Analysis of dynamic contrast enhanced MRI

Diagnostic performance of Gd-EOB-DTPA-enhanced MRI for evaluation of liver dysfunction: a multivariable analysis of 3T MRI sequences

OBJECTIVE

The aim of this study was to evaluate the diagnostic performance of a multiparametric gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)-enhanced MRI examination for the estimation of liver dysfunction classified by the Model for End-Stage Liver Disease (MELD) score.

RESULTS

Liver dysfunction can be assessed by different methods. In a logistic regression analysis, T1- and T2-weighted images were affected by impaired liver function. In the assessment of liver dysfunction, the reduction rate in T1 mapping sequences showed a significant correlation in simple and multiple logistic regression.

CONCLUSION

Changes in Gd-EOB-DTPA-enhanced MRI between plain images and images obtained during the hepatobiliary phase allowed good prediction of liver dysfunction, especially when using T1 mapping sequences.

MATERIALS AND METHODS

A total of 199 patients underwent contrast-enhanced MRI with a hepatocyte-specific contrast agent at 3T. In the multivariable analysis, the full range of available MRI sequences was used to estimate the liver dysfunction of patients with various MELD scores.

Conventional and advanced magnetic resonance imaging in patients with high-grade glioma

Magnetic resonance imaging is integral to the care of patients with high-grade gliomas. Anatomic detail can be acquired with conventional structural imaging, but newer approaches also add capabilities to interrogate image-derived physiologic and molecular characteristics of central nervous system neoplasms. These advanced imaging techniques are increasingly employed to generate biomarkers that better reflect tumor burden and therapy response. The following is an overview of current strategies based on advanced magnetic resonance imaging that are used in the assessment of high-grade glioma patients with an emphasis on how novel imaging biomarkers can potentially advance patient care.

Modulation of mammary tumor vascularization by mast cells: Ultrasonographic and histopathological approaches

AIMS

The inhibition of mast cells' degranulation may be an approach to prevent the formation of new vessels during the mammary carcinogenesis.

MATERIALS AND METHODS

Female Sprague-Dawley rats were randomly divided into five experimental groups. Mammary tumors were induced by intraperitoneal injection of N-methyl-N-nitrosourea (MNU). Animals from group II were treated with ketotifen for 18weeks immediately after the MNU administration, while animals from group III only received the ketotifen after the development of the first mammary tumor. Mammary tumors vascularization was assessed by ultrasonography (Doppler, B Flow and contrast-enhanced ultrasound) and immunohistochemistry (vascular endothelial growth factor-A).

KEY FINDINGS AND SIGNIFICANCE

Similar to what occurs in women with breast cancer, the majority of MNU-induced mammary tumors exhibited a centripetal enhancement order of the contrast agent, clear margin and heterogeneous enhancement. Ultrasonographic and immunohistochemical data suggest that the inhibition of mast cells' degranulation did not change the mammary tumors vascularization.

Gd-EOB-DTPA-enhanced MRI for evaluation of liver function: Comparison between signal-intensity-based indices and T1 relaxometry

Gadolinium ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) is a paramagnetic hepatobiliary magnetic resonance (MR) contrast agent. Due to its OATP1B1/B3-dependent hepatocyte-specific uptake and paramagnetic properties increasing evidence has emerged to suggest that Gd-EOB-DTPA-enhanced MRI can be potentially used for evaluation of liver function. In this paper we compare the diagnostic performance of Gd-EOB-DTPA-enhanced relaxometry-based and commonly used signal-intensity (SI)-based indices, including the hepatocellular uptake index (HUI) and SI-based indices corrected by spleen or muscle, for evaluation of liver function, determined using the Indocyanin green clearance (ICG) test. Simple linear regression model showed a significant correlation of the plasma disappearance rate of ICG (ICG-PDR) with all Gd-EOB-DTPA-enhanced MRI-based liver function indices with a significantly better correlation of relaxometry-based indices on ICG-PDR compared to SI-based indices. Among SI-based indices, HUI achieved best correlation on ICG-PDR and no significant difference of respective correlations on ICG-PDR could be shown. Assessment of liver volume and consecutive evaluation of multiple linear regression model revealed a stronger correlation of ICG-PDR with both (SI)-based and T1 relaxometry-based indices. Thus, liver function can be estimated quantitatively from Gd-EOB-DTPA-enhanced MRI-based indices. Here, indices derived from T1 relaxometry are superior to SI-based indices, and all indices benefit from taking into account respective liver volumes.

Neuroimaging

Imaging is integral to the management of patients with brain tumors. Conventional structural imaging provides exquisite anatomic detail but remains limited in the evaluation of molecular characteristics of intracranial neoplasms. Quantitative and physiologic biomarkers derived from advanced imaging techniques have been increasingly utilized as problem-solving tools to identify glioma grade and assess response to therapy. This chapter provides a comprehensive overview of the imaging strategies used in the clinical assessment of patients with gliomas and describes how novel imaging biomarkers have the potential to improve patient management.

Advanced magnetic resonance imaging of the physical processes in human glioblastoma

The most common malignant primary brain tumor, glioblastoma multiforme (GBM) is a devastating disease with a grim prognosis. Patient survival is typically less than two years and fewer than 10% of patients survive more than five years. Magnetic resonance imaging (MRI) can have great utility in the diagnosis, grading, and management of patients with GBM as many of the physical manifestations of the pathologic processes in GBM can be visualized and quantified using MRI. Newer MRI techniques such as dynamic contrast enhanced and dynamic susceptibility contrast MRI provide functional information about the tumor hemodynamic status. Diffusion MRI can shed light on tumor cellularity and the disruption of white matter tracts in the proximity of tumors. MR spectroscopy can be used to study new tumor tissue markers such as IDH mutations. MRI is helping to noninvasively explore the link between the molecular basis of gliomas and the imaging characteristics of their physical processes. We, here, review several approaches to MR-based imaging and discuss the potential for these techniques to quantify the physical processes in glioblastoma, including tumor cellularity and vascularity, metabolite expression, and patterns of tumor growth and recurrence. We conclude with challenges and opportunities for further research in applying physical principles to better understand the biologic process in this deadly disease. See all articles in this Cancer Research section, "Physics in Cancer Research."

