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DOE OSTI2024

Dosimetric and biological impact of activity extravasation of radiopharmaceuticals in PET imaging

The increasing use of nuclear medicine and PET imaging has intensified scrutiny of radiotracer extravasation. To our knowledge, this topic is understudied but holds great potential for enhancing our understanding of extravasation in clinical PET imaging. This work aims to (1) quantify the absorbed doses from radiotracer extravasation in PET imaging, both locally at the site of extravasation and with the extravasation location as a source of exposure to bodily organs and (2) assess the biological ramifications within the injection site at the cellular level. A radiation dosimetry simulation was performed using a whole-body 4D Extended Cardiac-Torso (XCAT) phantom embedded in the GATE Monte Carlo platform. A 10-mCi dose of 18 F-FDG was chosen to simulate a typical clinical PET scan scenario, with 10% of the activity extravasated in the antecubital fossa of the right arm of the phantom. The extravasation volume was modeled as a 5.5 mL rectangle in the hypodermal layer of skin. Absorbed dose contributions were calculated for the first two half-lives, assuming biological clearance thereafter. Dose calculations were performed as absorbed doses at the organ and skin levels. Energy deposition was simulated both at the local extravasation site and in multiple organs of interest and converted to absorbed doses based on their respective masses. Each simulation was repeated ten times to estimate Monte Carlo uncertainties. Biological impacts on cells within the extravasated volume were evaluated by randomizing cells and exposing them to a uniform radiation source of 18 F and 68 Ga. Particle types, their energies, and direction cosines were recorded in phase space files using a separate Geant4 simulation to characterize their entry into the nucleus of the cellular volume. Subsequently, the phase space files were imported into the TOPAS-nBio simulation to assess the extent of DNA damage, including double-strand breaks (DSBs) and single-strand breaks (SSBs). Organ-level dosimetric estimations are presented for 18 F and 68 Ga radionuclides in various organs of interest. With 10% extravasation, the hypodermal layer of the skin received the highest absorbed dose of 1.32 ± 0.01 Gy for 18 F and 0.99 ± 0.01 Gy for 68 Ga. The epidermal and dermal layers received absorbed doses of 0.07 ± 0.01 Gy and 0.13 ± 0.01 Gy for 18 F, and 0.14 ± 0.01 Gy and 0.29 ± 0.01 Gy for 68 Ga, respectively. In the extravasated volume, 18 F caused an average absorbed dose per nucleus of 0.17 ± 0.01 Gy, estimated to result in 10.58 ± 0.50 DSBs and 268.11 ± 12.43 SSBs per nucleus. For 68 Ga, the absorbed dose per nucleus was 0.11 ± 0.01 Gy, leading to an estimated 6.49 ± 0.34 DSBs and 161.24 ± 8.12 SSBs per nucleus. Absorbed doses in other organs were on the order of micro-gray (µGy). The likelihood of epidermal erythema resulting from extravasation during PET imaging is low, as the simulated absorbed doses to the epidermis remain below the thresholds that trigger such effects. Moreover, the organ-level absorbed doses were found to be clinically insignificant across various simulated organs. The minimal DNA damage at the extravasation site suggests that long-term harm, such as radiation-induced carcinogenesis, is highly unlikely.

DNA strand breaks↗

DOE OSTI2020

Imaging Supramolecular Morphogenesis with Confocal Laser Scanning Microscopy at Elevated Temperatures

The morphogenesis of supramolecular assemblies is a highly dynamic process that has only recently been recognized, and our understanding of this phenomenon will require imaging techniques capable of crossing scales. Shape transformations depend both on the complex energy landscapes of supramolecular systems and the kinetically controlled pathways that define their structures and functions. We report here the use of confocal laser scanning microscopy coupled with a custom-designed variable-temperature sample stage that enables in situ observation of such shape changes. The submicrometer resolution of this technique allows for real-time observation of the nanostructures in the native liquid environments in which they transform with thermal energy. We use this technique to study the temperature-dependent morphogenic behavior of peptide amphiphile nanofibers and photocatalytic chromophore amphiphile nanoribbons. Furthermore, the variable-temperature confocal microscopy technique demonstrated in this work can sample a large volume and provides real-time information on thermally induced morphological changes in the solution.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Optical Time Transfer for Bistatic SAR Spacecraft

