The authors thank Drs. Fahad Bafakih and Jim Mandell for acquisition and identification of patient samples, Garrett F. Beeghly for assistance with immunohistochemistry, and the Biorepository and Tissue Research Facility, the Cardiovascular Research Center Histology Core, and the Biomolecular Analysis Facility at the University of Virginia for assistance with sample acquisition, immunohistochemistry, and imaging.

This protocol identifies cellular components in formalin-fixed paraffin embedded (FFPE) samples, as is typical for banked clinical patient samples. Paraffin embedding allows for the best maintenance of cellular and tissue morphology as well as has better longevity of sections. The samples used for this analysis were accessed through the University of Virginia Biorepository and Tissue Research Facility. Patient samples were selected by a neuropathologist based on a definitive diagnosis of glioblastoma (astrocytoma, WHO grade IV) who had completed tumor resections at the University of Virginia between 2010 and 2013, and were de-identified prior to this analysis11.
1. FFPE Sample Deparaffinization and Rehydration
NOTE: This portion of the protocol is specific to FFPE samples. While paraffin-embedded samples can be more useful for this analysis because of the preservation of cellular and tissue morphology, this analysis can also be done with frozen sections. If using frozen sections, this portion can be omitted and proceed directly to chromogenic immunohistochemistry.
<ol>
	<li>Perform the following washes for 5 min each: Xylene, Xylene, 100% Ethanol, 100% Ethanol, 95% Ethanol, 95% Ethanol, 70% Ethanol, Deionized water, Deionized water</li>
</ol>
2. Antigen Retrieval
NOTE: This portion of the protocol is necessary to break methylene bridges formed during formalin fixation of FFPE samples and expose antigen sites for antibodies to bind.
<ol>
	<li>Dilute Tris-based high pH antigen unmasking solution at manufacturer recommendation in distilled water.</li>
	<li>Perform heat-mediated antigen retrieval using a microwave. Other forms of heat-mediated retrieval (such as pressure cooker, vegetable steamer, or boiling water) would also suffice.
	<ol>
		<li>Add the diluted unmasking solution into a non-sealed microwaveable vessel. Place slides into vessel. Place slides into microwave.</li>
		<li>Boil for 20 min at high power. Monitor liquid levels for evaporation, and replenish with distilled water as necessary.</li>
	</ol>
	</li>
	<li>Allow samples to cool in solution for 1 h at room temperature.</li>
</ol>
3. Chromogenic Immunohistochemistry
<ol>
	<li>Outline tissue sample with a hydrophobic pen to minimize volume of reagents necessary to cover sample. 
	NOTE: Be sure to keep tissue samples hydrated and do not let them dry out as this will affect staining efficacy.</li>
	<li>Pipet enough permeabilization solution (Tris-buffered saline (TBS) + 0.01% Triton-X) to cover tissue sample (typically about 100 - 200 &#181;L).</li>
	<li>Remove and discard solution and repeat step 3.2.</li>
	<li>Incubate samples at room temperature with blocking solution (2.5% horse serum + permeabilization solution).</li>
	<li>Incubate samples overnight in 4 &#186;C with primary antibodies diluted in blocking solution. 
	NOTE: All primary antibodies used here are diluted at 1:200, but optimal dilutions can be determined using serial dilutions starting with manufacturer recommendation. Detailed information on antibodies used in this protocol was previously published11.</li>
	<li>Detect primary antibodies using a horseradish peroxidase polymer reagent corresponding with the primary antibody host animal, following manufacturer protocol.</li>
	<li>Pipet enough permeabilization solution to cover tissue sample and incubate for 5 min.</li>
	<li>Remove and discard solution and repeat Step 3.7.</li>
	<li>Incubate slides in 0.3% H2O2 in 1x TBS for 15 min.</li>
	<li>Develop samples with a peroxidase diaminobenzidine (DAB) substrate for 2 - 10 min until desired stain intensity is achieved.</li>
	<li>Counterstain samples to identify cell nuclei, such as with hematoxylin, following manufacturer protocol.</li>
	<li>Dehydrate samples with 100% ethanol and xylene.</li>
	<li>Mount samples permanently with mounting media.</li>
</ol>
4. Regions of Interest Identification
<ol>
	<li>Image slides under brightfield microscopy capable of high resolution images. 
	NOTE: Use imaging cellular components at a minimum of 20x resolution.</li>
	<li>Move camera to specific regions of interest throughout tissue samples.</li>
	<li>Save images as TIFF files for quantification.</li>
</ol>
5. Image Analysis
<ol>
	<li>Open images in ImageJ for quantification of percent coverage.</li>
	<li>Use the Threshold Colour plugin to remove purple color from hematoxylin stained nuclei.</li>
	<li>Convert image to 8-bit.</li>
	<li>Add threshold without dark background.</li>
	<li>Process image using one of the 17 pre-loaded ImageJ threshold filters (i.e. MaxEntropy) so only DAB stained portions are included in the threshold. 
	NOTE: Select the optimal pre-loaded threshold filter that minimizes inclusion of background staining. This can depend on the quality of staining and specificity of antibody. Use the same threshold for all technical replicates within each patient sample.</li>
	<li>Apply threshold.</li>
	<li>Measure percent area of thresholded image.</li>
	<li>Average percent area coverage for multiple regions within each sample.</li>
</ol>

