This work was in part supported by a grant from the National Cancer Institute, grant number U24CA264298. We thank Dawn Holley, Kim Halbert, and Mehdi Khalighi from the PET/MRI Metabolic Service Center for their assistance with the acquisition of PET/MRI scans at the Lucas Research Center at Stanford. We thank the members of the Daldrup-Link lab for valuable input and discussions regarding this project.

This protocol has been generated for a prospective clinical trial and co-clinical research. The study was compliant with the Health Insurance Portability and Accountability Act (HIPAA) and approved by the Stanford University institutional review board (IRB). All patients or their legally authorized representative signed a written informed consent, and all children between 7 and 18 years of age signed an assent form.
1. Installing and starting the T2 Fit Map plugin
<ol>
	<li>Start the Osirix software. Install the T2 Fit Map plugin from the plugin manager and restart the software.
	<ol>
		<li>On the menu bar, click the Plugins button. Click on the drop-down menu and select Install a plugin package (Figure 1).</li>
		<li>Once the plugin manager is loaded, select the available plugins from the drop-down menu and then T2 Fit Map (Figure 2).</li>
		<li>Click download &#38; install. Close the plugin manager and restart the software.</li>
	</ol>
	</li>
	<li>Load the multi-echo gradient echo sequence images as DICOM files into the software.</li>
	<li>Change the mouse button function to draw a Region of Interest (ROI) (Figure 3).</li>
	<li>Using this mouse button function, define a shape for the required ROI: select Oval or Closed Polygon, or the desired shape from the drop-down menu (Figure 4).</li>
	<li>Draw ROIs in the required images with different echo times (TEs).</li>
	<li>Select the ROIs in all the images with different TEs for which the T2* map is required.</li>
	<li>Click the Plugins button, select Image filters from the drop-down menu, and then select T2 Fit Map.</li>
	<li>Click on T2 Fit Map. A dialog box will open; click on Generate Map (which is located at the bottom of the dialog box) (Figure 5). 
	NOTE: A fitting curve is generated with minimum, mean, and maximum T2* values for the selected ROIs with various TEs (ms). The mean T2* value is calculated and displayed below the curve (Figure 6).</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64773/64773fig01.jpg" /> 
Figure 1: Selecting &#39;Install a plugin package&#39; from the drop-down menu. <a href="https://www.jove.com/files/ftp_upload/64773/64773fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64773/64773fig02.jpg" /> 
Figure 2: Selecting &#39;T2 Fit Map&#39; from the available plugins. <a href="https://www.jove.com/files/ftp_upload/64773/64773fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/64773/64773fig03.jpg" /> 
Figure 3: Screenshot demonstrating how to change the mouse button function to draw a region of interest (ROI). <a href="https://www.jove.com/files/ftp_upload/64773/64773fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/64773/64773fig04.jpg" /> 
Figure 4: Screenshot showing how to select different shapes for the ROI. <a href="https://www.jove.com/files/ftp_upload/64773/64773fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/64773/64773fig05.jpg" /> 
Figure 5: Screenshot showing how to select &#39;Generate Map&#39; after selecting &#39;T2 Fit Map&#39;. <a href="https://www.jove.com/files/ftp_upload/64773/64773fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/64773/64773fig06.jpg" /> 
Figure 6: Screenshot showing the generation of a fitting curve for T2* values. <a href="https://www.jove.com/files/ftp_upload/64773/64773fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
2. Exclusion of noise using the definition of mask
NOTE: To define a mask on the first echo of the T2map_MSME data used to calculate the parametric maps, set a lower first-echo signal threshold for T2* value calculation (the T2* map volume will now exclude the pixels with signals too low for accurate calculation at the first multi-spin multi-echo (MSME) echo. The threshold can be increased to exclude more pixels, or decreased to include more pixels).
<ol>
	<li>To define the mask ROI on an image series outside the parametric data, open the desired series (e.g., first echo of the T2map_MSME with TE = 15) and select a slice.</li>
	<li>At bottom of the ROI drop-down menu, select Grow Region&#8230;.</li>
	<li>Select the 3D Growing Region&#8230; radio button (Figure 7).</li>
	<li>In the Algorithm drop-down menu, select Threshold (lower/upper bounds).</li>
	<li>Set the lower and upper thresholds to 0 and X% of the contralateral calf muscle signal, respectively (e.g., set the threshold to the value that will mask out the most speckle in the tumor ROI and will leave the most evaluable tumor T2(*)s).</li>
	<li>Set the ROI name as desired.</li>
	<li>Click on the image to place a seed for ROI growing.</li>
