Variability in CT lung-nodule quantification: Effects of dose reduction and reconstruction methods on density and texture based features

作者：P Lo, Stefano Young, H. J. Kim, Matthew S. Brown, Michael F. McNitt‐Gray · 发表于：Medical Physics · 年份：2016 · DOI：10.1118/1.4954845 · 被引用次数：62 · 研究领域：Advanced Radiotherapy Techniques、Effects of Radiation Exposure、Lung Cancer Diagnosis and Treatment

PURPOSE: To investigate the effects of dose level and reconstruction method on density and texture based features computed from CT lung nodules. METHODS: This study had two major components. In the first component, a uniform water phantom was scanned at three dose levels and images were reconstructed using four conventional filtered backprojection (FBP) and four iterative reconstruction (IR) methods for a total of 24 different combinations of acquisition and reconstruction conditions. In the second component, raw projection (sinogram) data were obtained for 33 lung nodules from patients scanned as a part of their clinical practice, where low dose acquisitions were simulated by adding noise to sinograms acquired at clinical dose levels (a total of four dose levels) and reconstructed using one FBP kernel and two IR kernels for a total of 12 conditions. For the water phantom, spherical regions of interest (ROIs) were created at multiple locations within the water phantom on one reference image obtained at a reference condition. For the lung nodule cases, the ROI of each nodule was contoured semiautomatically (with manual editing) from images obtained at a reference condition. All ROIs were applied to their corresponding images reconstructed at different conditions. For 17 of the nodule cases, repeat contours were performed to assess repeatability. Histogram (eight features) and gray level co-occurrence matrix (GLCM) based texture features (34 features) were computed for all ROIs...