Abstract:
In a method and magnetic resonance (MR) system to create an MR magnitude image data set and a phase image data set of an examination subject, first echo signals in a first raw MR data set are detected after a first echo time TE 1  and at least second echo signals in at least one second raw MR data set are detected after a second echo time TE 2  that is longer than TE 1 , a magnitude image data set is generated on the basis of the first raw MR data set and the at least one second raw MR data set with averaging of the first and the at least one second raw MR data set, and the phase image data set is generated based on the phase information contained in the at least two raw MR data sets, with averaging of the respective phase information contained in the at least two raw MR data sets.

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The invention concerns: a method to create a magnetic resonance (MR) magnitude image data set and a phase image data set of an examination subject; an MR system and a computer-readable data storage medium for implementing such a method in a computerized processor. 
     2. Description of the Prior Art 
     One application field of magnetic resonance systems is the monitoring of medical procedures or treatments, for example thermotherapy, in which the temperature in tissue (for example tumor cells) is specifically increased, which ideally leads to cell death or (given a smaller temperature increase) allows the cells to become more sensitive to accompanying therapy measures such as chemotherapy or radiation therapy. A cooling is likewise possible in a treatment known as cryotherapy. Particularly in the case of ablation of tumor tissue (for example by means if high-intensity focused ultrasound), magnetic resonance systems are increasingly commonly used for 3-dimensional temperature imaging in order to show the temperatures prevailing in the treated area with optimally high precision and high time resolution during a treatment. Optical monitoring during the treatment should not only show the temperature of the heated tissue with time and spatial resolution, but also it should be possible to establish a relationship of the measured temperature images with the anatomy of the examined person. 
     One possibility to show temperature changes with the use of magnetic resonance tomography is the proton resonance frequency method that is based on the temperature dependency of the resonant frequency of protons. The phase information of the MR signal that is obtained from gradient echo signals is used in order to conclude a temperature change from the difference of two phase images. The temperature information can be shown with spatial resolution through the presentation of phase difference images. The relation between phase change and a temperature changes is as follows:
 
φ=γB 0 TEαT, or Δφ=γB 0 TEαT,  (1)
 
wherein B 0  is the basic magnetic field strength, γ is the gyromagnetic ratio, TE is the echo time, α is the temperature dependency of the resonance frequency (which is −0.01 ppm/° C.) and ΔT is the temperature change. Since the acquired MR data that are used to create the phase differences are plagued with noise, the temperature changes determined from them can be determined only with a limited precision. As can be recognized from the above equation, it would be advantageous to select the echo time to be as long as possible in order to induce an optimally large phase change; however, this extends the acquisition time and reduces the signal-to-noise ratio overall since the signal level overall decreases with increasing echo time due to the T 2 * decay of the magnetization.
 
