WO2020242331A2

WO2020242331A2 - Coincidence detection system for measuring arterial blood time-activity curves and methods of using same

Info

Publication number: WO2020242331A2
Application number: PCT/QA2020/050007
Authority: WO
Inventors: Jim William O'DOHERTY; Othmane BOUHALI; Yassine TOUFIQUE
Original assignee: Qatar Foundation For Education, Science And Community Development; Sidra Medicine
Priority date: 2019-05-31
Filing date: 2020-05-30
Publication date: 2020-12-03
Also published as: WO2020242331A3

Abstract

The present disclosure describes a method for calculating measurements of the blood time activity curve (BTAC) for use with positron emission tomography (PET), using a small field of view coincidence detector system. The disclosed method of using a non-invasive in vivo arterial sampling system, which in combination with the use of computational stimulations, successfully calculates a blood-time activity curve (BTAC) within individual subjects. The BTAC can be used in the application of kinetic models without physical arterial sampling or reliance on image-based techniques. This method allows a non-invasive measurement of the same variable as that determined by invasive measurements, and leads to higher subject compliance.

Description

COINCIDENCE DETECTION SYSTEM FOR MEASURING ARTERIAL BLOOD TIME-ACTIVITY CURVES

AND METHODS OF USING SAME

Technical Field

[0001] The present disclosure generally relates to the field of nuclear medicine, particularly Positron Emission Tomography (PET) and simulations of a small field of view coincidence detector for the use of constructing the blood time activity curve (BTAC) and thus the arterial input function (AIF).

Cross Reference to Related Applications

[0002] This application claims the benefit of U.S. Provisional Application 62/855,338 filed on May 31, 2019, U.S. Provisional Application 62/870,315 filed on July 3, 2019, and U.S. Provisional Application 63/002,845 filed on March 31, 2020, each of which is hereby incorporated by reference in its entirety.

Background

[0003] Positron Emission Tomography (PET) is generally a functional medical imaging technique that uses radioactive materials (tracers or radiotracers) to measure metabolic processes in the body. PET is useful for measuring or detecting changes in metabolism, blood flow, absorption, etc. Once the tracer is injected into the body, it emits positrons, which can combine with neighbouring electrons to produce gamma rays. The gamma rays are generally detected by the ring of detectors within the scanner. A computer program utilizes the energy and location of the gamma rays to reconstruct a three-dimensional (3D) image of the tracer within the body.

[0004] Quantification of dynamic PET images or data is based on radiotracer kinetic modeling techniques. Kinetic modeling of the radiotracer provides a model of how the radiotracer is taken up and metabolized by an organ or tissue of interest. In general, kinetic modeling requires measurements of the time activity curve (TAC) in the tissue and the unchanged radiotracer concentration in the arterial plasma, i.e. the arterial input function (AIF). The TAC is acquired by a series of images from the PET scanner, while the AIF is typically obtained via arterial sampling. Arterial sampling is invasive; typically, a series of blood samples are collected from the radial artery starting at the time the radiotracer is injected for up to 60 to 90 minutes.

[0005] A blood time activity curve (BTAC) measurement from arterial blood can be used to calculate an arterial input function (AIF). Processing of a BTAC to determine the plasma time activity curve (PTAC) depends on the subject’s hematocrit levels, potential presence of radiolabeled metabolites, delay and decay correction. The AIF samples are often noisy and limited in numbers and can include the potential for complications such as infection, pseudoaneurysm, sepsis, and ischaemic damage. Scheer, B. et al, Clinical review: complications and risk factors of peripheral arterial catheters used for haemodynamic monitoring in anaesthesia and intensive care medicine, 2002, Crit Care. 6: 199-204. In addition, subjects are often averse to the invasive AIF sampling method and therefore, arterial cannulation often discourages patients and subjects from taking part in PET studies, and can lead to study cancellations due to technical considerations with arterial cannulation. Furthermore, skilled clinicians are required to place the cannula, adding to study costs.

[0006] Alternative methods to arterial cannulation for deriving the AIF have been explored in the past. For example, recent work developed a PET-Computed Technology (PET-CT) system designed to image rheumatoid and psoriatic arthritis in the wrist and the hands of patient, although as of now this system focuses only on high-resolution imaging of the joints of the wrist rather than detailing AIF. Chaudhari A. et al, High-resolution (18)F- FDG PET/CT for assessing disease activity in rheumatoid and psoriatic arthritis : findings of a prospective pilot study, 2016, Br J Radial. 89:20160138.

