Model-based injection dose optimization for long axial FOV PET imaging

Abstract

A computer-implemented method for determining scan parameters includes receiving a set of input parameters. An average per piece of a nuclear imaging scanner having a predetermined field of view (FOV) is determined based on the input parameters, and at least one scan parameter is determined based on the average per piece of the nuclear imaging scanner.

Description

Technical Field

[0001] This application relates generally to nuclear imaging, and more particularly to long-axis field-of-view nuclear imaging. Background Technology

[0002] Current short-axis field-of-view (FOV) scanners have an axial range variation of less than approximately 10 cm and an imaging diameter of approximately 80 cm. For short-axis FOV scanners, for a given organ and radiotracer, a uniform distribution of individual rates at the detector can be assumed, regardless of geometric differences. When using radiotracer compounds with short half-lives (e.g., O-15, Rb-82, etc.), patients can be injected with very high doses, enabling short-axis FOV systems to collect sufficient data (e.g., statistics) to generate a reconstruction. For long-axis FOV systems, sensitivity and data throughput are increased.

[0003] The radiotracer compound targets a specific organ that is subsequently imaged. Due to this targeting (i.e., concentration), the individual count rate at the detector level is not distributed in the same way as in a long-axis FOV system. Long-axis FOV systems have increased detection counts and distribution because additional organs in the body may not have the same radiotracer uptake (i.e., concentration) as the target organ. Summary of the Invention

[0004] In some embodiments, a computer-implemented method is disclosed. The computer-implemented method includes the step of receiving a set of input parameters. Based on the input parameters, an average single per block of a nuclear imaging scanner with a predetermined field of view (FOV) is determined, and at least one scanning parameter is determined based on the average single per block of the nuclear imaging scanner.

[0005] In some embodiments, a system is disclosed. The system includes a nuclear imaging scanner and a computer. The computer is configured to receive a set of input parameters, determine the average per-block individual of the nuclear imaging scanner's field of view (FOV) based on the input parameters, and determine at least one scanning parameter based on the average per-block individual of the nuclear imaging scanner. Attached Figure Description

[0006] The features and advantages of the present invention will become more fully disclosed in or through the following detailed description of preferred embodiments, which will be attached to the appendix. Figure 1 Considering that the same numbers refer to the same parts, and furthermore:

[0007] Figure 1 The illustration shows a nuclear imaging system according to some embodiments.

[0008] Figure 2 A block diagram of a computer system according to some embodiments is shown.

[0009] Figure 3 The illustration shows the organ activity distribution of the brain and heart relative to long-axis FOV systems and short-axis FOV systems according to some embodiments.

[0010] Figure 4 This is a flowchart illustrating a method for estimating the expected performance of a long-axis FOV system using patient data acquired on a short-axis FOV system, according to some embodiments.

[0011] Figure 5 This is a graph illustrating the dose distribution of a long-axis FOV system according to some embodiments.

[0012] Figure 6 This is a flowchart illustrating a method for generating patient dose and location relative to a large FOV system according to some embodiments. Detailed Implementation

[0013] The description of the preferred embodiments is intended to be read in conjunction with the accompanying drawings, which are considered an integral part of the entire written description of the invention. The drawings are not necessarily to scale, and for clarity and brevity, certain features of the invention may be shown enlarged to scale or in some schematic form. In this description, relative terms such as “horizontal,” “vertical,” “up,” “down,” “top,” “bottom,” and their derivatives (e.g., “horizontally,” “downward,” “upward,” etc.) should be interpreted as referring to the orientation as described below or shown in the drawings discussed. These relative terms are for ease of description and are generally not intended to require a specific orientation. Terms including “inward” versus “outward,” “longitudinal” versus “lateral,” etc., should be interpreted relative to each other or relative to an axis of extension or rotation or a center, as appropriate. Terms such as attachment, coupling, etc., and terms such as “connected” and “interconnected” refer to a relationship in which structures are directly or indirectly fixed or attached to each other, either directly or indirectly through an intervening structure, and both movable or rigid attachments or relationships, unless otherwise explicitly described. The term "operationally coupled" is an attachment, coupling, or connection that allows the related structures to operate as intended based on that relationship. In the claims, if used, the means plus function clause is intended to cover structures described, implied, or made clear by the written description or drawings for performing the stated function, including not only structural equivalents but also equivalent structures.