A spacecraft-to-spacecraft optical time-transfer simulation has been developed as a tool for informing NASA’s Surface Deformation and Change (SDC) mission architecture. The SDC mission will combine radar images from multiple spacecraft to improve understanding of the Earth’s sea-level and landscape changes. Spacecraft must be precisely synchronized in order to create sharp radar images. Simulation of multiple spacecraft time-synchronizing via laser communication can inform technology choices of a mission by providing a picosecond-precision level estimate of clock error. This timing and ranging simulation has been combined with a radar system performance analysis pipeline. The simulated timing errors are used to predict performance of bistatic SAR systems in the presence of oscillator noise and time synchronization in accuracy. This analysis includes both analytic approximation equations from existing literature, and a numerical radar simulation to extract key system performance parameters like phase error and signal-to-noise ratio (SNR)degradation. Precision time-transfer techniques facilitate the accurate synchronization of clocks between any combination of terminals. Most time-transfer technology for comparing two clocks at different terminals use radio frequencies (RF) to measure the time delay between the sending and receiving of signals. Laser technology offers the capability to transmit high data rates with systems that are of smaller size and lower power than comparable RF systems. The clocks on independent spacecraft will have some phase and frequency errors between them that result in clock drift. The two clock models that are included in this bi-directional MATLAB simulation are a cesium-based Chip-Scale Atomic Clock (CSAC) and a rubidium-based Miniature Atomic Clock (MAC). The CSAC has flown as hardware for small satellite missions such as the University of Florida’s CHOMPTT mission. A study of example orbits, including that of NASA NASA-ISRO Synthetic Aperture Radar Mission (NISAR) mission, and lasing rates demonstrate the impact of flight configuration parameters on the synchronization error between two spacecraft. The MATLAB timing simulation uses a Runge-Kutta 4th-order method to propagate spacecraft orbits and computes the light-travel time estimate between them. The simulation outputs the estimated range and estimated clock error based on a user-defined spacecraft cluster configuration. The radar simulation and analytic approximations are applied to evaluate a potential future NASA bistatic SAR constellation architecture. In the proposed architecture, satellites follow each other in the same orbit at 800 km altitude, with a 210 km baseline. We also baseline the CSAC as an ultra stable oscillator, and use NASA’s NISAR for baseline radar system parameters to compute a clock-system introduced phase error of 5.6 degrees without synchronization by frequent time transfer. We build on this base case with a sensitivity analysis of radar performance over a proposed range of constellation and radar system parameters. With this analysis pipeline, we comment on which radar parameters should or should not be changed to minimize synchronization requirements. This analysis technique could be extended or modified to evaluate the timing requirements of other geometries for other future multistatic SAR missions, or other interferometric satellite missions.

Surface Deformation and Change↗

DOE OSTI2020

Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images

Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning meaningful image features that would enable extension to new datasets. In situ electron microscopy provides a clear platform for utilizing automated image analysis. In this work, we consider the case of studying coarsening dynamics in supported nanoparticles, which is important for understanding, for example, the degradation of industrial catalysts. By systematically studying dataset preparation, neural network architecture, and accuracy evaluation, we describe important considerations in applying deep learning to physical applications, where generalizable and convincing models are required. With a focus on unique challenges that arise in high-resolution images, we propose methods for optimizing performance of image segmentation using convolutional neural networks, critically examining the application of complex deep learning models in favor of motivating intentional process design.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Imaging Science Requirements for a Uranus Flagship Mission