	<li>Click the Compute button.</li>
	<li>In the ROI menu, select Save All ROIs of this Series&#8230; (Figure 8). 
	NOTE: Now, the ROI defining the area to mask out of the parametric maps has been saved and can be applied to the parametric data.</li>
	<li>Open the Parametric dataset in the 4D viewer.</li>
	<li>In the ROI menu, select Import ROI(s).... 
	NOTE: The mask ROI is now in the first parametric series.</li>
	<li>Check that the ROIs are in the first 3D volume and not 4D.</li>
	<li>Apply mask to map the data. To do so, at the bottom of the ROI drop-down menu, select Set Pixel Values To. Then, select apply to: ROIs with same name&#8230; (Figure 9).</li>
	<li>Check the Propagate to 4D series box.</li>
	<li>Set pixels that are Inside ROIs.</li>
	<li>Set To this new value: as 0.</li>
</ol>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/64773/64773fig07.jpg" /> 
Figure 7: Screenshot showing the segmentation parameters. <a href="https://www.jove.com/files/ftp_upload/64773/64773fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/64773/64773fig08.jpg" /> 
Figure 8: Screenshot showing how to select &#34;Save All ROIs of this Series&#8230;&#34;. <a href="https://www.jove.com/files/ftp_upload/64773/64773fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/64773/64773fig09.jpg" /> 
Figure 9: Screenshot showing the values to be inputted in &#34;Set Pixel Values To&#34;. <a href="https://www.jove.com/files/ftp_upload/64773/64773fig09large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<ol>
	<li>Garbowski, M. W., 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=Biopsy-based+calibration+of+T2*+magnetic+resonance+for+estimation+of+liver+iron+concentration+and+comparison+with+R2+Ferriscan.">Biopsy-based calibration of T2* magnetic resonance for estimation of liver iron concentration and comparison with R2 Ferriscan.</a> Journal of Cardiovascular Magnetic Resonance. 16 (1), 40 (2014).</li><li>. OsiriXDICOM Viewer Available from: <a target="_blank" href="https://www.osirix-viewer.com/">https://www.osirix-viewer.com/</a> (2023)</li><li>Linfante, I., Llinas, R. H., Caplan, L. R., Warach, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MRI+features+of+intracerebral+hemorrhage+within+2+hours+from+symptom+onset.">MRI features of intracerebral hemorrhage within 2 hours from symptom onset.</a> Stroke. 30 (11), 2263-2267 (1999).</li><li>Labranche, R., 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=Liver+iron+quantification+with+MR+imaging:+a+primer+for+radiologists.">Liver iron quantification with MR imaging: a primer for radiologists.</a> Radiographics. 38 (2), 392-412 (2018).</li><li>Triadyaksa, P., Oudkerk, M., Sijens, P. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cardiac+T2*+mapping:+Techniques+and+clinical+applications.">Cardiac T2* mapping: Techniques and clinical applications.</a> Journal of Magnetic Resonance Imaging. 52 (5), 1340-1351 (2020).</li><li>Anderson, L. 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=Cardiovascular+T2-star+(T2*)+magnetic+resonance+for+the+early+diagnosis+of+myocardial+iron+overload.">Cardiovascular T2-star (T2*) magnetic resonance for the early diagnosis of myocardial iron overload.</a> European Heart Journal. 22 (23), 2171-2179 (2001).</li><li>Seo, M., 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=Estimation+of+T2*+relaxation+time+of+breast+cancer:+correlation+with+clinical,+imaging+and+pathological+features.">Estimation of T2* relaxation time of breast cancer: correlation with clinical, imaging and pathological features.</a> Korean Journal of Radiology. 18 (1), 238-248 (2017).</li><li>Serkova, N. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanoparticle-based+magnetic+resonance+imaging+on+tumor-associated+macrophages+and+inflammation.">Nanoparticle-based magnetic resonance imaging on tumor-associated macrophages and inflammation.</a> Frontiers in Immunology. 8, 590 (2017).</li><li>Chen, X., Qiu, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+pilot+study+of+short+T2*+measurements+with+ultrashort+echo+time+imaging+at+0.35+T.">A pilot study of short T2* measurements with ultrashort echo time imaging at 0.35 T.</a> BioMedical Engineering OnLine. 17 (1), 70 (2018).</li><li>Yi, J., Lee, Y. H., Song, H. -. T., Suh, J. -. S. <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+T2*+between+regular+echo+time+and+ultrashort+echo+time+with+3D+cones+at+3+tesla+for+knee+meniscus.">Comparison of T2* between regular echo time and ultrashort echo time with 3D cones at 3 tesla for knee meniscus.</a> Medicine. 97 (48), e13443 (2018).</li><li>Weishaupt, D., 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> How Does MRI Work?: An Introduction to the Physics and Function of Magnetic Resonance Imaging. , (2006).</li><li>Wood, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Guidelines+for+quantifying+iron+overload.">Guidelines for quantifying iron overload.</a> Hematology. American Society of Hematology. 