title: Heterogeneity in DCE-MRI parametric maps: a biomarker for treatment response?
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 (K(trans)) 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 K(trans), slope and max enhancement, and the highest specificity (71%) was achieved by K(trans). 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.
authors.affiliation: Department of Radiology, Erasmus MC Rotterdam, Rotterdam, The Netherlands. l.alic@erasmusmc.nl
authors.forename: L
authors.initials: L
authors.lastname: Alic
authors.forename: M
authors.initials: M
authors.lastname: van Vliet
authors.forename: C F
authors.initials: CF
authors.lastname: van Dijke
authors.forename: A M M
authors.initials: AM
authors.lastname: Eggermont
authors.forename: J F
authors.initials: JF
authors.lastname: Veenland
authors.forename: W J
authors.initials: WJ
authors.lastname: Niessen
mesh_terms: D014408:Biomarkers, Tumor / Q000032:analysis*; D003287:Contrast Media / Q000493:pharmacokinetics; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D012509:Sarcoma / Q000378:metabolism / Q000473:pathology* / Q000628:therapy*
chemical_list: D014408:Biomarkers, Tumor; D003287:Contrast Media