Noise-optimized virtual monoenergetic dual-energy computed tomography: optimization of kiloelectron volt settings in patients with gastrointestinal stromal tumors.

Abstract

The aim of this study was to evaluate the impact of a noise-optimized virtual monoenergetic imaging (VMI+) reconstruction technique on quantitative and qualitative image analysis in patients with gastrointestinal stromal tumors (GISTs) at dual-energy computed tomography (DECT) of the abdomen. Forty-five DECT datasets of 21 patients (14 men; 63.7±9.2years) with GISTs were reconstructed with the standard linearly blended (M_0.6) and VMI+ and traditional virtual monoenergetic (VMI) algorithm in 10-keV increments from 40 to 100keV. Attenuation measurements were performed in GIST lesions and abdominal metastases to calculate objective signal-to-noise (SNR) and contrast-to-noise ratios (CNR). Five-point scales were used to evaluate overall image quality, lesion delineation, image sharpness, and image noise. Quantitative image parameters peaked at 40-keV VMI+ series (SNR 27.8±13.0; CNR 26.3±12.7), significantly superior to linearly blended (SNR 16.8±7.3; CNR 13.6±6.9) and all VMI series (all P<0.001). Qualitative image parameters were highest for 60-keV VMI+ reconstructions regarding overall image quality and image sharpness (median 5, respectively; P≤0.023). Qualitative assessment of lesion delineation peaked in 40 and 50-keV VMI+ series (median 5, respectively). Image noise was superior in 90 and 100-keV VMI and VMI+ reconstructions (all medians 5). Low-keV VMI+ reconstructions significantly increase SNR and CNR of GISTs and improve quantitative and qualitative image quality of abdominal DECT datasets compared to traditional VMI and standard linearly blended image series.