This work has been funded by National Cancer Institute's grants R01 CA120368, R01 CA109558 (KMT, RWH, FEG, BWP), RO1 CA132750 (MJ, BWP) and K25 CA138578 (FL), and Canadian Institutes of Health Research postdoctoral fellowship award (KMT). The development of the fluorescence tomography system was partially funded by Advanced Research Technologies (Montreal, QC).

1. Animal Preparation
<ol>
 <li>Anesthetize nude mouse (Charles River, Wilmington, MA) with intra-peritoneal injection of ketamine-xylazine (100 mg/kg:10 mg/kg i.p.). </li>
 <li>Place mouse in stereotactic frame, make an incision into the scalp on the left-side of the skull and, using an 18-gauge needle, create a 1 mm-diameter hole into the skull 2 mm from the central line and 2 mm behind the bregma. </li>
 <li>Inject 5&times;105 U251 human neuronal glioblastoma cells (kindly provided by Dr. Mark Israel at Dartmouth College, Hanover, NH) in 5 &mu;l of phosphate buffer solution into the left cerebral hemisphere at a depth of approximately 2 mm below the surface of the brain. Use a Hamilton micro-syringe18 and a blunt ended 27-gauge needle for cell implantation and insert the tip of the needle 3 mm from the outer surface of the skull and then withdraw 1 mm to create a pocket for the cells. </li>
 <li>Suture incision site and allow recovery from surgery. </li>
 <li>Wait ~14 days to allow the tumor to grow before imaging. </li>
</ol>
2. Fluorescence Tomography System Calibration
<ol>
 <li>On the day of mouse imaging, initiate system and allow lasers and light detectors to warm-up for approximately 20 minutes to avoid drifts in system sensitivity. </li>
 <li>Place a 100&deg;-by-4&deg; engineered line diffusor (Thorlabs, Newton, NJ) at the direct center of the imaging gantry, normal to the excitation laser: a picosecond-pulsed 80-MHz multimode 635 nm laser diode (PicoQuant Photonics North America Inc., Westfield, MA). Adjust the angle of the diffusor to maximize the amount of signal detected by all five light collection channels. A complete description of the imaging geometry is provided elsewhere11,14,15.</li>
 <li>Place OD 2 neutral density filters (Thorlabs, Newton, NJ) in front of all fluorescence detection photomultiplier tubes (PMT) and OD 1 neutral density filters (Thorlabs, Newton, NJ) in front of all transmittance detection PMTs. Collect 100 temporal pulse spread profiles (TPSF) of the laser, each with a 1-s integration time. </li>
 <li>Normalize each TPSF by the laser reference, correct for temporal drift in the laser reference, and average over all iterations for each detector. These averaged TPSFs are the detector-specific instrument response functions (IRF) used in the optical image reconstruction. </li>
</ol>
3. Imaging Protocol
<ol>
 <li>Anesthetize the mouse with 2% isoflurane in oxygen (1 L/min). </li>
 <li>Inject 1 nanomole of IRDye 800CW-EGF and 1 nanomole of Alexa Fluor 647 in 100 &mu;l of phosphate buffer solution, intraperitoneally, 12 h prior to imaging to target epidermal growth factor receptor overexpression in the tumor. </li>
 <li>Place the mouse onto the fiberglass supports of the imaging bed, arranging the mouse so that its nose remains in a cone delivering isoflurane anesthesia. </li>
 <li>Ensure that the mouse is positioned appropriately on the bed: i.e., that when the bed is secured into the fluorescence tomography system the mouse is at the approximate center of the imaging gantry. This positioning can be guided by rotating the excitation laser 180&deg; about the mouse, ensuring that the focal point of the laser illuminates a point roughly on the center of the mouse from the perspective of the laser at all angles. </li>
 <li>Once positioned, carefully transfer the imaging bed and mouse to the microCT (eXplore Locus, GE Healthcare, London, ON) scanner and collect anatomical information at a resolution of 93-&mu;m isotropic for the whole head of the mouse. </li>
 <li>Visualize the CT image stack and choose the slice(s) to be imaged with the fluorescence tomography system. </li>
