Our lab's goal is to create entirely new technologies that address unanswered needs in the lab or the clinic. Our major focus is on ionizing radiation and how it can be used for imaging and therapeutic applications. Combining a variety of physical and engineering approaches, our work spans a wide breadth of application, from answering biological questions at the single cell level to improving the accuracy of radiation treatments.
It is becoming increasingly apparent that cell populations are heterogeneous in their functions, disease states and response to therapy. Substantial interest is now devoted to methods that operate at the single-cell level, as opposed to bulk analyses that can only measure the average properties of a population of cells. Fluorescence methods have long been used to measure molecular processes in single living cells. However, a vast number of small molecules remain invisible to fluorescence probing for lack of inherent fluorescence; moreover, most small molecules cannot be fluorescently labeled without altering their biochemical activity.
We are currently developing a new imaging tool called the radioluminescence microscope that can image radionuclide-labeled molecules in a standard microscopy environment, on the level of single cells. Virtually any molecule can be labled using beta-emitting isotopes, and imaged with high sensitivity with this approach.
Principle of Radioluminescence Microscopy
The key to radioluminescence microscopy is the scintillator. This inorganic crystal turns the ionization from incoming a beta particle into light, which can be visualized using a highly sensitive optical microscope. Single radioactive molecules can thereby be localized and entire images showing the distribution of such molecules can be reconstructed.
Cellular Imaging of Radiopharmaceuticals
As a demonstration, non-Hodgkins lymphoma cells were labeled with 64Cu-labeled rituximab, an anticancer monoclonal antibody. Binding of the drug to single cells can be clearly visualized using radioluminescence microscopy (RLM). By fusing the brightfield (BF) and radioluminescence (RLM) images together, one can verify that radioluminescence is coming specifically from single cells. Fluorescence can be used to verify the binding of the drug.
Radioluminescence (FDG; red), bioluminescence (FLuc; green) and fluorescence (nuclear stain; blue) can be acquired on the same instrument and combined into a single image to provide a multiparametric view of cellular states and behaviors, with unmatched spatial resolution.
Our current research efforts are directed both at improving the technology and applying it in a biomedical context. With regards to the first goal, we are investigating new types of thin-film scintillators that can provide higher spatial resolution and sensitivity. We have also developed a modular, easy-to-build platform to enable other labs to adopt this technique without requiring a dedicated bioluminescence microscope. Last, we are improving image reconstruction by exploiting the insight afforded by in silico simulations. We plan to release our software in the near future. With regards to application, our focus is primarily on the study of cancer metabolism using FDG and drug resistance using radiolabeled drugs.
Kim TJ, Türkcan S & Pratx G, “Modular low-light microscope for imaging cellular bioluminescence and radioluminescence”, Nat. Protoc. 12, pp. 1055–1076, Apr 2017
Sengupta D & Pratx G, "Single-cell characterization of FLT uptake with radioluminescence microscopy," J. Nucl. Med. 57(7), pp. 1136-1140, July 2016
Kim TJ, Tuerkcan S, Ceballos A & Pratx G, "Modular platform for low-light microscopy," Biomed. Opt. Express 6(11), pp. 4585-4598, Oct 2015
Natarajan A, Türkcan S, Gambhir SS & Pratx G, "A multiscale framework for imaging radiolabeled therapeutics," Mol. Pharm. 2015 12 (12), pp. 4554–4560, Oct 2015
Sengupta D, Miller S, Marton Z, Chin F, Nagarkar V, & Pratx G. "Bright Lu2O3:Eu Thin-Film Scintillators for High-Resolution Radioluminescence Microscopy.", Adv Healthc Mater 4(14), pp. 2064-2070, Jul 2015
Tüerkcan S., Nguyen J, Vilalta M, Shen B, Chin F, & Pratx G. "Single-Cell Analysis of [18F]Fluorodeoxyglucose Uptake by Droplet Radiofluidics." Anal Chem 87(13), pp. 6667-6673, Jul 2015
Pratx G, Chen K, Sun C, Axente M, Sasportas L, Carpenter C & Xing L, "High-Resolution Radioluminescence Microscopy of FDG Uptake by Reconstructing the Beta Ionization Track", J. Nucl. Imag. 54(10) pp.1841-1846, Oct. 2013
Pratx G, Chen K, Sun C, Martin L, Carpenter CM, Olcott PD & Xing L, "Radioluminescence microscopy: Measuring the heterogeneous uptake of radiotracers in single living cells", PLOS One7(10), e46285, Oct. 2012
Single-Cell Tracking with PET
Methods for spatiotemporal cell tracking are becoming increasingly important as interest in cell-based therapies continues to grow. Such methods can shed light on biodistribution and viability of cells, which may be important markers of treatment efficacy. In addition, cell tracking is potentially valuable for studying circulating tumor cells, a key to understanding cancer metastasis. We have recently developed a method for reconstructing the continuous spatiotemporal trajectory of moving point-like sources using a preclinical PET system. Our approach recognizes that current tomographic reconstruction methods (such as ML-EM) are not efficient for tracking point-like sources in real time. Our results thus far suggest that would be feasible to track single-cells labeled with an efficient radiotracer using this approach. We are currently in the process of refining and testing this novel approach.
Example of source tracking
To demonstrate cell tracking in a controlled environment, we use water in oil microdroplets to mimic moving cells. These droplets are loaded with [18F]FDG and flown through a helical piece of tubing while PET data are acquired. The reconstructed tracjectory accurately represents the true spatiotemporal trajectory of the microdroplet.
