Abstract:
Methods and apparatus for generating a difference image to determine perfusion parameters, such as mean transit time, cerebral blood flow, and cerebral blood volume utilizing a CT imaging system are described. To generate difference images, a difference projection data set including a first sub-set and a second sub-set of projection data is acquired. The first sub-set is obtained when no contrast medium is present in a patient or shortly after the contrast medium is injected into the patient. The second sub-set is obtained after the contrast medium is absorbed by the patient. The difference projection data is generated by subtracting the first sub-set from the second sub-set. The difference projection data then undergoes image reconstruction processing to generate the difference images. The difference images are then mapped to an image generated using the first sub-set, and perfusion parameters are determined utilizing the mapped difference image.

Description:
BACKGROUND OF THE INVENTION 
     This invention relates generally to methods and apparatus for CT imaging and other radiation imaging systems, and more particularly to utilizing CT images to determine perfusion parameters. 
     In at least some computed tomography (CT) imaging system configurations, an x-ray source projects a fan-shaped beam which is collimated to lie within an X-Y plane of a Cartesian coordinate system and generally referred to as an “imaging plane”. The x-ray beam passes through an object being imaged, such as a patient. The beam, after being attenuated by the object, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at a detector array is dependent upon the attenuation of the x-ray beam by the object. Each detector element of the array produces a separate electrical signal that is a measurement of the beam attenuation at the detector location. The attenuation measurements from all the detectors are acquired separately to produce a transmission profile. 
     In known third generation CT systems, the x-ray source and the detector array are rotated with a gantry within the imaging plane and around the object to be imaged, so the angle at which the x-ray beam intersects the object constantly changes. X-ray sources typically include x-ray tubes, which emit the x-ray beam at a focal spot. X-ray detectors typically include a collimator for collimating x-ray beams received at the detector, a scintillator adjacent the collimator, and photodetectors adjacent to the scintillator. A group of x-ray attenuation measurements, i.e., projection data, from the detector array at one gantry angle is referred to as a view. A scan of the object comprises a set of views made at different gantry angles during one revolution of the x-ray source and detector. 
     In an axial scan, the projection data is processed to construct an image that corresponds to a two dimensional slice taken through the object. One method for reconstructing an image from a set of projection data is referred to in the art as the filtered back projection technique. This process converts that attenuation measurements from a scan into integers called CT numbers or Hounsfield units, which are used to control the brightness of a corresponding pixel on a cathode ray tube display. 
     To reduce the total scan time, a helical scan may be performed. To perform a helical scan, the patient is moved while the data for the prescribed number of slices is acquired. Such a system generates a single helix from a fan beam helical scan. The helix mapped out by a fan beam yields projection data from which images in each prescribed slice may be reconstructed. 
     At least one known CT imaging system utilizes a detector array and a data acquisition system (DAS) for collecting image data. The detector array includes detector cells or channels that each produce an analog intensity signal which is representative of the x-ray energy impinged upon the cell. The analog signals are then supplied to the DAS for conversion to digital signals. The digital signals are then used to produce image data. Detector cell degradation as measured by gain non-linearity typically produces ring or band annoyance artifacts. 
     CT perfusion methods are utilized to assess the viability of tissue of an organ-of-interest by determining perfusion parameters such as a mean transit time (MTT), a cerebral blood flow (CBF), and a cerebral blood volume (CBV). To determine perfusion parameters, the patient is continuously scanned at the same physical location, i.e., the patient table is stationary, and variations in the reconstructed CT images are measured. The image variations are then utilized to determine the perfusion parameters. Because the patient table is stationary, only a very limited volume of tissue can be examined by the CT scanner. For example, using a single slice CT scanner, sampling at 1000 views/second, the maximum volume that can be examined with a stationary patient table is approximately 10 mm. With a multi-slice CT scanner, the coverage is approximately 20 mm or 32 mm. Typically, a coverage range of 80-100 mm of anatomy is required to determine perfusion parameters. 