2014 (1), 210-215 (2014).</li><li>Branisso, P. P. F., 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=Non-invasive+methods+for+iron+overload+evaluation+in+dysmetabolic+patients.">Non-invasive methods for iron overload evaluation in dysmetabolic patients.</a> Annals of Hepatology. 27 (4), 100707 (2022).</li><li>Schaefer, B., Meindl, E., Wagner, S., Tilg, H., Zoller, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intravenous+iron+supplementation+therapy.">Intravenous iron supplementation therapy.</a> Molecular Aspects of Medicine. 75, 100862 (2020).</li><li>Haacke, E. M., Mittal, S., Wu, Z., Neelavalli, J., Cheng, Y. -. C. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Susceptibility-weighted+imaging:+technical+aspects+and+clinical+applications,+part+1.">Susceptibility-weighted imaging: technical aspects and clinical applications, part 1.</a> AJNR: American Journal of Neuroradiology. 30 (1), 19-30 (2009).</li><li>. T2 Mapping Slicer Extension Available from: <a target="_blank" href="https://github.com/gattia/Slicer-T2mapping">https://github.com/gattia/Slicer-T2mapping</a> (2021)</li><li>3D Slicer image computing platform. 3D Slicer Available from: <a target="_blank" href="https://slicer.org/">https://slicer.org/</a> (2023)</li><li>Messroghli, D. R., 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=An+open-source+software+tool+for+the+generation+of+relaxation+time+maps+in+magnetic+resonance+imaging.">An open-source software tool for the generation of relaxation time maps in magnetic resonance imaging.</a> BMC Medical Imaging. 10, 16 (2010).</li><li>. GNU Octave Available from: <a target="_blank" href="https://octave.org/">https://octave.org/</a> (2023)</li><li>Chavhan, G. B., Babyn, P., Thomas, B., Shroff, M., Haacke, E. 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,+techniques,+and+applications+of+T2*-based+MR+imaging+and+its+special+applications.">Principles, techniques, and applications of T2*-based MR imaging and its special applications.</a> Radiographics. 29 (5), 1433-1449 (2009).</li><li>Aghighi, M., 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=Magnetic+resonance+imaging+of+tumor+associated+macrophages:+clinical+translation.">Magnetic resonance imaging of tumor associated macrophages: clinical translation.</a> Clinical Cancer Research. 24 (17), 4110-4118 (2018).</li><li>Trujillo-Alonso, V., 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=FDA-approved+ferumoxytol+displays+anti-leukaemia+efficacy+against+cells+with+low+ferroportin+levels.">FDA-approved ferumoxytol displays anti-leukaemia efficacy against cells with low ferroportin levels.</a> Nature Nanotechnology. 14 (6), 616-622 (2019).</li><li>Ishiyama, K., 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=Tumor-liver+contrast+and+subjective+tumor+conspicuity+of+respiratory-triggered+T2-weighted+fast+spin-echo+sequence+compared+with+T2*-weighted+gradient+recalled-echo+sequence+for+ferucarbotran-enhanced+magnetic+resonance+imaging+of+hepatic+malignant+tumors.">Tumor-liver contrast and subjective tumor conspicuity of respiratory-triggered T2-weighted fast spin-echo sequence compared with T2*-weighted gradient recalled-echo sequence for ferucarbotran-enhanced magnetic resonance imaging of hepatic malignant tumors.</a> Journal of Magnetic Resonance Imaging. 27 (6), 1322-1326 (2008).</li><li>Hirokawa, Y., 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=Hepatic+lesions:+improved+image+quality+and+detection+with+the+periodically+rotated+overlapping+parallel+lines+with+enhanced+reconstruction+technique-evaluation+of+SPIO-enhanced+T2-weighted+MR+images.">Hepatic lesions: improved image quality and detection with the periodically rotated overlapping parallel lines with enhanced reconstruction technique-evaluation of SPIO-enhanced T2-weighted MR images.</a> Radiology. 251 (2), 388-397 (2009).</li><li>Tonan, T., 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=Evaluation+of+small+(&#8804;2cm)+dysplastic+nodules+and+well-differentiated+hepatocellular+carcinomas+with+ferucarbotran-enhanced+MRI+in+a+1.0-T+MRI+unit:+Utility+of+T2*-weighted+gradient+echo+sequences+with+an+intermediate-echo+time.">Evaluation of small (&#8804;2cm) dysplastic nodules and well-differentiated hepatocellular carcinomas with ferucarbotran-enhanced MRI in a 1.0-T MRI unit: Utility of T2*-weighted gradient echo sequences with an intermediate-echo time.</a> European Journal of Radiology. 64 (1), 133-139 (2007).</li><li>Rief, M., 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=Detection+of+focal+liver+lesions+in+unenhanced+and+ferucarbotran-enhanced+magnetic+resonance+imaging:+a+comparison+of+T2-weighted+breath-hold+and+respiratory-triggered+sequences.">Detection of focal liver lesions in unenhanced and ferucarbotran-enhanced magnetic resonance imaging: a comparison of T2-weighted breath-hold and respiratory-triggered sequences.</a> Magnetic Resonance Imaging. 27 (9), 1223-1229 (2009).</li></ol>

