Patent Abstract:
Methods and computer-readable mediums are provided. In one embodiment, the method acquires patient data. The peak value in the patient data is determined. The patient data is divided into two data segments (i.e., one data segment representing the data before the peak value occurs and a second data segment representing the patient data after the peak occurs). The slopes of the first and second data segments are calculated. Thereafter the slopes are used to determine an appropriate adaptive framing protocol. A number of frames and duration of each frame in the adaptive framing protocol can be calculated or the adaptive framing protocol can be selected from a plurality of framing protocols. Embodiments of the invention also include computer-readable mediums that contain features similar to the features in the above described method.

Full Description:
BACKGROUND 
     1. Field of the Invention 
     Embodiments of the present invention generally relate to nuclear medicine, and systems for obtaining images of a patient&#39;s body organs of interest. In particular, the present invention relates to a novel method and system for utilizing an adaptive framing protocol in medical imaging. 
     2. Description of the Related Art 
     Heart disease is very common. The heart can be evaluated for large vessel and small vessel disease. One by-product of small vessel heart disease is poor heart oxygenation. 
     Nuclear medicine is a unique medical specialty wherein radiation is used to acquire images that show the function and anatomy of organs, bones and/or tissues of the body. Radiopharmaceuticals are introduced into the body, either by injection or ingestion, and are attracted to specific organs, bones and/or tissues of interest. For example, the radiopharmaceutical (e.g., rubidium) is injected into the bloodstream. 
     The radiopharmaceutical produces gamma photon emissions that emanate from the body. One or more detectors are used to detect the emitted gamma photons and the information collected from the detector(s) is processed to calculate the position of origin of the emitted photon from the source (i.e., the body organ or tissue under study). The accumulation of a large number of emitted gamma positions allows an image of the organ or tissue under study to be displayed. 
     How fast the radiopharmaceutical is taken in by the heart indicates how quickly the heart is being oxygenated and also indicates how healthy the small micro-vessels are in the heart. The rate of absorption of the radiopharmaceutical is determined by comparing the amount of radiopharmaceutical at one time with the amount at another time. 
     To calculate the rate of absorption, measurements are taken at various times. Data is acquired for each patient under “rest” and “stress” conditions. Stress is usually induced through either some form of exertion (e.g., walking or running on a treadmill) or by injection of a chemical which increases the heart rate. The ratio between stress and rest in a healthy heart is about a factor of 4 and in a diseased heart the stress/rest ratio is about a factor of 1.2. 
     In PET studies of cardiac function, emission data are typically collected in list mode. The list is then divided into a predetermined temporal sequence of frames (using a framing protocol), an image is reconstructed from the data in each frame, and the sequence of reconstructed images analyzed for evidence of disease. 
     To date, framing protocols have universally been fixed for every patient. Clinicians choose some invariant sequence of framing times, which never changes. These fixed framing protocols are the same within each clinic. 
     For example, Lorte,  Quantification of Myocardial Blood Flow with  82 Rb Dynamic PET Imaging , Eur. J. Nucl. Med. Mol. Imaging (2007) 34: 1765-1774, (“Lortie et al.”) analyzes all patient data using a framing protocol that consists of 17 frames organized as 12*10 s+2*30 s+1×60 s+1×120 s+1×240 s; and El Fakhri,  Absolute Quantitation of Regional Myocardial Blood Flow  ( MFB )  Using RB -82  PET: Experimental Validation Using Microspheres , J. Nucl. Med. 2007, 48 (Supplement 2) 54P, (“El Fakhri et al.”) analyzes all patient data using a framing protocol that consists of 34 frames organized as 24*5 s+6*10 s+4*20 s. In some studies, the first frame is started on a signal derived from the data, but in all studies the timing of the frames does not depend on any features of the data. 
     After image reconstruction, the amount of radioactivity in the heart can be measured. 
     One way to estimate dynamic physiological parameters from quantitative reconstructed images is given by Lortie et al., using a one-compartment model:
 
