Impact of noise-optimized virtual monoenergetic dual-energy computed tomography on image quality in patients with renal cell carcinoma

Eur J Radiol. 2017 Dec;97:1-7. doi: 10.1016/j.ejrad.2017.10.008. Epub 2017 Oct 6.

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.

Keywords: Computed tomography; Image quality; Oncology; Post-processing; Renal cell carcinoma.

Publication types

  • Comparative Study
  • Evaluation Study

MeSH terms

  • Abdomen
  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms
  • Carcinoma, Renal Cell / diagnostic imaging*
  • Female
  • Humans
  • Kidney Neoplasms / diagnostic imaging*
  • Male
  • Middle Aged
  • Noise*
  • Observer Variation
  • Radiographic Image Interpretation, Computer-Assisted / methods
  • Radiographic Image Interpretation, Computer-Assisted / standards
  • Radiography, Dual-Energy Scanned Projection / methods
  • Radiography, Dual-Energy Scanned Projection / standards
  • Radiologists
  • Reproducibility of Results
  • Retrospective Studies
  • Signal-To-Noise Ratio
  • Tomography, X-Ray Computed / methods
  • Tomography, X-Ray Computed / standards