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Our method proposed here is a quantitative approach to analyzing histological samples stained using traditional chromogenic immunohistochemistry. Current methodology for this type of analysis includes similar staining protocols followed by grading by independent pathologists. This method has been reliable, yet for a number of applications, a more precise understanding of the cellular make-up is required, such as better understanding of the heterogeneity associated with tumors and accurate recapitulation of tumors for in vitro studies.
This protocol demonstrates a straightforward technique for quantitatively analyzing the populations of glial cells within the brain tumor microenvironment. This technique is widely adaptable and can be expanded to identify many other components of the microenvironment, such as blood vessels, chemokines, and more, as well as other cancers, such as breast or pancreatic, where the tumor resections can have larger parenchymal regions. Furthermore, this technique can be adapted to acquire other measurements, such as counts, and perimeter of cells to assess cell shape, as well as more complex morphology outcomes isotropy, clustering, orientation, and more. These techniques are also not limited to cancer, in that these staining and quantification methodologies can be used for any brain analyses, as demonstrated in our representative Protein Atlas quantification of healthy tissue, and our previously published comparison with epileptic brain tissue11.
Critical steps within this protocol include proper incubation and development of the chromogenic secondary. Care should be taken such that the chromogenic dye does not over-develop. This will make it difficult to differentiate between positive staining and background. The development time varies depending on the substrate reagent used and the affinity of the primary antibody. We use bright field microscopy to monitor development to ensure optimal staining while minimizing background staining. After staining, proper thresholding during analysis can help differentiate background from positive staining. A major limitation for this method is the inability to stain multiple components within the same tissue sample due to the use of chromogenic staining development. Immunofluorescence analysis could be conducted in a similar manner, but requires modification of the tools discussed in this method.
Specific to glioblastoma, there are a number of markers and cellular stains that have been used to analyze patient samples. These include IDH114,15, EGFRvIII16,17 as prognostic markers, as well as CD11b and CD45 for microglia and macrophages18,19. Our method expands this type of analysis to the cellular microenvironment, an often overlooked component of the tumor microenvironment in glioblastoma. Studies have looked at microglia presence and density in tumors20,21,22 as well as contributions of astrocytes9,23,24. Here we developed a protocol examining all of the glia - astrocytes, microglia, and oligodendrocytes - in the brain tumor microenvironment and to differentiate the adjacent or invasive regions of the tumor from the tumor bulk, which is where markers are usually identified in these tumors. By doing this, we believe we can more accurately assess the patient situation because we determined intra-patient heterogeneity and our previous publication showed that analysis of these locations and inclusion in statistical models is stronger at predicting outcomes than either location alone or overall samples11. Furthermore, since glioblastoma invasion is so diffuse, making it difficult to resect completely1,2, we believe the tissue in the adjacent regions is more representative of the invasive tissue left behind after resection, which contributes to inevitable recurrence. Therefore, better understanding of the adjacent regions may give more information about disease recurrence and patient treatment planning, as opposed to the traditionally studied bulk tissue that is resected prior to therapy in glioblastoma patients.

Glioblastoma (GBM), the most common and malignant brain cancer, is characterized by highly diffuse invasion from the primary tumor bulk into the surrounding healthy brain parenchyma1,2. This diffuse invasion makes the tumor particularly difficult to resect fully, and the invading cancer cells that remain post-therapy is the most common reason for inevitable recurrence2,3,4. Previously, we found inhibiting the diffuse glioma cell invasion to be therapeutically beneficial5, however little is known about the complex mechanisms contributing to GBM invasion. The tumor microenvironment, or tissue surrounding the cancer, has been implicated in the progression of tumors in multiple cancers6,7. The glioblastoma tumor microenvironment, in particular, is relatively under-characterized and is uniquely complex, composing of multiple glial cells, such as astrocytes, microglia, and oligodendrocytes, as well as extracellular matrix, soluble factors, and biophysical factors. Experimentally, astrocytes and microglia have been shown to increase glioma progression and invasion8,9,10, but the composition of all glial cells in the native human brain microenvironment is unknown.
We previously showed microenvironmental components can predict patient survival by quantitatively analyzing cellular components of the glioblastoma microenvironment and incorporating our analyses into a proportional hazards model11. Here, we describe the quantitative analysis method for identifying the populations of glial cells within the tumor bulk and adjacent regions of tumor resections from glioblastoma patients. We used chromogenic immunohistochemistry to identify the glial cell populations and ImageJ to analyze percent coverage of staining for each glial population. Assessing percent coverage creates a simple measurement for determining the morphological differences of cells, particularly those affected by interactions with cancer cells. Previous studies for quantifying histopathological staining use standard staining such as hematoxylin and eosin12 or Masson&#39;s trichrome13, which do not take advantage of the specificity of antibody-based immunohistochemistry staining. Our method was developed to directly quantify the glial populations within glioblastoma patient tumor resections, which we aim to use to elucidate the complex glioblastoma microenvironment.

