The authors would like to thank Dr. Javed Mahmood for assistance with culturing MDA-MB-231 cells and implanting the MDA-MB-231 xenografts, Linyu Fan for preparing the CT-liposomes. Shawn Stapleton is grateful for funding from the Natural Sciences and Engineering Research Postgraduate Scholarships Program and the Terry Fox Foundation Strategic Initiative for Excellence in Radiation Research for the 21st Century (EIRR21) at CIHR. This study was supported by grants from the Terry Fox New Frontiers Program (020005) and the Canadian Institutes of Health Research (102569).

All in vivo experiments were performed under a protocol approved by the University Health Network Institutional Animal Care and Use Committee.
1. Animal Model
<ol>
	<li>Culture between 5 to 7 x 106 MDA-MB-231 breast adenocarcinoma tumor cells in DMEM together with 10% Fetal Bovine Serum (FBS) and 100x dilution of penicillin-streptomycin.</li>
	<li>Harvest cells when they are 80% confluent using a 0.05% trypsin-EDTA solution. After 3-5 min neutralize trypsin-EDTA with a 3x volume of DMEM. Take a 15 &#181;l aliquot of cells and count using a hemocytometer. Centrifuge cells into a pellet for 5 min at 200 x g, and re-suspend in HBS at a concentration of 10 x 106 cells per ml.</li>
	<li>Implant subcutaneous (SC) tumors by injecting 1 to 2 x 106 cells in the hind limb of each 8 to 12 week old female SCID mouse (n = 5). Use a standard 25 G needle for injection.</li>
	<li>Monitor tumor growth using calipers (Volume = 0.5 x Length x Width2) and start the measurements once the SC tumors have reached a volume &#62;200 mm3 (approximately 7 to 9 days).</li>
</ol>
2. CT-liposome Preparation and Characterization
<ol>
	<li>Liposome Preparation
	<ol>
		<li>Dissolve lipid components (200 mmol/L) for the CT-liposomes, including 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), cholesterol (CH), and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-poly(ethylene glycol) 2000 (DSPE-PEG2000) in anhydrous ethanol at 70 &#176;C at a molar ratio of 55:40:5 DPPC:CH:DSPE-PEG2000.</li>
		<li>Evaporate ethanol by maintaining heat at 70 &#176;C, then add the CT contrast agent iohexol (300 mg/ml of iodine) to the solution such that the final lipid concentration is 100 mM.</li>
		<li>Maintain the solution at 70 &#176;C for 4 hr with frequent vortexing.</li>
		<li>To obtain unilamellar vesicles, extrude the sample 5 times through two stacked 200 nm pore size membranes at a pressure of 250 psi and extrude again by 5 cycles through two stacked 80 nm pore size membranes at 400 psi using a 10 ml lipid extruder. Pipette a volume of 10 ml of liposomes into the extruder at the beginning of each extrusion cycle and collect into a sterile conical tube or glass vial after each extrusion cycle.</li>
		<li>Remove the un-encapsulated iohexol by 16 hr of dialysis using a 100 kDa molecular weight cut off (MWC) dialysis bag against a 250-fold volume excess of 0.02 mM HEPES-buffered saline solution (HBS, pH 7.4). For example, place 1 ml of liposome solution inside the dialysis bag with 250 ml of HBS outside the bag in a beaker.</li>
		<li>Concentrate the CT-liposomes using a 750,000 nomical MWC commercial tangential flow system according to the manufacturer&#39;s instructions. Concentrate to a final iodine concentration of approximately 55 mg ml-1.</li>
	</ol>
	</li>
	<li>Liposome Characterization
	<ol>
		<li>Measure encapsulation efficiency by rupturing the CT-liposomes using a 10-fold volume excess of ethanol to release the ioxehol and then dilute using a 100-fold volume excess of deionized water (i.e. 10 &#956;l of liposomes ruptured using 100 &#956;l of ethanol and then diluted to a final volume of 10 ml).</li>
		<li>Determine iohexol concentration using a UV spectrometer with detection at a wavelength of 245 nm. Calculate the encapsulations efficiency by taking the ratio amount of released iohexol agent to the amount of agent added during preparation.</li>
		<li>Measure the hydrodynamic diameter and zeta potential using a dynamic light scattering particle size analyzer system according to the manufacturer&#39;s instructions. Dilute the CT-liposome solution by 200x (i.e. 5 &#956;l of liposome in 1 ml of final volume) in deionized water to facilitate measurements.</li>
	</ol>
	</li>
</ol>
3. CT Imaging of Tumor Microcirculation and CT-liposome Distribution
NOTE: Follow the manufacturer&#39;s instructions for performing a volumetric scan if different software version or equipment is used.
<ol>
	<li>Anesthetize each mouse using 2% isoflurane mixed with medical air or oxygen and confirm by pinching the toe and observing no reaction. Apply ointment to the eyes to prevent dryness while under anesthesia. Immobilize animal in a prone position by taping paws to a thin plastic board.</li>
	<li>Place a custom 27 G catheter, connected to 20 cm on PE10 tubing, into the lateral tail vein and secure in place with several pieces of tape.</li>
	<li>Prepare a 1 ml syringe to contain at least 200 &#181;l of the CT-liposomes. Prepare a 1 ml syringe with saline to use to flush the catheter. Finally, prepare a 1 ml syringe with at least 150 &#181;l of free iohexol mixed with saline (9:1 ratio by volume).</li>
	<li>Place the mouse prone on the micro-CT scanner bed. Use the laser positioning system to place the tumor in approximately the same orientation for each scan.</li>
	<li>Place the CT-liposome syringe in a syringe pump and attach the catheter to the syringe. Set the pump rate of 10 &#181;l per sec.</li>
	<li>Initialize the system by performing a bright-dark calibration scan using the CT-scanner console software. Select the bright-dark scan option for each imaging protocol of interest, select bright-dark from the drop down menu and press the scan button to initiate the calibration.</li>
	<li>Perform a volumetric anatomical micro-CT of the tumor prior to any contrast agent injection. Look at the CT scanner console software indicator to ensure the CT-scanner safety interlocks have been cleared. On the CT scanner console select scan select an x-ray energy of 80 kV, a tube current of 70 mA, and captures 1,000 image projections over time 16 sec. Press the scan button to initiate the scan.</li>
	<li>Use the syringe pump to inject a bolus of CT-liposomes at a concentration of 400 mg iodine kg-1. Set the pump to inject a volume of approximately 150 &#181;l (assuming a 25 g mouse). Press the &#39;start&#39; button on the pump to inject. Manually flush the catheter with 50 &#181;l of saline (twice the volume of the catheter) to ensure the entire agent amount was injected and the catheter is clear.</li>
	<li>Wait 10 min after the injection of CT-liposomes and then perform a second anatomical scan using the same method and settings described in 3.5.</li>
	<li>Perform a DCE-CT scan by setting the syringe pump to inject a volume of 100 &#181;l of the free iohexol mixed with saline (9:1 ratio by volume) using the same injection rate setting described in 3.3.
	<ol>
		<li>On the CT-scanner console select the 5 min dynamic scan that uses an x-ray energy setting of 80 kV, a tube energy of 90mA, and captures 416 image projections every sec for the first 30 sec and followed by an acquisition every 10 sec. Capture 5 sec of DCE-CT data and then press the start button on the injection pump.</li>
		<li>After the DCE-CT scan perform a volumetric anatomical micro-CT scan.</li>
	</ol>
	</li>
	<li>Capture anatomical CT images between 48 and 72 hr post-injection of CT-liposomes, using the same volumetric CT settings as described in steps 3.5.</li>
	<li>Reconstruct the anatomical CT and DCE-CT data using the GPU-reconstruction software.
	<ol>
		<li>Load the image into the reconstruction software. Select the region of interest to be reconstructed by drawing an ROI over the image using a mouse. Set the save location and filename for the reconstructed imaged and select the output file type as &#39;.mat&#39;. 
		NOTE: The software will automatically set the reconstructed voxel size to 0.153 x 0.153 x 0.153 mm3 for anatomical scans and 0.153 x 0.153 x 0.462 mm3 for DCE-CT scans. Click the &#39;begin reconstruction&#39; button.</li>
	</ol>
	</li>
	<li>Use the pre-injection and 10 min post-injection scans of the CT-liposome to calculate the plasma volume fraction as previously described3. Furthermore, use the pre-injection and 5 min post-injection scans of iohexol to calculate the interstitial volume fraction as previously described7.</li>
	<li>Obtain time intensity curves (TICs) by importing the DCE-CT data into software that provides the ability to identify a region of interest (ROI) within the tumor volume. Then calculate the mean CT enhancement in the ROI as a function of time. In this experiment custom software was developed to identify a ROI and calculate the TIC.</li>
	<li>Obtain quantitative estimates of perfusion and vascular permeability by fitting measured TICs using a two-compartment tracer kinetic model. Fitting can be performed using DCE-CT analysis software and use the apriori estimates of the plasma volume fraction and interstitial volume fractions as fixed parameters in the two-compartment tracer kinetic model. Use previously reported methods to obtain apriori estimates of the plasma and interstitial volume fractions14.</li>
</ol>
4. Spatial Measurements of Tumor Interstitial Fluid Pressure
<ol>
	<li>To measure IFP connect the 25 G spinal needle to the pressure transducer and to the IFP acquisition system through 50 cm of PE20 polyethylene tubing. Flush the entire system with a heparin sulfate/saline solution (1:10).&#160;Sterilize the needle with 70% isopropyl before use.</li>
	<li>Turn on the acquisition system and launch the IFP acquisition software and load the settings files to calibrate the system to acquire IFP measurements in mmHg. Click the acquire button to continuously collect IFP data.</li>
	<li>Perform IFP measurements between 48 and 72 hr post-injection of CT-liposomes (this corresponds to the approximate time of peak accumulation of the CT-liposomes in the tumor), using the methods described in 4.8. Attach the IFP needle to the CT-IFP robot.</li>
	<li>Perform calibration scans to align the coordinate systems for the CT-IFP robot and the CT scanner. Add the fiducial marker attachment to the CT-IFP robot and perform a four volumetric CT scan with the fiducial marker in four different positions.
	<ol>
		<li>Launch the CT-IFP robot controller software, initialize the robot, and move the robot to the three positions by entering the x,y,z targeting positions and clicking the &#39;go&#39; button.</li>
		<li>Take a CT scan at the following x,y,z coordinates: (1) 0,0,0; (2) -10,0,0; (3) 0,7,0; and (4) 0,0,10. Select a 90 kV, 10 mA, 16 sec scan using the CT-scanner software and press &#39;Start&#39; to initiate the scan. Reconstruct the scan as described in 3.10.</li>
	</ol>
	</li>
	<li>Launch the CT-IFP robot alignment software. Click the &#39;add&#39; button loaded in the &#39;Registration Data&#39; region and select the four reconstructed registration scans obtained in 4.3, then click &#39;open&#39;. 
	NOTE: The pixel location of the fiducial marker will automatically be entered into the software.
	<ol>
		<li>Click the &#39;Calculate Transform&#39; button and then click the &#39;Apply Transform&#39; button. This generates alignment data that will be used to convert the CT-IFP robot coordinate system to the CT scanner coordinate system. After the calibration is complete, attach the animal platform to the CT-IFP robot.</li>
	</ol>
	</li>
	<li>Anesthetize each mouse using 2% isoflurane mixed with medical air or oxygen and confirm by pinching the toe and observing no reaction. Immobilize animal on the CT-IFP robot platform and position the mouse such that the tumor is accessible to the CT-IFP robot system. Immobilize the tumor using tape such that it does not move during IFP needle insertion.</li>
	<li>Perform an anatomic micro-CT scan prior to inserting the IFP needle. Reconstruct the CT data using the steps described in 3.10.</li>
	<li>Load the pre-needle insertion CT data into the CT-IFP robot alignment software. Adjust the window and level to visualize the tumor. Click on the rim of the tumor in any image, then click on a second rim location. 
	NOTE: The software will calculate a series of positions along a linear line between the two positions. Note the x, y and z coordinates for a series of 5 to 8 evenly spaced positions from the list.</li>
	<li>Prepare the IFP system by flushing the needle with heparin saline solution prior to insertion.</li>
	<li>Enter the first pre-determined needle positions into the x,y,z, into the CT-IFP robot control software and press-move to &#39;go&#39; button to move the robot to the desired position. Click the &#39;Insert Needle&#39; button to insert the needle into the tissue.
	<ol>
		<li>After inserting the needle ensure good fluid communication between the IFP needle and the tissue by pinching and releasing the PE20 tubing, noting that the IFP measurement increases and returns to pre-pinching value on the IFP acquisition software. Reject measurements that do not return to baseline.</li>
	</ol>
	</li>
	<li>Acquire an anatomic CT scan with the needle inserted, then click the &#39;Retract Needle&#39; button on the CT-IFP robot control software to retract the needle from the tissue. Reject any IFP measurements where the IFP value does not return to the pre-needle insertion value after withdrawal of the needle. This signifies the needle may have been clogged during the measurement. Repeat steps 4.8 to 4.10 for each needle position.</li>
	<li>Determine the needle position within the tumor volume by calculating the x, y, and z positions of the needle port relative to the center of mass of the tumor volume as identified in the post-insertion volumetric CT scan of the needle.</li>
	<li>Return animals to their cage after all measurements are complete. Do not leave animals unattended, and take care to observe them until consciousness has been regained and they are able to maintain sternal recumbency.</li>
</ol>

