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SCATTER ELIMINATION TECHNIQUE AND
APPARATUS IN RADIONUCLIDE EMISSION
AND TRANSMISSION IMAGING IN A
NUCLEAR CAMERA

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BACKGROUND OF THE INVENTION

The present invention relates to the elimination of scattered photons from transmission and emission images and, in particular, to the elimination of such photons as a function of pixel location.

The problem of Compton scattering is well-known in gamma cameras. This scattering results in photons appearing to have originated at incorrect locations. Some of these photons can be ignored on the basis of their significantly ^ reduced energy, but others have energy levels comparable to the unscattered photons.

In the typical 50 to 500 keV operating region of gamma cameras, small scattering angles are much more probable than large angles. Therefore, scattered photons still have a 20 high probability of passing through a collimator. The finite energy resolution of gamma cameras (8 to 10 percent) prevents discrimination of the slight energy shift caused by scattering. Because of varying angle, scattered photons detected in the camera point in the "wrong" direction and 25 decrease image quality. Because of the detection of photons emitted not only from the region of interest inside the patient body but also photons scattered from other regions, scattered photons make accurate quantitative analysis impossible.

Traditional SPECT cameras are increasingly being 30 employed for transmission scanning operations in conjunction with the standard emission study. A transmission scan uses an external radioactive source to quantify distribution of tissue densities. The information is used to correct for the nonuniform attenuation during emission study. 35

The photons of the transmission source are subject to the same Compton scattering process that occurs with emission photons. No current transmission scanning approach uses scatter elimination techniques to remove Compton-scattered events form the transmission images. The quantitative accu- 40 racy of the attenuation maps derived from these studies is therefore undefined.

Scatter elimination improves the resolution of an image, increases the contrast between "hot" (or radioactive high 45 uptake) areas and "cold" ones in an emission study, allows measurement of attenuation coefficients for "narrow beam" geometry for a transmission study, and makes accurate quantitative analysis possible for both types of studies.

Because of the nature of emitted photons and the method 50 of their detection, the energy of photons can be measured only with limited accuracy. Instead of a single spectral line in the energy domain, one has to deal with a photon spectrum or energy distribution (the number of events within a certain energy ranges). The spectrum is characterized by its 55 shape and a few parameters, such as, the energy corresponding to a centroid of a spectrum, and spectrum full width at half of maximum (FWHM). It is a well known fact that the spectrum of "direct" unscattered photons is characterized by a Gaussian distribution. go

It is important to keep in mind the Compton scattering is object dependent, because it depends on the distribution of the radioisotope inside the patient's body. Also, it is a tbjee-dimensional phenomenon, since photons are emitted isotropically within the subject. In addition, it is not space 65 uniform: it varies across the camera surface. This nonuniformity in the number of scattered photons detected by

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the camera results from its dependence on the subject, that is, the materials through which the photon should pass before detection by a camera. Therefore, the scatter content of an emission image will vary from patient to patient, from view to view at various angles around the same patient, and from area to area within the same view.

Various spatially independent methods have been proposed for reducing the scatter error, but these methods suffer greatly from the fact that the scatter error is typically very spatially dependent. The scatter error will spatially vary from patient to patient, from view to view at various angles around the same patient, and from area to area in the same view.

Various spatially dependent methods have also been proposed. These include dividing the photopeak region into two subwindows where the ratio of counts (or subwindow sizes adjusted to equal counts) is assumed to be a measure of scatter content. A fraction of events is removed from the lower subwindow on a pixel by pixel basis. This ignores the fact that many scattered photons will have been collected in the upper subwindow.

U.S. Pat. No. 5,371,672 estimates the number of scattered photons detected in each pixel from the number of events acquired within two narrow windows located on each side of the photopeak window. The contribution of the scattered events in the photopeak window is estimated as a trapezoidal area calculated to fit the counts in the narrow subwindows. The very small subwindows result in very noisy counting statistics and unreliable results on a pixel by pixel basis. In addition the assumed trapezoidal shape of the scatter function is not quantitatively accurate.