The authors have nothing to disclose.

Our protocol allows us to measure tumor T2* relaxation times based on multi-echo gradient-echo sequences, an external software, and a plugin for creating T2* maps. The critical steps within the protocol are the inclusion of the multi-echo gradient-echo sequence with very short TEs into the scanning protocol, and the monoexponential fit of the multi-echo gradient-echo images using external software. It is important to arrange the input multi-echo gradient-echo images according to their acquisition times. This can be achie...

Noninvasive quantification of tumor T2* relaxation times in various tissues of the body with magnetic resonance imaging (MRI) is widely established1. The rationale for this article is to provide a protocol for the measurement of tumor T2* relaxation times which is independent of scanner software like Osirix2. This will allow uniform analyses of imaging data from different centers, different scanners, and different vendors. Indeed, thousands of users could potentially use the same approach, thereby increasing the standardization of tumor T2* measurements. T2* measurements are used for different purposes by neuroradiologists, cardiac imaging experts, and abdominal imaging experts, among others. MRI pulse sequences for measurements of tissue T2* relaxation times have been applied and optimized for the assessment of intracranial bleeds3, hepatic iron content1,4, and cardiac iron content5,6, among others. Other investigators have used T2* measurements to generate quantitative estimates of iron oxide nanoparticle accumulations in malignant tumors7,8. However, many of these previous approaches utilized institutional software or specific scanner software, which would be limited to use at a specific institution or for processing data obtained on a specific scanner. Here, we describe a universally applicable approach for generating tumor T2* maps and tumor T2* relaxation times based on preclinical or clinical MRI data from any scanner that can generate multi-echo gradient echo images. The required gradient echo sequence should have very short first echo times and close inter-echo spacing9,10. The multi-echo gradient echo images are then fed into the external software, tumor T2* maps are calculated, and tumor T2* relaxation times are measured. The T2 Fit Map plugin in the external models&#39; T2* decay curves as a monoexponential fit to S(t) = Soe-t/T2* 11 where S(t) represents the signal or process value at a given time t; S0 is the initial value of the signal or process at t = 0; t denotes time; T2*, also known as the apparent transverse relaxation time, characterizes the decay rate of the signal or process; and e is the base of the natural logarithm (approximately equal to 2.71828). The equation describes an exponential decay, where the signal or process decreases over time as a function of the decay rate T2*. The larger the value of T2*, the slower the decay rate, and vice versa. The same software can also be used to input multi-echo spin echo images and generate tumor T2 values by fitting the T2 decay curve to S(t) = Soe-t/T2. The curve fitting was performed using external software, without incorporating a constant offset. Both decay curves exhibit single exponential behavior, with T2* demonstrating a shorter duration compared to T2.
In patients with hemosiderosis and hemochromatosis, the quantification of liver iron content by tissue biopsy is the gold standard, whereas noninvasive MR imaging is the point of care for establishing baseline values and monitoring changes over time noninvasively12,13. While generating T2* maps for liver iron quantification is well established4, there is no standardized protocol to measure tumor T2* relaxation times. While T2* maps can also be generated by scanner software, it is limited to a specific scanner and vendor. In the field of oncology, serial imaging studies of a given patient often occur on different scanners, and multicenter MRI data are acquired based on imaging studies from different scanners and different vendors. In addition, co-clinical imaging research is being increasingly implemented and requires the comparison of MRI data of patients and mouse models that simulate their tumor. The purpose of this protocol is to provide a protocol for the measurement of tumor T2* relaxation times that are independent of the scanner software. This will allow uniform analysis of imaging data from different centers and different scanners. Indeed, thousands of users could potentially use the same approach, thereby increasing the standardization and reproducibility of tumor T2* measurements. Our protocol utilizes external software, which can be downloaded from the internet. Multi-echo gradient echo images are fed into the software and fit to a formula for monoexponential decay to generate a T2* map, on which tumor T2* relaxation times can be measured using operator-defined regions of interest (ROIs)5. Iron oxide nanoparticles can be infused at different doses14, In our study, the patient received a Ferumoxytol injection (30 mg/mL) containing 510 mg of elemental iron in a 17 mL volume, at a dosage of 5 mg elemental iron per kg body weight. Subsequently multi-echo gradient echo sequences were obtained15 using set sequence parameters for data acquisition.

