scholarly journals Simulation Study for Designing a Dedicated Cardiac TOF-PET System

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1311
Author(s):  
Sandra Oliver ◽  
Laura Moliner ◽  
Víctor Ilisie ◽  
J.M. Benlloch ◽  
M.J. Rodríguez-Álvarez
Keyword(s):  
Positron Emission Tomography ◽  
Image Quality ◽  
Lesion Detection ◽  
Emission Tomography ◽  
Cardiac Pet ◽  
Tomography Scanners ◽  
Optimal Geometry ◽  
Positron Emission ◽  
Image Quality Improvement ◽  
Pet System

The development of dedicated positron emission tomography scanners is an active area of research, especially aiming at the improvement of lesion detection and in support of cancer treatment and management. Recently, dedicated Positron Emission Tomography (PET) systems with different configurations for specific organs have been developed for improving detection effectiveness. Open geometries are always subject to distortion and artifacts in the reconstructed images. Therefore, the aim of this work is to determine the optimal geometry for a novel cardiac PET system that will be developed by our team, and determine the time resolution needed to achieve reasonable image quality for the chosen geometry. The proposed geometries consist of 36 modules. These modules are arranged in two sets of two plates, each one with different configurations. We performed Monte Carlo simulations with different TOF resolutions, in order to test the image quality improvement in each case. Our results show, as expected, that increasing TOF resolution reduces distortion and artifact effects. We can conclude that a TOF resolution of the order of 200 ps is needed to reduce the artifacts, to acceptable levels, generated in the simulated cardiac-PET open geometries.

scholarly journals Reduction of the fluorine-18-labeled fluorodeoxyglucose dose for clinically dedicated breast positron emission tomography

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yoko Satoh ◽  
Tetsuro Sekine ◽  
Yoshie Omiya ◽  
Hiroshi Onishi ◽  
Utaroh Motosugi
Keyword(s):  
Positron Emission Tomography ◽  
Image Quality ◽  
Standard Dose ◽  
Radioactive Decay ◽  
Lesion Detection ◽  
Phantom Study ◽  
Emission Tomography ◽  
Multiple Time ◽  
List Mode ◽  
Positron Emission

Abstract Purpose To determine the clinically acceptable level of reduction in the injected fluorine-18 (18F)-labeled fluorodeoxyglucose (18F-FDG) dose in dedicated breast positron emission tomography (dbPET). Methods A breast phantom with four spheres exhibiting various diameters (5, 7.5, 10, and 16 mm), a background 18F-FDG radioactivity of 2.28 kBq/mL, and a sphere-to-background radioactivity ratio of 8:1 was used. True dose-reduced dbPET images were obtained by data acquisition for 20 min in list mode at multiple time points over 7 h of radioactive decay. Simulated dose-reduced images were generated by reconstruction with a portion of the list mode acquisition data. True and simulated dose-reduced images were visually and quantitatively compared. On the basis of the phantom study, dbPET images for 32 breasts of 28 women with abnormal uptake were generated after simulated reduction of the injected 18F-FDG doses; these images were compared with those acquired using current clinical doses. Results There were no qualitative differences between true and simulated dose-reduced phantom images. The phantom study revealed that the minimal required dose was 12.5% for the detection of 5-mm spheres and 25% for precise semi-quantification of FDG in the spheres. The 7-min reconstruction with a 100% dose was defined as the reference for the clinical study. The image quality and lesion conspicuity were clinically acceptable for the 25% dose images. Lesion detectability on the 12.5% dose images was maintained despite image quality degradation. Conclusions In summary, 25% of the standard 18F-FDG dose for dbPET can provide a clinically acceptable image quality, while 12.5% of the standard dose results in acceptable quality in terms of lesion detection when lesions are located at a sufficient distance from the edge of the dbPET detector.

scholarly journals Deep learning-based image quality improvement of 18F-fluorodeoxyglucose positron emission tomography: a retrospective observational study