<table border="0" cellpadding="0" cellspacing="0" width="573">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Xylene</td>
			<td style="width:71px;">Fisher Chemical</td>
			<td style="width:119px;">X3P</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Ethanol</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">High pH antigen unmasking solution</td>
			<td style="width:71px;">Vector Labs</td>
			<td>H-3301</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">TBS</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Triton-X</td>
			<td style="width:71px;">Amresco</td>
			<td style="width:119px;">9002-93-1</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Horse serum</td>
			<td style="width:71px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Anti-ALDH1L1&#160;</td>
			<td style="width:71px;">abcam&#160;</td>
			<td style="width:119px;">ab56777</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Anti-Iba1&#160;</td>
			<td style="width:71px;">abcam&#160;</td>
			<td style="width:119px;">ab5076</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Anti-Oligodendrocyte Specific Protein1&#160;</td>
			<td style="width:71px;">abcam&#160;</td>
			<td style="width:119px;">ab53041</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">ImmPRESS anti-goat</td>
			<td style="width:71px;">Vector Labs</td>
			<td style="width:119px;">MP-7405</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">ImmPRESS Universal (anti-mouse/rabbit)</td>
			<td style="width:71px;">Vector Labs</td>
			<td style="width:119px;">MP-7500</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Hydrogen peroxide</td>
			<td style="width:71px;">Sigma Aldrich</td>
			<td style="width:119px;">216763</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">ImmPACT DAB substrate</td>
			<td style="width:71px;">Vector Labs</td>
			<td style="width:119px;">SK-4105</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Hematoxylin counterstain</td>
			<td style="width:71px;">ThermoScientific</td>
			<td style="width:119px;">72404</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Histochoice Mounting Media</td>
			<td style="width:71px;">Amresco</td>
			<td style="width:119px;">H157-475</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Aperio Scanscope</td>
			<td style="width:71px;">Leica Biosystems</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Image Scanscope</td>
			<td style="width:71px;">Leica Biosystems</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="84">
			<td height="84" style="height:84px;width:216px;">Super HT PAP Pen</td>
			<td style="width:71px;">Research Products International</td>
			<td style="width:119px;">195506</td>
			<td></td>
		</tr>
	</tbody>
</table>

quantitative immunohistochemistry of the cellular microenvironment in patient glioblastoma resections

With the growing interest in the tumor microenvironment, we set out to develop a method to specifically determine the microenvironment components within patient samples of glioblastoma, the deadliest and most invasive brain cancer. Not only are quantitative methods beneficial for accurately describing diseased tissues, they can also potentially contribute to more accurate prognosis, diagnosis, and the development of tissue-engineered systems and replacements. In glioblastoma, glial cells, such as microglia and astrocytes, have been independently correlated with poor prognosis based on pathologist grading. However, the state of these cells and other glial cell components has not been well-described quantitatively. This can be difficult due to the large processes that mark these glial cells. Furthermore, most histological analyses focus on the overall tissue sample or only within the bulk of the tumor, as opposed to delineating quantifications based on regions within the highly heterogeneous tissue. Here, we describe a method for identifying and quantitatively analyzing the populations of glial cells within the tumor bulk and adjacent regions of tumor resections from glioblastoma patients. We used chromogenic immunohistochemistry to identify the glial cell populations in patient tumor resections and ImageJ to analyze percent coverage of staining for each glial population. With these techniques we are able to better describe the glial cells throughout regions of the glioma tumor microenvironment.

