A Task-Dependent Investigation on Dose and Texture in CT Image Reconstruction

Localizing and characterizing clinically significant lung nodules, a potential precursor to lung cancer, at the lowest achievable radiation dose is demanded to minimize the stochastic radiation effects from X-ray computed tomography (CT). A minimal dose level is heavily dependent on the image reconstruction algorithms and clinical task, in which the tissue texture always plays an important role. This article aims to investigate the dependence through a task-based evaluation at multiple dose levels and variable textures in reconstructions with prospective patient studies. One hundred and thirty three patients with a suspicious pulmonary nodule scheduled for biopsy were recruited and the data was acquired at 120 kVp with three different dose levels of 100, 40, and 20 mAs. Three reconstruction algorithms were implemented: 1) analytical filtered back-projection (FBP) with optimal noise filtering; 2) statistical Markov random field (MRF) model with optimal Huber weighting (MRF-H) for piecewise smooth reconstruction; and 3) tissue-specific texture model (MRF-T) for texture preserved statistical reconstruction. Experienced thoracic radiologists reviewed and scored all images at random, blind to the CT dose and reconstruction algorithms. The radiologists identified the nodules in each image, including the 133 biopsy target nodules and 66 other nontarget nodules. For target nodule characterization, only MRF-T at 40 mAs showed no statistically significant difference from FBP at 100 mAs. For localizing both the target nodules and the nontarget nodules, some as small as 3 mm, MRF-T at 40 and 20 mAs levels showed no statistically significant difference from FBP at 100 mAs, respectively. MRF-H and FBP at 40 and 20 mAs levels performed statistically differently from FBP at 100 mAs. This investigation concluded that: 1) the textures in the MRF-T reconstructions improves both the tasks of localizing and characterizing nodules at low-dose CT and 2) the task of characterizing nodules is more challenging than the task of localizing nodules and needs more dose or enhanced textures from the reconstruction.