[0014] Figure 1An embodiment of a nuclear imaging system 2 is illustrated. The nuclear imaging system 2 includes a scanner provided in a first gantry 16a for at least a first modality 12. The first modality 12 may include any suitable modality, such as, for example, computed tomography (CT) modality, positron emission tomography (PET) modality, single-photon emission computed tomography (SPECT) modality, etc. The first modality 12 may include a long-axis FOV scanner or a short-axis FOV scanner. A patient 17 lies on a movable patient bed 18 that is movable relative to the first gantry 16a. In some embodiments, the nuclear imaging system 2 includes a scanner provided in a second gantry 16b for a second modality 14. The second modality 14 may be any suitable imaging modality, such as, for example, CT modality, PET modality, SPECT modality, and / or any other suitable imaging modality. The second modality 14 may include a long-axis FOV scanner or a short-axis FOV scanner. Each of the first modality 12 and / or the second modality 14 may include one or more detectors 50 configured to detect annihilation photons, gamma rays, and / or other nuclear imaging events.

[0015] Scan data from the first mode 12 and / or the second mode 14 are stored in one or more computer databases 40 and processed by one or more computer processors 60 of the computer system 30. Figure 1 The graphical depiction of computer system 30 in the image is provided for illustrative purposes only, and computer system 30 may include, for example, as shown in the reference. Figure 2 The described one or more separate computing devices. Scan data may be provided by the first mode 12, the second mode 14, and / or may be provided as a separate dataset, such as from memory coupled to the computer system 30, for example. The computer system 30 may include one or more processing electronics for processing signals received from one of the plurality of detectors 50.

[0016] Figure 2 The illustration depicts a computer system 30 configured to perform one or more processes according to some embodiments. System 30 is a representative device and may include a processor subsystem 62, an input / output subsystem 64, a memory subsystem 66, a communication interface 68, and a system bus 70. In some embodiments, one or more components of system 30 may be combined or omitted, such as, for example, omitting the input / output subsystem 64. In some embodiments, system 30 may include... Figure 2 Other components not shown. For example, system 30 may also include, for example, a power subsystem. In other embodiments, system 30 may include... Figure 2 Several instances of the components shown are illustrated. For example, system 30 may include multiple memory subsystems 66. For the sake of brevity and clarity, and not limitation, [the following is a list of examples]. Figure 2 One of each component is shown in the diagram.

[0017] Processor subsystem 62 may include any processing circuitry that operates to control the operation and performance of system 30. In various aspects, processor subsystem 62 may be implemented as a general-purpose processor, a multi-processor on a chip (CMP), a special-purpose processor, an embedded processor, a digital signal processor (DSP), a network processor, an input / output (I / O) processor, a media access control (MAC) processor, a radio baseband processor, a coprocessor, a microprocessor (such as a Complex Instruction Set Computer (CISC) microprocessor, a Reduced Instruction Set Computing (RISC) microprocessor, and / or a Very Long Instruction Word (VLIW) microprocessor), or other processing device. Processor subsystem 62 may also be implemented by a controller, a microcontroller, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a programmable logic device (PLD), etc.

[0018] In various aspects, the processor subsystem 62 can be configured to run an operating system (OS) and various applications. Examples of OSs include those generally known by trademarks such as Apple OS, Microsoft Windows OS, Android OS, Linux OS, and any other proprietary or open-source OS. Examples of applications include, for example, network applications, local applications, data input / output applications, user interaction applications, etc.

[0019] In some embodiments, system 30 may include a system bus 70 coupling various system components, including a processing subsystem 62, an input / output subsystem 64, and a memory subsystem 66. System bus 70 may be any of one or more types of bus architectures, including a memory bus or memory controller, a peripheral bus or external bus, and / or a local bus using any of the available bus architectures, including but not limited to a 9-bit bus, Industry Standard Architecture (ISA), Micro Channel Architecture (MSA), Extended ISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB), Peripheral Component Interconnect Card International Association Bus (PCMCIA), Small Computer Interface (SCSI) or other proprietary buses, or any custom bus suitable for computing device applications.

[0020] In some embodiments, the input / output subsystem 6 may include any suitable mechanism or component that enables a user to provide input to the system 2 and enables the system 2 to provide output to the user. For example, the input / output subsystem 6 may include any suitable input mechanism, including but not limited to buttons, keypads, keyboards, dial wheels, touchscreens, motion sensors, microphones, cameras, etc.

