ABSTRACT
Recently developed iterative and deep learning-based approaches to computer-generated holography (CGH) have been shown to achieve high-quality photorealistic 3D images with spatial light modulators. However, such approaches remain overly cumbersome for patterning sparse collections of target points across a photoresponsive volume in applications including biological microscopy and material processing. Specifically, in addition to requiring heavy computation that cannot accommodate real-time operation in mobile or hardware-light settings, existing sampling-dependent 3D CGH methods preclude the ability to place target points with arbitrary precision, limiting accessible depths to a handful of planes. Accordingly, we present a non-iterative point cloud holography algorithm that employs fast deterministic calculations in order to efficiently allocate patches of SLM pixels to different target points in the 3D volume and spread the patterning of all points across multiple time frames. Compared to a matched-performance implementation of the iterative Gerchberg-Saxton algorithm, our algorithm's relative computation speed advantage was found to increase with SLM pixel count, reaching >100,000x at 512 × 512 array format.
ABSTRACT
White blood cells (WBCs) are a key component of the mammalian immune system and play an essential role in surveillance, defense, and adaptation against foreign pathogens. Apart from their roles in the active combat of infection and the development of adaptive immunity, immune cells are also involved in tumor development and metastasis. Antibody-based therapeutics have been developed to regulate (i.e. selectively activate or inhibit immune function) and harness immune cells to fight malignancy. Alternatively, non-invasive tracking of WBC distribution can diagnose inflammation, infection, fevers of unknown origin (FUOs), and cancer. Magnetic Particle Imaging (MPI) is a non-invasive, non-radioactive, and sensitive medical imaging technique that uses safe superparamagnetic iron oxide nanoparticles (SPIOs) as tracers. MPI has previously been shown to track therapeutic stem cells for over 87 days with a ~200 cell detection limit. In the current work, we utilized antibody-conjugated SPIOs specific to neutrophils for in situ labeling, and non-invasive and radiation-free tracking of these inflammatory cells to sites of infection and inflammation in an in vivo murine model of lipopolysaccharide-induced myositis. MPI showed sensitive detection of inflammation with a contrast-to-noise ratio of ~8-13.
Subject(s)
Cell Tracking/methods , Magnetics , Neutrophils/cytology , HumansABSTRACT
Magnetic fluid hyperthermia (MFH) has been widely investigated as a treatment tool for cancer and other diseases. However, focusing traditional MFH to a tumor deep in the body is not feasible because the in vivo wavelength of 300 kHz very low frequency (VLF) excitation fields is longer than 100 m. Recently we demonstrated that millimeter-precision localized heating can be achieved by combining magnetic particle imaging (MPI) with MFH. In principle, real-time MPI imaging can also guide the location and dosing of MFH treatments. Hence, the combination of MPI imaging plus real time localized MPI-MFH could soon permit closed-loop high-resolution hyperthermia treatment. In this review, we will discuss the fundamentals of localized MFH (e.g. physics and biosafety limitations), hardware implementation, MPI real-time guidance, and new research directions on MPI-MFH. We will also discuss how the scale up to human-sized MPI-MFH scanners could proceed.
