Craniopharyngiomas: identification of different semiological patterns with MRI

Eur Radiol. 2002 Jul;12(7):1829-36. doi: 10.1007/s00330-001-1196-y. Epub 2001 Nov 20.

Abstract

Our objectives were to analyze different semiological patterns in craniopharyngiomas studied with CT and MR sequences. Retrospective study of 26 patients with confirmed craniopharyngiomas. All cases were examined with CT and MR imaging using a variety of pulse sequences (spin echo, inversion recovery, gradient echo in-phase and opposed-phase). The analyzed component patterns were classified as solid, calcium, proteic-like, cerebrospinal fluid (CSF)-like, hematic-like, and fatty patterns. The different patterns were related by means of contingency tables and the Fisher exact test and also to epidemiological findings and tumor size. A solid pole was detected in all patients, whereas a cystic component was present in 92.3% of the cases. Calcification was visualized in 65.3%, proteic-like in 53.8%, CSF-like in 23%, hematic-like in 19.2%, and fatty component in 15.3%. There were no statistical associations between patterns, with the exception that in no case did CSF-like and proteic-like patterns coexist ( P=0.004). Tumor size was related to components. Hematic-like (17.0+/-18.9 vs 3.9+/-2.6 mm, non-present vs present) and CSF-like (16.9+/-19.6 vs 6.5+/-4.0 mm) patterns were observed most frequently in smaller tumors, whereas larger tumors usually had proteic-like (5.9+/-5.4 vs 21.1+/-21.0 mm) and calcified (4.6+/-1.9 vs 19.1+/-19.9 mm) patterns. Computed tomography and a combination of different MR images frequently allow the detection of different semiological patterns in these tumors. Semiological patterns were correlated only to tumor size.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Child
  • Child, Preschool
  • Craniopharyngioma / classification
  • Craniopharyngioma / diagnosis*
  • Craniopharyngioma / diagnostic imaging
  • Female
  • Humans
  • Magnetic Resonance Imaging* / methods
  • Male
  • Middle Aged
  • Pituitary Neoplasms / classification
  • Pituitary Neoplasms / diagnosis*
  • Pituitary Neoplasms / diagnostic imaging
  • Retrospective Studies
  • Tomography, X-Ray Computed