Abstract:
High-resolution elastography employs a multiple-step process in which successively finer samplings of data and smaller areas of data are evaluated to provide increasingly accurate displacement measurements, wherein each displacement measurement guides the determination of corresponding regions of comparison used in the next displacement evaluation.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is based on provisional application 60/725,475 filed Oct. 11, 2005, and entitled “Two-Step Strain Estimation in Elastography. 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
     This invention was made with United States government support awarded by the following agencies:
         NIH Grant R21 EB003853.       

     The United States has certain rights in this invention. 
    
    
     BACKGROUND OF THE INVENTION 
     The present invention relates to ultrasonic imaging and in particular to an apparatus and method for making ultrasonic elastography measurements. 
     Elastography is an imaging modality that reveals the stiffness properties of tissue, for example, axial strain, lateral strain, Poisson&#39;s ratio, Young&#39;s modulus and other common strain and strain-related measurements. In elastography, strain measurements may be collected over an area and compiled as a two-dimensional array of data which may be mapped to a grey or color scale to form a strain “image.” Analogously, strain measurements may be collected over a volume displayed either three-dimensionally or as a series of stacked two-dimensional images. 
     In quasi-static elastography, two images of tissue (“pre-compression” and “post-compression”) are obtained by the ultrasound device with the tissue in two different states of compression, for example, no compression and a given positive or negative (tensile) compression. The tissue may be compressed by an external agency such as a probe or the like, or muscular action or movement of organs near the tissue. Strain may be deduced from these two images by computing gradients of the relative local shifts or displacement in the images along the compression axis. Quasi-static elastography is analogous to a physician&#39;s palpation of tissue in which the physician identifies firm structures by pressing the tissue and detecting the amount the tissue yields under this pressure. 
     Determining the relative displacement of the tissue between the two compression images is normally done by analyzing successive portions of the ultrasonic signal in a series of discrete 1-D windows or 2-D or 3-D kernels. The windows define portions of the ultrasonic signal at successive times representing reflections from tissue at successive locations along the path of the ultrasound. Kernels denote 2-D or 3-D search regions in the 2-D or 3-D received ultrasound echo signals in the B-mode or RF data. The ultrasonic signal may be either an envelope of the amplitude of a received ultrasonic echo or the echo signal (RF) itself. 
     Generally, the signal in each window in the pre-compression image is cross-correlated to the signal in a search area of the post-compression image to find corresponding window in the post-compression data and thereby determine slight shifts between the signals and thus shifts in location of the underlying tissue with compression. This cross-correlation process is repeated for successive windows of the ultrasonic signal yielding local displacement of tissue for each window. The gradient of these local displacements yields a measure of the local strains in the tissue. 
     The resolution of elastography is fundamentally limited by the size of the windows used to determine the displacement of the tissue. Currently, larger windows are used, for example, on the order of twenty wavelengths (a centimeter or more at common ultrasound frequencies), too large to effectively image extremely smaller objects such as the calcifications that accompany breast cancer. 
     Smaller window sizes, for example, on the order of one wavelength (less than a millimeter at common ultrasound frequencies), potentially provide an increase in the resolution of elastography, but are practically limited by problems of tissue displacement moving the echo signals that arise from this tissue to be entirely out of the window and increased statistical miscorrelation as the amount of correlated data is reduced and the discipline of only correlating within corresponding windows is relaxed. 
     The problem of post-compressed tissue failing to remain within corresponding windows of the post-compressed tissue can be addressed by using larger size windows for the post-compression data or by temporal stretching of the post-compression data to improve the alignment of the tissue between windows. This latter approach tends to introduce artifacts into the post-compression data where some regions are over stretched while other regions are under stretched. The former approach still faces the problem of statistical mismatching in the cross correlation process promoted by the unmatched window sizes. 
