Comparison of enhancement quantification from virtual unenhanced images to true unenhanced images in multiphase renal Dual‐Energy computed tomography: A phantom study

摘要

Multiphase computed tomography (CT) exams are a commonly used imaging technique for the diagnosis of renal lesions and involve the acquisition of a true unenhanced (TUE) series followed by one or more postcontrast series. The difference in CT number of the mass in pre‐ and postcontrast images is used to quantify enhancement, which is an important criterion used for diagnosis. This study sought to assess the feasibility of replacing TUE images with virtual unenhanced (VUE) images derived from Dual‐Energy CT datasets in renal CT exams. Eliminating TUE image acquisition could reduce patient dose and improve clinical efficiency. A rapid kVp‐switching CT scanner was used to assess enhancement accuracy when using VUE compared to TUE images as the baseline for enhancement calculations across a wide range of clinical scenarios simulated in a phantom study. Three phantoms were constructed to simulate small, medium, and large patients, each with varying lesion size and location. Nonenhancing cystic lesions were simulated using distilled water. Intermediate (10‐20?HU [Hounsfield units]) and positively enhancing masses (≥20?HU) were simulated by filling the spherical inserts in each phantom with varied levels of iodinated contrast mixed with a blood surrogate. The results were analyzed using Bayesian hierarchical models. Posterior probabilities were used to classify enhancement measured using VUE compared to TUE images as significantly less, not significantly different, or significantly higher. Enhancement measured using TUE images was considered the ground truth in this study. For simulation of nonenhancing renal lesions, enhancement values were not significantly different when using VUE versus TUE images, with posterior probabilities ranging from 0.23‐0.56 across all phantom sizes and an associated specificity of 100%. However, for simulation of intermediate and positively enhancing lesions significant differences were observed, with posterior probabilities??0.05, indicating significantly lower measured enhancement when using VUE versus TUE images. Positively enhancing masses were categorized accurately, with a sensitivity of 91.2%, when using VUE images as the baseline. For all scenarios where iodine was present, VUE‐based enhancement measurements classified lesions with a sensitivity of 43.2%, a specificity of 100%, and an accuracy of 78.1%. Enhancement calculated using VUE images proved to be feasible for classifying nonenhancing and highly enhancing lesions. However, differences in measured enhancement for simulation of intermediately enhancing lesions demonstrated that replacement of TUE with VUE images may not be advisable for renal CT exams.