping can be acquired only by using separate MRI pulse sequences. Furthermore, DWI acquisitions can be particularly time consuming as the motion-encoding gradients are cycled. Due to inherently low SNR, DWI acquisition usually entails multiple repetitions and averaging.

[0010] Thus, it would be desirable to have systems and methods that are capable of delivering the imaging information needed to make clinical decisions, but without having to invest in extensive acquisition times and risk potential mis-registration between repeated acquisitions.

SUMMARY

[0011] The present disclosure provides systems and methods that overcome the aforementioned drawbacks by exploiting a dependence of ADC and T2 information of spin- echo diffusion weighted imaging (SE-DWI) to condense data acquisition for ADC mapping and T2 mapping, and/or other tensor-derived metrics, into a common acquisition that does not require extended scan times. Further, the ADC maps and T2 maps are inherently co- registered and therefore well suited for applications such as surgical planning that requiring high spatial correlation. This is not the case in traditional ADC map/T2 map acquisitions because two separate acquisitions are performed and even if all acquisition details are matched between the two, the patient may have moved during or between the two acquisitions.

[0012] In accordance with one aspect of the disclosure, a method is provided for generating apparent diffusion coefficient maps and T2 maps of a subject. The method includes (a) performing a pulse sequence, using a magnetic resonance imaging (MRI) system, including a plurality of motion encoding gradients to acquire diffusion weighted imaging (DWI) data at a given echo time (TE) and, (b) during step (a), varying the TE to acquire a combined dataset. The method also includes (c) reconstructing both a T2 map of the object and an apparent diffusion coefficient (ADC) map of the object from the combined dataset.

[0013] In accordance with another aspect of the disclosure, a magnetic resonance imaging (MRI) system is provided that includes a magnet system configured to generate a polarizing magnetic field about at least a portion of a subject arranged in the MRI system, a plurality of gradient coils configured to apply a gradient field to the polarizing magnetic field, and a radio frequency (RF) system configured to apply an excitation field to the subject and acquire MR image data. The system also includes a computer system programmed to control the plurality of gradient coils and the RF system to perform a pulse sequence by controlling the plurality of gradient coils to apply a plurality of motion encoding gradients while controlling the RF system to acquire diffusion weighted imaging (DWI) data. The computer is further programmed to control the plurality of gradient coils and the RF system to vary at least one of an echo time (TE) or values of the plurality of motion encoding gradients during the pulse sequence to acquire a combined dataset and reconstruct both a T2 map of the object and an apparent diffusion coefficient (ADC) map of the object from the combined dataset.

[0014] In accordance with yet another aspect of the disclosure, a method is provided for generating multiple tensor-derived maps of an object using a common pulse sequence. The method includes of (a) performing a pulse sequence, using a magnetic resonance imaging (MRI) system, including a plurality of motion encoding gradients to acquire diffusion weighted imaging (DWI) data at a given echo time (TE) and (b) during step (a) varying the TE to acquire a combined dataset. The method also includes (c) reconstructing multiple tensor-derived metrics, including at least two of a T2 map of the object, an apparent diffusion coefficient (ADC) map of the object, and a fractional anisotropy map, from the combined dataset.

[0015] The foregoing and other aspects and advantages of the invention will appear from the following description. In the description, reference is made to the accompanying drawings that form a part hereof, and in which there is shown by way of illustration a preferred embodiment of the invention. Such embodiment does not necessarily represent the full scope of the invention, however, and reference is made therefore to the claims and herein for interpreting the scope of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Fig. 1 is a block diagram of an example of a magnetic resonance imaging

("MRI") system configured in accordance with the present disclosure.

[0017] Fig. 2 is a flowchart setting forth the steps of an example pulse sequence in accordance with the present disclosure.

[0018] Fig. 3 is a flowchart setting forth the steps of an example method for acquiring ADC mapping data and T2 mapping data in a common scan acquisition.