     Flat-panel based volumetric CT (VCT), on the other hand, is capable of covering a larger volume than a multi-slice CT scanner covering approximately 20 cm. A 40 cm by 40 cm flat-panel is capable of examining approximately a 20 cm volume, which is sufficient for a CT perfusion study of a human brain and a heart. A typical readout speed of a panel, however, is 30 views/second. Approximately one-thousand views are needed to ensure artifact-free image reconstruction. The time period to acquire one complete projection set is approximately 33 seconds, which is a protracted length of time compared to MTT and CBF. Even when detector channels in z-direction are ganged together across multiple slices, the acquisition time of a flat-panel based VCT is greater than a typical CT scanner acquisition time of 0.5-1.0 seconds. 
     SUMMARY OF INVENTION 
     Methods and apparatus for generating a difference image to determine perfusion parameters such as a mean transit time, a cerebral blood flow, and a cerebral blood volume utilizing a CT imaging system are described. To generate difference images, a difference projection data set is generated. A first sub-set of the projection data set is obtained when no contrast medium is present in a patient or shortly after the contrast medium is injected into the patient, i.e., before the contrast medium is sufficiently absorbed by the patient to impact collected data. A second sub-set of the projection data set is obtained after the contrast medium is absorbed by the patient, i.e., after up-take of the contrast medium. The difference projection data is generated by subtracting, for each view, the first sub-set of projection data from the second sub-set of projection data. The difference projection data then undergoes image reconstruction processing to generate the difference images. The difference images are then mapped to an image generated using the first sub-set of projection data, and perfusion parameters are determined utilizing the mapped difference image. 
     In another aspect, a processor in the imaging system is programmed to generate difference images and determine perfusion parameters using the difference images. To generate difference images, a difference projection data set is generated. The processor is configured to obtain a first sub-set of the projection data when no contrast medium is present in a patient or shortly after the contrast medium is injected into the patient, i.e., before the contrast medium is sufficiently absorbed by the patient to impact collected data. A second sub-set of projection data is obtained after the contrast medium is absorbed by the patient, i.e., after up-take of the contrast medium. The difference projection data is generated by subtracting, for each view, the first sub-set of projection data from the second sub-set of projection data. The difference projection data then undergoes image reconstruction processing to generate the difference images. The difference images are then mapped to an image generated using the first sub-set of projection data, and perfusion parameters are determined utilizing the mapped difference image. 
     In yet another aspect, a computer-readable medium in the imaging system is provided which comprises a record of difference projections used to reconstruct a difference image. To generate difference images, a record of difference projection data set is generated. A record of a first sub-set of projection data is obtained when no contrast medium is present in a patient or shortly after the contrast medium is absorbed by the patient to impact collected data. A record of a second sub-set of projection data is obtained after the contrast medium is absorbed by the patient, i.e., after up-take of the contrast medium. The record of difference projection data is generated by subtracting, for each view, the record of the first sub-set of projection data from the record of the second sub-set of projection data. Difference images are then reconstructed utilizing the records of difference projection data. The difference images are then mapped to an image generated using the first sub-set of projection data, and the perfusion parameters are determined utilizing the mapped difference image. 
    
    
     BRIEF DESCRIPTION OF DRAWINGS 
     FIG. 1 is a pictorial view of a CT imaging system; 
     FIG. 2 is a block schematic diagram of the system illustrated in FIG. 1; and 
     FIG. 3 is a flow chart illustrating the steps executed by the CT system to calculate perfusion parameters. 
