Nuclear medicine diagnosis device, method, circuit, and program

Abstract

To provide useful information for improving time resolution and spatial resolution based on a charge distribution generated in a detector array.SOLUTION: A nuclear medicine diagnosis device according to an embodiment comprises: a detector array in which a plurality of detection elements are arranged; and a circuit that is connected with the detector array. The circuit includes first, second, third, and fourth summing circuits. The first summing circuit generates, based on signals output from the detection elements, first output corresponding to the total energy of the signals. The second summing circuit generates, based on the signals output from the detection elements, second output corresponding to the positions of the signals in a first dimension of the detector array. The third summing circuit generates, based on the signals output from the detection elements, third output corresponding to the positions of the signals in a second dimension of the detector array. The fourth summing circuit generates, based on the signals output from the detection elements, fourth output corresponding to the radius of the charge distribution of the signals.SELECTED DRAWING: Figure 6A

Description

Technical Field

[0001] The embodiments disclosed in this specification and the drawings relate to nuclear medicine diagnostic apparatuses, methods, circuits, and programs.

Background Art

[0002] Conventional positron emission tomography (PET) detectors use a crystal array to determine the position of incident gamma rays. By using a plurality of silicon photomultipliers (SiPMs) together with the crystal array, a detector array formed of a plurality of pixelated detection elements can be obtained. Signals from the SiPMs of the detector array are individually digitized or weighted and summed, and as a result, signals corresponding to the total energy of the signals and the two-dimensional (2D) coordinates of the detected gamma rays are obtained.

[0003] In the detector array, due to scattering and light sharing between the crystal and the SiPM, an incident gamma ray may be detected by a plurality of SiPMs, and as a result, a charge distribution may occur across the detector array. This charge distribution can provide useful information for improving the time resolution and spatial resolution. FIG. 1 shows a schematic diagram of scattering. As indicated by arrow 20, a 511 keV photon is received by a certain crystal 10a and scattered to another crystal 10b. In FIG. 1, the charge from the crystal array 10 received by the SiPM array 30 is schematically shown by curves 40 and 41.

[0004] Furthermore, a monolithic crystal can also be used in the detector array. In this case, the charge distribution can be used to derive the Depth of Interaction (DOI) of gamma rays. Figure 2 shows scattering and charge sharing information in a monolithic crystal. 511 keV photons at different depths are adsorbed by the monolithic crystal 50 and detected by SiPM 70. In Figure 2, the charge distributions of the two photons are shown as curves 80 and 81. The DOI is indicated by arrow 60.

[0005] In such detector arrays, achieving higher spatial resolution requires smaller crystals, resulting in a larger number of SiPMs. When the number of SiPMs to be read out is significantly large, the total number of outputs can be reduced using Anger logic. However, using Anger logic results in a loss of charge distribution.

[0006] For example, a conventional weighted summing circuit is described in Patent Document 1. Figure 2 of Patent Document 1 shows a readout circuit. In this system, there are only two total channels for positional information that limits the available information from the crystal array. [Prior art documents] [Patent Documents]

[0007] [Patent Document 1] U.S. Patent No. 9945965 [Overview of the Initiative] [Problems that the invention aims to solve]

[0008] One of the problems that the embodiments disclosed herein and in the drawings aim to solve is to provide useful information for improving temporal and spatial resolution based on the charge distribution occurring in the detector array. However, the problems that the embodiments disclosed herein and in the drawings aim to solve are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems. [Means for solving the problem]

[0009] The nuclear medicine diagnostic device according to the embodiment comprises a crystal that converts gamma rays into light, a detector array in which a plurality of detection elements are arranged to detect the light and output a signal based on the light, and a circuit connected to the detector array. The circuit includes a first adder circuit, a second adder circuit, a third adder circuit, and a fourth adder circuit. The first adder circuit generates a first output corresponding to the total energy of the signals by adding the signals output from each of the plurality of detection elements, weighted by a first weight. The second adder circuit generates a second output corresponding to the position of the signals in the first dimension of the detector array by adding the signals output from each of the plurality of detection elements, weighted by a second weight. The third adder circuit generates a third output corresponding to the position of the signals in the second dimension of the detector array by adding the signals output from each of the plurality of detection elements, weighted by a third weight. The fourth adder circuit generates a fourth output corresponding to the radius of the charge distribution of the signals by adding the signals output from each of the plurality of detection elements, weighted by a fourth weight. [Brief explanation of the drawing]

