DCE-MRI–Derived Measures of Tumor Hypoxia and Interstitial Fluid Pressure Predict Outcomes in Cervical Carcinoma

Characterization of Indeterminate Breast Lesions Based on Pressure Estimates by Noninvasive 3D Contrast-Enhanced Ultrasound

OBJECTIVE

To assess the ability of the pressure gradient between breast lesions and adjacent normal tissue estimated by 3D subharmonic-aided pressure estimation (SHAPE) to characterize indeterminate breast lesions.

METHODS

This prospective study enrolled patients scheduled for ultrasound-guided needle biopsies of a breast lesion. Before the biopsy, 3D SHAPE data were collected from the breast lesion during the infusion of an ultrasound contrast agent (Definity) as well as after clearance of the agent. Direct, invasive pressure measurements in the lesion and adjacent normal tissue were then obtained using an intracompartmental pressure monitoring system (C2DX) before tissue sampling as part of the biopsy procedure. The mean SHAPE gradient and invasive measurement gradient between the lesion and adjacent normal tissue were compared to the biopsy results. The SHAPE gradients were also compared to the invasive pressure gradients.

RESULTS

There were 8 malignant and 13 benign lesions studied. The SHAPE gradients and invasive pressure gradients were significantly different between the benign and malignant lesions (2.86 ± 3.24 vs. -0.03 ± 1.72 a.u.; p = 0.03 and 9.9 ± 8.5 vs. 20.9 ± 8.0 mmHg; p = 0.008, respectively). The area under the curves, specificities, and sensitivities for detecting malignancy by SHAPE gradients and invasive pressure gradients were 0.79 and 0.88, 77% and 92%, and 88% and 50%, respectively. A weak negative correlation was found between the SHAPE and invasive pressure gradients (r = -0.2).

CONCLUSION

The pressure gradient between a breast lesion and adjacent normal tissue estimated by 3D SHAPE shows potential for characterizing indeterminate breast lesions.

Analysis of Magnetic Resonance Imaging Perfusion Parameters for the Identification of Spinal Metastatic Tumors with Rich Blood Supply

PURPOSE

To determine the reliability of dynamic magnetic resonance imaging (MRI) perfusion parameters for the evaluation of blood supply to spinal metastatic tumors.

METHODS

A total of 36 patients with spinal metastasis who underwent dynamic contrast-enhanced magnetic resonance spinal perfusion imaging at Tianjin Hospital from December 2018 to December 2020 were reviewed. Subsequently, the patients underwent corresponding preoperative examination using digital subtraction angiography of the spine at the hospital and were divided into 2 groups accordingly. Differences in dynamic MRI perfusion parameters between the 2 groups were analyzed.

RESULTS

There were statistically significant differences between the 2 groups in the quantitative dynamic contrast-enhanced MRI perfusion parameters vascular permeability and plasma volume, as well as semi-quantitative peak enhancement and blood flow ratio parameters.

CONCLUSIONS

Dynamic MRI perfusion may distinguish spinal metastatic lesions with rich blood supply from those with poor blood supply and may help clinicians identify patients that can benefit from invasive spinal angiography and preoperative embolization. This technique may also provide guidance on decision taking for surgery basing on dynamic MRI perfusion parameters.

The Utility of Contrast-Enhanced Magnetic Resonance Imaging in Uterine Cervical Cancer: A Systematic Review

Correct staging of cervical cancer is essential to establish the best therapeutic procedure and prognosis for the patient. MRI is the best imaging modality for local staging and follow-up. According to the latest ESUR guidelines, T2WI and DWI-MR sequences are fundamental in these settings, and CE-MRI remains optional. This systematic review, according to the PRISMA 2020 checklist, aims to give an overview of the literature regarding the use of contrast in MRI in cervical cancer and provide more specific indications of when it may be helpful. Systematic searches on PubMed and Web Of Science (WOS) were performed, and 97 papers were included; 1 paper was added considering the references of included articles. From our literature review, it emerged that many papers about the use of contrast in cervical cancer are dated, especially about staging and detection of tumor recurrence. We did not find strong evidence suggesting that CE-MRI is helpful in any clinical setting for cervical cancer staging and detection of tumor recurrence. There is growing evidence that perfusion parameters and perfusion-derived radiomics models might have a role as prognostic and predictive biomarkers, but the lack of standardization and validation limits their use in a research setting.

