Validation of optimal DCE-MRI perfusion threshold to classify at-risk tumor imaging voxels in heterogeneous cervical cancer for outcome prediction

Magn Reson Imaging. 2014 Dec;32(10):1198-205. doi: 10.1016/j.mri.2014.08.039. Epub 2014 Aug 29.

Abstract

Purpose: To classify tumor imaging voxels at-risk for treatment failure within the heterogeneous cervical cancer using DCE MRI and determine optimal voxel's DCE threshold values at different treatment time points for early prediction of treatment failure.

Material and method: DCE-MRI from 102 patients with stage IB2-IVB cervical cancer was obtained at 3 different treatment time points: before (MRI 1) and during treatment (MRI 2 at 2-2.5 weeks and MRI 3 at 4-5 weeks). For each tumor voxel, the plateau signal intensity (SI) was derived from its time-SI curve from the DCE MRI. The optimal SI thresholds to classify the at-risk tumor voxels was determined by the maximal area under the curve using ROC analysis when varies SI value from 1.0 to 3.0 and correlates with treatment outcome.

Results: The optimal SI thresholds for MRI 1, 2 and 3 were 2.2, 2.2 and 2.1 for significant differentiation between local recurrence/control, respectively, and 1.8, 2.1 and 2.2 for death/survival, respectively.

Conclusion: Optimal SI thresholds are clinically validated to quantify at-risk tumor voxels which vary with time. A single universal threshold (SI=1.9) was identified for all 3 treatment time points and remained significant for the early prediction of treatment failure.

Keywords: Cervical cancer; Image analysis; Microcirculation; Perfusion imaging; Radiation therapy; Resistant tumor cell.

Publication types

  • Research Support, N.I.H., Extramural
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Area Under Curve
  • Disease-Free Survival
  • Female
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Microcirculation
  • Middle Aged
  • Neoplasm Recurrence, Local
  • Perfusion
  • ROC Curve
  • Treatment Outcome
  • Uterine Cervical Neoplasms / diagnosis*
  • Uterine Cervical Neoplasms / pathology*