National Cancer Institute (NIH). Cervical cancer treatment (PDQ®). http://www.cancer.gov/types/cervical/hp/cervical-treatment-pdq#section/_126. Accessed 3 Mar 2017.
Milosevic M, Fyles A, Hedley D, Pintilie M, Levin W, Manchul L, et al. Interstitial fluid pressure predicts survival in patients with cervix cancer independent of clinical prognostic factors and tumor oxygen measurements. Cancer Res. 2001;61:6400–5.
CAS
PubMed
Google Scholar
Walenta S, Wetterling M, Lehrke M, Schwickert G, Sundfor K, Rofstad EK, et al. High lactate levels predict likelihood of metastases, tumor recurrence, and restricted patient survival in human cervical cancers. Cancer Res. 2000;60:916–21.
CAS
PubMed
Google Scholar
Hockel M, Schlenger K, Aral B, Mitze M, Schaffer U, Vaupel P. Association between tumor hypoxia and malignant progression in advanced cancer of the uterine cervix. Cancer Res. 1996;56:4509–15.
CAS
PubMed
Google Scholar
Sundfor K, Lyng H, Trope CG, Rofstad EK. Treatment outcome in advanced squamous cell carcinoma of the uterine cervix: relationships to pretreatment tumor oxygenation and vascularization. Radiother Oncol. 2000;54:101–7.
Article
CAS
PubMed
Google Scholar
Sundfor K, Lyng H, Rofstad EK. Tumour hypoxia and vascular density as predictors of metastasis in squamous cell carcinoma of the uterine cervix. Br J Cancer. 1998;78:822–7.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hasan J, Byers R, Jayson GC. Intra-tumoural microvessel density in human solid tumours. Br J Cancer. 2002;86:1566–77.
Article
CAS
PubMed
PubMed Central
Google Scholar
Rofstad EK, Galappathi K, Mathiesen BS. Tumor interstitial fluid pressure—a link between tumor hypoxia, microvascular density, and lymph node metastasis. Neoplasia. 2014;16:586–94.
Article
PubMed
PubMed Central
Google Scholar
Ellingsen C, Egeland TA, Gulliksrud K, Gaustad JV, Mathiesen B, Rofstad EK. Assessment of hypoxia in human cervical carcinoma xenografts by dynamic contrast-enhanced magnetic resonance imaging. Int J Radiat Oncol Biol Phys. 2009;73:838–45.
Article
PubMed
Google Scholar
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;110:335–41.
Article
PubMed
Google Scholar
Ellingsen C, Walenta S, Hompland T, Mueller-Klieser W, Rofstad EK. The microenvironment of cervical carcinoma xenografts: associations with lymph node metastasis and its assessment by DCE-MRI. Transl Oncol. 2013;6:607–17.
Article
PubMed
PubMed Central
Google Scholar
Hompland T, Ellingsen C, Ovrebo KM, Rofstad EK. Interstitial fluid pressure and associated lymph node metastasis revealed in tumors by dynamic contrast-enhanced MRI. Cancer Res. 2012;72:4899–908.
Article
CAS
PubMed
Google Scholar
Mayr NA, Yuh WT, Magnotta VA, Ehrhardt JC, Wheeler JA, Sorosky JI, et al. Tumor perfusion studies using fast magnetic resonance imaging technique in advanced cervical cancer: a new noninvasive predictive assay. Int J Radiat Oncol Biol Phys. 1996;36:623–33.
Article
CAS
PubMed
Google Scholar
Cooper RA, Carrington BM, Loncaster JA, Todd SM, Davidson SE, Logue JP, et al. Tumour oxygenation levels correlate with dynamic contrast-enhanced magnetic resonance imaging parameters in carcinoma of the cervix. Radiother Oncol. 2000;57:53–9.
Article
CAS
PubMed
Google Scholar
Haider MA, Sitartchouk I, Roberts TP, Fyles A, Hashmi AT, Milosevic M. Correlations between dynamic contrast-enhanced magnetic resonance imaging-derived measures of tumor microvasculature and interstitial fluid pressure in patients with cervical cancer. J Magn Reson Imaging. 2007;25:153–9.
Article
PubMed
Google Scholar
Kopetz S, Lemos R, Powis G. The promise of patient-derived xenografts: the best laid plans of mice and men. Clin Cancer Res. 2012;18:5160–2.
Article
PubMed
PubMed Central
Google Scholar
Hidalgo M, Amant F, Biankin AV, Budinska E, Byrne AT, Caldas C, et al. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov. 2014;4:998–1013.
Article
CAS
PubMed
PubMed Central
Google Scholar
Rofstad EK, Simonsen TG, Huang R, Andersen LM, Galappathi K, Ellingsen C, et al. Patient-derived xenograft models of squamous cell carcinoma of the uterine cervix. Cancer Lett. 2016;373:147–55.
Article
CAS
PubMed
Google Scholar
Rofstad EK, Huang R, Galappathi K, Andersen LM, Wegner CS, Hauge A, et al. Functional intratumoral lymphatics in patient-derived xenograft models of squamous cell carcinoma of the uterine cervix: implications for lymph node metastasis. Oncotarget. 2016;7:56986–97.
Article
PubMed
PubMed Central
Google Scholar
Gaustad JV, Simonsen TG, Smistad R, Wegner CS, Andersen LM, Rofstad EK. Early effects of low dose bevacizumab treatment assessed by magnetic resonance imaging. BMC Cancer. 2015;15:900.
Article
PubMed
PubMed Central
Google Scholar
Tofts PS. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging. 1997;7:91–101.