Radiomic Analysis for Pretreatment Prediction of Recurrence Post-Radiotherapy in Cervical Squamous Cell Carcinoma Cancer

Background: The current study aims to predict the recurrence of cervical cancer patients treated with radiotherapy from radiomics features on pretreatment T1- and T2-weighted MR images. Methods: A total of 89 patients were split into model training (63 patients) and model testing (26 patients). The predictors of recurrence were selected using the least absolute shrinkage and selection operator (LASSO) regression. The machine learning used neural network classifiers. Results: Using LASSO analysis of radiomics, we found 25 features from the T1-weighted and 4 features from T2-weighted MR images, respectively. The accuracy was highest with the combination of T1- and T2-weighted MR images. The model performances with T1- or T2-weighted MR images were 86.4% or 89.4% accuracy, 74.9% or 38.1% sensitivity, 81.8% or 72.2% specificity, and 0.89 or 0.69 of the area under the curve (AUC). The model performance with the combination of T1- and T2-weighted MR images was 93.1% accuracy, 81.6% sensitivity, 88.7% specificity, and 0.94 of AUC. Conclusions: The radiomics analysis with T1- and T2-weighted MR images could highly predict the recurrence of cervix cancer after radiotherapy. The variation of the distribution and the difference in the pixel number at the peripheral and the center were important predictors.

Interstitial fluid pressure as an emerging biomarker in solid tumors

The physical microenvironment of cancer is characterized by elevated stiffness and tissue pressure, the main component of which is the interstitial fluid pressure (IFP). Elevated IFP is an established negative predictive and prognostic parameter, directly affecting malignant behavior and therapy response. As such, measurement of the IFP would allow to develop strategies aimed at engineering the physical microenvironment of cancer. Traditionally, IFP measurement required the use of invasive methods. Recent progress in dynamic and functional imaging methods such as dynamic contrast enhanced (DCE) magnetic resonance imaging and elastography, combined with numerical models and simulation, allows to comprehensively assess the biomechanical landscape of cancer, and may help to overcome physical barriers to drug delivery and immune cell infiltration. Here, we provide a comprehensive overview of the origin of elevated IFP, and its role in the malignant phenotype. Also, we review the methods used to measure IFP using invasive and imaging based methods, and highlight remaining obstacles and potential areas of progress in order to implement IFP measurement in clinical practice.

The Role of Imaging Biomarkers to Guide Pharmacological Interventions Targeting Tumor Hypoxia

Hypoxia is a common feature of solid tumors that contributes to angiogenesis, invasiveness, metastasis, altered metabolism and genomic instability. As hypoxia is a major actor in tumor progression and resistance to radiotherapy, chemotherapy and immunotherapy, multiple approaches have emerged to target tumor hypoxia. It includes among others pharmacological interventions designed to alleviate tumor hypoxia at the time of radiation therapy, prodrugs that are selectively activated in hypoxic cells or inhibitors of molecular targets involved in hypoxic cell survival (i.e., hypoxia inducible factors HIFs, PI3K/AKT/mTOR pathway, unfolded protein response). While numerous strategies were successful in pre-clinical models, their translation in the clinical practice has been disappointing so far. This therapeutic failure often results from the absence of appropriate stratification of patients that could benefit from targeted interventions. Companion diagnostics may help at different levels of the research and development, and in matching a patient to a specific intervention targeting hypoxia. In this review, we discuss the relative merits of the existing hypoxia biomarkers, their current status and the challenges for their future validation as companion diagnostics adapted to the nature of the intervention.

Tumor Microenvironment Modifications Recorded With IVIM Perfusion Analysis and DCE-MRI After Neoadjuvant Radiotherapy: A Preclinical Study

PURPOSE

Neoadjuvant radiotherapy (NeoRT) improves tumor local control and facilitates tumor resection in many cancers. Some clinical studies demonstrated that both timing of surgery and RT schedule influence tumor dissemination, and subsequently patient overall survival. Previously, we developed a pre-clinical model demonstrating the impact of NeoRT schedule and timing of surgery on metastatic spreading. We report on the impact of NeoRT on tumor microenvironment by MRI.