 <li>Carefully transfer the imaging bed and mouse back to the fluorescence tomography system. Choose the number of source positions to collect data about the mouse for each imaging slice (32), the integration time for each TPSF measurement (1 s), the number of iterations for each source position (10), and the position and number of desired imaging slices from the CT image stack from Step 3.6. The numbers in parentheses are typical values for each imaging parameter yielding ~ 5 minutes of data acquisition per imaging slice. </li>
 <li>Place triple notch filters (Chroma Technology Corp., Bellows Falls, VT) in front of the fluorescence detection PMTs, to restrict any laser light from reaching the fluorescence detectors, and OD 2 neutral density filters in front of the transmittance detection PMTs to avoid saturation of those detectors. </li>
 <li>Run the data acquisition software, collecting fluorescence and transmittance TPSFs at each defined source detector position and for each excitation wavelength (635 nm and 755 nm to excite the Alexa Fluor 647 and IRDye 800CW-EGF tracers, respectively). For every set of TPSFs collected, monitor and record the laser intensity with a reference PMT channel. </li>
</ol>
4. Image Reconstruction
<ol>
 <li>Determine the outer surface of the mouse and the location of the imaging bed support rods from the CT images and create masks that covers the confines of the mouse and the imaging rods separately.</li>
 <li>Use the mouse mask to produce a finite-element mesh of the animal using the NIRFAST software19. </li>
 <li>Localize the source and detector positions from the fluorescence tomography system on the surface of the mesh based on microCT and fluorescence spatial registration co-ordinates20. </li>
 <li>Remove optical data points associated with source or detector positions that interact with the location of the imaging bed support rods.</li>
 <li>Normalize data collected at each source detector position by the laser reference, correct for temporal drift in the laser reference, and correct for filter sensitivities, which were determined by experimental testing at time of purchase15. </li>
 <li>Take the Born Ratio of the data (fluorescence divided by transmittance) for each source-detector position and multiply with a forward model simulation of transmittance based on the finite-element animal mesh for uniform optical properties. This is done to mitigate errors associated with source- or detector-tissue coupling21, to calibrate the data to the model22, and to adjust data for other aspects of model-data mismatch23,24. </li>
 <li>Construct a data vector composed of the scaled difference of the born ratio data collected at both wavelengths. The scaling factor is chosen to maximize EGFR binding contrast. Perform time-domain image reconstruction with the calibrated difference data using the TPSF for each detection channel as an input, and create fluorescence maps of the contrast-enhanced targeted tracer15. </li>
</ol>
5. Representative Results
An example of a fluorescence reconstruction overlaid with a co-registered CT anatomical image from the head of a mouse with a U251 orthotopic glioma tumor is presented in Figure 1b. The center of mass of the glioma determined by the fluorescent reconstruction (Figure 1b) was within 1 mm of the tumor center of mass determined by contrast-enhance magnetic resonance imaging (Figure 1a). The CT and MRI images were co-registered based on a mutual-information transformation.
<img src="/files/ftp_upload/4050/4050fig1.jpg" alt="Figure 1" /> 
Figure 1. Contrast-enhanced (Gadolinium) magnetic resonance image of mouse head (a). The mouse was inoculated orthotopically with a U251 human glioma cell line. The location of the tumor, which absorbs more contrast agent than the normal brain, can be seen in the left cerebral hemisphere (right in image) and indicated by the white arrow. The corresponding computed tomography image (from the same location on the mouse head) is depicted in (b) with the epidermal growth factor targeted fluorescence minus the untargeted fluorescence reconstruction overlaid. The units of fluorescence are in inverse mm and relate to the absorption coefficient of bound targeted fluorescence multiplied by its quantum efficiency and by its concentration.