<table><tbody><tr><td>OsiriX</td><td>Pixmeo SARL</td><td></td><td>https://www.osirix-viewer.com/</td></tr><tr><td>3T GE MR 750</td><td>GE Healthcare, Chicago, IL</td><td></td><td></td></tr><tr><td>FERAHEME (ferumoxytol injection)</td><td>AMAG Pharmaceuticals, Inc. 1100 Winter Street Waltham, MA 02451</td><td></td><td></td></tr></tbody></table>

measurement of tumor t2* relaxation times after iron oxide nanoparticle administration

T2* relaxometry is one of the established methods to measure the effect of superparamagnetic iron oxide nanoparticles on tumor tissues with magnetic resonance imaging (MRI). Iron oxide nanoparticles shorten the T1, T2, and T2* relaxation times of tumors. While the T1 effect is variable based on the size and composition of the nanoparticles, the T2 and T2* effects are usually predominant, and T2* measurements are the most time-efficient in a clinical context. Here, we present our approach to measuring tumor T2* relaxation times, using multi-echo gradient echo sequences, external software, and a standardized protocol for creating a T2* map with scanner-independent software. This facilitates the comparison of imaging data from different clinical scanners, different vendors, and co-clinical research work (i.e., tumor T2* data obtained in mouse models and patients). Once the software is installed, the T2 Fit Map plugin needs to be installed from the plugin manager. This protocol provides step-by-step procedural details, from importing the multi-echo gradient echo sequences into the software, to creating color-coded T2* maps and measuring tumor T2* relaxation times. The protocol can be applied to solid tumors in any body part and has been validated based on preclinical imaging data and clinical data in patients. This could facilitate tumor T2* measurements for multi-center clinical trials and improve the standardization and reproducibility of tumor T2* measurements in co-clinical and multi-center data analyses.

<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/64773/64773fig10.jpg" /> 
Figure 10: The T2* map with an ROI overlaid on the metastatic osteosarcoma lesion which shows the mean and standard deviation T2* value. <a href="https://www.jove.com/files/ftp_upload/64773/64773fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
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Watch this Scientific Journal Video about Measurement of Tumor T2* Relaxation Times after Iron Oxide Nanoparticle Administration at JoVE.com

Measurement of Tumor T2* Relaxation Times after Iron Oxide Nanoparticle Administration

We present a standardized protocol for the quantification of T2* relaxation times of tumors using external software. Multi-echo gradient echo images are acquired and fed into the software to create tumor T2* maps and measure tumor T2* relaxation times.

T2* relaxometry is one of the established methods to measure the effect of superparamagnetic iron oxide nanoparticles on tumor tissues with magnetic ...

measurement-tumor-t2-relaxation-times-after-iron-oxide-nanoparticle

Research

JoVE Journal

Medicine

1.2K Views.  Stanford University, School of Medicine. We present a standardized protocol for the quantification of T2* relaxation times of tumors using external software. Multi-echo gradient echo images are acquired and fed into the software to create tumor T2* maps and measure tumor T2* relaxation times.

Video: Measurement of Tumor T2* Relaxation Times after Iron Oxide Nanoparticle Administration

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring 

Nanomedications can be carried by blood borne monocyte-macrophages into the reticuloendothelial system (RES; spleen, liver, lymph nodes) and to end organs. The latter include the lung, RES, and brain and are operative during human immunodeficiency virus type one (HIV-1) infection. Macrophage entry into tissues is notable in areas of active HIV-1 replication and sites of inflammation. In order to assess the potential of macrophages as nanocarriers, superparamagnetic iron-oxide and/or drug laden particles coated with surfactants were parenterally injected into HIV-1 encephalitic mice. This was done to quantitatively assess particle and drug biodistribution. Magnetic resonance imaging (MRI) test results were validated by histological coregistration and enhanced image processing. End organ disease as typified by altered brain histology were assessed by MRI. The demonstration of robust migration of nanoformulations into areas of focal encephalitis provides '"proof of concept" for the use of advanced bioimaging techniques to monitor macrophage migration. Importantly, histopathological aberrations in brain correlate with bioimaging parameters making the general utility of MRI in studies of cell distribution in disease feasible. We posit that using such methods can provide a real time index of disease burden and therapeutic efficacy with translational potential to humans.

