JP2011153975A - Nuclear medicine diagnosis device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a nuclear medicine diagnosis device capable of performing scattering correction by using information based on energy information. <P>SOLUTION: Coincidence data outputted from a coincidence circuit 35 are discriminated and classified into total coincidence data and coincidence data of each γ-ray having a deep detection layer of a γ-ray detector 32 having a prescribed depth by a detection depth information discrimination part 41 based on detection depth information which is information showing a detection depth of incidence of the γ-ray into the γ-ray detector 32. Scattering correction of the coincidence data is performed by a scattering correction part 43 based on the coincidence data of each γ-ray having the deep detection layer classified by the detection depth information discrimination part 41, to thereby perform scattering correction by using the detection depth information based on the energy information. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a nuclear medicine diagnostic apparatus for obtaining nuclear medicine data of a subject based on radiation generated from the subject to which a radiopharmaceutical is administered.

  As the above-described nuclear medicine diagnosis apparatus, that is, an ECT (Emission Computed Tomography) apparatus, a PET (Positron Emission Tomography) apparatus will be described as an example. The PET apparatus detects a plurality of gamma rays generated by annihilation of positrons, that is, positrons, and reconstructs a tomographic image of a subject only when the gamma rays are simultaneously detected by a plurality of detectors. It is configured.

  Specifically, a radiopharmaceutical containing a positron emitting nuclide is administered into a subject, and a 511 KeV pair annihilation gamma ray released from the administered subject consists of a group of a number of detection elements (for example, scintillators). Detect with a detector. And if γ-rays are detected at the same time by two detectors within a certain period of time, they are counted as a pair of annihilation γ-rays, and the point of occurrence of pair annihilation is on the straight line of the detected detector pair Is identified. By accumulating such coincidence information and performing reconstruction processing, a positron emitting nuclide distribution image (ie, a tomographic image) is obtained.

In order to detect γ rays at the same time (simultaneous counting), each γ ray is input to the coincidence circuit, and it is determined whether or not the time difference between the input γ rays falls within a predetermined time window. In an actual coincidence circuit, γ rays detected within a very short time window of about 4 ns to 20 ns (ns = 10 ⁻⁹ s) are generally regarded as “simultaneous”. Therefore, there is a possibility that one of γ rays generated at two different points is counted simultaneously. This is called “random coincidence”. On the other hand, when one or both of the pair of γ-rays are simultaneously counted after causing Compton scattering in the subject, this is called “scatter coincidence”. In addition, when both of a pair of γ rays are counted simultaneously, this is called “true coincidence”.

  In order to ensure the quantitativeness of the image in the nuclear medicine diagnosis, the above-described accurate correction of the scattering coincidence count (for example, subtraction processing from all coincidence count data) is necessary. Scattering components are detected in a shape with a flat spread around the actual radioactivity distribution, so a low-pass filter (LPF: Low) is added to the measurement data (true coincidence + scattering coincidence image or sinogram). A method of obtaining a scattering component by applying a Pass Filter (this method is referred to as “Method 1”), and a method of simulating scattering during measurement in consideration of the image including scattering and the distribution of the absorber (this is referred to as “ Method 2 ”) is commonly used.

  In an apparatus in which a plurality of energy windows can be set, two or more coincidence data is constructed based on the energy information, and coincidence data including only a small angle scattering component (that is, coincidence data with few scattered rays). ) And total coincidence data with high statistical accuracy are constructed, and a method of performing scatter correction of all coincidence data (this is referred to as “method 3”) is performed. Among these three methods, the method 3 using energy information can maintain the highest quantitativeness (see, for example, Patent Document 1 and Non-Patent Document 1).

  In the above-described method 3 described as the conventional method, coincidence data (in Japanese Patent Application Laid-Open No. 2004-151867) that is simultaneously counted between energy windows (UEW: Upper Energy Window) higher than a predetermined threshold (for example, 500 KeV, 511 KeV, or 600 KeV). Fig. 4 (see Fig. 1 of non-patent literature)) Estimates the scattering component (see "scattered rays" in Fig. 5 of patent literature 1) by a simple deconvolution method, and calculates the scattering component. The true coincidence UEW data is obtained by subtraction. Then, all coincidence data (FIG. 4 of Patent Document 1, non-patent document) simultaneously counted in the total energy (SEW: Standard Energy Window) in a predetermined range (for example, the lower limit value is 300 KeV to 400 KeV and the upper limit value is 600 KeV to 800 KeV). By subtracting the data obtained by amplifying the true coincidence UEW data from the literature (Fig. 1), SEW data with only scattered components is estimated. Further, smoothing processing (smoothing) for noise removal is applied to the estimated SEW data, and finally the SEW data of only the scattering component is obtained, and then the scattering finally obtained from the total coincidence data is obtained. By subtracting the SEW data of only the components, true coincidence data that does not include the scattering components can be obtained. In this way, the scattering of the coincidence data is corrected (see FIG. 5 of Patent Document 1 and FIG. 2 of Non-Patent Document).

JP 2007-218769 A (page 1-8, FIGS. 1, 3-5, 7)

Tetsuro Mizuta, et al .: Quantitative evaluation of scatter correction and absorption correction of Shimadzu 3D PET

  However, since the threshold value of the energy window for setting the UEW (as described above, for example, 500 KeV, 511 KeV, or 600 KeV) is set near the photoelectric peak, if the photoelectric peak channel indicating the detector output changes even slightly, the UEW The count (count value) increases or decreases, causing fluctuations in the pixel value. The output of the detector can change depending on the operating temperature of the detector, the change in the characteristics of the detection element, and the bias on the circuit. However, it is difficult to fundamentally take these measures.

