Effect of Slab Thickness on the Detection of Pulmonary Nodules by Use of CT Maximum and Minimum Intensity Projection

AJR Am J Roentgenol. 2019 Sep;213(3):562-567. doi: 10.2214/AJR.19.21325. Epub 2019 May 7.

Abstract

OBJECTIVE. The purpose of this study was to investigate the effect of slab thickness on the detection of pulmonary nodules by use of maximum-intensity-projection (MIP) and minimum-intensity-projection (MinIP) to process CT images. MATERIALS AND METHODS. Chest CT data of 221 patients with pulmonary nodules were retrospectively analyzed. Nodules were categorized into two groups according to density: solid nodules (SNs) and subsolid nodules (SSNs). Pulmonary nodules were independently evaluated by two radiologists using axial CT images with 1-mm and 5-mm section thickness and MIP and MinIP images. MIP images for SN detection and MinIP images for SSN detection were separately reconstructed with four (5, 10, 15, 20 mm) and three (3, 8, 15 mm) slab thicknesses. The numbers and locations of detected nodules were recorded, and interobserver agreement was assessed. For each reader, the differences in nodule detection rates were evaluated in different series of images. RESULTS. Among the different series of images, interobserver agreements for detecting nodules were all good to excellent (κ ≥ 0.687). For total SNs and SNs with a diameter < 5 mm, detection rates on 10-mm MIP images were significantly higher than in other series of images (reader 1, 84.5% and 83.8%; reader 2, 83.6% and 82.2%). For total SSNs and SSNs < 5 mm, detection rates on 3-mm MinIP images were significantly higher than those in other series of images, except for 1-mm (reader 1, 93.3% and 78.6%; reader 2, 95.0% and 81.0%). CONCLUSION. Ten-millimeter MIP images are extremely efficient for detecting SNs. Three-millimeter MinIP images are more useful for visualizing SSNs, the efficiency being comparable to that achieved by use of 1-mm axial images.

Keywords: CT; maximum intensity projection; minimum intensity projection; pulmonary nodule.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Female
  • Humans
  • Lung Neoplasms / diagnostic imaging*
  • Lung Neoplasms / pathology
  • Male
  • Middle Aged
  • Multiple Pulmonary Nodules / diagnostic imaging*
  • Multiple Pulmonary Nodules / pathology
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Retrospective Studies
  • Tomography, X-Ray Computed / methods*