Inflammatory Breast Cancer: Dynamic Contrast-enhanced MR in Patients Receiving Bevacizumab—Initial Experience

Transfer Learning Approach to Vascular Permeability Changes in Brain Metastasis Post-Whole-Brain Radiotherapy

The purpose of this study is to further validate the utility of our previously developed CNN in an alternative small animal model of BM through transfer learning. Unlike the glioma model, the BM mouse model develops multifocal intracranial metastases, including both contrast enhancing and non-enhancing lesions on DCE MRI, thus serving as an excellent brain tumor model to study tumor vascular permeability. Here, we conducted transfer learning by transferring the previously trained GBM CNN to DCE MRI datasets of BM mice. The CNN was re-trained to learn about the relationship between BM DCE images and target permeability maps extracted from the Extended Tofts Model (ETM). The transferred network was found to accurately predict BM permeability and presented with excellent spatial correlation with the target ETM PK maps. The CNN model was further tested in another cohort of BM mice treated with WBRT to assess vascular permeability changes induced via radiotherapy. The CNN detected significantly increased permeability parameter Ktrans in WBRT-treated tumors (p < 0.01), which was in good agreement with the target ETM PK maps. In conclusion, the proposed CNN can serve as an efficient and accurate tool for characterizing vascular permeability and treatment responses in small animal brain tumor models.

Molecular and functional imaging in cancer-targeted therapy: current applications and future directions

Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways vital to carcinogenesis and tumor growth rather than harming all rapidly dividing cells as in cytotoxic chemotherapy. The Response Evaluation Criteria in Solid Tumor (RECIST) system has been used to assess tumor response to therapy via changes in the size of target lesions as measured by calipers, conventional anatomically based imaging modalities such as computed tomography (CT), and magnetic resonance imaging (MRI), and other imaging methods. However, RECIST is sometimes inaccurate in assessing the efficacy of targeted therapy drugs because of the poor correlation between tumor size and treatment-induced tumor necrosis or shrinkage. This approach might also result in delayed identification of response when the therapy does confer a reduction in tumor size. Innovative molecular imaging techniques have rapidly gained importance in the dawning era of targeted therapy as they can visualize, characterize, and quantify biological processes at the cellular, subcellular, or even molecular level rather than at the anatomical level. This review summarizes different targeted cell signaling pathways, various molecular imaging techniques, and developed probes. Moreover, the application of molecular imaging for evaluating treatment response and related clinical outcome is also systematically outlined. In the future, more attention should be paid to promoting the clinical translation of molecular imaging in evaluating the sensitivity to targeted therapy with biocompatible probes. In particular, multimodal imaging technologies incorporating advanced artificial intelligence should be developed to comprehensively and accurately assess cancer-targeted therapy, in addition to RECIST-based methods.

Progress for Immunotherapy in Inflammatory Breast Cancer and Emerging Barriers to Therapeutic Efficacy

Simple Summary

Despite recent advances in the treatment of other breast cancer subtypes, inflammatory breast cancer (IBC) remains a significant clinical challenge, with an overall 5-year survival rate of 39%. Though immunotherapy has shown remarkable efficacy in other difficult-to-treat cancers, such approaches have yet to show substantial therapeutic efficacy in IBC. Here, we summarize the known immune composition of IBC tumors, as well as past and present efforts to advance immunotherapy in the treatment of IBC.

Abstract

Inflammatory breast cancer (IBC) is a rare and aggressive subtype of breast cancer that carries a particularly poor prognosis. Despite the efficacy of immunotherapy in other difficult to treat forms of breast cancer, progress for immunotherapy in IBC has been difficult. Though immunotherapy has been under clinical investigation in IBC since the 1970s, few approaches have shown significant therapeutic efficacy, and no immunotherapy regimens are currently used in the treatment of IBC. Here, we provide a comprehensive summary of what is known about the immune composition of IBC tumors, clinical and basic science evidence describing the role for immune checkpoints such as PD-L1 in IBC pathobiology, as well as past and present attempts to advance ICIs in the treatment of IBC.

An update on biomarkers of potential benefit with bevacizumab for breast cancer treatment: Do we make progress?

As the first monoclonal antibody against vascular endothelial growth factor (VEGF), bevacizumab (BEV) is a definitely controversial antiangiogenic therapy in breast cancer. The initial excitement over improvements in progression-free survival (PFS) with BEV was tempered by an absence of overall survival (OS) benefit and serious adverse effects. Missing targeted population urged us to identify the predictive biomarkers for BEV efficacy. In this review we focus on the research in breast cancer and provide recent investigations on clinical, radiological, molecular and gene profiling markers of BEV efficacy, including the new results from randomized phase III clinical trials evaluating the efficacy of BEV in combination with comprehensive biomarker analyses. Current evidences indicate some predictive values for genetic variants, molecular imaging, VEGF pathway factors or associated factors in peripheral blood and gene profiling. The current challenge is to validate those potential biomarkers and implement them into clinical practice.

Quantitative dynamic contrast-enhanced MR imaging for differentiating benign, borderline, and malignant ovarian tumors

PURPOSE

This study aimed to investigate the diagnostic performance of quantitative DCE-MRI for characterizing ovarian tumors.

METHODS

We prospectively assessed the differences of quantitative DCE-MRI parameters (K^trans, k_ep, and v_e) among 15 benign, 28 borderline, and 66 malignant ovarian tumors; and between type I (n = 28) and type II (n = 29) of epithelial ovarian carcinomas (EOCs). DCE-MRI data were analyzed using whole solid tumor volume region of interest (ROI) method, and quantitative parameters were calculated based on a modified Tofts model. The non-parametric Kruskal-Wallis test, Mann-Whitney U test, Pearson's chi-square test, intraclass correlation coefficient (ICC), variance test, and receiver operating characteristic curves (ROC) were used for statistical analysis.

RESULTS

The largest K^trans and k_ep values were observed in ovarian malignant tumors, followed by borderline and benign tumors (all P < 0.001). K_ep was the better parameter for differentiating benign tumors from borderline and malignant tumors, with a sensitivity of 89.3% and 95.5%, a specificity of 86.7% and 100%, an accuracy of 88.4% and 96.3%, and an area under the curve (AUC) of 0.94 and 0.992, respectively, whereas K^trans was better for differentiating borderline from malignant tumors with a sensitivity of 60.7%, a specificity of 78.8%, an accuracy of 73.4%, and an AUC of 0.743. In addition, a combination with k_ep could further improve the sensitivity to 78.9%. The median K^trans and k_ep values were significantly higher in type II than in type I EOCs.

CONCLUSION

DCE-MRI with volume quantification is a technically feasible method, and can be used for the differentiation of ovarian tumors and for discriminating between type I and type II EOCs.

