Pixel analysis of MR perfusion imaging in predicting radiation therapy outcome in cervical cancer

Nina A. Mayr, William T.C. Yuh, Jeffrey C. Arnholt, James C. Ehrhardt, Joel I. Sorosky, Vincent A. Magnotta, Kevin S. Berbaum, Weining Zhen, Arnold C. Paulino, Larry W. Oberley, Anil K. Sood, John M. Buatti

Research output: Contribution to journalArticlepeer-review

135 Scopus citations


The purpose of this study was to assess heterogeneity of tumor microcirculation determined by dynamic contrast-enhanced magnetic resonance (MR) imaging and its prognostic value for tumor radiosensitivity and long-term tumor control using pixel-by-pixel analysis of the dynamic contrast enhancement. Sixteen patients with advanced cervical cancer were examined with dynamic contrast-enhanced MR imaging at the time of radiation therapy. Pixel-by-pixel statistical analysis of the ratio of post- to precontrast relative signal intensity (RSI) values in the tumor region was performed to generate pixel RSI distributions of dynamic enhancement patterns. Histogram parameters were correlated with subsequent tumor control based on long-term cancer follow-up (median follow-up 4.6 years; range 3.8-5.2 years). The RSI distribution histograms showed a wide spectrum of heterogeneity in the dynamic enhancement pattern within the tumor. The quantity of low-enhancement regions (10th percentile RSI < 2.5) significantly predicted subsequent tumor recurrence (88% vs. 0%, P = 0.0004). Discriminant analysis based on both 10th percentile RSI and pixel number (reflective of tumor size) further improved the prediction rate (100% correct prediction of subsequent tumor control vs. recurrence). These preliminary results suggest that quantification of the extent of poor vascularity regions within the tumor may be useful in predicting long-term tumor control and treatment outcome in cervical cancer. (C) 2000 Wiley-Liss, Inc.

Original languageEnglish (US)
Pages (from-to)1027-1033
Number of pages7
JournalJournal of Magnetic Resonance Imaging
Issue number6
StatePublished - 2000

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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