Pulmonary Emphysema Quantification on Ultra-Low-Dose Computed Tomography Using Model-Based Iterative Reconstruction With or Without Lung Setting

J Comput Assist Tomogr. 2018 Sep/Oct;42(5):760-766. doi: 10.1097/RCT.0000000000000755.

Abstract

Objectives: To evaluate the influence of model-based iterative reconstruction (MBIR) with lung setting and conventional setting on pulmonary emphysema quantification by ultra-low-dose computed tomography (ULDCT) compared with standard-dose CT (SDCT).

Methods: Forty-five patients who underwent ULDCT (0.18 ± 0.02 mSv) and SDCT (6.66 ± 2.69 mSv) were analyzed in this retrospective study. Images were reconstructed using filtered back projection (FBP) with smooth and sharp kernels and MBIR with conventional and lung settings. Extent of emphysema was evaluated using fully automated software. Correlation between ULDCT and SDCT was assessed by interclass correlation coefficiency (ICC) and Bland-Altman analysis.

Results: Excellent correlation was seen between MBIR with conventional setting on ULDCT and FBP with smooth kernel on SDCT (ICC, 0.97; bias, -0.31%) and between MBIR with lung setting on ULDCT and FBP with sharp kernel on SDCT (ICC, 0.82; bias, -2.10%).

Conclusion: Model-based iterative reconstruction improved the agreement between ULDCT and SDCT on emphysema quantification.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Lung / diagnostic imaging
  • Male
  • Middle Aged
  • Pulmonary Emphysema / diagnostic imaging*
  • Radiation Dosage*
  • Radiographic Image Interpretation, Computer-Assisted / methods
  • Retrospective Studies
  • Tomography, X-Ray Computed / methods*