METHODS

According to our NeoRT model, MDA-MB 231 cells were implanted in the flank of SCID mice. Tumors were locally irradiated (PXI X-Rad SmART) with 2x5Gy and then surgically removed at different time points after RT. Diffusion-weighted (DW) and Dynamic contrast enhancement (DCE) MRI images were acquired before RT and every 2 days between RT and surgery. IntraVoxel Incoherent Motion (IVIM) analysis was used to obtain information on intravascular diffusion, related to perfusion (F: perfusion factor) and subsequently tumor vessels perfusion. For DCE-MRI, we performed semi-quantitative analyses.

RESULTS

With this experimental model, a significant and transient increase of the perfusion factor F [50% of the basal value (n=16, p<0.005)] was observed on day 6 after irradiation as well as a significant increase of the WashinSlope with DCE-MRI at day 6 (n=13, p<0.05). Using immunohistochemistry, a significant increase of perfused vessels was highlighted, corresponding to the increase of perfusion in MRI at this same time point. Moreover, Tumor surgical resection during this peak of vascularization results in an increase of metastasis burden (n=10, p<0.05).

CONCLUSION

Significant differences in perfusion-related parameters (F and WashinSlope) were observed on day 6 in a neoadjuvant radiotherapy model using SCID mice. These modifications are correlated with an increase of perfused vessels in histological analysis and also with an increase of metastasis spreading after the surgical procedure. This experimental observation could potentially result in a way to personalize treatment, by modulating the time of surgery guided on MRI functional data, especially tumor perfusion.

Normalizing Tumor Vasculature to Reduce Hypoxia, Enhance Perfusion, and Optimize Therapy Uptake

Simple Summary

In order for solid tumors to grow, they need to develop new blood vessels in order to support their increasing metabolic requirements. To facilitate the novel vessel formation, the tumor initiates an aggressive pro-angiogenic program. As a result of the aggressive angiogenesis, blood vessels form very rapidly and are often malformed and dysfunctional. There is a reduction in perfusion to the tumor, and often the tumors exhibit significant areas of tumor hypoxia. This review paper discusses the pro-tumorigenic environment induced by tumor hypoxia and how this can be targeted through normalization of the tumor vasculature. Here, we review tumor angiogenesis, the development of a hypoxic phenotype, and how this contributes to sustained tumorigenesis and resistance to therapy. We further discuss the potential of vascular normalization to reduce tumor hypoxia and facilitate uptake and efficacy of a variety of therapies.

Abstract

A basic requirement of tumorigenesis is the development of a vascular network to support the metabolic requirements of tumor growth and metastasis. Tumor vascular formation is regulated by a balance between promoters and inhibitors of angiogenesis. Typically, the pro-angiogenic environment created by the tumor is extremely aggressive, resulting in the rapid vessel formation with abnormal, dysfunctional morphology. The altered morphology and function of tumor blood and lymphatic vessels has numerous implications including poor perfusion, tissue hypoxia, and reduced therapy uptake. Targeting tumor angiogenesis as a therapeutic approach has been pursued in a host of different cancers. Although some preclinical success was seen, there has been a general lack of clinical success with traditional anti-angiogenic therapeutics as single agents. Typically, following anti-angiogenic therapy, there is remodeling of the tumor microenvironment and widespread tumor hypoxia, which is associated with development of therapy resistance. A more comprehensive understanding of the biology of tumor angiogenesis and insights into new clinical approaches, including combinations with immunotherapy, are needed to advance vascular targeting as a therapeutic area.

Imaging to assist fertility-sparing surgery

Cytological screening and human papilloma virus testing has led to diagnosis of cervical cancer in young women at an earlier stage. Defining the full extent of the disease within the cervix with imaging aids the decision on feasibility of fertility-sparing surgical options, such as extended cone biopsy or trachelectomy. High spatial resolution images with maximal contrast between tumour and surrounding background are achieved with T2-weighted and diffusion-weighted (DW) magnetic resonance imaging (MRI) obtained using an endovaginal receiver coil. Tumour size and volume demonstrated in this way correlates between observers and with histology and differences between MRI and histology estimates of normal endocervical canal length are not significant. For planning fertility-sparing surgery, this imaging technique facilitates the best oncological outcome while minimising subsequent obstetric risks. Parametrial invasion may be assessed on large field of view T2-weighted MRI. The fat content of the parametrium limits the utility of DW imaging in this context, because fat typically shows diffusion restriction. The use of contrast-enhanced MRI for assessing the parametrium does not provide additional benefits to the T2-weighted images and the need for an extrinsic contrast agent merely adds additional complexity and cost. For nodal assessment, 18fluorodeoxyglucose positron emission tomography-computerised tomography (18FDG PET-CT) remains the gold standard.

