The authors are thankful to Dr. Madsen at the University of Wisconsin-Madison and Cristel Baiu at Gammex Inc. for providing advice on TM materials. The authors are also grateful to Dr. Malcolm David Murray for providing the methods to construct the phantom.

1. Phantom Design
A drawing of the preclinical multimodality phantom is shown in Figure 1 7, 8. The size of the phantom is 38 mm in diameter and 115 mm in length to allow the phantom to be scanned in various animal scanners. The phantom contains five tumor-simulating test objects (diameter: 14, 10, 7, 4 and 2 mm) placed at a depth of 10 mm within the phantom.
2. Silicone Mold Construction
Silicone molds are prepared to cast the tumor-simulating test objects as described in this section 7. All acrylic plates and rods required for preparation of the silicone molds are cut with an accuracy of 25 &mu;m in the machine shop at the University of Texas Health Science Center at San Antonio (UTHSCSA).
<ol>
	<li>Make five holes (diameter: 14, 10, 7, 4, 2 mm) for test objects and another five holes (diameter: 6 mm) for alignment rods in two acrylic base plates (size: 4.2 cm &times; 11.5 cm &times; 0.9 cm) (Figure 2A).</li>
	<li>Cut spacer pairs with height of 7, 5, 3.5, 2 and 1 mm (size: 1.0 cm &times; 5.5 cm) (Figure 2B).</li>
	<li>Prepare steel balls (diameter: 14, 10, 7, 4 and 2 mm, accuracy: 2.5 &mu;m).</li>
	<li>Place two spacer pairs with height of 7 mm and a base plate onto a thin acrylic plate in sequence and tighten them using C-clamps (Figure 2C).</li>
	<li>Insert the steel ball with 14 mm diameter into 14 mm hole of the base plate and glue it using J-B KWIK (Figure 2C). Repeat the procedures for the rest of the balls (Figure 2D) and for the other base plate. Note that the steel balls in two base plates are glued as mirror images 7.</li>
	<li>Attach four 2.5 cm-high acrylic plates (size: 2.5 cm &times; 11.5 cm for two plates and 2.5 cm &times; 4.2 cm for another two plates) onto each base using masking tape like fences (Figure 3A).</li>
	<li>Attach the top plate (size: 4.2 cm &times; 11.5 cm, five holes with 0.8 cm of diameter, ten holes with 1.2 cm of diameter) in one of the base plate assemblies to insert five acrylic rods (diameter: 0.8 cm and length: 0.5 cm) with 1 mm tips, and to insert five alignment rods (diameter: 0.9 cm and length: 5.0 cm) and to pour silicone (Figure 3A).</li>
	<li>Insert the acrylic rods into the 0.8 cm holes in the top plate all the way to the top of steel balls and glue them using silicone glue. Then insert alignment rods into the holes in the base plate through larger holes in the top plate (Figure 3A).</li>
	<li>Mix part A of silicone rubber compound with part B in the ratio of 10 to 1 by weight.</li>
	<li>Pour the silicone rubber compound into the assembly and dry the assembly at room temperature for about 24 hr (Figure 3B).</li>
</ol>
3. Rotator Assembly
The rotator is prepared from PVC pipe and a rotisserie motor.
<ol>
	<li>Grind the end of a bolt to fit the hole of a rotisserie motor.</li>
	<li>Screw the ground bolt to the end of the PVC pipe (length: 270 mm and inner diameter: 75 mm) using a nut and a washer.</li>
	<li>Bend metal plates and glue them onto a plastic plate using J-B KWIK to support the PVC pipe and to adjust the height of PVC pipe 7.</li>
</ol>
4. TM Material Preparation
The protocols for preparing the TM materials are modified from those developed in Dr. Ernest L. Madsen's laboratory at the University of Wisconsin Madison and more details are in Lee et al. 8,11.
4.1 Background TM material preparation
<ol>
	<li>Pass commercial whole milk (200 cc) through 20 &mu;m and then 10 &mu;m mesh filters.</li>
	<li>Dissolve Thimerosal (0.2 g) in the filtered milk (100 cc).</li>
	<li>Using house vacuum, degas this milk solution for 30 sec at room temperature.</li>
	<li>Dissolve dry agarose (2 g) in deionized water (18 M&Omega;) (100 cc) at room temperature.</li>
	<li>Then add 1-propanol (7.9 cc) and BaSO4 (1 g) to the agarose solution.</li>
	<li>Degas the agarose solution and then heat it in a 95 &deg;C water bath until the agarose solution clears.</li>
	<li>While the agarose solution clears in the 95 &deg;C water bath, heat the condensed milk in a 55 &deg;C water bath.</li>
	<li>Move the molten agarose solution to the 55 &deg;C water bath to cool down.</li>
	<li>Once both solutions are at 55 &deg;C, mix agarose solution (50 cc) with condensed milk (50 cc) to make the ratio of 50 to 50 by volume and slowly stir the mixture followed by air bubble removal from the surface.</li>
	<li>Then add EDTA (0.103 g) and CuCl2&middot;2H2O (0.06 g) to the agarose-milk mixture followed by sufficient stirring to ensure homogeneity.</li>
	<li>Lastly, add glass beads (15 - 60 &mu;m diameter, mean diameter: 35 &mu;m) (0.1 g) and stir the final mixture repeatedly. Prior to use, soak the glass beads in concentrated nitric acid for 24 hr to remove any impurities and then rinse off the acid.</li>
</ol>
4.2 Test object TM material preparation
The test object TM material is prepared in a similar manner as the background TM material except for the following compositional differences:
<ol>
	<li>Pass commercial whole milk (20 cc) through 20 &mu;m and then 10 &mu;m mesh filters.</li>
	<li>Dissolve Thimerosal (0.02 g) in the filtered milk (10 cc).</li>
	<li>Dissolve dry agarose (0.60 g) in a room temperature solution of deionized water (10 cc) and 1-propanol (0.79 cc).</li>
	<li>Degas the agarose solution and then heat it in a 95 &deg;C water bath until the agarose solution clears.</li>
	<li>While the agarose solution clears in the 95 &deg;C water bath, heat the condensed milk in a 55 &deg;C water bath.</li>
	<li>Move the molten agarose solution to the 55 &deg;C water bath.</li>
	<li>Once both solutions are at 55 &deg;C, mix the agarose solution (5 cc) with condensed milk (5 cc) and slowly stir the mixture followed by air bubble removal from the surface.</li>
	<li>Then add EDTA (0.0017 g) and CuCl2&middot;2H2O (0.0010 g) to the agarose-milk followed by sufficient stirring.</li>
</ol>
5. Multimodality Phantom Assembly
Using the silicone molds, the following steps are accomplished to construct the multimodality phantom.
<ol>
	<li>On the silicone mold without 1 mm holes, attach nylon thread along the center of spheres and glue it at both ends of the mold using silicone glue (Figure 4A).</li>
	<li>Using a soft brush, apply silicone grease on the surface of two molds (Figure 4A) and assemble two molds using alignment rods.</li>
	<li>Prepare test object TM material as described in section 4.2 and pour it through 1 mm holes of the silicone mold using a 22-gauge needle of a syringe.</li>
	<li>To allow the test objects to set, store the molds in a refrigerator (5 &deg;C) for about 30 min.</li>
	<li>In each side of a half-cylindrical container (length: 115 mm and diameter: 38 mm), make two holes of 1 mm at a depth of 10 mm from the phantom surface in order to mount nylon thread with test objects. Make an additional hole of 6 mm to pour background TM material.</li>
	<li>Unload the test objects with nylon thread from the molds (Figure 4B) and then mount them in the half-cylindrical container (Figure 4C).</li>
	<li>Using 3M Scotch-Weld DP-100 and 3M duct tape, adhere thin non-conducting aluminum (thickness: 0.12 mm) onto the acrylic container. Block the 1 mm holes in the acrylic container using the same glue (Figure 4C).</li>
	<li>Prepare background TM material quickly and slowly pour it into the 6 mm hole of the container using a small plastic funnel.</li>
	<li>After removal of any air bubbles, glue the 6 mm hole using 3M Scotch-Weld DP-100.</li>
	<li>Once assembled, rotate the phantom at 2 rpm in the rotator for 4 to 5 hr at room temperature.</li>
	<li>Remove the nylon thread after the TM materials in the phantom completely hardens.</li>
</ol>
6. Multimodality Imaging
The phantom is scanned in preclinical ultrasound, CT and MRI and images in three modalities are acquired. The imaging protocols are described in detail in Lee et al. 7, 8.