Diagnostic investigation of breast magnetic resonance imaging in malignant and benign mass lesions

INTRODUCTION

Breast magnetic resonance imaging (BMRI) has been identified as a valuable modality in the diagnosis of breast cancer and monitoring the response to chemotherapy. The aim of this study was to evaluate the relative importance of different descriptors of breast masses in contrast-enhanced breast MRI.

MATERIAL AND METHODS

In a database of pathologically proven breast lesions, in total 433 masses in 312 patients detected by contrast-enhanced breast MRI were selected. All images were assessed according to the MRI BI-RADS lexicon and those with significant positive MRI findings (BI-RADS categories 3, 4, 5) were enrolled in the study.

RESULTS

Mean age of patients was 45.09 ±10.5 years. The most frequent BI-RADS score was 4 (60.7%), followed by 3 (27%). Among the morphologic descriptors of the enhancing masses, the findings most strongly associated with malignancy included spiculated margin (60.6%) and irregular shape (38%). Considering the dynamic descriptors, a wash-out pattern in the time-intensity curve was the most powerful finding associated with malignancy (27.9%). Among all breast MRI descriptors, the best odds ratio (OR) in association with malignancy was noted for speculated margin (OR = 10.2) followed by wash-out or plateau curves (OR = 6.1), size greater than 1 cm (OR = 4.3) and irregular shape (OR = 3.1).

CONCLUSIONS

It seems that morphologic descriptors of MRI BI-RADS for enhancing masses are quite specific, while dynamic descriptors of the masses are highly sensitive. Appropriate consideration and combination of different BI-RADS findings could help in better characterization of enhancing masses on breast MRI, lowering the rate of false positive reports and avoiding unnecessary biopsies.

DCE-MRI and parametric imaging in monitoring response to neoadjuvant chemotherapy in breast carcinoma: a preliminary report

Purpose

Neoadjuvant chemotherapy is recommended in patients with locally advanced breast cancer. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables evaluation of the tumour neovasculature that occurs prior to any volume change, which helps identify early treatment failures and allows prompt implementation of second-line therapy.

Material and methods

We conducted a prospective study in 14 patients with histopathologically proven breast cancer. DCE-MRI data were acquired using multisection, T1-weighted, 3D vibe sequences with fat suppression before, during, and after IV bolus injection (0.1 mmol/kg body weight, Gadoversetamide, Optimark). Post-processing of dynamic contrast perfusion data was done with the vendor’s Tissue 4D software to generate various dynamic contrast parameters, i.e. Ktrans, Kep, Ve, initial area under the time signal curve (IAUC), apparent diffusion coefficient (ADC), and enhancement curve. Patients underwent MRI examinations at baseline, and then after two cycles, and finally at completion of chemotherapy.

Results

Based on Sataloff criteria for pathological responses, four patients out of 14 were responders, and 10 were non-responders. At the 2nd MRI examination, IAUC was significantly smaller in responders than in non-responders (p = 0.023). When the results of the first and second MRI examinations were compared, Kep decreased from baseline to the second MRI (p = 0.03) in non-responders and in responders (p = 0.04). This change was statistically significant in both groups. The ADC values increased significantly in responders from baseline to the third MRI (p = 0.012).

Conclusions

In our study, IAUC and ADC were the only parameters that reliably differentiated responders from non-responders after two and three cycles of chemotherapy.

Linearization improves the repeatability of quantitative dynamic contrast-enhanced MRI

PURPOSE

The purpose of this study was to compare the repeatabilities of the linear and nonlinear Tofts and reference region models (RRM) for dynamic contrast-enhanced MRI (DCE-MRI).

MATERIALS AND METHODS

Simulated and experimental DCE-MRI data from 12 rats with a flank tumor of C6 glioma acquired over three consecutive days were analyzed using four quantitative and semi-quantitative DCE-MRI metrics. The quantitative methods used were: 1) linear Tofts model (LTM), 2) non-linear Tofts model (NTM), 3) linear RRM (LRRM), and 4) non-linear RRM (NRRM). The following semi-quantitative metrics were used: 1) maximum enhancement ratio (MER), 2) time to peak (TTP), 3) initial area under the curve (iauc64), and 4) slope. LTM and NTM were used to estimate K^trans, while LRRM and NRRM were used to estimate K^trans relative to muscle (R^Ktrans). Repeatability was assessed by calculating the within-subject coefficient of variation (wSCV) and the percent intra-subject variation (iSV) determined with the Gage R&R analysis.

RESULTS

The iSV for R^Ktrans using LRRM was two-fold lower compared to NRRM at all simulated and experimental conditions. A similar trend was observed for the Tofts model, where LTM was at least 50% more repeatable than the NTM under all experimental and simulated conditions. The semi-quantitative metrics iauc64 and MER were as equally repeatable as K^trans and R^Ktrans estimated by LTM and LRRM respectively. The iSV for iauc64 and MER were significantly lower than the iSV for slope and TTP.

CONCLUSION

In simulations and experimental results, linearization improves the repeatability of quantitative DCE-MRI by at least 30%, making it as repeatable as semi-quantitative metrics.

Simultaneous measurement of T1 /B1 and pharmacokinetic model parameters using active contrast encoding (ACE)-MRI

The aim of this study was to assess the feasibility of combining dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) with the measurement of the radiofrequency (RF) transmit field B₁ and pre-contrast longitudinal relaxation time T₁₀ . A novel approach has been proposed to simultaneously estimate B₁ and T₁₀ from a modified DCE-MRI scan that actively encodes the washout phase of the curve with different amounts of T₁ and B₁ weighting using multiple flip angles and repetition times, hence referred to as active contrast encoding (ACE)-MRI. ACE-MRI aims to simultaneously measure B₁ and T₁₀ , together with contrast kinetic parameters, such as the transfer constant K^trans , interstitial space volume fraction v_e and vascular space volume fraction v_p . The proposed method was tested using numerical simulations and in vivo studies with mouse models of breast cancer implanted in the flank and mammary fat pad, and glioma in the brain. In the numerical simulation study with a signal-to-noise ratio of 10, both B₁ and T₁₀ were estimated accurately with errors of 5.1 ± 3.5% and 12.3 ± 8.8% and coefficients of variation (CV) of 14.9 ± 8.6% and 15.0 ± 5.0%, respectively. Using the same ACE-MRI data, the kinetic parameters K^trans , v_e and v_p were also estimated with errors of 14.2 ± 8.3% (CV = 13.5 ± 4.6%), 14.7 ± 9.9% (CV = 13.3 ± 4.5%) and 14.0 ± 9.3% (CV = 14.0 ± 4.5%), respectively. For the in vivo tumor data from 11 mice, voxel-wise comparisons between ACE-MRI and DCE-MRI methods showed that the mean differences for the five parameters were as follows: ΔK^trans  = 0.006 (/min), Δv_e  = 0.016, Δv_p  = 0.000, ΔB₁  = -0.014 and ΔT₁  = -0.085 (s), which suggests a good agreement between the two methods. When compared with separately measured B₁ and T₁₀ , and DCE-MRI estimated kinetic parameters as a reference, the mean relative errors of ACE-MRI estimation were B₁  = -0.3%, T₁₀  = -8.5%, K^trans  = 11.4%, v_e  = 14.5% and v_p  = 4.5%. This proof-of-concept study demonstrates that the proposed ACE-MRI method can be used to estimate B₁ and T₁₀ , together with contrast kinetic model parameters.

