Kun-Han Lue1, Sung-Chao Chu2,3, Ling-Yi Wang4,5, Yen-Chang Chen2,6, Ming-Hsun Li6, Bee-Song Chang7, Sheng-Chieh Chan2,8, Yu-Hung Chen9,10, Chih-Bin Lin2,11, Shu-Hsin Liu1,8. 1. Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, Hualien, Taiwan. 2. School of Medicine, College of Medicine, Tzu Chi University, Hualien, Taiwan. 3. Department of Hematology and Oncology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan. 4. Epidemiology and Biostatistics Consulting Center, Department of Medical Research, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan. 5. Department of Pharmacy, School of Medicine, Tzu Chi University, Hualien, Taiwan. 6. Department of Anatomical Pathology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan. 7. Department of Cardiothoracic Surgery, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan. 8. Department of Nuclear Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan. 9. School of Medicine, College of Medicine, Tzu Chi University, Hualien, Taiwan. jedimasterchen@hotmail.com. 10. Department of Nuclear Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan. jedimasterchen@hotmail.com. 11. Department of Internal Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan.
Abstract
OBJECTIVE: The diagnostic performance of 18F-FDG PET for detecting regional lymph node metastasis in resectable lung cancer is variable, and its sensitivity for adenocarcinoma is even lower. We aimed to evaluate the value of 18F-FDG PET-derived features in predicting pathological lymph node metastasis in patients with lung adenocarcinoma. METHODS: We retrospectively analyzed pretreatment 18F-FDG PET-derived features of 126 lung adenocarcinoma patients who underwent curative surgery. A logistic regression model was used to analyze the association between study variables and pathological regional lymph node status obtained from the curative surgery. Furthermore, Cox regression analysis was used to test the effect of the study variables on survival outcomes, including disease-free survival (DFS) and overall survival (OS). RESULTS: The primary tumor entropy (OR = 1.7, p = 0.014) and visual interpretation of regional nodes via 18F-FDG PET (OR = 2.5, p = 0.026) independently predicted pathological regional lymph node metastasis. The areas under the receiver-operating-characteristic curves were 0.631, 0.671, and 0.711 for visual interpretation, primary tumor entropy, and their combination, respectively. Based on visual interpretation, a primary tumor entropy ≥ 3.0 improved the positive predictive value of positive visual interpretation from 51.2% to 63.0%, whereas an entropy < 3.0 improved the negative predictive value of negative visual interpretation from 75.3% to 82.6%. In cases with positive visual interpretation and low entropy, or negative visual interpretation and high entropy, the nodal metastasis rates were approximately 30%. In the survival analyses, the primary tumor entropy was also independently associated with DFS (HR = 2.7, p = 0.001) and OS (HR = 4.8, p = 0.001). CONCLUSIONS: Our preliminary results show that the primary tumor entropy may improve 18F-FDG PET visual interpretation in predicting pathological nodal metastasis in lung adenocarcinoma, and may also show a survival prognostic value. This versatile biomarker may facilitate tailored therapeutic strategies for patients with resectable lung adenocarcinoma.
OBJECTIVE: The diagnostic performance of 18F-FDG PET for detecting regional lymph node metastasis in resectable lung cancer is variable, and its sensitivity for adenocarcinoma is even lower. We aimed to evaluate the value of 18F-FDG PET-derived features in predicting pathological lymph node metastasis in patients with lung adenocarcinoma. METHODS: We retrospectively analyzed pretreatment 18F-FDG PET-derived features of 126 lung adenocarcinoma patients who underwent curative surgery. A logistic regression model was used to analyze the association between study variables and pathological regional lymph node status obtained from the curative surgery. Furthermore, Cox regression analysis was used to test the effect of the study variables on survival outcomes, including disease-free survival (DFS) and overall survival (OS). RESULTS: The primary tumor entropy (OR = 1.7, p = 0.014) and visual interpretation of regional nodes via 18F-FDG PET (OR = 2.5, p = 0.026) independently predicted pathological regional lymph node metastasis. The areas under the receiver-operating-characteristic curves were 0.631, 0.671, and 0.711 for visual interpretation, primary tumor entropy, and their combination, respectively. Based on visual interpretation, a primary tumor entropy ≥ 3.0 improved the positive predictive value of positive visual interpretation from 51.2% to 63.0%, whereas an entropy < 3.0 improved the negative predictive value of negative visual interpretation from 75.3% to 82.6%. In cases with positive visual interpretation and low entropy, or negative visual interpretation and high entropy, the nodal metastasis rates were approximately 30%. In the survival analyses, the primary tumor entropy was also independently associated with DFS (HR = 2.7, p = 0.001) and OS (HR = 4.8, p = 0.001). CONCLUSIONS: Our preliminary results show that the primary tumor entropy may improve 18F-FDG PET visual interpretation in predicting pathological nodal metastasis in lung adenocarcinoma, and may also show a survival prognostic value. This versatile biomarker may facilitate tailored therapeutic strategies for patients with resectable lung adenocarcinoma.
Authors: Hisao Asamura; Kari Chansky; John Crowley; Peter Goldstraw; Valerie W Rusch; Johan F Vansteenkiste; Hirokazu Watanabe; Yi-Long Wu; Marcin Zielinski; David Ball; Ramon Rami-Porta Journal: J Thorac Oncol Date: 2015-12 Impact factor: 15.609
Authors: Peter Goldstraw; Kari Chansky; John Crowley; Ramon Rami-Porta; Hisao Asamura; Wilfried E E Eberhardt; Andrew G Nicholson; Patti Groome; Alan Mitchell; Vanessa Bolejack Journal: J Thorac Oncol Date: 2016-01 Impact factor: 15.609
Authors: M Serra Fortuny; M Gallego; Ll Berna; C Montón; L Vigil; M J Masdeu; A Fernández-Villar; M I Botana; R Cordovilla; R García-Luján; E Cases; E Monsó Journal: BMC Pulm Med Date: 2016-12-08 Impact factor: 3.317