[0010] This application will be better understood in light of the description provided in a non-limiting manner with the accompanying drawings. [Figure 1] Figure 1 shows a diagram of scattering in a detector array. [Figure 2] Figure 2 shows the scattering in a monolithic crystal. [Figure 3]Figure 3 is a perspective view showing the PET apparatus according to the present application. [Figure 4] Figure 4 is a schematic diagram showing the PET apparatus and related hardware according to the present application. [Figure 5A] Figure 5A shows the arrangement of the crystal detector and photodetector array according to the present invention. [Figure 5B] Figure 5B shows the arrangement of the crystal detector and photodetector array according to the present invention. [Figure 5C] Figure 5C shows the arrangement of the crystal detector and photodetector array according to the present invention. [Figure 5D] Figure 5D shows the arrangement of the crystal detector and photodetector array according to the present invention. [Figure 6A] Figure 6A shows an adder circuit according to the first embodiment of the present application. [Figure 6B] Figure 6B shows an adder circuit according to a modified example of the first embodiment of the present application. [Figure 7] Figure 7 shows an example of a weighting circuit according to the present invention. [Figure 8] Figure 8 shows an additive amplifier according to a modified example of the present invention. [Figure 9] Figure 9 shows an example of the weighting used in the photodetector array according to the present invention. [Figure 10A] Figure 10A shows the weights by readout channel in the photodetector array according to the present invention. [Figure 10B] Figure 10B shows the weights by readout channels in the photodetector array according to the present invention. [Figure 10C] Figure 10C shows the weights by readout channel in the photodetector array according to the present invention. [Figure 10D] Figure 10D shows the weights by readout channels in the photodetector array according to the present invention. [Figure 11] Figure 11 shows an adder circuit according to a second embodiment of the present application. [Figure 12] Figure 12 shows position decoding using the summing circuit according to the present invention. [Figure 13] Figure 13 is a flowchart showing the weight adjustment and signal correction method according to the present invention. [Figure 14] Figure 14 is a graph showing the signal correction related to the present invention. [Figure 15] Figure 15 is a flowchart showing a method for calibrating the correction matrix according to a modified example of the present invention. [Modes for carrying out the invention]

[0011] The embodiments of the nuclear medicine diagnostic apparatus, method, circuit, and program will be described in detail below with reference to the drawings.

[0012] One embodiment relates to a circuit for receiving a signal from a photodetector array arranged to detect a signal generated by a crystal, and includes a plurality of summing circuits having a weighting circuit, the summing circuit configured to produce outputs corresponding to the total energy of the signal, the position of the signal in a first dimension of the photodetector array, the position of the signal in a second dimension of the photodetector array, and the radius of the charge distribution of the signal.

[0013] One embodiment relates to a PET apparatus having a crystal configured to receive gamma rays and a photodetector array arranged to detect a signal generated by the crystal, wherein a circuit connected to the photodetector array includes a plurality of summing circuits having a weighting circuit, the summing circuit being configured to produce outputs corresponding to the total energy of the signal, the position of the signal in a first dimension of the photodetector array, the position of the signal in a second dimension of the photodetector array, and the radius of the charge distribution of the signal.

[0014] One embodiment relates to a method for extracting information from gamma-ray interactions within a crystal, the method comprising generating an output signal from the interactions, and generating a first signal corresponding to the total energy of the output signal, a second signal corresponding to the energy of the output signal weighted according to the position of the output signal in a first dimension of the crystal, a third signal corresponding to the energy of the output signal weighted according to the position of the output signal in a second dimension of the crystal, and a fourth signal corresponding to the energy of the output signal weighted according to the dispersion of the positions of the output signal in the first and second directions.

[0015] One embodiment relates to a method for determining the location of a gamma-ray interaction in a crystal, the method comprising generating an output signal from the interaction, and generating a first signal corresponding to the total energy of the output signal, a second signal corresponding to the energy of the output signal weighted according to the location of the output signal in a first dimension of the crystal, a third signal corresponding to the energy of the output signal weighted according to the location of the output signal in a second dimension of the crystal, and a fourth signal corresponding to the energy of the output signal weighted according to the dispersion of the locations of the output signal in first and second directions, wherein the location of the interaction is determined using at least one of the ratio of the second signal to the first signal, the ratio of the third signal to the first signal, and the ratio of the sum of the squares of the first signal and the second signal to the square of the first signal minus the ratio of the fourth signal to the first signal.

[0016] Figures 3 and 4 show a PET apparatus according to the present invention. The PET apparatus 100 includes a plurality of gamma-ray detectors (GRDs) 101 (e.g., GRD1, GRD2 to GRDN), each configured as a rectangular detector module. According to one embodiment, the detectors are arranged in a ring that forms a circular bore 102 centered on a gantry 104. In this example, the ring includes 40 GRDs 101. The ring may have a different number of GRDs 101 depending on factors such as the desired size of the bore 102. The GRDs 101 include a scintillator crystal array for converting gamma rays into scintillation photons (e.g., optical, infrared, and ultraviolet wavelengths) that are detected by a photodetector. Each GRD 101 may include a two-dimensional array of individual detector crystals that absorb gamma rays and emit scintillation photons, or it may include a monolithic array or an array with slats. Scintillation photons can be detected by a two-dimensional array of devices (not shown), such as SiPMs, also located within the GRD101. A light guide can be placed between the array of detection crystals and the SiPMs. The arrangement of the crystals and SiPMs according to this application will be described in more detail below.

[0017] Figure 3 shows a schematic diagram of a PET apparatus 100 having a GRD (Gamma Radiograph) positioned to detect gamma rays emitted from the subject's obstetric OBJ (obstructive junction). The GRD 101 can measure the timing, position, and energy corresponding to each detected gamma ray. Note that the single PET detector ring in Figure 3 may be extrapolated along the axial length of the PET apparatus to include any number of PET detector rings.

[0018] Figure 4 shows an example of the arrangement of the PET apparatus 100, where the subject OBJ to be imaged is placed on the bed 206, and the GRDs 101 (GRD1 to GRDN) are arranged circumferentially around the subject OBJ and the bed 206. The GRDs 101 may include a PET detector ring and may be fixedly connected to a cylindrical bore 202 which is fixedly connected to the gantry 204. The gantry 204 houses many components of the PET apparatus. The gantry 204 of the PET apparatus also includes an open opening defined by the cylindrical bore 202 through which the subject OBJ and the bed 206 can pass, and the GRDs 101 can detect gamma rays emitted in the opposite direction from the subject OBJ due to annihilation events, and the coincidence count of gamma ray pairs can be determined using timing and energy information.