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Junichi Tsuchiya ◽  
Kota Yokoyama ◽  
Ken Yamagiwa ◽  
Ryosuke Watanabe ◽  
Koichiro Kimura ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Emission Tomography ◽  
Gaussian Filter ◽  
Fluorodeoxyglucose Positron Emission Tomography ◽  
Tumor Delineation ◽  
Standardized Uptake Values ◽  
Positron Emission ◽  
Image Quality Improvement ◽  
Fluorodeoxyglucose Positron Emission

Abstract Background Deep learning (DL)-based image quality improvement is a novel technique based on convolutional neural networks. The aim of this study was to compare the clinical value of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) images obtained with the DL method with those obtained using a Gaussian filter. Methods Fifty patients with a mean age of 64.4 (range, 19–88) years who underwent 18F-FDG PET/CT between April 2019 and May 2019 were included in the study. PET images were obtained with the DL method in addition to conventional images reconstructed with three-dimensional time of flight-ordered subset expectation maximization and filtered with a Gaussian filter as a baseline for comparison. The reconstructed images were reviewed by two nuclear medicine physicians and scored from 1 (poor) to 5 (excellent) for tumor delineation, overall image quality, and image noise. For the semi-quantitative analysis, standardized uptake values in tumors and healthy tissues were compared between images obtained using the DL method and those obtained with a Gaussian filter. Results Images acquired using the DL method scored significantly higher for tumor delineation, overall image quality, and image noise compared to baseline (P < 0.001). The Fleiss’ kappa value for overall inter-reader agreement was 0.78. The standardized uptake values in tumor obtained by DL were significantly higher than those acquired using a Gaussian filter (P < 0.001). Conclusions Deep learning method improves the quality of PET images.

Cardiac positron emission tomography (PET)

2017 ◽  
Author(s):  
Nikant Sabharwal ◽  
Parthiban Arumugam ◽  
Andrew Kelion
Keyword(s):  
Positron Emission Tomography ◽  
Single Photon ◽  
Photon Emission ◽  
Emission Tomography ◽  
Emission Computed Tomography ◽  
Cardiac Pet ◽  
Clinical Tool ◽  
Cardiac Positron Emission Tomography ◽  
Positron Emission ◽  
Recent Developments

As in single photon emission computed tomography (SPECT), positron emission tomography (PET) involves the injection of a radiopharmaceutical, the physiological properties of which determine its distribution within the patient. The labelling radionuclide then allows this distribution to be imaged. The value of cardiac PET as a routine clinical tool, particularly for perfusion imaging, was previously limited by the expense and scarcity of cameras and the short half-lives of the radionuclides with complex radiochemistry. The need for an on-site cyclotron to produce these radiopharmaceuticals made a clinical service non-viable. A number of recent developments, however, have led to renewed interest in cardiac PET. This chapter covers PET instrumentation, detail on the radiopharmaceuticals used in cardiac PET, and a number of sections on F-fluorodeoxyglucose (F-FDG) PET covering infection and inflammation imaging.

Verification of image quality and quantification in whole-body positron emission tomography with continuous bed motion

2019 ◽  
Vol 33 (4) ◽  
pp. 288-294
Author(s):  
Hideo Yamamoto ◽  
Shota Takemoto ◽  
Akira Maebatake ◽  
Shuhei Karube ◽  
Yuki Yamashiro ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Image Quality ◽  
Emission Tomography ◽  
Whole Body ◽  
Positron Emission

Relationship between the image quality and noise-equivalent count in time-of-flight positron emission tomography

2015 ◽  
Vol 30 (1) ◽  
pp. 68-74 ◽  
Author(s):  
Akira Maebatake ◽  
Go Akamatsu ◽  
Kenta Miwa ◽  
Yuji Tsutsui ◽  
Kazuhiko Himuro ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Image Quality ◽  
Time Of Flight ◽  
Emission Tomography ◽  
Positron Emission ◽  
Noise Equivalent Count
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