Quantitative magnetic resonance imaging biomarkers in oncological clinical trials: Current techniques and standardization challenges

Radiological imaging plays an important role in oncological trials to provide imaging biomarkers for disease staging, stratifying patients, defining dose setting, and evaluating the safety and efficacy of new candidate drugs and innovative treatment. This paper reviews the techniques of most commonly used quantitative magnetic resonance imaging (qMRI) biomarkers (dynamic contrast enhanced, dynamic susceptibility contrast, and diffusion weighted imaging) and their applications in oncological trials. Challenges of incorporating qMRI biomarkers in oncological trials are discussed including understanding biological mechanisms revealed by MRI biomarkers, consideration of rigorous trial design and standardized implementation of qMRI protocols.

Liver DCE-MRI Registration in Manifold Space Based on Robust Principal Component Analysis

A technical challenge in the registration of dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging in the liver is intensity variations caused by contrast agents. Such variations lead to the failure of the traditional intensity-based registration method. To address this problem, a manifold-based registration framework for liver DCE-MR time series is proposed. We assume that liver DCE-MR time series are located on a low-dimensional manifold and determine intrinsic similarities between frames. Based on the obtained manifold, the large deformation of two dissimilar images can be decomposed into a series of small deformations between adjacent images on the manifold through gradual deformation of each frame to the template image along the geodesic path. Furthermore, manifold construction is important in automating the selection of the template image, which is an approximation of the geodesic mean. Robust principal component analysis is performed to separate motion components from intensity changes induced by contrast agents; the components caused by motion are used to guide registration in eliminating the effect of contrast enhancement. Visual inspection and quantitative assessment are further performed on clinical dataset registration. Experiments show that the proposed method effectively reduces movements while preserving the topology of contrast-enhancing structures and provides improved registration performance.

Dynamic contrast enhanced MR imaging for evaluation of angiogenesis of hepatocellular nodules in liver cirrhosis in N-nitrosodiethylamine induced rat model

PURPOSE

To investigate whether dynamic contrast -enhanced MRI (DCE-MRI) can distinguish the type of liver nodules in a rat model with N-nitrosodiethylamine- induced cirrhosis.

METHODS

Liver nodules in cirrhosis were induced in 60 male Wistar rats via 0.01 % N-nitrosodiethylamine in the drinking water for 35-100 days. The nodules were divided into three groups: regenerative nodule (RN), dysplastic nodule (DN), and hepatocellular carcinoma (HCC). DCE-MRI was performed, and parameters including transfer constant (K^trans), rate constant (K_ep), extravascular extracellular space volume fraction (V_e), and initial area under the contrast concentration versus time curve (iAUC) were measured and compared.

RESULTS

The highest K^trans and iAUC values were seen in HCC, followed by DN and RN (all P < 0.05). The area under the receiver operating characteristic curve (AUROC) for DN and HCC were 0.738 and 0.728 for K^trans and iAUC, respectively. The AUROC for HCC were 0.850 and 0.840 for K^trans and iAUC, respectively. Ordinal logistic regression analysis showed that K^trans had a high goodness of fit (0.970, 95 % confidence interval, 13.751-24.958).

CONCLUSION

DCE-MRI is a promising method to differentiate of liver nodules. Elevated K^trans suggested that the nodules may be transformed into HCC.

KEY POINTS

• DCE-MRI is promising for differentiating among RN, DN, and HCC • K ^trans and iAUC positively correlated with malignancy degree of liver nodules • Elevated K ^trans suggests that the nodules may be transformed into HCC.

Synergistic Effect of Anti-Angiogenic and Radiation Therapy: Quantitative Evaluation with Dynamic Contrast Enhanced MR Imaging

Purpose

We assessed the effects of anti-angiogenic therapy (AAT) on radiation therapy (RT), evaluating the tumor growth and perfusion patterns on dynamic contrast enhanced MR (DCE-MR) images.

Methods

Thirteen nude mice with heterotopic xenograft cancer of human lung cancer cell line were used. To observe the interval change of the tumor size and demonstrate the time-signal intensity enhancement curve of the tumor, the mice were subdivided into four groups: control (n = 2), AAT (n = 2), RT (n = 5), and combined therapy (AART, n = 4). DCE-MR images were taken four weeks after treatment. Perfusion parameters were obtained based on the Brix model. To compare the interval size changes in the RT group with those in the AART group, repeated measures ANOVA was used. Perfusion parameters in both the RT and AART groups were compared using a Mann-Whitney U test.

Results

Tumor growth was more suppressed in AART group than in the other groups. Control group showed the rapid wash-in and wash-out pattern on DCE-MR images. In contrast to RT group with delayed and prolonged enhancement, both AAT and AART groups showed the rapid wash-in and plateau pattern. The signal intensity in the plateau/time to peak enhancement (P<0.016) and the maximum enhancement ratio (P<0.016) of AART group were higher than those of RT group.

Conclusions

AART showed synergistic effects in anticancer treatment. The pattern of the time-intensity curve on the DCE-MR images in each group implies that AAT might help maintain the perfusion in the cancer of AART group.

Dynamic contrast-enhanced MRI for oncology drug development

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising tool for evaluating tumor vascularity, as it can provide vasculature-derived, functional, and quantitative parameters. To implement DCE-MRI parameters as biomarkers for monitoring the effect of antiangiogenic or vascular-disrupting treatment, two crucial elements of surrogate endpoint, ie, validation and qualification, should be satisfied. Although early studies have shown the accuracy and reliability of DCE-MRI parameters for evaluating treatment-driven vascular alterations, there have been an increasing number of studies demonstrating the limitations of DCE-MRI parameters as surrogate endpoints. Therefore, in order to improve the application of DCE-MRI parameters in drug development, it is necessary to establish a standardized evaluation method and to determine the correct therapeutics-oriented meaning of individual DCE-MRI parameter. In this regard, this article describes the biophysical background and data acquisition/analysis techniques of DCE-MRI while focusing on the validation and qualification issues. Specifically, the causes of disagreement and confusion encountered in the preclinical and clinical trials using DCE-MRI are presented in detail. Finally, considering these limitations, we present potential strategies to optimize implementation of DCE-MRI. J. Magn. Reson. Imaging 2016;44:251-264.