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Bioimaging methods used to assess cell biodistribution of nanoparticles are applicable for therapeutic and diagnostic monitoring of nanoformulated compounds. The methods described herein are sensitive and specific when assessed by histological coregistration. The methodologies provide a translational pathway from rodent to human applications.

Nanomedications can be carried by blood borne monocyte-macrophages into the reticuloendothelial system (RES; spleen, liver, lymph nodes) and to end ...

Bioengineering

Radionuclide-fluorescence Reporter Gene Imaging to Track Tumor Progression in Rodent Tumor Models

Metastasis is responsible for most cancer deaths. Despite extensive research, the mechanistic understanding of the complex processes governing metastasis remains incomplete. In vivo models are paramount for metastasis research, but require refinement. Tracking spontaneous metastasis by non-invasive in vivo imaging is now possible, but remains challenging as it requires long-time observation and high sensitivity. We describe a longitudinal combined radionuclide and fluorescence whole-body in vivo imaging approach for tracking tumor progression and spontaneous metastasis. This reporter gene methodology employs the sodium iodide symporter (NIS) fused to a fluorescent protein (FP). Cancer cells are engineered to stably express NIS-FP followed by selection based on fluorescence-activated cell sorting. Corresponding tumor models are established in mice. NIS-FP expressing cancer cells are tracked non-invasively in vivo at the whole-body level by positron emission tomography (PET) using the NIS radiotracer [18F]BF4-. PET is currently the most sensitive in vivo imaging technology available at this scale and enables reliable and absolute quantification. Current methods either rely on large cohorts of animals that are euthanized for metastasis assessment at varying time points, or rely on barely quantifiable 2D imaging. The advantages of the described method are: (i) highly sensitive non-invasive in vivo 3D PET imaging and quantification, (ii) automated PET tracer production, (iii) a significant reduction in required animal numbers due to repeat imaging options, (iv) the acquisition of paired data from subsequent imaging sessions providing better statistical data, and (v) the intrinsic option for ex vivo confirmation of cancer cells in tissues by fluorescence microscopy or cytometry. In this protocol, we describe all steps required for routine NIS-FP-afforded non-invasive in vivo cancer cell tracking using PET/CT and ex vivo confirmation of in vivo results. This protocol has applications beyond cancer research whenever in vivo localization, expansion and long-time monitoring of a cell population is of interest.

We describe a protocol for preclinical in vivo tracking of cancer metastasis. It is based on a radionuclide-fluorescence reporter combining the sodium iodide symporter, detected by non-invasive [18F]tetrafluoroborate-PET, and a fluorescent protein for streamlined ex vivo confirmation. The method is applicable for preclinical in vivo cell tracking beyond tumor biology.

Metastasis is responsible for most cancer deaths. Despite extensive research, the mechanistic understanding of the complex processes governing metastasis ...

Cancer Research

Preparation and In Vitro Characterization of Dendrimer-based Contrast Agents for Magnetic Resonance Imaging

Paramagnetic complexes of gadolinium(III) with acyclic or macrocyclic chelates are the most commonly used contrast agents (CAs) for magnetic resonance imaging (MRI). Their purpose is to enhance the relaxation rate of water protons in tissue, thus increasing the MR image contrast and the specificity of the MRI measurements. Current clinically approved contrast agents are low molecular weight molecules that are rapidly cleared from the body. The use of dendrimers as carriers of paramagnetic chelators can play an important role in the future development of more efficient MRI contrast agents. Specifically, the increase in local concentration of the paramagnetic species results in a higher signal contrast. Furthermore, this CA provides a longer tissue retention time due to its high molecular weight and size. Here, we demonstrate a convenient procedure for the preparation of macromolecular MRI contrast agents based on poly(amidoamine) (PAMAM) dendrimers with monomacrocyclic DOTA-type chelators (DOTA &#8211; 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate). The chelating unit was appended by exploiting the reactivity of the isothiocyanate (NCS) group towards the amine surface groups of the PAMAM dendrimer to form thiourea bridges. Dendrimeric products were purified and analyzed by means of nuclear magnetic resonance spectroscopy, mass spectrometry, and elemental analysis. Finally, high resolution MR images were recorded and the signal contrasts obtained from the prepared dendrimeric and the commercially available monomeric agents were compared.

Preparation and In Vitro Characterization of Dendrimer-based Contrast Agents for Magnetic Resonance Imaging

This protocol describes the preparation and characterization of a dendrimeric magnetic resonance imaging (MRI) contrast agent that carries cyclen-based macrocyclic chelates coordinating paramagnetic gadolinium ions. In a series of MRI experiments in vitro, this agent produced an amplified MRI signal when compared to the commercially available monomeric analogue.