DETAILED DESCRIPTION

[0019] Referring particularly now to Fig. 1, an example of a magnetic resonance imaging ("MRI") system 100 that can implement the methods described here is illustrated. The MRI system 100 includes an operator workstation 102 that may include a display 104, one or more input devices 106 (e.g., a keyboard, a mouse), and a processor 108. The processor 108 may include a commercially available programmable machine running a commercially available operating system. The operator workstation 102 provides an operator interface that facilitates entering scan parameters into the MRI system 100. The operator workstation 102 may be coupled to different servers, including, for example, a pulse sequence server 110, a data acquisition server 112, a data processing server 114, and a data store server 116. The operator workstation 102 and the servers 110, 112, 114, and 116 may be connected via a communication system 140, which may include wired or wireless network connections.

[0020] The pulse sequence server 110 functions in response to instructions provided by the operator workstation 102 to operate a gradient system 118 and a radiofrequency ("RF") system 120. Gradient waveforms for performing a prescribed scan are produced and applied to the gradient system 118, which then excites gradient coils in a gradient coil assembly 122 to produce the magnetic field gradients G_x, G_y, and G_z that are used for spatially encoding magnetic resonance signals. The gradient coil assembly 122 forms part of a magnet assembly 124 that includes a polarizing magnet 126 and a whole- body RF coil 128.

[0021] RF waveforms are applied by the RF system 120 to the RF coil 128, or a separate local coil to perform the prescribed magnetic resonance pulse sequence. Responsive magnetic resonance signals detected by the RF coil 128, or a separate local coil, are received by the RF system 120. The responsive magnetic resonance signals may be amplified, demodulated, filtered, and digitized under direction of commands produced by the pulse sequence server 110. The RF system 120 includes an RF transmitter for producing a wide variety of RF pulses used in MRI pulse sequences. The RF transmitter is responsive to the prescribed scan and direction from the pulse sequence server 110 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 128 or to one or more local coils or coil arrays.

[0022] The RF system 120 also includes one or more RF receiver channels. An RF receiver channel includes an RF preamplifier that amplifies the magnetic resonance signal received by the coil 128 to which it is connected, and a detector that detects and digitizes the I and Q quadrature components of the received magnetic resonance signal. The magnitude of the received magnetic resonance signal may, therefore, be determined at a sampled point by the square root of the sum of the squares of the I and Q components:

[0023] and the phase of the received magnetic resonance signal may also be determined accordin to the following relationship:

[0024] The pulse sequence server 110 may receive patient data from a physiological acquisition controller 130. By way of example, the physiological acquisition controller 130 may receive signals from a number of different sensors connected to the patient, including electrocardiograph ("ECG") signals from electrodes, or respiratory signals from a respiratory bellows or other respiratory monitoring devices. These signals may be used by the pulse sequence server 110 to synchronize, or "gate," the performance of the scan with the subject's heart beat or respiration.

[0025] The pulse sequence server 110 may also connect to a scan room interface circuit 132 that receives signals from various sensors associated with the condition of the patient and the magnet system. Through the scan room interface circuit 132, a patient positioning system 134 can receive commands to move the patient to desired positions during the scan.

[0026] The digitized magnetic resonance signal samples produced by the RF system

120 are received by the data acquisition server 112. The data acquisition server 112 operates in response to instructions downloaded from the operator workstation 102 to receive the real-time magnetic resonance data and provide buffer storage, so that data is not lost by data overrun. In some scans, the data acquisition server 112 passes the acquired magnetic resonance data to the data processing server 114. In scans that require information derived from acquired magnetic resonance data to control the further performance of the scan, the data acquisition server 112 may be programmed to produce such information and convey it to the pulse sequence server 110. For example, during pre- scans, magnetic resonance data may be acquired and used to calibrate the pulse sequence performed by the pulse sequence server 110. As another example, navigator signals may be acquired and used to adjust the operating parameters of the RF system 120 or the gradient system 118, or to control the view order in which k-space is sampled. In still another example, the data acquisition server 112 may also process magnetic resonance signals used to detect the arrival of a contrast agent in a magnetic resonance angiography ("MRA") scan. For example, the data acquisition server 112 may acquire magnetic resonance data and processes it in real-time to produce information that is used to control the scan.

