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Radiomics and functional imaging in lung cancer: the importance of radiological heterogeneity beyond FDG PET/CT and lung biopsy

      Highlights

      • CT Texture Analysis differentiates malignant from benign lung nodules with SUV < 2.5.
      • Kurtosis and Skewness are the most accurate Texture parameters observed.
      • Texture Analysis might be a non-invasive imaging biomarker to reduce lung biopsies.

      Abstract

      Purpose

      [18F]-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography (FDG PET/CT) has a central role in the lung nodules’ characterization even if, with SUV < 2.5, percutaneous CT-guided Lung Biopsy (CTLB) is needed to assess nodule nature. In that scenario, CT Texture Analysis (CTTA) could be a non-invasive imaging biomarker. Our purpose is to test CTTA ability in differentiating malignant from benign nodules.

      Method

      Patients that underwent FDG PET/CT followed by CTLB between January 2013 and December 2018 were retrospectively enrolled. Were included patients with lung nodule SUV < 2.5 and histological diagnosis. Exclusion criteria: nodules SUV > 2.5, patients who refused CTLB or received oncological treatment before CTLB, indeterminate pathology report, CT motion artifacts. Two radiologists in consensus performed CTTA, drawing a volumetric Region of Interest of nodule with a dedicated first order TA software with and without spatial scaling filters, on preliminary CT performed for CTLB. Statistics included a comparison between malignant and benign neoplasms distribution (2-tailed T-test or Mann-Whitney test according to normal/non-normal data distribution), P-values < 0.05 were considered statistically significant. CTTA accuracy was tested with Receiver Operating Characteristics (ROC) curve.

      Results

      Form an initial population of 1178, 46 patients encountered inclusion criteria. Pathologist reported 27/46 (59%) malignant and 19/46 (41%) benign nodules. In malignant lesions CTTA showed lower Kurtosis’ and higher Skewness’ values (all P ≤ 0.0013 and all filtered TA P < 0.024, respectively). ROC curve showed significant Area Under the Curve for Kurtosis and Skewness (0.654 and 0.642, P < 0.001) at medium filtration.

      Conclusions

      CTTA is a promising radiological tool to characterize benign and malignant lung nodules, even in those cases without an altered glucose metabolism.

      Keywords

      Abbreviations:

      FDG PET/CT ([18F]- Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography), AUC (Area Under the Curve), CTLB (CT-guided lung biopsy), CTTA (CT Texture Analysis), MPP (Mean value of positive pixels), PACS (Picture archiving and communication system), ROSE (Rapid on-site evaluation), ROC curve (Receiver operating characteristics curve), ROI (Region of interest), SSF (Spatial scaling filter), SUV (Standardized uptake value)
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