<ol>
	<li>Seo, J. W., Zhang, H., Kukis, D. L., Meares, C. F., Ferrara, K. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+method+to+label+preformed+liposomes+with+64Cu+for+positron+emission+tomography+(PET)+imaging.">A novel method to label preformed liposomes with 64Cu for positron emission tomography (PET) imaging.</a> Bioconjugate chemistry. 19 (12), 2577-2584 (2008).</li><li>Huang, H., Dunne, M., Lo, J., Jaffray, D., Allen, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+Computed+Tomography-+and+Optical+Image-Based+Assessment+of+Liposome+Distribution.">Comparison of Computed Tomography- and Optical Image-Based Assessment of Liposome Distribution.</a> Molecular Imaging. 12 (3), 148-160 (2013).</li><li>Stapleton, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+mathematical+model+of+the+enhanced+permeability+and+retention+effect+for+liposome+transport+in+solid+tumors.">A mathematical model of the enhanced permeability and retention effect for liposome transport in solid tumors.</a> PloS one. 8 (12), e81157 (2013).</li><li>Zheng, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+multimodal+nano+agent+for+image-guided+cancer+surgery.">A multimodal nano agent for image-guided cancer surgery.</a> Biomaterials. 67, 160-168 (2015).</li><li>Zheng, J., Liu, J., Dunne, M., Jaffray, D. A., Allen, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+performance+of+a+liposomal+vascular+contrast+agent+for+CT+and+MR-based+image+guidance+applications.">In vivo performance of a liposomal vascular contrast agent for CT and MR-based image guidance applications.</a> Pharmaceutical research. 24 (6), 1193-1201 (2007).</li><li>Harrington, K. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effective+targeting+of+solid+tumors+in+patients+with+locally+advanced+cancers+by+radiolabeled+pegylated+liposomes.">Effective targeting of solid tumors in patients with locally advanced cancers by radiolabeled pegylated liposomes.</a> Clinical Cancer Research. 7 (2), 243-254 (2001).</li><li>Stapleton, S., Allen, C., Pintilie, M., Jaffray, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumor+perfusion+imaging+predicts+the+intra-tumoral+accumulation+of+liposomes.">Tumor perfusion imaging predicts the intra-tumoral accumulation of liposomes.</a> J Control Release. 172 (1), 351-357 (2013).</li><li>Lammers, T., Kiessling, F., Hennink, W. E., Storm, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanotheranostics+and+image-guided+drug+delivery:+current+concepts+and+future+directions.">Nanotheranostics and image-guided drug delivery: current concepts and future directions.</a> Mol. Pharm. 7, 1899-1912 (2010).</li><li>Stapleton, S., Milosevic, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Cancer Targeted Drug Delivery. , 241-272 (2013).</li><li>Blanco, E., Shen, H., Ferrari, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Principles+of+nanoparticle+design+for+overcoming+biological+barriers+to+drug+delivery.">Principles of nanoparticle design for overcoming biological barriers to drug delivery.</a> Nature biotechnology. 33 (9), 941-951 (2015).</li><li>Heldin, C. H., Rubin, K., Pietras, K., Ostman, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High+interstitial+fluid+pressure+-+an+obstacle+in+cancer+therapy.">High interstitial fluid pressure - an obstacle in cancer therapy.</a> Nat Rev Cancer. 4 (10), 806-813 (2004).</li><li>Chauhan, V. P., Stylianopoulos, T., Boucher, Y., Jain, R. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Delivery+of+molecular+and+nanoscale+medicine+to+tumors:+transport+barriers+and+strategies.">Delivery of molecular and nanoscale medicine to tumors: transport barriers and strategies.</a> Annual review of chemical and biomolecular engineering. 2, 281-298 (2011).</li><li>Bax, J. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+image-guided+robotic+needle+positioning+system+for+small+animal+interventions.">3D image-guided robotic needle positioning system for small animal interventions.</a> Medical physics. 40 (1), 011909 (2013).</li><li>Stapleton, S., Milosevic, M., Tannock, I. F., Allen, C., Jaffray, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+intra-tumoral+relationship+between+microcirculation,+interstitial+fluid+pressure+and+liposome+accumulation.">The intra-tumoral relationship between microcirculation, interstitial fluid pressure and liposome accumulation.</a> Journal of Controlled Release. 211, 163-170 (2015).</li><li>Stapleton, S., Allen, C., Pintilie, M., Jaffray, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumor+perfusion+imaging+predicts+the+intra-tumoral+accumulation+of+liposomes.">Tumor perfusion imaging predicts the intra-tumoral accumulation of liposomes.</a> J Control Release. 172 (1), 351-357 (2013).</li><li>Brix, G., Zwick, S., Kiessling, F., Griebel, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pharmacokinetic+analysis+of+tissue+microcirculation+using+nested+models:+multimodel+inference+and+parameter+identifiability.">Pharmacokinetic analysis of tissue microcirculation using nested models: multimodel inference and parameter identifiability.</a> Medical physics. 36 (7), 2923-2933 (2009).</li><li>Brix, G., Griebel, J., Kiessling, F., Wenz, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tracer+kinetic+modelling+of+tumour+angiogenesis+based+on+dynamic+contrast-enhanced+CT+and+MRI+measurements.">Tracer kinetic modelling of tumour angiogenesis based on dynamic contrast-enhanced CT and MRI measurements.</a> European journal of nuclear medicine and molecular imaging. 37 (1), 30-51 (2010).</li></ol>