Analysis of the changes induced by bevacizumab using a high temporal resolution DCE-MRI as prognostic factors for response to further neoadjuvant chemotherapy

BACKGROUND

Antiangiogenic drugs are being used in the treatment of locally advanced breast cancer. The effect of these drugs can be monitorized using high temporal resolution dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

PURPOSE

To evaluate changes in tumor microvasculature induced by bevacizumab and the usefulness of these changes predicting response to further neoadjuvant therapy.

MATERIAL AND METHODS

Seventy patients with locally advanced breast cancers were treated with one cycle of bevacizumab followed by neoadjuvant therapy, combining bevacizumab and cytotoxic chemotherapy. Two DCE-MRI were performed before and after bevacizumab. Changes in tumoral volume, pharmacodynamic curves, and pharmacokinetic variables (K(trans), Kep, Ve, AUC90) in a ROI (ROI 1) encompassing the entire tumor and in another ROI (ROI 2) in the area of higher values of K(trans) were analyzed. Correlations with pathological response were made: parametrical and non-parametrical statistical analysis and ROC curves were used; a P < 0.05 was considered significant.

RESULTS

Significant changes in tumoral volume (-4%), pharmacodynamic curves, and pharmacokinetic variables in ROI 1 K(trans) (-45%), Kep (-38%), Ve (-11%), and AUC90 (-44%) and ROI 2 K(trans) (-43%), Kep (-39%), Ve (-5%), and AUC90 (-45%) were observed after bevacizumab (P < 0.05). The effect of bevacizumab was not different between responders and non-responders (P > 0.05), and these changes could not predict response to further neoadjuvant therapy.

CONCLUSION

Bevacizumab induces remarkable tumoral volume, pharmacodynamics, and pharmacokinetic changes. However, these changes could not be used as early predictors for response to further neoadjuvant therapy.

Optimization of arterial spin labeling MRI for quantitative tumor perfusion in a mouse xenograft model

Perfusion is an important biomarker of tissue function and has been associated with tumor pathophysiology such as angiogenesis and hypoxia. Arterial spin labeling (ASL) MRI allows noninvasive and quantitative imaging of perfusion; however, the application in mouse xenograft tumor models has been challenging due to the low sensitivity and high perfusion heterogeneity. In this study, flow-sensitive alternating inversion recovery (FAIR) ASL was optimized for a mouse xenograft tumor. To assess the sensitivity and reliability for measuring low perfusion, the lumbar muscle was used as a reference region. By optimizing the number of averages and inversion times, muscle perfusion as low as 32.4 ± 4.8 (mean ± standard deviation) ml/100 g/min could be measured in 20 min at 7 T with a quantification error of 14.4 ± 9.1%. Applying the optimized protocol, heterogeneous perfusion ranging from 49.5 to 211.2 ml/100 g/min in a renal carcinoma was observed. To understand the relationship with tumor pathology, global and regional tumor perfusion was compared with histological staining of blood vessels (CD34), hypoxia (CAIX) and apoptosis (TUNEL). No correlation was observed when the global tumor perfusion was compared with these pathological parameters. Regional analysis shows that areas of high perfusion had low microvessel density, which was due to larger vessel area compared with areas of low perfusion. Nonetheless, these were not correlated with hypoxia or apoptosis. The results suggest that tumor perfusion may reflect certain aspect of angiogenesis, but its relationship with other pathologies needs further investigation.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging with Gd-EOB-DTPA for the Evaluation of Liver Fibrosis Induced by Carbon Tetrachloride in Rats

Purpose

To investigate the utility of dynamic contrast-enhanced MRI (DCE-MRI) with Gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) for detecting liver fibrosis induced by carbon tetrachloride (CCl₄) in rats.

Methods

This study was approved by the institutional animal care and use committee. Liver fibrosis in rats was induced by intraperitoneal injection of 1 mL/kg 50% CCl₄ twice a week for 4-13 weeks. Control rats were injected with saline. Liver fibrosis was graded using the Metaviar score: no fibrosis (F0), mild fibrosis (F1-F2) and advanced fibrosis (F3-F4). DCE-MRI with Gd-EOB-DTPA was performed for all rats. K^trans, K_ep, V_e and iAUC of the liver parenchyma were measured. Relative enhancement (RE) value of the liver was calculated on T₁-weighted images at 15, 20 and 25 min after Gd-EOB-DTPA administration.

Results

Thirty-five rats were included: no fibrosis (n=13), mild fibrosis (n=11) and advanced fibrosis (n=11). K^trans and iAUC values were highest in advanced fibrosis group and lowest in no fibrosis group (P＜0.05). The area under the receiver operating characteristic curve (AUROC) for fibrosis (stages F1 and greater) were 0.773 and 0.882 for K^trans and iAUC, respectively. AUROC for advanced fibrosis were 0.835 and 0.867 for K^trans and iAUC, respectively. K_ep and RE values were not able to differentiate fibrosis stages (all P＞0.05).

Conclusion

K^trans and iAUC obtained from DCE-MRI with Gd-EOB-DTPA are useful for the detection and staging of rat liver fibrosis induced by CCl₄.

Angiogenesis and tumor microenvironment: bevacizumab in the breast cancer model

Solid tumors require blood vessels for growth, and many new cancer therapies are directed against the tumor vasculature. Antiangiogenic therapies should destroy the tumor vasculature, thereby depriving the tumor of oxygen and nutrients. According to Jain et al., an alternative hypothesis could be that certain antiangiogenic agents can also transiently "normalize" the abnormal structure and function of tumor vasculature to make it more efficient for oxygen and drug delivery. With emphasize on the research works of Jain et al., the aim of this review is to describe the impact of antivascular endothelial growth factor (VEGF) therapy on "pseudo-normalization" of tumor vasculature and tumor microenvironment, its role in early and metastatic breast cancer, and the clinical evidence supporting this original concept. The phase III clinical trials showed that extended tumors, metastatic or locally advanced, are likely to benefit from bevacizumab therapy in combination with chemotherapy, assuming that a high level of tumor neoangiogenesis as in triple-negative tumors is the best target. In adjuvant setting, the lower level of tumor vasculature could mask a potential benefit of anti-VEGF therapy. All these findings highlight the need to identify biomarkers to help in the selection of patients most likely to respond to anti-VEGF therapy, to better understand the mechanism of angiogenesis and of resistance to anti-VEGF therapy according to molecular subtypes.

Investigation of using diffusion-weighted magnetic resonance imaging to evaluate the therapeutic effect of esophageal carcinoma treatment

AIM

To explore the associations of diffusion-weighted magnetic resonance imaging (DWI) measurements with the therapeutic effect (TE) on and survival of esophageal carcinoma patients treated with chemoradiotherapy (CRT).

METHODS

From March 2010 to December 2011, 77 patients were prospectively enrolled into a cohort study. DWI was performed at the beginning and 1-3 months after CRT. The immediate post-CRT TE was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST). The associations between the disappearance status of hyperintense expression (HE) in DWI and the apparent diffusion coefficient (ADC) of DWI with the complete response (CR) as TE and survival were analyzed.