     SUMMARY OF THE INVENTION 
     The present invention provides a high-resolution ultrasonic elastography machine using window sizes less than two wavelengths (on the order less than a millimeter) for common ultrasound frequencies. The above-described problems of small window sizes are avoided with a multi-step correlation process starting with large windows which provide a coarse estimation of tissue displacement. This coarse estimation is then used to guide the placement of successively smaller windows in later steps of the process, the displacement at each window size guiding the placement of the next smaller windows. As so guided, the successively smaller windows may be placed on corresponding echo signals, eliminating the problem of tissue movement outside of the windows and significantly reducing the risk of miscorrelation. 
     Specifically then, the present invention provides high resolution ultrasonic elastography in which pre-compression and post-compression ultrasonic data sets are collected, and a first comparison is made of the pre-compression and post-compression data at a plurality of corresponding first pre-compression region and first post-compression regions to determine a coarse-displacement of material of the imaged object resulting from compression. The determined coarse-displacements are then used to identify second post-compression regions corresponding to a plurality of second pre-compression regions within each first pre-compression region and a second comparison is made of the pre-compression and post-compression data within the plurality of second pre-compression regions corresponding second post-compression regions to determine a finer-displacement of material of the imaged object resulting from compression. An elastographic image based on the finer displacement is then output. 
     Thus, it is an object of at least one embodiment of the invention to obtain the benefits of a large window or kernel size in accommodating tissue displacement and the benefits of a small window or kernel size for high-resolution imaging. The large window or kernel sizes provide a coarse-displacement map which guides the small window comparisons. 
     The data of the first pre-compression regions and first post-compression regions are down-sampled to reduce the number of data samples that otherwise would need to be compared. 
     Thus it is another object of at least one embodiment of the invention to provide an efficient multistep/multiregion process where the amount of data is limited to be commensurate with the precision of the necessary displacement determination. 
     The first comparison compares amplitude envelopes of the ultrasonic data sets and the second comparison compares ultrasonic data underlying the amplitude envelopes. 
     Thus it is another object of at least one embodiment of the invention to provide a simple compression system (envelope extraction) that is resistant to aliasing that can occur with standard down-sampling. 
     The method may further include the steps using the determined finer-displacements to identify third post-compression regions corresponding to a plurality of third pre-compression regions within each second pre-compression region and making a third comparison of the pre-compression and post-compression data within the plurality of third pre-compression regions and corresponding third post-compression regions to determine an even finer displacement of material of the imaged object resulting from compression. 
     Thus, it is an object of the invention to provide an arbitrary number of steps of displacement refinement allowing extremely fine resolution to be obtained even when assumptions about continuity in the displacement field are invalid, such as when imaging blood vessels that are compressed or expanded under pulsatile blood flow. 
     The first comparison may compare portions of the ultrasonic data sets having no less than ten wavelengths of data while the second comparison may compare portions having less than ten wavelengths of data and preferably less than two wavelengths of data. 
     Thus, it is an object of the invention to significantly increase the resolution of ultrasonic elastography. 
     The first comparison may produce a set of displacement values as a function of depth along an ultrasonic axis through the imaged object and may include the step of interpolating between the displacement values to produce the coarse-displacement. 
     Thus, it is an object of the invention to provide extremely fast displacement mapping commensurate with the purpose of providing guidance for the smaller windows while minimizing any time penalty for two steps of comparison. 
     The coarse-displacement data set may be filtered before its use in guiding the placement of the smaller comparison windows. 
     Thus, it is another object of the invention to make use of a priori knowledge about properties of the imaged material, for instance, tissue, to improve the coarse-displacement data, for example, through low pass filtering or elimination of statistical anomalies. 
     The pre-compression and post-compression ultrasonic data may be RF data. 
     Thus, it is an object of the invention to provide a system that may take full advantage of single-wavelength features of the RF data. 
     The ultrasonic data may be acquired along the axis of compression or across the axis of compression and may be used to form a two-dimensional or three-dimensional image from multiple such ultrasound data acquired in a linear, curvilinear or angular fashion. 
     Thus, it is another object of the invention to provide for a strain mapping technique that is applicable to a wide variety of ultrasonic strain determination applications. 