Imaging biomarkers in primary brain tumours

We are getting used to referring to instrumentally detectable biological features in medical language as "imaging biomarkers". These two terms combined reflect the evolution of medical imaging during recent decades, and conceptually comprise the principle of noninvasive detection of internal processes that can become targets for supplementary therapeutic strategies. These targets in oncology include those biological pathways that are associated with several tumour features including independence from growth and growth-inhibitory signals, avoidance of apoptosis and immune system control, unlimited potential for replication, self-sufficiency in vascular supply and neoangiogenesis, acquired tissue invasiveness and metastatic diffusion. Concerning brain tumours, there have been major improvements in neurosurgical techniques and radiotherapy planning, and developments of novel target drugs, thus increasing the need for reproducible, noninvasive, quantitative imaging biomarkers. However, in this context, conventional radiological criteria may be inappropriate to determine the best therapeutic option and subsequently to assess response to therapy. Integration of molecular imaging for the evaluation of brain tumours has for this reason become necessary, and an important role in this setting is played by imaging biomarkers in PET and MRI. In the current review, we describe most relevant techniques and biomarkers used for imaging primary brain tumours in clinical practice, and discuss potential future developments from the experimental context.

Dynamic contrast-enhanced magnetic resonance imaging: fundamentals and application to the evaluation of the peripheral perfusion

INTRODUCTION

The ability to ascertain information pertaining to peripheral perfusion through the analysis of tissues' temporal reaction to the inflow of contrast agent (CA) was first recognized in the early 1990's. Similar to other functional magnetic resonance imaging (MRI) techniques such as arterial spin labeling (ASL) and blood oxygen level-dependent (BOLD) MRI, dynamic contrast-enhanced MRI (DCE-MRI) was at first restricted to studies of the brain. Over the last two decades the spectrum of ailments, which have been studied with DCE-MRI, has been extensively broadened and has come to include pathologies of the heart notably infarction, stroke and further cerebral afflictions, a wide range of neoplasms with an emphasis on antiangiogenic treatment and early detection, as well as investigations of the peripheral vascular and musculoskeletal systems.

APPLICATIONS TO PERIPHERAL PERFUSION

DCE-MRI possesses an unparalleled capacity to quantitatively measure not only perfusion but also other diverse microvascular parameters such as vessel permeability and fluid volume fractions. More over the method is capable of not only assessing blood flowing through an organ, but in contrast to other noninvasive methods, the actual tissue perfusion. These unique features have recently found growing application in the study of the peripheral vascular system and most notably in the diagnosis and treatment of peripheral arterial occlusive disease (PAOD).

REVIEW OUTLINE

The first part of this review will elucidate the fundamentals of data acquisition and interpretation of DCE-MRI, two areas that often remain baffling to the clinical and investigating physician because of their complexity. The second part will discuss developments and exciting perspectives of DCE-MRI regarding the assessment of perfusion in the extremities. Emerging clinical applications of DCE-MRI will be reviewed with a special focus on investigation of physiology and pathophysiology of the microvascular and vascular systems of the extremities.

Comparison of blood flow models and acquisitions for quantitative myocardial perfusion estimation from dynamic CT

Myocardial blood flow (MBF) can be estimated from dynamic contrast enhanced (DCE) cardiac CT acquisitions, leading to quantitative assessment of regional perfusion. The need for low radiation dose and the lack of consensus on MBF estimation methods motivates this study to refine the selection of acquisition protocols and models for CT-derived MBF. DCE cardiac CT acquisitions were simulated for a range of flow states (MBF = 0.5, 1, 2, 3 ml (min g)(-1), cardiac output = 3, 5, 8 L min(-1)). Patient kinetics were generated by a mathematical model of iodine exchange incorporating numerous physiological features including heterogenenous microvascular flow, permeability and capillary contrast gradients. CT acquisitions were simulated for multiple realizations of realistic x-ray flux levels. CT acquisitions that reduce radiation exposure were implemented by varying both temporal sampling (1, 2, and 3 s sampling intervals) and tube currents (140, 70, and 25 mAs). For all acquisitions, we compared three quantitative MBF estimation methods (two-compartment model, an axially-distributed model, and the adiabatic approximation to the tissue homogeneous model) and a qualitative slope-based method. In total, over 11 000 time attenuation curves were used to evaluate MBF estimation in multiple patient and imaging scenarios. After iodine-based beam hardening correction, the slope method consistently underestimated flow by on average 47.5% and the quantitative models provided estimates with less than 6.5% average bias and increasing variance with increasing dose reductions. The three quantitative models performed equally well, offering estimates with essentially identical root mean squared error (RMSE) for matched acquisitions. MBF estimates using the qualitative slope method were inferior in terms of bias and RMSE compared to the quantitative methods. MBF estimate error was equal at matched dose reductions for all quantitative methods and range of techniques evaluated. This suggests that there is no particular advantage between quantitative estimation methods nor to performing dose reduction via tube current reduction compared to temporal sampling reduction. These data are important for optimizing implementation of cardiac dynamic CT in clinical practice and in prospective CT MBF trials.

Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues

Delivery of anti-cancer drugs to tumor tissues, including their interstitial transport and cellular uptake, is a complex process involving various biochemical, mechanical, and biophysical factors. Mathematical modeling provides a means through which to understand this complexity better, as well as to examine interactions between contributing components in a systematic way via computational simulations and quantitative analyses. In this review, we present the current state of mathematical modeling approaches that address phenomena related to drug delivery. We describe how various types of models were used to predict spatio-temporal distributions of drugs within the tumor tissue, to simulate different ways to overcome barriers to drug transport, or to optimize treatment schedules. Finally, we discuss how integration of mathematical modeling with experimental or clinical data can provide better tools to understand the drug delivery process, in particular to examine the specific tissue- or compound-related factors that limit drug penetration through tumors. Such tools will be important in designing new chemotherapy targets and optimal treatment strategies, as well as in developing non-invasive diagnosis to monitor treatment response and detect tumor recurrence.

The 39 steps: evading error and deciphering the secrets for accurate dynamic susceptibility contrast MRI

Dynamic susceptibility contrast (DSC) MRI is the most commonly used MRI method to assess cerebral perfusion and other related haemodynamic parameters. Although the technique is well established and used routinely in clinical centres, there are still many problems that impede accurate perfusion quantification. In this review article, we present 39 steps which guide the reader through the theoretical principles, practical decisions, potential problems, current limitations and latest advances in DSC-MRI. The 39 steps span the collection, analysis and interpretation of DSC-MRI data, expounding issues and possibilities relating to the contrast agent, the acquisition of DSC-MRI data, data pre-processing, the contrast concentration-time course, the arterial input function, deconvolution, common perfusion parameters, post-processing possibilities, patient studies, absolute versus relative quantification and automated analysis methods.

Intraoperative Visualization of Residual Tumor: The Role of Perfusion-Weighted Imaging in a High-Field Intraoperative Magnetic Resonance Scanner

BACKGROUND:

High-field, intraoperative magnetic resonance imaging (iMRI) achieves free tumor margins in glioma surgery by involving anatomic neuronavigation and sophisticated functional imaging.

OBJECTIVE:

To evaluate the role of perfusion-weighted iMRI as an aid to detect residual tumor and to guide its resection.

METHODS:

Twenty-two patients undergoing intraoperative scanning (in a dual-room 1.5-T magnet setting) during the resection of high-grade gliomas were examined with perfusion-weighted iMRI. The generated relative cerebral blood volume (rCBV) maps were scrutinized for any hot spots indicative of tumor remnants, and region-of-interest analysis was performed. Differences among the rCBV region-of-interest estimates in residual tumor, free tumor margins, and normal white matter were analyzed. Histopathology of the tissue specimens and the neurosurgeon's intraoperative macroscopic estimations were considered the reference standards.

RESULTS:

In all cases, diagnostic rCBV perfusion maps were generated. Interpretation of perfusion maps demonstrated that gross total resection of gliomas was achieved in 4 of 22 cases (18%), which was macroscopically and histopathologically verified, whereas in 18 of 22 cases (82%), the perfusion-weighted iMRI revealed hot spots indicating subtotal tumor removal. The latter proved to be true in all but 1 case. The receiver-operating characteristic curves of the qualitative visual and quantitative analyses showed excellent sensitivity and specificity rates. Statistical analysis demonstrated statistically significant differences for the mean rCBV and maximum rCBV between residual disease and tumor-free margins (P = .002 for both).

CONCLUSION:

Perfusion-weighted iMRI may be implemented easily into imaging protocols and may assist the surgeon in detecting residual tumor volume.

High-resolution steady-state cerebral blood volume maps in patients with central nervous system neoplasms using ferumoxytol, a superparamagnetic iron oxide nanoparticle

Cerebral blood volume (CBV) measurement complements conventional magnetic resonance imaging (MRI) to indicate pathologies in the central nervous system (CNS). Dynamic susceptibility contrast (DSC) perfusion imaging is limited by low resolution and distortion. Steady-state (SS) imaging may provide higher resolution CBV maps but was not previously possible in patients. We tested the feasibility of clinical SS-CBV measurement using ferumoxytol, a nanoparticle blood pool contrast agent. SS-CBV measurement was analyzed at various ferumoxytol doses and compared with DSC-CBV using gadoteridol. Ninety nine two-day MRI studies were acquired in 65 patients with CNS pathologies. The SS-CBV maps showed improved contrast to noise ratios, decreased motion artifacts at increasing ferumoxytol doses. Relative CBV (rCBV) values obtained in the thalamus and tumor regions indicated good consistency between the DSC and SS techniques when the higher dose (510 mg) ferumoxytol was used. The SS-CBV maps are feasible using ferumoxytol in a clinical dose of 510 mg, providing higher resolution images with comparable rCBV values to the DSC technique. Physiologic imaging using nanoparticles will be beneficial in visualizing CNS pathologies with high vascularity that may or may not correspond with blood-brain barrier abnormalities.

Perfusion MRI: the five most frequently asked technical questions

OBJECTIVE

This and its companion article address the 10 most frequently asked questions that radiologists face when planning, performing, processing, and interpreting different MR perfusion studies in CNS imaging.

CONCLUSION

Perfusion MRI is a promising tool in assessing stroke, brain tumors, and patients with neurodegenerative diseases. Most of the impediments that have limited the use of perfusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols.