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No conflicts of interest declared.

Fluorescence tomography (FT) is a sensitive, ionizing radiation free molecular imaging modality based on visible and near-infrared light transport through biological tissue. Most of the interest in FT has been focused on its potential to expedite drug discovery and development in small animal experimental models1 and one key area of research has been the study of cancer biomarker expression and response to molecular therapies26. At present, there are two competing approaches to FT system design. The most common design is based on cooled charge-coupled device (CCD) cameras for fluorescence detection4-9. This design provides a high density of measurements, maximizing tissue sampling since each pixel in the CCD camera can detect light that has traveled a unique path through the tissue. However, CCD cameras have a limited dynamic range and read-out noise limits their ultimate sensitivity. The second design avoids the potential limitations of CCD camera detection by employing highly sensitive single-photon counting technology based on the use of such detectors as photomultiplier tubes or avalanche photodiodes10-13. The drawback of these more sensitive detection methods is that each detector can only collect light at a single point; therefore, to achieve dense tissue sampling, either many detectors have to be used (which is very expensive), or many projections have to be imaged with the same detector (which can be time consuming). While the optimal level of tissue sampling for small animal FT has not been agreed upon, and may vary on a case-by-case basis, it is agreed that single-photon counting instrumentation is better suited to explore the sensitivity limits of FT in terms of its ability to detect low concentrations of molecular markers. In this study, we provide a methodology for carrying out FT using single-photon counting detection instrumentation to localize tumors in mice. 
There are four critical steps involved to produce robust datasets with time-correlated single-photon counting FT. The first is the application of a suitable and straightforward calibration procedure. In the presented methodology, the respective sensitivities of each detection channel are accounted for by collecting a baseline measurement of excitation light transmitted through a line-diffusor designed to direct equal fractions of light to each detector15. Furthermore, the detected light during an experiment is continuously calibrated to the laser reference, in terms of both intensity and mean-time, which could fluctuate over time, by the operation of a laser reference channel11,15. The second critical step is the accurate collection and co-registration of anatomical imaging for guided fluorescence reconstructions. The FT data alone offers no anatomical information; therefore, in order to create a model of light transport that can be used to reconstruct the location of fluorescent sources within a specimen from the detected fluorescence at the surface of the specimen, the anatomy of the specimen in relation to the FT system must be accurately known. In our system, the anatomical information is acquired by a micro-computed tomography system with spatial coordinates that have been spatially registered with those of the FT system15,20. The third critical step involves ensuring that an optimal exposure (i.e., total photon detection time for each laser projection) is employed at every source-detector position. This is important for two reasons: first, to ensure that there is adequate signal-to-noise at each detection position and second to avoid detector saturation, which could damage the detection units. In order to achieve optimal exposure at each detector position, an automatic exposure control is employed, which essentially triangulates the optimum exposure from two, low-signal exposures14. The fourth critical step of the methodology is referencing the collected fluorescence data to the amount of transmitted excitation light. This referencing is often called the Born ratio, and provides many benefits for FT, with the main one being a mitigation of model-data mismatch errors23,24. The presented system was designed to detect both fluorescence and transmitted excitation light simultaneously by channeling the light in each detection channel into 2 separate photomultiplier tubes. By doing this, we avoid any effects of motion on the accuracy of the Born ratio.
With a robust dataset it hand, image reconstruction of time-domain data involves solving the inverse problem of the finite element mesh having the expression:
d=Jx
where d is a vector with n x m elements for n source-detector projections and m TPSF time gates; J is an n x m-by-l sensitivity matrix (or Jacobian), for l nodes in the mesh; and x is the vector of fluorescence optical properties in each node, having size l. d is the calibrated data collected during the experiment and J is simulated using the finite element solution to the time domain diffusion approximation of fluorescence transport25. The time-dimension of J is also convolved with the detector specific instrument response functions. x is a representation of the fluorescence map of interest and is solved for using a Levenberg-Marqardt non-negative least squares approach with Tikhonov regularization15. 
The methodology presented here, which describes a procedure capable of localizing fluorescently labeled tumors in mice using highly-sensitive photon counting fluorescence detection, has the potential to push the limits of FT. In a previous study, the potential of employing this approach in larger-than-mice animals models, such as rats, as well as improved sensitivity over existing system designs in mouse-sized specimens, was demonstrated17. The immediate application of this approach would be for the monitoring of biomarker expression in vivo in small animal tumor models to assess drug efficacy in a high-throughput means. The ability of the system to excite and detect fluorescence at multiple wavelengths allows the simultaneous detection of multiple fluorescent markers. Additional fluorescent markers provide a means of interrogating multiple aspects of a pathology, simultaneously, or could be used, as in this study, to employ more quantitative imaging approaches such as dual-reporter methods of measuring in vivo binding potential, a marker of receptor density26,27.

<table border="1">
	<tbody>
 	<tr>
 	<td>Name of the reagent</td>
 <td>Company</td>
 <td>Catalogue number</td>
 <td>	Comments (optional)</td>
 </tr>
 <tr>
 	<td>IRDye 800CW-EGF	</td>
 <td>LI-COR Biosciences</td>
 <td>926-08446	</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
			<td>Alexa Fluor 647, succinimidyl ester</td>
 <td>Life Technologies</td>
 <td>A20106</td>
 <td>Reacted with water to minimize non-specific binding</td>
 </tr>
 </tbody>
</table>

computed tomography-guided time-domain diffuse fluorescence tomography in small animals for localization of cancer biomarkers