  The present invention has been made in view of such circumstances, and an object thereof is to provide a nuclear medicine diagnostic apparatus that can perform scattering correction using information according to energy information.

In order to achieve such an object, the present invention has the following configuration.
That is, the nuclear medicine diagnostic apparatus according to the present invention is a nuclear medicine diagnostic apparatus for obtaining nuclear medical data of a subject based on radiation generated from the subject to which a radiopharmaceutical is administered,
Radiation detecting means for detecting the radiation;
A coincidence counting means for determining whether or not radiation is simultaneously detected by the radiation detection means, and outputting the simultaneously detected radiation as coincidence counting data;
The coincidence count data output by the coincidence counting unit is obtained by combining all coincidence count data and a predetermined depth based on detection depth information which is information indicating a detection depth at which radiation enters the radiation detection unit. A first coincidence classification unit that classifies the radiation detection unit of the radiation detection unit into deep coincidence count data;
The detection layer classified by the first coincidence classification unit includes scatter correction means for performing scatter correction of coincidence data based on coincidence data between deep radiation.

  [Action / Effect] When radiation generated from a subject to which a radiopharmaceutical is administered is incident on the radiation detection means, the scattering component with low incident energy interacts with the detection depth shallow from the low energy. Easy to wake up. On the other hand, radiation with a high incident energy has higher transmission characteristics than radiation with a low energy, so that interaction is likely to occur in a region with a deep detection depth, and the data detected in that region has a high probability of being high energy. It is predicted. Therefore, according to the nuclear medicine diagnosis apparatus according to the present invention, instead of the conventional energy information, the coincidence counting unit is based on detection depth information which is information indicating a detection depth at which radiation enters the radiation detection unit. The first coincidence classification means classifies the coincidence count data output in step 1 into total coincidence data and coincidence count data between radiations having a predetermined depth and a deep detection layer of the radiation detection means. Based on the coincidence data between the radiations having deep detection layers classified by the first coincidence classification unit, the scattering correction unit performs scattering correction of the coincidence data, so that the detection depth information according to the energy information is obtained. Can be used to perform scattering correction. Moreover, the influence by the fluctuation | variation of the photoelectric peak position in energy information can be avoided.

  In the above-described invention, the scattering correction may be performed using energy information in addition to the detection depth information. That is, the second coincidence classification unit that classifies the coincidence data output by the coincidence unit into total coincidence data and coincidence data having an energy window higher than a predetermined value based on the energy information of radiation. And the scatter correction unit may perform scatter correction of the coincidence data based on the coincidence data having a high energy window classified by the second coincidence classification unit.

  In addition, when performing scatter correction using energy information in addition to detection depth information, it is preferable to perform classification and scatter correction as follows. In other words, the second coincidence classification means outputs coincidence data between radiations with deep detection layers classified by the first coincidence classification means, total coincidence data between radiations with deep detection layers, and radiation with deep detection layers. Are classified into coincidence data having a high energy window, and the scatter correction means converts the radiation into the coincidence data having a high energy window between radiations having a deep detection layer classified by the second coincidence classification means. Based on the coincidence data of the deep counting radiation, the detection layer after the scattering correction is performed based on the coincidence counting data of the deep radiation. preferable.

  In these inventions described above, the radiation detection means is configured by laminating a plurality of layers in the depth direction in which the radiation is incident, and when the first layer, the second layer,. It is preferable that the first coincidence classification means classifies the coincidence data of the radiation detected together in the above as coincidence data of the radiation having a deep detection layer.

  When radiation is incident on the radiation detection means, the scattering component with low incident energy tends to interact with the shallow first layer, and the radiation with high incident energy interacts with the deep region after the second layer. It is easy to cause. Therefore, the coincidence data of the radiation detected together in the second and subsequent layers is classified as coincidence data of the radiation having a deep detection layer. By classifying in this way, the probability that the coincidence count data between radiations with deep detection layers is high energy is increased.

  In order to further improve the probability that the coincidence data between the radiations having deep detection layers has high energy, the coincidence data of the radiation detected together in the deepest layer is converted into the first coincidence classification means by the detection layer. It is more preferable to classify as deep coincidence count data.

  According to the nuclear medicine diagnostic apparatus according to the present invention, the coincidence counting data output by the coincidence counting unit is all based on the detection depth information that is information indicating the detection depth at which radiation enters the radiation detecting unit. The first coincidence classification unit classifies the coincidence data into coincidence data between radiations having a predetermined depth and a deep detection layer of the radiation detection unit. Based on the coincidence data between the radiations having deep detection layers classified by the first coincidence classification unit, the scattering correction unit performs scattering correction of the coincidence data, so that the detection depth information according to the energy information is obtained. Can be used to perform scattering correction.