The authors have nothing to disclose

The methods for image-based measurement presented herein enable determination of the spatial distribution of tumor microcirculation properties, IFP, and CT-liposome accumulation. Previous attempts to relate these properties have relied on performing bulk measurements across multiple tumor-bearing animals and therefore lack the sensitivity to elucidate mechanisms responsible for heterogeneity in intra-tumoral accumulation that has commonly been observed for nano-sized drug delivery systems15. DCE-CT provides a tool to measure the intra-tumoral variations in properties of the tumor microcirculation, volumetric CT provides an accurate depiction of CT-liposome deposition kinetics, and the CT-IFP robot system provides a tool to perform spatial mapping of IFP in the same animal. Furthermore, DCE-CT imaging is a clinically approved method for measuring tumor hemodynamics in the clinical setting, making the findings of this study potentially clinically translatable.
Given the complexity of the measurements, there are several critical factors to ensure the collection of robust data sets. DCE-CT based quantification of the tumor microcirculation is arguably the most difficult to ensure accurate estimates of tumor haemodynamics. It requires obtaining TICs with high signal to noise ratios (SNR) and employing a robust fitting algorithm to quantify the TICs16,17. Visual inspection of TICs can be used to remove low SNR data from the analysis. Furthermore, if care is not taken then the fitting of high SNR TICs may also lead to erroneous estimates of tumor perfusion, vascular permeability, plasma volume fraction, and interstitial volume fraction16. In order to maximize quantification accuracy a strategy was employed to obtain model independent estimates of the plasma and interstitial volume fractions, which are subsequently used as fixed parameters during the model fit of measured TICs. This method ensures robust estimates of tumor perfusion and vascular permeability are obtained15.
Robust analysis of the intra-tumoral distribution of CT-liposomes requires performing volumetric CT imaging after sufficient accumulation of the agent. From previous studies, the peak tumor accumulation of CT-liposomes occurs between 48 to 72 hr in mouse xenografts3,15. Furthermore a linear relationship exists between CT-liposome concentration and contrast enhancement in CT imaging allowing for simple quantification of the variations in intra-tumoral accumulation of CT-liposomes15.
Accurate measurements of IFP using the needle-based method require good fluid communication between the catheter and the tissue. Furthermore, it is important to only use tumors that have high central tumor IFP (&#62;5 to 10 mmHg), otherwise there will be minimal spatial variations in IFP. Spatial measurements of IFP using the CT-IFP robot systemcan be challenging due to tissue motion caused by needle insertion. Imaging pre- and post-needle placement is crucial for accurately identifying the needle placement; however, it can be difficult to relate the position between subsequent needle placements due to tissue warping between measurements. It was found that randomly choosing needle positions results in significant tissue deformation during needle insertion. As a result, this method provided the least accurate spatial mapping of IFP. Conversely, performing measurements along a linear track across the tumor volume and inserting the needle tangential to the track can improve the spatial accuracy of IFP measurements. Inserting the needle tangential to the track minimizes the effects of tissue deformation along the measurement track direction.
This study demonstrated the ability to measure the spatial distribution of tumor microcirculation, IFP and CT-liposome accumulation in an individual tumor. After mastering these techniques, it is then possible to perform these measurements independently or together to characterize the tumor microenvironment and its effects on drug delivery. Using these methods in the MDA-MB-231 breast xenograft model revealed that perfusion and plasma volume fraction are strong mediators of the intra-tumoral distribution of liposomes14. There was not found to be a strong relationship between IFP and liposome distribution. However, IFP was strongly correlated to measurements of tumor perfusion, suggesting that IFP may play an indirect role in mediating liposome distribution through modulation of blood flow.