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1. However, light absorption by tissue chromophores (e.g., hemoglobin, water, lipids, melanin) typically limits optical signal propagation through thicknesses larger than a few millimeters2. Compared to other visible wavelengths, tissue absorption for red and near-infrared (near-IR) light absorption dramatically decreases and non-elastic scattering becomes the dominant light-tissue interaction mechanism. The relatively recent development of fluorescent agents that absorb and emit light in the near-IR range (600-1000 nm), has driven the development of imaging systems and light propagation models that can achieve whole body three-dimensional imaging in small animals3.
Despite great strides in this area, the ill-posed nature of diffuse fluorescence tomography remains a significant problem for the stability, contrast recovery and spatial resolution of image reconstruction techniques and the optimal approach to FMI in small animals has yet to be agreed on. The majority of research groups have invested in charge-coupled device (CCD)-based systems that provide abundant tissue-sampling but suboptimal sensitivity4-9, while our group and a few others10-13 have pursued systems based on very high sensitivity detectors, that at this time allow dense tissue sampling to be achieved only at the cost of low imaging throughput. Here we demonstrate the methodology for applying single-photon detection technology in a fluorescence tomography system to localize a cancerous brain lesion in a mouse model.
The fluorescence tomography (FT) system employed single photon counting using photomultiplier tubes (PMT) and information-rich time-domain light detection in a non-contact conformation11. This provides a simultaneous collection of transmitted excitation and emission light, and includes automatic fluorescence excitation exposure control14, laser referencing, and co-registration with a small animal computed tomography (microCT) system15. A nude mouse model was used for imaging. The animal was inoculated orthotopically with a human glioma cell line (U251) in the left cerebral hemisphere and imaged 2 weeks later. The tumor was made to fluoresce by injecting a fluorescent tracer, IRDye 800CW-EGF (LI-COR Biosciences, Lincoln, NE) targeted to epidermal growth factor receptor, a cell membrane protein known to be overexpressed in the U251 tumor line and many other cancers18. A second, untargeted fluorescent tracer, Alexa Fluor 647 (Life Technologies, Grand Island, NY) was also injected to account for non-receptor mediated effects on the uptake of the targeted tracers to provide a means of quantifying tracer binding and receptor availability/density27. A CT-guided, time-domain algorithm was used to reconstruct the location of both fluorescent tracers (i.e., the location of the tumor) in the mouse brain and their ability to localize the tumor was verified by contrast-enhanced magnetic resonance imaging.
Though demonstrated for fluorescence imaging in a glioma mouse model, the methodology presented in this video can be extended to different tumor models in various small animal models potentially up to the size of a rat17.

Watch this Scientific Journal Video about Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers at JoVE.com

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

Diffuse fluorescence tomography offers a relatively low-cost and potentially high-throughout approach to preclinical in vivo tumor imaging. The methodology of optical data collection, calibration, and image reconstruction is presented for a computed tomography-guided non-contact time-domain system using fluorescent targeting of the tumor biomarker epidermal growth factor receptor in a mouse glioma model.

Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1. However, light ...

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12.2K Views.  Dartmouth College. Diffuse fluorescence tomography offers a relatively low-cost and potentially high-throughout approach to preclinical in vivo tumor imaging. The methodology of optical data collection, calibration, and image reconstruction is presented for a computed tomography-guided non-contact time-domain system using fluorescent targeting of the tumor biomarker epidermal growth factor receptor in a mouse glioma model.

Video: Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

Retrograde Perfusion and Filling of Mouse Coronary Vasculature as Preparation for Micro Computed Tomography Imaging

Visualization of the vasculature is becoming increasingly important for understanding many different disease states. While several techniques exist for imaging vasculature, few are able to visualize the vascular network as a whole while extending to a resolution that includes the smaller vessels1,2. Additionally, many vascular casting techniques destroy the surrounding tissue, preventing further analysis of the sample3-5. One method which circumvents these issues is micro-Computed Tomography (&mu;CT). &mu;CT imaging can scan at resolutions &lt;10 microns, is capable of producing 3D reconstructions of the vascular network, and leaves the tissue intact for subsequent analysis (e.g., histology and morphometry)6-11. However, imaging vessels by ex vivo &mu;CT methods requires that the vessels be filled with a radiopaque compound. As such, the accurate representation of vasculature produced by &mu;CT imaging is contingent upon reliable and complete filling of the vessels. In this protocol, we describe a technique for filling mouse coronary vessels in preparation for &mu;CT imaging.
Two predominate techniques exist for filling the coronary vasculature: in vivo via cannulation and retrograde perfusion of the aorta (or a branch off the aortic arch) 12-14, or ex vivo via a Langendorff perfusion system 15-17. Here we describe an in vivo aortic cannulation method which has been specifically designed to ensure filling of all vessels. We use a low viscosity radiopaque compound called Microfil which can perfuse through the smallest vessels to fill all the capillaries, as well as both the arterial and venous sides of the vascular network. Vessels are perfused with buffer using a pressurized perfusion system, and then filled with Microfil. To ensure that Microfil fills the small higher resistance vessels, we ligate the large branches emanating from the aorta, which diverts the Microfil into the coronaries. Once filling is complete, to prevent the elastic nature of cardiac tissue from squeezing Microfil out of some vessels, we ligate accessible major vascular exit points immediately after filling. Therefore, our technique is optimized for complete filling and maximum retention of the filling agent, enabling visualization of the complete coronary vascular network &#x2013; arteries, capillaries, and veins alike.

