Dynamic magnetic resonance imaging of tumor perfusion

Dynamic MRI for imaging tumor microvasculature: comparison of susceptibility and relaxivity techniques in pelvic tumors

PURPOSE

To assess the reproducibility of intrinsic relaxivity and both relaxivity- and susceptibility-based dynamic contrast enhanced (DCE) MRI in pelvic tumors; to correlate kinetic parameters obtained and to assess whether acute antivascular effects are seen in response to cisplatin- or taxane-based chemotherapy.

MATERIALS AND METHODS

T1-weighted and T2*-weighted DCE-MRI and basal R2* measurements were performed on three consecutive days in women with gynecological tumors. The third scan was 21.0 (range 17.3-23.5) hours after the first cycle of chemotherapy. Kinetic parameter estimates were obtained and correlated between techniques. Test-retest reproducibility and response to treatment were assessed.

RESULTS

Relative blood volume (rBV) and relative blood flow (rBF) correlated strongly with transfer constant (Ktrans), kep, and the initial area under the gadopentetate dimeglumine (Gd-DTPA) concentration-time curve (IAUGC) (all P<0.01). The group 95% confidence interval (CI) for change was -10.8 to +12.1%; +/-5.1%; -9.5 to +10.5%; +/-7.5%; for Ktrans, ve, kep, and IAUGC, respectively, and +/-13.6%, +/-2.4%, +/-11.6%, and +/-11.0%, for rBV, mean transit time (MTT), rBF, and R2*, respectively. There were no significant acute changes in kinetic parameter estimates in response to treatment on group analysis, apart from a small decrease in ve.

CONCLUSION

The results confirm the dominant influence of flow on Ktrans in untreated gynecological tumors. There is no evidence of an acute, large magnitude antivascular effect caused by cisplatin- or taxane-based chemotherapy.

Malignant-lesion segmentation using 4D co-occurrence texture analysis applied to dynamic contrast-enhanced magnetic resonance breast image data

PURPOSE

To investigate the use of four-dimensional (4D) co-occurrence-based texture analysis to distinguish between nonmalignant and malignant tissues in dynamic contrast-enhanced (DCE) MR images.

MATERIALS AND METHODS

4D texture analysis was performed on DCE-MRI data sets of breast lesions. A model-free neural network-based classification system assigned each voxel a "nonmalignant" or "malignant" label based on the textural features. The classification results were compared via receiver operating characteristic (ROC) curve analysis with the manual lesion segmentation produced by two radiologists (observers 1 and 2).

RESULTS

The mean sensitivity and specificity of the classifier agreed with the mean observer 2 performance when compared with segmentations by observer 1 for a 95% confidence interval, using a two-sided t-test with alpha = 0.05. The results show that an area under the ROC curve (A(z)) of 0.99948, 0.99867, and 0.99957 can be achieved by comparing the classifier vs. observer 1, classifier vs. union of both observers, and classifier vs. intersection of both observers, respectively.

CONCLUSION

This study shows that a neural network classifier based on 4D texture analysis inputs can achieve a performance comparable to that achieved by human observers, and that further research in this area is warranted.

Bayesian methods for pharmacokinetic models in dynamic contrast-enhanced magnetic resonance imaging

This paper proposes a new method for estimating kinetic parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based on adaptive Gaussian Markov random fields. Kinetic parameter estimates using neighboring voxels reduce the observed variability in local tumor regions while preserving sharp transitions between heterogeneous tissue boundaries. Asymptotic results for standard errors from likelihood-based nonlinear regression are compared with those derived from the posterior distribution using Bayesian estimation with and without neighborhood information. Application of the method to the analysis of breast tumors based on kinetic parameters has shown that the use of Bayesian analysis combined with adaptive Gaussian Markov random fields provides improved convergence behavior and more consistent morphological and functional statistics.