Measuring the intra-tumoral accumulation of nanoparticle drug delivery systems may provide an important tool to determine if an adequate concentration of cytotoxic drug has been achieved within the tumor. The development of &#34;image-able&#34; liposomal systems allows for non-invasive and quantitative in vivo detection of the drug delivery vehicle using imaging modalities such as positron emission tomography (PET)1, optical fluorescence2, and computed tomography (CT)3,4 and magnetic resonance imaging (MRI)5. Imaging has been used to determine the pharmacokinetics and biodistribution of liposome delivery systems and to reveal the extent of inter-subject and intra-tumoral heterogeneity in nanoparticle accumulation6,7. However, imaging of nanoparticles alone does not identify the biological barriers that have contributed to their poor accumulation and distribution. This knowledge is paramount to the rational development of more efficacious formulations, and strategies to improve intra-tumoral accumulation8. It has been demonstrated that therapeutic strategies can be applied to modulate specific biological barriers resulting in improved nanoparticle transport9. Additionally, nanoparticle formulations have been developed to specifically overcome specific biological transport barrier10. In both scenarios, measurements of biological barriers could be used to guide the use of an appropriate nanoparticle drug delivery strategy.
Tumor microcirculation and elevated IFP are believed to be two key determinants of the intra-tumoral accumulation of nanoparticles, such as liposomes, in solid tumors9,11. However, other barriers that to contribute to poor liposome accumulation include a dense extracellular matrix, impermeable vasculature, and solid tissue pressure12. These barriers are related in a spatio-temporal manner, with abnormal blood flow and elevated interstitial fluid pressure being two important factors driving the initial delivery and extravasation of nanoparticles. As previously discussed, establishing the relationship between the tumor microcirculation, elevated IFP, and the intra-tumoral accumulation of liposomes is imperative for proper interpretation of liposome imaging data. Herein quantitative methods to measure the relationship between the tumor microcirculation, elevated IFP, and nanoparticle accumulation in a solid tumor are presented. This is accomplished by performing co-localized measurements of the intra-tumoral distribution of a CT liposome contrast agent using volumetric CT imaging, tumor microcirculation using dynamic contrast enhanced computed tomography imaging, and tumor IFP using an image-guided robotic needle positioning system, termed the CT-IFP robot13.

<table><tbody><tr><td>MDA-MB-231 metastatic breast adenocarcinoma tumor cells&amp;nbsp;</td><td>ATCC</td><td>HTB-26</td><td></td></tr><tr><td>Dulbecco&#039;s Modified Eagle Medium (DMEM)&amp;nbsp;</td><td>Life Technologies</td><td>11965-092</td><td></td></tr><tr><td>Fetal Bovine Serum (FBS)</td><td>Sigma-Aldrich</td><td>F1051</td><td></td></tr><tr><td>HyClone Penicillin-Streptomycin 100x Solution</td><td>GE Healthcare Life Sciences</td><td>SV30010</td><td></td></tr><tr><td>Trypsin-EDTA (0.05%), phenol red</td><td>ThermoFisher Scientific</td><td>25300-054</td><td></td></tr><tr><td>1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC)</td><td>Avanti Lipids Inc., USA</td><td>850355P</td><td></td></tr><tr><td>Cholesterol (CH)</td><td>Avanti Lipids Inc., USA</td><td>700000P</td><td></td></tr><tr><td>1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-poly(ethylene glycol) 2000 (DSPE-PEG2000)</td><td>Avanti Lipids Inc., USA</td><td>880128P</td><td></td></tr><tr><td>Omnipaque (Iohexol) 300 mg of iodine/ml&amp;nbsp;</td><td>GE Healthcare, CA</td><td></td><td></td></tr><tr><td>80 nm pore size Track-Etch polycarbonate membranes</td><td>Whatman Inc., USA</td><td></td><td></td></tr><tr><td>200 nm pore size Track-Etch polycarbonate membranes</td><td>Whatman Inc., USA</td><td></td><td></td></tr><tr><td>10 m Lipex Extruder&amp;nbsp;</td><td>Nothern Lipids Inc, CA</td><td></td><td></td></tr><tr><td>Dialysis Bag Molecular Weight Cut Off (MWCO) of 8 kDa</td><td>Spectrum Labs, USA&amp;nbsp;</td><td></td><td></td></tr><tr><td>750,000 Nomical Molecular Weight Cut Off (NMWC) Tangential flow column&amp;nbsp;</td><td>MidGee ultrafiltration cartridge, GE Healthcare, CA</td><td></td><td></td></tr><tr><td>Peristaltic pump&amp;nbsp;</td><td>Watson Marlow Inc., USA</td><td></td><td></td></tr><tr><td>UV spectrometer</td><td>Helios &amp;gamma;, Spectronic Unicam,&amp;nbsp; USA</td><td></td><td></td></tr><tr><td>90Plus particle size analyzer&amp;nbsp;</td><td>Brookhaven, Holtsville, USA</td><td></td><td></td></tr><tr><td>eXplore Locus Ultra micro-CT system&amp;nbsp;</td><td>GE Healthcare, CA</td><td></td><td>Manipulated using CT-Console Software</td></tr><tr><td>AxRecon GPU-based Reconstruction</td><td>&amp;nbsp;Acceleware Corp. CA</td><td></td><td></td></tr><tr><td>27 G Catheter SURFLO Winged Infusion Set</td><td>Terumo Medical Products, USA</td><td>SV*27EL</td><td></td></tr><tr><td>PE20 polyethylyne tubing</td><td>Becton Dickinson, USA</td><td>427406</td><td></td></tr><tr><td>Pen tip 25 G &amp;times; 3.5&amp;prime;&amp;prime; Whitacre spinal needle&amp;nbsp;</td><td>Becton Dickinson, USA</td><td>405140</td><td>IFP needle</td></tr><tr><td>P23XL&amp;nbsp; pressure transducer&amp;nbsp;</td><td>Harvard Apparatus, CA</td><td>P23XL</td><td></td></tr><tr><td>PowerLab 4/35, Bridge Amp, with LabChart Pro 7.0</td><td>ADInstruments Pty Ltd., USA</td><td>PL3504, FE221</td><td>IFP acquisition system and acquisition software</td></tr><tr><td>CT-Sabre Small Animall Intervention system (CT-IFP Robot)</td><td>Parallax Innovations, CA</td><td></td><td>Manipulated using CT-IFP robot Control Software</td></tr><tr><td>CT-IFP robot alignment software</td><td></td><td></td><td>Custom Matlab software</td></tr><tr><td>DCE-CT Analysis Software</td><td></td><td></td><td>Custom Matlab software</td></tr><tr><td>Matlab 2013b</td><td>Mathworks, USA</td><td></td><td></td></tr></tbody></table>

spatial measurements of perfusion, interstitial fluid pressure and liposomes accumulation in solid tumors