Visualization of the coronary vessels is critical to advancing our understanding of cardiovascular diseases. Here we describe a method for perfusing murine coronary vasculature with a radiopaque silicone rubber (Microfil), in preparation for micro-Computed Tomography (&mu;CT) imaging.

Visualization of the vasculature is becoming increasingly important for understanding many different disease states. While several techniques exist for ...

Multi-modal Imaging of Angiogenesis in a Nude Rat Model of Breast Cancer Bone Metastasis Using Magnetic Resonance Imaging, Volumetric Computed Tomography and Ultrasound

Angiogenesis is an essential feature of cancer growth and metastasis formation. In bone metastasis, angiogenic factors are pivotal for tumor cell proliferation in the bone marrow cavity as well as for interaction of tumor and bone cells resulting in local bone destruction. Our aim was to develop a model of experimental bone metastasis that allows in vivo assessment of angiogenesis in skeletal lesions using non-invasive imaging techniques.
For this purpose, we injected 105 MDA-MB-231 human breast cancer cells into the superficial epigastric artery, which precludes the growth of metastases in body areas other than the respective hind leg1. Following 25-30 days after tumor cell inoculation, site-specific bone metastases develop, restricted to the distal femur, proximal tibia and proximal fibula1. Morphological and functional aspects of angiogenesis can be investigated longitudinally in bone metastases using magnetic resonance imaging (MRI), volumetric computed tomography (VCT) and ultrasound (US).
MRI displays morphologic information on the soft tissue part of bone metastases that is initially confined to the bone marrow cavity and subsequently exceeds cortical bone while progressing. Using dynamic contrast-enhanced MRI (DCE-MRI) functional data including regional blood volume, perfusion and vessel permeability can be obtained and quantified2-4. Bone destruction is captured in high resolution using morphological VCT imaging. Complementary to MRI findings, osteolytic lesions can be located adjacent to sites of intramedullary tumor growth. After contrast agent application, VCT angiography reveals the macrovessel architecture in bone metastases in high resolution, and DCE-VCT enables insight in the microcirculation of these lesions5,6. US is applicable to assess morphological and functional features from skeletal lesions due to local osteolysis of cortical bone. Using B-mode and Doppler techniques, structure and perfusion of the soft tissue metastases can be evaluated, respectively. DCE-US allows for real-time imaging of vascularization in bone metastases after injection of microbubbles7.
In conclusion, in a model of site-specific breast cancer bone metastases multi-modal imaging techniques including MRI, VCT and US offer complementary information on morphology and functional parameters of angiogenesis in these skeletal lesions.

In the pathogenesis of bone metastasis, angiogenesis is a crucial process and therefore represents a target for imaging and therapy. Here, we present a rat model of site-specific breast cancer bone metastasis and describe strategies to non-invasively image angiogenesis in vivo using magnetic resonance imaging, volumetric computed tomography and ultrasound.

Angiogenesis is an essential feature of cancer growth and metastasis formation. In bone metastasis, angiogenic factors are pivotal for tumor cell ...