     These particular objects and advantages may apply to only some embodiments falling within the claims, and thus do not define the scope of the invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a simplified block diagram of an ultrasound-imaging machine such as may be used for elastography per the present two-step invention;  FIG. 2  is a diagram showing the first step of the invention in which corresponding large windows of signals from pre-compressed and post-compressed tissue are compared to obtain a coarse determination of tissue displacement; 
         FIG. 3  is a graph showing a plot of the coarse-displacement determined in the first step of the invention for multiple corresponding large windows; 
         FIG. 4  is a figure similar to that of  FIG. 2  showing a second step of the invention in which corresponding small windows of signals from pre-compressed and post-compressed tissue are compared to obtain a fine determination of tissue displacement; the corresponding small windows being identified by the coarse-displacement map of  FIG. 3 ; 
         FIG. 5  is a figure similar to that of  FIG. 3  showing a refinement of the coarse-displacement map of  FIG. 3  using the measurements for the small windows of  FIG. 4 ; 
         FIG. 6  is a flow chart depicting the steps of  FIGS. 2 through 5 ; 
         FIG. 7  is a simplified perspective view of several different modes of ultrasonic acquisition strategy to which the present invention may be applied; 
         FIG. 8  is a representation of a pyramid, formed from the data of both of the pre-compression and post-compression ultrasound data, as successively compressed in a multi-step embodiment of the present invention, showing for each step of compression a matching depiction of a corresponding waveform and sampling, and a depiction of a relative window size; 
         FIG. 9  is a flowchart showing the steps of the multi-step embodiment; and 
         FIG. 10  is a set of figures similar to those of  FIGS. 2 and 4  showing refinements of displacement vectors using successively smaller windows in the multi-step process. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
     Referring now to  FIG. 1 , an ultrasonic imaging system  10  may provide an ultrasound transducer  12  producing and receiving ultrasonic echo signals  14  along multiple ray paths  16  through an imaged object such as tissue  18  of the patient. For the purpose of illustration, the received the ultrasonic echo signals  14  are shown superimposed on the tissue  18  to depict the relationship between these time domain signals to reflections of ultrasonic energy from various points along the ray paths  16 . 
     The ultrasonic echo signals  14  may be received and processed by ultrasound acquisition circuitry  20  of a type well known in the art to provide radio frequency data to an elastography processor  22 . A suitable ultrasonic imaging system  10  for the present invention may use 7.5-megahertz frequency with a transducer having five-hundred and twelve or more consecutive elements to provide for ultrasound beams generated with an aperture of sixty-four element beams of ultrasonic echo signal  14 . 
     Generally, as will be described in more detail below, the elastography processor  22  produces elastographic images  24  that may be displayed on a display terminal  26  communicating with the elastography processor  22 . The elastographic images  24  may provide for a visual representation of one or more measures of stiffness of the tissue  18  of the patient. An input device  28  may communicate with the elastography processor  22  to allow the user to set or change various processing parameters used by the ultrasound acquisition circuitry  20  or the elastography processor  22 . 
     Referring now to  FIGS. 1 ,  2 , and  6 , during a first step in an elastographic acquisition using the above-described ultrasonic imaging system  10  as indicated by process block  40  of  FIG. 6 , the tissue  18  of the patient may be compressed along a compression axis  30  typically, but not necessarily, aligned with the ray paths  16 . For this purpose, the ultrasonic imaging system  10  may include a separate compressor (not shown) or the compression may be incidental to muscle or organ movement, or performed manually by pressing down on the transducer  12  at an appropriate time. The compression is performed to allow the ultrasonic imaging system  10  to collect at least two sets of ultrasonic echo signals  14 , each with the tissue  18  in a different state of compression, e.g., pre-compression and post-compression. For simplicity, in the following description and claims, the terms “pre-compression” and “post compression” refer simply to two different states of compression and not necessarily a relative order of acquisition or relative magnitude of compression. Typically, a compression of approximately one percent is sought. Larger compressions can also be tracked using two-dimensional cross-correlation processing. 
