The skull unfolded: a cranial CT visualization algorithm for fast and easy detection of skull fractures

Radiology. 2010 May;255(2):553-62. doi: 10.1148/radiol.10091096. Epub 2010 Mar 23.


Purpose: To retrospectively assess the rate of detection of skull fractures at cranial computed tomography (CT) achieved with the use of curved maximum intensity projections (MIPs) compared with that achieved by reading transverse sections only.

Materials and methods: The institutional review board approved this research and waived informed consent. A curved thin (3-mm) MIP of the skull cap and a curved thick (50-mm) MIP of the skull base were obtained from the cranial CT data in 200 consecutive patients with head trauma. Four radiologists (two residents without experience in cranial CT and two consultants) independently evaluated all cases. Each radiologist reported findings in 100 patients by using transverse sections only and findings in the other 100 patients by using the unfolded view. The radiologists were blinded to patient names, and patient and group orders were randomized. The results were compared with a standard of reference established by two experts from all prior reading results, all reconstructions, and high-spatial-resolution multiplanar reformats. Logistic regression with repeated measurements was used for statistical analysis.

Results: The experts found 63 fractures in 30 patients. When transverse sections only were used, the mean patient-based fracture detection rate was 43% (13 of 30) for inexperienced and 70% (21 of 30) for experienced readers; with curved MIPs, the rates were 80% (24 of 30) and 87% (26 of 30), respectively. Overall sensitivity was higher with curved MIPs (P < .001); specificity was higher with transverse sections (P < .001).

Conclusion: Curved MIPs enable a significantly higher fracture detection rate than transverse sections. They also considerably close the experience gap in fracture detection rate between residents and experts.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms*
  • Child
  • Child, Preschool
  • Female
  • Humans
  • Infant
  • Logistic Models
  • Male
  • Middle Aged
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Retrospective Studies
  • Sensitivity and Specificity
  • Skull Fractures / diagnostic imaging*
  • Tomography, X-Ray Computed / methods*