[0007] Non-invasive approaches of determining the AIF and/or BTAC have also been developed, with the most common being the use of an image derived input function (IDIF) which can be determined through dynamic framing and reconstruction of the images of the initial phases of the radiotracer injection. Christensen, A. et al, Calibrated image-derived input functions for the determination of the metabolic uptake rate of glucose with [18FJ-FDG PET, 2014, Nucl Med Commun. 35:353-61. For certain studies, this IDIF can be obtained by the use of regions/volumes of interest in large vessels or blood pools where partial volume effects are minimal such as the aorta, or the left ventricle. However, in studies where large vessels and blood pools are not in the field of view (i.e. brain) regions of interest in smaller vessels (on the order of the scanner resolution must be used), requiring more complex processing methods for correcting for the effects of partial volume and the associated underestimation of peak activity. Blood samples may also still be required if there is metabolism of the tracer during the scan. There are many works detailing methods for segmenting vessels in the head and neck, and employing various partial volume processing techniques such as the use of recovery coefficients (Croteau, E. et al, Image-derived input function in dynamic human PET/CT: methodology and validation with ⁿC-acetate and ¹⁸ F- fluorothioheptadecanoic acid in muscle and ¹⁸F-fluorodeoxyglucose in brain, 2010, Eur J Nucl Med Mol Imaging, 37:1539-50), MR-guided segmentation (Sari, H., et al, Estimation of an image derived input function with MR-defined carotid arteries in FDG-PET human studies using a novel partial volume correction method, 2017, J Cereb Blood Flow Metab. 37:1398- 409), factor analysis (Simoncic, U. et al, Image-derived input function with factor analysis and a-priori information, 2015, Nucl Med Commun, 36:187-93), and dispersion modeling (Islam, M. et al, Estimation of arterial input by a noninvasive image derived method in brain H2(15)0 PET study: confirmation of arterial location using MR angiography, 2017, Phys Med Biol 62:4514-24).

[0008] Recent studies have shown that IDIF can only be successfully implemented with a minority of tracers. Therefore, it is not a“one-size-fits-all” approach to kinetic modeling and remains logistically challenging. Zanotti-Fregonara, P. et al, Population-based input function and image-derived input function for [(1 )(1 )C](R)-rolipram PET imaging: methodology, validation and application to the study of major depressive disorder, 2012, Neuroimage, 63:1532-41; Zanotti-Fregonara, P. et al, Population-based input function modeling for [(18)FJFMPEP-d 2, an inverse agonist radioligand for cannabinoid CB1 receptors: validation in clinical studies, 2013, PloS One, 8:e60231.

[0009] Population-based input functions (PBIF) have also gained interest as a way to avoid the reliance on invasive arterial measurements. This technique is based on the individual scaling of an already-defined tracer- specific input function of standard shape, and scaling can be performed a number of ways. For example, if blood is extracted for scaling, the technique typically requires a much-reduced number of venous blood samples over the scan length [Zanotti-Fregonara, 2012; Zanotti-Fregonara, 2013; Contractor K. et al, Evaluation of limited blood sampling population input approaches for kinetic quantification of [18F]fluorothymidine PET data, 2012, EJNMMI Res, 2: 11. Although not affected by issues with image quality or resolution, PBIF is usually represented by a mathematical function, and its greatest limitation is that the input function shape is determined from a specific population, such as healthy subjects, which may be inherently different from other populations, such as patients. Differences among populations can be due to altered metabolism/uptake of the radioligand. Furthermore, the accuracy of PBIF depends on the metabolite fraction of the tracer, and previous work has revealed issues in the accuracy of ^UC- PBR28 due to low parent fraction of the tracer at the end of the scan. Simoncic, 2015.

[0010] Tissue uptake functions have also been employed which have the potential to avoid any measurement of the AIF and/or BTAC from images or from blood. In a recent study, quantifying cerebral blood flow in 29 subjects using ¹⁵0-H20 employed a technique whereby the AIF and/or BTAC can be simulated using the tissue uptake function (from imaging) and a rate constant. Kudomi, N. et al, Reconstruction of input functions from a dynamic PET image with sequential administration of (15)02 and for noninvasive and ultra rapid measurement of CBF, OEF, and CMR02, 2018, J Cereb Blood Flow Metab, 38:780- 92; Kudomi, N. et al, Reconstruction of an input function from a dynamic PET water image using multiple tissue curves, 2016, Phys Med Biol, 61:5755-67. The estimated difference between measured and simulated AIF and/or BTAC and associated parametric maps were approximately < 10%. Although the technique shows promise, it requires the calculation of a minimum of 500 tissue uptake curves to enable the simulation, and is thus requires significant resources and experience to operate.