U.S. Pat. Nos. 4,839,808 and 5,081,581, incorporated herein by reference, require knowledge of a scatter-free spectrum and assumes the scatter spectrum can be represented by a third-order polynomial. For each pixel, the local spectrum is modeled as the sum of a polynomial approximating the scatter spectrum and a scatter-free spectrum multiplied by a constant Each measured spectrum is fitted to this model to obtain polynomial coefficients and the constant In practice, this method requires fine spectrum resolution and is very unstable, especially for pixels with low counts. The procedure for fitting spectra with two different functions assumes knowledge of these functions, for example, the order of the scatter spectrum polynomial. The method also requires knowledge of the camera's response with respect to photon energy.

U.S. Pat. No. 5315,506 adds an energy regularization term which allows the use of separate parameters for each energy channel within the fitting window. In this method higher order polynomials can be used or non-polynomial functions. This method also suffers from requiring knowledge of the scatter-free response of the camera and is even more computationally demanding.

U.S. Pat. No. 5,293,195 also uses a spectrum fitting approach. For the scatter function, a calculation of the probability of how many scatter interactions a photon has undergone based on the Nishina-Klein equations is performed. Besides the requirement of knowing the scatter-free response of the camera, this method requires knowledge of the relevant physical model for the scattering spectra. Lack of this knowledge results in substantial inaccuracy.

The weakness of all of these methods are exacerbated in the case of combination transmission and emission imaging. This type of imaging is finding increased use in a quest to provide corrections for image inaccuracies caused by variations in the subject's composition and geometry. The tra

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versing of the entire subject by transmission photons greatly within an energy window 14, the event is stored in the

increases the opportunity for scatter. uncorrected image memory 16. The memory 16 stores the

number of events or the count at each x,y location. The

SUMMARY OF THE INVENTION window 14 typically represents the photopeak area of the

The method for eliminating scattered photons from trans- 5 detected enerSy spectrum. For example, the photopeak winmission or emission images includes collecting a planar dow ^ correspond to plus or minus 10 percent about a photon image formed by collecting a count of detected Une of ^ radioisotope in use. For Tc-99m, a photons in a large matrix of pixels, each pixel including sPectni ^ exists at 140 keV and the corresponding phoposition coordinates and an energy spectrum for photons *°peak area is 126 keV to 154 keV. collected at the position coordinates. The image is divided 10 The data fr°m the camera 12 also follows a path where it into a plurality of local areas, each local area including at is stored in a multichannel acquisition memory 18. The least one pixel. A local energy centroid is calculated for each memory 18 stores not only the position (at the detector) of local area and a total energy centroid for the image is the event but also its energy, thus each position or pixel has calculated. a corresponding energy spectrum consisting of the number

The spectra of local areas having respective energy cen- 15 of events or counts at various energy levels. Data from the

troids less than a known threshold percentage of the total memory 18 is analyzed to create a correction table 20 The

energy centroid are used to estimate a local scatter correction values fr°mthe correction table 20 are combined with the

factor for each local area that are applied to the image. dataln *e memo^ 16 tou CTeat^ 3 corrected image 22. The

corrected image 22 may be used directly, or more typically,

BRIEF DESCRIPTION OF THE DRAWINGS 20 undergoes further processing such as additional error correction and/or inclusion into 3-D images.

FIG. 1 is a schematic diagram of a nuclear camera for Referrmg to FIGS. 3 and 4, a flow chart shows the

producing emission images. anal is rformed on the ^ stored m me muitichannel

FIG. 2 is a schematic diagram of a nuclear camera for memory 18 to create the correction table 20 which is applied

producing transmission images. 25 t0 the uncorrected image in memory 16 to produce the

FIG. 3 is a block diagram of a data processing system corrected image 22.

suitable for performing a method according to the invention. Sufficient counts need to have occurred at the positions of

FIG. 4 is a flow chart diagram of a method according to interest in an image to produce statistically reliable results,

the invention. 3Q For example, 30 counts provides for reasonably reliable

FIG. 5 is an axial end view of a cylindrical phantom. data.