Comparison between PUN and Tofts models in the quantification of dynamic contrast-enhanced MR imaging

Dynamic contrast-enhanced study in magnetic resonance imaging (DCE-MRI) is an important tool in oncology to visualize tissues vascularization and to define tumour aggressiveness on the basis of an altered perfusion and permeability. Pharmacokinetic models are generally used to extract hemodynamic parameters, providing a quantitative description of the contrast uptake and wash-out. Empirical functions can also be used to fit experimental data without the need of any assumption about tumour physiology, as in pharmacokinetic models, increasing their diagnostic utility, in particular when automatic diagnosis systems are implemented on the basis of an MRI multi-parametric approach. Phenomenological universalities (PUN) represent a novel tool for experimental research and offer a simple and systematic method to represent a set of data independent of the application field. DCE-MRI acquisitions can thus be advantageously evaluated by the extended PUN class, providing a convenient diagnostic tool to analyse functional studies, adding a new set of features for the classification of malignant and benign lesions in computer aided detection systems. In this work the Tofts pharmacokinetic model and the class EU1 generated by the PUN description were compared in the study of DCE-MRI of the prostate, evaluating complexity of model implementation, goodness of fitting results, classification performances and computational cost. The mean R² obtained with the EU1 and Tofts model were equal to 0.96 and 0.90, respectively, and the classification performances achieved by the EU1 model and the Tofts implementation discriminated malignant from benign tissues with an area under the receiver operating characteristic curve equal to 0.92 and 0.91, respectively. Furthermore, the EU1 model has a simpler functional form which reduces implementation complexity and computational time, requiring 6 min to complete a patient elaboration process, instead of 8 min needed for the Tofts model analysis.

Advanced magnetic resonance imaging biomarkers of cerebral metastases

There are a number of magnetic resonance imaging techniques available for use in the diagnosis and management of patients with cerebral metastases. This article reviews these techniques, in particular, the advanced imaging methodologies from which quantitative parameters can be derived, the role of these imaging biomarkers have in distinguishing metastases from primary central nervous system tumours and tumour mimics, and metrics that may be of value in predicting the origin of the primary tumour.

Dynamic contrast-enhanced MR perfusion imaging of head and neck tumors at 3 Tesla

BACKGROUND

Dynamic contrast-enhanced (DCE) MR perfusion imaging allows assessment of vascular density and integrity of tumors. The purpose of this study was to determine the diagnostic efficacy of time intensity curve analysis on DCE MRI for characterization of head and neck tumors.

METHODS

Twenty patients underwent T1-weighted fast field echo DCE MRI with temporal resolution of 2.6 seconds. In total, 100 dynamic phases covering 20 slices were obtained in 4.5 minutes. Time to peak (TTP), relative maximum enhancement (RME) ratio, and relative washout ratio (RWO) were calculated.

RESULTS

Malignant tumors had a significantly lower RME (p = .025) and prolonged TTP with lower RWO than benign lesions. Postradiation changes had a significantly longer TTP (p = .024) and lower RWO (p = .007) than did postradiation recurrent tumors. Receiver operating characteristic (ROC) analysis revealed RWO had highest accuracy (area under the curve [AUC] = 1.0).

CONCLUSIONS

DCE MR perfusion imaging provides pivotal information regarding microcirculation, potentially improves differentiation of malignant tumor from postradiation changes.

White matter and deep gray matter hemodynamic changes in multiple sclerosis patients with clinically isolated syndrome

The dynamic susceptibility contrast magnetic resonance imaging perfusion technique was used to investigate possible hemodynamic changes in normal appearing white matter and deep gray matter (DGM) of 30 patients with clinically isolated syndrome (CIS) and 30 patients with relapsing-remitting multiple sclerosis. Thirty normal volunteers were studied as controls. Cerebral blood volume, cerebral blood flow (CBF), and mean transit time values were estimated. Normalization was achieved for each subject with respect to average values of CBF and mean transit time of the hippocampi's dentate gyrus. Measurements concerned three regions of normal white matter of normal volunteers, normal appearing white matter of CIS and patients with relapsing-remitting multiple sclerosis, and DGM regions, bilaterally. All measured normal appearing white matter and DGM regions of the patients with CIS had significantly higher cerebral blood volume and mean transit time values, while averaged DGM regions had significantly lower CBF values, compared to those of normal volunteers (P < 0.001). Regarding patients with relapsing-remitting multiple sclerosis, all measured normal appearing white matter and DGM regions showed lower CBF values than those of normal volunteers and lower cerebral blood volume and CBF values compared to patients with CIS (P < 0.001). These data provide strong evidence that hemodynamic changes--affecting both white and DGM--may occur even at the earliest stage of multiple sclerosis, with CIS patients being significantly different than relapsing-remitting multiple sclerosis patients.

Quantifying heterogeneity in human tumours using MRI and PET

Most tumours, even those of the same histological type and grade, demonstrate considerable biological heterogeneity. Variations in genomic subtype, growth factor expression and local microenvironmental factors can result in regional variations within individual tumours. For example, localised variations in tumour cell proliferation, cell death, metabolic activity and vascular structure will be accompanied by variations in oxygenation status, pH and drug delivery that may directly affect therapeutic response. Documenting and quantifying regional heterogeneity within the tumour requires histological or imaging techniques. There is increasing evidence that quantitative imaging biomarkers can be used in vivo to provide important, reproducible and repeatable estimates of tumoural heterogeneity. In this article we review the imaging methods available to provide appropriate biomarkers of tumour structure and function. We also discuss the significant technical issues involved in the quantitative estimation of heterogeneity and the range of descriptive metrics that can be derived. Finally, we have reviewed the existing clinical evidence that heterogeneity metrics provide additional useful information in drug discovery and development and in clinical practice.