It is a side view of the PET apparatus which concerns on each Example. 1 is a block diagram of a PET apparatus according to Example 1. FIG. It is the schematic of the specific structure of a gamma ray detector. It is the figure which showed typically the discrimination and classification in the detection depth information discrimination part which concerns on Example 1. FIG. 7 is a flowchart illustrating a flow of processing related to scattering correction in a scattering correction unit according to the first embodiment. 7 is a flowchart illustrating a flow of processing related to scattering correction in a scattering correction unit according to the first embodiment. 7 is a flowchart illustrating a flow of processing related to scattering correction in a scattering correction unit according to the first embodiment. 6 is a block diagram of a PET apparatus according to Embodiment 2. FIG. (A) is an energy spectrum representing a count value of γ rays with respect to energy, and (b) is an energy distribution of each γ ray to be subjected to coincidence counting. It is the figure which showed typically the discrimination and classification | category in the detection depth information discrimination part and energy discrimination part which concern on Example 2. FIG. 10 is a flowchart illustrating a flow of processing related to scattering correction in a scattering correction unit according to the second embodiment. 10 is a flowchart illustrating a flow of processing related to scattering correction in a scattering correction unit according to the second embodiment. 10 is a flowchart illustrating a flow of processing related to scattering correction in a scattering correction unit according to the second embodiment.

Embodiment 1 of the present invention will be described below with reference to the drawings.
FIG. 1 is a side view of the PET apparatus according to the first embodiment, and FIG. 2 is a block diagram of the PET apparatus according to the first embodiment. In Example 1, including Example 2 described later, a PET (Positron Emission Tomography) apparatus will be described as an example of a nuclear medicine diagnosis apparatus.

  As shown in FIG. 1 including Example 2 described later, the PET apparatus 1 according to Example 1 includes a top plate 2 on which a subject M in a horizontal posture is placed. The top plate 2 is configured to move up and down and translate along the body axis of the subject M. The PET apparatus 1 includes a PET detection unit 3 that diagnoses a subject M placed on the top 2. The PET apparatus 1 corresponds to the nuclear medicine diagnostic apparatus in this invention.

  The PET detector 3 includes a gantry 31 having an opening 31a and a γ-ray detector 32 that detects γ-rays generated from the subject M. The γ-ray detector 32 is arranged in a ring shape so as to surround the body axis of the subject M, and is embedded in the gantry 31. The γ-ray detector 32 includes a scintillator block 32a, a light guide 32b, and a photomultiplier tube (PMT) 32c (see FIG. 3). The scintillator block 32a includes a plurality of scintillators. The scintillator block 32a converts the γ-rays generated from the subject M to which the radiopharmaceutical has been administered into light, the light guide 32b guides the converted light, and the photomultiplier tube 32c photoelectrically converts the light into electricity. Output to signal. The γ-ray detector 32 corresponds to the radiation detection means in this invention. A specific configuration of the γ-ray detector 32 will be described later with reference to FIG.

  Subsequently, a block diagram of the PET apparatus 1 will be described. As shown in FIG. 2, the PET apparatus 1 includes a console 4 in addition to the top plate 2 and the PET detection unit 3 described above. The PET detection unit 3 includes an amplifier 33, an AD converter 34, and a coincidence counting circuit 35 in addition to the gantry 31 and the γ-ray detector 32 described above. The coincidence circuit 35 corresponds to the coincidence means in the present invention.

  The console 4 includes a detection depth information discrimination unit 41, a scattering correction unit 43, an image reconstruction unit 44, a memory unit 45, an input unit 46, an output unit 47, and a controller 48. The detection depth information discriminating unit 41 corresponds to the first coincidence classification unit in the present invention, and the scattering correction unit 43 corresponds to the scattering correction unit in the present invention.

  The amplifier 33 amplifies the electrical signal detected and output by the γ-ray detector 32. The AD converter 34 converts the analog value of the electric signal amplified by the amplifier 33 into a digital value and outputs the digital value.

  The coincidence circuit 34 determines whether or not γ rays are simultaneously detected (that is, coincidence) by the γ ray detector 32. The coincidence count data (emission data) simultaneously counted by the coincidence counting circuit 51 is sent to the detection depth information discriminating unit 41 of the console 4.

  The detection depth information discriminating unit 41 calls the coincidence count data (in the first embodiment, the coronal section of the sinogram) as each data (in this specification, “Depth data” and “All data”) based on the detection depth information. 4 (see “Depth” and “All” in FIGS. 4 and 5 to 7)). Here, the detection depth information is information indicating the detection depth (see r in FIG. 3) at which the γ-rays are incident on the γ-ray detector 32, and includes the second embodiment described later. In the first embodiment, the information is for each layer of the scintillator block 32a (see FIG. 3) of the γ-ray detector 32.

  The scatter correction unit 43 calculates the coincidence data based on the coincidence data (here, the coronal cross section of the sinogram) of the gamma rays having a deep detection layer of the gamma ray detector 32 classified by the detection depth information discrimination unit 41. Scatter correction is performed. The scatter correction unit 43 sends the coincidence count data after the scatter correction to the image reconstruction unit 44. The image reconstruction unit 44 reconstructs the coincidence count data after the scattering correction and generates a tomographic image.

  The memory unit 45 receives, via the controller 48, the data obtained by the PET detection unit 3, the data classified by the detection depth information discrimination unit 41, the data and the image subjected to the scatter correction by the scatter correction unit 43, and the like. Data such as tomographic images reconstructed by the reconstruction unit 44 is written and stored, read out as necessary, and each data is sent to the output unit 47 via the controller 48 and output. The memory unit 45 is configured by a storage medium represented by ROM (Read-only Memory), RAM (Random-Access Memory), and the like.

