Respiratory Motion Correction Using A Novel Positron Emission Particle Tracking Technique: A Framework Towards Individual Lesion-Based Motion Correction

Tumpa, Tasmia Rahman; Acuff, Shelley; Gregor, Jens; Lee, Sanghyeb; Hu, Dongming; Osborne, Dustin

doi:10.1109/embc.2018.8513486

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…( 4) Data-driven gating techniques -instead of using hardware-driven motion correction strategies (as described in previous sections), new methods are being explored using data-driven software analysis. Some examples include (a) motion characterization directly from a patient's gated scan using the signal to create a single optimal bin, and leading to conformal adaptive imaging [101], and (b) motion information extraction from the reconstructed images [102]. The real-time data-driven motion correction, as opposed to post-processing methods, represents an important innovation in the speed of processing data for clinical practice [103].…”

Section: Respiratory Motion Correctionmentioning

confidence: 99%

Joint EANM/SNMMI/ESTRO practice recommendations for the use of 2-[18F]FDG PET/CT external beam radiation treatment planning in lung cancer V1.0

Vaz

Adam²,

Delgado-Bolton

et al. 2022

Eur J Nucl Med Mol Imaging

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Purpose 2-[18F]FDG PET/CT is of utmost importance for radiation treatment (RT) planning and response monitoring in lung cancer patients, in both non-small and small cell lung cancer (NSCLC and SCLC). This topic has been addressed in guidelines composed by experts within the field of radiation oncology. However, up to present, there is no procedural guideline on this subject, with involvement of the nuclear medicine societies. Methods A literature review was performed, followed by a discussion between a multidisciplinary team of experts in the different fields involved in the RT planning of lung cancer, in order to guide clinical management. The project was led by experts of the two nuclear medicine societies (EANM and SNMMI) and radiation oncology (ESTRO). Results and conclusion This guideline results from a joint and dynamic collaboration between the relevant disciplines for this topic. It provides a worldwide, state of the art, and multidisciplinary guide to 2-[18F]FDG PET/CT RT planning in NSCLC and SCLC. These practical recommendations describe applicable updates for existing clinical practices, highlight potential flaws, and provide solutions to overcome these as well. Finally, the recent developments considered for future application are also reviewed.

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Section: Respiratory Motion Correctionmentioning

confidence: 99%

Joint EANM/SNMMI/ESTRO practice recommendations for the use of 2-[18F]FDG PET/CT external beam radiation treatment planning in lung cancer V1.0

Vaz

Adam²,

Delgado-Bolton

et al. 2022

Eur J Nucl Med Mol Imaging

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“…When the particles are in the field of view, the positron-emitting traces are tracked, and the trajectories are reconstructed using the gamma rays detected by the gamma cameras and corresponding lines of response (LORs). PEPT particle tracking methods started with the Birmingham method [ 14 , 15 ], and have been expanded to include the line-density method [ 16 ], multiple location-allocation algorithm (MLAA) [ 17 , 18 ], K-Medoids [ 19 ], clustering methods [ 20 ], the feature point identification (FPI) method [ 21 ], Odo triangulation method [ 22 ], Voronoi-based multiple particle tracking (VMPT) [ 23 ], the time-of-flight PEPT (TOF-PEPT) algorithm to do motion correction in medical imaging [ 24 , 25 ] and recently-developed method of PEPT machine learning (PEPT-ML) which tracks multiple particles and does not require frame tracking [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

Using Gaussian process for velocity reconstruction after coronary stenosis applicable in positron emission particle tracking: An in-silico study

Keramati,

de Vecchi,

Rajani

et al. 2023

PLoS ONE

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Accurate velocity reconstruction is essential for assessing coronary artery disease. We propose a Gaussian process method to reconstruct the velocity profile using the sparse data of the positron emission particle tracking (PEPT) in a biological environment, which allows the measurement of tracer particle velocity to infer fluid velocity fields. We investigated the influence of tracer particle quantity and detection time interval on flow reconstruction accuracy. Three models were used to represent different levels of stenosis and anatomical complexity: a narrowed straight tube, an idealized coronary bifurcation with stenosis, and patient-specific coronary arteries with a stenotic left circumflex artery. Computational fluid dynamics (CFD), particle tracking, and the Gaussian process of kriging were employed to simulate and reconstruct the pulsatile flow field. The study examined the error and uncertainty in velocity profile reconstruction after stenosis by comparing particle-derived flow velocity with the CFD solution. Using 600 particles (15 batches of 40 particles) released in the main coronary artery, the time-averaged error in velocity reconstruction ranged from 13.4% (no occlusion) to 161% (70% occlusion) in patient-specific anatomy. The error in maximum cross-sectional velocity at peak flow was consistently below 10% in all cases. PEPT and kriging tended to overestimate area-averaged velocity in higher occlusion cases but accurately predicted maximum cross-sectional velocity, particularly at peak flow. Kriging was shown to be useful to estimate the maximum velocity after the stenosis in the absence of negative near-wall velocity.

