Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 2020 Apr 15;15(1):79.
doi: 10.1186/s13014-020-01526-2.

DCE-MRI of locally-advanced carcinoma of the uterine cervix: Tofts analysis versus non-model-based analyses

Kjersti V Lund  1   2 , Trude G Simonsen  1 , Gunnar B Kristensen  3   4 , Einar K Rofstad  5
Affiliations
Comparative Study

DCE-MRI of locally-advanced carcinoma of the uterine cervix: Tofts analysis versus non-model-based analyses

Kjersti V Lund et al. Radiat Oncol. .

Abstract

Background: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may provide biomarkers of the outcome of locally-advanced cervical carcinoma (LACC). There is, however, no agreement on how DCE-MR recordings should be analyzed. Previously, we have analyzed DCE-MRI data of LACC using non-model-based strategies. In the current study, we analyzed DCE-MRI data of LACC using the Tofts pharmacokinetic model, and the biomarkers derived from this analysis were compared with those derived from the non-model-based analyses.

Methods: Eighty LACC patients given cisplatin-based chemoradiotherapy with curative intent were included in the study. Treatment outcome was recorded as disease-free survival (DFS) and overall survival (OS). DCE-MRI series were analyzed voxelwise to produce Ktrans and ve frequency distributions, and ROC analysis was used to identify the parameters of the frequency distributions having the greatest potential as biomarkers. The prognostic power of these parameters was compared with that of the non-model-based parameters LETV (low-enhancing tumor volume) and TVIS (tumor volume with increasing signal).

Results: Poor DFS and OS were associated with low values of Ktrans, whereas there was no association between treatment outcome and ve. The Ktrans parameters having the greatest prognostic value were p35-Ktrans (the Ktrans value at the 35 percentile of a frequency distribution) and RV-Ktrans (the tumor subvolume with Ktrans values below 0.13 min- 1). Multivariate analysis including clinical parameters and p35-Ktrans or RV-Ktrans revealed that RV-Ktrans was the only independent prognostic factor of DFS and OS. There were significant correlations between RV-Ktrans and LETV and between RV-Ktrans and TVIS, and the prognostic power of RV-Ktrans was similar to that of LETV and TVIS.

Conclusions: Biomarkers of the outcome of LACC can be provided by analyzing DCE-MRI series using the Tofts pharmacokinetic model. However, these biomarkers do not appear to have greater prognostic value than biomarkers determined by non-model-based analyses.

Keywords: Biomarkers; Cervical carcinoma; DCE-MRI; Tofts pharmacokinetic model.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Representative anatomical MR images. a A sagittal and two axial T1-weighted scans showing the signal intensities of the two-chamber calibration tube. The dashed horizontal lines indicate the positions of the axial scans. b A proton density-weighted image, a precontrast T1-weighted image, and a postcontrast T1-weighted image showing the signal intensities of the tumor tissue. Scale bars: 2 cm
Fig. 2
Fig. 2
Representative Ktrans data. Single-voxel plots of Gd-DTPA concentration versus time after contrast injection, Ktrans frequency distribution, parametric Ktrans image, and binary Ktrans image of a a high-enhancing tumor and b a low-enhancing tumor. The dark grey regions in the frequency distributions and binary images represent RV-Ktrans. Scale bars: 1 cm
Fig. 3
Fig. 3
Log-rank and ROC analyses. The values of Ktrans at each percentile of the frequency distributions and the tumor volumes (RV-Ktrans) with Ktrans values below a wide range of threshold values were calculated for the 80 tumors included in the study, and for each Ktrans percentile and each Ktrans threshold value, the outcome of the patients with high values of Ktrans or RV-Ktrans was compared with the outcome of those with low values, using the log-rank test with DFS and OS as endpoints. ROC analysis was carried out to indentify the Ktrans percentile and Ktrans threshold value with the highest discriminative power. a Log-rank p value versus Ktrans percentile. b Area under ROC-curve versus Ktrans percentile. c Log-rank p value versus Ktrans threshold value. d Area under ROC-curve versus Ktrans threshold value
Fig. 4
Fig. 4
Treatment outcome. Kaplan–Meier curves for DFS and OS of LACC patients stratified by 35p-Ktransa,b and RV-Ktransc,d. p values: log-rank test
Fig. 5
Fig. 5
Model-based versus non-model-based RVs. Log scale plots of RV-Ktrans versus LETV a and TVIS b for patients with LACC. The patient cohort was divided into two groups consisting of one-third and two-thirds of the patients, and the discrimination levels are indicated by horizontal lines for RV-Ktrans and by vertical lines for LETV and TVIS. Points: individual tumors. Curves: linear regression. p values: Spearman rank order correlation test
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Höckel M, Knoop C, Schlenger K, Vorndran B, Baussmann E, Mitze M, et al. Intratumoral pO2 predicts survival in advanced cancer of the uterine cervix. Radiother Oncol. 1993;26:45–50. doi: 10.1016/0167-8140(93)90025-4. - DOI - PubMed
    1. Fyles AW, Milosevic M, Wong R, Kavanagh MC, Pintilie M, Sun A, et al. Oxygenation predicts radiation response and survival in patients with cervix cancer. Radiother Oncol. 1998;48:149–156. doi: 10.1016/S0167-8140(98)00044-9. - DOI - PubMed
    1. Sundfør K, Lyng H, Tropé CG, Rofstad EK. Treatment outcome in advanced squamous cell carcinoma of the uterine cervix: relationships to pretreatment tumor oxygenation and vascularization. Radiother Oncol. 2000;54:101–107. doi: 10.1016/S0167-8140(99)00175-9. - DOI - PubMed
    1. Barwick TD, Taylor A, Rockall A. Functional imaging to predict tumor response in locally advanced cervical cancer. Curr Oncol Rep. 2013;15:549–558. doi: 10.1007/s11912-013-0344-2. - DOI - PubMed
    1. Ellingsen C, Hompland T, Galappathi K, Mathiesen B, Rofstad EK. DCE-MRI of the hypoxic fraction, radioresponsiveness, and metastatic propensity of cervical carcinoma xenografts. Radiother Oncol. 2014;110:335–341. doi: 10.1016/j.radonc.2013.10.018. - DOI - PubMed

Publication types

MeSH terms