Simultaneous quantitative imaging of two PET radiotracers via the detection of positron–electron annihilation and prompt gamma emissions

Pratt, Edwin C.; López-Montes, Alejandro; Volpe, Alessia; Crowley, Michael J.; Carter, Lukas M.; Mittal, Vivek; Pillarsetty, Nagavarakishore; Ponomarev, Vladimir; Udías, J. M.; Grimm, Jan; Herraiz, Joaquín L.

doi:10.1038/s41551-023-01060-y

Cited by 47 publications

(13 citation statements)

References 52 publications

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“…It is worth mentioning that MCGPU-PET is the only one that allows additional gamma emissions from non-pure beta emitters. This feature was successfully utilized to eliminate spurious background signals from triple coincidences by Pratt et al (2023). It is noteworthy that several other physical processes are not accounted for in any of the GPU-optimized PET simulators, such as the lutetium activity within detectors, the impact of magnetic fields on positron range, or the simulation of optical photons within the detectors.…”

Section: Discussionmentioning

confidence: 99%

UMC-PET: a fast and flexible Monte Carlo PET simulator

Galve,

Arias-Valcayo,

Villa-Abaunza

et al. 2024

Phys. Med. Biol.

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Objective.The GPU-based Ultra-fast Monte Carlo Positron Emission Tomography simulator (UMC-PET) incorporates the physics of the emission, transport and detection of radiation in PET scanners. It includes positron range, non-colinearity, scatter and attenuation, as well as detector response. The objective of this work is to present and validate UMC-PET as a a multi-purpose, accurate, fast and flexible PET simulator. Approach. We compared UMC-PET against PeneloPET, a well-validated MC PET simulator, both in preclinical and clinical scenarios. Different phantoms for scatter fraction (SF) assessment following NEMA protocols were simulated in a 6R-SuperArgus and a Biograph mMR scanner, comparing energy histograms, NEMA SF, and sensitivity for different energy windows. A comparison with real data reported in the literature on the Biograph scanner is also shown.Main results. NEMA SF and sensitivity estimated by UMC-PET where within few percent of PeneloPET predictions. The discrepancies can be attributed to small differences in the physics modeling. Running in a 11 GB GeForce RTX 2080 Ti GPU, UMC-PET is ~1500 to ~2000 times faster than PeneloPET executing in a single core Intel(R) Xeon(R) CPU W-2155 @ 3.30GHz. Significance. UMC-PET employs a voxelized scheme for the scanner, patient adjacent objects (such as shieldings or the patient bed), and the activity distribution. This makes UMC-PET extremely flexible. Its high simulation speed allows applications such as MC scatter correction, faster system response matrix estimation for complex scanners, or even MC iterative image reconstruction.

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Section: Discussionmentioning

confidence: 99%

UMC-PET: a fast and flexible Monte Carlo PET simulator

Galve,

Arias-Valcayo,

Villa-Abaunza

et al. 2024

Phys. Med. Biol.

Self Cite

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“…For example, if a subject is administered with 44 Sc and 124 I simultaneously, it can discern the uptake maps of the two different isotopes, by tagging the LOR with the energy of the corresponding coincident gamma. Some recent work on so-called multiplexed PET (mPET) imaging has been done for a small animal PET scanner consisting of LSO crystals [33].…”

Section: Jinst 19 P01001mentioning

confidence: 99%

Tracking a moving point source using triple gamma imaging

Chmeissani,

Kolstein,

Ariño-Estrada

et al. 2024

J. Inst.

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With positron emission tomography (PET), the positron of a β + emitter radioisotope annihilates with a nearby electron producing a pair of back-to-back 511 keV gamma rays that can be detected in a scanner surrounding the point source. The position of the point source is somewhere along the Line of Response (LOR) that passes through the positions where the 511 keV gammas are detected. In standard PET, an image reconstruction algorithm is used to combine these LORs into a final image. This paper presents a new tomographic imaging technique to locate the position of a β + emitting point source without using a standard PET image reconstruction algorithm. The data were collected with a Proof-of-Concept (PoC) PET scanner which has high spatial and energy resolutions. The imaging technique presented in this paper uses events where a gamma undergoes Compton scattering. The positions and energies deposited by the Compton scattered gamma define the surface of a Compton cone (CC) which is the locus of all possible positions of the point source, allowed by the Compton kinematics. The position of the same point source is also located somewhere on the LOR. Therefore, the position of the point source is defined by the 3 gammas and is given by the intersection point of the LOR and the Compton cone inside the Field of View (FOV) of the scanner. We refer to this method as CC×LOR. This new technique can locate the point source with an uncertainty of about 1 mm, after collecting a minimum of 200 CC×LOR events.

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“…PET imaging involves the administration of radiotracers, labeled with positron-emitting isotopes, into the patient’s body. These radiotracers undergo radioactive decay and emit positrons, which then interact with surrounding electrons, resulting in the emission of two gamma rays ( 84 ). These gamma rays are detected by a circular array of detectors surrounding the patient, allowing for the reconstruction of images ( 3 ).…”

Section: Petmentioning

confidence: 99%

The novel imaging methods in diagnosis and assessment of cerebrovascular diseases: an overview

Liu,

Yao,

Zhu

et al. 2024

Front. Med.

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Cerebrovascular diseases, including ischemic strokes, hemorrhagic strokes, and vascular malformations, are major causes of morbidity and mortality worldwide. The advancements in neuroimaging techniques have revolutionized the field of cerebrovascular disease diagnosis and assessment. This comprehensive review aims to provide a detailed analysis of the novel imaging methods used in the diagnosis and assessment of cerebrovascular diseases. We discuss the applications of various imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and angiography, highlighting their strengths and limitations. Furthermore, we delve into the emerging imaging techniques, including perfusion imaging, diffusion tensor imaging (DTI), and molecular imaging, exploring their potential contributions to the field. Understanding these novel imaging methods is necessary for accurate diagnosis, effective treatment planning, and monitoring the progression of cerebrovascular diseases.

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Simultaneous quantitative imaging of two PET radiotracers via the detection of positron–electron annihilation and prompt gamma emissions

Cited by 47 publications

References 52 publications

UMC-PET: a fast and flexible Monte Carlo PET simulator

UMC-PET: a fast and flexible Monte Carlo PET simulator

Tracking a moving point source using triple gamma imaging

The novel imaging methods in diagnosis and assessment of cerebrovascular diseases: an overview

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