Quantifying differences in hepatic uptake of the liver specific contrast agents Gd-EOB-DTPA and Gd-BOPTA: a pilot study

OBJECTIVES

To develop and evaluate a procedure for quantifying the hepatocyte-specific uptake of Gd-BOPTA and Gd-EOB-DTPA using dynamic contrast-enhanced (DCE) MRI.

METHODS

Ten healthy volunteers were prospectively recruited and 21 patients with suspected hepatobiliary disease were retrospectively evaluated. All subjects were examined with DCE-MRI using 0.025 mmol/kg of Gd-EOB-DTPA. The healthy volunteers underwent an additional examination using 0.05 mmol/kg of Gd-BOPTA. The signal intensities (SI) of liver and spleen parenchyma were obtained from unenhanced and enhanced acquisitions. Using pharmacokinetic models of the liver and spleen, and an SI rescaling procedure, a hepatic uptake rate, K (Hep), estimate was derived. The K (Hep) values for Gd-EOB-DTPA were then studied in relation to those for Gd-BOPTA and to a clinical classification of the patient's hepatobiliary dysfunction.

RESULTS

K (Hep) estimated using Gd-EOB-DTPA showed a significant Pearson correlation with K (Hep) estimated using Gd-BOPTA (r = 0.64; P < 0.05) in healthy subjects. Patients with impaired hepatobiliary function had significantly lower K (Hep) than patients with normal hepatobiliary function (K (Hep) = 0.09 ± 0.05 min(-1) versus K (Hep) = 0.24 ± 0.10 min(-1); P < 0.01).

CONCLUSIONS

A new procedure for quantifying the hepatocyte-specific uptake of T (1)-enhancing contrast agent was demonstrated and used to show that impaired hepatobiliary function severely influences the hepatic uptake of Gd-EOB-DTPA.

KEY POINTS

• The liver uptake of contrast agents may be measured with standard clinical MRI. • Calculation of liver contrast agent uptake is improved by considering splenic uptake. • Liver function affects the uptake of the liver-specific contrast agent Gd-EOB-DTPA. • Hepatic uptake of two contrast agents (Gd-EOB-DTPA, Gd-BOPTA) is correlated in healthy individuals. • This method can be useful for determining liver function, e.g. before hepatic surgery.

Multiparametric MRI biomarkers for measuring vascular disrupting effect on cancer

Solid malignancies have to develop their own blood supply for their aggressive growth and metastasis; a process known as tumor angiogenesis. Angiogenesis is largely involved in tumor survival, progression and spread, which are known to be significantly attributed to treatment failures. Over the past decades, efforts have been made to understand the difference between normal and tumor vessels. It has been demonstrated that tumor vasculature is structurally immature with chaotic and leaky phenotypes, which provides opportunities for developing novel anticancer strategies. Targeting tumor vasculature is not only a unique therapeutic intervention to starve neoplastic cells, but also enhances the efficacy of conventional cancer treatments. Vascular disrupting agents (VDAs) have been developed to disrupt the already existing neovasculature in actively growing tumors, cause catastrophic vascular shutdown within short time, and induce secondary tumor necrosis. VDAs are cytostatic; they can only inhibit tumor growth, but not eradicate the tumor. This novel drug mechanism has urged us to develop multiparametric imaging biomarkers to monitor early hemodynamic alterations, cellular dysfunctions and metabolic impairments before tumor dimensional changes can be detected. In this article, we review the characteristics of tumor vessels, tubulin-destabilizing mechanisms of VDAs, and in vivo effects of the VDAs that have been mostly studied in preclinical studies and clinical trials. We also compare the different tumor models adopted in the preclinical studies on VDAs. Multiparametric imaging biomarkers, mainly diffusion-weighted imaging and dynamic contrast-enhanced imaging from magnetic resonance imaging, are evaluated for their potential as morphological and functional imaging biomarkers for monitoring therapeutic effects of VDAs.

Dynamic susceptibility contrast MRI in advanced pancreatic cancer: semi-automated analysis to predict response to chemotherapy

The purpose of this study was to assess whether dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) can predict response to chemotherapy in advanced pancreatic cancer. DSC-MRI was performed using gradient-echo echo-planar imaging after bolus injection of contrast material. Fifty-four patients with advanced pancreatic cancer who were scheduled for chemotherapy were enrolled. ΔR2* was calculated using semi-automated computer analysis capable of tracking moving lesions during DSC-MRI. Pre-treatment maximum ΔR2* and clinical factors including gender, age, tumor stage (UICC III/IV), initial tumor size, and chemotherapy regimen were compared between patients with progressive disease and patients with stable disease as was determined at 3-month follow-up, and between patients with progressive disease and patients with stable disease as was determined at 6-month follow-up. Receiver operating characteristic (ROC) analysis and the Kaplan-Meier method with log-rank test were used to assess the relationship between the pre-treatment maximum ΔR2* and early progression (i.e. at 3-month follow-up). The pre-treatment maximum ΔR2* of patients with disease progression at 3-month follow-up (10.68 ± 3.88 s(-1)) was significantly different (p < 0.01) from that of patients with stable disease at 3-month follow-up (6.94 ± 3.12 s(-1)). Pre-treatment maximum ΔR2* of patients with disease progression at 6-month follow-up was not significantly different from that of patients with stable disease at 6-month follow-up, although a trend was noted (p = 0.08). Pre-treatment clinical factors were not significantly different between progressive and stable patients at 3- and 6-month follow-up. Tumor progression rate was significantly higher in patients with a higher pre-treatment maximum ΔR2* than in those with a lower pre-treatment maximum ΔR2* (median progression time, 38 vs 138 days, p < 0.01, using a cut-off value of 8.13 s(-1) as determined by ROC analysis). In conclusion, DSC-MRI may predict early progression in patients with advanced pancreatic cancer undergoing chemotherapy.

