Pharmacokinetic analysis of DCE-MRI data of locally advanced cervical carcinoma with the Brix model

Acta Oncol. 2019 Jun;58(6):828-837. doi: 10.1080/0284186X.2019.1580386. Epub 2019 Feb 27.

Abstract

Background: There is significant evidence that DCE-MRI may have the potential to provide clinically useful biomarkers of the outcome of locally advanced cervical carcinoma. However, there is no consensus on how to analyze DCE-MRI data to arrive at the most powerful biomarkers. The purpose of this study was to analyze DCE-MRI data of cervical cancer patients by using the Brix pharmacokinetic model and to compare the biomarkers derived from the Brix analysis with biomarkers determined by non-model-based analysis [i.e., low-enhancing tumor volume (LETV) and tumor volume with increasing signal (TVIS)] of the same patient cohort. Material and methods: DCE-MRI recordings of 80 patients (FIGO stage IB-IVA) treated with concurrent cisplatin-based chemoradiotherapy were analyzed voxel-by-voxel, and frequency distributions of the three parameters of the Brix model (ABrix, kep, and kel) were determined. Moreover, risk volumes were calculated from the Brix parameters and termed RV-ABrix, RV-kep, and RV-kel, where the RVs represent the tumor volume with voxel values below a threshold value determined by ROC analysis. Disease-free survival (DFS) and overall survival (OS) were used as measures of treatment outcome. Results: Significant associations between the median value or any other percentile value of ABrix, kep, or kel and treatment outcome were not found. However, RV-ABrix, RV-kep, and RV-kel correlated with DFS and OS. Multivariate analysis revealed that the prognostic power of RV-ABrix, RV-kep, and RV-kel was independent of well-established clinical prognostic factors. RV-ABrix, RV-kep, and RV-kel correlated with each other as well as with LETV and TVIS. Conclusion: Strong biomarkers of the outcome of locally advanced cervical carcinoma can be provided by subjecting DCE-MRI series to pharmacokinetic analysis using the Brix model. The prognostic power of these biomarkers is not necessarily superior to that of biomarkers identified by non-model-based analyses.

MeSH terms

  • Adenocarcinoma / metabolism
  • Adenocarcinoma / pathology*
  • Adenocarcinoma / therapy
  • Adult
  • Aged
  • Aged, 80 and over
  • Carcinoma, Squamous Cell / metabolism
  • Carcinoma, Squamous Cell / pathology*
  • Carcinoma, Squamous Cell / therapy
  • Chemoradiotherapy / mortality
  • Contrast Media / pharmacokinetics*
  • Female
  • Follow-Up Studies
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Magnetic Resonance Imaging / methods*
  • Middle Aged
  • Models, Statistical*
  • Neoplasm Recurrence, Local / metabolism
  • Neoplasm Recurrence, Local / pathology*
  • Neoplasm Recurrence, Local / therapy
  • Prognosis
  • Survival Rate
  • Tissue Distribution
  • Uterine Cervical Neoplasms / metabolism
  • Uterine Cervical Neoplasms / pathology*
  • Uterine Cervical Neoplasms / therapy
  • Young Adult

Substances

  • Contrast Media