Paramagnetic complexes of gadolinium(III) with acyclic or macrocyclic chelates are the most commonly used contrast agents (CAs) for magnetic resonance ...

Chemistry

MR Molecular Imaging of Prostate Cancer with a Small Molecular CLT1 Peptide Targeted Contrast Agent

Tumor extracellular matrix has abundance of cancer related proteins that can be used as biomarkers for cancer molecular imaging. In this work, we demonstrated effective MR cancer molecular imaging with a small molecular peptide targeted Gd-DOTA monoamide complex as a targeted MRI contrast agent specific to clotted plasma proteins in tumor stroma. We performed the experiment of evaluating the effectiveness of the agent for non-invasive detection of prostate tumor with MRI in a mouse orthotopic PC-3 prostate cancer model. The targeted contrast agent was effective to produce significant tumor contrast enhancement at a low dose of 0.03 mmol Gd/kg. The peptide targeted MRI contrast agent is promising for MR molecular imaging of prostate tumor.

To demonstrate MR cancer molecular imaging with a small peptide targeted MRI contrast agent specific to clotted plasma proteins in tumor stroma in a mouse prostate cancer model.

Tumor extracellular  matrix has abundance of cancer related proteins that can be used as biomarkers  for cancer molecular imaging. In this work,  we ...

Biofunctionalized Prussian Blue Nanoparticles for Multimodal Molecular Imaging Applications

Multimodal, molecular imaging allows the visualization of biological processes at cellular, subcellular, and molecular-level resolutions using multiple, complementary imaging techniques. These imaging agents facilitate the real-time assessment of pathways and mechanisms in vivo, which enhance both diagnostic and therapeutic efficacy. This article presents the protocol for the synthesis of biofunctionalized Prussian blue nanoparticles (PB NPs) - a novel class of agents for use in multimodal, molecular imaging applications. The imaging modalities incorporated in the nanoparticles, fluorescence imaging and magnetic resonance imaging (MRI), have complementary features. The PB NPs possess a core-shell design where gadolinium and manganese ions incorporated within the interstitial spaces of the PB lattice generate MRI contrast, both in T1 and T2-weighted sequences. The PB NPs are coated with fluorescent avidin using electrostatic self-assembly, which enables fluorescence imaging. The avidin-coated nanoparticles are modified with biotinylated ligands that confer molecular targeting capabilities to the nanoparticles. The stability and toxicity of the nanoparticles are measured, as well as their MRI relaxivities. The multimodal, molecular imaging capabilities of these biofunctionalized PB NPs are then demonstrated by using them for fluorescence imaging and molecular MRI in vitro.

This protocol describes the synthesis of biofunctionalized Prussian blue nanoparticles and their use as multimodal, molecular imaging agents. The nanoparticles have a core-shell design where gadolinium or manganese ions within the nanoparticle core generate MRI contrast. The biofunctional shell contains fluorophores for fluorescence imaging and targeting ligands for molecular targeting.

Multimodal, molecular imaging allows the visualization of biological processes at cellular, subcellular, and molecular-level resolutions using multiple, ...

Nanodrug Targeting Oncogenic miRNA-10b for Treating Metastatic Breast Cancer

Monitoring of Nanodrug Accumulation in Murine Breast Cancer Metastases

Metastatic breast cancer is a devastating disease with very limited therapeutic options, calling for new therapeutic strategies. Oncogenic miRNAs have been shown to be associated with the metastatic potential of breast cancer and are implicated in tumor cell migration, invasion, and viability. However, it can be difficult to deliver an inhibitory RNA molecule to the tissue of interest. To overcome this challenge and deliver active antisense oligonucleotides to tumors, we utilized magnetic iron oxide nanoparticles as a delivery platform. These nanoparticles target tissues with increased vascular permeability, such as sites of inflammation or cancer. Delivery of these nanoparticles can be monitored in vivo by magnetic resonance imaging (MRI) due to their magnetic properties. Translation of this therapeutic approach into the clinic will be more accessible because of its compatibility with this relevant imaging modality. They can also be labeled with other imaging reporters such as a Cy5.5 near-infrared optical dye for correlative optical imaging and fluorescence microscopy. Here, we demonstrate that nanoparticles labeled with Cy5.5 and conjugated to therapeutic oligomers targeting oncogenic miRNA-10b (termed MN-anti-miR10b, or &#34;nanodrug&#34;) administered intravenously accumulate in metastatic sites, opening a possibility for therapeutic intervention of metastatic breast cancer.

Here, we describe the protocol for in vivo delivery of magnetic iron oxide nanoparticles carrying RNA oligomers to metastatic breast cancer in animal models, providing a clinically viable approach for the therapeutic silencing of oncogenic nucleic acids.