  In the first embodiment, including the second embodiment described later, the memory unit 45 stores in advance an amplification factor for amplifying depth data described later in a series of scattering correction processes in the scattering correction unit 43. Department. When the depth correction is performed by the scattering correction unit 43 using the amplification factor, the amplification factor stored in the amplification factor memory unit is read out.

  The input unit 46 sends data and commands input by the operator to the controller 48. The input unit 46 includes a pointing device represented by a mouse, a keyboard, a joystick, a trackball, a touch panel, and the like. The output unit 47 includes a display unit represented by a monitor and the like, a printer, and the like.

  The controller 48 comprehensively controls each part of the PET apparatus 1 according to the first embodiment including the second embodiment described later. The controller 48 includes a central processing unit (CPU). Each data obtained by the PET detection unit 3, data classified by the detection depth information discrimination unit 41, data subjected to scattering correction by the scattering correction unit 43, and tomographic image reconstructed by the image reconstruction unit 44 Such data is written to the memory unit 45 via the controller 48 and stored, or sent to the output unit 47 for output. When the output unit 47 is a display unit, output display is performed, and when the output unit 47 is a printer, output printing is performed.

  The γ-rays generated from the subject M to which the radiopharmaceutical is administered are converted into light by the scintillator block 32a (see FIG. 3) of the corresponding γ-ray detector 32 among the γ-ray detectors 32, and the converted The photomultiplier 32c (see FIG. 3) of the γ-ray detector 32 photoelectrically converts the light and outputs it as an electrical signal. The electric signal is sent to the amplifier 33 together with the coincidence circuit 35 as image information (pixel value).

  Specifically, when a radiopharmaceutical is administered to the subject M, two γ rays are generated due to the disappearance of the positron of the positron emission type RI. The coincidence circuit 35 checks the position of the scintillator block 32a (see FIG. 3) of the γ-ray detector 32 and the incident timing of the γ-ray, and two scintillator blocks 32a that are opposite to each other with the subject M interposed therebetween. Only when γ rays are incident at the same time (that is, when simultaneous counting is performed), the sent image information is determined as appropriate data. When γ rays are incident only on one of the scintillator blocks 32a, the coincidence counting circuit 35 treats it as noise instead of γ rays generated by the disappearance of the positron, and determines that the image information sent at that time is also noise. Dismiss.

  The image information sent to the coincidence counting circuit 35 is sent to the detection depth information discriminating unit 41 as coincidence counting data (emission data). Based on the detected depth information, the detected depth information discriminating unit 41 detects the coincidence count data, the All data as all coincidence count data, and a predetermined depth (second layer in the first embodiment). The data is classified into depth data, which is coincidence data between γ rays with deep layers, and sent to the scattering correction unit 42. The scatter correction unit 42 performs scatter correction on the coincidence count data based on the depth data classified by the detection depth information discriminating unit 41, and sends the coincidence count data after the scatter correction to the image reconstruction unit 44. The image reconstruction unit 44 reconstructs the coincidence count data after the scatter correction and generates a tomographic image.

  Next, a specific configuration of the γ-ray detector 32 according to the first embodiment will be described with reference to FIG. FIG. 3 is a schematic diagram of a specific configuration of the γ-ray detector.

  The γ-ray detector 32 includes a scintillator block 32a configured by combining a plurality of scintillators that are detection elements having different decay times in the depth direction, a light guide 32b optically coupled to the scintillator block 32a, and a light guide And a photomultiplier tube 32c optically coupled to 32b. Each scintillator in the scintillator block 32a detects γ-rays by emitting light by the incident γ-rays and converting it to light. The scintillator block 32a does not necessarily need to be combined with scintillators having different decay times in the depth direction (r in FIG. 3). Further, although two layers of scintillators are combined in the depth direction, the scintillator block 32a may be configured by a single layer scintillator.

  Next, discrimination / classification in the detection depth information discrimination unit 41 and scattering correction in the scattering correction unit 43 will be described with reference to FIGS. FIG. 4 is a diagram schematically illustrating discrimination / classification in the detection depth information discrimination unit according to the first embodiment, and FIGS. 5 to 7 relate to scattering correction in the scattering correction unit according to the first embodiment. It is a flowchart which shows the flow of a process.

  As shown in FIG. 3, the γ-ray detector 32 is configured by laminating a plurality of layers (two layers in FIGS. 3 and 4) in the depth direction (r in FIG. 3) where the γ-rays are incident. When the first layer, the second layer,... From the incident order, as shown in FIG. 4, the detected depth information discriminating unit 41 uses the coincidence count data of the γ rays detected together in the second layer and later. Discriminated and classified as coincidence data between γ rays with deep detection layers. More preferably, the coincidence count data of γ rays detected together in the deepest layer is discriminated and classified as coincidence count data of γ rays with deep detection layers by the detection depth information discriminating unit 41.

  In Example 1, including Example 2 described later, as shown in FIGS. 3 and 4, the γ-ray detector 32 is a combination of two scintillator blocks 32a (see FIG. 3) in the depth direction. As shown by the dotted line in FIG. 4, the coincidence data of γ rays detected together in the second layer is classified into Depth data which is coincidence data of γ rays deep in the detection layer. Note that the solid line in FIG. 4 is the coincidence count data of γ rays detected at least in the first layer. All coincidence count data including the dotted line of FIG. 4 and the solid line of FIG.