    
    
     DETAILED DESCRIPTION 
     Referring to FIGS. 1 and 2, a computed tomography (CT) imaging system  10  is shown as including a gantry  12  representative of a “third generation” CT scanner. Gantry  12  has an x-ray source  14  that projects a beam of x-rays  16  toward a detector array  18  on the opposite side of gantry  12 . Detector array  18  is formed by detector elements  20  which together sense the projected x-rays that pass through an object, such as a medical patient  22 . Each detector element  20  produces an electrical signal that represents the intensity of an impinging x-ray beam and hence the attenuation of the beam as it passes through object or patient  22 . During a scan to acquire x-ray projection data, gantry  12  and the components mounted thereon rotate about a center of rotation  24 . In one embodiment, and as shown in FIG. 2, detector elements  20  are arranged in one row so that projection data corresponding to a single image slice is acquired during a scan. In another embodiment, detector elements  20  are arranged in a plurality of parallel rows, so that projection data corresponding to a plurality of parallel slices can be acquired simultaneously during a scan. 
     Rotation of gantry  12  and the operation of x-ray source  14  are governed by a control mechanism  26  of CT system  10 . Control mechanism  26  includes an x-ray controller  28  that provides power and timing signals to x-ray source  14  and a gantry motor controller  30  that controls the rotational speed and position of gantry  12 . A data acquisition system (DAS)  32  in control mechanism  26  samples analog data from detector elements  20  and converts the data to digital signals for subsequent processing. An image reconstructor  34  receives sampled and digitized x-ray data from DAS  32  and performs high speed image reconstruction. The reconstructed image is applied as an input to a computer  36  which stores the image in a mass storage device  38 . 
     Computer  36  also receives commands and scanning parameters from an operator via console  40  that has a keyboard. An associated cathode ray tube display  42  allows the operator to observe the reconstructed image and other data from computer  36 . The operator supplied commands and parameters are used by computer  36  to provide control signals and information to DAS  32 , x-ray controller  28  and gantry motor controller  30 . In addition, computer  36  operates a table motor controller  44  which controls a motorized table  46  to position patient  22  in gantry  12 . Particularly, table  46  moves portions of patient  22  through gantry opening  48 . In one embodiment, a third generation CT scanner with a digital flat panel read-out capable of imaging a 20 cm volume along a patient view axis is utilized. 
     FIG. 3 is a flow chart  50  illustrating the steps executed to determine perfusion parameters. The method illustrated in FIG. 3 can be practiced by DAS  32  (shown in FIG.  2 ), image reconstructor  34  (shown in FIG.  2 ), or computer  36  (shown in FIG.  2 ). Generally, a processor in at least one of DAS  32 , reconstructor  34 , and computer  36  is programmed to execute the process steps described below. Of course, the method is not limited to practice in CT system  10  and can be utilized in connection with many other types and variations of imaging systems. 
     Referring specifically to FIG. 3, a set of scan data is acquired  52  with table  46  stationary. The scan data is pre-processed to generate a projection data. In one embodiment, a first sub-set of the projection data set is acquired prior to the injection  54  of contrast media to patient  22 . In another embodiment, the first sub-set of projection data is acquired, or after, as the contrast media is injected into patient  22  but before the contrast medium is sufficiently absorbed by the patient to impact the collected data. The first sub-set of projection data is sometimes referred to herein as reference data. In one embodiment, the reference data set is acquired at a low speed, e.g. sixty projections per second, to enable an artifact free image reconstruction. 
     A second sub-set of projection data is acquired  56  after contrast media is absorbed by patient  22 , i.e., after contrast media uptake. The second sub-set of projection data corresponds to the reference data set for each view. For example, in one embodiment, the reference data set is acquired during a single rotation of gantry  12  and a full-set of data is collected, e.g., approximately nine-hundred-and-eighty-four views are collected. The second sub-set of projection data is acquired faster than the reference data set. The second sub-set of projection data is acquired during a single rotation of gantry  12  and approximately sixty views are collected. In another embodiment, when the second sub-set of projection data is acquired, approximately thirty views are collected. The second sub-set of projection data is acquired before the contrast medium absorbed by the patient begins to dissipate from the tissues. 
