PURPOSE: The aim of this study is to assess a software-based method with semiautomated correction for partial volume effect (PVE) to quantify the metabolic activity of pulmonary malignancies in patients who underwent non-gated and respiratory-gated 2-deoxy-2-[(18)F]fluoro-D-glucose (FDG)-positron emission tomography (PET)/x-ray computed tomography(CT). PROCEDURES: The study included 106 lesions of 55 lung cancer patients who underwent respiratory-gated FDG-PET/CT for radiation therapy treatment planning. Volumetric PET/CT parameters were determined by using 4D PET/CT and non-gated PET/CT images. We used a semiautomated program employing an adaptive contrast-oriented thresholding algorithm for lesion delineation as well as a lesion-based partial volume effect correction algorithm. We compared respiratory-gated parameters with non-gated parameters by using pairwise comparison and interclass correlation coefficient assessment. In a multivariable regression analysis, we also examined factors, which can affect quantification accuracy, including the size of lesion and the location of tumor. RESULTS: This study showed that quantification of volumetric parameters of 4D PET/CT images using an adaptive contrast-oriented thresholding algorithm and 3D lesion-based partial volume correction is feasible. We observed slight increase in FDG uptake by using PET/CT volumetric parameters in comparison of highest respiratory-gated values with non-gated values. After correction for partial volume effect, the mean standardized uptake value (SUVmean) and total lesion glycolysis (TLG) increased substantially (p value <0.001). However, we did not observe a clinically significant difference between partial volume corrected parameters of respiratory-gated and non-gated PET/CT scans. Regression analysis showed that tumor volume was the main predictor of quantification inaccuracy caused by partial volume effect. CONCLUSIONS: Based on this study, assessment of volumetric PET/CT parameters and partial volume effect correction for accurate quantification of lung malignant lesions by using respiratory non-gated PET images are feasible and it is comparable to gated measurements. Partial volume correction increased both the respiratory-gated and non-gated values significantly and appears to be the dominant source of quantification error of lung lesions.
PURPOSE: The aim of this study is to assess a software-based method with semiautomated correction for partial volume effect (PVE) to quantify the metabolic activity of pulmonary malignancies in patients who underwent non-gated and respiratory-gated 2-deoxy-2-[(18)F]fluoro-D-glucose (FDG)-positron emission tomography (PET)/x-ray computed tomography(CT). PROCEDURES: The study included 106 lesions of 55 lung cancerpatients who underwent respiratory-gated FDG-PET/CT for radiation therapy treatment planning. Volumetric PET/CT parameters were determined by using 4D PET/CT and non-gated PET/CT images. We used a semiautomated program employing an adaptive contrast-oriented thresholding algorithm for lesion delineation as well as a lesion-based partial volume effect correction algorithm. We compared respiratory-gated parameters with non-gated parameters by using pairwise comparison and interclass correlation coefficient assessment. In a multivariable regression analysis, we also examined factors, which can affect quantification accuracy, including the size of lesion and the location of tumor. RESULTS: This study showed that quantification of volumetric parameters of 4D PET/CT images using an adaptive contrast-oriented thresholding algorithm and 3D lesion-based partial volume correction is feasible. We observed slight increase in FDG uptake by using PET/CT volumetric parameters in comparison of highest respiratory-gated values with non-gated values. After correction for partial volume effect, the mean standardized uptake value (SUVmean) and total lesion glycolysis (TLG) increased substantially (p value <0.001). However, we did not observe a clinically significant difference between partial volume corrected parameters of respiratory-gated and non-gated PET/CT scans. Regression analysis showed that tumor volume was the main predictor of quantification inaccuracy caused by partial volume effect. CONCLUSIONS: Based on this study, assessment of volumetric PET/CT parameters and partial volume effect correction for accurate quantification of lung malignant lesions by using respiratory non-gated PET images are feasible and it is comparable to gated measurements. Partial volume correction increased both the respiratory-gated and non-gated values significantly and appears to be the dominant source of quantification error of lung lesions.
Authors: S A Nehmeh; Y E Erdi; T Pan; A Pevsner; K E Rosenzweig; E Yorke; G S Mageras; H Schoder; Phil Vernon; O Squire; H Mostafavi; S M Larson; J L Humm Journal: Med Phys Date: 2004-12 Impact factor: 4.071
Authors: Andrea Lupi; Marta Zaroccolo; Matteo Salgarello; Veronica Malfatti; Pierluigi Zanco Journal: Ann Nucl Med Date: 2009-02-19 Impact factor: 2.668
Authors: Ali Salavati; Fenghai Duan; Bradley S Snyder; Bo Wei; Sina Houshmand; Benjapa Khiewvan; Adam Opanowski; Charles B Simone; Barry A Siegel; Mitchell Machtay; Abass Alavi Journal: Eur J Nucl Med Mol Imaging Date: 2017-07-08 Impact factor: 9.236
Authors: Daniele Muser; Pasquale Santangeli; Simon A Castro; Jackson J Liang; Andres Enriquez; Thomas J Werner; Gaetano Nucifora; Silvia Magnani; Tatsuya Hayashi; Erica S Zado; Fermin C Garcia; David J Callans; Sanjay Dixit; Benoit Desjardins; Francis E Marchlinski; Abass Alavi Journal: Eur J Nucl Med Mol Imaging Date: 2018-04-02 Impact factor: 9.236