Abstract
Background: Radiomics, a field of research, relies on the theory that quantified characteristics from radiographic images would reflect underlying pathophysiology. Lung cancer continues to stand as one of the prevalent and well-known forms of cancer, causing mortality. The slice thickness (ST) of computed tomography (CT) images would be key concern regarding generalizability of radiomic features (RF) results in oncology. There is scarcity of research that has delved into how ST affects variability of RF in lung tumors. Hence, aim of the study is to evaluate influence of ST on reproducibility of CT-RF for lung tumors. Methods: This is a prospective study, 32 patients with confirmed histopathological diagnosis of lung tumors were included. Contrast Enhanced CT (CECT) thorax was performed using a 128- Incisive CT (Philips Health Care). The image acquisition was performed with 5-mm and 2 mm ST, and was reconstructed retrospectively. RF were extracted from the CECT thorax images of 5-mm and 2-mm ST. We conducted a paired t-test to evaluate the disparity in RF between the two thicknesses. Lin’s Concordance Correlation Coefficient (CCC) was performed to identify the reproducibility of RF between the two thicknesses. Results: Out of 107 RF extracted, 66 (61.6%) exhibited a statistically significant distinction (p<0.05) when comparing two slice thicknesses and while 41 (38.3%) RF did not show significant distinction (p>0.05) between the two ST measurements. 29 features (CCC ≥ 0.90) showed excellent to moderate reproducibility, and 78 features (CCC ≤ 0.90) showed poor reproducibility. Among the 7 RF categories, the shape-based features (57.1%) showed the maximum reproducibility whereas NGTDM-based features showed negligible reproducibility. Conclusions: The slice thickness had a notable impact on the majority of CT-RF of lung tumors. Shape based features (57.1%). First order (44.4%) features showed highest reproducibility compared to other RF categories.
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