The heterogeneous intra-tumoral accumulation of liposomes is a critical determinant of their efficacy. Both the chaotic tumor microcirculation and elevated IFP are linked to the heterogeneous intra-tumoral distribution of nanotechnology-based drug delivery systems such as liposomes. In the present study, the relationship between tumor microcirculation, elevated IFP, and accumulation of nanoparticles was investigated through in vivo experimentation. This was accomplished by evaluation of the tumor microcirculation using dynamic contrast enhanced computed tomography (DCE-CT) and measurement of tumor IFP using a novel image-guided robotic needle placement system connected to the micro-CT scanner. The intra-tumoral accumulation of liposomes was determined by CT image-based assessment of a nanoparticle liposomal formulation that stably encapsulate the contrast agent iohexol (CT-liposomes). CT imaging allowed for co-localization of the spatial distribution of tumor hemodynamics, IFP and CT-liposome accumulation in an individual subcutaneous xenograft mouse model of breast cancer. Measurements led to the discovery that perfusion and plasma volume fraction are strong mediators of the intra-tumoral distribution of liposomes. Furthermore, the results suggest that IFP plays an indirect role in mediating liposome distribution through modulating blood flow.

The aforementioned protocol should yield CT-liposomes with an encapsulated concentration of iohexol, mean liposome diameter, and zeta potential of 55 mg ml-1, 91.8 &#177; 0.3 nm and -45.5 &#177; 2.5 mV, respectively. Figure 1a includes representative DCE-CT imaging results, yielding a time series of volumetric data that show the temporal changes in intra-tumoral accumulation of iohexol. Selecting a ROI within the tumor yields a TIC that can be quantified using tracer kinetic modeling methods to obtain estimates of perfusion, vascular permeability, plasma volume fraction, and interstitial volume fraction (Figure 1b). In this study, a two-compartment tracer kinetic model was used and fit to the measured TIC using a non-linear curve fitting routine implemented in Matlab14. Segmenting the tumor volume into multiple regions of interest of equal size allows for quantification of the spatial distribution of haemodynamic parameters within the tumor volume (Figure 1c). Segmentation can be performed either manually, which is time consuming and difficult, or automatically as performed here using an algorithm that divides the tumor in multiple equal sized ROIs using a spherical coordinate system. The DCE-CT methods provide quantitative estimates of the spatial distribution of perfusion, vascular permeability, plasma volume fraction, and interstitial volume fraction. These parameters were observed to be spatially heterogeneous with higher levels of perfusion, plasma and interstitial volume fractions along the periphery compared to the central tumor volume.
The volumetric CT imaging method reveals the biodistribution and intra-tumoral distribution of CT-liposomes. Figure 2a shows the biodistribution of CT-liposomes at 48 hr post-injection. The agent is still circulating in the vascular system, with substantial uptake observed in the spleen and liver. The intra-tumoral accumulation of CT-liposomes was observed to be heterogeneous, with predominantly peripheral accumulation compared to the center, as denoted by the bright regions within the tumor volume (Figure 2b).
Volumetric CT imaging can be used to track the location of IFP measurements made using the CT-IFP robot setup. Figure 3a shows the placement of the IFP needle within the tumor volume as imaged using high-resolution micro-CT. The needle can clearly be identified within the tumor volume allowing for spatial localization of the IFP measurements within the tumor volume (Figure 3b). It is possible to generate a spatial map of IFP throughout the tumor by performing multiple IFP measurements within the tumor volume. The spatial IFP can then be correlated with the corresponding measurements of tumor microcirculation and CT-liposome accumulation.
Volumetric CT imaging allows for a common frame of reference making it possible to co-localize measurements of haemodynamics, IFP, and CT-liposome accumulation. Figure 4 gives an example of spatially co-localized measurements of CT-liposome accumulation, IFP, perfusion, vascular permeability, plasma volume fraction, and interstitial volume fraction. It was observed that perfusion and the plasma volume fraction was significantly correlated with the intra-tumoral accumulation of CT-liposomes in subcutaneous MDA-MB-231 tumors. Furthermore, the radial distribution of IFP correlated with haemodynamic measurements. These results suggest a complex spatio-temporal relationship exists between the tumor microcirculation, IFP and the intra-tumoral accumulation of liposomes14.
<img alt="Figure 1" src="/files/ftp_upload/54226/54226fig1.jpg" /> 
Figure 1: DCE-CT Imaging of the Tumor Microcirculation. (a) A representative series of temporal CT images collected within the tumor volume, depicting the contrast agent kinetics as a function of time. The red contour represents a ROI where the time intensity curve (TIC) is measured. (b) The TIC is fit using a two-compartment tracer kinetic model to yield quantitative estimates of haemodynamic parameters within the ROI. (c) Representative spatial distribution of quantitative haemodynamic parameters in the tumor. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54226/54226fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54226/54226fig2.jpg" /> 
Figure 2: Volumetric CT-Imaging of Liposome Accumulation. (a) A representative 3D volume-rendered image demonstrating the biodistribution of CT-liposomes. (b) Representative axial, coronal, and sagittal slices taken through the center of the tumor showing the intra-tumoral accumulation of CT-liposomes at 48 hr post-injection. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54226/54226fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/54226/54226fig3.jpg" /> 
Figure 3: Image Guided IFP Measurements. (a) A representative 3D volume-rendered image of the CT-IFP robot system (green) post-needle insertion into a subcutaneous tumor at 48 hr post-injection of CT-liposomes (orange). (b) A representative CT image of the post-needle insertion. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54226/54226fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/54226/54226fig4.jpg" /> 
Figure 4: Co-localized Measurements of Tumor Microcirculation, IFP, and CT-liposome accumulation. Panel showing a representative spatial co-localization of CT-liposome accumulation taken 48 hr post-injection, IFP, perfusion, vascular permeability, plasma volume fraction and interstitial volume fraction. Re-print with permission from14. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54226/54226fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Spatial Measurements of Perfusion, Interstitial Fluid Pressure and Liposomes Accumulation in Solid Tumors at JoVE.com

Spatial Measurements of Perfusion, Interstitial Fluid Pressure and Liposomes Accumulation in Solid Tumors

The heterogeneous intra-tumoral accumulation of liposomes has been linked to an abnormal tumor microenvironment. Herein methods are presented to measure tumor microcirculation by perfusion imaging and elevated interstitial fluid pressure (IFP) using an image-guided robotic system. Measurements are compared to the intra-tumoral accumulation of liposomes, determined using volumetric micro-CT imaging.