     SUMMARY OF THE INVENTION 
     An object of the present invention is to provide a method in which phase information in an MR phase image can be determined with improved precision. 
     According to a first aspect of the invention, a method is provided to generate an MR magnitude image data set and a phase image data set of an examination subject, wherein first echo signals are acquired in a first raw data set after a first echo time TE and at least second echo signals are acquired in a second raw MR data set after a second echo time TE 2  that is longer than TE 1 . The magnitude image data set can subsequently be determined on the basis of the first raw MR data set and the at least one second raw MR data set with averaging of the first and the at least one second raw MR data set. Furthermore, the phase image data set is generated with the use of the phase information contained in the at least two raw MR data sets, and the respective phase information contained in the at least two raw MR data sets is averaged. Overall the signal-to-noise ratio in the phase information can be increased by the use of the phase information at the different echo times, which reduces errors in the phase information overall. 
     The phase information in the phase image data set contains typical information about a physical variable that is connected with the phase information through a formula. According to one embodiment of the invention, in the averaging of the phase information the averaging is implemented depending on a connection of the phase information with the physical variable in the formula. Since the phase images are typically not used as such in most applications (rather the phase information allows a conclusion of data such as temperature, flow or the like), a noise of the phase images for different echo times can indicate a varying strength of the signal-to-noise ratio of the corresponding physical variable. In this case a simple arithmetic averaging is no longer productive and a weighting must be conducted corresponding to the physical formula that underlies the specific phase information. This is explained in the following example. If an identical phase noise is assumed at the different echo times—for example a specific value of 2°—according to the above Equation (1) this means a smaller error given a large echo time than given a shorter echo time. Assuming that, for example, a phase difference of Δφ=11° corresponds to a temperature difference of ΔT=1° C. given TE=50 ms, the phase change per ° C. is only half as large (i.e. 5°) given a TE of approximately 25 ms. If a phase noise of 2° is assumed for both measurements, it is apparent that the 2° mean a larger error given the shorter time than given the longer echo time. By taking into account the formula which specifies the connection between phase information and physical variable, the correct averaging of the different phase information at the different echo times can result. 
     In the generation of the phase image data set, the averaging of the phase information contained in the at least two raw data sets ensues depending on noise of the respective phase information contained in the raw data set. The averaging in particular ensues depending on the variance of the respective phase information contained in the raw data set. Strictly speaking, this applies only for a noise with Gaussian distribution, which is not necessarily the case in every image data set. It is, however, a good approximation. 
     If this method to determine the phase information is applied to temperature imaging, the temperature difference is determined from the difference of two phase image data sets using a variance, under consideration of the averaging of the individual items of phase information depending on the connection between phase information and temperature difference. The spatially resolved temperature change is advantageously calculated as follows in a pixel image point i,j: 
                     Δ   ⁢           ⁢     T   ij       =         1       ∑     n   =   1     N     ⁢     TE   n         ⁢     (       ∑     n   =   1     N     ⁢       TE   n     ⁢   Δ   ⁢           ⁢     T   ij   n         )       =       k       ∑     n   =   1     N     ⁢     TE   n         ⁢     (       ∑     n   =   1     N     ⁢     Δ   ⁢           ⁢     φ   ij   n         )                 (   2   )               
wherein TE n  is the n-th echo of a multi-gradient echo sequence with at least N echoes per excitation pulse. For example, N can be between 3 and 5. ΔT ij   n  is the temperature difference, pixel i,j is calculated from the n-th echo and Δφ ij   n  is the associated phase difference.
 
     One problem in the determination of a physical variable based on a phase value can be that, after a phase transition given the limit of 2π, the result value can no longer be unambiguously associated. A specific phase value or, respectively, a specific phase difference φ 0  can correspond to φ=φ 0 +N·2π. The corresponding physical variable can no longer be unambiguously calculated with the equation. With regard to the temperature imaging this means that the temperature change ΔT can no longer be unambiguously determined. The phase information that is generated at the short first echo time can now be used. A value range of the phase information at other, greater echo times can be concluded from the value range of the phase values that are generated in the difference images at the first echo time, wherein it can be determined whether the additional value ranges exceed the value range of 2π and how often they exceed this value range of 2π. For example, if the value range of the phase values at a first echo time comprises the phase values from zero to 200°, the value range at the doubled echo time already comprises 400°, wherein this 400° is represented in the value range between zero and 360° and a phase transition consequently occurs. Starting from the value range at the short echo time, the value ranges at the longer echo times can now be determined and the phase transitions can be corrected and accounted for in that the number of phase transitions is calculated in order to correctly determine the underlying physical variable. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  schematically shows an MR system coupled with a therapy apparatus with which temperature information can be reliably determined. 
         FIG. 2  shows a portion of a multi-echo sequence with generation of a first echo and a second echo. 
         FIG. 3  is a flow diagram with the steps that are necessary to reliably determine the temperature difference. 
     