     A difference projection data set is determined  58  by subtracting, for each view, the corresponding projection data in the reference data set from the second sub-set of projection data. In the difference projection data set, the human anatomy related structures are removed while data for vessels and tissues that have absorbed the contrast media remain. The projection data set is utilized to generate a difference image. Because projection data has to be acquired before the contrast medium dissipates from the tissues, e.g., the data must be collected quickly such that the amount of change between data sets is relatively small. There is not enough time to collect a complete set of views, e.g., approximately nine-hundred-eighty-four views. Therefore, approximately thirty to sixty views are collected for the second data set. 
     In one embodiment, an algebraic reconstruction technique is utilized to reconstruct  60  a set of difference images from the difference projection set. Of course, other image reconstruction techniques can be utilized. Once the difference image is generated, it is mapped  62 , e.g., a one-to-one correspondence is performed, against an original image produced from the reference data set. The set of difference images is used to determine  64  perfusion parameters, e.g., MTT, CBF, and CBV, by comparing contrast uptake in the region of interest to contrast uptake in a main artery. 
     In one embodiment, a plurality of difference projections are determined and a difference image for each view is determined by subtracting the reference projection data from a particular projection acquisition. For example, the difference projection of the 1 st  sub-set of projection data, e.g., reference projection data, and a 3 rd  sub-set of projection data is used to determine the difference images at the time of the 3 rd  projection acquisition. The difference image of the 3 rd  projection acquisition is determined by subtracting the reference projection data from the 3 rd  sub-set of projection data for the same view angles. Therefore, the difference image of an n th  sub-set projection acquisition is determined by subtracting the reference projection data from the n th  sub-set of projection data. 
     In an alternative embodiment, difference projections of adjacent projection sets are utilized to determine the difference image. For example, the difference projection of the n th  sub-set of projection data and an m th  sub-set of projection data is used to arrive at the difference image between the n th  and the m th  acquisition, where m&gt;n. For instance, the difference projection of the 7 th  projection acquisition is determined by subtracting the 6 th  sub-set of projection data from the 7 th  sub-set of projection data. In addition, the difference projection of the 8 th  projection acquisition is determined by subtracting the 7 th  sub-set of projection data from the 8 th  sub-set of projection data. Of course, various incremental values can be utilized when determining a difference projection. For example, in one embodiment, an 8 th  projection acquisition can be determined by subtracting the 6 th  sub-set of projection data from the 8 th  sub-set of projection data. Then the difference image is generated by accumulating the difference images of all prior acquisition pairs. 
     In yet another embodiment, CT system  10  includes a computer program residing on a computer-readable medium within mass storage  38  for reconstructing the difference image. The program includes a plurality of rules to reconstruct a difference image from a plurality of records of projection data stored on the computer-readable medium. The program utilizes a plurality of rules to determine perfusion parameters from the difference image. 
     For cardiac imaging, the heart is in continuous motion during the entire data acquisition period. Therefore, the difference image contains not only the difference due to the absorption of contrast media, but also the motion of the heart. As a result, the difference image contains higher frequency components, and an increased number of projection views are used in image reconstruction. Using an increased number of views results in prolonging the data acquisition which, in turn, is further influenced by heart motion. 
     To reduce the influence of the heart motion, in one embodiment, the data acquisition speed, e.g., gantry  12  rotation speed, is synchronized with the heart rate. The projections of the same angle will then correspond to the same phase of the heart motion. This same technique can be used to examine brain perfusion. Then, only a few projections, e.g., sixty projections, are used to accurately reconstruct the difference images due to contrast uptake. 
     In another embodiment, the difference images for a perfusion study are used to reduce cone-beam related artifacts. Specifically, the difference projections contain only low-contrast and low-frequency information. Therefore, cone beam related image artifact are suppressed by using cone beam reconstruction techniques, e.g., Feldkamp algorithm, to perform perfusion studies of relatively large cone angles. 
     While the invention has been described in terms of various specific embodiments, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the claims.