Purpose: The present study aimed to determine whether fractal analysis of morphological complexity and intratumoral heterogeneity of FDG uptake can help to differentiate malignant from benign pulmonary nodules.
Materials and methods: We retrospectively analyzed data from 54 patients with suspected non-small cell lung cancer (NSCLC) who were examined by FDG PET/CT. Pathological assessments of biopsy specimens confirmed 35 and 19 nodules as NSCLC and inflammatory lesions, respectively. The morphological fractal dimension (m-FD), maximum standardized uptake value (SUV(max)) and density fractal dimension (d-FD) of target nodules were calculated from CT and PET images. Fractal dimension is a quantitative index of morphological complexity and tracer uptake heterogeneity; higher values indicate increased complexity and heterogeneity.
Results: The m-FD, SUV(max) and d-FD significantly differed between malignant and benign pulmonary nodules (p<0.05). Although the diagnostic ability was better for d-FD than m-FD and SUV(max), the difference did not reach statistical significance. Tumor size correlated significantly with SUV(max) (r=0.51, p<0.05), but not with either m-FD or d-FD. Furthermore, m-FD combined with either SUV(max) or d-FD improved diagnostic accuracy to 92.6% and 94.4%, respectively.
Conclusion: The d-FD of intratumoral heterogeneity of FDG uptake can help to differentially diagnose malignant and benign pulmonary nodules. The SUV(max) and d-FD obtained from FDG-PET images provide different types of information that are equally useful for differential diagnoses. Furthermore, the morphological complexity determined by CT combined with heterogeneous FDG uptake determined by PET improved diagnostic accuracy.
Keywords: (18)F-FDG PET/CT; Diagnostic accuracy; Non-small cell lung cancer; Texture analysis.
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