Manuel Piñeiro-Fiel1,2, Alexis Moscoso1,2, Lucía Lado-Cacheiro3, María Pombo-Pasín2, David Rey-Bretal1,2, Noemí Gómez-Lado1,2, Cristina Mondelo-García4,5, Jesús Silva-Rodríguez1,2, Virginia Pubul2, Manuel Sánchez3, Álvaro Ruibal1,2,6, Pablo Aguiar7,8. 1. Molecular Imaging and Medical Physics Group, Radiology Department, Faculty of Medicine, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain. 2. Nuclear Medicine Department and Molecular Imaging Research Group, University Hospital and Health Research Institute of Santiago de Compostela (IDIS), Travesía da Choupana S/N, 15706, Santiago de Compostela, Galicia, Spain. 3. Radiological Protection and Radiation Physics Department, University Hospital and Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain. 4. Pharmacology Group, Health Research Institute of Santiago de Compostela (FIDIS), 15706, Santiago de Compostela, Spain. 5. Pharmacy Department, University Clinical Hospital of Santiago de Compostela (SERGAS), 15706, Santiago de Compostela, Spain. 6. Fundación Tejerina, Madrid, Spain. 7. Molecular Imaging and Medical Physics Group, Radiology Department, Faculty of Medicine, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain. pablo.aguiar.fernandez@sergas.es. 8. Nuclear Medicine Department and Molecular Imaging Research Group, University Hospital and Health Research Institute of Santiago de Compostela (IDIS), Travesía da Choupana S/N, 15706, Santiago de Compostela, Galicia, Spain. pablo.aguiar.fernandez@sergas.es.
Abstract
OBJECTIVES: We aimed at investigating the origin of the correlations between tumor volume and 18F-FDG-PET texture indices in lung cancer. METHODS: Eighty-five consecutive patients with newly diagnosed non-small cell lung cancer (NSCLC) underwent a 18F-FDG-PET/CT scan before treatment. Seven phantom spheres uniformly filled with 18F-FDG, and covering a range of activities and volumes similar to that found in lung tumors, were also scanned. Established texture indices were computed for lung tumors and homogeneous spheres. The dependence between textural indices and volume in homogeneous spheres was modeled and then used to predict texture indices in lung tumors. Correlation analyses were carried out between predicted and texture features measured in lung tumors. Cox proportional hazards regression was used to investigate the associations between overall survival and volume-adjusted textural features. RESULTS: All textural features showed strong, non-linear correlations with volume, both in tumors and homogeneous spheres. Correlations between predicted versus measured texture features were very high for contrast (r2 = 0.91), dissimilarity (r2 = 0.90), ZP (r2 = 0.90), GLNN (r2 = 0.86), and homogeneity (r2 = 0.82); high for entropy (r2 = 0.50) and HILAE (r2 = 0.53); and low for energy (r2 = 0.30). Cox regressions showed that among volume-adjusted features, only HILAE was associated with overall survival (b = - 0.35, p = 0.008). CONCLUSION: We have shown that texture indices previously found to be correlated with a number of clinically relevant outcomes might not provide independent information apart from that driven by their correlation with tumor volume, suggesting that these metrics might not be suitable as intratumor heterogeneity markers. KEY POINTS: • Associations between texture FDG-PET indices and overall survival have been widely reported in lung cancer, with tumor volume also being associated with overall survival, and therefore, it is still unclear whether the predictive power of textural indices is simply driven by this correlation. • Our results demonstrated strong non-linear correlations between textural indices and volume, showing an analogous behavior for lung tumors from patients and homogeneous spheres inserted in phantoms. • Our findings showed that texture FDG-PET indices might not provide independent information apart from that driven by their correlation with tumor volume.
OBJECTIVES: We aimed at investigating the origin of the correlations between tumor volume and 18F-FDG-PET texture indices in lung cancer. METHODS: Eighty-five consecutive patients with newly diagnosed non-small cell lung cancer (NSCLC) underwent a 18F-FDG-PET/CT scan before treatment. Seven phantom spheres uniformly filled with 18F-FDG, and covering a range of activities and volumes similar to that found in lung tumors, were also scanned. Established texture indices were computed for lung tumors and homogeneous spheres. The dependence between textural indices and volume in homogeneous spheres was modeled and then used to predict texture indices in lung tumors. Correlation analyses were carried out between predicted and texture features measured in lung tumors. Cox proportional hazards regression was used to investigate the associations between overall survival and volume-adjusted textural features. RESULTS: All textural features showed strong, non-linear correlations with volume, both in tumors and homogeneous spheres. Correlations between predicted versus measured texture features were very high for contrast (r2 = 0.91), dissimilarity (r2 = 0.90), ZP (r2 = 0.90), GLNN (r2 = 0.86), and homogeneity (r2 = 0.82); high for entropy (r2 = 0.50) and HILAE (r2 = 0.53); and low for energy (r2 = 0.30). Cox regressions showed that among volume-adjusted features, only HILAE was associated with overall survival (b = - 0.35, p = 0.008). CONCLUSION: We have shown that texture indices previously found to be correlated with a number of clinically relevant outcomes might not provide independent information apart from that driven by their correlation with tumor volume, suggesting that these metrics might not be suitable as intratumor heterogeneity markers. KEY POINTS: • Associations between texture FDG-PET indices and overall survival have been widely reported in lung cancer, with tumor volume also being associated with overall survival, and therefore, it is still unclear whether the predictive power of textural indices is simply driven by this correlation. • Our results demonstrated strong non-linear correlations between textural indices and volume, showing an analogous behavior for lung tumors from patients and homogeneous spheres inserted in phantoms. • Our findings showed that texture FDG-PET indices might not provide independent information apart from that driven by their correlation with tumor volume.
Authors: Marco Gerlinger; Andrew J Rowan; Stuart Horswell; James Larkin; David Endesfelder; Eva Gronroos; Pierre Martinez; Nicholas Matthews; Aengus Stewart; Charles Swanton; M Math; Patrick Tarpey; Ignacio Varela; Benjamin Phillimore; Sharmin Begum; Neil Q McDonald; Adam Butler; David Jones; Keiran Raine; Calli Latimer; Claudio R Santos; Mahrokh Nohadani; Aron C Eklund; Bradley Spencer-Dene; Graham Clark; Lisa Pickering; Gordon Stamp; Martin Gore; Zoltan Szallasi; Julian Downward; P Andrew Futreal Journal: N Engl J Med Date: 2012-03-08 Impact factor: 91.245
Authors: Fergus Davnall; Connie S P Yip; Gunnar Ljungqvist; Mariyah Selmi; Francesca Ng; Bal Sanghera; Balaji Ganeshan; Kenneth A Miles; Gary J Cook; Vicky Goh Journal: Insights Imaging Date: 2012-10-24