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1.  3D Printing of Preclinical X-ray Computed Tomographic Data Sets 
Three-dimensional printing allows for the production of highly detailed objects through a process known as additive manufacturing. Traditional, mold-injection methods to create models or parts have several limitations, the most important of which is a difficulty in making highly complex products in a timely, cost-effective manner.1 However, gradual improvements in three-dimensional printing technology have resulted in both high-end and economy instruments that are now available for the facile production of customized models.2 These printers have the ability to extrude high-resolution objects with enough detail to accurately represent in vivo images generated from a preclinical X-ray CT scanner. With proper data collection, surface rendering, and stereolithographic editing, it is now possible and inexpensive to rapidly produce detailed skeletal and soft tissue structures from X-ray CT data. Even in the early stages of development, the anatomical models produced by three-dimensional printing appeal to both educators and researchers who can utilize the technology to improve visualization proficiency. 3, 4 The real benefits of this method result from the tangible experience a researcher can have with data that cannot be adequately conveyed through a computer screen. The translation of pre-clinical 3D data to a physical object that is an exact copy of the test subject is a powerful tool for visualization and communication, especially for relating imaging research to students, or those in other fields. Here, we provide a detailed method for printing plastic models of bone and organ structures derived from X-ray CT scans utilizing an Albira X-ray CT system in conjunction with PMOD, ImageJ, Meshlab, Netfabb, and ReplicatorG software packages.
doi:10.3791/50250
PMCID: PMC3671719  PMID: 23542702
Medicine; Issue 73; Anatomy; Physiology; Molecular Biology; Biomedical Engineering; Bioengineering; Chemistry; Biochemistry; Materials Science; Engineering; Manufactured Materials; Technology; Animal Structures; Life Sciences (General); 3D printing; X-ray Computed Tomography; CT; CT scans; data extrusion; additive printing;  in vivo imaging; clinical techniques; imaging
2.  Dual tracer imaging of SPECT and PET probes in living mice using a sequential protocol 
Over the past 20 years, multimodal imaging strategies have motivated the fusion of Positron Emission Tomography (PET) or Single Photon Emission Computed Tomography (SPECT) scans with an X-ray computed tomography (CT) image to provide anatomical information, as well as a framework with which molecular and functional images may be co-registered. Recently, pre-clinical nuclear imaging technology has evolved to capture multiple SPECT or multiple PET tracers to further enhance the information content gathered within an imaging experiment. However, the use of SPECT and PET probes together, in the same animal, has remained a challenge. Here we describe a straightforward method using an integrated trimodal imaging system and a sequential dosing/acquisition protocol to achieve dual tracer imaging with 99mTc and 18F isotopes, along with anatomical CT, on an individual specimen. Dosing and imaging is completed so that minimal animal manipulations are required, full trimodal fusion is conserved, and tracer crosstalk including down-scatter of the PET tracer in SPECT mode is avoided. This technique will enhance the ability of preclinical researchers to detect multiple disease targets and perform functional, molecular, and anatomical imaging on individual specimens to increase the information content gathered within longitudinal in vivo studies.
PMCID: PMC3484419  PMID: 23145357
Dual tracer imaging; trimodal imaging; Positron Emission Tomography (PET); Single Photon Emission Computed Tomography (SPECT); X-ray Computed Tomography (CT); nuclear imaging
3.  Imaging and Analysis of Pseudomonas aeruginosa Swarming and Rhamnolipid Production ▿ † 
Applied and Environmental Microbiology  2011;77(23):8310-8317.
Many bacteria spread over surfaces by “swarming” in groups. A problem for scientists who study swarming is the acquisition of statistically significant data that distinguish two observations or detail the temporal patterns and two-dimensional heterogeneities that occur. It is currently difficult to quantify differences between observed swarm phenotypes. Here, we present a method for acquisition of temporal surface motility data using time-lapse fluorescence and bioluminescence imaging. We specifically demonstrate three applications of our technique with the bacterium Pseudomonas aeruginosa. First, we quantify the temporal distribution of P. aeruginosa cells tagged with green fluorescent protein (GFP) and the surfactant rhamnolipid stained with the lipid dye Nile red. Second, we distinguish swarming of P. aeruginosa and Salmonella enterica serovar Typhimurium in a coswarming experiment. Lastly, we quantify differences in swarming and rhamnolipid production of several P. aeruginosa strains. While the best swarming strains produced the most rhamnolipid on surfaces, planktonic culture rhamnolipid production did not correlate with surface growth rhamnolipid production.
doi:10.1128/AEM.06644-11
PMCID: PMC3233055  PMID: 21984238

Results 1-3 (3)