Article
CAS
PubMed
Google Scholar
Benjaminsen IC, Graff BA, Brurberg KG, Rofstad EK. Assessment of tumor blood perfusion by high-resolution dynamic contrast-enhanced MRI: a preclinical study of human melanoma xenografts. Magn Reson Med. 2004;52:269–76.
Article
PubMed
Google Scholar
Rofstad EK, Maseide K. Radiobiological and immunohistochemical assessment of hypoxia in human melanoma xenografts: acute and chronic hypoxia in individual tumours. Int J Radiat Biol. 1999;75:1377–93.
Article
CAS
PubMed
Google Scholar
Weidner N. Intratumor microvessel density as a prognostic factor in cancer. Am J Pathol. 1995;147:9–19.
CAS
PubMed
PubMed Central
Google Scholar
Rofstad EK, Galappathi K, Mathiesen B, Ruud EB. Fluctuating and diffusion-limited hypoxia in hypoxia-induced metastasis. Clin Cancer Res. 2007;13:1971–8.
Article
CAS
PubMed
Google Scholar
Ozerdem U, Hargens AR. A simple method for measuring interstitial fluid pressure in cancer tissues. Microvasc Res. 2005;70:116–20.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hawighorst H, Knapstein PG, Weikel W, Knopp MV, Zuna I, Knof A, et al. Angiogenesis of uterine cervical carcinoma: characterization by pharmacokinetic magnetic resonance parameters and histological microvessel density with correlation to lymphatic involvement. Cancer Res. 1997;57:4777–86.
CAS
PubMed
Google Scholar
Zahra MA, Tan LT, Priest AN, Graves MJ, Arends M, Crawford RA, et al. Semiquantitative and quantitative dynamic contrast-enhanced magnetic resonance imaging measurements predict radiation response in cervix cancer. Int J Radiat Oncol Biol Phys. 2009;74:766–73.
Article
PubMed
Google Scholar
Andersen EK, Hole KH, Lund KV, Sundfor K, Kristensen GB, Lyng H, et al. Pharmacokinetic parameters derived from dynamic contrast enhanced MRI of cervical cancers predict chemoradiotherapy outcome. Radiother Oncol. 2013;107:117–22.
Article
PubMed
Google Scholar
Kallinowski F, Schlenger KH, Runkel S, Kloes M, Stohrer M, Okunieff P, et al. Blood flow, metabolism, cellular microenvironment, and growth rate of human tumor xenografts. Cancer Res. 1989;49:3759–64.
CAS
PubMed
Google Scholar
Aparicio S, Hidalgo M, Kung AL. Examining the utility of patient-derived xenograft mouse models. Nat Rev Cancer. 2015;15:311–6.
Article
CAS
PubMed
Google Scholar
Litjens GJS, Heisen M, Buurman J, Romeny BMtH. Pharmacokinetic models in clinical practice: What model to use for DCE-MRI of the breast? In: 2010 IEEE international symposium on biomedical imaging: from nano to macro. 2010. p. 185–8.
Wegner CS, Gaustad JV, Andersen LM, Simonsen TG, Rofstad EK. Diffusion-weighted and dynamic contrast-enhanced MRI of pancreatic adenocarcinoma xenografts: associations with tumor differentiation and collagen content. J Transl Med. 2016;14:161.
Article
PubMed
PubMed Central
Google Scholar
Brurberg KG, Benjaminsen IC, Dorum LM, Rofstad EK. Fluctuations in tumor blood perfusion assessed by dynamic contrast-enhanced MRI. Magn Reson Med. 2007;58:473–81.
Article
PubMed
Google Scholar
Egeland TA, Gaustad JV, Galappathi K, Rofstad EK. Magnetic resonance imaging of tumor necrosis. Acta Oncol. 2011;50:427–34.
Article
CAS
PubMed
Google Scholar
Hall EJ, Giaccia AJ. Oxygen Effect and Reoxygenation. In: Mitchell CW, editor. Radiobiology for the radiologist. Philadelphia: Lippincott Williams & Wilkins; 2012. p. 86–103.
Google Scholar
Cuenod CA, Balvay D. Perfusion and vascular permeability: basic concepts and measurement in DCE-CT and DCE-MRI. Diagn Interv Imaging. 2013;94:1187–204.
Article
CAS
PubMed
Google Scholar
Dunn T. Oxygen and cancer. N C Med J. 1997;58:140–3.
CAS
PubMed
Google Scholar
Heldin CH, Rubin K, Pietras K, Ostman A. High interstitial fluid pressure—an obstacle in cancer therapy. Nat Rev Cancer. 2004;4:806–13.
Article
CAS
PubMed
Google Scholar
Boucher Y, Jain RK. Microvascular pressure is the principal driving force for interstitial hypertension in solid tumors: implications for vascular collapse. Cancer Res. 1992;52:5110–4.
CAS
PubMed
Google Scholar
Chauhan VP, Stylianopoulos T, Boucher Y, Jain RK. Delivery of molecular and nanoscale medicine to tumors: transport barriers and strategies. Annu Rev Chem Biomol Eng. 2011;2:281–98.
Article
CAS
PubMed
Google Scholar
Egeland TA, Gulliksrud K, Gaustad JV, Mathiesen B, Rofstad EK. Dynamic contrast-enhanced-MRI of tumor hypoxia. Magn Reson Med. 2012;67:519–30.
Article
PubMed
Google Scholar
Ovrebo KM, Hompland T, Mathiesen B, Rofstad EK. Assessment of hypoxia and radiation response in intramuscular experimental tumors by dynamic contrast-enhanced magnetic resonance imaging. Radiother Oncol. 2012;102:429–35.
Article
CAS
PubMed
Google Scholar