[0011] Accordingly, there is a need for alternative methods. Disclosed herein is an alternative method using simulations of a small field of view coincidence detector in order to construct the BTAC in vivo, without the need for invasive arterial sampling or the complex processing techniques and limitations associated with IDIF. Also disclosed herein is a novel, non-invasive in vivo arterial sampling system, which in combination with the use of computational stimulations, may successfully record BTAC in a subject. The BTAC can be used in the application of kinetic models without physical arterial sampling or reliance on image-based techniques. Allowing a non-invasive measurement of the same variable as that determined by invasive measurements, will lead to higher patient compliance. Summary

[0012] The present disclosure is, in part, related to a novel, non-invasive in vivo arterial sampling system for use during or related to PET studies. Specifically, the methods relate to the use of computational stimulations for measuring and/or recording BTAC using detectors in coincidence. The stimulations and recordings can be used to design and build future devices.

[0013] As described herein, in some embodiments are methods for calculating BTAC are provided. The methods use an external detection system aimed at non-invasively measuring BTAC in vivo using simulations of a small field of view coincidence detector.

[0014] According to one non-limiting aspect of the present disclosure, an example embodiment of a method for calculating measurements of a blood time activity curve (BTAC) for use with positron emission tomography (PET) is described. The detector system may be arranged in an open ring configuration.

[0015] In an embodiment, the detector system arranged in an open ring configuration may comprise a small field of view coincidence detector system.

[0016] In an embodiment, the detector system arranged in an open ring configuration may be comprised of detectors.

[0017] In an embodiment, the detectors of the open ring may be comprised of scintillation crystal material.

[0018] In an embodiment, the open ring may be comprised of at least one detector.

[0019] In an embodiment, the open ring may be comprised of eight detectors.

[0020] In an embodiment, the detectors of the open ring may be comprised of the scintillation crystal material Bismuth Germanate (BGO).

[0021] In an embodiment, the detector system arranged in an open ring configuration may use a pulsatile blood flow model of stimulation. [0022] In an embodiment, the detector system may be comprised of more than one open ring.

[0023] In an embodiment, a method of calculating measurements of a blood time activity curve (BTAC) for use with positron emission tomography (PET) is described. The detector system may be arranged in a closed ring configuration.

[0024] In an embodiment, the detector system arranged in a closed ring configuration may comprise a small field of view coincidence detector system.

[0025] In an embodiment, the detector system arranged in a closed ring configuration may be comprised of detectors.

[0026] In an embodiment, the detectors of the detector system arranged in a closed ring configuration may be comprised of scintillation crystal material.

[0027] In an embodiment, the closed ring may be comprised of at least one detector.

[0028] In an embodiment, the closed ring may be comprised of fourteen detectors.

[0029] In an embodiment, the detectors of the closed ring may be comprised of the scintillation crystal material Bismuth Germanate (BGO).

[0030] In an embodiment, the detector system arranged in a closed ring configuration may use a pulsatile blood flow model of stimulation.

[0031] In an embodiment, the detector system may be comprised of more than one closed ring.

Brief Description of the Drawings

[0032] FIG. 1 shows an embodiment. FIG. 1A shows a cross section drawing of the lower forearm; detailing the anatomical location of the blood vessels and bones near the wrist, based on MR images. FIG. IB shows a shows a cross section schematic of the basic wrist phantom (not drawn to scale). [0033] FIG. 2 shows an embodiment of the wristPET 1 and wristPET 2 simulated scanner systems. The wristPET 1 system consists of fourteen detectors in a closed ring design (FIG. 2A). The second system, wristPET 2 consists of a subset of detectors (eight detectors; detector Nos. 4-11) in an open-ring design (FIG. 2B).

[0034] FIG. 3 shows an embodiment of an open-ring simulated scanner system, wristPET 2, with more than one detection ring. For example, two, three, and four axial rings of detectors may be used.

[0035] FIG. 4 shows singles and coincidence rates for each of five crystal material types (Bismuth Germanate (BGO), Gadolinium Orthosilicate (GSO), Lutetium Oxyorthosciilicate (LSO), Cerium Bromide (CeBr3), Lanthanum Bromide (LaBr3)) using wristPET 1 (FIG.2A). The highest counts for singles and coincidence events is observed for BGO crystals.

[0036] FIG. 5 shows count rate performance of the eight detector system embodiment, the wristPET 2 (FIG. 2B) using a point source at different Y positions inside about an 8 cm diameter water phantom. FIG. 5A shows count rate performance at Y position about -1 cm below the center of the scanner. FIG. 5B shows count rate performance at Y position about - 2 cm below the center of the scanner. FIG. 5C shows count rate performance at Y position about -3 cm below the center of the scanner. FIG. 5D shows the comparison of NECR at Y = -1 cm, Y = -2 cm, and Y = -3 cm, where NECRmax is 8,360 cps, 13041 cps and 20,476 cps at an activity of 3.5 MBq.