[0027] The data processing server 114 receives magnetic resonance data from the data acquisition server 112 and processes the magnetic resonance data in accordance with instructions provided by the operator workstation 102. Such processing may include, for example, reconstructing two-dimensional or three-dimensional images by performing a Fourier transformation of raw k-space data, performing other image reconstruction algorithms (e.g., iterative or backprojection reconstruction algorithms), applying filters to raw k-space data or to reconstructed images, generating functional magnetic resonance images, or calculating motion or flow images. [0028] Images reconstructed by the data processing server 114 are conveyed back to the operator workstation 102 for storage. Real-time images may be stored in a data base memory cache, from which they may be output to operator display 102 or a display 136. Batch mode images or selected real time images may be stored in a host database on disc storage 138. When such images have been reconstructed and transferred to storage, the data processing server 114 may notify the data store server 116 on the operator workstation 102. The operator workstation 102 may be used by an operator to archive the images, produce films, or send the images via a network to other facilities.

[0029] The MRI system 100 may also include one or more networked workstations

142. For example, a networked workstation 142 may include a display 144, one or more input devices 146 (e.g., a keyboard, a mouse), and a processor 148. The networked workstation 142 may be located within the same facility as the operator workstation 102, or in a different facility, such as a different healthcare institution or clinic.

[0030] The networked workstation 142 may gain remote access to the data processing server 114 or data store server 116 via the communication system 140. Accordingly, multiple networked workstations 142 may have access to the data processing server 114 and the data store server 116. In this manner, magnetic resonance data, reconstructed images, or other data may be exchanged between the data processing server 114 or the data store server 116 and the networked workstations 142, such that the data or images may be remotely processed by a networked workstation 142.

[0031] As described above, spin-echo ("SE") pulse sequences are advantageous for performing diffusion weighted imaging ("DWI") studies. Portions of the following description of a SE pulse sequence will refer to echo planar imaging ("EPI"). However, it is noted at the outset that this is for purposes of providing an example only. That is, one of ordinary skill in the art will readily recognize that the present systems and methods are applicable to other pulse sequences in addition to SE-EPI. For example, so-called twice refocused SE and so-called diffusion prepared sequences are two such non-limiting examples.

[0032] The present disclosure recognizes that SE-DWI signals are governed by the tissue's apparent diffusion coefficient (ADC) and T2 relaxation time, as well as the sequence's diffusion encoding b-value [b] and echo time (TE). The signal model can be given by:

_TE

S{b E) = S,e-^hDe ^T> (3); where So is the initial SE signal and D is the diffusivity along a particular direction. The ADC is the measured average diffusivity across a range (>3) of sampled directions. As will be described, the present disclosure recognizes that acquisition of several signals with varying TEs and b-values permits joint reconstruction of both ADC and T2 maps, and/or other tensor-derived metrics, such as fractional anisotropy and the like.

[0033] Specifically, referring to Fig. 2, an example of one process 200 for data acquisition and reconstruction of both ADC maps and T2-weighted images. The process 200 beings by performing a diffusion weighted acquisition at process block 202. By way of one non-limiting example and referring to Fig. 3, a spin-echo, echo planar imaging ("EPI") pulse sequence 300 may be used for acquiring image data with the MRI system 100 illustrated in Fig. 1. While this exemplary pulse sequence is illustrated here, it will be appreciated by those skilled in the art that other pulse sequences can be employed.