RESULTS

3 patients were excluded due to the absence of HE in DWI. Analysis of the remaining 74 patients indicated that their ADC values were significantly improved from 1.64 ± 0.48 to 2.65 ± 0.58 mm2/s from pre-CRT to post-CRT (p = 0.000). Both univariate and multivariate Cox model analyses showed that high post-CRT ADC values and the disappearance status of HE associated significantly with the TE (CR rate) and survival.

CONCLUSIONS

DWI examination could afford useful markers to predict the treatment response as well as the survival of patients with esophageal squamous cell carcinoma. The non-disappearance of HE in DWI and low ADC values after CRT were risk factors.

Is there any correlation between model-based perfusion parameters and model-free parameters of time-signal intensity curve on dynamic contrast enhanced MRI in breast cancer patients?

OBJECTIVE

To find out any correlation between dynamic contrast-enhanced (DCE) model-based parameters and model-free parameters, and evaluate correlations between perfusion parameters with histologic prognostic factors.

METHODS

Model-based parameters (Ktrans, Kep and Ve) of 102 invasive ductal carcinomas were obtained using DCE-MRI and post-processing software. Correlations between model-based and model-free parameters and between perfusion parameters and histologic prognostic factors were analysed.

RESULTS

Mean Kep was significantly higher in cancers showing initial rapid enhancement (P = 0.002) and a delayed washout pattern (P = 0.001). Ve was significantly lower in cancers showing a delayed washout pattern (P = 0.015). Kep significantly correlated with time to peak enhancement (TTP) (ρ = -0.33, P < 0.001) and washout slope (ρ = 0.39, P = 0.002). Ve was significantly correlated with TTP (ρ = 0.33, P = 0.002). Mean Kep was higher in tumours with high nuclear grade (P = 0.017). Mean Ve was lower in tumours with high histologic grade (P = 0.005) and in tumours with negative oestrogen receptor status (P = 0.047). TTP was shorter in tumours with negative oestrogen receptor status (P = 0.037).

CONCLUSIONS

We could acquire general information about the tumour vascular physiology, interstitial space volume and pathologic prognostic factors by analyzing time-signal intensity curve without a complicated acquisition process for the model-based parameters.

KEY POINTS

• Kep mainly affected the initial and delayed curve pattern in time-signal intensity curve. • There is significant correlation between model-based and model-free parameters. • We acquired information about tumour vascular physiology, interstitial space volume and prognostic factors.

Antiangiogenesis therapy for breast cancer: an update and perspectives from clinical trials

The development of new blood vessels is a crucial step in breast cancer growth, progression and dissemination, making it a promising therapeutic target. Breast cancer has a heterogeneous nature and the diversity of responsible angiogenic pathways between different tumors has been studied for many years. Inhibiting different targets in these pathways has been under investigation in preclinical and clinical studies for more than decades, among which antibody against vascular endothelial growth factor is the most studied. However, the clinical impact from antiangiogenic treatment alone or in combination with standard chemotherapeutic regimens has been relatively small till today. In this review, we summarize the most clinically relevant data from breast cancer treatment clinical trials and discuss safety and efficacy of common antiangiogenic therapies as well as biological predictive markers.

Dynamic contrast-enhanced MRI-based biomarkers of therapeutic response in triple-negative breast cancer

OBJECTIVE

To predict the response of breast cancer patients to neoadjuvant chemotherapy (NAC) using features derived from dynamic contrast-enhanced (DCE) MRI.

MATERIALS AND METHODS

60 patients with triple-negative early-stage breast cancer receiving NAC were evaluated. Features assessed included clinical data, patterns of tumor response to treatment determined by DCE-MRI, MRI breast imaging-reporting and data system descriptors, and quantitative lesion kinetic texture derived from the gray-level co-occurrence matrix (GLCM). All features except for patterns of response were derived before chemotherapy; GLCM features were determined before and after chemotherapy. Treatment response was defined by the presence of residual invasive tumor and/or positive lymph nodes after chemotherapy. Statistical modeling was performed using Lasso logistic regression.

RESULTS

Pre-chemotherapy imaging features predicted all measures of response except for residual tumor. Feature sets varied in effectiveness at predicting different definitions of treatment response, but in general, pre-chemotherapy imaging features were able to predict pathological complete response with area under the curve (AUC)=0.68, residual lymph node metastases with AUC=0.84 and residual tumor with lymph node metastases with AUC=0.83. Imaging features assessed after chemotherapy yielded significantly improved model performance over those assessed before chemotherapy for predicting residual tumor, but no other outcomes.

CONCLUSIONS

DCE-MRI features can be used to predict whether triple-negative breast cancer patients will respond to NAC. Models such as the ones presented could help to identify patients not likely to respond to treatment and to direct them towards alternative therapies.

Clinical application of magnetic resonance imaging in management of breast cancer patients receiving neoadjuvant chemotherapy

Neoadjuvant chemotherapy (NAC), also termed primary, induction, or preoperative chemotherapy, is traditionally used to downstage inoperable breast cancer. In recent years it has been increasingly used for patients who have operable cancers in order to facilitate breast-conserving surgery, achieve better cosmetic outcome, and improve prognosis by reaching pathologic complete response (pCR). Many studies have demonstrated that magnetic resonance imaging (MRI) can assess residual tumor size after NAC, and that provides critical information for planning of the optimal surgery. NAC also allows for timely adjustment of administered drugs based on response, so ineffective regimens could be terminated early to spare patients from unnecessary toxicity while allowing other effective regimens to work sooner. This review article summarizes the clinical application of MRI during NAC. The use of different MR imaging methods, including dynamic contrast-enhanced MRI, proton MR spectroscopy, and diffusion-weighted MRI, to monitor and evaluate the NAC response, as well as how changes of parameters measured at an early time after initiation of a drug regimen can predict final treatment outcome, are reviewed. MRI has been proven a valuable tool and will continue to provide important information facilitating individualized image-guided treatment and personalized management for breast cancer patients undergoing NAC.

¹⁸F-FDG PET/CT imaging versus dynamic contrast-enhanced CT for staging and prognosis of inflammatory breast cancer

PURPOSE

Inflammatory breast cancer (IBC) is the most aggressive type of breast cancer with a poor prognosis. Locoregional staging is based on dynamic contrast-enhanced (DCE) CT or MRI. The aim of this study was to compare the performances of FDG PET/CT and DCE CT in locoregional staging of IBC and to assess their respective prognostic values.

METHODS

The study group comprised 50 women (median age: 51 ± 11 years) followed in our institution for IBC who underwent FDG PET/CT and DCE CT scans (median interval 5 ± 9 days). CT enhancement parameters were net maximal enhancement, net early enhancement and perfusion.

