Abstract
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Objectives We assessed the clinical value of tumor heterogeneity measured with 18F-FLT and 18F-FDG as a biomarker for lung cancer diagnosis and staging, and compared the performance to SUV of both tracers using final pathology as gold standard.
Methods Thirty-five subjects with lung nodules (19 M, 16 F, age 70 ± 9 y) who underwent both 18F-FDG and 18F-FLT PET/CT scans were included in our study. We applied the global Moran I(d) analysis to characterize the intra-tumor heterogeneity on PET images 1h post-injection. Different from texture analysis, which is widely used in heterogeneity estimation, I(d) statistic is a measurement of spatial autocorrelation that characterized by the correlation among 3D neighboring voxels. Each suspicious volume of interest (VOI) was automatically delineated by a thresholding algorithm. Receiver operating characteristic curve (ROC) analysis was then used to determine the diagnostic accuracy of each biomarker. The reference diagnosis and staging was determined by final pathology from biopsy or surgery.
Results The heterogeneity derived from 18F-FLT images significantly differentiated benign subjects (0.24 ± 0.09, N=10) from early stage malignancy group (0.40 ± 0.09, N=10; P = 0.002), as well as early stage malignancy from advanced stage malignancy (0.50 ± 0.07, N=15, P = 0.005). 18F-FDG heterogeneity and SUV values did not demonstrate similar capability. ROC curve analysis confirms that FLT heterogeneity yielded identification of benign vs early malignant tumors with an area under curve value (AUC) of 0.88 (95% confidence interval) as well as staging for early/advanced stage tumors (AUC 0.89), and significantly superior performance compared to FDG heterogeneity (AUC = 0.51 and 0.71, respectively) as to SUVmax of both FLT (0.67 and 0.78) and FDG (0.53 and 0.76).
Conclusions 18F-FLT tumor heterogeneity has great potential to augment diagnostic accuracy and improve tumor staging in oncological practice.