<ol>
	<li>Prasad, S. 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=CT+tumor+measurement+for+therapeutic+response+assessment:+Comparison+of+unidimensional,+bidimensional,+and+volumetric+techniques-Initial+observations.">CT tumor measurement for therapeutic response assessment: Comparison of unidimensional, bidimensional, and volumetric techniques-Initial observations.</a> Radiology. 225 (2), 416-419 (2002).</li><li>Cortes, 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=Comparison+of+unidimensional+and+bidimensional+measurement+in+metastatic+non-small+cell+lung+cancer.">Comparison of unidimensional and bidimensional measurement in metastatic non-small cell lung cancer.</a> Br. J. Cancer. 87 (2), 158-160 (2002).</li><li>Saini, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Radiologic+measurement+of+tumor+size+in+clinical+trials:+past,+present,+and+future.">Radiologic measurement of tumor size in clinical trials: past, present, and future.</a> AJR Am. J. Roentgenol. 176 (2), 333-334 (2001).</li><li>Suzuki, C., 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=Radiologic+measurements+of+tumor+response+to+treatment:+practical+approaches+and+limitations.">Radiologic measurements of tumor response to treatment: practical approaches and limitations.</a> Radiographics. 28 (2), 329-344 (2008).</li><li>Therasse, P., 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=RECIST+revisited:+A+review+of+validation+studies+on+tumour+assessment.">RECIST revisited: A review of validation studies on tumour assessment.</a> Eur. J. Cancer. 42 (8), 1031-1039 (2006).</li><li>O'Connor, P. B., 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=Quantitative+imaging+biomarkers+in+the+clinical+development+of+targeted+therapeutics:+current+and+future+perspectives.">Quantitative imaging biomarkers in the clinical development of targeted therapeutics: current and future perspectives.</a> Lancet Oncol. 9 (8), 766-776 (2008).</li><li>Lee, Y. C., 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=Preclinical+multimodality+phantom+design+for+quality+assurance+of+tumor+size+measurement.">Preclinical multimodality phantom design for quality assurance of tumor size measurement.</a> BMC Med. Phys. 11 (1), (2011).</li><li>Lee, Y. C., 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=QA+procedures+for+multimodality+preclinical+tumor+drug+response+testing.">QA procedures for multimodality preclinical tumor drug response testing.</a> Med. Phys. 37 (9), 4806-4816 (2010).</li><li>Park, 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=Measuring+response+in+solid+tumors:+comparison+of+RECIST+and+WHO+response+criteria.">Measuring response in solid tumors: comparison of RECIST and WHO response criteria.</a> Jpn. J. Clin. Oncol. 33 (10), 533-537 (2003).</li><li>Eisenhauer, E. A., 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=New+response+evaluation+criteria+in+solid+tumors:+revised+RECIST+guideline+(version+1.1).">New response evaluation criteria in solid tumors: revised RECIST guideline (version 1.1).</a> Eur. J. Cancer. 45 (2), 228-247 (2009).</li><li>D'Souza, W. 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=Tissue+mimicking+materials+for+a+multi-imaging+modality+prostate+phantom.">Tissue mimicking materials for a multi-imaging modality prostate phantom.</a> Med. Phys. 28 (4), 688-700 (2001).</li><li>Mitchell, M. 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=Agarose+as+a+tissue+equivalent+phantom+material+for+NMR+images.">Agarose as a tissue equivalent phantom material for NMR images.</a> Magn. Reson. Imaging. 4 (3), 263-266 (1986).</li></ol>

