Impact of noise-optimized virtual monoenergetic dual-energy computed tomography on image quality in patients with renal cell carcinoma.
Abstract
OBJECTIVE:
The aim of this study was to evaluate the impact of a noise-optimized virtual monoenergetic imaging (VMI+) reconstruction technique on image quality and lesion delineation in patients with renal cell carcinoma (RCC) undergoing abdominal dual-energy computed tomography (DECT).
MATERIALS AND METHODS:
Fifty-two patients (33 men; 61.5±13.6years) with RCC underwent contrast-enhanced DECT during the corticomedullary and nephrogenic phase of renal enhancement. DECT datasets were reconstructed with standard linearly-blended (M_0.6), as well as traditional virtual monoenergetic (VMI) and VMI+ algorithms in 10-keV increments from 40 to 100 keV. Contrast-to-noise (CNR) and tumor-to-cortex ratios for corticomedullary- and nephrogenic-phase images were objectively measured by a radiologist with 3 years of experience. Subjective image quality and RCC delineation were evaluated by three independent radiologists.
RESULTS:
Greatest CNR values were found for 40-keV VMI+ series in both corticomedullary- (8.9±4.9) and nephrogenic-phase (7.1±4.6) images and were significantly higher compared to all other reconstructions (P<0.001). Furthermore, tumor-to-cortex ratios were highest for 40-keV nephrogenic-phase VMI+ (2.1±3.5; P≤0.016), followed by 50-keV and 60-keV VMI+ (2.0±3.2 and 1.8±2.8, respectively). Qualitative image quality scored highest for 50-keV VMI+ series in corticomedullary-phase reconstructions and 60-keV in nephrogenic-phase reconstructions (P≤0.031). Highest scores for lesion delineation were assigned for 40-keV VMI+ reconstructions (P≤0.074).
CONCLUSION:
Low-keV VMI+ reconstructions lead to improved image quality and lesion delineation of corticomedullary- and nephrogenic-phase DECT datasets in patients with RCC.