[0037] FIG. 6 shows single and prompt count rate of a pulsatile flow model using models of BTAC and the wristPET 2 system (FIG. 2B), for ^1SF (FIGS. 6A and 6B) and ¹⁵0 (FIGS. 6C and 6D).

[0038] FIG. 7 shows simulations performed using wristPET 2 with its single ring (FIG. 2B), compared to adding additional rings of detectors; an extra one, two, and three rings of detectors (FIG. 3). Count rates were largely enhanced by the addition of extra detection rings, leading to higher overall sensitivity of the system, for both ^1SF (FIGS. 7A, 7B, and 7C) and

¹⁵0 (FIGS. 7D, 7E, and 7F).

[0039] FIG. 8 shows total singles and coincidence event rates for wristPET 2 system (FIG. 2B) with its single ring, compared to adding additional rings of detectors; an extra one, two, and three rings of detectors (FIG. 3). Count rates were enhanced by the addition of extra detection rings (FIG.8), leading to higher overall sensitivity of the system for both ^1SF (FIGS. 8A and 8B) and ¹⁵0 (FIGS. 8C and 8D).

[0040] FIG. 9 shows the increased sensitivity of the addition of extra detection rings (FIG. 3) compared to the single ring of wristPET 2 (FIG. 2B). Singles and coincidences for the stimulated ^1SF (FIGS. 9A and 9B) and ¹⁵0 (FIGS. 9C and 9D), were performed in a full, three-dimensional (3D) acquisition using a pulsatile blood flow model.

Detailed Description

[0041] Definitions

[0042] Some definitions are provided hereafter. Nevertheless, definitions may be located in the“Embodiments” section below, and the above header“Definitions” does not mean that such disclosures in the“Embodiments” section are not definitions.

[0043] As used herein,“about,”“approximately” and“substantially” are understood to refer to numbers in a range of numerals, for example the range of -10% to +10% of the referenced number, preferably -5% to +5% of the referenced number, more preferably -1% to +1% of the referenced number, most preferably -0.1% to +0.1% of the referenced number.

[0044] All numerical ranges herein should be understood to include all integers, whole or fractions, within the range. Moreover, these numerical ranges should be construed as providing support for a claim directed to any number or subset of numbers in that range. For example, a disclosure of from 1 to 10 should be construed as supporting a range of from 1 to 8, from 3 to 7, from 1 to 9, from 3.6 to 4.6, from 3.5 to 9.9, and so forth.

[0045] As used in this disclosure and the appended claims, the singular forms“a,”“an” and“the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to“a component” or“the component” includes two or more components.

[0046] The words“comprise,”“comprises” and“comprising” are to be interpreted inclusively rather than exclusively. Likewise, the terms“include,”“including,”“containing” and“having” should all be construed to be inclusive, unless such a construction is clearly prohibited from the context. Further in this regard, these terms specify the presence of the stated features but not preclude the presence of additional or further features.

[0047] Nevertheless, the compositions and methods disclosed herein may lack any element that is not specifically disclosed herein. Thus, a disclosure of an embodiment using the term“comprising” is (i) a disclosure of embodiments having the identified components or steps and also additional components or steps, (ii) a disclosure of embodiments“consisting essentially of’ the identified components or steps, and (iii) a disclosure of embodiments “consisting of’ the identified components or steps. Any embodiment disclosed herein can be combined with any other embodiment disclosed herein.

[0048] The term“and/or” used in the context of“X and/or Y” should be interpreted as “X,” or“Y,” or“X and Y.” Similarly,“at least one of X or Y” should be interpreted as“X,” or“Y,” or“X and Y.”

[0049] Where used herein, the terms “example” and “such as,” particularly when followed by a listing of terms, are merely exemplary and illustrative and should not be deemed to be exclusive or comprehensive.

[0050] A“subject” or“individual” is a mammal, preferably a human.

[0051] Embodiments

[0052] A preferred embodiment consists of a basic phantom of the human lower forearm. The phantom design, based on Magnetic Resonance (MR) images of the human forearm (FIG. 1A), consists of a cylinder, about 20 cm long and about 8 cm in diameter (FIG. IB). Internally, two additional cylinders, about 2.5 cm in diameter, represent the radius and ulna bones (given the physical properties of bone; according to the Geant4 Application for Tomographic Emission (GATE) simulations). Jan, S. et al, GATE - Geant4 Application for Tomographic Emission: a simulation toolkit for PET and SPECT, Oct. 7, 2004, Phys Med Biol, 49(19): 4543-4561. These two cylinders, positioned parallel to the central axis, are separated by a distance of about 1.1 cm. Furthermore, two additional cylinders, representing the radial and ulnar arteries, are about 2.5 mm in diameter (given the physical properties of blood). In addition, two cylinders of about 1.5 mm diameter each, representing the radial and ulnar veins, are also included. Preferably, the background tissue in the phantom is given the properties of water. Also, preferably, the phantom is centered in the scanner geometry on simulation.