[0021] In some embodiments, the input / output subsystem 64 may include a visual peripheral output device for providing a visual display to a user. For example, the visual peripheral output device may include a screen, such as a liquid crystal display (LCD) screen. As another example, the visual peripheral output device may include a portable display or projection system for providing content display on a surface remote from system 30. In some embodiments, the visual peripheral output device may include an encoder / decoder—also called a codec—to convert digital media data into analog signals. For example, the visual peripheral output device may include a video codec, an audio codec, or any other suitable type of codec.

[0022] Visual peripheral output devices may include a display driver, circuitry for driving the display driver, or both. Visual peripheral output devices may operate under the guidance of processor subsystem 62 to display content. For example, a visual peripheral output device may be able to play media playback information, application screens of applications implemented on system 30, information about ongoing communication operations, information about incoming communication requests, or device operation screens, to name just a few.

[0023] In some embodiments, the communication interface 68 may include any suitable hardware, software, or a combination of hardware and software capable of coupling the system 30 to one or more networks and / or additional devices. The communication interface 68 may be arranged to operate using any suitable technology to control information signals using a desired set of communication protocols, services, or operating procedures. The communication interface 68 may include appropriate physical connectors for connection to a corresponding communication medium—whether wired or wireless.

[0024] The carriers of communication include networks. In various aspects, networks can include local area networks (LANs) and wide area networks (WANs), and include without limitation: the Internet; wired channels; wireless channels; communication devices including telephones, computers, wires, wireless equipment, optical or other electromagnetic channels; and combinations thereof, including other devices and / or components capable of transmitting data and associated with data transmission. For example, communication environments include in-body communication, various devices, and various communication modes, such as wireless communication, wired communication, and combinations thereof.

[0025] Wireless communication modes include any communication mode between points (e.g., nodes) that at least partially utilize wireless technology, including various protocols and combinations of protocols associated with wireless transmissions, data, and devices. These points include, for example: wireless devices, such as wireless headsets; audio and multimedia devices and apparatuses, such as audio players and multimedia players; telephones, including mobile phones and cordless phones; and computers and computer-related devices and components, such as printers, network-connected machines; and / or any other suitable devices or third-party devices.

[0026] Wired communication modes encompass any communication mode between points utilizing wired technology, including various protocols and combinations of protocols associated with wired transmission, data, and devices. These points include, for example: devices such as audio and multimedia equipment and apparatus, such as audio players and multimedia players; telephones, including mobile phones and cordless phones; and computers and computer-related devices and components, such as printers, network-connected machines; and / or any other suitable device or third-party device. In various implementations, the wired communication module can communicate according to a variety of wired protocols. Examples of wired protocols can include Universal Serial Bus (USB) communication, RS-232, RS-422, RS-423, RS-485 serial protocols, FireWire, Ethernet, Fibre Channel, MIDI, ATA, Serial ATA, Fast PCI, T-1 (and its variants), Industry Standard Architecture (ISA) parallel communication, Small Computer System Interface (SCSI) communication, or Peripheral Component Interconnect (PCI) communication, to name just a few.

[0027] Therefore, in various aspects, communication interface 68 may include one or more interfaces, such as, for example, wireless communication interfaces, wired communication interfaces, network interfaces, transmission interfaces, receiving interfaces, media interfaces, system interfaces, component interfaces, switching interfaces, chip interfaces, controllers, and so on. For example, when implemented by a wireless device or within a wireless system, communication interface 68 may include a wireless interface that includes one or more antennas, transmitters, receivers, transceivers, amplifiers, filters, control logic, and so on.

[0028] In various aspects, the communication interface 68 can provide data communication functionality according to a variety of protocols. Examples of protocols may include various wireless local area network (WLAN) protocols, including the Institute of Electrical and Electronics Engineers (IEEE) 802.xx series of protocols, such as IEEE 802.11a / b / g / n / ac, IEEE 802.16, IEEE 802.20, and so on. Other examples of wireless protocols may include various wireless wide area network (WWAN) protocols, such as GSM cellular wirelessphone system protocols with GPRS, CDMA cellular wirelessphone communication systems with 1xRTT, EDGE systems, EV-DO systems, EV-DV systems, HSDPA systems, and so on. Further examples of wireless protocols may include wireless personal area network (PAN) protocols, such as infrared protocols, protocols from the Bluetooth Special Interest Group (SIG) series of protocols (e.g., Bluetooth specification versions 5.0, 6, 7, legacy Bluetooth protocols, etc.), and one or more Bluetooth profiles, and so on. Yet another example of wireless protocols may include near-field communication technologies and protocols, such as electromagnetic induction (EMI) technology. Examples of EMI technologies can include passive or active radio frequency identification (RFID) protocols and devices. Other suitable protocols may include ultra-wideband (UWB), digital office (DO), digital home, trusted platform module (TPM), ZigBee, etc.

