Effect of Tumor Volume on Drug Delivery in Heterogeneous Vasculature of Human Brain Tumors

Drug distribution in tumors is strongly dependent on tumor biological properties such as tumor volume, vasculature, and porosity. An understanding of the drug distribution pattern in tumors can help in enhancing the effectiveness of anticancer treatment. A numerical model is employed to study the distribution of contrast agent in the heterogeneous vasculature of human brain tumors of different volumes. Dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) has been done for a number of patients with different tumor volumes. Leaky tracer kinetic model (LTKM) is employed to obtain perfusion parameters from the DCE-MRI data. These parameters are used as input in the computational fluid dynamics (CFD) model to predict interstitial fluid pressure (IFP), interstitial fluid velocity (IFV), and distribution of the contrast agent in different tumors. Numerical results demonstrate that the IFP is independent of tumor volume. On the other hand, the IFV increases as the tumor volume increases. Further, the concentration of contrast agent also increases with the tumor volume. The results obtained in this work are in line with the experimental DCE-MRI data. It is observed that large volume tumors tend to retain a higher concentration of contrast agent for a longer duration of time because of large extravasation flux and slow washout as compared to smaller tumors. These results may be qualitatively extrapolated to chemotherapeutic drug delivery, implying faster healing in large volume tumors. This study helps in understanding the effect of tumor volume on the treatment outcome for a wide range of human tumors.

Evaluation of Maximum and Minimum Signal Intensity and the Linear Relationship between Concentration and Signal Intensity in Saturation Recovery T1-weighted Images by use of a Turbo Fast Low-Angle Shot Sequence

Background: The relationship between the concentration of contrast agents and signal intensity (SI) are affected by some image parameters, phase-encoding scheme, magnetic field strength, image sequences, and iron oxide nanoparticles used and Gd-DTPA as MRI contrast agents.Objective: In this article, the effect of saturation times (TSs) on the maximum and minimum SI, and also the linear relationship between the concentration of the contrast agent and SI are evaluated. Additionally, we evaluated the concentration of contrast agent that results the minimum SI using a saturation recovery TurboFLASH sequence.Material and Methods: A phantom was designed to hold vials with different concentrations of Gd-DTPA (0–19.77mmol/L). The mean SI was acquired from the nine central pixels of every vial at various TSs.Results: This study shows that the maximum SI in an image is dependent on short TSs (up to 400ms) and independent of long TSs (400–1000ms). The result also shows that the concentration at which a maximum linear relationship between concentration and SI is maintained that gave an R2 equal to 0.95 and 0.99 dependent on the TS. Moreover, the outcome demonstrates that as TS increases, the concentration of the contrast agent decreases. This causes SI to be minimized.Conclusion: This study demonstrated that the TS is a key parameter for measuring the maximum and minimum SI and also TS plays the role in determining the maximum linear relationship between the MRI contrast agent concentration and SI in an in vivo perfusion study.

MRI-Based Quantification of Magnetic Susceptibility in Gel Phantoms: Assessment of Measurement and Calculation Accuracy

The local magnetic field inside and around an object in a magnetic resonance imaging unit depends on the magnetic susceptibility of the object being magnetized, in combination with its geometry/orientation. Magnetic susceptibility can thus be exploited as a source of tissue contrast, and susceptibility imaging may also become a useful tool in contrast agent quantification and for assessment of venous oxygen saturation levels. In this study, the accuracy of an established procedure for quantitative susceptibility mapping (QSM) was investigated. Three gel phantoms were constructed with cylinders of varying susceptibility and geometry. Experimental results were compared with simulated and analytically calculated data. An expected linear relationship between estimated susceptibility and concentration of contrast agent was observed. Less accurate QSM-based susceptibility values were observed for cylindrical objects at angles, relative to the main magnetic field, that were close to or larger than the magic angle. Results generally improved for large objects/high spatial resolution and large volume coverage. For simulated phase maps, accurate susceptibility quantification by QSM was achieved also for more challenging geometries. The investigated QSM algorithm was generally robust to changes in measurement and calculation parameters, but experimental phase data of sufficient quality may be difficult to obtain in certain geometries.