No conflicts of interest declared.

The goal of this article was to provide the methods for making TM materials for multimodality imaging and constructing a preclinical multimodality phantom as a QA tool for accurate tumor size measurement using different modalities in multiple institutions. As previously mentioned, TM materials were originally developed by Dr. Ernest L. Madsen's laboratory at the University of Wisconsin Madison for a multi-imaging modality prostate phantom. We modified Dr. Madsen's TM material protocols for our own purpose in order to hav...

Assessment of the change in tumor size is an important endpoint for evaluating the activity of anti-tumor drugs in both tumor shrinkage and disease progression 9, 10. World Health Organization (WHO) and Response Evaluation Criteria in Solid Tumors (RECIST) are the codified methods for the anatomic assessment of tumor lesions in imaging modalities such as ultrasound (US), computed tomography (CT) or magnetic resonance imaging (MRI). For WHO criteria, the product of tumor maximum diameter and its largest perpendicular diameter in the transverse plane for target regions is calculated 4. In contrast, for RECIST, the sum of longest diameters in the transverse plane for a limited number of target lesions is calculated 4. In spite of continuously growing interest in tumor therapeutic response assessment, there has been no preclinical quality assurance (QA) phantom/QA procedures for the imaging biomarker.
Considering that tumor size measurement based on WHO criteria and/or RECIST is the only imaging biomarker approved by the United States Food and Drug Administration (FDA), as a starting point of QA for any other imaging biomarkers, Lee et al. designed and constructed UTHSCSA/Gammex Mark 1 and Mark 2 phantoms for QA of tumor size measurement in collaboration with Gammex Inc 7. The Mark 1 phantom was a revised version of a Gammex commercial US phantom and thus, the size was too large to fit into animal CT and MR scanners. Also some tools in the Mark 1 phantom were unnecessary for tumor size measurement. The Mark 2 phantom was designed based on RECIST which is the most recent FDA-approved imaging biomarker. However, the size of the Mark 2 phantom was still too large for MR scanners, and CT and MR image quality of the phantom was not acceptable for accurate tumor size measurement 7.
The QA phantom described herein was re-designed to overcome shortcomings of the previous phantoms and constructed using modified tissue-mimicking (TM) materials and protocols developed in our lab. This paper describes the details of the protocols for phantom construction: First, methods are introduced for preparing the silicone molds needed for casting tumor-simulating test objects and for assembling a rotator for rotating a phantom to prevent gravitation sedimentation. Second, protocols for preparing TM materials modified from D'Souza et al.'s for US, CT and MR imaging are described 11. The physical properties of the TM materials were tested in each modality to ensure that the TM materials represented human soft tissues as observed in the images acquired with the various modalities, but the results are not displayed here. Third, the protocol for phantom construction is described. Lastly, US, CT and MR images of the phantom are presented as results.