Introduction: Our presentation will summarize the requirements for UV/Visible/Near-IR remote-sensing imaging science instruments (including mapping spectrometers) envisioned for the Uranus Orbiter and Probe (UOP) mission recommended by the recent planetary decadal survey. The Uranus system offers many targets for imaging investigations. Imaging science investigations are crucial to answering fundamental questions about various physical processes that shape the Uranian system and drive its evolution. Each science objective addressed through imaging has requirements for observation and illumination geometries as well as coverage and resolution in the spatial, spectral and temporal dimensions. By combining the requirements for the diverse science targets in the Uranian system, we present a set of overarching imaging science requirements for UOP. Atmospheric Science: The study of Uranus’ atmosphere is crucial in understanding the planet's energy balance and interior heat flux. Imaging observations map how the atmosphere scatters incident solar radiation. Imaging is key to characterizing planetary-scale energy/material transport though global atmospheric dynamics and local meteorology. Hyperspectral mapping combined with radiative transfer analysis reveals the vertical distribution of clouds and hazes. Chronicling temporal variabilities of atmospheric features is key to understanding the various processes that operate within the dynamic Uranian atmosphere. A comprehensive understanding of Uranus' atmosphere is essential in deciphering the planet's origins and evolution as well as providing insight into the broader field of planetary and exoplanetary science. Magnetospheric Interactions: Imaging science is critical to understand the elusive Uranian aurorae. Mapping the aurorae and their temporal dynamics will reveal the interaction of Uranus’ complex magnetosphere with the solar wind. The apparent decades-long cooling of Uranus’ upper atmosphere is thought to be due to changes in energy input from the overlying magnetosphere, and so mapping and quantifying the auroral evidence for this energy flux is particularly relevant for upper atmospheric science In addition, Uranus’ large moons may generate auroral footprints, which can be used to constrain the planet’s unusual magnetic field structure. Satellite Interiors: Imaging science can address the potential habitability of the larger moons of Uranus by measuring their shapes and rotational states (including librations), which combined with gravity data are crucial to understanding their internal density structure. Satellite Origins: Origin markers such as organics and volatiles may be preserved on the satellite surfaces, which may be sensed by UV/IR mapping. Imaging combined with the moons’ densities may reveal whether the moons formed in Uranus’ circumplanetary disk, rings, or from ejecta of a giant impact on Uranus. Satellite Geology: Imaging investigations, including stereo imaging to obtain topography, will enable constraining each satellite’s geologic history by investigating the distributions and morphologies of impact craters, tectonic and potential cryovolcanic features, and regolith and mass wasting deposits. These records will help unravel the past complex history of orbital resonances that occurred between Uranian satellites, which may have driven geologic activity. Analyses of these features will also point to resurfacing styles and modification processes important for understanding each moon’s thermal evolution, and any present-day geological activity, including potential subsurface deep oceans or possible current activity. Additionally, hyperspectral imaging will enable mapping the surface composition and identifying the potential presence of material that may point to a subsurface ocean, such as ammonia-bearing species. Rings and Small Moons: Imaging observations elucidate the physical processes that contribute to the complex ring-moon system’s inferred unstable state. Imaging surveys will seek smaller moons and other debris that could provide evidence of past collisions, while precise astrometric data of moons will determine the current dynamical state of the system. Many of Uranus' rings are exceptionally narrow, and images of the rings covering a broad range of longitudes, and high-resolution images of features within the rings will reveal how these rings are confined and maintained, as well as illustrating the rings' internal structure and dynamics. Images of the rings and moons obtained at a variety of wavelengths and lighting conditions are also needed to quantify the composition and the size distribution of the small satellites and ring particles.

K M Sayanagi↗

DOE OSTI2021

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Abstract Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems. However, the present paradigm involves time-intensive manual analysis that is inherently biased, error-prone, and unable to accommodate the large volumes of data produced by modern instrumentation. While more automated approaches have been proposed, many are not robust to a high variety of data, and do not generalize well to diverse microstructural features and material systems. Here, we present a flexible, semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems: (1) epitaxial heterostructures of SrTiO 3 /Ge, (2) La 0.8 Sr 0.2 FeO 3 thin films, and (3) MoO 3 nanoparticles. We demonstrate that the few-shot learning method is more robust against noise, more reconfigurable, and requires less data than conventional image analysis methods. This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Understanding Portability of Automotive Workload: A Case Study with the Points-to-Image Kernel in SYCL on Heterogeneous Computing Platforms

SYCL is a promising programming model for heterogenous computing across vendors’ devices. In this paper, we study whether SYCL can be applied to an automotive workload and its portability on heterogeneous computing platforms. We explain the automotive benchmark, describe our implementations and optimizations of the benchmark, and evaluate the performance of the benchmarks using SYCL and other programming models on heterogeneous computing devices. The study also allows us to have a better understanding of portability of the benchmark across these platforms.