RESULTS

The PET/CT scans showed intense FDG uptake in all primary tumours. Concordance rate between PET/CT and DCE CT for breast tumour localization was 92%. No significant correlation was found between SUVmax and CT enhancement parameters in primary tumours (p > 0.6). PET/CT and DCE CT results were poorly correlated for skin infiltration (kappa = 0.19). Ipsilateral foci of increased axillary FDG uptake were found in 47 patients (median SUV: 7.9 ± 5.4), whereas enlarged axillary lymph nodes were observed on DCE CT in 43 patients. Results for axillary node involvement were fairly well correlated (kappa = 0.55). Nineteen patients (38%) were found to be metastatic on PET/CT scan with a significant shorter progression-free survival than patients without distant lesions (p = 0.01). In the primary tumour, no statistically significant difference was observed between high and moderate tumour FDG uptake on survival, using an SUVmax cut-off of 5 (p = 0.7 and 0.9), or between high and low tumour enhancement on DCE CT (p > 0.8).

CONCLUSION

FDG PET/CT imaging provided additional information concerning locoregional involvement to that provided by DCE CT on and allowed detection of distant metastases in the same whole-body procedure. Tumour FDG uptake or CT enhancement parameters were not correlated and were not found to have any prognostic value.

First-in-humans trial of an RNA interference therapeutic targeting VEGF and KSP in cancer patients with liver involvement

RNA interference (RNAi) is a potent and specific mechanism for regulating gene expression. Harnessing RNAi to silence genes involved in disease holds promise for the development of a new class of therapeutics. Delivery is key to realizing the potential of RNAi, and lipid nanoparticles (LNP) have proved effective in delivery of siRNAs to the liver and to tumors in animals. To examine the activity and safety of LNP-formulated siRNAs in humans, we initiated a trial of ALN-VSP, an LNP formulation of siRNAs targeting VEGF and kinesin spindle protein (KSP), in patients with cancer. Here, we show detection of drug in tumor biopsies, siRNA-mediated mRNA cleavage in the liver, pharmacodynamics suggestive of target downregulation, and antitumor activity, including complete regression of liver metastases in endometrial cancer. In addition, we show that biweekly intravenous administration of ALN-VSP was safe and well tolerated. These data provide proof-of-concept for RNAi therapeutics in humans and form the basis for further development in cancer.

SIGNIFICANCE

The fi ndings in this report show safety, pharmacokinetics, RNAi mechanism of action, and clinical activity with a novel fi rst-in-class LNP-formulated RNAi therapeutic in patients with cancer. The ability to harness RNAi to facilitate specifi c multitargeting, as well as increase the number of druggable targets, has important implications for future drug development in oncology.

Do imaging biomarkers relate to outcome in patients treated with VEGF inhibitors?

The management of solid tumors has been transformed by the advent of VEGF pathway inhibitors. Early clinical evaluation of these drugs has used pharmacodynamic biomarkers derived from advanced imaging such as dynamic MRI, computed tomography (CT), and ultrasound to establish proof of principle. We have reviewed published studies that used these imaging techniques to determine whether the same biomarkers relate to survival in renal, hepatocellular, and brain tumors in patients treated with VEGF inhibitors. Data show that in renal cancer, pretreatment measurements of K(trans) and early pharmacodynamic reduction in tumor enhancement and density have prognostic significance in patients treated with VEGF inhibitors. A weaker, but significant, relationship is seen with subtle early size change (10% in one dimension) and survival. Data from high-grade glioma suggest that pretreatment fractional blood volume and K(trans) were prognostic of overall survival. However, lack of control data with other therapies prevents assessment of the predictive nature of these biomarkers, and such studies are urgently required.

Evaluation of therapeutic effect of tumor-targeted therapy

The response evaluation criteria in solid tumors, which are based on tumor size alone, are the most frequently used and effective criteria by which to evaluate the tumor response to chemotherapy. However, the mechanism of tumor-targeted drugs is different from traditional cytotoxic drugs. Tumor-targeted drugs are designed to interfere with specific aberrant biological pathways involved in tumorigenesis. For this reason, the response evaluation in solid tumors is not adequate for the evaluation of targeted therapy. Molecular and functional imaging techniques such as dynamic contrast-enhanced perfusion computed tomography, dynamic contrast-enhanced magnetic resonance imaging, dynamic contrast-enhanced ultrasound, and fluorodeoxyglucose-positron emission tomography can reflect tumor blood flow and cellular metabolic changes directly, and are being used more frequently for the evaluation of targeted therapies. This article gives an overview of some of the new computed tomography criteria and the commonly used methods of targeted therapy evaluation.

Assessing early therapeutic response to bevacizumab in primary breast cancer using magnetic resonance imaging and gene expression profiles

Antiangiogenic therapy is a promising approach for the treatment of breast cancer. In practice, however, only a subset of patients who receive antiangiogenic drugs demonstrate a significant response. A key challenge, therefore, is to discover biomarkers that are predictive of response to antiangiogenic therapy. To address this issue, we have designed a window-of-opportunity study in which bevacizumab is administered as a short-term first-line treatment to primary breast cancer patients. Central to our approach is the use of a detailed pharmacodynamic assessment, consisting of pre- and post-bevacizumab multi-parametric magnetic resonance imaging scans and core biopsies for exon array gene expression analysis. Here, we illustrate three intrinsic patterns of response to bevacizumab and discuss the molecular mechanisms that may underpin each. Our results illustrate how the combination of dynamic imaging data and gene expression profiles can guide the development of biomarkers for predicting response to antiangiogenic therapy.

Vascular and metabolic response to bevacizumab-containing regimens in two patients with colorectal liver metastases measured by dynamic contrast-enhanced MRI and dynamic 18F-FDG-PET

Early monitoring of response to treatment is one of the cornerstones of personalized treatment. As new and often expensive targeted therapies, which are tumoristatic rather than tumoricidal, become available, new demands are posed on response assessment. Bevacizumab, an antiangiogenic agent causing normalization of the tumor microvasculature, potentiates the effect of cytotoxic agents on colorectal liver metastases. It is known that assessment of glucose metabolism by (dynamic) positron emission tomography using [(18)F]-2-fluoro-2-deoxy-D-glucose ((18)F-FDG PET) can be used as an early surrogate endpoint to determine treatment efficacy. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to quantify functional tumor vasculature (permeability, vascular surface area). Here, we describe the response of colorectal liver metastases to cytotoxic regimens including bevacizumab using both (18)F-FDG PET and DCE-MRI in 2 cases. In both cases, a large reduction in glucose metabolic rate and functional tumor vasculature are observed after 3 treatment cycles.