<table border="1">
	<tbody>
		<tr>
			<td>Reagent/Material</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>PVC pipe</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>Home Depot</td>
		</tr>
		<tr>
			<td>Bolt, nut, washer and metal plates</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>Home Depot</td>
		</tr>
		<tr>
			<td>Acrylic plates and rods</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>Plastic supply in San Antonio, TX</td>
		</tr>
		<tr>
			<td>Steel balls</td>
			<td>Nordex, Inc.</td>
			<td>AEC-M2-2, -4, -7, -10 and -14</td>
			<td>2, 4, 7, 10 and 14 mm diameter</td>
		</tr>
		<tr>
			<td>C-clamps</td>
			<td>Adjustable Clamp</td>
			<td>1420-C</td>
			<td>2 inch length</td>
		</tr>
		<tr>
			<td>Masking tape</td>
			<td>3M Industrial Adhesives and Tapes</td>
			<td>2600</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Duct tape</td>
			<td>3M Industrial Adhesives and Tapes</td>
			<td>S-3763SIL</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>J-B KWIK</td>
			<td>J-B WELD Co.</td>
			<td>380238</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>3M Scotch-Weld Epoxy Adhesive</td>
			<td>3M Industrial Adhesives and Tapes</td>
			<td>DP-100</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Silicone grease</td>
			<td>Permatex, Inc.</td>
			<td>22058</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Silicone glue</td>
			<td>DAP, Inc.</td>
			<td>688</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Silicone rubber compound</td>
			<td>Smooth-ON, Inc.</td>
			<td>Smooth-SilTM950 Part A and B</td>
			<td>A:B mix ratio = 10:1 by weight</td>
		</tr>
		<tr>
			<td>Brush</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>Hobby Lobby</td>
		</tr>
		<tr>
			<td>Syringe</td>
			<td>Becton Dickinson</td>
			<td>309604</td>
			<td>10 ml</td>
		</tr>
		<tr>
			<td>Needle</td>
			<td>Becton Dickinson</td>
			<td>305156</td>
			<td>22-gauge 1.5 inch length</td>
		</tr>
		<tr>
			<td>Funnel</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Mesh filters</td>
			<td>Small parts, Inc.</td>
			<td>CMN-0010-C and CMN-0020-C</td>
			<td>10 and 20 &mu;m</td>
		</tr>
		<tr>
			<td>Whole milk</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>HEB in San Antonio, TX</td>
		</tr>
		<tr>
			<td>Thimerosal</td>
			<td>Sigma-Aldrich Co.</td>
			<td>T5125</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Propanol</td>
			<td>Sigma-Aldrich Co.</td>
			<td>33538</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>Sigma-Aldrich Co.</td>
			<td>431788</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>CuCl2</td>
			<td>Sigma-Aldrich Co.</td>
			<td>459097</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Agarose</td>
			<td>Sigma-Aldrich Co.</td>
			<td>A0169</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>BaSO4</td>
			<td>Sigma-Aldrich Co.</td>
			<td>B8675</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Glass beads</td>
			<td>Potters Industries, Inc.</td>
			<td>3000E</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>PET/AL/LLDPE*</td>
			<td>Pechiney Plastic Packaging, Inc.</td>
			<td>Pechiney Spec 151</td>
			<td>Phantom cover material</td>
		</tr>
		<tr>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>*Polyethylene terephthalate/aluminum/linear low density polyethylene</td>
		</tr>
		<tr>
			<td>Equipment</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Rotisserie motor</td>
			<td>Brinkmann</td>
			<td>812-7103-S</td>
			<td>Home Depot</td>
		</tr>
		<tr>
			<td>Water bath 1</td>
			<td>Precision, Inc.</td>
			<td>Model: 282, Serial #: 601091552</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Water bath 2</td>
			<td>VWR, Inc.</td>
			<td>Model: 1212, Serial #: 08119606</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>Ultrasound</td>
			<td>Visualsonics</td>
			<td>Serial #: 770/120-259</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>CT</td>
			<td>Gamma Medica-Ideas</td>
			<td>Serial #: GR 0050</td>
			<td>&nbsp;</td>
		</tr>
		<tr>
			<td>MRI</td>
			<td>Bruker</td>
			<td>Part #: W3301390, Serial #: 0030</td>
			<td>&nbsp;</td>
		</tr>
	</tbody>
</table>

construction of a preclinical multimodality phantom using tissue-mimicking materials for quality assurance in tumor size measurement