For this analysis, two regions of interests within our tumor resections - the primary tumor bulk and the adjacent regions, primarily composed of healthy tissue with diffuse invading cancer cells (Figure 1A, 1B) - were identified by collaborating neuropathologists on hematoxylin and eosin stained patient samples. Within each patient sample, positive staining for astrocytes (Figure 1C), microglia (Figure 1D), and oligodendrocytes (Figure 1E) via chromogenic immunohistochemistry was identified. These populations were identified using primary antibodies ALDH1L1, Iba1, and Oligodendrocyte-Specific Protein (OSP1) respectively11. Optimization of antibody dilutions is recommended, as well as consultation with manufacturer protocols to confirm if staining is accurate and positive (Figure 2). For example, we performed staining with no primary antibody for a negative control (Figure 2A), the manufacturer recommended (Figure 2B), and further dilutions (Figure 2C, 2D) before settling on the 1:200 dilution (Figure 2C) due to optimal positive staining of cell body and processes with minimizing background for the anti-ALDH1L1 antibody.
Using ImageJ, the percent coverage of OSP1+ oligodendrocyte staining was quantified to eventually compare differences in our regions of interest (Figure 3A). We removed the counterstained nuclei from the image using the Threshold Colour plugin in order to solely assess the positive DAB staining (Figure 3B). After converting the image to 8bit (Figure 3C), we then applied the MaxEntropy default threshold to the remaining positive DAB staining (Figure 3D). Here, we used the MaxEntropy threshold default because this particular default threshold best captured our positive stain while minimizing background, but different thresholds can be used to ensure analysis of the population of interest. Once the appropriate threshold has been applied to the image (Figure 3E), the percent coverage from the threshold can be measured (Figure 3F) and compared for multiple patients. Here, we quantified 3 - 5 areas within each region of interest, depending on the total area of the region of interest, and compared groups using paired t-tests with GraphPad Prism software. We also compared our GBM analyses with corresponding staining found in healthy brain tissue in the Protein Atlas database (Figure 3F). In our previous publication, we used this analysis for multiple microenvrionmental components (astrocytes, microglia, oligodendrocytes, and blood vessels) across 33 patients to develop a proportional hazards model for predicting overall patient survival11.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56025/56025fig1.jpg" /> 
Figure 1: Comparison of Tumor Bulk and Tumor Adjacent Regions of Interest for Glial Cells. 
A) Whole tumor sample from Patient 63 stained with hematoxylin and eosin with bulk and adjacent regions indicated. B) Hematoxylin and eosin staining, C) ALDH1L1+ astrocytes, D) Iba1+ microglia, and E) Oligodendrocyte Specific Protein-1 (OSP1)+ oligodendrocytes. Scale bar = 100 &#181;m. <a href="http://cloudflare.jove.com/files/ftp_upload/56025/56025fig1large.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/56025/56025fig2.jpg" /> 
Figure 2: Example Titration of Anti-ALDH1L1 Antibody. 
A) Negative control, B) 1:70 manufacturer recommendation dilution from stock, C) 1:200 dilution from stock, and D) 1:400 dilution from stock. 1:200 dilution was used for staining and analysis due to optimal positive staining of cell body and processes with minimizing background. Scale bar= 100 &#181;m. <a href="http://cloudflare.jove.com/files/ftp_upload/56025/56025fig2large.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/56025/56025fig3.jpg" /> 
Figure 3: ImageJ Analysis and Quantification of Area Coverage for Oligodendrocytes. 
A) Original OSP1+ staining of Patient 52. B) Removal of purple nuclei using Threshold_Colour plugin. C) Conversion to 8bit. D) MaxEntropy threshold captured and E) applied to minimize background staining. F) Comparison of adjacent and bulk regions in five patient samples, as well as healthy brain tissue through the Protein Atlas, for OSP1+ percent coverage. ***p&#60; 0.001, ****p&#60; 0.0001 via paired t-tests. Scale bar= 100 &#181;m. <a href="http://cloudflare.jove.com/files/ftp_upload/56025/56025fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections at JoVE.com

Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections

This protocol was developed to quantitatively identify tumor microenvironment components in glioblastoma patient resections using chromogenic immunohistochemistry and ImageJ.

With the growing interest in the tumor microenvironment, we set out to develop a method to specifically determine the microenvironment components within ...

quantitative-immunohistochemistry-cellular-microenvironment-patient

Nanyang Technological University

Research

JoVE Journal

Medicine

9.6K Views.  University of Virginia. This protocol was developed to quantitatively identify tumor microenvironment components in glioblastoma patient resections using chromogenic immunohistochemistry and ImageJ. 

