PET Counting Response Variability Depending on Tumor Location, Activity, and Patient Obesity: A Feasibility Study of Solitary Pulmonary Nodule Using Monte Carlo
We aim to investigate the counting response variations of positron emission tomography (PET) scanners with different detector configurations in the presence of solitary pulmonary nodule (SPN). Using experimentally validated Monte Carlo simulations, the counting performance of four different scanner...
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Published in | IEEE transactions on medical imaging Vol. 38; no. 7; pp. 1763 - 1774 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.07.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | We aim to investigate the counting response variations of positron emission tomography (PET) scanners with different detector configurations in the presence of solitary pulmonary nodule (SPN). Using experimentally validated Monte Carlo simulations, the counting performance of four different scanner models with varying tumor activity, location, and patient obesity is represented using a noise equivalent count rate (NECR). NECR is a well-established quantitative metric which has positive correlation with clinically perceived image quality. The combined effect of tumor displacement and increased activity shows a linear ascending trend for NECR with slope ranges of (12.5-18.2)*10 −3 (kBq/cm 3 ) −1 for three-ring (3R) scanners and (15.3-21.5)*10 −3 (kBq/cm 3 ) −1 for four-ring (4R). The trend for the combined effect of tumor displacement and patient obesity is exponential decay with 3R configurations weakly dependent on the patient obesity if the tumor is located at the center of the field of view with exponent's range of (6.6-33.8)*10 −2 cm −1 . The dependence is stronger for 4R scanners (9.6-38.5)*10 −2 cm −1 . The analysis indicates that quantitative PET data from the same SPN patient possibly examined in different time points (e.g., during staging or for the evaluation of treatment response) are affected by the different detector configurations and need to be normalized with patient weight, activity, and tumor location to reduce unwanted bias of the diagnosis. This paper provides also with a proof of concept for the ability of properly tuned simulations to provide additional insights into the counting response variability especially in tumor types where often borderline decisions have to be made regarding their characterization. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0278-0062 1558-254X |
DOI: | 10.1109/TMI.2019.2891578 |