[MRT versus CT in the diagnosis of pneumonias: an evaluation of a T2-weighted ultrafast turbo-spin-echo sequence (UTSE)]

Rofo. 1999 May;170(5):449-56. doi: 10.1055/s-2007-1011072.
[Article in German]

Abstract

Purpose: To evaluate a T2-weighted URSE sequence for the assessment of pulmonary infiltrations in comparison to CT.

Methods: 28 MRT scans of 22 patients with confirmed pneumonia were recorded on a 1.5 Tesla apparatus with an expiratory and diastolic triggered, T2-weighted ultrafast-spin-echo sequence in axial slice mode with the following parameters: TReff/TE/Turbo-factor 2000-4000/90 ms/21-23; slice thickness/separation 6/0.6 mm; FOV 360 mm; 24 slices. 24 spiral CTs (since thickness/table advance: 1-2 mm/10mm) were available for comparison. The separate evaluation of MRTs and CTs was performed by three radiologists in a consensus procedure with regard to pulmonary lesions (e.g., infiltration, round foci, net patterns) and image quality of the MRTs (4-step scale).

Results: In 71% of the cases the CTs and MRTs agreed with the diagnosis and representation of the lesions, in 25% MRT was superior. MRT was better for the detection of pulmonary abscesses. In 93% the image quality of the MRT was very good to good.

Conclusions: MRT in the technique presented here is in most cases equal to CT for the detection of pneumonia. Diagnosis of pulmonary abscesses seems to be better with MRT.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Diagnosis, Differential
  • Evaluation Studies as Topic
  • Female
  • Humans
  • Lung / diagnostic imaging
  • Lung / pathology
  • Lung Abscess / diagnosis
  • Lung Diseases, Fungal / diagnosis
  • Magnetic Resonance Imaging / instrumentation
  • Magnetic Resonance Imaging / methods*
  • Magnetic Resonance Imaging / statistics & numerical data
  • Male
  • Middle Aged
  • Observer Variation
  • Pneumonia, Bacterial / diagnosis*
  • Tomography, X-Ray Computed / instrumentation
  • Tomography, X-Ray Computed / methods*
  • Tomography, X-Ray Computed / statistics & numerical data