Jørgen Frøkiær

(18)F-FDG-PET/CT for very early response evaluation predicts CT response in Erlotinib treated NSCLC patients - A comparison of assessment methods

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(18)F-FDG-PET/CT for very early response evaluation predicts CT response in Erlotinib treated NSCLC patients - A comparison of assessment methods. / Fledelius, Joan; Winther-Larsen, Anne; Khalil, Azza Ahmed; Bylov, Catharina Mølgaard; Hjorthaug, Karin; Bertelsen, Aksel; Frøkiær, Jørgen; Meldgaard, Peter.

In: Journal of Nuclear Medicine, Vol. 58, No. 12, 01.12.2017, p. 1931-1937.

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@article{c1d3d130eeae4083b41e8420b9f1381f,
title = "(18)F-FDG-PET/CT for very early response evaluation predicts CT response in Erlotinib treated NSCLC patients - A comparison of assessment methods",
abstract = "The purpose of this study was to determine which method for early response evaluation with (18)F-fluoro-D-glucose positron emission tomography combined with whole body computed tomography ((18)F-FDG-PET/CT) performed most optimal for prediction of response on a later CT-scan in erlotinib treated non-small cell lung cancer (NSCLC) patients. Methods:(18)F-FDG-PET/CT scans were performed prior to and after 7-10 days of erlotinib treatment in 50 NSCLC patients. The scans were evaluated using a qualitative approach and various semi-quantitative methods including percentage change in Standardized Uptake values, lean body mass corrected (SUL) SULpeak, SULmax and Total Lesion Glycolysis (TLG). The PET parameters and their corresponding response categories were compared to the percentage change in the sum of the longest diameter (SLD) in target lesions and the resulting response categories from a CT scan performed after 9-11 weeks of erlotinib treatment using Receiver Operating Characteristics (ROC) analysis, linear regression and quadratic weighted kappa. Results: TLG delineation according to the PET evaluation response criteria in solid tumors (PERCIST) showed the strongest correlation to SLD (R = 0.564, p<0.001), compared to SULmax (R=0.298, P = 0.039) and SULpeak (R=0.402, P = 0.005). For predicting progression on CT, ROC analysis show area under the curves (AUCs) between 0.79 and 0.92 with the highest AUC of 0.92 (95% confidence interval (CI): 0.84-1.00) found for TLG (PERCIST). Furthermore, using a cut-off of 25% change in TLG (PERCIST) for both partial metabolic response (PMR) and progressive metabolic disease (PMD), which is the best predictor of the CT response categories showed a kappa value of 0.53 (95%CI: 0.31-0.75). This method identifies 41% of the later PDs on CT, with no false positives. Visual evaluation correctly identified 50% with a kappa value of 0.47 (95%CI: 0.24-0.70). Conclusion: TLG (PERCIST) was the optimal predictor of response on later CT scans outperforming both SULpeak and SULmax. Using TLG (PERCIST) with a 25% cut-off after 1-2 weeks of treatment allows us to safely identify 41% of the patients who will not benefit from erlotinib and stop the treatment at this time.",
keywords = "FDG PET/CT, Percist 1.0, Early response evaluation, Lung cancer",
author = "Joan Fledelius and Anne Winther-Larsen and Khalil, {Azza Ahmed} and Bylov, {Catharina M{\o}lgaard} and Karin Hjorthaug and Aksel Bertelsen and J{\o}rgen Fr{\o}ki{\ae}r and Peter Meldgaard",
note = "Copyright {\textcopyright} 2017 by the Society of Nuclear Medicine and Molecular Imaging, Inc.",
year = "2017",
month = dec,
day = "1",
doi = "10.2967/jnumed.117.193003",
language = "English",
volume = "58",
pages = "1931--1937",
journal = "Journal of Nuclear Medicine",
issn = "0161-5505",
publisher = "SOC NUCLEAR MEDICINE INC",
number = "12",

}

RIS

TY - JOUR

T1 - (18)F-FDG-PET/CT for very early response evaluation predicts CT response in Erlotinib treated NSCLC patients - A comparison of assessment methods