 C   m ( t )= K   1   e   −k     2     t   *C   a ( t )  Equation (1)
 
     where C a (t) and C m (t) are the measured concentrations of the radiotracer in the arterial blood and the tissue of interest, respectively. K 1  is a measure of how quickly the radiotracer flows into the tissue of interest and k 2  represents how quickly it flows out. To estimate the model parameters K 1  and k 2 , least squared error minimization can be used, with each frame assigned a weight proportional to its duration in time. 
     The prior art analyzes small vessel disease using a fixed framing protocol which often leads to an excessive number of frames used in the analysis. 
     Therefore, there exists a need in the art for a protocol which is adapted for each individual patient to minimize the number of frames used in the analysis of the medical images. 
     SUMMARY 
     These and other deficiencies of the prior art are addressed by embodiments of the present invention, for obtaining images of a patient&#39;s body organs of interest. In particular, the present invention relates to a novel method and system for utilizing an adaptive framing protocol in medical imaging. In one embodiment, the method acquires patient data. The peak value in the patient data is determined. The patient data is divided into two data segments (i.e., one data segment representing the data before the peak value occurs and a second data segment representing the patient data after the peak occurs). The slopes of the first and second data segments are calculated. Thereafter the slopes are used to determine an appropriate adaptive framing protocol. A number of frames and duration of each frame in the adaptive framing protocol can be calculated or the adaptive framing protocol can be selected from a plurality of framing protocols. Embodiments of the invention also include computer-readable mediums that contain features similar to the features in the above described method. 
     Other embodiments are also provided in which a computer-readable medium performs similar features recited by the above method. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       So that the manner in which the above recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments. 
         FIG. 1  depicts a graph in accordance with the prior art; 
         FIG. 2  depicts a data flow diagram in accordance with the prior art; 
         FIG. 3  depicts a fixed frame protocol in accordance with the prior art; 
         FIG. 4  depicts a graph in accordance with aspects disclosed herein; 
         FIG. 5  depicts another graph in accordance with aspects disclosed herein; 
         FIG. 6  depicts an embodiment of a data flow diagram in accordance with aspects disclosed herein; 
         FIG. 7  depicts a diagram of an exemplary method according to a preferred embodiment in accordance with aspects disclosed herein; and 
         FIG. 8  depicts an embodiment of a high-level block diagram of a computer architecture used in accordance with aspects disclosed herein. 
     
    
    