[0019] Figure 4 also shows the circuitry and hardware for acquiring, storing, processing, and distributing gamma-ray detection data. This circuitry and hardware includes a processor 207, a network controller 203, a memory 205, and a Data Acquisition System (DAS) 208. The PET imaging system also includes data channels that route detection measurement results from the GRD 101 to the DAS 208, processor 207, memory 205, and network controller 203. The DAS 208 can control the acquisition, digitization, and routing of detection data from the detector. In one embodiment, the DAS 208 controls the movement of the patient bed 206. The processor 207 performs functions including identification of placement errors, pre-reconstruction processing of detection data, image reconstruction, and post-reconstruction processing of image data. Here, the processor 207 is an example of a processing circuit.

[0020] According to one embodiment, the processor 207 of the PET apparatus 100 in Figures 3 and 4 is configured to perform the method described herein. The processor 207 may include a CPU (Central Processing Unit) that can be executed as individual logic gates, such as an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), or other Complex Programmable Logic Device (CPLD). The FPGA or CPLD implementation may be coded in VHDL, Verilog, or other hardware description language, and the code may be stored directly in the electronic memory of the FPGA or CPLD, or in separate electronic memory. Furthermore, the memory 305 may be a hard disk drive, CD-ROM drive, DVD drive, flash drive, RAM, ROM, or any other electronic storage device known in the art. The memory 205 may be non-volatile, such as ROM, EPROM, EEPROM, or flash memory. The memory 205 can also be volatile, such as static or dynamic RAM, and a processor, such as a microcontroller or microprocessor, may be provided to manage the electronic memory, as well as the interaction between the FPGA or CPLD and the memory.

[0021] Alternatively, the CPU within processor 207 may execute a computer program comprising a set of computer-readable instructions that perform the methods described herein, the program being stored in any of the aforementioned non-temporary electronic memory and / or hard disk drives, CDs, DVDs, flash drives, or any other known storage medium. Furthermore, the computer-readable instructions may be provided as utility applications, background daemons, or components of an operating system, or a combination thereof, and may be executed in cooperation with processors such as Intel Xenon or AMD Opteron processors, and Microsoft Vista, UNIX®, Solaris, Linux, Apple, MAC-OS, and other operating systems known to those skilled in the art. Furthermore, the CPU may be executed as multiple processors working concurrently and cooperatively to execute instructions. The instructions may be stored in memory 205 or in memory (not shown) located in the network controller 203.

[0022] In one embodiment, the PET apparatus may include a display for displaying reconstructed images or the like. The display can be an LCD display, a CRT display, a plasma display, an OLED, an LED, or any other display known to those skilled in the art.

[0023] Network controllers 203, such as Intel Ethernet PRO network interface cards from Intel, can interface between various parts of a PET imaging device. Furthermore, network controller 203 can also interface with an external network. As can be understood, this external network can be a public network such as the Internet, or a private network such as a LAN or WAN network, or any combination thereof, and may include PSTN or ISDN subnetworks. The external network can also be wired, such as an Ethernet network, or wireless, such as a cellular network including EDGE, 3G, and 4G wireless cellular systems. The wireless network can be WiFi, Bluetooth, or any other known wireless communication format.

[0024] In the GRD101 according to this application, a photodetector such as a SiPM array is coupled to a crystal array, a stack of slat crystals, or a monolithic crystal. Figures 5A to 5D show these structures. These figures are examples and show typical numbers of crystals and SiPM elements. The number of crystals and SiPM elements can be varied according to the needs and requirements of the PET apparatus. Figures 5A and 5B show a crystal array 10 coupled to a 1-1 coupled SiPM array 30 and a mismatched coupled SiPM array 31. Here, mismatched coupling means that the number of crystals and the number of SiPMs are different. In the example in Figure 5B, the SiPM array 31 has a larger pitch (or fewer elements) than the number of crystals in the array. The SiPM arrays 30 and 31 are composed of multiple detector elements, and the crystal array 10 is composed of multiple crystals. Figure 5C shows an embodiment using a monolithic crystal 50, and Figure 5D shows an embodiment having a crystal array 90 using a stack of slat crystals.

[0025] In a crystal array, the crystals may be separated from each other by gaps, reflectors, or opaque materials. The separation between crystals does not need to completely separate the light transmitted through them. For example, some light may be shared between crystals if reflectors shorter than the length of the crystals are placed in the gaps.

[0026] The signals from individual channels of the photodetector array are summed to derive information about the received signal. In this application, the signals from the photodetector array are advantageously fed to a group of summing circuits having specially designed weights. The summing circuits may be part of the DAS208 or located in the GRD101. For example, four or more groups of summing circuits may be arranged. In this example, one group is designed to generate a signal of one energy by adding equal weights. Two other groups generate a signal of coordinates using channel-dependent weights. A fourth group generates a signal of the radius of the charge distribution using channel-dependent weights.

[0027] In principle, the charge distribution can be expressed as the sum of moments of all orders. Probability distribution within a bounded interval, in this application, the charge distribution is expressed as the sum of all moments (of all orders m n =∫x n The charge distribution is uniquely determined by the set of f(x)dx (n=0~∞) (Hausdorff moment problem, moment (mathematics), Wikipedia; https: / / en.wikipedia.org / wiki / Moment_(mathematics)). Therefore, if it is necessary to extract more features of the charge distribution, additional groups may be added.