     Two-Step Processing 
     Referring to  FIG. 2 , the ultrasonic echo signals  14  acquired in pre-compressed tissue  18  may be compared to ultrasonic echo signals  14  post-compressed tissue  18 ′ to deduce tissue movement or deformation caused by the compression. For this purpose, each ultrasonic echo signal  14  and  14 ′ is divided into a set of time sequential coarse-scale kernels or windows  32  and  32 ′, respectively, normally each greater than ten wavelengths of the ultrasonic echo signal  14  and preferably on the order of twenty wavelengths. As is understood in the art, a wavelength is the distance the ultrasonic echo signal  14  travels through the tissue  18  during one cycle of the ultrasound signals  14 , and thus will vary depending on the frequency of the ultrasonic transducer  12 . 
     The compression of the tissue  18  (depicted as tissue  18 ′) will cause a shifting of relative portions of the ultrasound signals  14  between coarse-scale windows  32  and  32 ′ caused by displacement of underlying tissue  18 ,  18 ′. That is, the ultrasonic echo signal  14  associated with a particular structure in the tissue  18  will be found in a different location in coarse-scale window  32  than in  32 ′. Ideally coarse-scale windows  32  and  32 ′ are sized so that, with foreseeable compression of the tissue  18 , a portion of the ultrasonic echo signal  14  in coarse-scale window  32  will still be within coarse-scale window  32 ′ for conceivable compression amounts thus limiting the search area (e.g., the amount of relative shifting) that will be required of the coarse-scale window  32 ′ necessary to find a location that provides good correlation with the data of the coarse-scale window  32 . 
     As indicated by process block  42  of  FIG. 6 , for each of the coarse-scale windows  32  on ultrasonic echo signals  14 , a cross correlation may be performed with the corresponding coarse-scale window  32 ′ on the ultrasonic echo signal  14 ′ as a function of movement of the location of the coarse-scale window  32 ′. The cross correlation provides a peak value that indicates a shift of tissue relative to window  32  during the compression reflected in the offset of the coarse scale windows  32  and  32 ′ at maximum correlation. The amount of this shift provides data points  46  indicating tissue displacement (Δz) as a function of depth (z) along the ray path  16  and may be stored to produce a coarse-displacement map  44  for each ultrasonic echo signal  14 . One data point  46  may be calculated for each coarse-scale window  32 , and the separation between displacement points  46  is therefore a function of the size of coarse scale windows  32 . In the preferred embodiment, each coarse-scale window  32  does not overlap the next window on a given ultrasonic echo signal  14  to speed processing because only a coarse-displacement map  44  is required. 
     The coarse-displacement map  44  may be further processed by interpolating between points  46  to provide a continuous function  48  and low pass filtering of that function according to a priori knowledge of tissue characteristics in smoothing displacement of post-compressed tissue. Other statistical measures may be taken to improve the coarse-displacement map  44  including, for example, curve fitting and the elimination of statistically outlying points caused by noise or other artifacts. 
     Referring now to  FIG. 4  and process block  50  of  FIG. 6 , fine-scale windows  52  and  52 ′ on each of ultrasonic echo signals  14  and  14 ′, respectively, are less than ten wavelengths, preferably less than two wavelengths, and as little as a single wavelength of the ultrasonic echo signal  14  in length. The reduced size of each fine-scale window  52  and  52 ′ significantly reduces the likelihood that tissue in a fine-scale window  52  in the pre-compressed tissue  18  will by chance contain the same tissue as that in fine-scale window  52 ′ in the post-compressed tissue  18 ′ at the same relative location. Further, the limited amount of data in the fine-scale window  52  increases the possibility of false correlations with unrelated portions of ultrasonic echo signal  14 ′ should fine-scale window  52 ′ be scanned over an arbitrarily large search area in making a correlation. 
     For these reasons, a new, displaced, fine-scale window  52 ″ having the same dimensions as fine-scale window  52  is identified on ultrasonic echo signal  14 ′ having a displacement from fine-scale window  52 ′ derived from the coarse-displacement map  44  of  FIG. 3 . Specifically, for each fine-scale window  52 , the z-location of the fine-scale window  52  is applied to the coarse-displacement map  44  to determine the likely tissue shift Δz at that z-location, and thereby anticipate the likely location of fine-scale window  52 ″ covering a portion of ultrasonic echo signals  14 ′ from the same tissue as that producing the ultrasonic echo signal  14  covered by fine-scale window  52 . 
