Single cell analysis has become a crucial goal since cellular heterogeneity was acknowledged as one of the greatest challenges in cancer therapeutics. Radioactive probes can play an important role in single cell study thanks to its unique capability of tracking small molecules with minimal modification of their chemical structure. Our lab has recently developed a new technique known as radioluminescence microscopy (RLM) to measure the amount of radiotracer in single cells. Yet, RLM can image only up to about 100 cells and lacks capability of integrating with subsequent sample processing such as cell sorting. Here we introduce a robust, high throughput single cell radiometry based on radiofluorogenesis and droplet optofluidics. As an example, we quantitated [18F]-fluorodeoxyglucose radiotracer uptake in single human breast cancer cells and assessed cellular heterogeneity in single cell metabolism.
With 2500 scanners installed and 2 million scans performed last year in the United States, positron emission tomography (PET) has emerged as one of the most important imaging tools in oncology. The widespread availability of PET imaging and radiochemistry facilities has stirred the development of new PET tracers. The current pipeline for radiotracer development uses analytical tools that assume that the targeted cell populations are homogeneous. For instance, in vivo imaging tests reduce results to a single quantitative metrics, the standardized uptake value, which represents the average behavior of millions of cells. In reality, tumors and other organs are formed by clonally heterogeneous collections of different cell types; the average of these cells is not necessarily representative of the individual cells that make up the population. To give an example, the PET signal measured in a tumor is often ascribed to cancer cells alone when in fact other cell types such as immune cells and stromal cell contribute significantly to the average signal. These considerations have led to the development of a novel method, radioluminescence microscopy (RLM), that can characterize radiotracer uptake heterogeneity at the level of single cells. RLM combines optical and ionizing radiation to yield high-resolution microscopic images of cells and their interactions with radiotracers. The fundamental principles of RLM will be explained and its application to radiotracer discovery and validation will be presented.
Radionuclides are used for sensitive and specific detection of small molecules in vivo and in vitro. Recently, radioluminescence microscopy extended their use to single-cell studies. Here we propose a new single-cell radioisotopic assay that improves throughput while adding sorting capabilities. The new method uses fluorescence-based sensor for revealing single-cell interactions with radioactive molecular markers. This study focuses on comparing two different experimental approaches. Several probes were tested and Dihydrorhodamine 123 was selected as the best compromise between sensitivity, brightness and stability. The sensor was incorporated either directly within the cell cytoplasm (direct approach), or it was coencapsulated with radiolabeled single-cells in oil-dispersed water droplets (droplet approach). Both approaches successfully activated the fluorescence signal following cellular uptake of 18F-fluorodeoxyglucose (FDG) and external Xrays exposure. The direct approach offered single-cell resolution and longtime stability ( > 20 hours), moreover it could discriminate FDG uptake at labelling concentration as low as 300 μCi/ml. In cells incubated with Dihydrorhodamine 123 after exposure to high radiation doses (8-16 Gy), the fluorescence signal was found to increase with the depletion of ROS quenchers. On the other side, the droplet approach required higher labelling concentrations (1.00 mCi/ml), and, at the current state of art, three cells per droplet are necessary to produce a fluorescent signal. This approach, however, is independent on cellular oxidative stress and, with further improvements, will be more suitable for studying heterogeneous populations. We anticipate this technology to pave the way for the analysis of single-cell interactions with radiomarkers by radiofluorogenic-activated single-cell sorting.
Optical and ionizing radiation are two physical ways in which we can probe the living world. Until recently, these forms
of radiation were used in distinct imaging and therapeutic applications—radiation therapy, photodynamic therapy, X-ray
imaging, and diffuse optical tomography, to name a few. It has now been recognized that physical phenomena in which
ionizing radiation and light are inherently coupled may provide powerful new capabilities for imaging and treating
diseases. This presentation will review the physics and applications of radioluminescence, with a particular focus on
molecular imaging. One such method, X-ray luminescence computed tomography (XLCT), uses narrow kilovolt X-ray
beams to stimulate optical emissions from biologically targeted radioluminescent nanoparticles, thus providing high-resolution
images even deep in tissue. A different phenomenon, Cherenkov luminescence, can also be harnessed to
localize radiopharmaceuticals in vivo, allowing surgeons to visualize the molecular status of the tissues they are
resecting. Recent progress towards routine implantation of these methods will be reviewed and sources of endogenous
radioluminescence signal will be discussed.
X-ray induced photoacoustic tomography, also called X-ray acoustic computer tomography (XACT) is investigated in
this paper. Short pulsed (μs-range) X-ray beams from a medical linear accelerator were used to generate ultrasound. The ultrasound signals were collected with an ultrasound transducer (500 KHz central frequency) positioned around an
object. The transducer, driven by a computer-controlled step motor to scan around the object, detected the resulting
acoustic signals in the imaging plane at each scanning position. A pulse preamplifier, with a bandwidth of 20 KHz–2
MHz at −3 dB, and switchable gains of 40 and 60 dB, received the signals from the transducer and delivered the
amplified signals to a secondary amplifier. The secondary amplifier had bandwidth of 20 KHz–30 MHz at −3 dB, and a
gain range of 10–60 dB. Signals were recorded and averaged 128 times by an oscilloscope. A sampling rate of 100 MHz
was used to record 2500 data points at each view angle. One set of data incorporated 200 positions as the receiver moved
360°. The x-ray generated acoustic image was then reconstructed with the filtered back projection algorithm. The twodimensional
XACT images of the lead rod embedded in chicken breast tissue were found to be in good agreement with
the shape of the object. This new modality may be useful for a number of applications, such as providing the location of
a fiducial, or monitoring x-ray dose distribution during radiation therapy.
Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes.
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