FIG. 6 is a partial plan view of the phantom of FIG. 5 as 111 some cases> mere ^ not be enough positions or

it is to be imaged. pixels with sufficient counts to proceed on a pixel by pixel

TM~, _ . , . .c. . basis. In this case pixels can be grouped together to provide

FIG. 7 is an exemplary graph of the camera image along sufficient data the line S—5 of FIG. 6 showing exemplary data with and 35

without scatter correction according to the invention. For sample, pixels may be grouped together in the form

o • ., i j- r . , • of 2 pixel by 2 pixel (4 pixel by 4 pixel, 8 pixel by 8 pixel,

naSis a blockdiagram ofammtichannelacquisi^ and so on) local areas or boxes.

memory suitable for use with the invention. „, , ,

Choosing local areas larger than a single pixel also may

DESCRIPTION OF THE PREFERRED 40 be desirable for reducing computational overhead, but at the

EMBODIMENT expense of spatial resolution.

Referring to FIG. 1, a simple nuclear camera or gamma * me case of £local ff8 mf a sfSle P^1' an camera for producing emission images consists of a planar ener§y ... for each local area is formed by adding the image detector 2. A subject 3 contains a radioisotope the sPectra of the "^dividual pixels within the local area, emits photons 3 that are detected by the detector 2 to form 45 Whether a local area consists of lxl pixel or greater, an an image of the activity within the subject 2. energy centroid is calculated for each local area based on the

Referring to FIG. 2, a simple nuclear camera for produc- counts obtained at various energy levels. The energy cening transmission images consists of a planar image detector tiolds m calculated by the first momenta method. 2 and a photon source 4 (a radioisotope). Photons 3' travel A*1 of me local area spectra are added and a total energy through the subject 1' to the detector 2. An image of the centroid is calculated for the summed spectra, subject 1'is formed at the detector 2 from the attenuation and It has been found desirable also to exclude local areas other effects upon the transmission through the subject 1' of having very few counts from the process (e.g., less than 30 photons from the source 4. counts).

These cameras can be combined by adding the source 4 to 55 It has been discovered that the best measures of scatter the camera of FIG. 1. This allows transmission studies to be come from the local areas having a local energy centroid less performed to measure such parameters as attenuation by the than a threshold percentage of the total energy centroid. This subject. These parameters can then be used to improve the percentage may be, for example, 95 to 99 percent, with 99 quality of emission studies. percent providing excellent results.

Referring to FIG. 3, a data processing system 10 receives 60 ^ a local energy centroid for a local area is less than the event data from a gamma camera 12. For each event, this threshold, the corresponding spectrum for that local area is data includes the x-coordinate and y-coordinate of the event included in a sum of all such spectra to produce a global in the detection plane, along with the energy value. The scatter curve.

system 10 may be implemented in specialized hardware or The next task is to locally normalize the global scatter as part of a general purpose computer. 65 curve to provide a local scatter curve for each local area.

The data from the camera 12 branches in one path to a It has been discovered that a small window just below the conventional image memory 16. If the energy of an event is low side of the photopeak is the optimal-area for determin

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ing a normalization factor. This energy normalization window can be, for example, the energy range from 15 to 10 percent below a spectral line of the radioisotope in use. For the example of Tc-99m, this would be 119 keV to 126 keV.

A global scatter count is determined from the number of photon counts in the global scatter curve within the energy normalization window.

A local scatter count is determined for each local area from the number of photon counts in the respective local area within the energy normalization window.

The local scatter curves are determined by scaling the global scatter curve by the ratio of the respective local scatter count to the global scatter count

The next task is to determine a local correction factor for each local area.

A local photopeak total count of photons is determined for each local area from the total number of photon counts in the respective local area within the photopeak window.

A local photopeak scatter count of photons is determined for each local area from the number of photon counts in the local scatter curve within the photopeak window.

Subtracting the ratio of the local photopeak scatter count to the local photopeak total count from one gives the local correction factor for each local area. This factor represents a estimate of the number of unscattered photons in the local area photopeak as a fraction of the total photons in the local area photopeak.

The resulting local correction factors can be stored in the table 20 and applied to the uncorrected image memory 16. Multiplication of respective correction factors times the counts stored in each position of the uncorrected image memory results in the corrected image 22.

Referring to FIG. 5, a cylindrical test phantom 24 contains three inner cylinders 26, 28, 30. The cylinder 26 is filled water containing a radioisotope. The cylinder 28 is filled with water containing a lesser concentration of a radioisotope. The balance of the phantom 24 is filled with water.