[0028] Figure 6A shows a first embodiment of the summing circuit according to the present invention. This configuration is a single-stage summing circuit. SiPMs D11 to D33 arranged in a 3x3 matrix are shown as an example. Typically, a larger number of SiPMs are summed. Each output of the SiPM is first buffered using a buffer circuit 110 and then transferred to an array of weighting circuits 111. The buffer circuit 110 consists of amplifiers used to terminate the electrodes of the SiPMs and drive the outputs for weighting. A typical buffer circuit used with SiPMs is a transimpedance input amplifier (TIA). This converts the current signal from the SiPM into a voltage signal with a desired amplitude. The weighting circuit 111 controls the weights applied to the signal before it is summed by the summing amplifier 112. Note that in Figure 6A, for the sake of clarity, only the energy and X signals are shown for the connection between the buffer circuit 110 and the weighting circuit 111. However, the output of the buffer circuit connected to SiPM D11~D33 is also supplied to the weighting circuit 111 for the Y and radius signals.

[0029] Figure 7 shows an example of the weighting circuit 111. The weighting circuit 111 may be implemented as a variable resistor or a variable impedance device and is controllable by the processor. The weighting circuit is adjusted as needed to provide an appropriate input from the signal generated by the SiPM to the summing amplifier. The control of the weighting circuit is described in more detail below.

[0030] Each of the weighting circuits 111 can be connected to an instrument channel and controlled by the processor 207 to set and adjust the appropriate weights. A buffer circuit 110 can also be connected to an instrument channel for gain control. This gain can be adjusted to compensate for fluctuations in the SiPM gain. It is also possible to adjust the weights to compensate for fluctuations in the SiPM gain. Note that in Figure 6A, for clarity, only one buffer circuit 110 and one weighting circuit 111 are shown connected to the instrument channel.

[0031] The output of the weighting circuit 111 is input to the summing amplifier 112, which provides an energy signal. In addition, X and Y signals representing coordinate signals are generated with channel-dependent weights, and a radius signal is generated with channel-dependent weights. The summing amplifier 112 aggregates the input signals and outputs a signal proportional to the sum of the input signals. For example, the voltage values ​​of the signals output by the weighting circuit 111 are summed to generate a total voltage value. The summed output is output to the correction matrix 113. The correction matrix 113 can consist of hardware, an FPGA, a processor configured to execute a program embedded in the processor or a program stored in memory 205, a transformation table, or a neural network. The operation of the correction matrix 113 is described in more detail below. The correction matrix 113 may be omitted, and the summed output may be used without correction.

[0032] As an example, the weighting circuit 111 may be part of the summing amplifier. Figure 8 shows a summing amplifier 115 having a weighting circuit 111 and an adder 114. For example, the summing amplifier 115 is configured to be integrated with multiple weighting circuits 111 and adders 114.

[0033] Here, we will explain signal weighting in more detail. First, for energy (E) channels, equal weights are used and can be calculated using the following formula. E = ΣE xy

[0034] In this equation, x and y represent the two-dimensional positions of the SiPMs within the SiPM array, and E xy is the value of the signal from the buffer circuit at the position (x, y). Also, for the X channel, the weight is proportional to the horizontal position x and is obtained by the following equation. X = ΣxE xy

[0035] Similarly, for the Y channel, the weight is proportional to the vertical position y and is obtained by the following equation. Y = ΣyE xy

[0036] Finally, for the radius (R) channel, the weight is proportional to (x 2 + y 2 ) and is obtained by the following equation. R = Σ(x 2 + y 2 )E xy

[0037] Also, the processor 207 can derive the total variance of the charge distribution using the following equation. σ x 2 = R / E - (X 2 + Y 2 ) / E 2

[0038] Here, the total variance serves as an indicator of scatter or DOI (Z). For example, the processor 207 derives the DOI of gamma rays based on the total variance of the charge distribution.

[0039] Also, as a variant, when it is necessary to separate the variances of the charge distributions in both the x and y directions, two radius channels may be used as follows. R x = Σx 2 E xy R y = Σy 2 E xy

[0040] In this modified example, the summed variances can be calculated using the following formula. σ x 2 =R x / EX 2 / E 2 σ y 2 =R y / EY 2 / E 2

[0041] Furthermore, when using a monolithic crystal, charge sharing occurs due to both DOI and scattering, but the charge distributions for each are different. Therefore, in order to separate these two factors, a group of higher-order summing circuits (third moment, skewness) may be added according to the following equation. S=Σ(x 3 +y 3 )E xy

[0042] Figure 6B shows a simplified portion of the first embodiment in which a skew summing circuit is included. In Figure 6B, the array is not shown. Alternatively, one of the four groups may generate the skew signal S with weights adjusted by the processor 207. Timing information can also be measured using the energy signal. Timing information can also be measured using another signal from the SiPM array, for example, as shown in Figure 6A. In Figure 6A, the bias voltage is applied and sent to the timing channel.

