Heterogeneity in DCE-MRI parametric maps: A biomarker for treatment response?

L. Alic*, M. Van Vliet, C. F. Van Dijke, A. M.M. Eggermont, J. F. Veenland, W. J. Niessen

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

75 Citations (Scopus)

Abstract

This study aims to quantify the heterogeneity of tumour enhancement in dynamic contrast-enhanced MRI (DCE-MRI) using texture analysis methods. The suitability of the coherence and the fractal dimension to monitor tumour response was evaluated in 18 patients with limb sarcomas imaged by DCE-MRI pre- and post-treatment. According to the histopathology, tumours were classified into responders and non-responders. Pharmacokinetic (Ktrans) and heuristic model-based parametric maps (slope, max enhancement, AUC) were computed from the DCE-MRI data. A substantial correlation was found between the pharmacokinetic and heuristic model-based parametric maps: ρ = 0.56 for the slope, ρ = 0.44 for maximum enhancement, and ρ = 0.61 for AUC. From all four parametric maps, the enhancing fraction, and the heterogeneity features (i.e. coherence and fractal dimension) were determined. In terms of monitoring tumour response, using both pre- and post-treatment DCE-MRI, the enhancing fraction and the coherence showed significant differences between the response group and the non-response group (i.e. the highest sensitivity (91%) for K trans, and the highest specificity (83%) for max enhancement). In terms of treatment prediction, using solely the pre-treatment DCE-MRI, the enhancing fraction and coherence discriminated between responders and non-responders. For prediction, the highest sensitivity (91%) was shared by Ktrans, slope and max enhancement, and the highest specificity (71%) was achieved by Ktrans. On average, tumours that responded showed a high enhancing fraction and high coherence on the pre-treatment scan. These results suggest that specific heterogeneity features, computed from both pharmacokinetic and heuristic model-based parametric maps, show potential as a biomarker for monitoring tumour response.

Original languageEnglish
Pages (from-to)1601-1616
Number of pages16
JournalPhysics in medicine and biology
Volume56
Issue number6
DOIs
Publication statusPublished - 21 Mar 2011
Externally publishedYes

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