[0034] As illustrated, the spin-echo EPI sequence 300 begins with an RF excitation pulse 302 that is played out in the presence of a slice selective gradient 304. To mitigate signal losses resulting from phase dispersions produced by the slice selective gradient 304, a rephasing lobe 306 is applied after the slice selective gradient 304. Next, a rephasing RF pulse 308 is applied in the presence of another slice selective gradient 310. The slice- selective gradient 310 is further bridged by a first and second diffusion weighting gradient, 316 and 318, respectively. Though two lobes for the diffusion weighting gradients are illustrated, this is non-limiting. Other numbers of lobes can be used. These diffusion weighting gradients 316 and 318, while shown on a separate "diffusion weighting" gradient axis, are in fact produced through the application of diffusion weighting gradient lobes along each of the slice-encoding, phase-encoding, and frequency-encoding gradient directions. By changing the amplitudes and other characteristics of the diffusion weighting gradient lobes, the acquired echo signals can be weighted for diffusion occurring along any arbitrary direction. For example, when the diffusion weighting gradients 316 and 318 are composed solely of gradient lobes applied along the G_z gradient axis, then the acquired echo signals will be weighted for diffusion occurring along the z-direction. For another example, however, if the diffusion weighting gradients 316 and 318 are composed of gradient lobes applied along both the G_x and G gradient axes, then the echo signals will be weighted for diffusion occurring in the x-y plane along a direction defined by the relative amplitudes of the gradient lobes. In this way, a desired number of directions of diffusion weighted data may be acquired. To generate ADC maps, images weighted by diffusion weighting gradients 316 and 318 may be normalized by non-diffusion weighted images without gradients 316 and 318 being played. For these acquisitions, additional crusher gradients 312 and 314 may be played out before and after the slice-selective gradient 310 and the refocusing pulse in order to substantially reduce unwanted phase dispersions.

[0035] Data is acquired by sampling a series of diffusion weighted spin echo signals in the presence of an alternating readout gradient 320. The alternating readout gradient is preceded by the application of a pre-winding gradient 322 that acts to move the first sampling point along the frequency-encoding, or readout, direction by a distance Ak_x in k- space. Spatial encoding of the echo signals along a phase-encoding direction may be performed by a series of phase encoding gradient "blips" 324, which are each played out in between the successive signals readouts such that each echo signal is separately phase encoded. The phase encoding gradient blips 324 may be preceded by the application of a pre-winding gradient 326 that acts to move the first sampling point along the phase- encoding direction a distance Ak in k-space. Together, the pre-winding gradients 322 and 326 serve to begin the sampling of k-space at a defined k-space location

[0036] Referring again to Fig. 2, to increase the effective TE resolution of the estimation, one has the option at decision block 204 to vary the TE between each diffusion encoding direction and magnitude. If so preferred, between a given diffusion encoding direction and magnitude, the TE can be adjusted at process block 206 and the DWI acquisition continues at process block 202. That is, unlike in the framework of conventional ADC estimation, each diffusion-weighted image can be acquired at a different TE. It is noted that the entire DWI acquisition does not need to be re-acquired with a new TE. Rather, the above-described process can acquire arbitrary combinations of b-value, direction, and TE. However, if advantageous, the entire DWI acquisition may be repeated for each new TE.

[0037] Non-diffusion-weighted images can be acquired with shorter echo times than permitted by long diffusion encoding gradients in order to adequately sample the signal decay of short-T2 species. The result is data that, as will be described, includes the necessary information to produce ADC maps and T2-weighted images. Thus, the data can be referred to as a combined ADC and T2 dataset.

[0038] For example, if one repeats 3-direction diffusion weighted acquisitions with varying TE, the resultant dataset will contain enough information to simultaneously solve for T2 and ADC within each voxel using equation (3). Furthermore, equation (3) can be simplified to:

TE

\n(S) = HS₀) - bD -— (4).

[0039] Equation 4 can be solved in a variety of ways, including linear or non-linear methods. In one non-limiting example, by performing multiple acquisitions (S_n), each with its own weighting (b_n, TE_n), an over-determined system of linear equations can be created as:

