Dose escalated radiotherapy improves outcomes for men with prostate cancer. A plateau for benefit from dose escalation using EBRT may not have been reached for some patients with higher risk disease. The use of increasingly conformal techniques, such as step and shoot IMRT or more recently VMAT, has allowed treatment intensification to be achieved whilst minimising associated increases in toxicity to surrounding normal structures. To support further safe dose escalation, the uncertainties in the treatment target position will need be minimised using optimal planning and image-guided radiotherapy (IGRT). In particular the increasing usage of profoundly hypo-fractionated stereotactic therapy is predicated on the ability to confidently direct treatment precisely to the intended target for the duration of each treatment. This article reviews published studies on the influences of varies types of motion on daily prostate position and how these may be mitigated to improve IGRT in future. In particular the role that MRI has played in the generation of data is discussed and the potential role of the MR-Linac in next-generation IGRT is discussed.

The purpose of this study was to assess the effects of cellularinterstitial water exchange on estimates of tracer kinetics parameters obtained using rapid dynamic contrast-enhanced (DCE) MRI. Data from the internal obturator muscle of six patients were examined using three models of water exchange: no exchange (NX), fast exchange limit (FXL), and intermediate rate

Dynamic contrast-enhanced MRI is used to estimate microvascular parameters by tracer kinetics analysis. The time for the contrast agent to travel from the artery to the tissue of interest (bolus arrival time (BAT)) is an important parameter that must be measured in such studies because inaccurate estimates or neglect of BAT contribute to inaccuracy in model fitting. Furthermore, although the precision with which these parameters are estimated is very important, it is rarely reported. To address these issues, two investigations were undertaken. First, simulated data were used to validate an independent method for estimation of BAT. Second, the adiabatic approximation to the tissue homogeneity model was fitted to experimental data acquired in prostate and muscle tissue of 22 patients with prostate cancer. A bootstrap error analysis was performed to estimate the precision of parameter estimates. The independent method of estimating BAT was found to be more accurate and precise than a model-fitting approach. Estimated precisions for parameters measured in the prostate gland were 14% for extraction fraction (median coefficient of variation), 19% for blood flow, 28% for permeability-surface area product, 35% for volume of the extravascular-extracellular space, and 36% for blood volume. The study of microvascular characteristics is essential for understanding a wide range of disease processes. In particular, tumor growth and metastasis rely on rapid angiogenesis (1), which produces hyperpermeable vessels with a highly disorganized structure, arteriovenous shunts, branching, and uneven diameter (2). Measures of vascular permeability, flow, and mean transit time (MTT) through the capillary bed, for example, may be useful for describing the tumor vascular characteristics (3). Such measures have been shown to indicate tumor grade, malignancy, and treatment efficacy (4 -6).MR and CT are often used to probe microvascular characteristics (7). The benefit of using CT is the linear relationship between signal intensity and contrast agent concentration (8); however, MRI has a higher sensitivity to contrast agent and does not involve the use of ionizing radiation, which is a particular advantage for repeated scans to monitor treatment response. The dynamic image acquisition in MR can be either T 1 -weighted (T 1 W) or T 2 /T 2 *W. The T 1 W approach produces positive signal enhancement during uptake of the agent, as opposed to the negative enhancement shown in T 2 /T 2 *W images, meaning that a higher contrast-to-noise ratio (CNR) is maintained throughout the dynamic series. The T 1 -based contrast mechanism is more localized to the contrast-agent molecules, and the effect of leakage on the signal is much easier to quantify than in T 2 *W methods (9), which makes the T 1 approach attractive for measuring microvascular parameters. The uptake curve can be qualitatively assessed, or a tracer kinetics model can be fitted to the data to gain estimates of flow, vascular permeability, and the size of the compartments in which the tracer...

Dynamic contrast-enhanced MRI has been used in conjunction with tracer kinetics modeling in a wide range of tissues for treatment monitoring, oncology drug development, and investigation of disease processes. Accurate measurement of model parameters relies on acquiring data with high temporal resolution and low noise, particularly for models with large numbers of free parameters, such as the adiabatic approximation to the tissue homogeneity model for separate measurements of blood flow and vessel permeability. In this simulation study, accuracy of the adiabatic approximation to the tissue homogeneity model was investigated, examining the effects of temporal resolution, noise levels, and error in the measured arterial input function. A temporal resolution of 1.5 s and high SNR (noise sd 5 0.05) were found to ensure minimal bias (<5%) in all four model parameters (extraction fraction, blood flow, mean transit time, and extravascular extracellular volume), and the sampling interval can be relaxed to 6 s, if the transit time need not be measured accurately (bias becomes >10%). A 10% error in the measured height of the arterial input function first pass peak resulted in an error of at most 10% in each model parameter. Modeling of tracer kinetics in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become increasingly common in oncology drug development (see Ref. 1 and references therein), investigation of pathophysiology (2-5), and monitoring of treatment effect (6-8). In contrast to semiquantitative measures of tracer uptake [e.g., the area under the uptake curve (9)], which are reproducible (10) but dependent on the protocol used, tracer kinetics model parameters are intended to reflect underlying physiological properties of the tissue and are, therefore, valuable for their insensitivity to differences in protocol and equipment. The most commonly used model in DCE-MRI data analysis is the Kety model (11), which allows estimation of the transfer constant (K trans ), the size of the extravascular extracellular space (v e ) and also the blood volume (v b ) when using the modified version (12). A major disadvantage of this model is that it does not directly estimate perfusion, and it assumes that the time taken for blood to pass from the arterial to the venous side of the capillary bed (the transit time T c ) is negligibly short. This assumption is unsuitable for many tissues where T c is long [e.g., in the prostate (13)]. A more accurate description of underlying tissue physiology is possible using models more complex than the Kety model (14-16) that include the effects of a finite transit time and allow a distinct measurement of perfusion. A more realistic physiological representation often results in a better fit to the data (17). However, increased model complexity requires higher quality data measurements [in terms of temporal resolution and signal to noise ratio (SNR)] to maintain parameter accuracy and precision. An investigation of the data quality required for accurate parameter estimates for ...