The heterogeneous intra-tumoral accumulation of liposomes is a critical determinant of their efficacy. Both the chaotic tumor microcirculation and ...

spatial-measurements-perfusion-interstitial-fluid-pressure-liposomes

Nanyang Technological University

Research

JoVE Journal

Medicine

7.7K Views.  University of Toronto. The heterogeneous intra-tumoral accumulation of liposomes has been linked to an abnormal tumor microenvironment. Herein methods are presented to measure tumor microcirculation by perfusion imaging and elevated interstitial fluid pressure (IFP) using an image-guided robotic system. Measurements are compared to the intra-tumoral accumulation of liposomes, determined using volumetric micro-CT imaging.

Video: Spatial Measurements of Perfusion, Interstitial Fluid Pressure and Liposomes Accumulation in Solid Tumors

Contrast Ultrasound Targeted Treatment of Gliomas in Mice via Drug-Bearing Nanoparticle Delivery and Microvascular Ablation

We are developing minimally-invasive contrast agent microbubble based therapeutic approaches in which the permeabilization and/or ablation of the microvasculature are controlled by varying ultrasound pulsing parameters.  Specifically, we are testing whether such approaches may be used to treat malignant brain tumors through drug delivery and microvascular ablation.  Preliminary studies have been performed to determine whether targeted drug-bearing nanoparticle delivery can be facilitated by the ultrasound mediated destruction of "composite" delivery agents comprised of 100nm poly(lactide-co-glycolide) (PLAGA) nanoparticles that are adhered to albumin shelled microbubbles. We denote these agents as microbubble-nanoparticle composite agents (MNCAs). When targeted to subcutaneous C6 gliomas with ultrasound, we observed an immediate 4.6-fold increase in nanoparticle delivery in MNCA treated tumors over tumors treated with microbubbles co-administered with nanoparticles and a 8.5 fold increase over non-treated tumors. Furthermore, in many cancer applications, we believe it may be desirable to perform targeted drug delivery in conjunction with ablation of the tumor microcirculation, which will lead to tumor hypoxia and apoptosis. To this end, we have tested the efficacy of non-theramal cavitation-induced microvascular ablation, showing that this approach elicits tumor perfusion reduction, apoptosis, significant growth inhibition, and necrosis. Taken together, these results indicate that our ultrasound-targeted approach has the potential to increase therapeutic efficiency by creating tumor necrosis through microvascular ablation and/or simultaneously enhancing the drug payload in gliomas.

Insonation of microbubbles is a promising strategy for tumor ablation at reduced time-averaged acoustic powers, as well as for the targeted delivery of therapeutics. The purpose of the present study is to develop low duty cycle ultrasound pulsing strategies and nanocarriers to maximize non-thermal microvascular ablation and payload delivery to subcutaneous C6 gliomas.

We are developing minimally-invasive contrast agent microbubble based therapeutic approaches in which the permeabilization and/or ablation of the ...

Bioengineering

Magnetic Resonance Imaging Quantification of Pulmonary Perfusion using Calibrated Arterial Spin Labeling

This demonstrates a MR imaging method to measure the spatial distribution of pulmonary blood flow in healthy subjects 
during normoxia (inspired O2, fraction (FIO2) = 0.21) hypoxia (FIO2 = 0.125), and hyperoxia 
(FIO2 = 1.00). In addition, the physiological responses of the subject are monitored in the MR scan environment. MR images 
were obtained on a 1.5 T GE MRI scanner during a breath hold from a sagittal slice in the right lung at functional residual capacity. An arterial 
spin labeling sequence (ASL-FAIRER) was used to measure the spatial distribution of pulmonary blood flow 1,2 and a multi-echo fast 
gradient echo (mGRE) sequence 3 was used to quantify the regional proton (i.e. H2O) density, allowing the quantification 
of density-normalized perfusion for each voxel (milliliters blood per minute per gram lung tissue). 
With a pneumatic switching valve and facemask equipped with a 2-way non-rebreathing valve, different oxygen concentrations 
were introduced to the subject in the MR scanner through the inspired gas tubing. A metabolic cart collected expiratory gas via expiratory tubing. Mixed expiratory O2 and CO2 concentrations, oxygen consumption, carbon dioxide production, respiratory exchange ratio, 
respiratory frequency and tidal volume were measured. Heart rate and oxygen saturation were monitored using pulse-oximetry. 
Data obtained from a normal subject showed that, as expected, heart rate was higher in hypoxia (60 bpm) than during normoxia (51) or hyperoxia (50) and the arterial oxygen saturation (SpO2) was reduced during hypoxia to 86%. Mean ventilation was 8.31 L/min BTPS during hypoxia, 7.04 L/min during normoxia, and 6.64 L/min during hyperoxia. Tidal volume was 0.76 L during hypoxia, 0.69 L during normoxia, and 0.67 L during hyperoxia. 
Representative quantified ASL data showed that the mean density normalized perfusion was 8.86 ml/min/g during hypoxia, 8.26 ml/min/g during normoxia and 8.46 ml/min/g during hyperoxia, respectively. In this subject, the relative dispersion4, an index of global heterogeneity, was increased in hypoxia (1.07 during hypoxia, 0.85 during normoxia, and 0.87 during hyperoxia) while the fractal dimension (Ds), another index of heterogeneity reflecting vascular branching structure, was unchanged (1.24 during hypoxia, 1.26 during normoxia, and 1.26 during hyperoxia). 
Overview. This protocol will demonstrate the acquisition of data to measure the distribution of pulmonary perfusion noninvasively under conditions of normoxia, hypoxia, and hyperoxia using a magnetic resonance imaging technique known as arterial spin labeling (ASL). 
Rationale: Measurement of pulmonary blood flow and lung proton density using MR technique offers high spatial resolution images which can be quantified and the ability to perform repeated measurements under several different physiological conditions. In human studies, PET, SPECT, and CT are commonly used as the alternative techniques. However, these techniques involve exposure to ionizing radiation, and thus are not suitable for repeated measurements in human subjects.

A MR imaging method to study the distribution of pulmonary blood flow under a variety of physiological conditions, in this case exposure to three different inspired oxygen concentrations: hypoxia, normoxia, and hyperoxia, is described. This technique utilizes human pulmonary physiology research techniques in an MR scanning environment.

This demonstrates a MR imaging method to measure the spatial distribution of pulmonary blood flow in healthy subjects 
during normoxia (inspired O2, ...

