Impact of incremental increase in CT image noise on detection of low-contrast hypodense liver lesions

Acad Radiol. 2014 Oct;21(10):1233-9. doi: 10.1016/j.acra.2014.05.011. Epub 2014 Jul 30.

Abstract

Rationale and objectives: To determine the impact of incremental increases in computed tomography (CT) image noise on detection of low-contrast hypodense liver lesions.

Material and methods: We studied 50 CT examinations acquired at image noise index (NI) of 15 and hypodense liver lesions and 50 examinations with no lesions. Validation of a noise addition tool to be used in the evaluation of the CT examinations was performed with a liver phantom. Using this tool, three 100-image sets were assembled: an NI of 17.4 (simulating 75% of the original patient radiation dose), 21.2 (simulating 50% dose), and 29.7 (simulating 25%). Three readers scored certainty of lesion presence using a five-point Likert scale.

Results: For original images (NI 15) plus images with NI of 17.4 and 21.2, sensitivity was >90% threshold (range, 95%-98%). For images with NI of 29.7, sensitivity was just below the threshold (89%). Reader Az values for receiver operating characteristic curves were good for original, NI 17.4, and NI 21.2 images (0.976, 0.973, and 0.96, respectively). For NI of 29.7, the Az decreased to 0.913. Detection sensitivity was <90% for both lesion size < 10 mm (85%) and lesion-to-liver contrast <60 Hounsfield units (85%) only at NI 29.7.

Conclusions: For low-contrast lesion detection in liver CT, image noise can be increased up to NI 21.2 (a 50% patient radiation dose reduction) without substantial reduction in sensitivity.

Keywords: CT; image noise; liver lesion detection; radiation dose.

MeSH terms

  • Artifacts*
  • Humans
  • Liver Neoplasms / diagnostic imaging*
  • Phantoms, Imaging
  • Radiographic Image Enhancement / methods*
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Signal-To-Noise Ratio
  • Tomography, X-Ray Computed / methods*