  In the first embodiment, the γ-ray detector 32 is configured by combining a plurality of scintillators having different attenuation times in the depth direction, so that the depth direction is discriminated. However, the present invention is not limited to this. Each γ-ray detector 32 may be assembled in the depth direction as long as it can be read out individually for each γ-ray detector 32. Further, the γ-ray detector 32 may be configured by combining a plurality of scintillators formed of the same substance in the depth direction. Further, the depth direction may be discriminated based on the position on the two-dimensional position map where the center of gravity is calculated by devising how to put the reflective material in the γ-ray detector 32.

  As shown in FIGS. 4 to 7, a sinogram coronal section will be described as an example of coincidence counting data. In addition, it is not limited to a sinogram, A cross section other than the coronal cross section (for example, an axial cross section, a sagittal cross section) may be used.

  In the first embodiment including the second embodiment described later, the following will be described assuming that the coincidence coincidence has already been removed. In order to eliminate coincidence coincidence, there is a coincidence using delayed coincidence counting with a time difference, or coincidence estimated from a single count counted by a counter provided for each detector block or detection element. Correction for removing the coincidence may be performed. After the coincidence coincidence is removed, each coincidence count data becomes two components of a true coincidence count and a scattering coincidence count. Therefore, all coincidence count data All is also referred to as “All (T + S)” as shown in FIG. The coincidence count data Depth between γ rays with deep detection layers is also expressed as “Depth (T + S)” as shown in FIG. T in parentheses in each data represents a true coincidence component, and S represents a scattering coincidence component (ie, a scattering component).

  The scatter correction unit 43 performs scatter correction in steps S1 to S3 in FIG. 5 and steps S4 to S6 in FIG. 6 based on the Depth data classified by the detected depth information discrimination unit 41, as shown in FIG. The coincidence count data All (T) after scattering correction is output.

  First, with respect to coincidence count data Depth (= Depth (T + S)) of γ-rays with deep detection layers classified by the detection depth information discriminating unit 41, a scattering component is obtained by the deconvolution method and removed (FIG. 5). (See “deconvolution” in step S1). Specifically, the scattering component Depth (S) is estimated by applying a deconvolution filter based on a two-dimensional Fourier transform, a low-pass filter (LPF), and a two-dimensional inverse Fourier transform. The two-dimensional Fourier transform is performed on the coronal section of the sinogram to develop it in the spatial frequency domain. Since the scattered component appears in the low-frequency region, only the scattered component in the low-frequency region is allowed to pass by applying a low-pass filter (LPF) to the data after the two-dimensional Fourier transform. By performing the two-dimensional inverse Fourier transform, the original coronal section is restored, and the scattered component Depth (S) is obtained and estimated in addition to the original coincidence data Depth (T + S).

  Next, the estimated scattering component Depth (S) is subtracted from the original coincidence data Depth (T + S) (“Depth (T) = Depth (T + S) −Depth (S)” in step S2 in FIG. 5). Thus, Depth (T) from which the scattering component Depth (S) is removed is obtained. By applying the amplification factor f to Depth (T) from which the scattering component Depth (S) has been removed, f × Depth (T) amplified to the same sensitivity as All (T) is created (in FIG. 5). (See “f * Depth (T)” in step S3).

  The amplification factor f is obtained in advance by preparing a test cylindrical phantom into which a radiopharmaceutical is injected. First, as with the subject M, for the cylindrical phantom, a sinogram of all coincidence data All (= All (T + S)) and a coincidence data Depth (= Depth (T + S)) of γ rays with deep detection layers. And classify each. While changing the amplification factor f, a pseudo-scattering component sinogram given by All (T + S) −f × Depth (T) is obtained. A high pass filter (HPF: High Pass Filter) is applied to the pseudo-scattering component sinogram to perform the process of setting the amplification factor f that minimizes the power spectrum to the optimum amplification factor. This process is based on foreseeing information that the scattering component consists of only the low frequency component and does not contain the high frequency component. When the amplification factor f obtained by such processing is written and stored in advance in the amplification factor memory unit of the memory unit 45 and the scattering correction unit 43 amplifies Depth (T) using the amplification factor, the amplification factor memory The amplification factor stored in the unit is read out.

  F × Depth (T) amplified to the same sensitivity as All (T) is subtracted from the total coincidence data All (T + S) (“All (S ′) = All (T + S) −f in step S4 in FIG. 6). (Refer to x Depth (T))) to obtain All (S ') from which f x Depth (T) amplified to the same sensitivity as All (T) is removed. For noise removal processing, smoothing (smoothing) is performed on All (S ′) (see “smoothing” in step S5 in FIG. 6) to obtain All (S) after the smoothing processing. .

  Then, using All (S) as the final scattering component, the total coincidence data All (T + S) is subtracted (see “All (T) = All (T + S) −All (S)” in step S6 in FIG. 6). Thus, the coincidence count data All (T) from which All (S) has been removed as the final scattering component, that is, the coincidence count data All (T) after the final scattering correction is obtained as shown in FIG. In this way, true coincidence data All (T) that does not include a scattering component is obtained. The coincidence count data All (T) after the scatter correction is sent to the image reconstruction unit 44, and the image reconstruction unit 44 reconstructs the sent coincidence count data after the scatter correction to generate a tomographic image.