World Health Organization (WHO) and the Response Evaluation Criteria in Solid Tumors (RECIST) working groups advocated standardized criteria for radiologic assessment of solid tumors in response to anti-tumor drug therapy in the 1980s and 1990s, respectively. WHO criteria measure solid tumors in two-dimensions, whereas RECIST measurements use only one-dimension which is considered to be more reproducible 1, 2, 3,4,5. These criteria have been widely used as the only imaging biomarker approved by the United States Food and Drug Administration (FDA) 6. In order to measure tumor response to anti-tumor drugs on images with accuracy, therefore, a robust quality assurance (QA) procedures and corresponding QA phantom are needed.
To address this need, the authors constructed a preclinical multimodality (for ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI)) phantom using tissue-mimicking (TM) materials based on the limited number of target lesions required by RECIST by revising a Gammex US commercial phantom 7. The Appendix in Lee et al. demonstrates the procedures of phantom fabrication 7. In this article, all protocols are introduced in a step-by-step fashion beginning with procedures for preparing the silicone molds for casting tumor-simulating test objects in the phantom, followed by preparation of TM materials for multimodality imaging, and finally construction of the preclinical multimodality QA phantom. The primary purpose of this paper is to provide the protocols to allow anyone interested in independently constructing a phantom for their own projects. QA procedures for tumor size measurement, and RECIST, WHO and volume measurement results of test objects made at multiple institutions using this QA phantom are shown in detail in Lee et al. 8.

Figure 3B and Figure 5 show two silicone molds for casting test objects, and the multimodality phantom, respectively. The length &times; width &times; depth of each mold is 109 mm &times; 37 mm &times; 21 mm and two molds are identical mirror-images. One mold has 1 mm holes where TM material can be inserted using a thin needle. Each mold has an additional five holes for alignment rods. The length &times; width &times; depth of the phantom is 115 mm &times; 38 mm &times; 24 mm and its ini...

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Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement

This paper describes in-house procedures of constructing a preclinical multimodality phantom made of tissue-mimicking (TM) materials for quality assurance (QA) of tumor size measurement in animal imaging modalities such as ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI).

World Health Organization (WHO) and the Response Evaluation Criteria in Solid Tumors (RECIST) working groups advocated standardized criteria for ...

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11.2K ビュー.  University of Kansas School of Medicine. 本論文では、ファントムは、このような超音波（米国）、コンピュータ断層撮影（CT）や磁気などの動物の画像診断法における腫瘍サイズ測定の品質保証（QA）のための（TM）材料組織模倣で作られた前臨床マルチモダリティを構築する社内手順について説明します共鳴イメージング（MRI）。

ビデオ: Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement

Viral Nanoparticles for In vivo Tumor Imaging

The use of nanomaterials has the potential to revolutionize materials science and medicine. Currently, a number of different nanoparticles are being investigated for applications in imaging and therapy. Viral nanoparticles (VNPs) derived from plants can be regarded as self-assembled bionanomaterials with defined sizes and shapes. Plant viruses under investigation in the Steinmetz lab include icosahedral particles formed by Cowpea mosaic virus (CPMV) and Brome mosaic virus (BMV), both of which are 30 nm in diameter. We are also developing rod-shaped and filamentous structures derived from the following plant viruses: Tobacco mosaic virus (TMV), which forms rigid rods with dimensions of 300 nm by 18 nm, and Potato virus X (PVX), which form filamentous particles 515 nm in length and 13 nm in width (the reader is referred to refs. 1 and 2 for further information on VNPs).
From a materials scientist's point of view, VNPs are attractive building blocks for several reasons: the particles are monodisperse, can be produced with ease on large scale in planta, are exceptionally stable, and biocompatible. Also, VNPs are "programmable" units, which can be specifically engineered using genetic modification or chemical bioconjugation methods 3. The structure of VNPs is known to atomic resolution, and modifications can be carried out with spatial precision at the atomic level4, a level of control that cannot be achieved using synthetic nanomaterials with current state-of-the-art technologies.
In this paper, we describe the propagation of CPMV, PVX, TMV, and BMV in Vigna ungiuculata and Nicotiana benthamiana plants. Extraction and purification protocols for each VNP are given. Methods for characterization of purified and chemically-labeled VNPs are described. In this study, we focus on chemical labeling of VNPs with fluorophores (e.g. Alexa Fluor 647) and polyethylene glycol (PEG). The dyes facilitate tracking and detection of the VNPs 5-10, and PEG reduces immunogenicity of the proteinaceous nanoparticles while enhancing their pharmacokinetics 8,11. We demonstrate tumor homing of PEGylated VNPs using a mouse xenograft tumor model. A combination of fluorescence imaging of tissues ex vivo using Maestro Imaging System, fluorescence quantification in homogenized tissues, and confocal microscopy is used to study biodistribution. VNPs are cleared via the reticuloendothelial system (RES); tumor homing is achieved passively via the enhanced permeability and retention (EPR) effect12. The VNP nanotechnology is a powerful plug-and-play technology to image and treat sites of disease in vivo. We are further developing VNPs to carry drug cargos and clinically-relevant imaging moieties, as well as tissue-specific ligands to target molecular receptors overexpressed in cancer and cardiovascular disease.

Viral Nanoparticles for In vivo Tumor Imaging

Plant viral nanoparticles (VNPs) are promising platforms for applications in biomedicine. Here, we describe the procedures for plant VNP propagation, purification, characterization, and bioconjugation. Finally, we show the application of VNPs for tumor homing and imaging using a mouse xenograft model and fluorescence imaging.