Measurement of R1 dynamics using sliding window-DESPOT

PURPOSE

To measure longitudinal relaxation rate (R1) changes during contrast agent studies using a driven equilibrium single pulse observation of T1 (DESPOT) method with a sliding window (sw) acquisition.

MATERIALS AND METHODS

A sw-DESPOT technique was implemented that uses several three-dimensional (3D) image data sets to calculate R1 with a temporal resolution of only a single data set. Different sources of systematic errors were studied in simulations, and the technique was tested in a tumor-bearing mouse using an intravascular contrast agent.

RESULTS

Consistent concentration distributions of the CA were calculated with a temporal resolution of 10 s.

CONCLUSION

Sw-DESPOT offers a precise and fast method to monitor the CA dynamics in 3D volumes.

Dynamic susceptibility contrast perfusion MR imaging in distinguishing malignant from benign head and neck tumors: a pilot study

PURPOSE

To preliminarily investigate the utility of dynamic susceptibility contrast perfusion MR imaging in distinguishing malignant from benign head and neck tumors.

MATERIAL AND METHODS

Seventy eight patients with head and neck masses underwent single shot dynamic susceptibility contrast T2*-weighted perfusion weighted MR imaging after bolus infusion of gadolinium-DTPA was administrated. The signal intensity time curve of the lesion was created. Dynamic susceptibility contrast percentage (DSC%) was calculated and correlated with pathological findings.

RESULTS

The mean DSC% of malignant tumor (n=40) was 39.3±9.6% and of benign lesions (n=38) was 24.3±10.3%. There was a statistically significant difference of the DSC% between benign and malignant tumors (P=0.001) and within benign tumors (P=0.001). When DSC% of 30.7% was used as a threshold for differentiating malignant from benign tumors, the best results were obtained: accuracy of 84.6%, sensitivity of 80% and specificity of 89.2%.

CONCLUSION

Dynamic susceptibility contrast perfusion weighted MR imaging is a non-invasive imaging technique that can play a role in differentiation between malignant and benign head and neck tumors.

Rheumatoid synovial inflammation: pixel-by-pixel dynamic contrast-enhanced MR imaging time-intensity curve shape analysis--a feasibility study

PURPOSE

To analyze the distribution of different shapes of time-intensity curves (TICs) in synovial tissue of patients with rheumatoid arthritis (RA) and to compare relative numbers of TIC shapes between patients with RA and healthy control subjects.

MATERIALS AND METHODS

This prospective study was approved by the institutional review board; patients and control subjects gave written informed consent. Dynamic contrast material-enhanced magnetic resonance (MR) imaging of the knee joint in five patients with early RA and in five control subjects was performed. Parametric maps showing seven TIC shape types were created. Spatial information of the synovial TIC shape distribution pattern and relative number of TIC shapes were calculated on a three-dimensional region of interest. Relative TIC shape numbers were compared by using a nonparametric Mann-Whitney U test.

RESULTS

Synovial enhancement in patients with RA consisted of type 2 TIC shapes (slow enhancement) with heterogeneous zones of types 3 (fast enhancement followed by plateau phase), 4 (fast enhancement followed by early washout phase), and 5 (fast enhancement followed by slow enhancement increase) TIC shapes, compared with almost only type 2 TIC shapes in control subjects. The heterogeneous zones were seen in the lateral and medial knee compartments and around the cruciate ligaments. A significantly higher relative number of type 4 TIC shapes was observed in the patient group compared with the control group (16.5% vs 6.9%, P = .008).

CONCLUSION

The pixel-by-pixel dynamic contrast-enhanced MR imaging TIC shape analysis may help distinguish patients with RA from control subjects on the basis of the relative number of type 4 TIC shapes. This study provides the rationale for future research to evaluate the utility of this approach in clinical practice.

Early changes in functional dynamic magnetic resonance imaging predict for pathologic response to neoadjuvant chemotherapy in primary breast cancer

PURPOSE

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows noninvasive, in vivo measurements of tissue microvessel perfusion and permeability. We examined whether DCE-MRI done after two cycles of neoadjuvant chemotherapy could predict final clinical and pathologic response in primary breast cancers.

EXPERIMENTAL DESIGN

Thirty-seven patients with primary breast cancer, due to receive six cycles of neoadjuvant 5-fluorouracil, epirubicin and cyclophosphamide chemotherapy, were examined using DCE-MRI before neoadjuvant chemotherapy and after two cycles of treatment. Changes in DCE-MRI kinetic parameters (K(trans), k(ep), v(e), MaxGd, rBV, rBF, MTT) were correlated with the final clinical and pathologic response to neoadjuvant chemotherapy. Test-retest variability was used to determine individual patient response.

RESULTS

Twenty-eight patients were evaluable for response (19 clinical responders and 9 nonresponders; 11 pathologic responders and 17 nonresponders). Changes in the DCE-MRI kinetic parameters K(trans), k(ep), MaxGd, rBV, and rBF were significantly correlated with both final clinical and pathologic response (P < 0.01). Change in K(trans) was the best predictor of pathologic nonresponse (area under the receiver operating characteristic curve, 0.93; sensitivity, 94%; specificity, 82%), correctly identifying 94% of nonresponders and 73% of responders. Change in MRI-derived tumor size did not predict for pathologic response.

CONCLUSION

Changes in breast tumor microvessel functionality as depicted by DCE-MRI early on after starting anthracycline-based neoadjuvant chemotherapy can predict final clinical and pathologic response. The ability to identify nonresponders early may allow the selection of patients who may benefit from a therapy change.