[0040] Thus, at process block 208, reconstruction is begun by assembling the acquired data into a system of linear equations. At process block 210, the combined ADC and T2 datasets can be jointly reconstructed into ADC maps and T2 maps, for example, via matrix inversion using equation (5). Thus, at process block 212, the ADC maps and T2- weighted images can be displayed. Advantageously, the ADC maps and T2 maps can be displayed in a registered manner without a registration process because the data was jointly acquired. Of course, the images can be displayed separately or together in a non- registered manner. [0041] Thus, a system and method are provided to perform T2 and ADC mapping using a single MRI pulse sequence. That is, data for the reconstruction of both maps is acquired in a common acquisition using the above-described pulse sequence. This stands in contrast to the conventional need to perform two separate and distinct acquisitions with respective pulse sequences. In this manner, the above-described process may be referred to as enabling the ability to acquire the data to produce T2 and ADC maps simultaneously. Accordingly, scan time can be reduced compared to traditional processes that utilize two, distinct pulse sequences to acquire the T2 and ADC data. Additionally or alternatively, the signal-to-noise can be improved by extending the duration of the single pulse sequence. As was demonstrated, ADC maps can be created that are substantially free of T2 weighting.

[0042] EXAMPLES

[0043] In one non-limiting example, single-shot SE-DWI EPI images were acquired using a 3.0 T scanner (Siemens Prisma) and a polyethylene glycol (PEG) and gadolinium phantom, which contained a range of T2 and ADC values known nominally from chemical composition using 1.0x1.0x5.0mm resolution, GRAPPA factor 2, 5/8 partial Fourier, bandwidth=1000 Hz/Pixel, TR=3800ms. The acquisitions spanned a range of ten TEs (TE=35-100ms) each acquired four times and also included DWI (b=1000 s/mm2) along three directions at four TEs (TE=60, 65, 70, 75ms) each acquired ten times. Whole volume brain images were also acquired using the same protocol in healthy volunteers (N=5) subsequent to IRB approved consent.

[0044] Three subsets of the acquired images with matched acquisition durations were reconstructed. Jointly reconstructed T2 and ADC maps were generated using weighted linear least-squares from 8 TEs plus DWI spanning 4 TEs (2 averages each, scan time: 2.5min) and compared to reference T2 maps from all 10 TEs (4 averages, scan time: 2.5min) and reference ADC maps from DWI (TE=60ms, 10 averages, scan time: 2.5min). The bias±95% confidence interval (CI) of joint T2 and ADC reconstructions were calculated by voxel-wise subtraction from the reference maps. T2 and ADC estimates in two ROIs in the PEG phantom (PEG1 and PEG2) and in white-matter (WM) and grey-matter (GM) ROIs were compared using a paired t-test. [0045] T2 and ADC values for the joint and reference reconstructions were both in agreement with the nominal T2 and ADC values in the PEG phantom, as illustrated in Table 1.

TABLE 1

[0046] Voxel-wise comparison of the pooled joint T2 and ADC data to the reference

T2 and ADC data showed that joint reconstruction did not introduce substantial bias: T2- bias=0.5±37ms and ADC-bias=0.01±0.8 xl0-3mm2/s. There was no significant difference between the median T2 or ADC values reported in WM or GM ROIs (Figure 2) by the joint and reference reconstructions (p>0.6). Jointly reconstructed ADC and T2 maps from an in vivo acquisition demonstrated excellent qualitative agreement between the methods.

[0047] In the proposed method, the TE is varied with each repetition in place of averaging. When coupled with the acquisition of non-DWI short TE images, this permits the reconstruction of a quantitative T2 map in addition to the ADC map with no increase in scan time compared to independently acquiring each.

[0048] Thus, joint acquisition and estimation of T2 and ADC maps was demonstrated to be feasible in the brain. Furthermore, the results shows that no loss in accuracy was created compared to independent mapping protocols that require twice the scan time.

[0049] In another non-limiting example, Bloch equation simulations were used to generate signals for a broad range of T2 (20-70ms) and ADC (0.1-2.4xl0-3mm2/s) using 10 TEs (17-100 ms) and b=500 s/mm2 (TE=60- 68ms) along 3 directions. Complex Gaussian noise was added to each signal such that the signal to noise ratio (SNR) of the minimum TE, b=0 signal matched that of acquired data (SNR = 38).