[0043] Each output from SiPM D11-D33 is supplied to a group of weighting circuits corresponding to specific outputs: energy, X, Y, and radius. Figure 9 shows an example of weighting. A 4x4 SiPM array is used to illustrate the weighting. The table in Figure 9 shows the weights for the X output (W_X), the Y output (W_Y), the energy output (W_E), and the radius output (W_R). Figures 10A-10D show the weights corresponding to the 4x4 SiPM array. As mentioned above, the weights for X and Y are proportional to the positions x and y, the energy weight is constant, and the radius weight is (x 2 +y 2 It changes depending on the ). Note that the radius weight is nonlinear. Such nonlinear weights can also be applied to the coordinates X and Y, as well as the energy, thereby allowing for better adjustment. For example, a SiPM at one location may have a lower gain than at another location, but the location of the SiPM with the lower gain can be compensated for by appropriately scaling the weight applied to the relevant channel using a coefficient inversely proportional to the SiPM gain. As a result, the weight is no longer linear with respect to the X or Y coordinate.

[0044] Note that the single-stage adder circuit in Figure 6A requires numerous connections between the buffer circuit and the weighting circuit. In contrast, Figure 11 shows a second embodiment that includes a two-stage adder circuit with fewer connections. In Figure 11, a 3x3 matrix of SiPMs D11~D33 is shown for clarity, but a different number of SiPMs can also be used. In this embodiment, the signal is first buffered using the buffer circuit 120, and then locally weighted using the weighting circuit 121. The signal weighted by the weighting circuit 121 is supplied to the adder amplifier 122, which then adds a series of local energy signals, X and Y, called E yn , X yn and R yn This is generated. In this example, each output of the SiPM, which is in the same row along the X direction, first produces three signals E y , X yand R y It is totaled. Here, E y This represents the total energy of the row, X y This represents the weighted position x of the row, and R y represents the radius. These three signals are determined according to the following formula. E y =Σ y E xy X y =Σ y xE xy R y =Σ y (x 2 +y 2 )E xy

[0045] Next, these signals are input to the weighting circuit 123, and then summed by the summing amplifier 124 to generate energy (E), X, Y, and radius (R) signals. These signals are generated according to the following equations. E = ΣE y X = ΣX y Y=ΣyE y R=ΣR y

[0046] The buffer circuit 120 and the weighting circuits 121 and 123 are connected to the processor 207 and DAS208 via an instrument channel for controlling the weighting values, similar to the first embodiment. Also, similar to the first embodiment, an adder circuit integrating the weighting circuits as shown in Figure 8 may be used.

[0047] Compared to the first embodiment, the maximum number of signals sent to the adder circuit and the required number of weights are n in the single-stage embodiment. 2 However, in the two-stage embodiment, it becomes 3n. Here, n is the number of SiPMs along the x-direction. The number of summing amplifiers is 4 in the one-stage embodiment, but becomes 3n+4 in the two-stage embodiment. Number of buffer amplifiers (n 2) is the same in both the single-stage embodiment and the two-stage embodiment. In the two-stage embodiment, the number of summing amplifiers increases. However, even when the number of SiPMs in the array is large, the number of required weights can be significantly reduced. In a large-sized array, by reducing the number of weights, the number of traces in the circuit can be reduced, making it easier to manage the design and trace routing.

[0048] FIG. 12 shows an example of position decoding. This can be applied to both the first and second embodiments. Here, a 4×4 array having the weights shown in FIGS. 9 and 10A to 10D is used as an example. For ease of explanation, six different cases having a maximum of two hits per matrix are illustrated. FIG. 12 includes the total output and the decoded position. The total output is determined from the weights as follows. X sum =Σx i E i Y sum =Σy i E i E sum =ΣE i R sum =Σ(x i 2 +y i 2 )E i

[0049] The decoded position is determined as follows. PX = X sum / E sum PY = Y sum / E sum PE = E sum PR = R sum / E sum -(x sum 2 +y sum 2 ) / E sum 2

[0050] In Example 1, hit 1 occurs at (1,1) in the matrix. The weights for X, Y, and E are all 1 at the (1,1) position. The decoding position information (X=Y=1) indicates that the hit occurred at (1,1). In Example 2, hit 1 occurs at (2,2), with weights for X and Y being 2 each, and the decoding position information (X=Y=2) indicates that the hit occurred at (2,2). Examples 3-6 each contain two hits, hit 1 and hit 2. From the position of each hit, a unique set of values ​​for X, Y, and R can be obtained. From the unique sets of values ​​for X, Y, and R, the positions of hit 1 and hit 2 can be determined. The processor 207 can determine the position (single or multiple) of a hit (single or multiple) by comparing the calculated values ​​of X, Y, and R obtained during the sampling period with values ​​that have been empirically determined in advance and stored in memory 205, for example. The above analysis can also be performed on any number of hits greater than two in the sampling matrix, and the processor 207 can determine the location of the hits by comparing the calculated values ​​with the stored values.

[0051] Furthermore, by understanding the location of detected hits through unique combinations of X, Y, and R values, the distance between hits can be determined using the decoding location information. In subsequent image reconstruction, image quality can be improved by selecting appropriate Time-of-Flight (TOF) and Point-Spread Function (PSF) kernels using this distance information. Both temporal and spatial resolution are affected by the charge distribution. Conventionally, image reconstruction uses average TOF and PSF kernels for all events. In contrast, this invention can provide charge distribution information for selecting appropriate TOF (for temporal resolution) and PSF (for spatial resolution) kernels for a given event.

[0052] In the first and second embodiments, the group of adder circuits can be expressed as moments, based on moment mathematics (Moment (mathematics) Wikipedia). The energy channel is the zeroth moment, i.e., the integral. The X and Y channels are the first moments, i.e., the mean values. The radius channel is the second moment, i.e., the dispersion of the charge distribution across the array, corresponding to the level of charge spread.