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“…PEPT has been mostly used in industrial applications such as flow patterns 30,31 and velocity measurements. 32 Other than our patent 33 and preliminary early work, [34][35][36] a variant of the PEPT algorithm was presented under the moniker positron emission tracking (PeTrack) for use in radiotherapy as well as cardiac PET studies using external markers. 37,38 PeTrack requires an initial estimate of the marker positions and has several user-defined threshold parameters.…”

Section: Introductionmentioning

confidence: 99%

A data‐driven respiratory motion estimation approach for PET based on time‐of‐flight weighted positron emission particle tracking

et al. 2020

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Purpose Respiratory motion of patients during positron emission tomography (PET)/computed tomography (CT) imaging affects both image quality and quantitative accuracy. Hardware‐based motion estimation, which is the current clinical standard, requires initial setup, maintenance, and calibration of the equipment, and can be associated with patient discomfort. Data‐driven techniques are an active area of research with limited exploration into lesion‐specific motion estimation. This paper introduces a time‐of‐flight (TOF)‐weighted positron emission particle tracking (PEPT) algorithm that facilitates lesion‐specific respiratory motion estimation from raw listmode PET data. Methods The TOF‐PEPT algorithm was implemented and investigated under different scenarios: (a) a phantom study with a point source and an Anzai band for respiratory motion tracking; (b) a phantom study with a point source only, no Anzai band; (c) two clinical studies with point sources and the Anzai band; (d) two clinical studies with point sources only, no Anzai band; and (e) two clinical studies using lesions/internal regions instead of point sources and no Anzai band. For studies with radioactive point sources, they were placed on patients during PET/CT imaging. The motion tracking was performed using a preselected region of interest (ROI), manually drawn around point sources or lesions on reconstructed images. The extracted motion signals were compared with the Anzai band when applicable. For the purposes of additional comparison, a center‐of‐mass (COM) algorithm was implemented both with and without the use of TOF information. Using the motion estimate from each method, amplitude‐based gating was applied, and gated images were reconstructed. Results The TOF‐PEPT algorithm is shown to successfully determine the respiratory motion for both phantom and clinical studies. The derived motion signals correlated well with the Anzai band; correlation coefficients of 0.99 and 0.94‐0.97 were obtained for the phantom study and the clinical studies, respectively. TOF‐PEPT was found to be 13–38% better correlated with the Anzai results than the COM methods. Maximum Standardized Uptake Values (SUVs) were used to quantitatively compare the reconstructed‐gated images. In comparison with the ungated image, a 14–39% increase in the max SUV across several lesion areas and an 8.7% increase in the max SUV on the tracked lesion area were observed in the gated images based on TOF‐PEPT. The distinct presence of lesions with reduced blurring effect and generally sharper images were readily apparent in all clinical studies. In addition, max SUVs were found to be 4–10% higher in the TOF‐PEPT‐based gated images than in those based on Anzai and COM methods. Conclusion A PEPT‐ based algorithm has been presented for determining movement due to respiratory motion during PET/CT imaging. Gating based on the motion estimate is shown to quantifiably improve the image quality in both a controlled point source phantom study and in clinical data patient studies. The algorithm has the...

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Respiratory Motion Correction Using A Novel Positron Emission Particle Tracking Technique: A Framework Towards Individual Lesion-Based Motion Correction

Cited by 4 publications

References 14 publications

Joint EANM/SNMMI/ESTRO practice recommendations for the use of 2-[18F]FDG PET/CT external beam radiation treatment planning in lung cancer V1.0

Joint EANM/SNMMI/ESTRO practice recommendations for the use of 2-[18F]FDG PET/CT external beam radiation treatment planning in lung cancer V1.0

Using Gaussian process for velocity reconstruction after coronary stenosis applicable in positron emission particle tracking: An in-silico study

A data‐driven respiratory motion estimation approach for PET based on time‐of‐flight weighted positron emission particle tracking

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