Video: Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

In 2010 approximately 68,720 melanomas will be diagnosed in the US alone, with around 8,650 resulting in death 1. To date, the only effective treatment for melanoma remains surgical excision, therefore, the key to extended survival is early detection 2,3. Considering the large numbers of patients diagnosed every year and the limitations in accessing specialized care quickly, the development of objective in vivo diagnostic instruments to aid the diagnosis is essential. New techniques to detect skin cancer, especially non-invasive diagnostic tools, are being explored in numerous laboratories. Along with the surgical methods, techniques such as digital photography, dermoscopy, multispectral imaging systems (MelaFind), laser-based systems (confocal scanning laser microscopy, laser doppler perfusion imaging, optical coherence tomography), ultrasound, magnetic resonance imaging, are being tested. Each technique offers unique advantages and disadvantages, many of which pose a compromise between effectiveness and accuracy versus ease of use and cost considerations. Details about these techniques and comparisons are available in the literature 4.
Infrared (IR) imaging was shown to be a useful method to diagnose the signs of certain diseases by measuring the local skin temperature. There is a large body of evidence showing that disease or deviation from normal functioning are accompanied by changes of the temperature of the body, which again affect the temperature of the skin 5,6. Accurate data about the temperature of the human body and skin can provide a wealth of information on the processes responsible for heat generation and thermoregulation, in particular the deviation from normal conditions, often caused by disease. However, IR imaging has not been widely recognized in medicine due to the premature use of the technology 7,8 several decades ago, when temperature measurement accuracy and the spatial resolution were inadequate and sophisticated image processing tools were unavailable. This situation changed dramatically in the late 1990s-2000s. Advances in IR instrumentation, implementation of digital image processing algorithms and dynamic IR imaging, which enables scientists to analyze not only the spatial, but also the temporal thermal behavior of the skin 9, allowed breakthroughs in the field.
In our research, we explore the feasibility of IR imaging, combined with theoretical and experimental studies, as a cost effective, non-invasive, in vivo optical measurement technique for tumor detection, with emphasis on the screening and early detection of melanoma 10-13. In this study, we show data obtained in a patient study in which patients that possess a pigmented lesion with a clinical indication for biopsy are selected for imaging. We compared the difference in thermal responses between healthy and malignant tissue and compared our data with biopsy results. We concluded that the increased metabolic activity of the melanoma lesion can be detected by dynamic infrared imaging.

We demonstrated that malignant pigmented lesions with increased metabolic activity generate quantifiable amounts of heat and the measurement of the transient thermal response of the skin to a cooling excitation allows quantitative identification of melanoma and other skin cancers (vs. non-proliferative nevi) at an early stage of the disease.

In 2010 approximately 68,720 melanomas will be diagnosed in the US alone, with around 8,650 resulting in death 1. To date, the only effective treatment ...

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester (CFSE)

Tumor heterogeneity represents a fundamental feature supporting tumor robustness and presents a central obstacle to the development of therapeutic strategies1. To overcome the issue of tumor heterogeneity, it is essential to develop assays and tools enabling phenotypic, (epi)genetic and functional identification and characterization of tumor subpopulations that drive specific disease pathologies and represent clinically relevant targets. It is now well established that tumors exhibit distinct sub-fractions of cells with different frequencies of cell division, and that the functional criteria of being slow cycling is positively associated with tumor formation ability in several cancers including those of the brain, breast, skin and pancreas as well as leukemia2-8. The fluorescent dye carboxyfluorescein succinimidyl ester (CFSE) has been used for tracking the division frequency of cells in vitro and in vivo in blood-borne tumors and solid tumors such as glioblastoma2,7,8. The cell-permeant non-fluorescent pro-drug of CFSE is converted by intracellular esterases into a fluorescent compound, which is retained within cells by covalently binding to proteins through reaction of its succinimidyl moiety with intracellular amine groups to form stable amide bonds9. The fluorescent dye is equally distributed between daughter cells upon divisions, leading to the halving of the fluorescence intensity with every cell division. This enables tracking of cell cycle frequency up to eight to ten rounds of division10. CFSE retention capacity was used with brain tumor cells to identify and isolate a slow cycling subpopulation (top 5% dye-retaining cells) demonstrated to be enriched in cancer stem cell activity2. 
This protocol describes the technique of staining cells with CFSE and the isolation of individual populations within a culture of human glioblastoma (GBM)-derived cells possessing differing division rates using flow cytometry2. The technique has served to identify and isolate a brain tumor slow-cycling population of cells by virtue of their ability to retain the CFSE labeling.

Identification and Isolation of Slow-Dividing Cells in Human Glioblastoma Using Carboxy Fluorescein Succinimidyl Ester CFSE

This video protocol demonstrates the application of the fluorescent dye carboxyfluorescein succinimidyl ester (CFSE) for the identification and separation of different sub-populations of cells in human glioblastoma based on frequency of cell division.

Tumor heterogeneity represents a fundamental feature supporting tumor robustness and presents a central obstacle to the development of therapeutic ...