Ouyang Y, Kim TJ & Pratx G, "Evaluation of a BGO-Based PET System for Single-Cell Tracking Performance by Simulation and Phantom Studies," Mol. Imaging 15, pp. 1-8, May 2016 [PubMed]
Lee KS, Kim TJ, Pratx G, “Single-Cell Tracking with PET using a Novel Trajectory Reconstruction Algorithm,” IEEE Trans Med Imag, pp. 994-1003, Nov 2014 [Pubmed]
Droplet-Based Single-Cell Radiometric Assay
This project aims to develop an innovative methodology for measuring radionuclide uptake in single cells with throughput similar to flow cytometer. Flow cytometry in its current form can only interrogate cellular states by detecting fluorescence emissions from single cells, a process that excludes small-molecule compounds that are neither intrinsically fluorescent nor can be labeled with a fluorophore. Many small molecules can be labeled with beta-emitting radionuclides such as 11C, 18F, 32P, 35S, 64Cu, and 124I, which makes the proposed approach almost universal with respect to the range of molecules that can be utilized. However, detecting radionuclides within a flow cytometer poses a major challenge. Due to the high throughput, each cell can only be measured for a few milliseconds, which is too short for a significant number of radioactive decays to occur. Thus, we plan to use radiation responsive sensors to chemically record and store the number of radioactive decays that occur within each single cell over a prolonged exposure. Using microfluidics technology, we encapsulate radioactive single cells and radiofluorogenic sensors (which become fluorescent upon exposure to ionizing radiation) inside microdroplets. This helps ensure that the sensors are uniquely associated with a single cell. After complete decay of the radionuclide label, the fluorescence of each droplet is individually read out to estimate the number of radioactive decays that occurred within each single cell.
- Gallina ME, Kim TJ, Shelor M, Vasquez J, Mongersun A, Kim M, Tang SKY, Abbyad P & Pratx G, “Towards a droplet-based single-cell radiometric assay”, Anal. Chem. 89 (12), pp 6472–6481, May 2017
X-ray Molecular Imaging
Molecular imaging offers the ability to probe subtle biological signals that are characteristic of disease onset and progression. It can also monitor the response of a disease to treatment before any anatomical changes occur. Our research explores two emerging imaging techniques that can probe multiple disease biomarkers in a non-invasive fashion. In both imaging techniques, a contrast agent is introduced that can produce a distinguishable signal when irradiated with X-ray. This feature makes it possible to obtain molecular information during a CT examination. The two imaging techniques differ in the following: In X-ray luminescence imaging, the contrast agent is a radioluminescent nanoparticle that produces near-infrared light under X-ray irradiation. In X-ray fluorescence imaging, the contrast agent is a high-atomic-number element that emits a characteristic X-ray signal under irradiation.
Pratx G, Carpenter CM, Sun C & Xing L, "Tomographic molecular imaging of X-ray-excitable nanoparticles", Opt. Lett. 35(20), pp. 3345-3347, Oct. 2010 [Pubmed]
Pratx G, Carpenter CM, Sun C & Xing L, "X-Ray luminescence computed tomography via selective excitation: A feasibility study", IEEE Trans. Med. Imag. 29(12), pp. 1992-1999, Dec. 2010 [Pubmed]
Sun C, Pratx G, Carpenter CM, Liu HG, Cheng Z, Gambhir SS & Xing L, "Synthesis and radioluminescence of PEGylated Eu3+-dopednanophosphors as bioimaging probes", Adv. Mater., 23(24), pp. H195-H199, Jun. 2011 [Pubmed]
Bazalova M, Kuang Y, Pratx G & Xing L, "Investigation of x-ray fluorescence computed tomography (XFCT) and K-edge imaging", IEEE Trans. Med. Imag. 31(8), pp. 1620-1627, Aug 2012 [Pubmed]
Kuang Y, Pratx G, Bazalova M, Meng B, Qian J & Xing L, "First demonstration of multiplexed X-ray fluorescence computed tomography (XFCT) imaging", IEEE Trans. Med. Imag. 32(2), pp. 262-267, Feb 2013 [Pubmed]
Ahmad M, Pratx G, Bazalova M & Xing, L., "X-Ray Luminescence and X-Ray Fluorescence Computed Tomography: New Molecular Imaging Modalities," Access, IEEE , vol.2, no., pp.1051,1061, 2014 [Pubmed]
High-Performance Medical Computing
Efficient computing now requires using multi- and many-core processors--which embed multiple computing elements in a single chip. New medical imaging algorithms must be designed that are aware of the parallel computing capabilities of new computer hardware. In our work, we develop medical imaging algorithms adapted to these new parallel architectures. Clinically, those algorithms can shorten the time required to process data by as much as tenfold, removing a critical bottleneck in the clinical workflow. One of the most promising platform for medical computing is the graphics processing unit: originally a gadget sought by serious computer gamers, it is now used as an inexpensive supercomputer on-a-chip by researchers in all fields.
Pratx G, Chinn G, Olcott PD & Levin CS, "Fast, accurate and shift-varying line projections for iterative reconstruction using the GPU", IEEE Trans. Med. Imag. 28(3), pp. 435-445, Mar. 2009 [Pubmed]
Pratx G & Xing L, "Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce", J. Biomed. Opt. 16(12) pp. 125003, Dec. 2011 [Pubmed]