Jin, Zheming↗

NASA NTRS2005

Wavefront Amplitude Variation of TPF's High Contrast Imaging Testbed: Modeling and Experiment

Knowledge of wavefront amplitude is as important as the knowledge of phase for a coronagraphic high contrast imaging system. Efforts have been made to understand various contributions of the amplitude variation in Terrestrial Planet Finder's (TPF) High Contrast Imaging Testbed (HCIT). Modeling of HCIT with as-built mirror surfaces has shown an amplitude variation of 1.3% due to the phase-amplitude mixing for the testbed's front-end optics. Experimental measurements on the testbed have shown the amplitude variation is about 2.5% with the testbed's illumination pattern has a major contribution as the low order amplitude variation.

coronagraph↗

NASA NTRS1990

Pyramid image codes

All vision systems, both human and machine, transform the spatial image into a coded representation. Particular codes may be optimized for efficiency or to extract useful image features. Researchers explored image codes based on primary visual cortex in man and other primates. Understanding these codes will advance the art in image coding, autonomous vision, and computational human factors. In cortex, imagery is coded by features that vary in size, orientation, and position. Researchers have devised a mathematical model of this transformation, called the Hexagonal oriented Orthogonal quadrature Pyramid (HOP). In a pyramid code, features are segregated by size into layers, with fewer features in the layers devoted to large features. Pyramid schemes provide scale invariance, and are useful for coarse-to-fine searching and for progressive transmission of images. The HOP Pyramid is novel in three respects: (1) it uses a hexagonal pixel lattice, (2) it uses oriented features, and (3) it accurately models most of the prominent aspects of primary visual cortex. The transform uses seven basic features (kernels), which may be regarded as three oriented edges, three oriented bars, and one non-oriented blob. Application of these kernels to non-overlapping seven-pixel neighborhoods yields six oriented, high-pass pyramid layers, and one low-pass (blob) layer.

Watson, Andrew B.↗

NASA NTRS2018

Developing a Novel Platform for Characterizing Thermoelectric Materials for Uncooled Detectors for Land Imaging Applications

Thermal land imaging (imaging at ~8-14 micron optical wavelength) is an essential tool for understanding and managing terrestrial freshwater resources. Current thermal imaging instruments employ low temperature detectors, which require cryocoolers. Consequently, cost-saving reductions in size, weight, and power can be achieved by employing uncooled detectors. One uncooled detector concept, which NASA is pursuing, is a thermopile detector with sub-micron thick doped-Si thermoelectric materials. In order to characterize the thermoelectric properties of the doped silicon, we designed and optimized a novel apparatus. This simple apparatus measures the Seebeck coefficient with thermally isolated stages and LABVIEW automation. We optimized thermal stability using PID tuning and optimized the thermal contact between the thin film samples and stages using electrically conductive springs. Utilizing our apparatus, we measured the Seebeck coefficient of 0.45 micron thick phosphorus-doped single crystal Si samples bonded to alumina substrates. Using these Seebeck coefficient measurements and four-wire electrical resistivity measurements, we determined the relationship between the thermoelectric figure of merit and dopant concentration. These characterization results for doped-Si will guide our thermopile detector design to provide an optimal and competitive detector alternative for future thermal imaging instruments.

Reid, Riley A.↗

NASA NTRS1992

High resolution imaging at Palomar

For the last two years we have embarked on a program of understanding the ultimate limits of ground-based optical imaging. We have designed and fabricated a camera specifically for high resolution imaging. This camera has now been pressed into service at the prime focus of the Hale 5 m telescope. We have concentrated on two techniques: the Non-Redundant Masking (NRM) and Weigelt's Fully Filled Aperture (FFA) method. The former is the optical analog of radio interferometry and the latter is a higher order extension of the Labeyrie autocorrelation method. As in radio Very Long Baseline Interferometry (VLBI), both these techniques essentially measure the closure phase and, hence, true image construction is possible. We have successfully imaged binary stars and asteroids with angular resolution approaching the diffraction limit of the telescope and image quality approaching that of a typical radio VLBI map. In addition, we have carried out analytical and simulation studies to determine the ultimate limits of ground-based optical imaging, the limits of space-based interferometric imaging, and investigated the details of imaging tradeoffs of beam combination in optical interferometers.