Live Imaging of Drug Responses in the Tumor Microenvironment in Mouse Models of Breast Cancer

The tumor microenvironment plays a pivotal role in tumor initiation, progression, metastasis, and the response to anti-cancer therapies. Three-dimensional co-culture systems are frequently used to explicate tumor-stroma interactions, including their role in drug responses. However, many of the interactions that occur in vivo in the intact microenvironment cannot be completely replicated in these in vitro settings. Thus, direct visualization of these processes in real-time has become an important tool in understanding tumor responses to therapies and identifying the interactions between cancer cells and the stroma that can influence these responses. Here we provide a method for using spinning disk confocal microscopy of live, anesthetized mice to directly observe drug distribution, cancer cell responses and changes in tumor-stroma interactions following administration of systemic therapy in breast cancer models. We describe procedures for labeling different tumor components, treatment of animals for observing therapeutic responses, and the surgical procedure for exposing tumor tissues for imaging up to 40 hours. The results obtained from this protocol are time-lapse movies, in which such processes as drug infiltration, cancer cell death and stromal cell migration can be evaluated using image analysis software.

We describe a method for imaging response to anti-cancer treatment in vivo and at single cell resolution.

The tumor microenvironment plays a pivotal role in tumor initiation, progression, metastasis, and the response to anti-cancer therapies. Three-dimensional ...

Cell-based Assay Protocol for the Prognostic Prediction of Idiopathic Scoliosis Using Cellular Dielectric Spectroscopy

This protocol details the experimental and analytical procedure for a cell-based assay developed in our laboratory as a functional test to predict the prognosis of idiopathic scoliosis in asymptomatic and affected children. The assay consists of the evaluation of the functional status of Gi and Gs proteins in peripheral blood mononuclear cells (PBMCs) by cellular dielectric spectroscopy (CDS), using an automated CDS-based instrument, and the classification of children into three functional groups (FG1, FG2, FG3) with respect to the profile of imbalance between the degree of response to Gi and Gs proteins stimulation. The classification is further confirmed by the differential effect of osteopontin (OPN) on response to Gi stimulation among groups and the severe progression of disease is referenced by FG2. Approximately, a volume of 10 ml of blood is required to extract PBMCs by Ficoll-gradient and cells are then stored in liquid nitrogen. The adequate number of PBMCs to perform the assay is obtained after two days of cell culture. Essentially, cells are first incubated with phytohemmaglutinin (PHA). After 24 hr incubation, medium is replaced by a PHA-free culture medium for an additional 24 hr prior to cell seeding and OPN treatment. Cells are then spectroscopically screened for their responses to somatostatin and isoproterenol, which respectively activate Gi and Gs proteins through their cognate receptors. Both somatostatin and isoproterenol are simultaneously injected with an integrated fluidics system and the cells&#39; responses are monitored for 15 min. The assay can be performed with fresh or frozen PBMCs and the procedure is completed within 4 days.

A structured protocol is presented for a cell-based assay as a functional test to predict the prognosis of idiopathic scoliosis using cellular dielectric spectroscopy (CDS). The assay can be performed with fresh or frozen peripheral blood mononuclear cells (PBMCs) and the procedure is completed within 4 days.

This protocol details the experimental and analytical procedure for a cell-based assay developed in our laboratory as a functional test to predict the ...

Tumor Treating Field Therapy in Combination with Bevacizumab for the Treatment of Recurrent Glioblastoma

A novel device that employs TTF therapy has recently been developed and is currently in use for the treatment of recurrent glioblastoma (rGBM). It was FDA approved in April 2011 for the treatment of patients 22 years or older with rGBM. The device delivers alternating electric fields and is programmed to ensure maximal tumor cell kill1.
Glioblastoma is the most common type of glioma and has an estimated incidence of approximately 10,000 new cases per year in the United States alone2. This tumor is particularly resistant to treatment and is uniformly fatal especially in the recurrent setting3-5. Prior to the approval of the TTF System, the only FDA approved treatment for rGBM was bevacizumab6. Bevacizumab is a humanized monoclonal antibody targeted against the vascular endothelial growth factor (VEGF) protein that drives tumor angiogenesis7. By blocking the VEGF pathway, bevacizumab can result in a significant radiographic response (pseudoresponse), improve progression free survival and reduce corticosteroid requirements in rGBM patients8,9. Bevacizumab however failed to prolong overall survival in a recent phase III trial26. A pivotal phase III trial (EF-11) demonstrated comparable overall survival between physicians&#8217; choice chemotherapy and TTF Therapy but better quality of life were observed in the TTF arm10.
There is currently an unmet need to develop novel approaches designed to prolong overall survival and/or improve quality of life in this unfortunate patient population. One appealing approach would be to combine the two currently approved treatment modalities namely bevacizumab and TTF Therapy. These two treatments are currently approved as monotherapy11,12, but their combination has never been evaluated in a clinical trial. We have developed an approach for combining those two treatment modalities and treated 2 rGBM patients. Here we describe a detailed methodology outlining this novel treatment protocol and present representative data from one of the treated patients.

