Cancer nanotherapeutics are rapidly progressing and are being implemented to solve several limitations of conventional drug delivery systems such as nonspecific biodistribution and targeting, lack of water solubility, poor oral bioavailability, and low therapeutic indices. To improve the biodistribution of cancer drugs, nanoparticles have been designed for optimal size and surface characteristics to increase their circulation time in the bloodstream. They are also able to carry their loaded active drugs to cancer cells by selectively using the unique pathophysiology of tumors, such as their enhanced permeability and retention effect and the tumor microenvironment. In addition to this passive targeting mechanism, active targeting strategies using ligands or antibodies directed against selected tumor targets amplify the specificity of these therapeutic nanoparticles. Drug resistance, another obstacle that impedes the efficacy of both molecularly targeted and conventional chemotherapeutic agents, might also be overcome, or at least reduced, using nanoparticles. Nanoparticles have the ability to accumulate in cells without being recognized by P-glycoprotein, one of the main mediators of multidrug resistance, resulting in the increased intracellular concentration of drugs. Multifunctional and multiplex nanoparticles are now being actively investigated and are on the horizon as the next generation of nanoparticles, facilitating personalized and tailored cancer treatment.

https://clincancerres.aacrjournals.org/content/clincanres/14/5/1310.full.pdf

Therapeutic Nanoparticles for Drug Delivery in Cancer

Magnetic Nanoparticles in MR Imaging and Drug Delivery

This article reviews the requirements for successful compressed sensing (CS), describes their natural fit to MRI, and gives examples of four interesting applications of CS in MRI. The authors emphasize on an intuitive understanding of CS by describing the CS reconstruction as a process of interference cancellation. There is also an emphasis on the understanding of the driving factors in applications, including limitations imposed by MRI hardware, by the characteristics of different types of images, and by clinical concerns.

/pdf/compressed-sensing-mri-2wgw41cvre.pdf

Compressed Sensing MRI

Optogenetics in neural systems.

The investigation of the functional connectivity of precise neural circuits across the entire intact brain can be achieved through optogenetic functional magnetic resonance imaging (ofMRI), which is a novel technique that combines the relatively high spatial resolution of high-field fMRI with the precision of optogenetic stimulation. Fiber optics that enable delivery of specific wavelengths of light deep into the brain in vivo are implanted into regions of interest in order to specifically stimulate targeted cell types that have been genetically induced to express light-sensitive trans-membrane conductance channels, called opsins. fMRI is used to provide a non-invasive method of determining the brain's global dynamic response to optogenetic stimulation of specific neural circuits through measurement of the blood-oxygen-level-dependent (BOLD) signal, which provides an indirect measurement of neuronal activity. This protocol describes the construction of fiber optic implants, the implantation surgeries, the imaging with photostimulation and the data analysis required to successfully perform ofMRI. In summary, the precise stimulation and whole-brain monitoring ability of ofMRI are crucial factors in making ofMRI a powerful tool for the study of the connectomics of the brain in both healthy and diseased states.

/pdf/optogenetic-functional-mri-3f5e4u0ul5.pdf

Optogenetic Functional MRI.

Comparison of fMRI analysis methods for heterogeneous BOLD responses in block design studies

Carbon monofilament electrodes for unit recording and functional MRI in same subjects.