  When γ-rays generated from the subject M to which the radiopharmaceutical is administered are incident on the γ-ray detector 32, the scattering component with low incident energy interacts with the detection depth shallow from the low energy. Cheap. On the other hand, γ-rays with high incident energy have higher transmission characteristics than γ-rays with low energy, so they are more likely to interact in a deep detection area, and the probability that the data detected in that area is high energy. Is expected to be high. Therefore, according to the PET apparatus 1 according to the first embodiment having the above-described configuration, detection is information indicating the detection depth at which γ-rays enter the γ-ray detector 32 instead of the conventional energy information. Based on the depth information, the coincidence count data output from the coincidence counting circuit 35 includes all coincidence count data and coincidence count data between γ rays having a predetermined detection layer of the γ ray detector 32 having a predetermined depth. The detected depth information discriminating unit 41 classifies them. The scattering correction unit 43 performs scatter correction of the coincidence data based on the coincidence data between the γ rays having deep detection layers classified by the detection depth information discriminating unit 41, so that the detection depth according to the energy information is detected. Scatter correction can be performed using the depth information. Moreover, the influence by the fluctuation | variation of the photoelectric peak position in energy information can be avoided.

  In the first embodiment, the γ-ray detector 32 is configured by laminating a plurality of layers (two layers in FIGS. 3 and 4) in the depth direction (r in FIG. 3) where γ-rays are incident, and in the order of incidence. When the first layer, the second layer,... Are used, it is preferable that the coincidence data of the γ rays detected from the second layer onward is detected by the detection depth information discriminating unit 41. Are classified and classified as coincidence data.

  When γ-rays are incident on the γ-ray detector 32, scattering components with low incident energy are likely to interact with the shallow first layer, and radiation with higher incident energy is a deep region after the second layer. It is easy to cause interaction. Accordingly, the coincidence count data of γ rays detected together in the second layer and thereafter are classified as coincidence count data of γ rays with deep detection layers. By classifying in this way, the probability that coincidence count data between γ rays with deep detection layers is high energy increases.

  In order to further improve the probability that coincidence data between γ-rays with deep detection layers has high energy, more preferably, coincidence data with γ-rays detected together in the deepest layer is discriminated from detection depth information. The unit 41 discriminates and classifies the data as coincidence count data of γ rays having a deep detection layer.

Next, Embodiment 2 of the present invention will be described with reference to the drawings.
FIG. 8 is a block diagram of the PET apparatus according to the second embodiment. In addition, about the outline of PET apparatus 1, it is the structure similar to FIG. Parts that are the same as those in the first embodiment are given the same reference numerals, and descriptions thereof are omitted.

  In the PET apparatus 1 according to the second embodiment, as illustrated in FIG. 8, the console 4 includes a detection depth information discriminating unit 41, a scattering correction unit 43, an image reconstruction unit 44, and a memory unit 45 as in the first embodiment. In addition to an input unit 46, an output unit 47, and a controller 48, an energy discriminating unit 42 is provided. The energy discriminating unit 42 corresponds to the second coincidence classification means in the present invention.

The energy discriminating unit 42 discriminates and classifies coincidence count data (coronal cross section of sinogram in the second embodiment) by discriminating each data (UEW data and SEW data in the second embodiment) based on energy information of γ rays. Here, SEW data all coincidence data, a predetermined value the coincidence count data having a higher energy window than _{(U from} in FIG. 9) and UEW data.

  The scatter correction unit 43 performs scatter correction of the coincidence count data based on the UEW data that is the coincidence count data having the high energy window classified by the energy discriminating unit. Similar to the first embodiment, the scattering correction unit 43 sends the coincidence count data after the scattering correction to the image reconstruction unit 44. The image reconstruction unit 44 reconstructs the coincidence count data after the scattering correction and generates a tomographic image.

  In the second embodiment, the energy discriminating unit 42 displays the coincidence data Depth of γ rays with deep detection layers classified by the detection depth information discriminating unit 41, and the total coincidence data SEW of γ rays with deep detection layers. And coincidence data UEW having a high energy window between the deep γ-rays in the detection layer. Then, the scattering correction unit 43 uses the coincidence data between the γ-rays having a deep detection layer based on the coincidence data UEW in which the detection layers classified by the energy discrimination unit 42 are deep γ-rays and have a high energy window. After the depth scatter correction, the scatter correction of the coincidence data is performed based on the coincidence data between the γ rays whose detection layers after the scatter correction are deep.

  Next, the discrimination / classification in the energy discriminating unit 42 and the scattering correction in the scattering correcting unit 43 will be described with reference to FIGS. FIG. 9A is an energy spectrum showing a count value of γ rays with respect to energy, FIG. 9B is an energy distribution of each γ ray targeted for coincidence counting, and FIG. FIG. 11 is a diagram schematically illustrating discrimination and classification in the detection depth information discriminating unit and energy discriminating unit according to FIG. 2, and FIGS. 11 to 13 illustrate processing related to scattering correction in the scattering correcting unit according to the second embodiment. It is a flowchart which shows a flow.

  As shown in FIG. 9A, when the horizontal axis is energy and the vertical axis is the count value of γ rays, the energy spectrum represents the count value of γ rays with respect to energy. In addition, as shown in FIG. 9B, among the γ-ray energies to be counted simultaneously, the horizontal axis represents the energy of one γ-ray (in FIG. 9B, “Energy of photon 1”). ), Where the vertical axis is the energy of the other γ-ray (indicated by “Energy of photon 2” in FIG. 9B), the energy distribution of each γ-ray to be subjected to simultaneous counting is obtained.