Magnetic resonance perfusion imaging in neuro-oncology

Recent advances in magnetic resonance imaging (MRI) have seen the development of techniques that allow quantitative imaging of a number of anatomical and physiological descriptors. These techniques have been increasingly applied to cancer imaging where they can provide some insight into tumour microvascular structure and physiology. This review details technical approaches and application of quantitative MRI, focusing particularly on perfusion imaging and its role in neuro-oncology.

Comparison of dynamic susceptibility-weighted contrast-enhanced MR methods: recommendations for measuring relative cerebral blood volume in brain tumors

PURPOSE

To investigate whether estimates of relative cerebral blood volume (rCBV) in brain tumors, obtained by using dynamic susceptibility-weighted contrast material-enhanced magnetic resonance (MR) imaging vary with choice of data acquisition and postprocessing methods.

MATERIALS AND METHODS

Four acquisition methods were used to collect data in 22 high-grade glioma patients, with informed written consent under HIPAA-compliant guidelines approved by the institutional review board. During bolus administration of a standard single dose of gadolinium-based contrast agent (0.1 mmol per kilogram of body weight), one of three acquisition methods was used: gradient-echo (GRE) echo-planar imaging (echo time [TE], 30 msec; flip angle, 90 degrees ; n = 10), small-flip-angle GRE echo-planar imaging (TE, 54 msec; flip angle, 35 degrees ; n = 7), or dual-echo GRE spiral-out imaging (TE, 3.3 and 30 msec; flip angle, 72 degrees ; n = 5). Next, GRE echo-planar imaging (TE, 30 msec; flip angle, 90 degrees ; n = 22) was used to collect data during administration of a second dose of contrast agent (0.2 mmol/kg). Subsequently, six methods of analysis were used to calculate rCBV. Mean rCBV values from whole tumor, tumor hot spots, and contralateral brain were normalized to mean rCBV in normal-appearing white matter.

RESULTS

Friedman two-way analysis of variance and Kruskal-Wallis one-way analysis of variance results indicated that qualitative rCBV values were dependent on acquisition and postprocessing methods for both tumor and contralateral brain. By using the nonparametric Mann-Whitney test, a consistently positive (greater than zero) tumor-contralateral brain rCBV ratio resulted when either the preload-postprocessing correction approach or dual-echo acquisition approach (P < .008 for both methods) was used.

CONCLUSION

The dependence of tumor rCBV on the choice of acquisition and postprocessing methods is caused by their varying sensitivities to T1 and T2 and/or T2* leakage effects. The preload-correction approach and dual-echo acquisition approach are the most robust choices for the evaluation of brain tumors when the possibility of contrast agent extravasation exists.

Quantitative imaging biomarkers in the clinical development of targeted therapeutics: current and future perspectives

Targeted therapeutics have challenged how imaging techniques assess tumour response to treatment because many new agents are thought to cause cytostasis rather than cytotoxicity. Advanced tracer development, image acquisition, and image analysis have been used to produce quantitative biomarkers of pathophysiology, with particular focus on measurement of tumour vascular characteristics. Here, we critically appraise strategies available to generate imaging biomarkers for use in development of targeted therapeutics. We consider important practical and technical features of data acquisition and analysis because these factors determine the precise physiological meaning of every biomarker. We discuss the merits of volume-based and other size-based metrics for assessment of targeted therapeutics, and we examine the strengths and weaknesses of CT, MRI, and PET biomarkers derived from conventional clinical data. We review imaging biomarkers of tumour microvasculature and discuss imaging strategies that probe other physiological processes including cell proliferation, apoptosis, and tumour invasion. We conclude on the need to develop comprehensive compound-specific imaging biomarkers that are appropriate for every class of targeted therapeutics, and to investigate the complementary information given in multimodality imaging studies of targeted therapeutics.

Implementation of a semi-automated post-processing system for parametric MRI mapping of human breast cancer

Magnetic resonance imaging (MRI) investigations of breast cancer incorporate computationally intense techniques to develop parametric maps of pathophysiological tissue characteristics. Common approaches employ, for example, quantitative measurements of T (1), the apparent diffusion coefficient, and kinetic modeling based on dynamic contrast-enhanced MRI (DCE-MRI). In this paper, an integrated medical image post-processing and archive system (MIPAS) is presented. MIPAS demonstrates how image post-processing and user interface programs, written in the interactive data language (IDL) programming language with data storage provided by a Microsoft Access database, and the file system can reduce turnaround time for creating MRI parametric maps and provide additional organization for clinical trials. The results of developing the MIPAS are discussed including potential limitations of the use of IDL for the application framework and how the MIPAS design supports extension to other programming languages and imaging modalities. We also show that network storage of images and metadata has a significant (p < 0.05) increase in data retrieval time compared to collocated storage. The system shows promise for becoming both a robust research picture archival and communications system working with the standard hospital PACS and an image post-processing environment that extends to other medical image modalities.

Imaging tumor vascular heterogeneity and angiogenesis using dynamic contrast-enhanced magnetic resonance imaging

This article reviews the application of dynamic contrast-enhanced magnetic resonance imaging in both clinical studies and early-phase trials of angiogenesis inhibitors. Emphasis is placed on how variation in image acquisition and analysis affects the meaning and use of derived variables. We then review the potential for future developments, with particular reference to the application of dynamic contrast-enhanced magnetic resonance imaging to evaluate the heterogeneity of tumor tissues.

