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Details

Autor(en) / Beteiligte
Titel
Magnetic resonance imaging contrast-enhanced relaxometry of breast tumors: an MRI multicenter investigation concerning 100 patients
Ist Teil von
  • Magnetic resonance imaging, 2004-05, Vol.22 (4), p.475-481
Ort / Verlag
Netherlands: Elsevier Inc
Erscheinungsjahr
2004
Quelle
MEDLINE
Beschreibungen/Notizen
  • Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using extracellular contrast agents has proved to be useful for the characterization of breast tumors. DCE-MRI has demonstrated a high sensitivity (around 95%) but a rather poor and controversial specificity, varying, according to the different studies, from 45% to 90%. In order to increase (a) the specificity and (b) the robustness of this quantitative approach in multicenter evaluation (five MRI units), a quantitative approach called dynamic relaxometry has been developed. According to the proposed method, the time-dependent longitudinal relaxation rate measured on region of interest of the lesion was calculated during the contrast uptake, after intravenous bolus injection of contrast agent. A specifically developed method was used for fast R 1 measurements. Relaxometry time curves are fitted to the Tofts model allowing the measurement of the parameters describing the enhancement curve (maximum relation rate enhancement, initial, 30-s and 60-s slopes) and the tissue parameters [transfer constant ( K trans min −1) and extracellular extravascular space fraction ( v e )]. Correspondence factorial analysis followed by hierarchical ascendant classification are then performed on the different parameters. Higher K trans values were observed in infiltrative ductal carcinomas than in infiltrative lobular carcinomas, in agreement with data published by other groups. Specificity of DCE-MRI has been increased up to 85%, with a sensitivity of 95% with K trans / v e and enhancement index I (ratio of initial slope by maximum relaxation rate enhancement). A multiparametric data analysis of the calculated parameters opens the way to include quantitative image-based information in new nosologic approaches to breast tumors.

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