Metastatic breast cancer is a devastating disease with very limited therapeutic options, calling for new therapeutic strategies. Oncogenic miRNAs have ...

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 ...

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

MRI provides a sensitive and specific imaging tool to detect acute ischemic stroke by means of a reduced diffusion coefficient of brain water. In a rat model of ischemic stroke, differences in quantitative T1 and T2 MRI relaxation times (qT1 and qT2) between the ischemic lesion (delineated by low diffusion) and the contralateral non-ischemic hemisphere increase with time from stroke onset. The time dependency of MRI relaxation time differences is heuristically described by a linear function and thus provides a simple estimate of stroke onset time. Additionally, the volumes of abnormal qT1 and qT2 within the ischemic lesion increase linearly with time providing a complementary method for stroke timing. A (semi)automated computer routine based on the quantified diffusion coefficient is presented to delineate acute ischemic stroke tissue in rat ischemia. This routine also determines hemispheric differences in qT1 and qT2 relaxation times and the location and volume of abnormal qT1 and qT2 voxels within the lesion. Uncertainties associated with onset time estimates of qT1 and qT2 MRI data vary from &plusmn; 25 min to &plusmn; 47 min for the first 5 hours of stroke. The most accurate onset time estimates can be obtained by quantifying the volume of overlapping abnormal qT1 and qT2 lesion volumes, termed 'Voverlap' (&plusmn; 25 min) or by quantifying hemispheric differences in qT2 relaxation times only (&plusmn; 28 min). Overall, qT2 derived parameters outperform those from qT1. The current MRI protocol is tested in the hyperacute phase of a permanent focal ischemia model, which may not be applicable to transient focal brain ischemia.

A protocol for stroke onset time estimation in a rat model of stroke exploiting quantitative magnetic resonance imaging (qMRI) parameters is described. The procedure exploits diffusion MRI for delineation of the acute stroke lesion and quantitative T1 and T2 (qT1 and qT2) relaxation times for timing of stroke.

MRI provides a sensitive and specific imaging tool to detect acute ischemic stroke by means of a reduced diffusion coefficient of brain water. In a rat ...

Neuroscience

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 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 ...

Synthesis, Characterization, and Application of Superparamagnetic Iron Oxide Nanoprobes for Extrapulmonary Tuberculosis Detection

A molecular imaging probe comprising superparamagnetic iron oxide (SPIO) nanoparticles and Mycobacterium tuberculosis surface antibody (MtbsAb) was synthesized to enhance imaging sensitivity for extrapulmonary tuberculosis (ETB). An SPIO nanoprobe was synthesized and conjugated with MtbsAb. The purified SPIO-MtbsAb nanoprobe was characterized using TEM and NMR. To determine the targeting ability of the probe, SPIO-MtbsAb nanoprobes were incubated with Mtb for in vitro imaging assays and injected into Mtb-inoculated mice for in vivo investigation with magnetic resonance (MR). The contrast enhancement reduction on magnetic resonance imaging (MRI) of Mtb and THP1 cells showed proportional to the SPIO-MtbsAb nanoprobe concentration. After 30 min of intravenous SPIO-MtbsAb nanoprobe injection into Mtb-infected mice, the signal intensity of the granulomatous site was enhanced by 14-fold in the T2-weighted MR images compared with that in mice receiving PBS injection. The MtbsAb nanoprobes can be used as a novel modality for ETB detection.

To improve serological diagnostic tests for Mycobacterium tuberculosis antigens, we developed superparamagnetic iron oxide nanoprobes to detect extrapulmonary tuberculosis.

A molecular imaging probe comprising superparamagnetic iron oxide (SPIO) nanoparticles and Mycobacterium tuberculosis surface antibody (MtbsAb) was ...

Measurement of Tumor T2* Relaxation Times after Iron Oxide Nanoparticle Administration

Summary

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Chapters in this video

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring

Radionuclide-fluorescence Reporter Gene Imaging to Track Tumor Progression in Rodent Tumor Models

Preparation and In Vitro Characterization of Dendrimer-based Contrast Agents for Magnetic Resonance Imaging

MR Molecular Imaging of Prostate Cancer with a Small Molecular CLT1 Peptide Targeted Contrast Agent

Biofunctionalized Prussian Blue Nanoparticles for Multimodal Molecular Imaging Applications

Monitoring of Nanodrug Accumulation in Murine Breast Cancer Metastases

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

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

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

Synthesis, Characterization, and Application of Superparamagnetic Iron Oxide Nanoprobes for Extrapulmonary Tuberculosis Detection