     To facilitate understanding, identical reference numerals have been used, wherever possible, to designate identical elements that are common to the figures. 
     DETAILED DESCRIPTION 
     In the following description, numerous specific details are set forth to provide a more thorough understanding of the invention. As will be apparent to those skilled in the art, however, various changes using different configurations may be made without departing from the scope of the invention. In other instances, well-known features have not been described in order to avoid obscuring the invention. Thus, the invention is not considered limited to the particular illustrative embodiments shown in the specification and all such alternate embodiments are intended to be included in the scope of the appended claims. 
     Aspects of this disclosure are described herein with respect to applying an adaptive framing protocol in PET systems. However, the description provided herein is not intended in any way to limit the invention to PET systems. Aspects of the material disclosed herein may be utilized in other imaging technologies (e.g., SPECT systems, etc.). 
     Although aspects of this disclosure are described herein with respect to blood flow through a heart, those descriptions are for exemplary purposes only and not intended in any way to limit the scope of the material disclosed herein. For example, the material disclosed herein may be used to examine blood flow through other organs/limbs/tissue (e.g., a toe, brain, etc.). 
     Some guidelines in selecting a framing protocol are (1) during initial phase of acquisition, when the data are changing rapidly, to divide the data into a large number of short flames, to capture the dynamics; (2) during a later phase of acquisition, when the data are changing slowly (when compared to the initial phase), to divide the data into a small number of long frames, to maximize noise performance; (3) to choose a framing protocol which behaves properly given the range dynamical behavior observed in all clinical data sets (i.e., from all patients); and (4) to minimize the overall number of frames so as to reduce the computational burden, and the time, needed by image reconstruction and analysis. 
       FIG. 1  (prior art) depicts a graph  100  of cardiac rubidium studies of two patients. Specifically, the graph  100  includes a “Y” axis  102  delineating a number of radioactive decay events and an “X” axis  104  delineating time in seconds. The graph  100  includes two cardiac rubidium plots (P 1  Rest  110  and P 1  Stress  108 ) for patient P 1 , and two cardiac rubidium plots (P 4  Rest  114  and P 4  Stress  112 ) for patient P 4 . The graph  100  also includes a legend  106  identifying each of the plots (“P 1  Rest,” “P 2  Stress,” “P 4  Rest,” and “P 4  Stress”) in graph  100 . Note that the P 1  Rest  110  and P 1  Stress  108  reach their peak before P 4  Rest  114  and P 4  Stress  112 . In other words, the level of radiotracer increases more rapidly for P 1  than for P 4 . 
       FIG. 2  depicts a data flow diagram  200  in accordance with a fixed framing protocol of the prior art. Specifically, the data flow diagram  200  includes PET event data  201  acquired from a patient. For illustrative purposes, the PET event data is the data (i.e., the plots P 1  Rest, P 1  Stress, P 4  Rest, and P 4  Stress) depicted in graph  100 . Fixed framing protocol  202  is a fixed framing protocol utilized by a clinic for all patients examined by the clinic. In this example of the prior art, the fixed framing protocol  202  includes eight segments (two 5 sec, two 10 sec, two 20 sec, and two 40 sec segments) depicted as look-up table  206 . The event data  201  is divided into eight list segments and mapped to a fixed framing protocol algorithm  202 . The length of each segment is predetermined in advance regardless of the dynamic data of an individual patient. The data in look-up table  206  is used by an image reconstruction module  204 . These list segments are then individually reconstructed as two 5 sec images, two 10 sec images, two 20 sec images, and two 40 sec images, yielding a fixed number of images  208 . Quantities extracted from the image sequence are then used to perform dynamic parameter estimation (e.g., using Equation (1)), yielding some physiological result  212 . 
       FIG. 3  depicts a fixed frame protocol  300  applied to graph  100  in accordance with the prior art. Specifically,  FIG. 3  includes the “Y” axis  102  delineating the number of radioactive decay events and the “X” axis  104  delineating time in seconds.  FIG. 3  also includes the two cardiac rubidium plots (P 1  Rest  110  and P 1  Stress  108 ) for patient P 1 , and the two cardiac rubidium plots (P 4  Rest  114  and P 4  Stress  112 ) for patient P 4 . In addition, the legend  106  identifying each of the plots (“P 1  Rest,” “P 2  Stress,” “P 4  Rest,” and “P 4  Stress”) is depicted. 
     This protocol is a fixed framing protocol and consists of 26 frames (i.e., twelve 5 sec, six 10 sec, four 20 sec, and four 40 sec frames). In this diagram the vertical lines  302   1 ,  302   19 , . . . ,  302   26  (collectively vertical lines  302 ) indicate the segments in time for subsequent analysis. The plots of patient P 1  peaks prior to the plots of patient P 4 . However, the fixed framing protocol doesn&#39;t take into account the faster increase in rubidium levels of P 1  relative to P 4 . 
     In general, the fixed framing leads to an excessive number of frames (before and after a peak occurs), since the high-frequency part at the beginning of the fixed protocol must be long enough to capture the activity peak in all studies, regardless of how late the peak occurs. 
     Aspects disclosed herein tailor the framing protocol to adapt to the observed peak in each individual data set, by performing a fast, preliminary analysis of the data while it is still in list mode. The adaptive framing protocol samples at the appropriate frequency around peak activity and at lower frequency after the peak. As a result, the number of frames utilized by this method is significantly less than the number of frames required by the fixed framing method, with little or no loss of dynamic resolution. 