[0053] Disclosed is an embodiment, a simulated scanner, the wristPET 1 configuration (FIG.2A). The wristPET 1 configuration is a simulated scanner that comprises approximately fourteen detectors organized in a single ring. Generally, the ring diameter fits the dimension of a human wrist circumference, about 10.94 cm (FIG. 2A). Additionally, or alternatively, other ring diameters may be used by a person of ordinary skill in the art.

[0054] In addition, the closed ring configuration of the wristPET 1 system, may comprise more than fourteen detectors. In addition, or alternatively, the closed ring configuration of the wristPET 1 system, may also comprise less than fourteen detectors. The number of detectors in the ring and their size may be further optimized with minimal or no reduction in detection efficiency.

[0055] Also disclosed is another embodiment, a simulated scanner, the wristPET 2 configuration (FIGS. 2B and 3B). The wristPET 2 configuration is a simulated scanner comprises a subset of the wristPET 1 detectors. The wristPET 2 comprises eight detectors (detector Nos. 4-11) organized in an open-ring. The distance between detectors Nos. 4 and 11 can be determined by one of ordinary skill in the art, similar to the diameter of wristPET 1.

[0056] In addition, the open-ring configuration of the wristPET 2 system, may comprise more than eight detectors. In addition, or alternatively, the open-ring configuration of the wristPET 2 system, may also comprise less than eight detectors. The number of detectors in the ring and their size may be further optimized.

[0057] Each detector consists of a monolithic scintillation crystal (FIGS. 2 and 3). The crystal materials are identified in Table I: Bismuth Germanate (BGO), Gadolinium Orthosilicate (GSO), Lutetium Oxyorthosciilicate (LSO), Cerium Bromide (CeBr3), Lanthanum Bromide (LaBr3). Michel, C. et al, Influence of crystal material on the performance of the HiRez 3D PET scanner: A Monte Carlo study, 2006, IEEE Nuclear Science Symposium Conference Record. The dimensions of the independent crystals can vary. For example, independent crystals or single detector can measures approximately 2.45 x 2.0 x 3 cm³ (FIG. 2) or to a size selected by a person of ordinary skill in the art. Owing to the low scatter properties of the simulated geometry, scatter corrections were not applied.

Table I

Properties of scintillator materials

Z_eff represents the effective atomic number and stopping power and can be calculated as the inverse of the attenuation length.

[0058] In a preferred embodiment, the detector comprises BGO crystals.

[0059] There are a number of aspects to be considered for the development of the wristPET 1 and wristPET 2 detection systems. For example, the choice of the scintillation crystal material type can be a trade-off between different important parameters such as decay time, material density, thickness, etc. For the requirements of producing a BTAC, generation of an image may not be required, and therefore, crystals that are known to produce better image quality, such as LSO crystals, may not be the best choice. Melcher, C.L., Scintillation of crystals for PET , 2000, J Nucl Med, 41:1051-5.

[0060] Embodiments disclosed herein, can utilize crystals with higher decay time and longer coincidence time window, at the expense of a higher randoms rate and longer decay time, such as BGO. This can provide adequate performance for the signal detection purposes. A higher decay time of the scintillation crystal may be acceptable due to the expected activity concentration (and thus, the count rate) being lower than that measured. For example, in the left ventricle, due to dilution of the radiotracer by the time the bolus reaches the position of the radial and ulnar arteries. In this case, the trade-off for higher detector efficiency is warranted, with a relatively low risk of encountering issues with dead-time losses. Monolithic BGO crystals can also be desirable because of lower cost implications for fabrication of the system, higher photoelectric fraction (percentage of photons interacting with the photoelectric effect) and lack of intrinsic radioactivity (present in some LSO crystals depending on the crystal growing technique).

[0061] Furthermore, another embodiment is disclosed, wherein the simulated scanner consists of an open-ring configuration with added detection rings in the axial direction (FIG. 3). More than one detection ring can be used, for example, two axial rings of detectors (about 6 cm FoV), three axial rings of detectors (about 9 cm FoV), and/or four axial rings of detectors (about 12 cm FoV). The term“ring” alone, does not necessarily define wither the ring is “open” or“closed.” More than four axial rings of detectors may also be used.

[0062] Also disclosed is a method of stimulating the wristPET 1 and/or the wristPET 2 systems that employs a constant, uniform blood velocity through the veins. This first blood flow model, uses a uniform blood flow through the arterial vessels of the phantom (assuming a mean value of about 15 cm/sec). For this uniform blood flow model, venous return blood does not need to be included (as described below), although it can be included if desired by one of ordinary skill in the art.