     For each of the fine-scale windows  52  on ultrasonic echo signals  14 , a cross correlation may be performed with the corresponding fine-scale window  52 ″ on the ultrasonic echo signal  14 ′ at various offsets in a limited range about this initial location of fine-scale window  52 ″. The cross correlation, as before with windows  32  and  32 ′, provides a peak value that indicates a shift of tissue relative to window  52  during the compression. 
     This cross-correlation process is repeated for each of a series of windows  52  as indicated by process block  56  to create a new fine-displacement map  44 ′ from the cross correlations between corresponding fine-scale window  52  and  52 ″. Fine-scale windows  52  may overlap slightly so as to provide data points  46 ′ that may be more frequent than the width of the fine-scale window  52 . 
     The fine-displacement map  44 ′, as indicated by process block  58  of  FIG. 6 , may be used directly to create an elastographic image where stiffness is deduced by the slope of the curve of the fine-displacement map  44 ′ according to methods well-known in the art. Additional processing, for example, filtering and statistical processing, may be optionally performed on fine displacement map  44 ′ prior to reconstruction of the image. 
     Multistep (Pyramid) Processing 
     Referring now to  FIG. 8 , the pre-compression ultrasonic echo signals  14  and post-compression ultrasonic echo signals  14 ′ may be assembled into a radio-frequency data array  70  having successive rows incorporating digitized samples  74  of echo signals  14  or  14 ′ from spatially adjacent tissue. While the data array  70  is shown as a two-dimensional array, it will be understood that it may alternatively be a three dimensional array of data representing data over three corresponding spatial dimensions in the tissue  18 . 
     The radio-frequency data array  70  may be down-sampled to produce first down-sampled data set  76  providing fewer data points and thus generally fewer rows and columns. The down-sampling process may simply down-sampling of radio-frequency data array  70 , e.g., by combining and interpolating between the samples  74  (in two or three dimensions) of radio-frequency data array  70  to produce the smaller set of samples for first down-sampled data set  76 , or may, in the preferred embodiment, be samples  80  taken at a lower sample rate on amplitude envelope  82  of the echo signals  14  or  14 ′ using well known amplitude demodulation techniques. The amplitude envelope  82 , having inherently lower frequency than the waveform  72  eliminates problems that may occur if the sample rate of samples  80  is less than the Nyquist frequency, (e.g., less than twice the highest frequency of echo signals  14  or  14 ′). The interpolation or enveloping is preferably performed in two directions for two dimensional array  70  reducing the number of rows and columns of data in the first down-sampled data set  76  and in three dimension for a three-dimensional array  70 . 
     Similarly, the first down-sampled data set  76  may be down-sampled to produce second down-sampled data set  84  by down sampling and interpolation or other compression processes providing even fewer data points from samples  86  at a yet lower rate, and thus generally fewer rows and columns. 
     As will be discussed further below, the successive down-sampling of the radio-frequency data array  70  as first down-sampled data set  76  and second down-sampled data set  84  allows for efficient correlation of successively larger kernel or windows  110 ,  100  and  92 , respectively, at higher speeds. The kernels or windows  110 ,  100 , and  92  can be two or three dimensional depending on the dimensions of the data array  70 . The larger windows provide lower accuracy displacement measurements, but such measurements are suitable for the successive refinement of displacement measurements provided by the present invention. Note that the combination of down-sampling and larger window sizes allows each window to have, if desired, a comparable number of data points for different sampling resolutions. 
     Referring now to FIGS,  8 ,  9  and  10 , at a first step indicated by process block  90  of this multi-step version of the invention, occurring after step  40  of  FIG. 6 , a displacement map  44 ′ providing a series of displacement vectors  96  is created using the data of the second down-sampled data set  84  analyzed using a large window  92 . The size of window  92  may, for example, be such as to fully cover a blood vessel  94 , whose compression may be effected by the normal pulsatile flow of blood through the vessel  94 . In this situation, the wall of the vessel  94  closest to the transducer (not shown) may move toward the transducer while the wall of the vessel  94  furthest from the transducer may move away from the transducer creating a non-monotonic displacement field normally unexpected in conventional displacement calculating algorithms. While the window  92  is relatively large, the down-sampling of the second down-sampled data set  84  means that the computational burden for cross correlation of the pre- and post-compression data of window  92  is well managed. The comparison of the data of the windows  92  and  92 ′ maybe in two or three dimensions as would be appropriate for the data. 