Assessment of perfusion and capillary permeability is important in both malignant and nonmalignant lung disease. Kinetic modeling of T 1 -weighted dynamic contrast-enhanced MRI (DCE-MRI) data may provide such an assessment. This study establishes the feasibility and interrelationship of kinetic modeling approaches designed to estimate microvascular properties in malignant and nonmalignant tissues of the lung. DCE-MRI data were acquired using a low molecular weight contrast agent with 4-sec temporal resolution in lung cancer patients. A model-free parameterization and three kinetic models of increasing complexity, each related to the classical Kety model, were applied. Lung cancer is one of the most common forms of cancer, accounting for Ϸ15% of cancer incidence in the UK in 1998 and Ϸ22% of cancer-induced mortality in the UK in 2000, making it the most likely cause of cancer-related death (1). There is, therefore, a pressing need for effective treatment and for methods that may be used to monitor treatment efficacy. In cancer, dynamic contrast-enhanced MRI (DCE-MRI) is finding increasing application in preclinical and clinical trials of antivascular treatments, which act via a tumor's reliance on the recruitment of a vascular supply to generate growth (2). Other diseases of the lung, such as asthma and emphysema, may also be characterized by abnormalities of perfusion, and of endothelial and epithelial permeability. Methods that are sensitive to the blood supply of tumors, and that are able to quantify features such as blood flow and capillary wall permeability, are likely to be of use in this situation, as these features match the targets of the therapies.The first aim of this work was to assess a range of kinetic modeling and model-free analysis methods in lung tumors, assessing the trade-off between accuracy and precision inherent in utilizing more or less complex analyses. A family of kinetic models that may be identified as being closely related to the classical Kety model (3) describing contrast agent diffusion between tissue compartments was evaluated. Each model represents an increasing level of complexity (4), allowing us to investigate the limits on microvascular information content in T 1 -weighted DCE-MRI time series.Previous studies have used T 1 -weighted time series acquisitions to characterize parenchymal perfusion using first-pass methods (5-8). However, these studies have not attempted to account for the leakage of contrast agent from capillary to the extravascular parenchymal space that occurs readily in the lung, an acknowledged limitation (5) that can lead to erroneous estimates of blood flow and blood volume. The second aim of this work was therefore to demonstrate the practicality of quantifying the leakage via normal lung capillaries, while simultaneously quantifying perfusion, with the aim of improving the accuracy of assessment of the microvascular functional characteristics of the lung. MATERIALS AND METHODS Data Acquisition and PreprocessingHigh temporal resolution 3D short echo time ...

Purpose: To evaluate microvascular and relaxation parameters of prostate and nearby muscle in patients with benign prostatic hyperplasia (BPH), and to examine measurement reproducibility. Materials and Methods:In this prospective study, 13 patients with BPH were imaged twice prior to surgery. The imaging protocol included a three-dimensional (3D) inversion-recovery turbo field-echo measurement of T 1 , a multiecho measurement of T 2 , and a high temporal resolution (1.5 seconds per volume) dynamic contrast-enhanced (DCE) acquisition. The DCE data were analyzed using a distributed parameter tracer kinetics model to provide estimates of perfusion (F b ), extraction fraction (E), mean transit time (T c ), and extravascular-extracellular volume (v e ) in both the central gland (CG) and the peripheral zone (PZ) of the prostate, and in nearby muscle. Precision of these estimates was calculated using a bootstrap technique and the reproducibility was evaluated using the within-patient coefficient of variation (wCV). Results:The microvascular parameters were estimated in the prostate with high precision; in particular, E, F b , and v e had median CVs of Յ6%, Յ4 %, and Յ5%, respectively. Reproducibilities of the T 1 and T 2 measurements were excellent (wCV Յ 4%), and reproducibility of the other parameters reflected values seen in previous studies. Conclusion:Microvascular and relaxation properties of BPH can be measured precisely with reproducibilities for a distributed parameter tracer kinetics model that are comparable to those for a simpler model. Measurements of T 1 and T 2 were highly reproducible.

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