[0063] Another method of stimulating the wristPET 1 and/or the wristPET 2 systems is also disclosed and comprises a more realistic pulsatile blood flow model. In the pulsatile blood flow model, the cylinders representing the arteries are moved through the scanner in a pulsatile motion according to a measured velocity profile of blood through the radial artery. Masuda, M. et al, Evaluation of blood flow velocity waveform in common carotid artery using multi-branched arterial segment model of human arteries, 2013, Biomed Signal Proc Control, 8:509-19. Generally, a standard heart rate of about 60 bpm for repetition of the pulses can be utilized. Venous return of blood from the capillary bed of the hand can be can be simulated, in the opposite direction of the arterial flow, through the radial and ulnar veins of the phantom at a uniform velocity of about 5 cm/s at a reference time of about 5 seconds later. Hellige, G. et al, Measurement of arterial and venous reactivity by an advanced strain gauge plethysmograph, 1979, Angiology, 30:539-48.

[0064] In both blood flow models disclosed herein, changes in the activity concentration for providing a simulation of the BTAC were achieved by employing a model linear- exponential equation. The equations were fitted to a sample BTACs acquired from patient studies on a fully calibrated, automated blood sampling system (Allogg AB, Sweden) acquiring extracted arterial blood activity concentration after an injection of 1000 MBq of [¹⁵0] H2O and 250 MBq [¹⁸F]-fallypride at 1 second intervals. Two average BTACs were created from five samples of these tracers, respectfully, and the series of equations used to fit these two averages can be summarized as, Equation 1 (Eq. 1):

McGrath, D. et al, Comparison of model-based arterial input functions for dynamic contrast-enhanced MRI in tumor bearing rats , Magn Reson Med. 2009, 61(5): 1173-84. Parameters used can be found in Table II. Fits of the average BTAC curves were both r²

>0.98.

Table

Fit parameters for arterial

nd venous data fits to

[¹⁵0]-H20 and [¹⁸F]-fallypride data using, Eg. 1

[0065] These fitted noise-free BTACs can be used as input to the radial and ulnar arteries of the phantom, for the specific radiotracer with the activity concentration of the arteries of the phantom varied according to the activity concentration as determined from Eq. 1. The function describing volumetric flow per unit time can be implemented along with the function describing the changing activity concentration of the sources as described by Eq. 1.

[0066] Eq 1 can also, optionally be used to generate dispersed (broadened peak with concomitant loss of peak height) and/or delayed (time shifted) venous output functions with the following parameters: for ¹⁵0-H20 venous functions, parameters: a = 2.606867, b = -4.457742e + 02, ci = 1.809687e + 05, di = -3.902e - 02, c₂ = 2.06, and di = -8.271e - 04. Parameters for the ¹⁸F-fallypride fit were: a = 1.291773e - 01, b = -2.208932e + 01, ci = 1.19687e + 04, di = -3.902e - 02, c₂ = 2.06, and di = -8.27 le - 04.

[0067] Additionally, other blood flow models, known to a person of ordinary skill in the art may be employed with either of the detection systems disclosed herein

[0068] In accordance with non-limiting aspect of the present disclosure, which may be used in combination with each or any of the above-mentioned aspects, the method allows for calculation of BTAC where large blood vessels and/or blood pools are not in the field of view. The method may be used in brain studies.

[0069] In accordance with a non-limiting aspect of the present disclosure, which may be used in combination with each or any of the above-mentioned aspects, the method allows for smaller blood vessels to be examined. The method prevents underestimation of peak activity.

[0070] In accordance with a further, non-limiting aspect of the present disclosure, which may be used in combination with each or any of the above-mentioned aspects, the method is more accurate than population based input functions and less time consuming than tissue uptake functions.

[0071] In accordance with another, non-limiting aspect of the present disclosure, which may be used in combination with each or any of the above-mentioned aspects, the method is not limited to specific tracers or processing pipelines and provides a measurement of BTAC in the same manner as online arterial blood extraction systems.

[0072] In accordance with another, non-limiting aspect of the present disclosure, which may be used in combination with each or any of the above-mentioned aspects, the method of calculating BTAC disclosed herein, improves compliance and participation of people taking part in PET studies.