The use of nanomaterials has the potential to revolutionize materials science and medicine. Currently, a number of different nanoparticles are being ...

Production of Large Numbers of Size-controlled Tumor Spheroids Using Microwell Plates

Tumor spheroids are increasingly recognized as an important in vitro model for the behavior of tumor cells in three dimensions. More physiologically relevant than conventional adherent-sheet cultures, they more accurately recapitulate the complexity and interactions present in real tumors. In order to harness this model to better assess tumor biology, or the efficacy of novel therapeutic agents, it is necessary to be able to generate spheroids reproducibly, in a controlled manner and in significant numbers.
The AggreWell system consists of a high-density array of pyramid-shaped microwells, into which a suspension of single cells is centrifuged. The numbers of cells clustering at the bottom of each microwell, and the number and ratio of distinct cell types involved depend only on the properties of the suspension introduced by the experimenter. Thus, we are able to generate tumor spheroids of arbitrary size and composition without needing to modify the underlying platform technology. The hundreds of microwells per square centimeter of culture surface area in turn ensure that extremely high production levels may be attained via a straightforward, nonlabor-intensive process. We therefore expect that this protocol will be broadly useful to researchers in the tumor spheroid field.

We introduce a protocol for the generation of large numbers (thousands to hundreds of thousands) of uniform size- and composition-controlled tumor spheroids, using commercially available microwell plates.

Tumor spheroids are increasingly recognized as an important in vitro model for the behavior of tumor cells in three dimensions. More physiologically ...

Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and modified as part of a set of complex, two-way mechanosensitive interactions. While the development of biologically-relevant 3D tumor models have facilitated mechanistic studies on the impact of matrix rheology on tumor growth, the inverse problem of mapping changes in the mechanical environment induced by tumors remains challenging. Here, we describe the implementation of particle-tracking microrheology (PTM) in conjunction with 3D models of pancreatic cancer as part of a robust and viable approach for longitudinally monitoring physical changes in the tumor microenvironment, in situ. The methodology described here integrates a system of preparing in vitro 3D models embedded in a model extracellular matrix (ECM) scaffold of Type I collagen with fluorescently labeled probes uniformly distributed for position- and time-dependent microrheology measurements throughout the specimen. In vitro tumors are plated and probed in parallel conditions using multiwell imaging plates. Drawing on established methods, videos of tracer probe movements are transformed via the Generalized Stokes Einstein Relation (GSER) to report the complex frequency-dependent viscoelastic shear modulus, G*(&#969;). Because this approach is imaging-based, mechanical characterization is also mapped onto large transmitted-light spatial fields to simultaneously report qualitative changes in 3D tumor size and phenotype. Representative results showing contrasting mechanical response in sub-regions associated with localized invasion-induced matrix degradation as well as system calibration, validation data are presented. Undesirable outcomes from common experimental errors and troubleshooting of these issues are also presented. The 96-well 3D culture plating format implemented in this protocol is conducive to correlation of microrheology measurements with therapeutic screening assays or molecular imaging to gain new insights into impact of treatments or biochemical stimuli on the mechanical microenvironment.

Particle-tracking microrheology can be used to non-destructively quantify and spatially map changes in extracellular matrix mechanical properties in 3D tumor models.

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and ...

Construction and Characterization of a Novel Vocal Fold Bioreactor

In vitro engineering of mechanically active tissues requires the presentation of physiologically relevant mechanical conditions to cultured cells. To emulate the dynamic environment of vocal folds, a novel vocal fold bioreactor capable of producing vibratory stimulations at fundamental phonation frequencies is constructed and characterized. The device is composed of a function generator, a power amplifier, a speaker selector and parallel vibration chambers. Individual vibration chambers are created by sandwiching a custom-made silicone membrane between a pair of acrylic blocks. The silicone membrane not only serves as the bottom of the chamber but also provides a mechanism for securing the cell-laden scaffold. Vibration signals, generated by a speaker mounted underneath the bottom acrylic block, are transmitted to the membrane aerodynamically by the oscillating air. Eight identical vibration modules, fixed on two stationary metal bars, are housed in an anti-humidity chamber for long-term operation in a cell culture incubator. The vibration characteristics of the vocal fold bioreactor are analyzed non-destructively using a Laser Doppler Vibrometer (LDV). The utility of the dynamic culture device is demonstrated by culturing cellular constructs in the presence of 200-Hz sinusoidal vibrations with a mid-membrane displacement of 40 &#181;m. Mesenchymal stem cells cultured in the bioreactor respond to the vibratory signals by altering the synthesis and degradation of vocal fold-relevant, extracellular matrix components. The novel bioreactor system presented herein offers an excellent in vitro platform for studying vibration-induced mechanotransduction and for the engineering of functional vocal fold tissues.

A novel vocal fold bioreactor capable of delivering physiologically relevant, vibratory stimulation to cultured cells is constructed and characterized. This dynamic culture device, when combined with a fibrous poly(&#949;-caprolactone) scaffold, creates a vocal fold-mimetic environment that modulates the behaviors of mesenchymal stem cells.