AU - Fledelius, Joan

AU - Winther-Larsen, Anne

AU - Khalil, Azza Ahmed

AU - Bylov, Catharina Mølgaard

AU - Hjorthaug, Karin

AU - Bertelsen, Aksel

AU - Frøkiær, Jørgen

AU - Meldgaard, Peter

N1 - Copyright © 2017 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

PY - 2017/12/1

Y1 - 2017/12/1

N2 - The purpose of this study was to determine which method for early response evaluation with (18)F-fluoro-D-glucose positron emission tomography combined with whole body computed tomography ((18)F-FDG-PET/CT) performed most optimal for prediction of response on a later CT-scan in erlotinib treated non-small cell lung cancer (NSCLC) patients. Methods:(18)F-FDG-PET/CT scans were performed prior to and after 7-10 days of erlotinib treatment in 50 NSCLC patients. The scans were evaluated using a qualitative approach and various semi-quantitative methods including percentage change in Standardized Uptake values, lean body mass corrected (SUL) SULpeak, SULmax and Total Lesion Glycolysis (TLG). The PET parameters and their corresponding response categories were compared to the percentage change in the sum of the longest diameter (SLD) in target lesions and the resulting response categories from a CT scan performed after 9-11 weeks of erlotinib treatment using Receiver Operating Characteristics (ROC) analysis, linear regression and quadratic weighted kappa. Results: TLG delineation according to the PET evaluation response criteria in solid tumors (PERCIST) showed the strongest correlation to SLD (R = 0.564, p<0.001), compared to SULmax (R=0.298, P = 0.039) and SULpeak (R=0.402, P = 0.005). For predicting progression on CT, ROC analysis show area under the curves (AUCs) between 0.79 and 0.92 with the highest AUC of 0.92 (95% confidence interval (CI): 0.84-1.00) found for TLG (PERCIST). Furthermore, using a cut-off of 25% change in TLG (PERCIST) for both partial metabolic response (PMR) and progressive metabolic disease (PMD), which is the best predictor of the CT response categories showed a kappa value of 0.53 (95%CI: 0.31-0.75). This method identifies 41% of the later PDs on CT, with no false positives. Visual evaluation correctly identified 50% with a kappa value of 0.47 (95%CI: 0.24-0.70). Conclusion: TLG (PERCIST) was the optimal predictor of response on later CT scans outperforming both SULpeak and SULmax. Using TLG (PERCIST) with a 25% cut-off after 1-2 weeks of treatment allows us to safely identify 41% of the patients who will not benefit from erlotinib and stop the treatment at this time.

AB - The purpose of this study was to determine which method for early response evaluation with (18)F-fluoro-D-glucose positron emission tomography combined with whole body computed tomography ((18)F-FDG-PET/CT) performed most optimal for prediction of response on a later CT-scan in erlotinib treated non-small cell lung cancer (NSCLC) patients. Methods:(18)F-FDG-PET/CT scans were performed prior to and after 7-10 days of erlotinib treatment in 50 NSCLC patients. The scans were evaluated using a qualitative approach and various semi-quantitative methods including percentage change in Standardized Uptake values, lean body mass corrected (SUL) SULpeak, SULmax and Total Lesion Glycolysis (TLG). The PET parameters and their corresponding response categories were compared to the percentage change in the sum of the longest diameter (SLD) in target lesions and the resulting response categories from a CT scan performed after 9-11 weeks of erlotinib treatment using Receiver Operating Characteristics (ROC) analysis, linear regression and quadratic weighted kappa. Results: TLG delineation according to the PET evaluation response criteria in solid tumors (PERCIST) showed the strongest correlation to SLD (R = 0.564, p<0.001), compared to SULmax (R=0.298, P = 0.039) and SULpeak (R=0.402, P = 0.005). For predicting progression on CT, ROC analysis show area under the curves (AUCs) between 0.79 and 0.92 with the highest AUC of 0.92 (95% confidence interval (CI): 0.84-1.00) found for TLG (PERCIST). Furthermore, using a cut-off of 25% change in TLG (PERCIST) for both partial metabolic response (PMR) and progressive metabolic disease (PMD), which is the best predictor of the CT response categories showed a kappa value of 0.53 (95%CI: 0.31-0.75). This method identifies 41% of the later PDs on CT, with no false positives. Visual evaluation correctly identified 50% with a kappa value of 0.47 (95%CI: 0.24-0.70). Conclusion: TLG (PERCIST) was the optimal predictor of response on later CT scans outperforming both SULpeak and SULmax. Using TLG (PERCIST) with a 25% cut-off after 1-2 weeks of treatment allows us to safely identify 41% of the patients who will not benefit from erlotinib and stop the treatment at this time.

KW - FDG PET/CT

KW - Percist 1.0

KW - Early response evaluation

KW - Lung cancer

U2 - 10.2967/jnumed.117.193003

DO - 10.2967/jnumed.117.193003

M3 - Journal article

C2 - 28490472

VL - 58

SP - 1931

EP - 1937

JO - Journal of Nuclear Medicine

JF - Journal of Nuclear Medicine

SN - 0161-5505

IS - 12

ER -