Referring to FIG. 6, the phantom 24 is shown oriented to match the image plane.

Referring to FIG. 7, a graph of exemplary onedimensional image data is shown for the phantom 24 along the line 5—5. The graph A corresponds to the uncorrected image data and the graph B corresponds to image data Corrected by the invention. It can be seen that both resolution and contrast have been improved.

This elimination of scatter improves the resolution of an image and increases the contrast between "hot" and "cold" areas for emission studies. This method is applicable not only to emission images but also to the increasingly desirable transmission images. It allows measurement of attenuation coefficients for narrow beam geometry for transmission studies. It makes accurate quantitative analysis possible for both types of studies.

Because of the feature of acquiring local spectra, the camera energy response "map" across the camera face is measured without scattering, and this "energy map" with calculated energy centroid locations and peak FWHM for energy spectra at each pixel is stored. This map can be used during scatter correction as a table, but it also can be displayed as an image for quick inspection to make a decision if a new energy calibration is necessary.

As an additional feature, if the scatter curve is too noisy because of low statistics of events in local areas with "pure scattering", the scatter curve could be smoothed.

In order to verify the method for scatter removal, experimental studies were performed with a simple phantom. The

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phantom was a 20 cm diameter cylinder of 20 cm length. It contained three 5 cm cylinders inserted into the larger one (see FIGS. 5 and 6). The smaller cylinders could be filled with a water solution of Tc-99m of known activity. The outer

5 cylinder could be empty, filled with inert water, or filled with water containing some background activity. Also, the inverse situation was addressed where activity was inserted in the outer cylinder and the inner cylinders could be empty, filled with inert water, or filled with water containing some

10 background activity. In addition, scatter media consisting of 6 cm Lucite plates was inserted between the phantom and the collimator of the camera for some measurements in all cases the planar images of the phantom were acquired and analyzed in detail. The cylinder, with or without Lucite

15 layers, was placed on the collimator in a vertical or horizontal orientation (the axis of the cylinder oriented perpendicular or parallel to the collimator surface, respectively). In experiments using Lucite layers, the cylinder was placed on a special support, that allowed the easy insertion of layers

20 between the cylinder and collimator surface.

The images of the phantom were acquired simultaneously in two acquisition memories: one with the standard information of the spatial location of an event and, a second, special multichannel acquisition memory, which in addition

25 to spatial (x,y) information of an event stored the energy spectrum of the events accumulated in a particular location.

Initially, activity was placed in a small cylinder and the outer cylinder filled with water. The image acquired in the multichannel acquisition memory was analyzed for the local

3o area, or boxes, consisting of 2x2 pixels (box size of 7.2 mm). The spectra for different image areas were reconstructed. To describe the spectra, two parameters were used: spectra centroid location calculated by first momenta method and spectrum width—or peak FWHM. The areas were chosen

35 starting from the middle of the bright area corresponding to an image of the central part of the small cylinder filled with activity (so-called "hot" area), following in the direction towards the edge of the hot area and continuing into a dark (or so called "cold") areas. It was found that across the hot

40 area, the spectra shape remains basically constant with distinguishable change at the edge and gradual changing as the area under investigation is moved away from the hot area. The parameter more sensitive to spectrum change was found to be the centroid location, which was used therefore

45 for further analysis.

For Tc-99m, the centroid location of box spectra changed less than 0.5 percent across the hot area, dropped about 1 percent at the edge, and shifted into the direction of smaller energies a few percent as boxes moved away from the hot

so area into the cold region where only the scattered photons contribution can be considered. The gradual shift of the centroid location of spectra is the result of larger contribution of photons of higher orders of scattering and photons the undergo only one scatter interaction, but with larger angle

55 and larger energy transfer (so their resulting energy became lower).

Boxes were identified whose centroid location was shifted more than 1 percent in comparison with the centroid location for the image as a whole to obtain a scatter curve (or scatter

60 function). The number and locations of chosen pixels were different with only one limitation of sufficient counting statistics to reconstruct the spectrum inside the box. For those boxes, the spectra were added to each other to result in a scatter curve. It was found that the shape of the resulting

65 scatter curve is basically constant, and practically does not change for a particular study. The curve shape does change for different studies, for example, when using additional

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