A novel methodology that is employed for the treatment of recurrent glioblastomas is described. This treatment approach employs the application of alternating electric tumor treating fields (TTFields), known as TTF Therapy in combination with bevacizumab, a targeted agent that is currently FDA approved as monotherapy.

A novel device that employs TTF therapy has recently been developed and is currently in use for the treatment of recurrent glioblastoma (rGBM). It was FDA ...

A "Patient-Like" Orthotopic Syngeneic Mouse Model of Hepatocellular Carcinoma Metastasis

The majority of cancer-related deaths are caused by the metastasis of the cancer rather than the primary tumor itself. Yet, the underlying mechanisms of cancer metastasis are still unclear. Animal models are essential for elucidating the mechanisms and for evaluating novel strategies for the treatment of metastatic cancers. Here, an in-depth description of a &#8220;patient-like&#8221; orthotopic syngeneic mouse model for exploring the mechanisms of metastasis of solid organ tumors is provided. The survival surgical implantation of BNL 1ME A.7R.1 mouse hepatocellular carcinoma cells directly into the liver (the organ of origin) of the inbred wild-type immune competent laboratory mouse strain, BALB/c is described. The success and reproducibility of this methodology recommends it for widespread use in elucidating the biological mechanisms of solid organ cancer metastasis.

The metastatic spread of cancer is the major cause of cancer-related deaths. We provide an in-depth description of our survival surgery methodology for establishing a &#8220;patient-like&#8221; orthotopic syngeneic mouse model system for studying the mechanisms of metastasis in solid organ tumors.

The majority of cancer-related deaths are caused by the metastasis of the cancer rather than the primary tumor itself. Yet, the underlying mechanisms of ...

A Human Glioblastoma Organotypic Slice Culture Model for Study of Tumor Cell Migration and Patient-specific Effects of Anti-Invasive Drugs

Glioblastoma (GBM) continues to carry an extremely poor clinical prognosis despite surgical, chemotherapeutic, and radiation therapy. Progressive tumor invasion into surrounding brain parenchyma represents an enduring therapeutic challenge. To develop anti-migration therapies for GBM, model systems that provide a physiologically relevant background for controlled experimentation are essential. Here, we present a protocol for generating slice cultures from human GBM tissue obtained during surgical resection. These cultures allow for ex vivo experimentation without passaging through animal xenografts or single cell cultures. Further, we describe the use of time-lapse laser scanning confocal microscopy in conjunction with cell tracking to quantitatively study the migratory behavior of tumor cells and associated response to therapeutics. Slices are reproducibly generated within 90 min of surgical tissue acquisition. Retrovirally-mediated fluorescent cell labeling, confocal imaging, and tumor cell migration analyses are subsequently completed within two weeks of culture. We have successfully used these slice cultures to uncover genetic factors associated with increased migratory behavior in human GBM. Further, we have validated the model&#39;s ability to detect patient-specific variation in response to anti-migration therapies. Moving forward, human GBM slice cultures are an attractive platform for rapid ex vivo assessment of tumor sensitivity to therapeutic agents, in order to advance personalized neuro-oncologic therapy.

Current ex vivo models of glioblastoma (GBM) are not optimized for physiologically relevant study of human tumor invasion. Here, we present a protocol for generation and maintenance of organotypic slice cultures from fresh human GBM tissue. A description of time-lapse microscopy and quantitative cell migration analysis techniques is provided.

Glioblastoma (GBM) continues to carry an extremely poor clinical prognosis despite surgical, chemotherapeutic, and radiation therapy. Progressive tumor ...

Generation of Microtumors Using 3D Human Biogel Culture System and Patient-derived Glioblastoma Cells for Kinomic Profiling and Drug Response Testing

The use of patient-derived xenografts for modeling cancers has provided important insight into cancer biology and drug responsiveness. However, they are time consuming, expensive, and labor intensive. To overcome these obstacles, many research groups have turned to spheroid cultures of cancer cells. While useful, tumor spheroids or aggregates do not replicate cell-matrix interactions as found in vivo. As such, three-dimensional (3D) culture approaches utilizing an extracellular matrix scaffold provide a more realistic model system for investigation. Starting from subcutaneous or intracranial xenografts, tumor tissue is dissociated into a single cell suspension akin to cancer stem cell neurospheres. These cells are then embedded into a human-derived extracellular matrix, 3D human biogel, to generate a large number of microtumors. Interestingly, microtumors can be cultured for about a month with high viability and can be used for drug response testing using standard cytotoxicity assays such as 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and live cell imaging using Calcein-AM. Moreover, they can be analyzed via immunohistochemistry or harvested for molecular profiling, such as array-based high-throughput kinomic profiling, which is detailed here as well. 3D microtumors, thus, represent a versatile high-throughput model system that can more closely replicate in vivo tumor biology than traditional approaches.