[0053] The above equations for deriving the moment of charge distribution and the location of charge deposition in the crystal in the first and second embodiments are the simplest forms assuming no heterogeneity in the crystal and SiPM. In practice, variations in detector response, crystal heterogeneity, and crystal boundaries necessitate further corrections to convert the raw sums into physical measurements. Common forms for converting the raw sums of X, Y, radius, and energy to physical values ​​(X, Y, Z, and energy) include, but are not limited to, linear matrices, products of multiple matrices, multi-order transformation tables, lookup tables, or neural networks, where Z represents either the depth of interaction or the spatial separation of Compton hits, depending on the application.

[0054] Further optimization of the weights assigned to signals from SiPMs allows for the extraction of relevant information in the most efficient and accurate manner. For example, the weights may be calibrated using simulation results or calibration measurements. In the case of crystal arrays (individual or slat) the relevant information includes energy, X and Y positions, and the distance between hits from the same gamma ray. In the case of monolithic crystals, the relevant information may include energy, X and Y positions, DOI, and the distance between hits from the same gamma ray. Weights can also be compensated for manufacturing variations. Calibration measurements may be used for this compensation.

[0055] Figure 13 shows the data processing and calibration process for spatial information. In this example, this process is applied to a monolithic crystal to extract spatial information. In the case of a monolithic crystal, spatial information corresponding to the three-dimensional positions (X, Y, and Z) of the gamma-ray interaction points is extracted. In addition, the DOI is usually extracted using the R channel along with the X and Y positions.

[0056] First, in step 130, summation weights are set for the photodetector. Next, in step 131, gamma rays are irradiated to discrete positions in the detector matrix by exposing a collimated gamma-ray source, such as pinhole collimation. In the system shown in Figure 3, the collimated gamma-ray source is placed in the bore 102 and gamma rays are irradiated to the selected GRD 101. Next, in step 132, the raw summed output (X_sum, Y_sum, E_sum, and R_sum) is generated. Next, in step 133, the summed output is corrected by processing with the correction matrix 113 / 125, and in step 134, the physical variables X, Y, Z, and E are generated.

[0057] Typically, the weights of the summation are optimized to maximize the resolution of the detector for the information to be extracted. In Figure 13, preferably, in step 135, the optimization process using the performance matrix is ​​performed on the processor 207. For monolithic crystals for which DOI or Z information is desired, one way to optimize the summation weights is to evaluate the peak-to-valley ratio of the corrected physical Z values. For example, a set of data is obtained by placing collimated gamma-ray sources at two discrete depths. Referring to Figure 14, the distribution of corrected physical Z values ​​based on a given weight is plotted. The peak heights 140 / 141 representing the two calibration depths and the valley heights 142 representing the ambiguity between the two depths are compared to optimize the summation weights so that the peak-to-valley ratio is maximized.

[0058] Here, optimization can be achieved using either a trial-and-error method, which involves comparing results while varying the weights, or an iterative method to find the optimal settings. Another approach is to model the detector response predicted for different weights, thereby achieving optimization with fewer iterations. A similar procedure may be applied to the X and Y channels.

[0059] Furthermore, a correction matrix is ​​used to reconstruct physical values ​​close to ground truth. This correction matrix can be calibrated by minimizing a cost function using data collected from gamma-ray sources placed at known discrete locations. Here, the cost function is the chi-square function between ground truth and measured values. Figure 15 shows the process of calibrating the correction matrix. First, steps 130 to 134 described above for Figure 13 are performed, and in step 134, the physical variables X, Y, Z, and E are generated. Subsequently, in step 136, a correction is performed by minimizing the cost function using the physical values. The correction performed in step 136 is used to calibrate the correction performed in step 133.

[0060] Furthermore, by using detector responses modeled with different weights, weight optimization and correction matrix calibration can be performed together to improve overall performance and reduce the number of steps. Future mathematical optimization / minimization / maximization methods include, but are not limited to, least squares, maximum likelihood, and machine learning.

[0061] While the first and second embodiments described above are based on a square (n×n) array, this invention is also applicable to n×m arrays with an uneven number of rows and columns. Furthermore, it is possible to set the weights to zero to effectively disable a portion of the matrix or channels as desired.

[0062] Furthermore, although the above embodiment is an example of a PET device, this embodiment can also be applied to other nuclear medicine diagnostic devices such as SPECT (Single-Photon Emission Computerized Tomography) devices.

[0063] This invention can significantly reduce the number of signals digitized from a photodetector array. Furthermore, it can measure the charge distribution across the detector array and provide information about the distance between scattered hits. In addition, it can provide DOI information in the case of a monolithic crystal.

[0064] Furthermore, this invention simplifies the readout design to reduce the number of digitized channels in a monolithic crystal, and can also provide DOI information while generally requiring the readout of individual SiPMs.

[0065] Furthermore, this invention enables the evaluation of DOI in crystal arrays with a light-sharing design.

[0066] It is obvious, in consideration of the above description, that this application is subject to numerous modifications and alterations. Therefore, it should be understood that this application may be implemented in ways other than those specifically described herein, within the scope of the attached claims.

[0067] According to at least one embodiment described above, useful information for improving temporal and spatial resolution can be provided based on the charge distribution occurring in the detector array.