       FIG. 4  depicts a graph  400  in accordance with aspects disclosed herein. Specifically,  FIG. 4  includes the “Y” axis  102  delineating the number of radioactive decay events and the “X” axis  104  delineating time in seconds.  FIG. 4  also includes the two cardiac rubidium plots (P 1  Rest  110  and Pt Stress  108 ) for patient P 1 . In addition, a legend  404  identifying both plots for P 1  is depicted.  FIG. 4  illustrates the results of an adaptive framing protocol applied to P 1  Rest  110  and P 1  Stress  108 . The data, while still in list mode, is analyzed (using e.g., a polynomial approximation) to determine when a peak value occurs. As a result, short sequences are applied before the determined peak value and longer sequences are applied after the determined peak. 
     In  FIG. 4 , the adaptive protocol includes fourteen frames (( 402   1 , . . . ,  402   11 , . . . , and  402   14 ) collectively frames  402 ). Because P 1  Rest  110  and P 1  Stress  108  peak earlier than P 4  Rest  114  and P 4  Stress  112  shorter frames can be applied to P 1  Rest  110  and P 1  Stress  108  up to the determined peak and longer sequences can be applied after the determined peak. In the sharply peaked case of patient P 1 , a smaller number (relative to patient P 4 ) of high frequency frames are used prior to peak. 
       FIG. 5  depicts another graph  500  in accordance with aspects disclosed herein. Specifically,  FIG. 5  includes the “Y” axis  102  delineating the number of radioactive decay events and the “X” axis  104  delineating time in seconds.  FIG. 5  also includes the two cardiac rubidium plots (P 4  Rest  114  and P 4  Stress  112 ) for patient P 4 . In addition, a legend  504  identifying both plots for P 4  is depicted. 
       FIG. 5  illustrates the results of an adaptive framing protocol applied to P 4  Rest  114  and P 4  Stress  112 . The data for P 4 , while still in list mode, is analyzed (using e.g., a polynomial approximation) to determine when a peak value occurs. The plots for patient P 4  peak slower (than patient P 1 ) which allows lower frequency frames (i.e., fewer frames) before peak occurs. 
     In  FIG. 5 , the adaptive protocol includes twelve frames (( 502   1 , . . . ,  502   9 , . . . , and  502   12 ) collectively frames  502 ). Because P 1  Rest  110  and P 1  Stress  108  peak earlier than P 4  Rest  114  and P 4  Stress  112  shorted frames can be applied to P 1  Rest  110  and P 1  Stress  108  up to the determined peak and longer sequences can be applied after the determined peak. Juxtaposition (not shown) of  FIGS. 4 and 5  shows the differences between the framing protocols (i.e., frames  402  and  502 ) utilized to analyze patients P 1  and P 4  respectively. 
       FIG. 6  depicts a data flow diagram  600  in accordance with aspects disclosed herein. Specifically, the data flow diagram  600  includes PET event data  201  acquired from all of the patients. For illustrative purposes, the PET event data is the data (i.e., the plots P 1  Rest, P 1  Stress, P 4  Rest, and P 4  Stress) depicted in graph  100 . An adaptive framing module  602  is separately applied to the data for each patient (i.e., applied to patient P 1  and P 4  separately). 
     Illustratively, the adaptive framing module  602  is depicted as being one of two different framing protocols (framing protocols  604  and  606 ). However, that depiction is not intended in any way to limit the scope of the invention. For example, the adaptive framing module  602  may contain more than two framing protocols. 
     Framing protocol  604  includes four frames (four 5 sec, one 10 sec, one 20 sec, and one 30 sec frames) and framing protocol  606  includes four frames (one 10 sec one 20 sec, one 30 sec, and one 40 sec frames). The number of frames is for illustrative purposes only and is used to depict that there is a difference between framing protocols  604  and  606 . 
     After analyzing a patient&#39;s data, a determination is made which framing protocol is the most appropriate framing protocol to utilize for the patient. After the determination is made which of the framing protocols is the most appropriate the data can be subsequently analyzed by an image reconstruction module  608 . These list segments are then individually reconstructed into image lists (in this example depicts as one of two image lists  610  and  612  corresponding to the adaptive framing protocol previously selected). Quantities extracted from the image sequence are then used to perform dynamic parameter estimation by the dynamic parameter module  614 , yielding some physiological result  616 . 
       FIG. 7  depicts an exemplary method  700  in accordance with embodiments disclosed herein. The method  700  begins at step  702 . 
     After step  702 , the method  700  proceeds towards step  704 . At step  704 , a patient&#39;s data is acquired. The patient data may be acquired from memory, transmitted from a remote device, or transmitted towards a processor. The patient data includes the number of radioactive decay events (for both stress and rest) and the times at which the events occurred. After, the acquisition step  704 , the method  700  proceeds towards step  706 . 
     At step  706 , a peak value (i.e., the highest value) of the acquired patient data is determined. After determination of the peak value, the method  700  proceeds towards step  708 . 
     At step  708 , the peak value is used to divide the patient&#39;s data into two temporal segments (i.e., one segment including all data before the peak value occurs and the other segment including all data after the peak value occurs). After step  708 , the method  700  proceeds towards step  710 . 
     At step  710 , the method  700  analyzes the segment which includes the data that occurred before the peak value. A subset of points which are both close to the peak value and greater than 10% of the maximum. The rising slope (i.e., the slope prior to and approaching peak) is calculated (e.g., using linear regression). After step  710 , the method  700  proceeds towards step  712 . 
     At step  712 , the slope (i.e., a declining slope) after the peak value has occurred is calculated. Although various calculations may be used to determine the slope after the peak value has occurred, illustratively the slope is calculated using Equations (2) and (3) below. The best fit to a decaying exponential can be calculating using Equation (2):
 