Multiple receiver-coil data collection is an effective approach to reduce scan time. There are many parallel imaging techniques that reduce scan time using multiple receiver coils. One of these methods, partially parallel imaging with localized sensitivities (PILS), utilizes the localized sensitivity of each coil. The advantages of PILS over other parallel imaging methods include the simplicity of the algorithm, good signal-to-noise ratio (SNR) properties, and the fact that there is no additional complexity involved in applying the algorithm to arbitrary k-space trajectories. This PILS method can be further improved to provide truly parallel broadband imaging with the use of multiple-demodulation hardware. By customizing the demodulation based on each coil’s location, the k-space sampling rate can be chosen based on each coil’s localized sensitivity region along the readout direction. A simulated demodulation of data from 2D Fourier transform (FT) and spiral trajectories is shown to demonstrate the method’s feasibility. Magn Reson Med 54: 669 – 676, 2005. © 2005 Wiley-Liss, Inc. Image acquisition and reconstruction methods using multiple receiver coils are very effective ways to improve the signal-to-noise ratio (SNR) or reduce scan time. Traditionally, phased-array imaging methods (1) were commonly used to improve SNR (2). In phased-array imaging, SNR is improved by reducing the noise volume of each coil. Recently, various methods designed to decrease scan time using multiple receiver coils (3) were developed under the name of parallel imaging. These methods include sensitivity encoding (SENSE) (4), simultaneous acquisition of spatial harmonics (SMASH) (5), and partially parallel imaging with localized sensitivities (PILS) (6). The main difference between phased-array imaging and parallel imaging is the fact that parallel imaging utilizes the coils’ sensitivity pattern as an encoding scheme. The sensitivity provides additional encoding on top of the gradient encoding. This allows the process of encoding to be more parallel since the multiple sensitivity-encoded data are acquired simultaneously using multiple coils. SENSE is a method that utilizes the precise knowledge of the receiver coils’ sensitivity function as spatial encoding information. The sensitivity of the coil is a smooth function that can be measured with low-resolution scans and can then be used as an additional encoding method. By measuring this sensitivity and using it to invert the encoding matrix to reconstruct the image, the number of samples needed for Fourier encoding can be decreased. The SMASH method is similar to SENSE in that it uses the sensitivity of the coil for encoding; however, SMASH uses this information in a very different way. SMASH relies on making sinusoids out of the coils’ sensitivity patterns. Therefore, it tries to fill in the missing k-space lines by making sinusoids that normally would have been generated through gradients. In other words, it tries to interpolate data in k-space by assuming that the sensitivity pattern mimics a sinusoidal pattern. In contrast, the PILS method is a simpler method that utilizes the fact that each coil can be sensitive to a different region of the imaging FOV, so that images from different coils can be simply cut and pasted together. This method can be treated as a special case of SENSE when the sensitivity of the coils are completely orthogonal to each other. In this paper, a method to improve the PILS technique is proposed along with a new hardware configuration that will allow such a method to be implemented. THEORY

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.20595

Broadband multicoil imaging using multiple demodulation hardware: a feasibility study.

The concentric rings two-dimensional (2D) k-space trajectory enables flexible trade-offs between image contrast, signal-to-noise ratio (SNR), spatial resolution, and scan time. However, to realize these benefits for in vivo imaging applications, a robust method is desired to deal with fat signal in the acquired data. Multipoint Dixon techniques have been shown to achieve uniform fat suppression with high SNR-efficiency for Cartesian imaging, but application of these methods for non-Cartesian imaging is complicated by the fact that fat off-resonance creates significant blurring artifacts in the reconstruction. In this work, two fat–water separation algorithms are developed for the concentric rings. A retracing design is used to sample rings near the center of k-space through multiple revolutions to characterize the fat–water phase evolution difference at multiple time points. This acquisition design is first used for multipoint Dixon reconstruction, and then extended to a spectroscopic approach to account for the trajectory's full evolution through 3D k-t space. As the trajectory is resolved in time, off-resonance effects cause shifts in frequency instead of spatial blurring in 2D k-space. The spectral information can be used to assess field variation and perform robust fat–water separation. In vivo experimental results demonstrate the effectiveness of both algorithms. Magn Reson Med, 2009. © 2008 Wiley-Liss, Inc.

Jin Hyung Lee

Papers

Optogenetic Functional MRI.

Comparison of fMRI analysis methods for heterogeneous BOLD responses in block design studies

Carbon monofilament electrodes for unit recording and functional MRI in same subjects.

Broadband multicoil imaging using multiple demodulation hardware: a feasibility study.

Fat/water separation using a concentric rings trajectory.