In vitro engineering of mechanically active tissues requires the presentation of physiologically relevant mechanical conditions to cultured cells. To ...

Design and Construction of Artificial Extracellular Matrix (aECM) Proteins from Escherichia coli for Skin Tissue Engineering

Recombinant technology is a versatile platform to create novel artificial proteins with tunable properties. For the last decade, many artificial proteins that have incorporated functional domains derived from nature (or created de novo) have been reported. In particular, artificial extracellular matrix (aECM) proteins have been developed; these aECM proteins consist of biological domains taken from fibronectin, laminins and collagens and are combined with structural domains including elastin-like repeats, silk and collagen repeats. To date, aECM proteins have been widely investigated for applications in tissue engineering and wound repair. Recently, Tjin and coworkers developed integrin-specific aECM proteins designed for promoting human skin keratinocyte attachment and propagation. In their work, the aECM proteins incorporate cell binding domains taken from fibronectin, laminin-5 and collagen IV, as well as flanking elastin-like repeats. They demonstrated that the aECM proteins developed in their work were promising candidates for use as substrates in artificial skin. Here, we outline the design and construction of such aECM proteins as well as their purification process using the thermo-responsive characteristics of elastin.

Design and Construction of Artificial Extracellular Matrix aECM Proteins from Escherichia coli for Skin Tissue Engineering

Recombinant technologies have enabled material designers to create novel artificial proteins with customized functionalities for tissue engineering applications. For example, artificial extracellular matrix proteins can be designed to incorporate structural and biological domains derived from native ECMs. Here, we describe the construction and purification of aECM proteins containing elastin-like repeats.

Recombinant technology is a versatile platform to create novel artificial proteins with tunable properties. For the last decade, many artificial proteins ...

Agarose-based Tissue Mimicking Optical Phantoms for Diffuse Reflectance Spectroscopy

This protocol describes how to make agarose-based tissue-mimicking phantoms and demonstrates how to determine their optical properties using a conventional optical system with an integrating sphere. Measuring systems for the acquisition of the diffuse reflectance and total transmittance spectra are constructed with a broadband white light source, a light guide, an achromatic lens, an integrating sphere, a sample holder, an optical fiber probe, and a multi-channel spectrometer. An acrylic mold consisting of two rectangular acrylic pieces and a U-shaped acrylic piece is constructed to create an epidermal phantom and a dermal phantom with whole blood. The application of a sodium dithionite (Na2S2O4) solution to the dermal phantom enables the researcher to deoxygenate hemoglobin in red blood cells distributed in the dermal phantom. The inverse Monte Carlo simulation with the diffuse reflectance and total transmittance spectra measured by a spectrometer with an integrating sphere is performed to determine the absorption coefficient spectrum &#181;a(&#955;) and the reduced scattering coefficient spectrum &#181;s&#39;(&#955;) of each layer phantom. A two-layered phantom mimicking the diffuse reflectance of human skin tissue is also demonstrated by piling up the epidermal phantom on the dermal phantom.

Here, we demonstrate how agarose-based tissue-mimicking optical phantoms are made and how their optical properties are determined using a conventional optical system with an integrating sphere.

This protocol describes how to make agarose-based tissue-mimicking phantoms and demonstrates how to determine their optical properties using a ...

Manufacturing Abdominal Aorta Hydrogel Tissue-Mimicking Phantoms for Ultrasound Elastography Validation

Ultrasound (US) elastography, or elasticity imaging, is an adjunct imaging technique that utilizes sequential US images of soft tissues to measure the tissue motion and infer or quantify the underlying biomechanical characteristics. For abdominal aortic aneurysms (AAA), biomechanical properties such as changes in the tissue's elastic modulus and estimates of the tissue stress may be essential for assessing the need for the surgical intervention. Abdominal aortic aneurysms US elastography could be a useful tool to monitor AAA progression and identify changes in biomechanical properties characteristic of high-risk patients.
A preliminary goal in the development of an AAA US elastography technique is the validation of the method using a physically relevant model with known material properties. Here we present a process for the production of AAA tissue-mimicking phantoms with physically relevant geometries and spatially modulated material properties. These tissue phantoms aim to mimic the US properties, material modulus, and geometry of the abdominal aortic aneurysms. Tissue phantoms are made using a polyvinyl alcohol cryogel (PVA-c) and molded using 3D printed parts created using computer aided design (CAD) software. The modulus of the phantoms is controlled by altering the concentration of PVA-c and by changing the number of freeze-thaw cycles used to polymerize the cryogel. The AAA phantoms are connected to a hemodynamic pump, designed to deform the phantoms with the physiologic cyclic pressure and flows. Ultra sound image sequences of the deforming phantoms allowed for the spatial calculation of the pressure normalized strain and the identification of mechanical properties of the vessel wall. Representative results of the pressure normalized strain are presented.

