Technical aspects of real time positron emission tracking for gated radiotherapy

Chamberland, Marc; McEwen, M; Xu, Tingfa

doi:10.1118/1.4939664

Cited by 3 publications

(6 citation statements)

References 83 publications

(84 reference statements)

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“…Of course, in the course of implementation of the above radiotherapy techniques, if modern auxiliary equipment can be incorporated with them, they can be better implemented in patients. The modern auxiliary equipment includes respiratory gate control [16, 17], CBCT image guidance technology [18–20], and so on. In future clinical studies, we hope to see more applications of these advanced radiotherapy techniques and radiotherapy auxiliary equipment.…”

Section: Discussionmentioning

confidence: 99%

The Dosimetric Comparisons of CRT, IMRT, ARC, CRT+IMRT, and CRT+ARC of Postoperative Radiotherapy in IIIA-N2 Stage Non-Small-Cell Lung Cancer Patients

Zhang

Han

et al. 2019

BioMed Research International

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Currently, studies about PORT in stage IIIA-N2 NSCLC patients in recent years have mostly adopted the conformal radiation therapy (CRT) technique, while other modern techniques such as intensity modulated radiation therapy (IMRT), volumetric modulated arc therapy (VMAT, hereinafter referred to as ARC), helical tomotherapy (HT), and so forth are also developing quickly. In this paper, we intended to compare the dosimetric characteristics of CRT, IMRT, ARC, CRT+IMRT, and CRT+ARC of PORT in stage IIIA-N2 NSCLC patients. Ten patients with stage IIIA-N2 completely resected NSCLC, whom were treated by PORT in the radiotherapy department of our hospital from January 1, 2017, to January 1, 2018, were randomly selected in this study. For each patient, the CRT plan, IMRT plan, ARC plan, CRT+IMRT plan, and CRT+ARC plan were designed separately on the same set of CT images. The isodose distribution and dose-volume histogram (DVH) of the five plans were compared to determine the dosimetric parameters of the targets, OAR (organs at risk), and the normal tissue (defined as body subtracted to PTV (planning target volume), B-P). No plan had absolute dosimetry advantages than any other plans. In clinical practice, the plans could be chosen according to their dosimetry characteristics.

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Section: Discussionmentioning

confidence: 99%

The Dosimetric Comparisons of CRT, IMRT, ARC, CRT+IMRT, and CRT+ARC of Postoperative Radiotherapy in IIIA-N2 Stage Non-Small-Cell Lung Cancer Patients

Zhang

Han

et al. 2019

BioMed Research International

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“…In this work, the PeTrack algorithm [40][41][42] was used as the basis for tracking a positron-emitting marker during PET imaging. The PET scanner records coincidence events from the fiducial marker during imaging.…”

Section: A Tracking Algorithmmentioning

confidence: 99%

“…The location of the markers, which are the only positron sources in the system, can be determined with submillimeter precision using an expectation-maximization algorithm with only tens of coincident events. [40][41][42] However, it is impossible to use PeTrack during PET imaging as the events from the low activity markers are drowned out by the millions of events from the physiological tracer. To overcome this issue, we developed an adaptive region of interest (ADROI) filtering method that can efficiently filter out most of the physiological background and enable PeTrack to extract three-dimensional (3D) motion information directly from the raw list-mode data, with no need for image reconstruction or binning the data into sinograms.…”

Section: Introductionmentioning

confidence: 99%

“…Coincident events from the markers are collected with two pairs of opposing detector modules instead of a conventional PET scanner with a full ring of detectors. The location of the markers, which are the only positron sources in the system, can be determined with submillimeter precision using an expectation‐maximization algorithm with only tens of coincident events 40–42 . However, it is impossible to use PeTrack during PET imaging as the events from the low activity markers are drowned out by the millions of events from the physiological tracer.…”

Section: Introductionmentioning

confidence: 99%

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Motion tracking of low‐activity fiducial markers using adaptive region of interest with list‐mode positron emission tomography