     At process block  90 , the pre-compression data of the second down-sampled data set  84  for each of a series of windows  92  is compared to the post-compression data of the second down-sampled data set  84  in corresponding windows  92 ′ to determine a displacement vector  96  associated with each window  92 ,  92 ′. 
     At process block  98 , a number of smaller windows  100  and  100 ′ are then defined within each window  92  or a similar search area, as applied to the pre-compression and post-compression data, respectively, of the first down-sampled data set  76 . Corresponding locations of windows  100  and  100 ′ are determined using previously computed displacement vector  96  for the window  92  in which window  100  is located. Generally window  100 ′ need not be in the same window  92  as window  100 . 
     At process block  102  the comparison of these smaller corresponding windows  100  and  100 ′ as the latter is scanned over a limited search area, is used to produce a new displacement map comprised of a set of displacement vectors  104  providing more accuracy than displacement vectors  96 . 
     Process block  98  may then be repeated with yet smaller data window  110  being defined within each data window  100  applied to pre-compression data of the data set  70  and matched to a corresponding data window  110 ′ in the post-compression data of the data set  70 . At process block  102 , a yet even more accurate displacement map may be constructed using displacement vectors  108  calculated from a comparison of the data of windows  110  and  110 ′. Data window  110  may be small enough that the assumptions about continuity or monotonicity of the displacement field apply. 
     At each level of this process, when displacement vectors  96 ,  104  and  108 , are calculated, displacement vectors associated with low normalized cross-correlation coefficients may be replaced or interpolated from surrounding displacement vectors having higher normalized cross-correlation value. The threshold for such replacement may be empirically chosen. 
     In addition other filtering may be applied to the displacement vectors, for example, smoothing them with a cubic spline smoothing function. 
     Referring now to  FIG. 7 , the present invention is applicable to a wide variety of ultrasonic elastographic acquisitions where improved resolution is required including a two-dimensional acquisition in which the ultrasonic transducer produces a linear or sector acquisition  60  along the compression axis  30 , or three-dimensional acquisition, with the ultrasonic transducer  12   b , which produces a sector or linear array ultrasound data  62 , or where an ultrasound beam  60  is swept through an area for a three-dimensional acquisition (not shown) or in acquisitions in which a transducer  12   c  (as shown by ultrasonic transducer  12   c ′) obtains both axial and lateral acquisitions over a three-dimensional or two-dimensional volume. As used herein, “axial” is the direction of the compression axis  30  and the term “lateral” will be used to describe axes that cross the compression axis  30  including, but not necessarily limited to, those perpendicular to the compression axis  30 . Thus, the present techniques may apply to a number of elastography applications wherever fine or high resolution displacement must be determined including those techniques described in U.S. patent applications Ser. No. 10/094,844 filed Mar. 8, 2002; U.S. Pat. No. 6,749,571 issued Jun. 15, 2004; Ser. Nos. 10/420,125 filed Apr. 21, 2003; 10/772,663 filed Feb. 4, 2004; 10/765,293 filed Jan. 24, 2005; and 10/784,526 filed Feb. 23, 2005, all hereby incorporated by reference and assigned to the same assignee as the present application. 
     It should be noted that the present technique can be used with envelope waveforms, transmission ultrasound (as opposed to echo ultrasound), that the sizes of the windows  32  and  54  may be freely adjusted by the user, that this technique can be used in conjunction with other techniques such as stretching of post-compression data and that the image need not be of tissue, but that the present invention is applicable to other materials. It is therefore specifically intended that the present invention not be limited to the embodiments and illustrations contained herein, but include modified forms of those embodiments including portions of the embodiments and combinations of elements of different embodiments as come within the scope of the following claims.