[0029] In some embodiments, at least one non-transitory computer-readable storage medium having computer-executable instructions embodied thereon is provided, wherein, when executed by at least one processor, the computer-executable instructions cause the at least one processor to perform embodiments of the methods described herein. This computer-readable storage medium may be embodied in a memory subsystem 66.

[0030] In some embodiments, memory subsystem 66 may include any machine-readable or computer-readable medium capable of storing data, including both volatile / non-volatile memory and removable / non-removable memory. Memory subsystem 8 may include at least one non-volatile memory cell. The non-volatile memory cell is capable of storing one or more software programs. The software program may contain, for example, applications, user data, device data, and / or configuration data, or combinations thereof, to name just a few. The software program may contain instructions executable by various components of system 30.

[0031] In various aspects, the memory subsystem 66 may include any machine-readable or computer-readable medium capable of storing data, including both volatile / non-volatile memory and removable / non-removable memory. For example, the memory may include read-only memory (ROM), random access memory (RAM), dynamic RAM (DRAM), double data rate DRAM (DDR-RAM), synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory (e.g., NOR or NAND flash memory), content-addressable memory (CAM), polymer memory (e.g., ferroelectric polymer memory), phase-change memory (e.g., ovonic memory), ferroelectric memory, silicon-oxygen-nitrogen-oxygen-silicon (SONOS) memory, disk memory (e.g., floppy disk, hard disk, optical disk, magnetic disk), or card (e.g., magnetic card, optical card), or any other type of medium suitable for storing information.

[0032] In one embodiment, the memory subsystem 66 may include a file-based instruction set for performing various methods as described herein, such as those including A / B testing and cache optimization. The instruction set may be stored in any acceptable machine-readable instruction form, including source code or various suitable programming languages. Some examples of programming languages ​​that may be used to store the instruction set include, but are not limited to, Java, C, C++, C#, Python, Objective-C, Visual Basic, or .NET programming. In some embodiments, a compiler or interpreter is included to translate the instruction set into machine-executable code for execution by the processing subsystem 62.

[0033] Figure 3 The illustration shows the organ activity distribution of a first organ 102 and a second organ 104 relative to a short-axis FOV system 110 and a long-axis FOV system 120, according to some embodiments. During the scan, the patient 100 is positioned in bed, such as, for example... Figure 1The image shows a bed 18. In the short-axis FOV system 110, the FOV detection of detector 112 originates from a first set of events 114a, 114b within a first organ 102, such as the heart, and a second set of events 116a, 116b within a second organ 104, such as the brain. The short FOV limits the number of events detected from the first organ 102 or the second organ 104, thus requiring a large dose of radiotracer (e.g., a radioisotope) to generate sufficient data for reconstruction. In contrast, the large-axis FOV scanner 120 includes a detector 122 extending over a larger portion of the patient 100 (e.g., from the head to the mid-thigh). The large-axis detector 122 detects the first set of events 124a, 124b in the first organ 102 and the second set of events 126a-126e in the second organ 104. The number of events detected by the large-axis FOV scanner 120 is greater than the number of events detected by the short-axis FOV scanner 110.

[0034] In some embodiments, data obtained using a first axial FOV system (such as short axial FOV system 110) can be used to estimate the expected performance of a second axial FOV system (such as long axial FOV system 120).

[0035] Figure 4 This diagram illustrates a flowchart of method 200 according to some embodiments, which involves estimating the expected performance of long-axis FOV system 120 using patient data acquired using short-axis FOV system 110. While this document uses data from short-axis FOV system 110 to estimate the performance of long-axis FOV system 120 to discuss embodiments, it will be appreciated that systems with a first axial FOV (e.g., short, long, etc.) can be used to estimate the performance of any other system with a second axial FOV (e.g., short, long, etc.). At step 202, scan data 220 of one or more modalities is obtained using short-axis FOV system 110. Scan data 220 can be obtained using one or more suitable modalities, such as, for example, CT modal, PET modal, SPECT modal, and / or any other suitable modal. In the illustrated embodiment, the dataset includes PET and CT data.