Imaging oxygenation of human tumours

Tumour hypoxia represents a significant challenge to the curability of human tumours leading to treatment resistance and enhanced tumour progression. Tumour hypoxia can be detected by non-invasive and invasive techniques but the inter-relationships between these remains largely undefined. ¹⁸F-MISO and Cu-ATSM-PET, and BOLD-MRI are the lead contenders for human application based on their non-invasive nature, ease of use and robustness, measurement of hypoxia status, validity, ability to demonstrate heterogeneity and general availability, these techniques are the primary focus of this review. We discuss where developments are required for hypoxia imaging to become clinically useful and explore potential new uses for hypoxia imaging techniques including biological conformal radiotherapy.

Dynamic contrast-enhanced magnetic resonance imaging is a poor measure of rectal cancer angiogenesis

BACKGROUND

The aim of this study was to investigate the use of magnetic resonance imaging (MRI) for non-invasive measurement of rectal cancer angiogenesis and hypoxia.

METHODS

Fifteen patients with rectal adenocarcinoma underwent preoperative dynamic contrast-enhanced (DCE) and blood oxygenation level-dependent (BOLD) MRI. Microvessel density (CD31 level), and expression of vascular endothelial growth factor (VEGF) and carbonic anhydrase (CA) 9 were measured immunohistochemically in histological tumour sections from 12 patients. Serum VEGF levels were also measured in 14 patients. Correlations between quantitative imaging indices and immunohistochemical variables were examined.

RESULTS

There was good correlation between circulating VEGF and CD31 expression (r(S) = 0.88, P < 0.001). CD31 expression did not correlate with any dynamic MRI parameter, except transfer constant, with which it correlated inversely (r(S) = -0.65, P = 0.022). Tissue and circulating VEGF levels did not correlate, and neither correlated with any tumour DCE MRI parameter. No relationship was seen between BOLD MRI and CA-9 expression.

CONCLUSION

The negative correlation between transfer constant (reflecting tumour blood flow and microvessel permeability) with CD31 expression is paradoxical. DCE MRI methods for assessing tissue vascularity correlate poorly with histological markers of angiogenesis and hypoxia, suggesting that DCE MRI does not simply reflect static histological vascular properties in patients with rectal cancer.

Informatics in Radiology (infoRAD): Magnetic Resonance Imaging Workbench: analysis and visualization of dynamic contrast-enhanced MR imaging data

Magnetic Resonance Imaging Workbench (MRIW) allows analysis of T1- and T2*-weighted dynamic contrast-enhanced magnetic resonance imaging data sets to extract tissue permeability and perfusion characteristics by using standard pharmacokinetic models. Parametric maps are calculated from individual pixel enhancement curves in regions of interest (ROIs) and displayed as color overlays on the anatomic images. User-defined ROIs can be saved to ensure consistency of later reanalysis. Individual parametric maps are visualized together with user-selected parameter time-series plots. The following selections are available: overall ROI enhancement curve and fit, histogram, and individual pixel enhancement curve and fit. Summary data (transfer constant, leakage space, rate constant, integrated area under the gadolinium curve after 60 seconds, relative blood volume, relative blood flow, and mean transit time) may be exported to permanent storage along with per-pixel results for statistical analysis. Numerical values for parameters are displayed below the plot for easy reference. The dynamic range of plots and parametric map overlays is interactively adjustable. Viewing individual enhancement curves and parametric maps allows radiologists to investigate the heterogeneity of contrast agent kinetics for lesion characterization and to scrutinize serial changes in response to therapy. MRIW is written in IDL, enabling it to be used on a variety of computer systems.

Statistical analysis of pharmacokinetic models in dynamic contrast-enhanced magnetic resonance imaging

This paper assesses the estimation of kinetic parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Asymptotic results from likelihood-based nonlinear regression are compared with results derived from the posterior distribution using Bayesian estimation, along with the output from an established software package (MRIW). By using the estimated error from kinetic parameters, it is possible to produce more accurate clinical statistics, such as tumor size, for patients with breast tumors. Further analysis has also shown that Bayesian methods are more accurate and do not suffer from convergence problems, but at a higher computational cost.