Computational Modeling of Interstitial Fluid Pressure and Velocity in Head and Neck Cancer Based on Dynamic Contrast-Enhanced Magnetic Resonance Imaging: Feasibility Analysis

We developed and tested the feasibility of computational fluid modeling (CFM) based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for quantitative estimation of interstitial fluid pressure (IFP) and velocity (IFV) in patients with head and neck (HN) cancer with locoregional lymph node metastases. Twenty-two patients with HN cancer, with 38 lymph nodes, underwent pretreatment standard MRI, including DCE-MRI, on a 3-Tesla scanner. CFM simulation was performed with the finite element method in COMSOL Multiphysics software. The model consisted of a partial differential equation (PDE) module to generate 3D parametric IFP and IFV maps, using the Darcy equation and Ktrans values (min⁻¹, estimated from the extended Tofts model) to reflect fluid influx into tissue from the capillary microvasculature. The Spearman correlation (ρ) was calculated between total tumor volumes and CFM estimates of mean tumor IFP and IFV. CFM-estimated tumor IFP and IFV mean ± standard deviation for the neck nodal metastases were 1.73 ± 0.39 (kPa) and 1.82 ± 0.9 × (10⁻⁷ m/s), respectively. High IFP estimates corresponds to very low IFV throughout the tumor core, but IFV rises rapidly near the tumor boundary where the drop in IFP is precipitous. A significant correlation was found between pretreatment total tumor volume and CFM estimates of mean tumor IFP (ρ = 0.50, P = 0.004). Future studies can validate these initial findings in larger patients with HN cancer cohorts using CFM of the tumor in concert with DCE characterization, which holds promise in radiation oncology and drug-therapy clinical trials.

A multicompartment model for intratumor tissue-specific analysis of DCE-MRI using non-negative matrix factorization

PURPOSE

A pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data is subject to inaccuracy and instability partly owing to the partial volume effect (PVE). We proposed a new multicompartment model for a tissue-specific pharmacokinetic analysis in DCE-MRI data to solve the PVE problem and to provide better kinetic parameter maps.

METHODS

We introduced an independent parameter named fractional volumes of tissue compartments in each DCE-MRI pixel to construct a new linear separable multicompartment model, which simultaneously estimates the pixel-wise time-concentration curves and fractional volumes without the need of the pure-pixel assumption. This simplified convex optimization model was solved using a special type of non-negative matrix factorization (NMF) algorithm called the minimum-volume constraint NMF (MVC-NMF).

RESULTS

To test the model, synthetic datasets were established based on the general pharmacokinetic parameters. On well-designed synthetic data, the proposed model reached lower bias and lower root mean square fitting error compared to the state-of-the-art algorithm in different noise levels. In addition, the real dataset from QIN-BREAST-DCE-MRI was analyzed, and we observed an improved pharmacokinetic parameter estimation to distinguish the treatment response to chemotherapy applied to breast cancer.

CONCLUSION

Our model improved the accuracy and stability of the tissue-specific estimation of the fractional volumes and kinetic parameters in DCE-MRI data, and improved the robustness to noise, providing more accurate kinetics for more precise prognosis and therapeutic response evaluation using DCE-MRI.

Targeting self-assembled F127-peptide polymer with pH sensitivity for release of anticancer drugs

The treatment of breast cancer mainly relies on chemotherapy drugs, which present significant side effects.

Computational Modeling of Interstitial Fluid Pressure and Velocity in Non-small Cell Lung Cancer Brain Metastases Treated With Stereotactic Radiosurgery

Background: Early imaging-based treatment response assessment of brain metastases following stereotactic radiosurgery (SRS) remains challenging. The aim of this study is to determine whether early (within 12 weeks) intratumoral changes in interstitial fluid pressure (IFP) and velocity (IFV) estimated from computational fluid modeling (CFM) using dynamic contrast-enhanced (DCE) MRI can predict long-term outcomes of lung cancer brain metastases (LCBMs) treated with SRS.