[0050] Reconstructions were performed using linear least-squares on a subset of the simulated data (TE=17, 20, 30, 50, 70, 100ms) to reflect a feasible in vivo acquisition (scan time: 18s). Mapping accuracy and precision were determined by the bias and standard deviation (SD) of T2 and ADC compared to programmed values. Images were acquired on a 3.0 T Siemens Skyra system in an ex vivo infarcted porcine heart using single-shot SE EPI with TEs and b-values to match simulated parameters. T2 and ADC maps were jointly reconstructed using linear least-squares from 6 TEs plus 3 DWI sets and compared to: 1) Best-Available T2-maps from all 10 TEs; 2) Best-Available ADC maps from DWI (3 directions, 6 averages); 3) Independent T2 maps from 6 TEs; and 4) Independent ADC maps from 3 DWI averages.

[0051] Joint reconstruction of simulated data recovered T2 and ADC values with bias<l% and SD<10% for a broad range of tissues and even lower for healthy and infarcted myocardium, as shown in Table 2.

TABLE 2

[0052] Reconstructed ADC and T2 maps from the ex vivo acquisition showed that the joint estimation maps were closer to the Best-Available T2 or ADC maps than the Independent T2 or ADC maps alone (Joint Estimation Maps: T2-bias=-0.5 %, ADC-bais=- 4.8%; Independent Maps: T2-bias=-4.1%, ADC-bias=-14.1%).

[0053] Thus, joint acquisition and estimation of T2 and ADC maps was shown to be feasible in a breath hold and can improve quantitative accuracy and precision compared to independent T2 or ADC mapping. DWI acquisitions typically require multiple averages to improve SNR. Here, varying TE takes the place of signal averaging and permits the reconstruction of a perfectly registered T2 map.

[0054] The present invention has been described in terms of one or more preferred embodiments, and it should be appreciated that many equivalents, alternatives, variations, and modifications, aside from those expressly stated, are possible and within the scope of the invention.

Claims

1. A method for generating apparent diffusion coefficient maps and T2 maps of an object, the method including steps comprising:

(a) performing a pulse sequence, using a magnetic resonance imaging (MRI) system, including a plurality of motion encoding gradients to acquire diffusion weighted imaging (DWI) data at a given echo time (TE);

(b) during step (a) varying the TE to acquire a combined dataset; and

(c) reconstructing both a T2 map of the object and an apparent diffusion coefficient (ADC) map of the object from the combined dataset.

2. The method of claim 1, wherein step (b) includes repeating step (a) at least three times, each repetition with a different TE or value of the motion encoding gradients.

3. The method of claim 1, wherein the pulse sequence includes a single shot spin echo pulse sequence.

4. The method of claim 1, wherein the pulse sequence includes a diffusion weighted echo planar imaging (EPI) pulse sequence.

5. The method of claim 1, wherein the pulse sequence further includes varying the TE between each diffusion encoding direction.

6. The method of claim 1, wherein step (c) includes simultaneously solving for T2 value and ADC for each voxel in an image of the object.

7. The method of claim 1, wherein step (c) includes using a signal model given by:

_TE

S(b,TE) = S₀e-^bDe^~T> ; where b is a value of the motion encoding gradients used by the pulse sequence, So is an initial value of a spin echo signal from the object in a given voxel, D is an ADC value in a given voxel, and T2 is the T2 value in a given voxel.

8. The method of claim 1, wherein step (c) includes solving a system of linear equations given by:

where Si is a signal received to acquire DWI data during a first acquisition of step (a), S₂ is a signal received to acquire DWI data during a second acquisition of step (a), S_n is a signal received to acquire DWI data during an nth acquisition of step (a), TEi is a TE used in the pulse sequence during the first acquisition of step (a), TE2 is a TE used in the pulse sequence during the second acquisition of step (a) , TE_n is a TE used in the pulse sequence during the nth acquisition of step (a), bi is a value of the motion encoding gradients used in the pulse sequence during the first acquisition of step (a) , b₂ is a value of the motion encoding gradients used in the pulse sequence during the second acquisition of step (a) , and bn is a value of the motion encoding gradients used in the pulse sequence during the nth acquisition of step (a) .