Metabolic and molecular imaging in neuro-oncology

Techniques for human brain imaging have undergone rapid developments in recent years. Technological progress has enabled the assessment of many physiological parameters in vivo that are highly relevant for tumour grading, tissue characterisation, definition of the extent and infiltration of tumours, and planning and monitoring of therapy. In this review, we provide a brief overview of advanced MRI and molecular-tracer techniques that have many potential clinical uses. A broad range of techniques, including dynamic MRI, PET, and single photon emission computed tomography, provide measurements of various features of tumour blood flow and microvasculature. Using PET to measure glucose consumption enables visualisation of tumour metabolism, and magnetic resonance spectroscopy techniques provide complementary information on energy metabolism. Changes in protein and DNA synthesis can be assessed through uptake of labelled amino acids and nucleosides. Advanced imaging techniques can be used to assess tumour malignancy, extent, and infiltration, and might provide diagnostic clues to distinguish between lesion types and between recurrent tumour and necrosis. Stereotactic biopsies should be taken from the most malignant part of tumours, which can be identified by changes in microvascular structure and metabolic activity. Functional and metabolic imaging can improve the planning and monitoring of radiation and chemotherapy and contribute to the development of new therapies.

Pixel-by-pixel analysis of DCE MRI curve patterns and an illustration of its application to the imaging of the musculoskeletal system

Dynamic contrast enhanced (DCE) MRI is a widespread method that has found broad application in the imaging of the musculoskeletal (MSK) system. A common way of analyzing DCE MRI images is to look at the shape of the time-intensity curve (TIC) in pixels selected after drawing an ROI in a highly enhanced area. Although often applied to a number of MSK affections, shape analysis has so far not led to a unanimous correlation between these TIC patterns and pathology. We hypothesize that this might be a result of the subjective ROI approach. To overcome the shortcomings of the ROI approach (sampling error and interuser variability, among others), we created a method for a fast and simple classification of DCE MRI where time-curve enhancement shapes are classified pixel by pixel according to their shape. The result of the analysis is rendered in multislice, 2D color-coded images. With this approach, we show not only that differences on a short distance range of the TIC patterns are significant and cannot be appreciated with a conventional ROI analysis but also that the information that shape maps and conventional standard DCE MRI parameter maps convey are substantially different.

An independent component analysis approach for minimizing effects of recirculation in dynamic susceptibility contrast magnetic resonance imaging

In dynamic susceptibility contrast (DSC) perfusion-weighted imaging, effects of recirculation are normally minimized by a gamma-variate fitting procedure of the concentration curves before estimating hemodynamic parameters. The success of this method, however, hinges largely on the extent to which magnetic resonance signal is altered in the presence of a contrast agent and a temporal separation between the first and subsequent passages of the contrast agent. Moreover, important physiologic information might be compromised by imposing an analytic equation to all measured concentration curves. This investigation proposes to exploit independent component analysis to minimize effects of recirculation in DSC. Results obtained from simulation, normal healthy volunteers, and acute stroke patients show that such a technique can greatly minimize the effects of recirculation despite a substantial overlap between the first passage and recirculation. This in turn should improve estimation of cerebral hemodynamics particularly when an overlap between the first passage and recirculation is suspected as in an ischemic lesion.

Optimized and combinedT1 andB1 mapping technique for fast and accurateT1 quantification in contrast-enhanced abdominal MRI

Fast T(1) mapping techniques are a valuable means of quantitatively assessing the distribution and dynamics of intravenously or orally applied paramagnetic contrast agents (CAs) by noninvasive imaging. In this study a fast T(1) mapping technique based on the variable flip angle (VFA) approach was optimized for accurate T(1) quantification in abdominal contrast-enhanced (CE) MRI. Optimization methods were developed to maximize the signal-to-noise ratio (SNR) and ensure effective RF and gradient spoiling, as well as a steady state, for a defined T(1) range of 100-800 ms and a limited acquisition time. We corrected B(1) field inhomogeneities by performing an additional measurement using an optimized fast B(1) mapping technique. High-precision in vitro and abdominal in vivo T(1) maps were successfully generated at a voxel size of 2.8 x 2.8 x 15 mm(3) and a temporal resolution of 2.3 s per T(1) map on 1.5T and 3T MRI systems. The application of the proposed fast T(1) mapping technique in abdominal CE-MRI enables noninvasive quantification of abdominal tissue perfusion and vascular permeability, and offers the possibility of quantitatively assessing dilution, distribution, and mixing processes of labeled solutions or drugs in the gastrointestinal tract.

Inter- and intraobserver variability in the evaluation of dynamic breast cancer MRI

PURPOSE

To quantify variations within and between observers ascribable to manual region of interest (ROI) placement in patients with breast cancer undergoing dynamic MRI.

MATERIALS AND METHODS

Expert and nonexpert observers independently outlined tumor ROIs on 30 dynamic T(1)-weighted (T(1)W) MRI scans on five occasions over two months. Lesion size (number of pixels) and kinetic parameter estimates, including the transfer constant (K(trans)), were calculated for each ROI placement. Inter- and intraobserver variability was assessed with respect to the interval between drawings, lesion morphology, and observer experience.

RESULTS

For the nonexpert, the variability reduced with decreasing time intervals between ROI drawings (the coefficient of variance (wCV) values at two months, two weeks, one day, and same-day time intervals were respectively 11.6%, 10.7%, 4.8%, and 2.6% for lesion size, and 8.9%, 9.7%, 6.7%, and 3.2% for K(trans)). For the expert observer, the variability was smaller overall and more constant, but improved for same-day ROI placements (region size wCV: 7.5%, 6.2%, 7.1%, and 3.7%; K(trans) wCV: 5.4%, 5.3%, 5.6%, and 4.5%).

CONCLUSION

Significant observer variability in manual ROI placement occurs in dynamic MRI of breast cancer. For serial patient studies, ROI placements should be outlined at the same sitting to minimize observer error.