Chamberland

deKemp

Xu³

2020

Medical Physics

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Purpose: Motion compensated positron emission tomography (PET) imaging requires detecting and monitoring of patient body motion. We developed a semiautomatic list-mode method to track the three-dimensional (3D) motion of fiducial positron-emitting markers during PET imaging. Methods: A previously developed motion tracking method using positron-emitting markers (PeTrack) was enhanced to work with PET imaging. A novel combination of filtering methods was developed to reject physiological tracer background, which would drown out the events from the marker if unfiltered. The most critical filter rejects events whose line-of-response (LOR) is outside an adaptive region of interest (ADROI). The size of ROI was optimized by exploiting the distinct differences between the distributions of events from background and marker. The ADROI PeTrack method was evaluated with Monte Carlo and phantom studies. A 92.5-kBq 22 Na marker moving sinusoidally in 3D was simulated with Monte Carlo methods. The simulated events were combined with list-mode data from cardiac PET imaging patients to evaluate the performance of the tracking. In phantom studies, three 22 Na markers were placed on a dynamic torso phantom with an initial activity of 680 MBq of 82 Rb in its cardiac insert. The motion of the markers was tracked while the phantom simulated various types of patient motion. Motion correction on an event-by-event basis of the list-mode data was then applied and images were reconstructed. Results: Simulation results show that the background rejection methods can significantly suppress the tracer background and increase the fraction of marker events by a factor of up to 2500. A 92.5-kBq marker can be tracked in 3D at a frequency of 2.0 Hz with an accuracy of 0.8 mm and a precision of 0.3 mm. The phantom study experimentally confirms that the algorithm can track various types of motion. The relative accuracy of the experimental tracking is 0.26 AE 0.14 mm. Motion-corrected images from the phantom study show reduced blurring. Conclusions: An algorithm and background rejection methods were developed that can track the 3D motion of low-activity positron-emitting markers during PET imaging. The motion information may be used for motion-compensated PET imaging.

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“…PET has the advantage of providing tumor functional, biological, and molecular information for diagnosis, planning, therapy monitoring and evaluation, but its relatively long acquisition and image reconstruction time have prevented conventional PET imaging from being used for RMTT (Hugo andRosu 2012, Yang et al 2014). Using an implanted marker on the tumor can achieve real-time tumor tracking by PET (Chamberland et al 2016), but this is an invasive and clinically challenging method. Another approach is to completely avoid tracking by directly irradiating the beam along a PET-detected coincidence line-of-response (LOR) in real time (Fan et al 2012, Oderinde et al 2021.…”

Section: Introductionmentioning

confidence: 99%

Real-time marker-less tumor tracking with TOF PET: in silico feasibility study

Cheng¹,

Yang²,

Zhong³

et al. 2022

Phys. Med. Biol.

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Purpose: Although Positron Emission Tomography (PET) can provide a functional image of static tumors for RT guidance, it’s conventionally very challenging for PET to track a moving tumor in real-time with a multiple frame/s sampling rate. In this study, we developed a novel method to enable PET based 3-dimention (3D) real-time marker-less tumor tracking (RMTT) and demonstrated its feasibility with a simulation study. Methods: For each line-of-response (LOR) acquired, its positron-electron annihilation position is calculated based on the time difference between the two gamma interactions detected by the TOF PET detectors. The accumulation of these annihilation positions from data acquired within a single sampling frame forms a coarsely measured 3D distribution of positron-emitter radiotracer uptakes of the lung tumor and other organs and tissues (background). With clinically relevant tumor size and sufficient differential radiotracer uptake concentrations between the tumor and background, the high-uptake tumor can be differentiated from the surrounding low-uptake background in the measured distribution of radiotracer uptakes. With a volume-of-interest (VOI) that closely encloses the tumor, the count-weighted centroid of the annihilation positions within the VOI can be calculated as the tumor position. All these data processes can be conducted online. The feasibility of the new method was investigated with a simulated cardiac-torso digital phantom and stationary dual-panel TOF PET detectors to track a 28 mm diameter lung tumor with a 4:1 tumor-to-background 18FDG activity concentration ratio. Results: The initial study shows TOF PET based RMTT can achieve <2.0 mm tumor tracking accuracy with 5 frame/s sampling rate under the simulated conditions. In comparison, using reconstructed PET images to track a similar size tumor would require >30 s acquisition time to achieve the same tracking accuracy. Conclusion: With the demonstrated feasibility, the new method may enable TOF PET based RMTT for practical RT applications.

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Technical aspects of real time positron emission tracking for gated radiotherapy

Cited by 3 publications

References 83 publications

The Dosimetric Comparisons of CRT, IMRT, ARC, CRT+IMRT, and CRT+ARC of Postoperative Radiotherapy in IIIA-N2 Stage Non-Small-Cell Lung Cancer Patients

The Dosimetric Comparisons of CRT, IMRT, ARC, CRT+IMRT, and CRT+ARC of Postoperative Radiotherapy in IIIA-N2 Stage Non-Small-Cell Lung Cancer Patients

Motion tracking of low‐activity fiducial markers using adaptive region of interest with list‐mode positron emission tomography

Real-time marker-less tumor tracking with TOF PET: in silico feasibility study

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