Assessing Tumor Microenvironment of Metastasis Doorway-Mediated Vascular Permeability Associated with Cancer Cell Dissemination using Intravital Imaging and Fixed Tissue Analysis

The most common cause of cancer related mortality is metastasis, a process that requires dissemination of cancer cells from the primary tumor to secondary sites. Recently, we established that cancer cell dissemination in primary breast cancer and at metastatic sites in the lung occurs only at doorways called Tumor MicroEnvironment of Metastasis (TMEM). TMEM doorway number is prognostic for distant recurrence of metastatic disease in breast cancer patients. TMEM doorways are composed of a cancer cell which over-expresses the actin regulatory protein Mena in direct contact with a perivascular, proangiogenic macrophage which expresses high levels of TIE2 and VEGF, where both of these cells are tightly bound to a blood vessel endothelial cell. Cancer cells can intravasate through TMEM doorways due to transient vascular permeability orchestrated by the joint activity of the TMEM-associated macrophage and the TMEM-associated Mena-expressing cancer cell. In this manuscript, we describe two methods for assessment of TMEM-mediated transient vascular permeability: intravital imaging and fixed tissue immunofluorescence. Although both methods have their advantages and disadvantages, combining the two may provide the most complete analyses of TMEM-mediated vascular permeability as well as microenvironmental prerequisites for TMEM function. Since the metastatic process in breast cancer, and possibly other types of cancer, involves cancer cell dissemination via TMEM doorways, it is essential to employ well established methods for the analysis of the TMEM doorway activity. The two methods described here provide a comprehensive approach to the analysis of TMEM doorway activity, either in na&#239;ve or pharmacologically treated animals, which is of paramount importance for pre-clinical trials of agents that prevent cancer cell dissemination via TMEM.

We describe two methods for assessing transient vascular permeability associated with tumor microenvironment of metastasis (TMEM) doorway function and cancer cell intravasation using intravenous injection of high-molecular weight (155 kDa) dextran in mice. The methods include intravital imaging in live animals and fixed tissue analysis using immunofluorescence.

The most common cause of cancer related mortality is metastasis, a process that requires dissemination of cancer cells from the primary tumor to secondary ...

Cancer Research

In vivo Imaging of Tumor Angiogenesis using Fluorescence Confocal Videomicroscopy

Fibered confocal fluorescence in vivo imaging with a fiber optic bundle uses the same principle as fluorescent confocal microscopy. It can excite fluorescent in situ elements through the optical fibers, and then record some of the emitted photons, via the same optical fibers. The light source is a laser that sends the exciting light through an element within the fiber bundle and as it scans over the sample, recreates an image pixel by pixel. As this scan is very fast, by combining it with dedicated image processing software, images in real time with a frequency of 12 frames/sec can be obtained.
We developed a technique to quantitatively characterize capillary morphology and function, using a confocal fluorescence videomicroscopy device. The first step in our experiment was to record 5 sec movies in the four quadrants of the tumor to visualize the capillary network. All movies were processed using software (ImageCell, Mauna Kea Technology, Paris France) that performs an automated segmentation of vessels around a chosen diameter (10 &mu;m in our case). Thus, we could quantify the 'functional capillary density', which is the ratio between the total vessel area and the total area of the image. This parameter was a surrogate marker for microvascular density, usually measured using pathology tools.
The second step was to record movies of the tumor over 20 min to quantify leakage of the macromolecular contrast agent through the capillary wall into the interstitium. By measuring the ratio of signal intensity in the interstitium over that in the vessels, an 'index leakage' was obtained, acting as a surrogate marker for capillary permeability.

In vivo Imaging of Tumor Angiogenesis using Fluorescence Confocal Videomicroscopy

In this paper, we present a method to analyze tumor microvessels in vivo using dynamic contrast-enhanced fluorescence videomicroscopy. Two quantitative parameters were acquired: functional capillary density reflecting the vascularity of the tumor, and index leakage reflecting the leakiness of the endothelial wall.

Fibered confocal fluorescence in vivo imaging with a fiber optic bundle uses the same principle as fluorescent confocal microscopy. It can excite ...

A Permanent Window for Investigating Cancer Metastasis to the Lung

Metastasis, accounting for ~90% of cancer-related mortality, involves the systemic spread of cancer cells from primary tumors to secondary sites such as the bone, brain, and lung. Although extensively studied, the mechanistic details of this process remain poorly understood. While common imaging modalities, including computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI), offer varying degrees of gross visualization, each lacks the temporal and spatial resolution necessary to detect the dynamics of individual tumor cells. To address this, numerous techniques have been described for intravital imaging of common metastatic sites. Of these sites, the lung has proven especially challenging to access for intravital imaging owing to its delicacy and critical role in sustaining life. Although several approaches have previously been described for single-cell intravital imaging of the intact lung, all involve highly invasive and terminal procedures, limiting the maximum possible imaging duration to 6-12 h. Described here is an improved technique for the permanent implantation of a minimally invasive thoracic optical Window for High-Resolution Imaging of the Lung (WHRIL). Combined with an adapted approach to microcartography, the innovative optical window facilitates serial intravital imaging of the intact lung at single-cell resolution across multiple imaging sessions and spanning multiple weeks. Given the unprecedented duration of time over which imaging data can be gathered, the WHRIL can facilitate the accelerated discovery of the dynamic mechanisms underlying metastatic progression and numerous additional biologic processes within the lung.

Here, we present a protocol for the surgical implantation of a permanently indwelling optical window for the murine thorax, which enables high-resolution, intravital imaging of the lung. The permanence of the window makes it well-suited to the study of dynamic cellular processes in the lung, especially those that are slowly evolving, such as metastatic progression of disseminated tumor cells.

Metastasis, accounting for ~90% of cancer-related mortality, involves the systemic spread of cancer cells from primary tumors to secondary sites such as ...

Automated Measurement of Microcirculatory Blood Flow Velocity in Pulmonary Metastases of Rats

Because the lung is a major target organ of metastatic disease, animal models to study the physiology of pulmonary metastases are of great importance. However, very few methods exist to date to investigate lung metastases in a dynamic fashion at the microcirculatory level, due to the difficulty to access the lung with a microscope. Here, an intravital microscopy method is presented to functionally image and quantify the microcirculation of superficial pulmonary metastases in rats, using a closed-chest pulmonary window and automated analysis of blood flow velocity and direction. The utility of this method is demonstrated to measure increases in blood flow velocity in response to pharmacological intervention, and to image the well-known tortuous vasculature of solid tumors. This is the first demonstration of intravital microscopy on pulmonary metastases in a closed-chest model. Because of its minimized invasiveness, as well as due to its relative ease and practicality, this technology has the potential to experience widespread use in laboratories that specialize on pulmonary tumor research.

A method is presented to measure microcirculatory blood flow velocity in pulmonary cancer metastases of the pleural surface in rats in an automated fashion, using closed-chest pulmonary intravital microscopy. This model has potential to be used as a widespread tool to perform physiologic research on pulmonary metastases in rodents.

Because the lung is a major target organ of metastatic disease, animal models to study the physiology of pulmonary metastases are of great importance. ...