Examples

[0073] General Methods [0074] GATE simulations were performed using a Raad2, Cray XC40-AC supercomputer with 4,128 Intel Xeon Haswell cores; containing 172 computation nodes, each with 24 cores, along with 128GB of RAM. However, any capable computer generally known to a person of ordinary skill in the art can be used to perform the simulations. GATE (Geant4 Applied for Tomographic Emission) is a Monte Carlo code based on GEANT4. Surrut, D. et al, A review of the use and potential of the GATE Monte Carlo code for radiation therapy and dosimetry applications, 2014, Med. Phys. 41(6): 06430E It includes specific modules required to perform realistic simulations of imaging technology and offers a complete set of validated physical models, description of complex geometries, description of the source motion and geometry, generation and monitoring of particles, visualization of volumes and particle trajectories.

[0075] Example 1

[0076] Five different crystal materials were tested using the wristPET 1 system (FIG. 2A), including GSO, LSO, BGO, CeBR3, and LaBr3. Simulations were performed to determine the crystal material with the highest efficiency for low activity detection. In all simulation cases, the digitizer module converting hits to singles and coincidences consisted of a series of signal processors (adder, readout, blurring, deadtime, energy response, spatial response, and threshold electronics). Random corrections were applied to the resulting coincidence count rate data using the‘ KeepIfAUAreGood' policy of the coincidence sorter. The coincidence time of the crystal itself was used.

[0077] Singles and coincidence rates for each of the five crystal material types are shown in FIG. 4, considering single sources of radiation travelling through the ulnar and radial arteries only (no venous return of blood in this simulation), at a uniform velocity (uniform blood flow model). The highest counts for singles and coincidence events was observed for BGO crystals. Similar responses were observed for LaBr3 and CeB3, therefore, they appear as overlapping in FIG. 4.

[0078] The same experiment was performed with the wristPET 1 system, having the dimensions shown in FIG. 2A. Singles and coincidence rates for each of the five crystal material types are shown in FIG. 4. A summary of the peak singles rates (kcps), sensitivity (cps/kBq), and relative efficiency for each of the five crystal materials types are shown in

Table III.

Table III

Summary of simulations comparing crystal sensitivity and relative e fficiency

[0079] Example 2

[0080] The anatomical position of the blood vessels transporting blood through the forearm/wrist of humans is primarily towards the volar or ventral aspect of the forearm. Thus, in the simulated phantom (and the position of the phantom inside the scanner), plotting the total number of singles on the detectors of wristPET 1 over an entire simulation demonstrates that the majority of coincident events (> 75%) are observed in detector Nos. 4-12. A similar effect is noted in PET myocardial perfusion scans during the initial phases of dynamic imaging owing to the proximity of the heart to the top of a full ring clinical PET scanner. O' Doherty, J. et al, Effect of scanner dead time on kinetic parameters determined from image derived input functions in 13N cardiac PET, 2014, SNMMI Annual Meeting 2014, St Louis, USA; O' Doherty, J. et al, The effect of high count rates on cardiac perfusion quantification in a simultaneous PET-MR system using a cardiac perfusion phantom, 2017, EJNMMI Phys. 4:31. Thus, given that approximately 25% of singles are incident on the remaining detectors of wristPET 1, wristPET 2 provides an alternative design to the full, closed ring system, without significant reduction in the count statistics.

[0081] Example 3

[0082] Simulations of the count rate capabilities for the wristPET 2 system (FIG. 2B) were analysed using a decaying point source experiment, with a 1 ml point source of activity (14 MBq of ^1SF at starting time) located within an 8 cm diameter water-only phantom, entirely in the FoV of the system in three different positions corresponding to where the arteries may be found. The point source (1 mm³) was simulated at the position of (X, Y, Z) = (0 cm, -1 cm, 0 cm), (0 cm, -2 cm, 0 cm) and (0 cm, -3 cm, 0 cm) and the count rates determined as the source decayed. NECR (noise equivalent count rate) was calculated with the standard equation:

where T, S, R represent the number of true, scatter and random coincidences respectively and k=l for this configuration. Furthermore, we also performed simulations of added detection rings in the axial direction (two, three and four rings) of wristPET 2 (FIG. 3) in order to investigate increased sensitivity of the system.

[0083] Results for count rate performance of the wristPET 2 system (FIG. 2B) are shown in FIG. 5, using a point source at different Y positions inside an 8 cm diameter water phantom at Y = - 1 cm below center of the scanner (FIG. 5A), Y = -2 cm below the center of the scanner (FIG. 5B), and Y = -3 cm below the center of the scanner (FIG. 5C). FIG. 5D shows a comparison of NECR at Y = -1 cm, Y = -2 cm, and Y = -3 cm where NECRmax is 8,360 cps and 20,476 cps at an activity of 3.5 MBq.

[0084] In addition, differences in sensitivity due to the use of different radiotracers for ^1SF and ¹⁵0 was also investigated, given that these radiotracers are commonly used in brain studies where large vessels or blood pools are unlikely to be in the imaging field of view and cannot be used for image-based input functions. Use of these radiotracers for imaging studies nominally uses different levels of injected activity of approximately 250 MBq and 1,000 MBq for ^1SF and ¹⁵0, respectively.