As shown in FIG. 9A, the distribution has a peak at the energy of γ-rays of 511 keV. The overall energy windows from S _from to _S-to (in FIG. 9 SEW), setting the energy windows to _S-to (in FIG. 9 UEW) from a predetermined threshold value (in FIG. 9 _{U from),} 9 As shown in (b). Is set to S _from the 300KeV~400KeV the lower limit value is set to the _S-to the 600KeV~800KeV becomes the upper limit value, the predetermined threshold value as a U _from, 500 KeV to be near the peak, 511 KeV or preferably Is set to an energy 600 KeV higher than the peak (550 KeV in FIG. 9B). By setting energy near the peak or higher than the peak as the energy window higher than the predetermined threshold, the γ-ray scattering component is reduced to some extent, as is apparent from the energy spectrum of FIG. An energy window can be selected.

  Based on such an energy window, the energy discriminating unit 42 classifies the total coincidence data SEW and the coincidence data UEW having a high energy window. As described above, in the second embodiment, as illustrated in FIG. 10, the total coincidence data All is detected, and the detection depth information discriminating unit 41 performs the coincidence of the total coincidence data All and the γ rays having a deep detection layer. The data depth is classified into data depths, and the detection layer classified by the detection depth information discriminating unit 41 includes the coincidence data Depth of the deep γ rays, the total coincidence data SEW of the deep γ rays of the detection layer, and the detection layer It classify | categorizes into the coincidence count data UEW which has a high energy window between deep gamma rays.

  In the second embodiment, as in the first embodiment described above, the following will be described assuming that the coincidence coincidence has already been removed. Similar to the first embodiment, the total coincidence data All is also represented as “All (T + S)”, and the coincidence data Depth between the γ-rays having deep detection layers is also represented as “Depth (T + S)”. . Further, the total coincidence data SEW between the γ rays with the deep detection layer is also expressed as “SEW (T + S)”, and the coincidence data UEW with the high energy window between the deep γ rays with the detection layer is expressed as “UEW ( T + S) ”. T in parentheses in each data represents a true coincidence component, and S represents a scattering coincidence component (ie, a scattering component). In Example 2, unless otherwise noted, the total coincidence data SEW between the deep γ rays in the detection layer is abbreviated as “total coincidence data SEW”, and the detection layer is deep between the γ rays and high. The coincidence counting data UEW having an energy window is abbreviated as “simultaneous counting data UEW having a high energy window” and will be described below.

  Based on the coincidence count data UEW having a high energy window, the scatter correction unit 43 performs scatter correction of the coincidence count data Depth in steps T1 to T3 in FIG. 11 and steps T4 to T6 in FIG. Based on the coincidence data Depth of the γ-rays with deep detection layers after that, the coincidence data of Steps S1 to S6 in FIG. 13 is subjected to scatter correction, and as shown in FIG. (T) is output.

  First, the coincidence count data Depth (= Depth (T + S)) classified by the detection depth information discriminating unit 41 is set as all coincidence count data SEW (= SEW (T + S)) of γ rays with deep detection layers. Further, from the total coincidence data SEW, the coincidence data UEW (= UEW (T + S)) having a high energy window classified by the energy discriminating unit 42 is obtained by obtaining a scattering component by the deconvolution method and removing it (see FIG. 11 (see “deconvolution” in step T1). Since the deconvolution method is the same as that of the first embodiment, the description thereof is omitted. In addition to the original coincidence data UEW (T + S), the scattering component UEW (S) is obtained and estimated by the deconvolution method.

  Next, the estimated scattering component UEW (S) is subtracted from the original coincidence data UEW (T + S) (“UEW (T) = UEW (T + S) −UEW (S)” in step T2 in FIG. 11). Thus, UEW (T) from which the scattering component UEW (S) has been removed is obtained. The amplification factor f is applied to UEW (T) from which the scattering component UEW (S) has been removed to create f × UEW (T) amplified to the same sensitivity as SEW (T) (in FIG. 11). (See “f * UEW (T)” in step T3).

  F × UEW (T) amplified to the same sensitivity as SEW (T) is subtracted from the total coincidence data SEW (T + S) (“SEW (S ′) = SEW (T + S) −f in step T4 in FIG. 12). SEW (S ′) from which f × UEW (T) amplified to the same sensitivity as SEW (T) is removed is obtained. For noise removal processing, smoothing processing (smoothing) is performed on SEW (S ′) (see “smoothing” in step T5 in FIG. 12) to obtain SEW (S) after smoothing processing. .

  Then, SEW (S) is subtracted from the total coincidence data SEW (T + S) as a scattering component (see “SEW (T) = SEW (T + S) −SEW (S)” in step T6 in FIG. 12). Thus, coincidence count data SEW (T) from which SEW (S) has been removed as the scattering component, that is, coincidence count data SEW (T) after scattering correction is obtained as shown in FIG. 11 and FIG. 12 of the second embodiment, All in the flow of FIG. 5 and FIG. 6 of the first embodiment is replaced with SEW in the second embodiment, and Depth is replaced with UEW in the second embodiment. The content is clear.