Patient-derived xenografts of glioblastoma multiforme can be miniaturized into living microtumors using 3D human biogel culture system. This in vivo-like 3D tumor assay is suitable for drug response testing and molecular profiling, including kinomic analysis.

The use of patient-derived xenografts for modeling cancers has provided important insight into cancer biology and drug responsiveness. However, they are ...

Extended Time-lapse Intravital Imaging of Real-time Multicellular Dynamics in the Tumor Microenvironment

In the tumor microenvironment, host stromal cells interact with tumor cells to promote tumor progression, angiogenesis, tumor cell dissemination and metastasis. Multicellular interactions in the tumor microenvironment can lead to transient events including directional tumor cell motility and vascular permeability. Quantification of tumor vascular permeability has frequently used end-point experiments to measure extravasation of vascular dyes. However, due to the transient nature of multicellular interactions and vascular permeability, the kinetics of these dynamic events cannot be discerned. By labeling cells and vasculature with injectable dyes or fluorescent proteins, high-resolution time-lapse intravital microscopy has allowed the direct, real-time visualization of transient events in the tumor microenvironment. Here we describe a method for using multiphoton microscopy to perform extended intravital imaging in live mice to directly visualize multicellular dynamics in the tumor microenvironment. This method details cellular labeling strategies, the surgical preparation of a mammary skin flap, the administration of injectable dyes or proteins by tail vein catheter and the acquisition of time-lapse images. The time-lapse sequences obtained from this method facilitate the visualization and quantitation of the kinetics of cellular events of motility and vascular permeability in the tumor microenvironment.

This protocol describes the use of multiphoton microscopy to perform extended time-lapse imaging of multicellular interactions in real time, in vivo at single cell resolution.

In the tumor microenvironment, host stromal cells interact with tumor cells to promote tumor progression, angiogenesis, tumor cell dissemination and ...

Quantitative [18F]-Naf-PET-MRI Analysis for the Evaluation of Dynamic Bone Turnover in a Patient with Facetogenic Low Back Pain

Imaging techniques that reflect dynamic bone turnover may aid in characterizing a wide range of bone pathologies. Bone is a dynamic tissue undergoing continuous remodeling with the competing activity of osteoblasts, which produce the new bone matrix, and osteoclasts, whose function is to eliminate mineralized bone. [18F]-NaF is a positron emission tomography (PET) radiotracer that enables visualization of bone metabolism. [18F]-NaF is chemically absorbed into hydroxyapatite in the bone matrix by osteoblasts and can thus noninvasively detect osteoblastic activity, which is occult to conventional imaging techniques. Kinetic modeling of dynamic [18F]-NaF-PET data provides detailed quantitative measures of bone metabolism. Conventional semi-quantitative PET data, which utilizes standardized uptake values (SUVs) as a measure of radiotracer activity, is referred to as a static technique due to its snapshot of tracer uptake in time.&#160; Kinetic modeling, however, utilizes dynamic image data where tracer levels are continuously acquired providing tracer uptake temporal resolution. From the kinetic modeling of dynamic data, quantitative values like blood flow and metabolic rate (i.e., potentially informative metrics of tracer dynamics) can be extracted, all with respect to the measured activity in the image data. When combined with dual modality PET-MRI, region-specific kinetic data can be correlated with anatomically registered high-resolution structural and pathologic information afforded by MRI. The goal of this methodological manuscript is to outline detailed techniques for performing and analyzing dynamic [18F]-NaF-PET-MRI data. The lumbar facet joint is a common site of degenerative arthritis disease and a common cause for axial low back pain.&#160; Recent studies suggest [18F]-NaF-PET may serve as a useful biomarker of painful facetogenic disease.&#160; The human lumbar facet joint will, therefore, be used as a prototypical region of interest for dynamic [18F]-NaF-PET-MRI analysis in this manuscript.

Quantitative [18F]-Naf-PET-MRI Analysis for the Evaluation of Dynamic Bone Turnover in a Patient with Facetogenic Low Back Pain

Imaging techniques that reflect dynamic bone turnover may aid in characterizing a wide range of bone pathologies. We present detailed methodologies for performing and analyzing dynamic [18F]-NaF-PET-MRI data in a patient with facetogenic low back pain using the lumbar facet joints as a prototypical region of interest.

Imaging techniques that reflect dynamic bone turnover may aid in characterizing a wide range of bone pathologies. Bone is a dynamic tissue undergoing ...