[0085] Simulations were performed using the wristPET 2 system (FIG. 2B) using fits to measured BTAC corresponding to injections of approximately 250 MBq of ¹⁸F and 1,000 MBq of ¹⁵0, in order to evaluate the characteristics of the wristPET 2 system to high and low count rates. Results of single and prompt count rate of a pulsatile flow model using models of BTAC and the wristPET 2 system are displayed in FIGS. 6A and 6B for ¹⁸F and in FIGS. 6C and 6D for ¹⁵0. An overlap of the signals from the venous and arterial functions can be observed, in these cases with only a small contribution from the veins. In both cases (¹⁸F and ¹⁵0), the coincidence rates show that the BTAC can be described by the system. Less noise is noted for the BTAC described due to ¹⁵0, as the activity used in the simulation was four times higher than that of ^1SF.

[0086] Simulations were performed to investigate the sensitivity of wristPET 2 with its single ring (FIG. 2B), compared to adding additional rings of detectors; an extra one, two, and three rings of detectors (FIG. 3). All variables were kept constant, except for the number of detection rings and full three-dimensional (3D) coincidences between the rings was allowed. Count rates were largely enhanced by the addition of extra detection rings (FIG. 7), leading to higher overall sensitivity of the system. Gains of over a factor of five were obtained for an increase of one to four rings of BGO crystals, and the summation of the arterial and venous return curves can be clearly observed in the simulations of both ^1SF (FIGS. 7A-C) and 1⁵0 (FIGS. 7D-F). Furthermore, the sensitivity can be seen to increase in a linear manner with the addition of extra detection rings (Table IV).

Table IV

Gain in singles rates, coincidence rates, and sensitivity for the wristPET 2 system (FIG. 2B)

with increasing number of detection rings.

[0087] Example 4

[0088] An additional simulation was performed, similar to Example 3, using the wristPET 2, but with the dimensions represented in FIG. 2B, using BGO crystals. Similar to Example 3, additional rings of the detectors were also added (an extra one, two, and three rings of detectors, as shown in FIG. 3). Here, simulations were performed with initial injected activity of 350 MBq for ^1SF and 1,000 MBq for ¹⁵0. Both the uniform and the pulsatile blood flow models were used.

[0089] Simulations using the pulsatile blood flow model with additional rings of detectors revealed that count rates were enhanced by the addition of the extra detection rings (FIG. 8), similar to results shown in Example 3. Here, gains of over a factor of seven in the singles rate were obtained for an increase of one to four rings of BGO crystals. In addition, the summation of the arterial and venous return curves can be clearly observed in the simulations of both ^1SF (FIGS. 8A and 8B) and ¹⁵0 (FIGS. 8C and 8D). Furthermore, a larger increase in the number of coincidences up to 100 was observed. The sensitivity of the addition of extra detection rings can be seen to increase in a linear manner when allowing for cross ring detection (FIG. 9; Table V).

Table V

with increasing number of detection rings.

Claims

Claims The invention is claimed as follows:

1. A method of calculating measurements of a blood time activity curve (BTAC) for use with positron emission tomography (PET) comprising: using a detector system arranged in an open ring configuration.

2. The method of claim 1, wherein the detector system comprises a small field of view coincidence detector system.

3. The method of claim 1, wherein the detector system is comprised of detectors.

4. The method of claim 3, wherein the detectors are comprised of scintillation crystal material.

5. The method of claim 1, wherein the open ring is comprised of at least one detector.

6. The method of claim 1, wherein the open ring is comprised of eight detectors.

7. The method of claim 4, wherein the scintillation crystal material is Bismuth Germanate (BGO).

8. The method of claim 1, including using a pulsatile blood flow model of stimulation.

9. The method of claim 1, wherein the detector system comprises more than one open ring.

10. A method of calculating measurements of a blood time activity curve (BTAC) for use with positron emission tomography (PET) comprising: using a detector system arranged in a closed ring configuration.

11. The method of claim 10, wherein the detector system comprises a small field of view coincidence detector system.

12. The method of claim 10, wherein the detector system is comprised of detectors.

13. The method of claim 12, wherein the detectors are comprised of scintillation crystal material.

14. The method of claim 10, wherein the closed ring is comprised of at least one detector.

15. The method of claim 10, wherein the closed ring is comprised of fourteen detectors.

16. The method of claim 10, wherein the scintillation crystal material is Bismuth Germanate (BGO).

17. The method of claim 10, including using a pulsatile blood flow model of stimulation.

18. The method of claim 10, wherein the detector system comprises more than one closed ring.