Kulkarni, Shrinivas R.↗

DOE OSTI2024

The influence of laser energy on deuterium emission characteristics from a Zircaloy-4 plasma

Laser-produced plasma coupled with optical emission spectroscopy (OES) is a promising technique for detecting certain isotopes, with unique capabilities such as standoff and rapid detection and minimal to no sample preparation requirements. The key figure-of-merit for isotopic analysis using optical spectroscopy tools is the linewidth relative to the isotope shift. Although the isotopes of hydrogen (1H, 2H, and 3H) possess large isotopic shifts (1H–2H ≈ 180 pm, 1H–3H ≈ 240 pm), being a light element, the H transitions are susceptible to various broadening mechanisms in the plasma environment. One of the critical parameters that influence the linewidth of a transition in an LPP is the incident laser energy. In the present study, we evaluated the role of laser energy on plume expansion dynamics, deuterium emission intensity, and linewidth in a nanosecond laser-produced Zircaloy-4 plasma. The changes in 2Hα emission intensity and linewidth were investigated for varying laser fluence and time after plasma onset. Spatially resolved and spatially integrated OES were performed and compared to investigate the emission spectral features and linewidth of 2Hα. Monochromatic two-dimensional time-resolved imaging was also performed to understand the morphology of the deuterium and protium emission relative to all species in the plume. Our results showed that 1Hα and 2Hα emissions predominantly occur closer to the target. Measurements of 2Hα linewidth approached similar values at later times of plasma evolution regardless of the laser energy. The linewidths of the 2Hα transition showed insignificant differences between spatially resolved and spatially integrated measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2001

Reaction Mechanisms and Particle Interaction in Burning Two-Phase Systems

The main objective of this research is to understand the mechanisms by which particle interactions affect ignition and combustion in the two-phase systems. Combustion of metal aerosols representing the two-phase systems is carried out in the microgravity environment enabling one to avoid the buoyant flows that mask the particle motion due to the particle-particle interaction effects. In addition, relatively large, e.g., 100 micron diameter particles can be used, that remain aerosolized (i.e., do not fall down as they would at normal gravity) so that their behavior ahead, behind, and within the propagating flame can be resolved optically. An experimental apparatus exploiting this approach has been designed for the 2.2-s drop tower microgravity experiments. A typical experiment includes fluidizing metal particles under microgravity in an acoustic field, turning off the acoustic exciter, and igniting the created aerosol at a constant pressure using a hot wire igniter. The flame propagation and details of the individual particle combustion and particle interactions are studied using high-speed movie and video cameras coupled with microscope lenses to resolve individual particles. Recorded flame images are digitized and various image processing techniques including flame position tracking, color separation, and pixel by pixel image comparisons are employed to understand the processes occurring in the burning aerosols. Condensed combustion products are collected after each experiment for the phase, composition, and morphology analyses. New experiments described in this paper address combustion of Ti and Al particle clouds in air and combustion of Mg particle clouds in CO2. In addition, microgravity combustion experiments have been conducted with the particles of the newly produced Al-Mg mechanical alloys aerosolized in air.

Dreizin, Edward L.↗

DOE OSTI2023

Mapping foliar photosynthetic capacity in sub-tropical and tropical forests with UAS-based imaging spectroscopy: Scaling from leaf to canopy

Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemical and morphological traits at the canopy scale, but there is only limited evidence for retrieving canopy photosynthetic capacity (e.g., maximum carboxylation rate, V c,max and maximum electron transport rate, J max ). Moreover, the effect of canopy structure within forest communities on scaling up spectra-trait relationships from leaf to canopy level is not well known. To advance the spectra-trait approach and enable the estimation of key traits using remote sensing, we collected imaging spectroscopy data from an Unoccupied Aerial System (UAS) platform over two forest sites in China (a subtropical forest in Mt. Dinghu and a tropical rainforest in Xishuangbanna). At these sites, we also collected ground measurements of leaf spectra and traits, including biochemical (leaf nitrogen, phosphorus, chlorophyll, and water content), morphological (leaf mass per area, LMA) and physiological (V c,max25 and J max25 ) traits (n=135 tree-crowns from 42 species across two sites). Using a partial least-squares regression (PLSR) approach, we built and tested spectra-trait models with repeated cross-validation. The spectral models developed with leaf spectra were directly transferred to canopy spectra to evaluate the effect of canopy structure. Here we further applied canopy spectral models to map these traits at individual tree-crown scale. The results demonstrate that (1) UAS-based canopy spectra can be used to estimate V c,max (R 2 =0.55, nRMSE=11.79%), Jmax (R 2 =0.54, nRMSE=12.34%), and five additional foliar traits (R 2 =0.38-0.60, nRMSE=10.11-13.56%) at the tree-crown scale with demonstrated generalizability across two sites; (2) canopy structure strongly affects the spectratrait relationships from leaf to canopy level, but the effects vary considerably across foliar traits and cannot be well captured by the 4SAIL canopy radiative transfer model. UAS-based imaging spectroscopy maps large variability in all foliar traits (including physiological traits) with spatially explicit information, reproducing the field-observed inter- and intra-specific variations. These results demonstrate the capability of using UAS-based imaging spectroscopy for characterizing the variability of foliar physiological traits at individual tree-crown scale over forest landscapes and highlight the similar generalizability but different biophysical mechanisms underlying spectra-trait relationships at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Atomic-scale secondary electron imaging for heterogeneous catalysis research