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     An MR system  10  with a basic field magnet  11  to generate a B 0  field and to generate a resulting magnetization in an examined person  12  (who is arranged on a bed  13  in the MR system) is shown  FIG. 1 . Furthermore, a device for application of focused ultrasound—what is known as an ultrasound applicator  14 —is shown with which the tissue of the examined person  12  can be specifically heated, for example to kill tumors. The MR system furthermore has a central control unit  15  with a sequence controller  16  in which the sequence of the radiated RF pulses and the magnetic field gradients is controlled. A gradient control unit  17  is provided to switch the gradients and an RF control unit  18  is provided to switch the RF pulses. An image computer  19  calculates an MR image from the MR signals detected with the aid of a coil (not shown), wherein the image computer can calculate a magnitude image or a phase image. How MR magnitudes or phase images can be generated via radiation of RF pulses and switching of gradients is familiar to those skilled in the art, such that a detailed description thereof is not necessary herein. Furthermore, a computer  20  can be provided that—as explained in the following—calculates phase information with improved signal-to-noise ratio and calculates a temperature difference from a phase difference, for example. It is likewise possible that the operations executed in the computer are implemented in the image computer  19 . Furthermore, a display unit  21  and an input unit  22  are provided. 
     A portion of a multi-echo gradient sequence with which temperature changes can be presented according to the invention (as described in the following) is shown in  FIG. 2 . After radiation of an RF pulse  23 , multiple bipolar gradients  24  and  25  are switched in the readout direction, which gradients  24  and  25  respectively lead to a gradient echo  26  and  27 . The first gradient echo  26  ensues at a first echo point in time TE 1 ; the second gradient echo ensues at a second echo point in time TE 2 . In the depiction of  FIG. 2 , only two gradient echoes are shown; however, multiple echoes—for example three to five echoes—can also be read out after an RF excitation pulse. The echo times can lie between 5 and 45 ms, for example. Temperature changes can be non-invasively shown with these gradient echo sequences since the temperature dependency of the chemical shift of the water protons is used. The magnetic field environment that is altered by the temperature-dependent chemical shift results in a temperature-dependent resonance frequency that can be shown in a temperature-dependent phase information at the point in time of the echo. The use of a gradient echo sequence is advantageous since this is sensitive to slight local magnetic field differences. The examined tissue accumulates a frequency-dependent (i.e. temperature-dependent) phase φ at the point in time of the echo TE. If the tissue is heated and the measurement is repeated at a later point in time, a per-pixel temperature change can be concluded according to the above Equation (1) by taking the per-pixel difference in the phase images. As mentioned above, a linear connection between phase change and  temperature change results according to the following relationships
 
Δφ˜TE·B 0 ·ΔT or
 
 k·Δφ=TE·ΔT   (3)
 
     The magnitude image generated with the aid of the imaging sequence from  FIG. 2  has an improved signal-to-noise ratio since the MR signals acquired at different points in time TE can be averaged. A simple example of this is the arithmetic averaging of the magnitude images M n  with 
     
       
         
           
             
               
                 
                   
                     M 
                     total 
                   
                   = 
                   
                     
                       ∑ 
                       
                         n 
                         = 
                         1 
                       
                       N 
                     
                     ⁢ 
                     
                       M 
                       n 
                     
                   
                 
               
               
                 
                   ( 
                   4 
                   ) 
                 
               
             
           
         
       
     
     This leads to an improvement of the signal-to-noise ratio with a factor of √N. This generally known effect is utilized if multiple images are acquired in succession with identical acquisition parameters in the MR imaging and the images are then added. In addition to the magnitude images, it is also possible to improve the phase image quality. However, since phase images are typically not used as such (but rather offer conclusions about functional data such as temperature, flow or the like), noise of the phase images for different echo times can indicate a signal-to-noise ratio of varying strength for the corresponding physical variables. In this case a simple arithmetic averaging is no longer productive and a weighting must be conducted corresponding to the physical relationship that underlies the specific variable. Such averagings are generally designated as weighted averages and take place according to the formula 
                     m   _     =       1       ∑     n   =   1     N     ⁢     W   n         ⁢     (       ∑     n   =   1     N     ⁢       W   n     ⁢     m   n         )               (   5   )               
wherein  m  is the averaged variable and W n  are the weighting factors for the N components m n  over that are averaged. According to the invention, it is now possible to use the connection between physical variable and phase information in the averaging of the phase images in order to implement the averaging.
 