[0036] At step 204, a system such as computer system 30 determines whether CT or topographic scan data 220a is available. If CT or topographic scan data 220a is available (e.g., a CT scan has been performed), the system locates each organ within the FOV of the small axial FOV system 110 based on the CT scan data 220a. For example, for Figure 3In the embodiment illustrated, the system can identify the heart 102 as located within the FOV of the small axial FOV system 110. The system can use any suitable method, such as organ segmentation, a trained classification network, etc., to identify organ locations. If no CT or topographic scan data 220a is available, the system uses the average location of similar patients (e.g., the average location of adult males, adult females, adolescent males, adolescent females, etc.) to estimate the location of a specific organ within the FOV 224.

[0037] At step 206, the system determines the absorbed dose 230 per unit activity applied. The absorbed dose may be determined based on the patient's biometrics, such as the patient's age 220b and / or the radiotracer 220c used during short-axis FOV scanning. For example, in some embodiments, a lookup table based on age 220b and radiotracer 220c is used to determine the absorbed dose 230 per unit activity applied. The lookup table may include publicly available data 236, such as data available, for example, in ICRP publication 128, “Radiation Dose to Patients from Radiopharmaceuticals: A Compendium of Current Information Related to Frequently Used Substances,” and / or may include non-public data, such as proprietary lookup tables.

[0038] At step 208, the absorbed dose 230 is normalized for each scanned organ 220d included in the scan data 220. The absorbed dose 230 can be normalized by selecting the organ group 220d with the highest percentage of absorption. In other embodiments, the absorbed dose 230 can be normalized using a predetermined normalization factor. At step 210, the detected activities (e.g., events) included in the scan data 220 are distributed based on a predetermined or stereo angle at the organ 220d location. The stereo angle can be based on the position of the short-axis FOV scanner 110 during data capture.

[0039] At step 212, the distributed individuals (e.g., events) are standardized by organ 220d. The distributed individuals are standardized based on the distributed activity and average per-piece rate 220e generated at step 210. For the long-axis FOV system 120, the standardized distributed individuals are equal to the average per-piece 234. At step 214, patient-specific parameters for the long-axis FOV scanner 120 are determined based on the average per-piece 234 determined at step 212, the patient dose and weight 220f for the short-axis FOV scanner 110, and / or the performance model 240 for the long-axis FOV scanner 120. The performance model 240 for the long-axis FOV scanner 120 may be predetermined based on modeling of the long-axis FOV scanner 120. In some embodiments, the patient-specific parameters for the long-axis FOV scanner 120 include a recommended dose intensity 238 and a performance value 242 for the requested activity based on the patient of the specific long-axis FOV scanner 120. In some embodiments, the recommended dose intensity 238 for the long-axis FOV scanner 120 is less than the dose for the short-axis FOV scanner 110.

[0040] Figure 5 This is a graph 300 illustrating the dose distribution 302 of a long-axis FOV system 120 according to some embodiments. Graph 300 includes an x-axis and a y-axis, where the x-axis shows the dose in kilobecquerels (kBq) per milliliter (ml), and the y-axis shows the noise equivalent count (NEC). The dose distribution 302 includes an estimated noise equivalent count (NEC) curve for a predetermined long-axis FOV scanner 120. A first position 304 on the dose distribution 302 corresponds to a recommended dose that does not take into account prior patent imaging data and / or long-axis FOV scanner performance models. A second position 306 corresponds to an optimized dose for a specific patient and a specific long-axis FOV scanner 120. Figure 5 As illustrated, the optimized dose 306 is less than the recommended dose 304, resulting in lower radiation exposure for the patient during imaging. The disclosed method 200 allows clinicians to estimate the dose for subsequent long-axis FOV scans using prior scan data, such as previous short-axis FOV PET scan data.

[0041] Figure 6 This is a flowchart 400 illustrating a method for generating patient dose and location relative to a long-axis FOV system according to some embodiments. A set of pre-scan data 402 is received by a system such as computer system 30. This set of pre-scan data 402a-402e includes system geometry information 402a of the long-axis FOV scanner 120, patient anthropometric statistics such as height and weight 402b, a set of organs to be scanned 402c, radioactive tracer identifiers 402d, and patient age 402e.