Assessment of Viability of Human Fat Injection into Nude Mice with Micro-Computed Tomography

Lipotransfer is a vital tool in the surgeon&#8217;s armamentarium for the treatment of soft tissue deficits of throughout the body. Fat is the ideal soft tissue filler as it is readily available, easily obtained, inexpensive, and inherently biocompatible.1 However, despite its burgeoning popularity, fat grafting is hampered by unpredictable results and variable graft survival, with published retention rates ranging anywhere from 10-80%. 1-3
To facilitate investigations on fat grafting, we have therefore developed an animal model that allows for real-time analysis of injected fat volume retention. Briefly, a small cut is made in the scalp of a CD-1 nude mouse and 200-400 &#181;l&#160;of processed lipoaspirate is placed over the skull. The scalp is chosen as the recipient site because of its absence of native subcutaneous fat, and because of the excellent background contrast provided by the calvarium, which aids in the analysis process. Micro-computed tomography (micro-CT) is used to scan the graft at baseline and every two weeks thereafter. The CT images are reconstructed, and an imaging software is used to quantify graft volumes.
Traditionally, techniques to assess fat graft volume have necessitated euthanizing the study animal to provide just a single assessment of graft weight and volume by physical measurement ex vivo. Biochemical and histological comparisons have likewise required the study animal to be euthanized. This described imaging technique offers the advantage of visualizing and objectively quantifying volume at multiple time points after initial grafting without having to sacrifice the study animal. The technique is limited by the size of the graft able to be injected as larger grafts risk skin and fat necrosis. This method has utility for all studies evaluating fat graft viability and volume retention. It is particularly well-suited to providing a visual representation of fat grafts and following changes in volume over time.

Fat grafting is an essential technique for reconstructing soft tissue deficits. However, it remains an unpredictable procedure characterized by variable graft survival. Our goal was to devise a mouse model that utilizes a novel imaging method to compare volume retention between differing techniques of fat graft preparation and delivery.

Lipotransfer is a vital tool in the surgeon&#8217;s armamentarium for the treatment of soft tissue deficits of throughout the body. Fat is the ideal soft ...

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer

Lung cancer is the most lethal cancer in the world. Intensive research is ongoing worldwide to identify new therapies for lung cancer. Several mouse models of lung cancer are being used to study the mechanism of cancer development and to experiment with various therapeutic strategies. However, the absence of a real-time technique to identify the development of tumor nodules in mice lungs and to monitor the changes in their size in response to various experimental and therapeutic interventions hampers the ability to obtain an accurate description of the course of the disease and its timely response to treatments. In this study, a method using a micro-computed tomography (CT) scanner for the detection of the development of lung tumors in a mouse model of lung adenocarcinoma is described. Next, we show that monthly follow-up with micro-CT can identify dynamic changes in the lung tumor, such as the appearance of additional nodules, increase in the size of previously detected nodules, and decrease in the size or complete resolution of nodules in response to treatment. Finally, the accuracy of this real-time assessment method was confirmed with end-point histological quantification. This technique paves the way for planning and conducting more complex experiments on lung cancer animal models, and it enables us to better understand the mechanisms of carcinogenesis and the effects of different treatment modalities while saving time and resources.

We describe a method for the detection of tumor nodule development in the lungs of an adenocarcinoma mouse model using micro-computed tomography and its use for monitoring changes in nodule size over time and in response to treatment. The accuracy of the assessment was confirmed with end-point histological quantification.

Lung cancer is the most lethal cancer in the world. Intensive research is ongoing worldwide to identify new therapies for lung cancer. Several mouse ...

Combined Near-infrared Fluorescent Imaging and Micro-computed Tomography for Directly Visualizing Cerebral Thromboemboli

Direct thrombus imaging visualizes the root cause of thromboembolic infarction. Being able to image thrombus directly allows far better investigation of stroke than relying on indirect measurements, and will be a potent and robust vascular research tool. We use an optical imaging approach that labels thrombi with a molecular imaging thrombus marker&#160;&#8212; a Cy5.5 near-infrared fluorescent (NIRF) probe that is covalently linked to the fibrin strands of the thrombus by the fibrin-crosslinking enzymatic action of activated coagulation factor XIIIa during the process of clot maturation. A micro-computed tomography (microCT)-based approach uses thrombus-seeking gold nanoparticles (AuNPs) functionalized to target the major component of the clot: fibrin. This paper describes a detailed protocol for the combined in vivo microCT and ex vivo NIRF imaging of thromboemboli in a mouse model of embolic stroke. We show that in vivo microCT and fibrin-targeted glycol-chitosan AuNPs (fib-GC-AuNPs) can be used for visualizing both in situ thrombi and cerebral embolic thrombi. We also describe the use of in vivo microCT-based direct thrombus imaging to serially monitor the therapeutic effects of tissue plasminogen activator-mediated thrombolysis. After the last imaging session, we demonstrate by ex vivo NIRF imaging the extent and the distribution of residual thromboemboli in the brain. Finally, we describe quantitative image analyses of microCT and NIRF imaging data. The combined technique of direct thrombus imaging allows two independent methods of thrombus visualization to be compared: the area of thrombus-related fluorescent signal on ex vivo NIRF imaging vs. the volume of hyperdense microCT thrombi in vivo.