  Next, since the coincidence data SEW (T) is coincidence data between deep γ rays in the detection layer, the coincidence data Depth (= Depth (T + S)) between the deep γ rays in the detection layer is implemented. Processing similar to that in Example 1 (steps S1 to S6) is performed. Steps S1 to S6 are the same as steps S1 to S6 in FIGS. Finally, true coincidence data All (T) that does not include a scattering component is obtained. The coincidence count data All (T) after the scatter correction is sent to the image reconstruction unit 44, and the image reconstruction unit 44 reconstructs the sent coincidence count data after the scatter correction to generate a tomographic image.

  As described above, in the second embodiment, the scattering correction is performed using the energy information in addition to the detection depth information. That is, the energy discriminating unit 42 classifies the coincidence count data output from the coincidence counting circuit 35 into total coincidence count data and coincidence count data having an energy window higher than a predetermined value based on the energy information of γ rays. The scatter correction unit 43 performs scatter correction on the coincidence data based on the coincidence data having a high energy window classified by the energy discriminating unit 42.

  Further, in the case of performing scatter correction using energy information in addition to the detected depth information as in the second embodiment, classification and scatter correction are performed as described above. That is, the energy discriminating unit 42 detects coincidence data of γ rays with deep detection layers classified by the detection depth information discrimination unit 41, total coincidence data of γ rays with deep detection layers, and deep detection layers. They are classified into coincidence data having γ rays and having a high energy window. Then, the scattering correction unit 43 calculates the coincidence data of the γ-rays having deep detection layers based on the coincidence data having the detection layers classified by the energy discriminating unit 42 and having high energy windows. After performing the scatter correction, the scatter correction of the coincidence count data is performed based on the coincidence count data of the γ rays having deep detection layers after the scatter correction.

  The present invention is not limited to the above-described embodiment, and can be modified as follows.

  (1) In each of the above-described embodiments, the PET apparatus alone has been described as an example. However, an apparatus that combines a PET apparatus and a transmission apparatus, an apparatus that combines a PET apparatus and an X-ray CT apparatus, and a PET apparatus. As exemplified in a device combining a MR device and an MR device, the present invention may be applied to a combined PET device combining a PET device and another device.

  (2) In each of the above-described embodiments, γ rays have been taken as an example of radiation, but it can also be used for nuclear medicine diagnosis using radiation other than γ rays (α rays and β rays).

  (3) In each of the above-described embodiments, the deconvolution method, the amplification with the amplification factor f, and the smoothing processing method are combined as the scattering correction. However, the present invention is not limited to this.

DESCRIPTION OF SYMBOLS 1 ... PET apparatus 32 ... γ-ray detector 35 ... Simultaneous counting circuit 41 ... Detection depth information discrimination part 42 ... Energy discrimination part 43 ... Scatter correction part M ... Subject

Claims (5)

A nuclear medicine diagnostic apparatus for obtaining nuclear medical data of a subject based on radiation generated from the subject to which a radiopharmaceutical is administered,
Radiation detecting means for detecting the radiation;
A coincidence counting means for determining whether or not radiation is simultaneously detected by the radiation detection means, and outputting the simultaneously detected radiation as coincidence counting data;
The coincidence count data output by the coincidence counting unit is obtained by combining all coincidence count data and a predetermined depth based on detection depth information which is information indicating a detection depth at which radiation enters the radiation detection unit. A first coincidence classification unit that classifies the radiation detection unit of the radiation detection unit into deep coincidence count data;
A nuclear medicine diagnosis apparatus comprising: a scatter correction unit that scatter-corrects coincidence data based on coincidence data between radiations having deep detection layers classified by the first coincidence classification unit. The nuclear medicine diagnosis apparatus according to claim 1,
Second coincidence classification for classifying the coincidence data output by the coincidence means into total coincidence data and coincidence data having an energy window higher than a predetermined value based on the energy information of the radiation. With means,
The nuclear medicine diagnosis apparatus, wherein the scatter correction unit performs scatter correction of the coincidence data based on the coincidence data having the high energy window classified by the second coincidence classification unit. The nuclear medicine diagnosis apparatus according to claim 2,
The second coincidence classification unit includes coincidence data between radiations with deep detection layers classified by the first coincidence classification unit, total coincidence data between radiations with deep detection layers, and deep detection layers. Classifying the radiation data and the coincidence data having the high energy window,
The scattering correction unit is configured to perform simultaneous counting of radiations having a deep detection layer based on coincidence data in which the detection layers classified by the second coincidence classification unit are deep radiations and have a high energy window. A nuclear medicine diagnostic apparatus characterized in that after performing scatter correction of data, scatter correction of coincidence data is performed based on coincidence data between radiations in which the detection layer after the scatter correction is deep. In the nuclear medicine diagnostic apparatus according to any one of claims 1 to 3,
The radiation detection means is configured by laminating a plurality of layers in a depth direction where the radiation is incident,
When the first layer, the second layer,... Are arranged in the order of incidence, the first coincidence classification means uses the simultaneous coincidence data of the radiation detected in the second and subsequent layers. A nuclear medicine diagnostic apparatus characterized by being classified as counting data. In the nuclear medicine diagnostic apparatus according to claim 4,
The nuclear medicine diagnosis apparatus characterized in that the first coincidence classification means classifies the coincidence data of the radiation detected in the deepest layer as coincidence data of the deep radiation in the detection layer.

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