 f ( t )= Ae   −st   Equation (2)
 
     where f(t) represents the data, A represents an initial value, e represents the natural base, t is time, and s is a decay parameter that indicates the rate at which the data values declines (i.e., the slope) after the peak. 
     There are various ways to calculate the decay parameter s. For example, the decay parameter s may be calculated using Equation (3): 
                   s   =         n   ⁢       ∑       t   i     ≥   p       ⁢           ⁢     (       t   i     ⁢     ln   ⁡     (     f   ⁡     (     t   i     )       )         )         -       ∑       t   i     ≥   p       ⁢           ⁢       t   i     ⁢       ∑       t   i     ≥   p       ⁢           ⁢     ln   ⁡     (     f   ⁡     (     t   i     )       )                     ∑       t   i     ≥   p       ⁢     t   i   2       -       (       ∑       t   i     ≥   p       ⁢           ⁢     t   i       )     2                 Equation   ⁢           ⁢     (   3   )                 
where s is the decay parameter (i.e., the slope), t is time, n is the number of data points following the peak value, the summation is taken over t≧p (where p is the peak value), and f(t) denotes the data. After calculation of the declining slope, the method  700  proceeds towards step  714 .
 
     At step  714 , a framing protocol is selected based upon the properties of the data. The number of frames and the parameters of the frames (offset in time and frame duration) may change in response to the measured position in time and sharpness in time of the peak in the data. In various embodiments, the framing protocol is selected from a group of framing protocols stored in memory (e.g., stored in a look-up table). In other embodiments, the number of frames, in the framing protocol, and their durations may be calculated. Thereafter the method  700  proceeds towards and ends at step  716 . 
     Although method  700  is described as calculating the rising slope prior to calculating the declining slope that description is not intended in any way to limit the scope of the invention. For example, in various embodiments, the declining slope may be calculated before the rising slope. 
       FIG. 8  depicts a high-level block diagram of a general-purpose computer architecture  800  for providing an adaptive framing protocol. For example, the general-purpose computer  800  is suitable for use in performing the method of  FIG. 7 . The general-purpose computer of  FIG. 8  includes a processor  810  as well as a memory  804  for storing control programs and the like. In various embodiments, memory  804  also includes programs (e.g., depicted as an “adaptive framing module”  812  for determination of a framing protocol based on the properties of the data) for performing the embodiments described herein. The processor  810  cooperates with conventional support circuitry  808  such as power supplies, clock circuits, cache memory and the like as well as circuits that assist in executing the software routines  806  stored in the memory  804 . As such, it is contemplated that some of the process steps discussed herein as software processes may be loaded from a storage device (e.g., an optical drive, floppy drive, disk drive, etc.) and implemented within the memory  804  and operated by the processor  810 . Thus, various steps and methods of the present invention can be stored on a computer readable medium. The general-purpose computer  800  also contains input-output circuitry  802  that forms an interface between the various functional elements communicating with the general-purpose computer  800 . 
     Although  FIG. 8  depicts a general-purpose computer  800  that is programmed to perform various control functions in accordance with the present invention, the term computer is not limited to just those integrated circuits referred to in the art as computers, but broadly refers to computers, processors, microcontrollers, microcomputers, programmable logic controllers, application specific integrated circuits, and other programmable circuits, and these terms are used interchangeably herein. In addition, although one general-purpose computer  800  is depicted, that depiction is for brevity on. It is appreciated that each of the methods described herein can be utilized in separate computers. 
     The invention having been described, it will be apparent to those skilled in the art that the same may be varied in many ways without departing from the spirit and scope of the invention. In particular, while the invention has been described with reference to utilizing Equations (2) and (3), the inventive concept does not depend upon the use of Equations (2) and (3). Any acceptable methods may be used determine the slope before peak value and the slope after peak value. As previously explained adaptive framing may be performed by a programmable computer loaded with a software program, firmware, ASIC chip, DSP chip or hardwired digital circuit. Any and all such modifications are intended to be included within the scope of the following claims. 
     While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.

Technology Classification (CPC): 0