Breast MR with special focus on DW-MRI and DCE-MRI

The use of magnetic resonance imaging (MRI) for the assessment of breast lesions was first described in the 1970s; however, its wide application in clinical routine is relatively recent. The basic principles for diagnosis of a breast lesion rely on the evaluation of signal intensity in T2-weighted sequences, on morphologic assessment and on the evaluation of contrast enhancement behaviour. The quantification of dynamic contrast behaviour by dynamic contrast-enhanced (DCE) MRI and evaluation of the diffusivity of water molecules by means of diffusion-weighted MRI (DW-MRI) have shown promise in the work-up of breast lesions. Therefore, breast MRI has gained a role for all indications that could benefit from its high sensitivity, such as detection of multifocal lesions, detection of contralateral carcinoma and in patients with familial disposition. Breast MRI has been shown to have a role in monitoring of neoadjuvant chemotherapy, for the evaluation of therapeutic results during the course of therapy. Breast MRI can improve the determination of the remaining tumour size at the end of therapy in patients with a minor response. DCE-MRI and DW-MRI have shown potential for improving the early assessment of tumour response to therapy and the assessment of residual tumour after the end of therapy. Breast MRI is important in the postoperative work-up of breast cancers. High sensitivity and specificity have been reported for the diagnosis of recurrence; however, pitfalls such as liponecrosis and changes after radiation therapy have to be carefully considered.

Diagnostic and therapeutic imaging for cancer: therapeutic considerations and future directions

As cancer treatment cost soar and the mantra for "personalized medicine" grows louder, we will increasingly be searching for solutions to these diametrically opposed forces. In this review we highlight several exciting novel imaging strategies including MRI, CT, PET SPECT, sentinel node, and ultrasound imaging that hold great promise for improving outcomes through detection of lymph node involvement. We provide clinical data that demonstrate how these evolving strategies have the potential to transform treatment paradigms.

Biomarkers to predict the clinical efficacy of bevacizumab in cancer

Bevacizumab is a monoclonal antibody against vascular endothelial growth factor that has antiangiogenic activity and improves progression-free survival in many solid malignancies when combined with cytotoxic chemotherapy, but has little effect on overall survival. Despite the effects of this drug in unselected patients, the Response Evaluation Criteria in Solid Tumours are suboptimum to predict benefit. Additionally, tumours show inherent and emerging resistance to regimens that include bevacizumab. The ability to target therapy towards well selected subgroups of patients would increase the likelihood of benefits and would improve cost-effectiveness and therapeutic outcomes. In this review we discuss putative clinical, radiological, and molecular markers of bevacizumab efficacy, derived from data obtained in clinical trials. Current evidence indicates some predictive value for hypertension, vascular imaging, and polymorphisms affecting components of the vascular endothelial growth factor pathway in patients receiving bevacizumab. Many questions relating to these and other surrogate biomarkers, however, remain unanswered and their clinical usefulness has yet to be proven.

Perfusion MRI in the early clinical development of antivascular drugs: decorations or decision making tools?

INTRODUCTION

Classically, the first step in the clinical development of drugs in oncology involves assessments of dose limiting toxicity (DLT) and maximum tolerated dose (MTD). New paradigms are needed for antiangiogenic drugs and vascular disrupting agents (VDAs) as they are active at doses well below the MTD and as single agents their use might not translate into anti-tumour efficacy. MRI is able to assess the antivascular effects of antivascular drugs via changes in functional kinetic parameters; however, the usefulness of MRI in decision making has been questioned by many.

OBJECTIVES

Our aim is to review the experience of using dynamic contrast-enhanced MRI (DCE-MRI) in early clinical development of vascular directed anticancer therapies over the last decade. Thirty-nine phase I and II studies including data on more than 700 patients have been published as abstracts and/or papers, documenting DCE-MRI changes after the administration of antiangiogenic drugs and VDAs.

DISCUSSION

Perfusion MRI is helpful in assessing whether mechanistic goals are achieved, in assisting dose selection for phase II studies, in selecting subpopulations enriched for response and in predicting patient benefit. Imaging tools are increasingly available. Future challenges for imaging include correlation with clinical measures of efficacy and determining relationships with blood and serum biomarkers.

Inflammatory breast cancer: the disease, the biology, the treatment

Inflammatory breast cancer (IBC) is a rare and aggressive form of invasive breast cancer accounting for 2.5% of all breast cancer cases. It is characterized by rapid progression, local and distant metastases, younger age of onset, and lower overall survival compared with other breast cancers. Historically, IBC is a lethal disease with less than a 5% survival rate beyond 5 years when treated with surgery or radiation therapy. Because of its rarity, IBC is often misdiagnosed as mastitis or generalized dermatitis. This review examines IBC's unique clinical presentation, pathology, epidemiology, imaging, and biology and details current multidisciplinary management of the disease, which comprises systemic therapy, surgery, and radiation therapy.

The role of dynamic contrast-enhanced MRI in cancer diagnosis and treatment

Angiogenesis is a key step in the pathophysiology of tumor growth and metastatic spread. Recently, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has emerged as a method for assessing angiogenesis both during the initial diagnosis and for follow up of anti-angiogenic therapies. In this review, we discuss the technical aspects of implementing DCE-MRI in clinical practice with emphasis on acquisition methods and analytic techniques.

Systemic therapy of inflammatory breast cancer from high-dose chemotherapy to targeted therapies: the French experience

BACKGROUND

Aggressiveness of inflammatory breast cancer (IBC) is related to its metastatic potential. The introduction of primary chemotherapy in the multimodality treatment has dramatically changed the prognosis. However, survival remains poor. Since 1995, innovative systemic therapies have been assessed in France in multicentric clinical trials, initially centered on high-dose chemotherapy (HDC) with hematopoietic stem cell transplantation (HSCT), and, more recently, on targeted therapies.

METHODS

The authors present the rationale and first results of these French studies specifically dedicated to nonmetastastic IBC.

RESULTS

More than 380 patients have been included in 5 trials. The first 3 trials enrolled 329 women and concerned HDC (PEGASE 02, 05, 07). PEGASE 02 and PEGASE 05 showed a high pathological complete response rate (30%) after primary sequential HDC, and suggested that more than 4 cycles does not seem to provide any benefit. PEGASE 07 tested adjuvant maintenance chemotherapy after neoadjuvant HDC. Analysis is ongoing. The 2 other trials currently underway combine targeted therapies with conventional-dose chemotherapy in ERBB2-negative (Beverly 1 trial; bevacizumab) and ERBB2-positive (Beverly 2; bevacizumab and trastuzumab) IBC.

CONCLUSIONS

HDC with HSCT remains experimental with high pCR rates and which likely benefits to subgroups of patients that remain to be identified. Targeted therapies, such as anti-ERBB2 and antiangiogenic drugs, are being tested, and should improve survival as demonstrated in non-IBC. With emerging targeted drugs, there is hope that a cure becomes an achievable goal for more patients. Because of the rarity and the heterogeneity of disease, well-designed large-scale collaborative studies are mandatory.