This protocol describes the application of combined near-infrared fluorescent (NIRF) imaging and micro-computed tomography (microCT) for visualizing cerebral thromboemboli. This technique allows the quantification of thrombus burden and evolution. The NIRF imaging technique visualizes fluorescently labeled thrombus in excised brain, while the microCT technique visualizes thrombus inside living animals using gold-nanoparticles.

Direct thrombus imaging visualizes the root cause of thromboembolic infarction. Being able to image thrombus directly allows far better investigation of ...

Disposable Dosators for Pulmonary Insufflation of Therapeutic Agents to Small Animals

Development of new therapeutic products requires efficacy testing in an animal model. The pulmonary route of administration can be utilized to deliver drugs locally and systemically. Evaluation of dry powder aerosols necessitates an efficient dispersion mechanism to maintain high concentrations in an exposure chamber or for direct endotracheal administration. While solutions exist to expose animals by passive inhalation to dry powder aerosols, most require masses of powder in large excess of the dose delivered. This precludes conducting early feasibility studies as insufficient drug is available at the research or early development stage to support the dose delivery requirements for conventional aerosol delivery systems. When designing an aerosol drug product, aerodynamic performance can relate directly to delivery efficiency and efficacy. Dispersion of powder into an aerosol requires energy input sufficient to overcome interparticulate forces, and particle engineering approaches can substantially improve aerosol performance. We have developed a dispersion system (dosator) which can aerosolize engineered dry powder aerosols efficiently for the purpose of direct pulmonary insufflation, dispersion into an exposure system or generation for analytical purposes.

During development of drugs for pulmonary delivery, it is necessary to evaluate pharmacokinetics and efficacy in an animal model. We present a method to build a disposable aerosol dispersion system from of-the-shelf components that can be used to administer intrapulmonary dry powder aerosol to rodents.

Development of new therapeutic products requires efficacy testing in an animal model. The pulmonary route of administration can be utilized to deliver ...

Cone Beam Intraoperative Computed Tomography-based Image Guidance for Minimally Invasive Transforaminal Interbody Fusion

Transforaminal lumbar interbody fusion (TLIF) is commonly used for the treatment of spinal stenosis, degenerative disc disease, and spondylolisthesis. Minimally invasive surgery (MIS) approaches have been applied to this technique with an associated decrease in estimated blood loss (EBL), length of hospital stay, and infection rates, while preserving outcomes with traditional open surgery. Previous MIS TLIF techniques involve significant fluoroscopy that subjects the patient, surgeon, and operating room staff to non-trivial levels of radiation exposure, particularly for complex multi-level procedures. We present a technique that utilizes an intraoperative computed tomography (CT) scan to aid in placement of pedicle screws, followed by traditional fluoroscopy for confirmation of cage placement. Patients are positioned in the standard fashion and a reference arc is placed in the posterior superior iliac spine (PSIS) followed by intraoperative CT scan. This allows for image-guidance-based placement of pedicle screws through a one-inch skin incision on each side. Unlike traditional MIS-TLIF that requires significant fluoroscopic imaging during this stage, the operation can now be performed without any additional radiation exposure to the patient or operating room staff. After completion of the facetectomy and discectomy, final TLIF cage placement is confirmed with fluoroscopy. This technique has the potential to decrease operative time and minimize total radiation exposure.

The purpose of this article is to provide image-guidance for minimally invasive transforaminal interbody fusion.

Transforaminal lumbar interbody fusion (TLIF) is commonly used for the treatment of spinal stenosis, degenerative disc disease, and spondylolisthesis. ...

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans

Coronary artery calcification (CAC) provides an objective measure of coronary artery disease and can readily be identified on non-gated computed tomography (CT) scans with a high correlation with gated cardiac CT scans. This standardized protocol takes a step-wise approach to not only optimizing an image for the identification of calcification but also to distinguishing CAC from other common causes of calcification in the cardiac silhouette. Recognition of CAC on non-gated CT scans helps to identify a very powerful prognostic factor that can influence therapeutic interventions or downstream diagnostic testing without requiring a gated cardiac scan. These non-gated CT scans are often acquired as part of the routine care of the patient, and this data is readily available without another dose of&#160;ionizing radiation. This protocol allows for the precise and accurate extraction of this data for the purposes of retrospective data analysis in clinical research studies, but also in the clinical evaluation and management of patients.