[0068] While several embodiments have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents. [Explanation of symbols]

[0069] 100 Positron Emission Tomography System 101 Gamma-ray detector 10, 90 crystal array 50 Monolithic Crystals 30, 31 SiPM arrays 110, 120 buffer circuit 111, 121, 123 Weighting Circuits 112, 115, 122 Adding Amplifier 207 Processor

Claims

1. a crystal configured to convert gamma rays into photons; a photodetector array arranged to detect the photons and output a signal based on the detected photons; a circuit connected to the photodetector array; Equipped with the circuit includes a plurality of summing circuits having a plurality of weighting circuits; the plurality of summing circuits are configured to weight and sum the signals output by the photodetector array with weights determined for positions in a first dimension and a second dimension of the photodetector array, to generate a first signal weighted with a constant weight as an output corresponding to a total energy of the signal, a second signal weighted with a weight proportional to a position in the first dimension as an output corresponding to a position of the signal in the first dimension of the photodetector array, a third signal weighted with a weight proportional to a position in the second dimension as an output corresponding to a position of the signal in the second dimension of the photodetector array, and a fourth signal weighted with a weight that varies nonlinearly with position in the first dimension or the second dimension as an output corresponding to a radius of a charge distribution of the signal, a first summing circuit in the plurality of summing circuits includes a plurality of weighting circuits each having the same weight to generate an output corresponding to the total energy of the signal; a second summing circuit included in the plurality of summing circuits includes a plurality of weighting circuits having weights corresponding to positions of the photodetector array in the first dimension; a third summing circuit included in the plurality of summing circuits includes a plurality of weighting circuits having weights corresponding to positions of the photodetector array in the second dimension; a fourth summing circuit included in the plurality of summing circuits includes a plurality of weighting circuits having weights corresponding to a variance of the positions in the first dimension and in the second dimension of the photodetector array; the photodetector array is comprised of a matrix of photodetector elements in two dimensions, an x-dimension and a y-dimension corresponding to the first dimension and the second dimension, respectively; The plurality of weighting circuits included in the first adding circuit include E = ΣE xy generating a signal E as an output corresponding to the total energy of the signal using The plurality of weighting circuits included in the second summation circuit generate a signal X corresponding to the x-dimension using the following formula: X = ΣxE xy The plurality of weighting circuits included in the third summation circuit generate a signal Y corresponding to the y dimension using the following formula: Y = ΣyE xy The weighting circuits included in the fourth summing circuit generate a signal R corresponding to the charge distribution using the following equation: R=Σ(x 2 +y 2 )E xy where E xy is the value of the signal from the buffer corresponding to the photodetector element at position (x, y); Nuclear medicine diagnostic equipment.

2. Based on the E, X, Y and R signals, the summed variance σ of the charge distribution is calculated using the following formula: ｘ and further comprising a processing circuit for deriving s ｘ ２ =R / E-(X) ２ +Y ２ ) / E ２ The nuclear medicine diagnostic apparatus according to claim 1 .

3. The circuit further includes a fifth summing circuit for generating a skewness signal S using the formula: S = S (x) ３ +y ３ )E ｘｙ The nuclear medicine diagnosis apparatus according to claim 1 or 2.

4. At least the weights of the plurality of weighting circuits included in the fourth summing circuit are nonlinear with respect to a dimension of the photodetector array. The nuclear medicine diagnosis apparatus according to claim 1 or 2.

5. The adding circuit includes: a plurality of buffer circuits each configured to receive the output of one element of the photodetector array; a plurality of sets of weighting circuits configured to receive an output of one of the plurality of buffer circuits; a plurality of summing amplifiers each configured to receive outputs from one set of said weighting circuits; The nuclear medicine diagnosis apparatus according to claim 1 or 2, comprising:

6. each of the plurality of summing amplifiers is configured to be integrated with a corresponding set of the weighting circuits; The nuclear medicine diagnosis apparatus according to claim 5.

7. The adding circuit includes: a plurality of buffer circuits each configured to receive the output of one element of the photodetector array; a plurality of sets of first weighting circuits configured to receive outputs from corresponding groups of the plurality of buffer circuits; a first set of summing amplifiers configured to receive outputs from one set of the first weighting circuits; a second set of weighting circuits configured to receive selected ones of the outputs of the first set of summing amplifiers; a plurality of second summing amplifiers each configured to receive outputs from one of the sets of second weighting circuits; The nuclear medicine diagnosis apparatus according to claim 1 or 2, comprising:

8. 1. A method for application to a nuclear medicine diagnostic device comprising a crystal configured to convert gamma rays into photons and a photodetector array arranged to detect the photons and output a signal based on the detected photons, comprising: generating a weighted first signal as an output corresponding to a total energy of the signal; generating a weighted second signal as an output corresponding to a position of the signal in the first dimension of the photodetector array, the second signal being weighted with a weight proportional to a position of the signal in the first dimension of the photodetector array; generating a weighted third signal as an output corresponding to a position of the signal in the second dimension of the photodetector array, the third signal being weighted with a weight proportional to a position of the signal in the second dimension of the photodetector array; generating a fourth signal weighted with a weight that varies nonlinearly with respect to position in the first or second dimension of the photodetector array as an output corresponding to a radius of the charge distribution of the signal; Including, The step of generating the first signal includes generating the first signal using a first summing circuit including a plurality of weighting circuits, each of the weighting circuits having the same weight; The step of generating the second signal includes generating the second signal using a second summing circuit including a plurality of weighting circuits having weights corresponding to positions of the photodetector array in the first dimension; generating the third signal using a third summing circuit including a plurality of weighting circuits having weights corresponding to positions of the photodetector array in the second dimension; generating the fourth signal using a fourth summing circuit including a plurality of weighting circuits having weights corresponding to the variance of the positions in the first dimension and in the second dimension of the photodetector array; the photodetector array is comprised of a matrix of photodetector elements in two dimensions, an x-dimension and a y-dimension corresponding to the first dimension and the second dimension, respectively; The plurality of weighting circuits included in the first adding circuit include E = ΣE xy generating a signal E as an output corresponding to the total energy of the signal using The plurality of weighting circuits included in the second summation circuit generate a signal X corresponding to the x-dimension using the following formula: X = ΣxE xy The plurality of weighting circuits included in the third summation circuit generate a signal Y corresponding to the y dimension using the following formula: Y = ΣyE xy The weighting circuits included in the fourth summing circuit generate a signal R corresponding to the charge distribution using the following equation: R=Σ(x 2 +y 2 )E xy where E xy is the value of the signal from the buffer corresponding to the photodetector element at position (x, y); method.

