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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 ( A Brix , k ep , and k el ) were determined. Moreover, risk volumes were calculated from the Brix parameters and termed RV- A Brix , RV- k ep , and RV- k el , 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 A Brix , k ep , or k el and treatment outcome were not found. However, RV- A Brix , RV- k ep , and RV- k el correlated with DFS and OS. Multivariate analysis revealed that the prognostic power of RV- A Brix , RV- k ep , and RV- k el was independent of well-established clinical prognostic factors. RV- A Brix , RV- k ep , and RV- k el 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.

Background: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may provide prognostic biomarkers for cervix carcinoma. We have shown previously that the early phase of the signal intensity-versus-time curve (SITC) may have significant prognostic power. The purpose of the present investigation was to explore the prognostic value of the late phase of the SITC., Material and Methods: DCE-MRI data of 80 patients (FIGO stage IB-IVA) treated with concurrent chemoradiotherapy were examined. Four parameters were calculated from the late-phase SITC: tumor volume with decreasing signal, tumor fraction with decreasing signal, tumor volume with increasing signal (TVIS), and tumor fraction with increasing signal., Results: Multivariate analysis involving clinical parameters and late-phase SITC parameters suggested that TVIS is a strong independent prognostic factor for both disease-free and overall survival. When early-phase SITC parameters were included in the multivariate analysis, the early-phase SITC, but not the late-phase SITC, was found to have independent prognostic value., Conclusion: The late-phase SITC can provide prognostic factors for the outcome of cervix carcinoma, that is, a large tumor volume with increasing late-phase SITCs is associated with poor outcome. However, the prognostic power of the late-phase SITC is not as strong as that of the early-phase SITC.

Introduction: Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse., Materials and Methods: Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, K(trans) and ύ(e), were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters., Results: Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels., Conclusions: Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control.