Biology and management of inflammatory breast cancer

Inflammatory breast cancer is an aggressive subtype of a locally advanced breast cancer that is thought to account for approximately 1-5% of all newly diagnosed breast cancers diagnosed in the USA. Historically, IBC was considered to be a uniformly fatal disease with less than 5% of patients surviving past 5 years. With the advent of a multidisciplinary approach to management, survival outcomes have improved with 5-year survival rates of over 40% being reported. Research efforts are now focused on trying to better understand the epidemiological and molecular characteristics of this disease to further improve survival. Two genes, Rhoc GTPase and WISP3, have been identified that have been found to be concordantly altered in the majority of inflammatory breast cancer tumors and may serve as potential targets for future therapeutic agents. The purpose of this review is to summarize the latest epidemiological and molecular characteristics of IBC, describe the difficulties encountered in trying to clinically diagnose this entity, highlight the importance of a multidisciplinary approach and present some of the latest data on the management of this disease.

Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy

There is an increasing awareness that anatomical approaches based on measurements of tumor size have significant limitations for assessing therapy response. Functional imaging techniques are increasing being used to monitor response to therapies with novel mechanisms of action, often predicting the success of therapy before conventional measurements have changed. Dynamic contrast-enhanced and diffusion magnetic resonance imaging (MRI) are the most advanced in their evidence base, and in this manuscript we focus on them as response parameters. Technology, data gathering methods, and current limitations for these techniques are addressed. With few exceptions, most studies shows that successful treatment is reflected by increases in tumor water diffusion values visible as increased apparent diffusion coefficient values. Most response assessment studies also show that successful treatment results in decreases in tumor vascularization and microvessel permeability.

Chemotherapy response monitoring of colorectal liver metastases by dynamic Gd-DTPA-enhanced MRI perfusion parameters and 18F-FDG PET metabolic rate

In this study, we examined the in vivo relationship between functional tumor vasculature, determined by dynamic contrast-enhanced (DCE-) MRI, and tumor metabolism, determined by dynamic (18)F-FDG PET, during cytotoxic treatment of patients with colorectal liver metastases.

METHODS

Twenty-three patients underwent DCE-MRI (using gadolinium dimeglumine) and dynamic (18)F-FDG PET at baseline and after 3 treatment cycles, unless treatment was terminated because of toxicity. Parameters for vasculature (rate constant between extravascular extracellular space and blood plasma [k(ep)] and volume transfer constant [K(trans)]), extracellular space (v(e)), tumor size (the maximal axial diameter of each included lesion [MAD]), and metabolism (glucose metabolic rates [MR(glc)]) were derived, and changes during treatment were correlated. Overall survival (OS) and progression-free survival (PFS) served as outcome measures for the predictive abilities of pretreatment parameters and of treatment-related parameter changes.

RESULTS

Pretreatment MR(glc) and MAD were individually predictive for OS and PFS. During treatment, K(trans) increased significantly, but this increase could not be confirmed in a lesion-by-lesion analysis. MR(glc) decreased significantly (P < 0.001). No correlations were found for changes in DCE-MRI parameters and DeltaMR(glc). No relationship was found between changes in DCE-MRI parameters and OS or PFS. DeltaMR(glc) was able to predict OS (P = 0.008) after correction for confounders.

CONCLUSION

The efficacy of cytotoxic chemotherapy assessed by reduction in tumor metabolism does not depend on pretreatment properties of the tumor vasculature determined by DCE-MRI. Cytotoxic chemotherapy does not alter DCE-MRI-derived properties of tumor vasculature but decreases glucose consumption of tumor cells.

Washout of small molecular contrast agent in carcinoma-derived experimental tumors

The use of contrast-enhanced magnetic resonance imaging (MRI) for the assessment of breast carcinomas reveals satisfactory sensitivity, but due to low specificity, it does not obviate the need for subsequent tissue sampling. Its capability to differentiate benign from malignant lesion is under continuous investigation. Dynamic contrast-enhanced MRI (DCE-MRI) could improve specificity of MRI through the analysis of the kinetic of contrast enhancement. In particular, the study of the washout pattern is considered a promising tool to improve in vivo diagnosis and even to evaluate the response under chemotherapy. To provide a comprehensive characterization of this parameter in malignant tumor models, in vivo mapping of the washout of small molecular contrast agent (Gd-DTPA, molecular weight 0.57 kDa) was carried out in three transplanted/spontaneous mammary tumors, which differed in their histopathological and microvascular features. It resulted that in all models around 40% of tumor volume lacks efficient washout; washout areas are frequently, but not always, restricted to the tumor periphery and that non-washout areas are not restricted to necrotic regions. Difference in the distribution of lymphatic vessels characterized spontaneous vs. transplanted tumors but did not produce a corresponding different washout pattern, confirming that Gd-DTPA drainage does not mainly depend on lymphatic architecture. Finally, the efficiency of washout is correlated with parameters obtainable during the earlier phases of the enhancement curve and in malignant tumors it could be indirectly estimated from them.

Imaging of tumor angiogenesis: functional or targeted?

OBJECTIVE

Angiogenesis--the growth of new vessels--is both a normal physiologic response and a critical step in many pathologic processes, particularly cancer. Imaging has long relied on the different enhancement characteristics of cancer compared with normal tissue; the information generated is often primarily morphologic and qualitative. However, more quantitative methods based on functional and targeted imaging have recently emerged.

CONCLUSION

In this article, we review both functional and targeted imaging techniques for assessing tumor angiogenesis.

Diffusion-weighted magnetic resonance imaging for predicting and detecting early response to chemoradiation therapy of squamous cell carcinomas of the head and neck

PURPOSE

The aim of this study was to investigate the utility of apparent diffusion coefficient (ADC) for prediction and early detection of treatment response in head and neck squamous cell carcinomas (HNSCC).

EXPERIMENTAL DESIGN

Diffusion-weighted magnetic resonance imaging studies were performed on 40 patients with newly diagnosed HNSCC before, during, and after the end of chemoradiation therapy. Analysis was done on data from 33 patients after exclusion of 7 patients that had incomplete data.

RESULTS

Pretreatment ADC value of complete responders (1.04 +/- 0.19 x 10(-3) mm2/s) was significantly lower (P < 0.05) than that from partial responders (1.35 +/- 0.30 x 10(-3) mm2/s). A significant increase in ADC was observed in complete responders within 1 week of treatment (P < 0.01), which remained high until the end of the treatment. The complete responders also showed significantly higher increase in ADC than the partial responders by the first week of chemoradiation (P < 0.01). When pretreatment ADC value was used for predicting treatment response, the area under the receiver operating characteristic curve was 0.80 with a sensitivity of 65% and a specificity of 86%. However, change in ADC within the first week of chemoradiation therapy resulted in an area under the receiver operating characteristic curve of 0.88 with 86% sensitivity and 83% specificity for prediction of treatment response.

CONCLUSIONS

These results suggest that ADC can be used as a marker for prediction and early detection of response to concurrent chemoradiation therapy in HNSCC.