Preparing a Microfluidics-Based Vascularized Human Micro-Tumor Model

Establishing a Physiologic Human Vascularized Micro-Tumor Model for Cancer Research

A lack of validated cancer models that recapitulate the tumor microenvironment of solid cancers in vitro remains a significant bottleneck for preclinical cancer research and therapeutic development.&#160;To overcome this problem, we have developed the vascularized microtumor (VMT), or tumor chip, a microphysiological system that realistically models the complex human tumor microenvironment. The VMT forms de novo within a microfluidic platform by co-culture of multiple human cell types under dynamic, physiological flow conditions. This tissue-engineered micro-tumor construct incorporates a living perfused vascular network that supports the growing tumor mass just as newly formed vessels do in vivo. Importantly, drugs and immune cells must cross the endothelial layer to reach the tumor, modeling in vivo physiological barriers to therapeutic delivery and efficacy. Since the VMT platform is optically transparent, high-resolution imaging of dynamic processes such as immune cell extravasation and metastasis can be achieved with direct visualization of fluorescently labeled cells within the tissue. Further, the VMT retains in vivo tumor heterogeneity, gene expression signatures, and drug responses. Virtually any tumor type can be adapted to the platform, and primary cells from fresh surgical tissues grow and respond to drug treatment in the VMT, paving the way toward truly personalized medicine. Here, the methods for establishing the VMT and utilizing it for oncology research are outlined. This innovative approach opens new possibilities for studying tumors and drug responses, providing researchers with a powerful tool to advance cancer research.

Author Spotlight: Creating Human Vascularized Micro-Tumors as Models for Translational Cancer Research 

This protocol presents a physiologically relevant tumor-on-a-chip model to perform high-throughput basic and translational human cancer research, advancing drug screening, disease modeling, and personalized medicine approaches with a description of loading, maintenance, and evaluation procedures.

A lack of validated cancer models that recapitulate the tumor microenvironment of solid cancers in vitro remains a significant bottleneck for preclinical ...

Guided Tumor Inoculation and Multimodal Imaging in Mice

A Dorsal Skinfold Window Chamber Tumor Mouse Model for Combined Intravital Microscopy and Magnetic Resonance Imaging in Translational Cancer Research

Preclinical intravital imaging such as microscopy and optical coherence tomography have proven to be valuable tools in cancer research for visualizing the tumor microenvironment and its response to therapy. These imaging modalities have micron-scale resolution but have limited use in the clinic due to their shallow penetration depth into tissue. More clinically applicable imaging modalities such as CT, MRI, and PET have much greater penetration depth but have comparatively lower spatial resolution (mm scale). 
To translate preclinical intravital imaging findings into the clinic, new methods must be developed to bridge this micro-to-macro resolution gap. Here we describe a dorsal skinfold window chamber tumor mouse model designed to enable preclinical intravital and clinically applicable (CT and MR) imaging in the same animal, and the image analysis platform that links these two disparate visualization methods. Importantly, the described window chamber approach enables the different imaging modalities to be co-registered in 3D using fiducial markers on the window chamber for direct spatial concordance. This model can be used for validation of existing clinical imaging methods, as well as for the development of new ones through direct correlation with "ground truth" high-resolution intravital findings. 
Finally, the tumor response to various treatments-chemotherapy, radiotherapy, photodynamic therapy-can be monitored longitudinally with this methodology using preclinical and clinically applicable imaging modalities. The dorsal skinfold window chamber tumor mouse model and imaging platforms described here can thus be used in a variety of cancer research studies, for example, in translating preclinical intravital microscopy findings to more clinically applicable imaging modalities such as CT or MRI.

Author Spotlight: Integrating High-Resolution Intravital Imaging and MRI to Enhance Stereotactic Body Radiation Therapy Planning

Translation of Intravital microscopy findings is challenged by its shallow depth penetration into tissue. Here we describe a dorsal window chamber mouse model that enables co-registration of intravital microscopy and clinically applicable imaging modalities (e.g., CT, MRI) for direct spatial correlation, potentially streamlining clinical translation of intravital microscopy findings.

Preclinical intravital imaging such as microscopy and optical coherence tomography have proven to be valuable tools in cancer research for visualizing the ...

Preclinical Imaging of Tumor Oxygen Levels Using EPRI and Ultrasound

Tumor Hypoxia Assessment: In Vivo 3D Oxygen Imaging Through Electron Paramagnetic Resonance

The precise and real-time measurement of oxygen partial pressure (pO2) brings valuable information in many pathologies, including cancer. Low tumor pO2 (i.e., hypoxia) is connected to tumor aggressiveness and poor response to therapy. The quantification of tumor pO2 allows the evaluation of treatment effectiveness. Electron Paramagnetic Resonance Imaging (EPRI), particularly Pulse EPRI, has emerged as an advanced three-dimensional (3D) method of assessing tissue oxygenation in vivo. This innovation was enabled by the technological developments in EPR (Electron Paramagnetic Resonance) and the application of the water-soluble oximetric spin probes from the triaryl family, offering fast and sensitive oxygenation data. The relaxation time of the spin probe (T1 and/or T2) provides accurate information about pO2 in selected voxels.
Human glioblastoma LN229 tumors were grown in the interscapular fad pad of BALB/c nude mice. Ultrasound (US) imaging was used as a reference for tumor anatomical information. To image tissue pO2, the animals were placed in a fixed position in the animal bed with fiducials, enabling registration between the imaging modalities. After the OX071 contrast agent was administered, EPRI was performed, followed by US B-mode. Because of the low spin probe toxicity, the procedure can be repeated during tumor growth or treatment. Following imaging, the registration process was carried out using software written in MATLAB. Ultimately, the hypoxic fraction can be calculated for a specific tumor, and the histogram of pO2 tissue distribution can be compared over time. EPRI combined with ultrasound is an excellent tool for oxygen mapping of tumors in the preclinical setting.

Quantitative 3D oxygen maps of murine tumors were imaged noninvasively using Pulse Electron Paramagnetic Resonance. Ultrasound B-mode and Power Doppler were used for anatomy and vascular structure. Images from both modalities were superimposed enabling multi-parametric tumor analysis.

The precise and real-time measurement of oxygen partial pressure (pO2) brings valuable information in many pathologies, including cancer. Low tumor pO2 ...

Intravital Microscopy of Tumor-associated Vasculature Using Advanced Dorsal Skinfold Window Chambers on Transgenic Fluorescent Mice

Tumor and tumor vessel development, as well as tumor response to therapeutics, are highly dynamic biological processes. Histology provides static information and is often not sufficient for a correct interpretation. Intravital evaluation, in which a process is followed in time, provides extra and often unexpected information. With the creation of transgenic animals expressing cell-specific markers and live cell tracers, improvements to imaging equipment, and the development of several imaging chambers, intravital microscopy has become an important tool to better understand biological processes. This paper describes an experimental design for the investigation of tumor vessel development and of therapeutic effects in a spatial and temporal manner. Using this setup, the stage of vessel development, tip cell and lumen formation, blood flow, extravasation, an established vascular bed, and vascular destruction can be visualized and followed. Furthermore, therapeutic effects, intratumoral fate, and the localization of chemotherapeutic compounds can also be followed.

This protocol describes the intravital imaging of transgenic mice expressing cell-specific fluorescent markers. Intravital imaging provides a non-invasive method for high-resolution observations in living animals using implantable windows through which the microscopic visualization of processes is possible. This method is especially useful to study longitudinal processes.

Spatial Measurements of Perfusion, Interstitial Fluid Pressure and Liposomes Accumulation in Solid Tumors

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