[0042] At step 404, the absorbed dose 420 per unit of activity is determined based on the patient's age 402e and a dataset that associates the radiotracer identifier 402d with dose information, such as those provided, for example, in publicly available datasets 421, such as ICRP publication 128 "Radiation Dose to Patients from Radiopharmaceuticals: A Compendium of Current Information Related to Frequently Used Substances", and / or in proprietary datasets. For example, the absorbed dose 420 per unit of activity can be determined by using a lookup table, although it will be appreciated that any suitable method can be used to identify the absorbed dose 420 per unit of activity.

[0043] At step 406, the absorbed dose 420 per unit activity and the identifier of the group of organs 402c to be scanned are used to normalize the absorbed dose 420 per unit activity to the absorption rate of the organ with the highest percentage of absorption in the group of organs 402c to be scanned.

[0044] At step 408, based on the standardized absorbed dose per unit activity 420, patient body statistics 402b, and system geometry information 402a, the expected event activity (e.g., individual activity) is distributed by organ location for a predetermined (e.g., stereo) angle. The distribution of expected event activity generates an average per individual (event) 422.

[0045] At step 410, the system identifies a performance model for the long-axis FOV scanner 120 based on an average per-piece identifier 422. The performance model includes a recommended injection dose intensity 424 and a recommended patient position 426 within the FOV. The recommended injection dose intensity 424 is patient- and long-axis FOV scanner 120-specific, and the patient position within the FOV 426 is a specific location of the bed within the FOV relative to the long-axis FOV scanner 120. In some embodiments, the computer system 30 is configured to automatically locate the patient bed at the recommended patient position within the FOV 426.

[0046] In various embodiments, the disclosed method allows clinicians to identify the optimal bed position and radiotracer dose level for producing best images. The optimal radiotracer dose level is generally a dose level lower than that recommended for short-axis FOV scanners. The disclosed method adapts dose and bed position based on patient body type and age, improves images, and reduces dose, for example, in pediatric imaging. Optimized dose levels allow clinicians to obtain only the dose required by the patient, thereby reducing the cost and inventory of radiotracers.

[0047] The various computer-implemented methods disclosed herein can be implemented using any suitable method, system, or format. For example, in some embodiments, computer-implemented methods (such as method 200 or method 400 discussed above) can be implemented by state systems, programs, functions, trained machine learning functions, neural networks, etc.

[0048] In a first embodiment, a computer-implemented method is disclosed. The method includes receiving a set of pre-scan parameters, determining an average per-block size of a long-axis field-of-view (FOV) scanner based on the pre-scan parameters, and determining at least one scan parameter based on the average per-block size of the long-axis FOV scanner.

[0049] In the computer-implemented method of the first embodiment, the average activity per individual can be based on the distribution activity by organ location at a predetermined angle of the long-axis FOV scanner. The distribution activity by organ can be determined based on the absorption rate normalized to the highest absorption organ rate of a set of target organs.

[0050] In any of the foregoing embodiments, the set of pre-scanning parameters includes patient height, patient weight, and system geometry information for the long-axis FOV scanner, and the organ distribution activity is based on patient body mass index and system geometry information.

[0051] In any of the foregoing embodiments, the pre-scan parameters may include patient age and radiotracer identifier, and the average per-piece individual may be determined based on the absorbed dose per unit of activity administered for the patient age and radiotracer identifier.

[0052] In any of the foregoing embodiments, at least one scanning parameter may include the dose intensity of the identified radioactive tracer.

[0053] In any of the foregoing embodiments, at least one scanning parameter may include the patient bed position within the FOV of the long-axis FOV scanner.

[0054] In a second embodiment, a system is disclosed. The system includes a long-axis field-of-view (FOV) scanner and a computer. The computer is configured to receive a set of pre-scan parameters, determine the average per-block size of the long-axis FOV scanner based on the pre-scan parameters, and determine at least one scan parameter based on the average per-block size of the long-axis FOV scanner.

[0055] In the second embodiment, the average activity per individual can be based on the distribution activity by organ location at a predetermined angle of the long-axis FOV scanner. The distribution activity by organ is determined based on the absorption rate normalized to the highest absorption organ rate of a set of target organs.

[0056] In any of the foregoing embodiments, the set of pre-scanning parameters may include patient height, patient weight, and system geometry information for a long-axis FOV scanner, and the distributional activity by organ may be based on patient body mass index and system geometry information.