Here, we present a protocol to reliably and systematically identify coronary artery calcification (CAC) on non-gated computed tomography (CT) scans of the chest or abdomen. CAC provides an objective measure of coronary artery disease for both research and clinical purposes.

Coronary artery calcification (CAC) provides an objective measure of coronary artery disease and can readily be identified on non-gated computed ...

Continuous Blood Sampling in Small Animal Positron Emission Tomography/Computed Tomography Enables the Measurement of the Arterial Input Function

For quantitative analysis and bio-kinetic modeling of positron emission tomography/computed tomography (PET/CT) data, the determination of the temporal blood time-activity concentration also known as arterial input function (AIF) is a key point, especially for the characterization of animal disease models and the introduction of newly developed radiotracers. The knowledge of radiotracer availability in the blood helps to interpret PET/CT-derived data of tissue activity. For this purpose, online blood sampling during the PET/CT imaging is advisable to measure the AIF. In contrast to manual blood sampling and image-derived approaches, continuous online blood sampling has several advantages. Besides the minimized blood loss, there is an improved resolution and a superior accuracy for the blood activity measurement. However, the major drawback of online blood sampling is the costly and time-consuming preparation to catheterize the femoral vessels of the animal. Here, we describe an easy and complete workflow for catheterization and continuous blood sampling during small animal PET/CT imaging and compared it to manual blood sampling and an image-derived approach. Using this highly-standardized workflow, the determination of the fluorodeoxyglucose ([18F]FDG) AIF is demonstrated. Further, this procedure can be applied to any radiotracer in combination with different animal models to create fundamental knowledge of tracer kinetic and model characteristics. This allows a more precise evaluation of the behavior of pharmaceuticals, both for diagnostic and therapeutic approaches in the preclinical research of oncological, neurodegenerative and myocardial diseases.

Here a protocol for continuous blood sampling during PET/CT imaging of rats to measure the arterial input function (AIF) is described. The catheterization, the calibration and setup of the system and the data analysis of the blood radioactivity are demonstrated. The generated data provide input parameters for subsequent bio-kinetic modeling.

For quantitative analysis and bio-kinetic modeling of positron emission tomography/computed tomography (PET/CT) data, the determination of the temporal ...

Four-Dimensional Computed Tomography-Guided Valve Sizing for Transcatheter Pulmonary Valve Replacement

The measurements of the right ventricle (RV) and pulmonary artery (PA), for selecting the optimal prosthesis size for transcatheter pulmonary valve replacement (TPVR), vary considerably. Three-dimensional (3D) computed tomography (CT) imaging for device size prediction is insufficient to assess the displacement of the right ventricular outflow tract (RVOT) and PA, which could increase the risk of stent misplacement and paravalvular leak. The aim of this study is to provide a dynamic model to visualize and quantify the anatomy of the RVOT to PA over the entire cardiac cycle by four-dimensional (4D) cardiac CT reconstruction to obtain an accurate quantitative evaluation of the required valve size. In this pilot study, cardiac CT from sheep J was chosen to illustrate the procedures. 3D cardiac CT was imported into 3D reconstruction software to build a 4D sequence which was divided into eleven frames over the cardiac cycle to visualize the deformation of the heart. Diameter, cross-sectional area, and circumference of five imaging planes at the main PA, sinotubular junction, sinus, basal plane of the pulmonary valve (BPV), and RVOT were measured at each frame in 4D straightened models prior to valve implantation to predict the valve size. Meanwhile, dynamic changes in the RV volume were also measured to evaluate right ventricular ejection fraction (RVEF). 3D measurements at the end of the diastole were obtained for comparison with the 4D measurements. In sheep J, 4D CT measurements from the straightened model resulted in the same choice of valve size for TPVR (30 mm) as 3D measurements. The RVEF of sheep J from pre-CT was 62.1 %. In contrast with 3D CT, the straightened 4D reconstruction model not only enabled accurate prediction for valve size selection for TPVR but also provided an ideal virtual reality, thus presenting a promising method for TPVR and the innovation of TPVR devices.

This study assessed a new methodology with a straightened model generated from the four-dimensional cardiac computed tomography sequence to obtain the desired measurements for valve sizing in the application of transcatheter pulmonary valve replacement.

The measurements of the right ventricle (RV) and pulmonary artery (PA), for selecting the optimal prosthesis size for transcatheter pulmonary valve ...