Surface characterization at the atomic scale is essential for understanding the catalytic properties of supported metal nanoparticles. Secondary electron (SE) imaging in scanning transmission electron microscopy (STEM) provides three-dimensional surface topographic information, enabling the characterization of the size, morphology, and distribution of supported nanoparticles. Furthermore, real-time observation of catalyst materials in a gaseous environment would enhance the understanding of catalyst dynamics under operational conditions. Ongoing technical developments in SE-STEM and advancements in computational methods are expected to facilitate atomic-scale surface observations and enable more quantitative and statistical analyses. This progress will not only elucidate fundamental mechanisms at the atomic level but also provide comprehensive and universal insights into catalyst performances. Here, this minireview showcases the recent advancements and research findings in surface-sensitive SE imaging in STEM for the characterization of active catalyst materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

Imaging shapes of atomic nuclei in high-energy nuclear collisions

Atomic nuclei are self-organized, many-body quantum systems bound by strong nuclear forces within femtometre-scale space. These complex systems manifest a variety of shapes, traditionally explored using non-invasive spectroscopic techniques at low energies. However, at these energies, their instantaneous shapes are obscured by long-timescale quantum fluctuations, making direct observation challenging. Here we introduce the collective-flow-assisted nuclear shape-imaging method, which images the nuclear global shape by colliding them at ultrarelativistic speeds and analysing the collective response of outgoing debris. This technique captures a collision-specific snapshot of the spatial matter distribution within the nuclei, which, through the hydrodynamic expansion, imprints patterns on the particle momentum distribution observed in detectors. We benchmark this method in collisions of ground-state uranium-238 nuclei, known for their elongated, axial-symmetric shape. Our findings show a large deformation with a slight deviation from axial symmetry in the nuclear ground state, aligning broadly with previous low-energy experiments. This approach offers a new method for imaging nuclear shapes, enhances our understanding of the initial conditions in high-energy collisions and addresses the important issue of nuclear structure evolution across energy scales.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Imaging biomarkers in neurodegeneration: current and future practices

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course “Biomarkers in neurodegenerative diseases”. In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Combining Multicolor FISH with Fluorescence Lifetime Imaging for Chromosomal Identification and Chromosomal Sub Structure Investigation

Understanding the structure of chromatin in chromosomes during normal and diseased state of cells is still one of the key challenges in structural biology. Using DAPI staining alone together with Fluorescence lifetime imaging (FLIM), the environment of chromatin in chromosomes can be explored. Fluorescence lifetime can be used to probe the environment of a fluorophore such as energy transfer, pH and viscosity. Multicolor FISH (M-FISH) is a technique that allows individual chromosome identification, classification as well as assessment of the entire genome. Here we describe a combined approach using DAPI as a DNA environment sensor together with FLIM and M-FISH to understand the nanometer structure of all 46 chromosomes in the nucleus covering the entire human genome at the single cell level. Upon DAPI binding to DNA minor groove followed by fluorescence lifetime measurement and imaging by multiphoton excitation, structural differences in the chromosomes can be studied and observed. This manuscript provides a blow by blow account of the protocol required to perform M-FISH-FLIM of whole chromosomes.

59 BASIC BIOLOGICAL SCIENCES↗