     The optimal weighting in the averaging depends on the noise or, respectively, the underlying statistical distribution of the measurement variable over which it should be averaged. The averaging is frequently conducted in a form in which the noise of the different components is normalized. An optimal weighting of measurement variables whose noise has a Gaussian distribution is an averaging with regard to the variances V n  of the individual components. 
     For 
                 w   n     =     1     V   n         ,         
the following Equation results from the above Equation:
 
     
       
         
           
             
               
                 
                   
                     m 
                     _ 
                   
                   = 
                   
                     
                       1 
                       
                         
                           ∑ 
                           
                             n 
                             = 
                             1 
                           
                           N 
                         
                         ⁢ 
                         
                           1 
                           
                             V 
                             n 
                           
                         
                       
                     
                     ⁢ 
                     
                       ( 
                       
                         
                           ∑ 
                           
                             n 
                             = 
                             1 
                           
                           N 
                         
                         ⁢ 
                         
                           
                             1 
                             
                               V 
                               n 
                             
                           
                           ⁢ 
                           
                             m 
                             n 
                           
                         
                       
                       ) 
                     
                   
                 
               
               
                 
                   ( 
                   6 
                   ) 
                 
               
             
           
         
       
     
     It can be formally shown that a distribution with identical average value and minimal variance is created with this averaging. Since phase images only have a Gaussian distribution in the boundary case of a very low phase noise, other weighted averagings can also be necessary for an optimal phase image precision. Above Equations (1) through (3) describe the connection between phase change and temperature change. If the phase image data sets that are subtracted from one another are now acquired with larger, different echoes, and if an identical phase noise in all spatially resolved phase images φ ij   n  at the pixel position i,j is assumed, a suitably weighted averaging ensues as follows under consideration of the above Equations: 
                     Δ   ⁢           ⁢     T   ij       =         1       ∑     n   =   1     N     ⁢     TE   n         ⁢     (       ∑     n   =   1     N     ⁢       TE   n     ⁢   Δ   ⁢           ⁢     T   ij   n         )       =       k       ∑     n   =   1     N     ⁢     TE   n         ⁢     (       ∑     n   =   1     N     ⁢     Δ   ⁢           ⁢     φ   ij   n         )                 (   7   )               
wherein ΔT ij  the averaged, spatially resolved temperature at the pixel i,j, ΔT ij   n  corresponds to the spatially resolved temperature determined from the phase difference images of the respective echo n with the associated echo point in time TE n , and Δφ ij   n  is the associated phase difference.
 
     With the relationship for the variances for temperature V n   T  and phase V n   φ  of ΔT and Δφ using the above Equation (3), it then applies that 
     
       
         
           
             
               
                 
                   
                     V 
                     n 
                     T 
                   
                   = 
                   
                     
                       
                         k 
                         2 
                       
                       
                         TE 
                         n 
                         2 
                       
                     
                     ⁢ 
                     
                       V 
                       n 
                       φ 
                     
                   
                 
               
               
                 
                   ( 
                   8 
                   ) 
                 
               
             
           
         
       
     
     and the following results with the above Equation (7): 
     
       
         
           
             
               
                 
                   
                     Δ 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     
                       T 
                       ij 
                     
                   
                   = 
                   
                     
                       
                         1 
                         
                           
                             ∑ 
                             
                               n 
                               = 
                               1 
                             
                             N 
                           
                           ⁢ 
                           
                             
                               ( 
                               
                                 TE 
                                 n 
                               
                               ) 
                             