[0057] In any of the foregoing embodiments, the pre-scan parameters may include patient age and radiotracer identifier, and the average per-piece individual may be determined based on the absorbed dose per unit of activity administered for the patient age and radiotracer identifier.

[0058] In any of the foregoing embodiments, at least one scanning parameter may include the dose intensity of the identified radioactive tracer.

[0059] In any of the foregoing embodiments, at least one scanning parameter may include the patient bed position within the FOV of the long-axis FOV scanner.

[0060] In a third embodiment, a non-transitory computer-readable medium includes instructions that, when executed by a processor, cause the processor to perform one or more computer-implemented methods disclosed herein, such as the computer-implemented methods of the first embodiment or any variations thereof.

[0061] In a fourth embodiment, a computer-implemented method is disclosed for determining the optimal dose for a long-axis FOV scanner based on data obtained using a short-axis FOV scanner. This computer-implemented method includes receiving scan data obtained using a short-axis FOV scanner and patient data associated with the scan data.

[0062] Although the subject matter has been described with reference to exemplary embodiments, it is not limited thereto. Rather, the appended claims should be interpreted broadly to include other variations and embodiments that may be made by those skilled in the art.

Claims

1. A computer-implemented method, comprising: Receive a set of input parameters; The average number of events per block in a nuclear imaging scanner with a predetermined field of view (FOV) is determined based on the set of input parameters, wherein the average number of events per block is based on organ-specific activity distribution within the nuclear imaging scanner with the predetermined FOV; and At least one scanning parameter of the long-axis FOV scanner is determined based on the average events per block of the nuclear imaging scanner.

2. The computer-implemented method of claim 1, wherein, The organ-specific activity is determined based on the absorption rate normalized to the highest absorption organ rate of a set of target organs.

3. The computer-implemented method according to claim 1, wherein, The set of input parameters includes the patient's biometrics and system geometry information of the nuclear imaging scanner, wherein the organ-specific activity distribution is based on the patient's body mass index and the system geometry information.

4. The computer-implemented method according to claim 1, wherein, The set of input parameters includes patient biometrics and a radiotracer identifier, and wherein the average per-block event is determined based on the absorbed dose per unit of activity applied to the patient biometrics and the radiotracer identifier.

5. The computer-implemented method according to claim 1, wherein, The at least one scanning parameter includes the dose intensity of the identified radioactive tracer.

6. The computer-implemented method according to claim 1, wherein, The at least one scanning parameter includes the patient's position within the predetermined field of view (FOV) of the nuclear imaging scanner.

7. A system comprising: Nuclear imaging scanner; and The computer is configured as follows: Receive a set of input parameters; The average events per block of the nuclear imaging scanner are determined based on the input parameters, wherein the average events per block are based on organ-specific activity distribution within the nuclear imaging scanner having the predetermined field of view (FOV); and At least one scanning parameter of the long-axis FOV scanner is determined based on the average events per block of the nuclear imaging scanner.

8. The system according to claim 7, wherein, The average event per block is based on the distribution of activity at predetermined locations within the nuclear imaging scanner according to organ location.

9. The system according to claim 8, wherein, The organ-specific activity is determined based on the absorption rate normalized to the highest absorption organ rate of a set of target organs.

10. The system according to claim 8, wherein, The set of input parameters includes the patient's biometrics and system geometry information of the nuclear imaging scanner, wherein the organ-specific activity distribution is based on the patient's body mass index and the system geometry information.

11. The system according to claim 7, wherein, The input parameters include patient biometrics and a radiotracer identifier, and the average per-block event is determined based on the absorbed dose per unit of activity applied to the patient biometrics and the radiotracer identifier.

12. The system according to claim 7, wherein, The at least one scanning parameter includes the dose intensity of the identified radioactive tracer.

13. The system according to claim 7, wherein, The at least one scanning parameter includes the patient bed position within the FOV of the nuclear imaging scanner.

14. A non-transitory computer-readable medium storing instructions configured to cause a computer system to perform the following steps: Receive a set of input parameters; The average number of events per block by a nuclear imaging scanner with a predetermined field of view (FOV) is determined based on the set of input parameters, wherein, The average event per block is based on organ-specific distribution activity within a nuclear imaging scanner having the predetermined field of view (FOV); and At least one scanning parameter of the long-axis FOV scanner is determined based on the average events per block of the nuclear imaging scanner.

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