9. 1. A circuit for use in a nuclear medicine diagnostic device comprising a crystal configured to convert gamma rays into photons, and a photodetector array arranged to detect the photons and output a signal based on the detected photons, a plurality of summing circuits having a plurality of weighting circuits; the plurality of summing circuits are configured to weight and sum the signals output by the array with weights determined for positions in a first and second dimension of the photodetector array, to generate a first signal weighted with a constant weight as an output corresponding to a total energy of the signal, a second signal weighted with a weight proportional to a position in the first dimension as an output corresponding to a position of the signal in the first dimension of the photodetector array, a third signal weighted with a weight proportional to a position in the second dimension as an output corresponding to a position of the signal in the second dimension of the photodetector array, and a fourth signal weighted with a weight that varies non-linearly with position in the first or second dimension as an output corresponding to a radius of a charge distribution of the signal, a first summing circuit in the plurality of summing circuits includes a plurality of weighting circuits each having the same weight to generate an output corresponding to the total energy of the signal; a second summing circuit included in the plurality of summing circuits includes a plurality of weighting circuits having weights corresponding to positions of the photodetector array in the first dimension; a third summing circuit included in the plurality of summing circuits includes a plurality of weighting circuits having weights corresponding to positions of the photodetector array in the second dimension; a fourth summing circuit included in the plurality of summing circuits includes a plurality of weighting circuits having weights corresponding to a variance of the positions in the first dimension and in the second dimension of the photodetector array; the photodetector array is comprised of a matrix of photodetector elements in two dimensions, an x-dimension and a y-dimension corresponding to the first dimension and the second dimension, respectively; The plurality of weighting circuits included in the first adding circuit include E = ΣE xy generating a signal E as an output corresponding to the total energy of the signal using The plurality of weighting circuits included in the second summation circuit generate a signal X corresponding to the x-dimension using the following formula: X = ΣxE xy The plurality of weighting circuits included in the third summation circuit generate a signal Y corresponding to the y dimension using the following formula: Y = ΣyE xy The weighting circuits included in the fourth summing circuit generate a signal R corresponding to the charge distribution using the following equation: R=Σ(x 2 +y 2 )E xy where E xy is the value of the signal from the buffer corresponding to the photodetector element at position (x, y); circuit.

10. A program applied to a nuclear medicine diagnostic device including a crystal configured to convert gamma rays into photons, and a photodetector array arranged to detect the photons and output a signal based on the detected photons, generating a weighted first signal as an output corresponding to a total energy of the signal; generating a weighted second signal as an output corresponding to a position of the signal in the first dimension of the photodetector array, the second signal being weighted with a weight proportional to a position of the signal in the first dimension of the photodetector array; generating a weighted third signal as an output corresponding to a position of the signal in the second dimension of the photodetector array, the third signal being weighted with a weight proportional to a position of the signal in the second dimension of the photodetector array; generating a fourth signal weighted with a weight that varies nonlinearly with respect to position of the first or second dimension of the photodetector array as an output corresponding to a radius of the charge distribution of the signal; Run the following on your computer: The step of generating the first signal includes generating the first signal using a first summing circuit including a plurality of weighting circuits each having the same weight; The step of generating the second signal includes generating the second signal using a second summing circuit including a plurality of weighting circuits having weights corresponding to positions of the photodetector array in the first dimension; The step of generating the third signal includes generating the third signal using a third summing circuit including a plurality of weighting circuits having weights corresponding to positions of the photodetector array in the second dimension; The step of generating the fourth signal includes generating the fourth signal using a fourth summing circuit including a plurality of weighting circuits having weights corresponding to a variance of the positions in the first dimension and in the second dimension of the photodetector array; the photodetector array is comprised of a matrix of photodetector elements in two dimensions, an x-dimension and a y-dimension corresponding to the first dimension and the second dimension, respectively; The plurality of weighting circuits included in the first adding circuit include E = ΣE xy generating a signal E as an output corresponding to the total energy of the signal using The plurality of weighting circuits included in the second summation circuit generate a signal X corresponding to the x-dimension using the following formula: X = ΣxE xy The plurality of weighting circuits included in the third summation circuit generate a signal Y corresponding to the y dimension using the following formula: Y = ΣyE xy The weighting circuits included in the fourth summing circuit generate a signal R corresponding to the charge distribution using the following equation: R=Σ(x 2 +y 2 )E xy where E xy is the value of the signal from the buffer corresponding to the photodetector element at position (x, y); program.

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