Here we describe a method to manufacture aneurysmal, aortic tissue-mimicking phantoms for the use in testing ultrasound elastography. The combined use of computer-aided design (CAD) and 3-dimensional (3D) printing techniques produce aortic phantoms with predictable, complex geometries to validate the elastographic imaging algorithms with controlled experiments.

Ultrasound (US) elastography, or elasticity imaging, is an adjunct imaging technique that utilizes sequential US images of soft tissues to measure the ...

Patient-Specific Polyvinyl Alcohol Phantom Fabrication with Ultrasound and X-Ray Contrast for Brain Tumor Surgery Planning

Phantoms are essential tools for clinical training, surgical planning and the development of novel medical devices. However, it is challenging to create anatomically accurate head phantoms with realistic brain imaging properties because standard fabrication methods are not optimized to replicate any patient-specific anatomical detail and 3D printing materials are not optimized for imaging properties. In order to test and validate a novel navigation system for use during brain tumor surgery, an anatomically accurate phantom with realistic imaging and mechanical properties was required. Therefore, a phantom was developed using real patient data as input and 3D printing of molds to fabricate a patient-specific head phantom comprising the skull, brain and tumor with both ultrasound and X-ray contrast. The phantom also had mechanical properties that allowed the phantom tissue to be manipulated in a similar manner to how human brain tissue is handled during surgery. The phantom was successfully tested during a surgical simulation in a virtual operating room.
The phantom fabrication method uses commercially available materials and is easy to reproduce. The 3D printing files can be readily shared, and the technique can be adapted to encompass many different types of tumor.

This protocol describes the fabrication of a patient specific skull, brain and tumor phantom. It uses 3D printing to create molds, and polyvinyl alcohol (PVA-c) is used as the tissue mimicking material.

Phantoms are essential tools for clinical training, surgical planning and the development of novel medical devices. However, it is challenging to create ...

Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device

Mimicking in vivo environmental conditions is crucial for in vitro studies on complex life machinery. However, current techniques targeting live cells and organs are either highly expensive, like robotics, or lack nanoliter volume and millisecond time accuracy in liquid manipulation. We herein present the design and fabrication of a microfluidic system, which consists of 1,500 culture units, an array of enhanced peristaltic pumps and an on-site mixing modulus. To demonstrate the capacities of the microfluidic device, neural stem cell (NSC) spheres are maintained in the proposed system. We observed that when the NSC sphere is exposed to CXCL in day 1 and EGF in day 2, the round-shaped conformation is well maintained. Variation in the input order of 6 drugs causes morphological changes to the NSC sphere and the expression level representative marker for NSC stemness (i.e., Hes5 and Dcx). These results indicate that dynamic and complex environmental conditions have great effects on NSC differentiation and self-renewal, and the proposed microfluidic device is a suitable platform for high throughput studies on the complex life machinery.

We present a microfluidic system for high throughput studies on complex life machinery, which consists of 1500 culture units, an array of enhanced peristaltic pumps and an on-site mixing modulus. The microfluidic chip allows for the analysis of the highly complex and dynamic micro-environmental conditions in vivo.

Mimicking in vivo environmental conditions is crucial for in vitro studies on complex life machinery. However, current techniques targeting live cells and ...

Simple, Affordable, and Modular Patterning of Cells using DNA

The relative positioning of cells is a key feature of the microenvironment that organizes cell-cell interactions. To study the interactions between cells of the same or different type, micropatterning techniques have proved useful. DNA Programmed Assembly of Cells (DPAC) is a micropatterning technique that targets the adhesion of cells to a substrate or other cells using DNA hybridization. The most basic operations in DPAC begin with decorating cell membranes with lipid-modified oligonucleotides, then flowing them over a substrate that has been patterned with complementary DNA sequences. Cells adhere selectively to the substrate only where they find a complementary DNA sequence. Non-adherent cells are washed away, revealing a pattern of adherent cells. Additional operations include further rounds of cell-substrate or cell-cell adhesion, as well as transferring the patterns formed by DPAC to an embedding hydrogel for long-term culture. Previously, methods for patterning oligonucleotides on surfaces and decorating cells with DNA sequences required specialized equipment and custom DNA synthesis, respectively. We report an updated version of the protocol, utilizing an inexpensive benchtop photolithography setup and commercially available cholesterol modified oligonucleotides (CMOs) deployed using a modular format. CMO-labeled cells adhere with high efficiency to DNA-patterned substrates. This approach can be used to pattern multiple cell types at once with high precision and to create arrays of microtissues embedded within an extracellular matrix. Advantages of this method include its high resolution, ability to embed cells into a three-dimensional microenvironment without disrupting the micropattern, and flexibility in patterning any cell type.

Here we present a protocol to micropattern cells at single-cell resolution using DNA-programmed adhesion. This protocol uses a benchtop photolithography platform to create patterns of DNA oligonucleotides on a glass slide and then labels cell membranes with commercially available complementary oligonucleotides. Hybridization of the oligos results in programmed cell adhesion.

The relative positioning of cells is a key feature of the microenvironment that organizes cell-cell interactions. To study the interactions between cells ...