                             2 
                           
                         
                       
                       ⁢ 
                       
                         ( 
                         
                           
                             ∑ 
                             
                               n 
                               = 
                               1 
                             
                             N 
                           
                           ⁢ 
                           
                             
                               
                                 ( 
                                 
                                   TE 
                                   n 
                                 
                                 ) 
                               
                               2 
                             
                             ⁢ 
                             Δ 
                             ⁢ 
                             
                                 
                             
                             ⁢ 
                             
                               T 
                               ij 
                               n 
                             
                           
                         
                         ) 
                       
                     
                     = 
                     
                       
                         k 
                         
                           
                             ∑ 
                             
                               n 
                               = 
                               1 
                             
                             N 
                           
                           ⁢ 
                           
                             
                               ( 
                               
                                 TE 
                                 n 
                               
                               ) 
                             
                             2 
                           
                         
                       
                       ⁢ 
                       
                         ( 
                         
                           
                             ∑ 
                             
                               n 
                               = 
                               1 
                             
                             N 
                           
                           ⁢ 
                           
                             Δ 
                             ⁢ 
                             
                                 
                             
                             ⁢ 
                             
                               TE 
                               n 
                             
                             ⁢ 
                             
                               φ 
                               ij 
                               n 
                             
                           
                         
                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   9 
                   ) 
                 
               
             
           
         
       
     
     As is apparent from Equation (9), the temperature difference can be determined with the aid of the individual echo times and the phase differences belonging to the individual echo times. 
     If the resolution or bandwidth should be varied in addition to the echo sequence imaging parameters, corresponding weightings for these variables must likewise be taken into account. 
     The steps with which the temperature difference can be calculated as mentioned above are now summarized in  FIG. 3 . After creating a first phase image data set with N echoes in Step  31  and the creation of an additional phase image data set at a later point in time in Step  32  (for example during the heating of the tissue), the two phase image data sets can be subtracted from one another to generate a phase difference image data set in Step  33 . The temperature difference in the individual pixels can be determined in Step  34  via the above Equation (9). In the determination of the temperature difference the problem can now occur that this can no longer by unambiguously established since only phase values between zero and 2π are shown, and in taking the difference it cannot be absolutely established whether a phase transition was present or not. Typical echo times TE in a basic magnetic field of 1.5 Tesla cover a range from 70 to 200° C., which is sufficient for the temperature difference depiction. However, for higher fields of 3 Tesla this range of non-ambiguity of the temperature calculation is already halved to 35 to 50° C. Add to this that in many cases the optimal echo times TE for the MR temperature imaging are markedly higher than at 1.5 Tesla. The removal of the phase transition in the phase information is thus necessary. This applies all the more for the temperature imaging at 7 Tesla. Since the importance of 7 Tesla is significantly increasing in MR apparatuses, the removal of the phase transition for the MR temperature imaging is important since here only an unambiguous phase value range over a temperature range of 10 to 15° C. can be achieved. According to the invention, this is now possible with the use of the value ranges at the short echo times. For example, a phase difference image can only be generated with the aid of the phase information that is acquired at the echo point in time TE 1 . Given a heating this shortest echo point in time leads to a predetermined value range at phase differences, for example a value range from 0° to 150°. If the echo time is doubled, given the same temperature change the value range is already at 300°; if even longer echo times are used the value range is thus no longer situated within 2π. With the aid of the value range at the short echo time it can now be determined how many phase transitions must be present at the longer echo points in time since a linear connection between echo time and phase change (and therefore between echo time and phase value range) exists. 
     The calculation of phase information from the multiple echoes N is typically necessary without movement correction since the movement of the examined subject that occurs within the different echo times can normally be ignored. 
     Although modifications and changes may be suggested by those skilled in the art, it is the intention of the inventor to embody within the patent warranted hereon all changes and modifications as reasonably and properly come within the scope of his contribution to the art.