Tumor Lesion Glycolysis and Tumor Lesion Proliferation for Response Prediction and Prognostic Differentiation in Patients With Advanced Non–Small Cell Lung Cancer Treated With Erlotinib

Kahraman, Deniz; Holstein, Arne; Scheffler, Matthias; Zander, Thomas; Nogová, Lucia; Lammertsma, Adriaan A.; Boellaard, Ronald; Neumaier, Bernd; Dietlein, Markus; Wolf, Jürgen; Kobe, Carsten

doi:10.1097/rlu.0b013e3182639747

Cited by 44 publications

(37 citation statements)

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“…Although patients carrying mutations of the EGFR gene generally respond better to tyrosine kinase inhibitors (TKIs) [1], erlotinib may improve survival even in subjects with EGFR wild-type tumors [2]. Several studies have shown that FDG-PET is a useful imaging modality for predicting response to erlotinib in patients with non-small cell lung cancer (NSCLC) [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. However, most of these studies used only the primary tumor as the target lesion for sequential imaging [3][4][5][6][7][8][9][10][11][12], and treatment response was largely assessed using the European Organization for Research and Treatment of Cancer (EORTC) criteria [3][4][5][6][7][8][9]20].…”

Section: Introductionmentioning

confidence: 99%

TLG-S criteria are superior to both EORTC and PERCIST for predicting outcomes in patients with metastatic lung adenocarcinoma treated with erlotinib

Fang

Chung

et al. 2016

Eur J Nucl Med Mol Imaging

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Section: Introductionmentioning

confidence: 99%

TLG-S criteria are superior to both EORTC and PERCIST for predicting outcomes in patients with metastatic lung adenocarcinoma treated with erlotinib

Fang

Chung

et al. 2016

Eur J Nucl Med Mol Imaging

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“…However, the correlation with proliferation is partially shown in response to treatment. The association with progression-free survival and 18 F-FLT uptake was shown in patients treated with erlotinib (73). In 30 patients with stage IV non-small cell lung cancer imaged before, 1 wk, and 6 wk after the start of erlotinib treatment, 18 F-FLT and 18 F-FDG PET imaging was done.…”

Section: Lung Cancermentioning

confidence: 99%

PET Imaging of Proliferation with Pyrimidines

Tehrani

Shields

2013

J Nucl Med

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“…For non-small cell lung cancer (NSCLC), 18 F-FDG PET/CT image quantification has been shown to provide prognostic information. PET image-derived features, including metabolically active tumor volume (MATV), mean standardized uptake value (SUV mean ), and total lesion glycolysis (TLG, defined as MATV · SUV mean ), have been shown to provide an accurate assessment of tumor burden with potentially higher prognostic value than standard maximum SUV (SUV max ), for both surgical and nonsurgical patients (5)(6)(7)(8)(9).…”

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confidence: 99%

Visual Versus Quantitative Assessment of Intratumor ¹⁸F-FDG PET Uptake Heterogeneity: Prognostic Value in Non–Small Cell Lung Cancer

et al. 2014

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The goal of this study was to compare visual assessment of intratumor 18 F-FDG PET uptake distribution with a textural-features (TF) automated quantification and to establish their respective prognostic value in non-small cell lung cancer (NSCLC). Methods: The study retrospectively included 102 consecutive patients. Only primary tumors were considered. Intratumor heterogeneity was visually scored (3-level scale [H visu ]) by 2 nuclear medicine physicians. Tumor volumes were automatically delineated, and heterogeneity was quantified with TF. Mean and maximum standardized uptake value were also included. Visual interobserver agreement and correlations with quantitative assessment were evaluated using the κ test and Spearman rank (ρ) coefficient, respectively. Association with overall survival and recurrencefree survival was investigated using the Kaplan-Meier method and Cox regression models. Results: Moderate correlations (0.4 , ρ , 0.6) between TF parameters and H visu were observed. Interobserver agreement for H visu was moderate (κ 5 0.64, discrepancies in 27% of the cases). High standardized uptake value, large metabolic volumes, and high heterogeneity according to TF were associated with poorer overall survival and recurrence-free survival and remained an independent prognostic factor of overall survival with respect to clinical variables. Conclusion: Quantification of 18 F-FDG uptake heterogeneity in NSCLC through TF was correlated with visual assessment by experts. However, TF also constitutes an objective heterogeneity quantification, with reduced interobserver variability, and independent prognostic value potentially useful for patient stratification and management. PET/ CT imaging with 18 F-FDG is today a well-established tool for diagnostic oncology applications (1). Its exploitation for tumor delineation in the planning of radiotherapy treatment (2) or monitoring of response to therapy (3,4) is increasing. For non-small cell lung cancer (NSCLC), 18 F-FDG PET/CT image quantification has been shown to provide prognostic information. PET image-derived features, including metabolically active tumor volume (MATV), mean standardized uptake value (SUV mean ), and total lesion glycolysis (TLG, defined as MATV · SUV mean ), have been shown to provide an accurate assessment of tumor burden with potentially higher prognostic value than standard maximum SUV (SUV max ), for both surgical and nonsurgical patients (5-9).Intratumor 18 F-FDG uptake heterogeneity has been associated with treatment failure (10), and its quantification has recently generated interest (11-14), including in lung cancer (15). Several methodologies have been proposed to assess intratumor heterogeneity, including visual evaluation (16), SUV coefficient of variation (SUV COV ) (17), area under the curve of the cumulative histogram (CH AUC ) (18), and textural-features (TF) analysis (17,19).TF analysis can generate many features quantifying heterogeneity within a delineated MATV. Recent studies have identified a few of these features that are ...

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Tumor Lesion Glycolysis and Tumor Lesion Proliferation for Response Prediction and Prognostic Differentiation in Patients With Advanced Non–Small Cell Lung Cancer Treated With Erlotinib

Cited by 44 publications

References 0 publications

TLG-S criteria are superior to both EORTC and PERCIST for predicting outcomes in patients with metastatic lung adenocarcinoma treated with erlotinib

TLG-S criteria are superior to both EORTC and PERCIST for predicting outcomes in patients with metastatic lung adenocarcinoma treated with erlotinib

PET Imaging of Proliferation with Pyrimidines

Visual Versus Quantitative Assessment of Intratumor ¹⁸F-FDG PET Uptake Heterogeneity: Prognostic Value in Non–Small Cell Lung Cancer

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Tumor Lesion Glycolysis and Tumor Lesion Proliferation for Response Prediction and Prognostic Differentiation in Patients With Advanced Non–Small Cell Lung Cancer Treated With Erlotinib

Cited by 44 publications

References 0 publications

TLG-S criteria are superior to both EORTC and PERCIST for predicting outcomes in patients with metastatic lung adenocarcinoma treated with erlotinib

TLG-S criteria are superior to both EORTC and PERCIST for predicting outcomes in patients with metastatic lung adenocarcinoma treated with erlotinib

PET Imaging of Proliferation with Pyrimidines

Visual Versus Quantitative Assessment of Intratumor 18F-FDG PET Uptake Heterogeneity: Prognostic Value in Non–Small Cell Lung Cancer

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Visual Versus Quantitative Assessment of Intratumor ¹⁸F-FDG PET Uptake Heterogeneity: Prognostic Value in Non–Small Cell Lung Cancer