9. The method of claim 1, further comprising (d) displaying the T2-weighted map of the object and the ADC map of the object registered together.

10. The method of claim 1, wherein step (c) includes reconstructing both a T2- weighted map of the object and the ADC map of the object simultaneously.

11. A magnetic resonance imaging (MRI) system comprising:

a magnet system configured to generate a polarizing magnetic field about at least a portion of an object arranged in the MRI system; a plurality of gradient coils configured to apply a gradient field to the polarizing magnetic field;

a radio frequency (RF) system configured to apply an excitation field to the object and acquire MR image data;

a computer system programmed to:

control the plurality of gradient coils and the RF system to perform a pulse sequence by controlling the plurality of gradient coils to apply a plurality of motion encoding gradients while controlling the RF system to acquire diffusion weighted imaging (DWI) data;

control the plurality of gradient coils and the RF system to vary at least one of an echo time (TE) or values of the plurality of motion encoding gradients during the pulse sequence to acquire a combined dataset; and

reconstruct both a T2 map of the object and an apparent diffusion coefficient (ADC) map of the object from the combined dataset.

12. The system of claim 11, wherein the computer system is further

programmed to repeat the pulse sequence at least three times, each repetition with a different TE or value of the motion encoding gradients.

13. The system of claim 11, wherein the pulse sequence includes a single shot spin echo pulse sequence.

14. The system of claim 11, wherein the pulse sequence includes a diffusion weighted spin echo pulse sequence.

15. The system of claim 11, wherein the computer system is further

programmed to control the RF system to vary the TE between each diffusion encoding direction.

16. The system of claim 11, wherein the computer system is further programmed to simultaneously solve for T2 value and ADC for each voxel in an image of the object.

17. The system of claim 11, wherein the computer system is further

programmed to use a signal model to reconstruct both T2-weighted images of the object and an ADC map, wherein the signal model is given by:

_TE

S(b,TE) = S₀e-^bDe^{~ T>} ;

where b is a value of the motion encoding gradients used by the pulse sequence, So is an initial value of a spin echo signal from the object in a given voxel, and D is an ADC value in a given voxel.

18. The system of claim 11, wherein the computer system is further

programmed to use a signal model to reconstruct both a T2 map of the object and an ADC map by solving a system of linear equations given by:

where Si is a signal received to acquire DWI data during a first acquisition of step (a), S₂ is a signal received to acquire DWI data during a second acquisition of step (a), S_n is a signal received to acquire DWI data during an nth acquisition of step (a), TEi is a TE used in the pulse sequence during the first acquisition of step (a), TE2 is a TE used in the pulse sequence during the second acquisition of step (a) , TEn is a TE used in the pulse sequence during the nth acquisition of step (a), bi is a value of the motion encoding gradients used in the pulse sequence during the first acquisition of step (a) , b₂ is a value of the motion encoding gradients used in the pulse sequence during the second acquisition of step (a) , and bn is a value of the motion encoding gradients used in the pulse sequence during the nth acquisition of step (a) .

19. The system of claim 11, further comprising a display and wherein the computer system is further programmed to cause the display to display the T2 map of the object and the ADC map of the object registered together.

20. The method of claim 11, wherein the computer system is further

programmed to reconstruct both the T2 map of the object and the ADC map of the object simultaneously.

21. The method of claim 11, wherein the computer system is further

programmed to reconstruct a fractional anisotropy map of the object from the combined dataset.

22. A method for generating multiple tensor-derived maps of an object using a common pulse sequence, the method including steps comprising:

(a) performing a pulse sequence, using a magnetic resonance imaging (MRI) system, including a plurality of motion encoding gradients to acquire diffusion weighted imaging (DWI) data at a given echo time (TE);

(b) during step (a) varying the TE to acquire a combined dataset; and

(c) reconstructing multiple tensor-derived metrics, including at least two of a T2 map of the object, an apparent diffusion coefficient (ADC) map of the object, and a fractional anisotropy map, from the combined dataset.