Angiogenesis imaging in the management of prostate cancer

Angiogenesis is an integral part of benign prostatic hyperplasia, is associated with prostatic intraepithelial neoplasia and is a key factor in the growth and metastasis of prostate cancer. This review focuses on ultrasound and dynamic MRI in the evaluation of prostate cancer angiogenesis, and compares these techniques to functional CT and hydrogen magnetic resonance spectroscopic imaging. Image-based evaluation of angiogenesis in the prostate has established clinical roles in lesion detection, tumor staging and the detection of suspected tumor recurrence. One limitation of all these imaging techniques, however, is inadequate lesion characterization, particularly in differentiating prostatitis from cancer in the peripheral zone of the prostate, and in distinguishing between benign prostatic hyperplasia and central-gland tumors. Ultimately, local availability, expertise and the need to minimize patients' radiation burden will influence which technique is used in prostatic evaluations.

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.

Effects of platinum/taxane based chemotherapy on acute perfusion in human pelvic tumours measured by dynamic MRI

Dynamic contrast enhanced MRI (DCE-MRI) is being used increasingly in clinical trials to demonstrate that vascular disruptive and antiangiogenic agents target tumour microcirculation. Significant reductions in DCE-MRI kinetic parameters are seen within 4–24 and 48 h of treatment with vascular disruptive and antiangiogenic agents, respectively. It is important to know whether cytotoxic agents also cause significant acute reductions in these parameters, for reliable interpretation of results. This study investigated changes in transfer constant (K^trans) and the initial area under the gadolinium curve (IAUGC) following the first dose of chemotherapy in patients with mostly gynaecological tumours. A reproducibility analysis on 20 patients (using two scans performed on consecutive days) was used to determine the significance of DCE-MRI parameter changes 24 h after chemotherapy in 18 patients. In 11 patients who received platinum alone or with a taxane, there were no significant changes in K^trans or IAUGC in either group or individual patient analyses. When the remaining seven patients (treated with a variety of agents including platinum and taxanes) were included (n=18), there were also no significant changes in K^trans. Therefore, if combination therapy does show changes in DCE-MRI parameters then the effects can be attributed to antivascular therapy rather than chemotherapy.

Pelvic malignancy: integrating form and function

Despite the essential role morphological imaging plays in the management of patients with malignancy, anatomical techniques are limited in their ability to report on tumour biology and behaviour. It has therefore been necessary to develop imaging techniques that integrate form and function to probe the micro and molecular environments of cancers. The role of clinical functional and molecular magnetic resonance imaging is discussed with an emphasis on pelvic malignancy. It is argued that the radiological sciences need to take a lead in translating molecular and functional imaging techniques into man. Imaging in support of drug development is suggested as a focus for that development.

An adaptive tissue characterization network for model-free visualization of dynamic contrast-enhanced magnetic resonance image data

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become an important source of information to aid cancer diagnosis. Nevertheless, due to the multi-temporal nature of the three-dimensional volume data obtained from DCE-MRI, evaluation of the image data is a challenging task and tools are required to support the human expert. We investigate an approach for automatic localization and characterization of suspicious lesions in DCE-MRI data. It applies an artificial neural network (ANN) architecture which combines unsupervised and supervised techniques for voxel-by-voxel classification of temporal kinetic signals. The algorithm is easy to implement, allows for fast training and application even for huge data sets and can be directly used to augment the display of DCE-MRI data. To demonstrate that the system provides a reasonable assessment of kinetic signals, the outcome is compared with the results obtained from the model-based three-time-points (3TP) technique which represents a clinical standard protocol for analysing breast cancer lesions. The evaluation based on the DCE-MRI data of 12 cases indicates that, although the ANN is trained with imprecisely labeled data, the approach leads to an outcome conforming with 3TP without presupposing an explicit model of the underlying physiological process.

The assessment of antiangiogenic and antivascular therapies in early-stage clinical trials using magnetic resonance imaging: issues and recommendations

Vascular and angiogenic processes provide an important target for novel cancer therapeutics. Dynamic contrast-enhanced magnetic resonance imaging is being used increasingly to noninvasively monitor the action of these therapeutics in early-stage clinical trials. This publication reports the outcome of a workshop that considered the methodology and design of magnetic resonance studies, recommending how this new tool might best be used.