Methods: Pre- and post-treatment T₁-weighted DCE-MRI data were obtained in 41 patients treated with SRS for intact LCBMs. The imaging response was assessed using RANO-BM criteria. For each lesion, extravasation of contrast agent measured from Extended Tofts pharmacokinetic Model (volume transfer constant, K^trans) was incorporated into a computational fluid model to estimate tumor IFP and IFV. Estimates of mean IFP and IFV and heterogeneity (skewness and kurtosis) were calculated for each lesion from pre- and post-SRS imaging. The Wilcoxon rank-sum test was utilized to assess for significant differences in IFP, IFV, and IFP/IFV change (Δ) between response groups.

Results: Fifty-three lesions from 41 patients were included. Median follow-up time after SRS was 11 months. The objective response (OR) rate (partial or complete response) was 79%, with 21% demonstrating stable disease (SD) or progressive disease (PD). There were significant response group differences for multiple posttreatment and Δ CFM parameters: post-SRS IFP skewness (mean −0.405 vs. −0.691, p = 0.022), IFP kurtosis (mean 2.88 vs. 3.51, p = 0.024), and IFV mean (5.75e-09 vs. 4.19e-09 m/s, p = 0.027); and Δ IFP kurtosis (mean −2.26 vs. −0.0156, p = 0.017) and IFV mean (1.91e-09 vs. 2.38e-10 m/s, p = 0.013). Posttreatment and Δ thresholds predicted non-OR with high sensitivity (sens): post-SRS IFP skewness (−0.432, sens 84%), kurtosis (2.89, sens 84%), and IFV mean (4.93e-09 m/s, sens 79%); and Δ IFP kurtosis (−0.469, sens 74%) and IFV mean (9.90e-10 m/s, sens 74%).

Conclusions: Objective response was associated with lower post-treatment tumor heterogeneity, as represented by reductions in IFP skewness and kurtosis. These results suggest that early post-treatment assessment of IFP and IFV can be used to predict long-term response of lung cancer brain metastases to SRS, allowing a timelier treatment modification.

Towards noninvasive estimation of tumour pressure by utilising MR elastography and nonlinear biomechanical models: a simulation and phantom study

The solid and fluid pressures of tumours are often elevated relative to surrounding tissue. This increased pressure is known to correlate with decreased treatment efficacy and potentially with tumour aggressiveness and therefore, accurate noninvasive estimates of tumour pressure would be of great value. We present a proof-of-concept method to infer the total tumour pressure, that is the sum of the fluid and solid parts, by examining stiffness in the peritumoural tissue with MR elastography and utilising nonlinear biomechanical models. The pressure from the tumour deforms the surrounding tissue leading to changes in stiffness. Understanding and accounting for these biases in stiffness has the potential to enable estimation of total tumour pressure. Simulations are used to validate the method with varying pressure levels, tumour shape, tumour size, and noise levels. Results show excellent matching in low noise cases and still correlate well with higher noise. Percent error remains near or below 10% for higher pressures in all noise level cases. Reconstructed pressures were also calculated from experiments with a catheter balloon embedded in a plastisol phantom at multiple inflation levels. Here the reconstructed pressures generally match the increases in pressure measured during the experiments. Percent errors between average reconstructed and measured pressures at four inflation states are 17.9%, 52%, 23.2%, and 0.9%. Future work will apply this method to in vivo data, potentially providing an important biomarker for cancer diagnosis and treatment.

Intratumor Heterogeneity in Interstitial Fluid Pressure in Cervical and Pancreatic Carcinoma Xenografts

Preclinical studies have suggested that interstitial fluid pressure (IFP) is uniformly elevated in the central region of tumors, whereas clinical studies have revealed that IFP may vary among different measurement sites in the tumor center. IFP measurements are technically difficult, and it has been claimed that the intratumor heterogeneity in IFP reported for human tumors is due to technical problems. The main purpose of this study was to determine conclusively whether IFP may be heterogeneously elevated in the central tumor region, and if so, to reveal possible mechanisms and possible consequences. Tumors of two xenograft models were included in the study: HL-16 cervical carcinoma and Panc-1 pancreatic carcinoma. IFP was measured with Millar SPC 320 catheters in two positions in each tumor and related to tumor histology or the metastatic status of the host mouse. Some tumors of both models showed significant intratumor heterogeneity in IFP, and this heterogeneity was associated with a compartmentalized histological appearance (i.e., the tissue was divided into compartments separated by thick connective tissue bands) in HL-16 tumors and with a dense collagen-I-rich extracellular matrix in Panc-1 tumors, suggesting that these connective tissue structures prevented efficient interstitial convection. Furthermore, some tumors of both models developed lymph node metastases, and of the two IFP values measured in each tumor, only the higher value was significantly higher in metastatic than in non-metastatic tumors, suggesting that metastatic propensity was determined by the tumor region having the highest IFP.

