Can perfusion MRI predict response to preoperative treatment in rectal cancer?

Milou H. Martens*, Samina Subhani, Luc A. Heijnen, Doenja M. J. Lambregts, Jeroen Buijsen, Monique Maas, Robert G. Riedl, Cecile R. L. P. N. Jeukens, Geerard L. Beets, Ewelina Kluza, Regina G. H. Beets-Tan

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


BACKGROUND AND PURPOSE: Dynamic contrast-enhanced MRI (DCE-MRI) provides information on perfusion and could identify good prognostic tumors. Aim of this study was to evaluate whether DCE-MRI using a novel blood pool contrast-agent can accurately predict the response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. MATERIALS AND METHODS: Thirty patients underwent DCE-MRI before and 7-10weeks after chemoradiotherapy. Regions of interest were drawn on DCE-MRI with T2W-images as reference. DCE-MRI-based kinetic parameters (initial slope, initial peak, late slope, and AUC at 60, 90, and 120s) determined pre- and post-CRT and their Delta were compared between good (TRG1-2) and poor (TRG3-5) responders. Optimal thresholds were determined and sensitivities, specificities, positive predictive values (PPV), and negative predictive values (NPV) were calculated. RESULTS: Pre-therapy, the late slope was able to discriminate between good and poor responders (-0.05x10-3 vs. 0.62x10-3, p<0.001) with an AUC of 0.90, sensitivity 92%, specificity 82%, PPV 80%, and NPV 93%. Other pre-CRT parameters showed no significant differences, nor any post-CRT parameters or their Delta. CONCLUSIONS: The kinetic parameter 'late slope' derived from DCE-MRI could potentially be helpful to predict before the onset of neoadjuvant chemoradiotherapy which tumors are likely going to respond. This could allow for personalized treatment-options in rectal cancer patients.
Original languageEnglish
Pages (from-to)218-223
JournalRadiotherapy and Oncology
Issue number2
Publication statusPublished - Feb 2015


  • Rectal cancer
  • Neoadjuvant chemoradiation
  • Response prediction
  • Preoperative treatment

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