How Tumor Cells Can Make Use of Interstitial Fluid Flow in a Strategy for Metastasis

Introduction

The phenomenon of lymph node metastasis has been known for a long time. However, the underlying mechanism by which malignant tumor cells are able to break loose from the primary tumor site remains unclear. In particular, two competing fluid sensitive migration mechanisms have been reported in the experimental literature: (i) autologous chemotaxis (Shields et al. in Cancer Cell 11:526-538, 2007) which gives rise to downstream migration; (ii) an integrin-mediated and strain-induced upstream mechanism (Polacheck et al. in PNAS 108:11115-11120, 2011). How can these two competing mechanisms be used as a means for metastatic behavior in a realistic tumor setting? Excessive fluid flow is typically produced from leaky intratumoral blood vessels and collected by lymphatics in the peritumoral region giving rise to a heterogeneous fluid velocity field and a corresponding heterogeneous cell migration behavior, quite different from the experimental setup.

Method

In order to shed light on this issue there is a need for tools which allow one to extrapolate the observed single cell behavior in a homogeneous microfluidic environment to a more realistic, higher-dimensional tumor setting. Here we explore this issue by using a computational multiphase model. The model has been trained with data from the experimental results mentioned above which essentially reflect one-dimensional behavior. We extend the model to an envisioned idealized two-dimensional tumor setting.

Result

A main observation from the simulation is that the autologous chemotaxis migration mechanism, which triggers tumor cells to go with the flow in the direction of lymphatics, becomes much more aggressive and effective as a means for metastasis in the presence of realistic IF flow. This is because the outwardly directed IF flow generates upstream cell migration that possibly empowers small clusters of tumor cells to break loose from the primary tumor periphery. Without this upstream stress-mediated migration, autologous chemotaxis is inclined to move cells at the rim of the tumor in a homogeneous and collective, but space-demanding style. In contrast, inclusion of realistic IF flow generates upstream migration that allows two different aspects to be synthesized: maintain the coherency and solidity of the the primary tumor and at the same time cleave the outgoing waves of tumor cells into small clusters at the front that can move collectively in a more specific direction.

DCE-MRI and Quantitative Histology Reveal Enhanced Vessel Maturation but Impaired Perfusion and Increased Hypoxia in Bevacizumab-Treated Cervical Carcinoma

PURPOSE

This study had a dual purpose: to investigate (1) whether bevacizumab can change the microvasculature and oxygenation of cervical carcinomas and (2) whether any changes can be detected with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

METHODS AND MATERIALS

Two patient-derived xenograft models of cervical cancer (BK-12 and HL-16) were included in the study. Immunostained histologic preparations from untreated and bevacizumab-treated tumors were analyzed with respect to microvascular density, vessel pericyte coverage, and tumor hypoxia using CD31, α-SMA, and pimonidazole as markers, respectively. DCE-MRI was performed at 7.05 T, and parametric images of K^trans and v_e were derived from the data using the Tofts pharmacokinetic model.

RESULTS

The tumors of both models showed decreased microvascular density, increased vessel pericyte coverage, and increased vessel maturation after bevacizumab treatment. Bevacizumab-treated tumors were more hypoxic and had lower K^trans values than untreated tumors in the BK-12 model, whereas bevacizumab-treated and untreated HL-16 tumors had similar hypoxic fractions and similar K^trans values. Significant correlations were found between median K^trans and hypoxic fraction, and the data for untreated and bevacizumab-treated tumors were well fitted by the same curve in both tumor models.

CONCLUSIONS

Bevacizumab-treated tumors show less abnormal microvessels than untreated tumors do, but because of treatment-induced vessel pruning, the overall function of the microvasculature might be impaired after bevacizumab treatment, resulting in increased tumor hypoxia. DCE-MRI has great potential for monitoring bevacizumab-induced changes in tumor hypoxia in cervical carcinoma.