This work was supported by a research grant from&#160;the Flemish Research Foundation [G027422N].

All procedures are in accordance with the European guidelines (directive 2010/63/EU), and the protocol was approved by the local Animal Ethical Committee of Ghent University (ECD 23/33). Twelve Sprague Dawley rats (six female, six male) were included in the study. Their PET scans were obtained using the following protocol at multiple time points ranging from 2 weeks before to 18 weeks after an induced intracerebral hemorrhage. At the time of the first scan, all animals were 18 weeks of age and the females weighed 244.8 &#177; 10.1 g (mean &#177; SD) while males weighed 363.6 &#177; 13.3 g.
Ensure that radioactive materials are only worked with and handled by trained personnel. Keep the dose to staff and animals as low as reasonably achievable (ALARA).
1. Data acquisition
NOTE: See the Table of Materials for details about the preclinical PET imager and software used for data acquisition. The imager is a 45 detector (arranged in 5-rings) PET scanner covering an axial field of view (FOV) of 13 cm and a transaxial FOV of 7.6 cm, using LYSO crystals and SiPM detectors. The system shows a spatial resolution of 850 &#181;m, a sensitivity of 12%, and an energy resolution of 12.6%12. The following steps were written with this in mind.
<ol>
	<li>Food-deprive the animals for 6-14 h prior to scanning by removing all food from their cage. Once the animal has undergone a sufficient fasting period, start preparations for data acquisition as follows.</li>
	<li>Turn on a heating pad and allow it to warm up to 30&#8211;35 &#176;C.</li>
	<li>Anesthetize the animal with isoflurane by placing the animal in a gas anesthesia chamber filled with 5% isoflurane in medical O2 at a flow rate of 2,000 mL/min. Help maintain the animal&#39;s body temperature by placing a heating lamp 30 cm from the chamber. Once the respiration rate has decreased to 0.5&#8211;1 breaths per second, confirm adequate anesthesia depth by checking for the absence of a paw withdrawal reflex in response to pressure applied to the paw pad.</li>
	<li>Weigh the animal.</li>
	<li>Place the animal on the heating pad. Use a nose cone to administer 2% isoflurane in medical O2 at a flow rate of 500 mL/min. Adjust the isoflurane dose as necessary to keep the animal properly anesthetized. Apply ocular lubricant to prevent corneal drying.</li>
	<li>Shave a section of the animal&#39;s neck between the shoulder blades.</li>
	<li>Tail vein preparation for tracer injection:
	<ol>
		<li>Turn the animal on its left or right side and use the heating lamp to warm its tail, causing vasodilation.</li>
		<li>Take approximately 20 cm of BTPE-10 tubing. Using a needle holder, break off the shaft of a 30 G needle and insert 1&#8211;2 mm of its back end into the PE tubing. Fill a 1 mL insulin syringe with saline and insert the needle tip 3&#8211;5 mm into the PE tubing. Prefill the PE tubing with saline from the filled syringe, and keep the saline syringe connected to the PE tubing.</li>
		<li>Clean the animal&#39;s tail with ethanol. Remove the heating lamp.</li>
		<li>Insert the needle tip of the PE tubing into a lateral tail vein. Confirm proper placement of the needle: look for blood entering the PE tubing when the plunger is pulled back, an absence of resistance while injecting, and the formation of subcutaneous bleb (indicating paravenous injection) at the injection site. If the entry has not been successful, remove the needle from the tail and try again at a more proximal section.</li>
		<li>Secure the needle with a drop of instant glue at the penetration site and tape the PE tubing to the tail. 
		&#8203;NOTE: Avoid movement of the PE tubing. If at any moment blood enters the PE tubing, flush it immediately with saline to prevent clogging.</li>
	</ol>
	</li>
	<li>Switch to medetomidine sedation:
	<ol>
		<li>Place the animal in a prone position on the heating mat. Reapply ocular lubricant if necessary.</li>
		<li>Prepare PE tubing (40&#8211;100 cm) to connect to an infusion pump that is placed close to the PET scanner. Using a needle holder, break off the shaft of a 30 G needle and insert 1&#8211;2 mm of its back into the PE tubing. Fill a 1 mL plastic syringe with a 30 G needle with at least 0.2 mL medetomidine (per animal), and insert the needle tip 3&#8211;5 mm into the PE tubing. Prefill the PE tubing with medetomidine from the syringe.</li>
		<li>Place the syringe with medetomidine in the infusion pump. Turn on the pump and select the correct syringe by clicking Find syringe | BD Plastic | 1 mL.</li>
		<li>Eject boli of 0.005 mL using the pump until a drop emerges from the needle at the other end of the PE tubing. Ensure no air bubbles are present in the PE tubing.</li>
		<li>Insert the needle of the PE tubing 2&#8211;3 mm subcutaneously between the shoulder blades of the animal. Secure the needle with a drop of instant glue at the penetration site and gently tape the PE tubing to the animal&#39;s back.</li>
		<li>Inject a bolus of volume v of medetomidine (rate: 3 mL/min) based on the animal&#39;s weight: 
		<img alt="Equation 1" src="/files/ftp_upload/67458/67458eq1v2.jpg" /> 
		Where d = 0.05&#160;mg/kg (the dose of medetomidine in mg per kg of animal weight), m&#160;is the animal&#39;s weight in kg, and c&#160;is the concentration of medetomidine in mg/mL.</li>
		<li>Stop isoflurane administration 10 min after the administration of the medetomidine bolus, adjusting the isoflurane dose as necessary to maintain stable anesthesia during this waiting period. 
		NOTE: Isoflurane combined with medetomidine significantly slows the animal&#39;s respiratory rate. Close monitoring is essential until isoflurane administration ceases.</li>
		<li>Five minutes after stopping isoflurane, begin a continuous infusion of medetomidine at a rate of: 
		rcont = r&#160;&#8226; m 
		Where r = 0.1&#160;mg/(kg&#183;h); the amount of medetomidine in mg per animal body weight in kg/h), and m&#160;is the animal&#39;s weight in kg. 
		&#8203;NOTE: An equilibration period of an additional 25 min after starting continuous infusion (thus 30 min after stopping isoflurane) is needed before the scan can be initiated to ensure the animal&#39;s system is free of isoflurane. During this time, proceed with the following steps.</li>
	</ol>
	</li>
	<li>Animal positioning in the PET scanner:
	<ol>
		<li>Prepare the scanner bed with a heating pad, a pressure sensor, and paper tissues. Use the sensor to monitor the animal&#39;s respiratory rate and the paper tissues for absorbing urine excreted by the animal. 
		NOTE: Due to the medetomidine, the animal will typically excrete large amounts of urine.</li>
		<li>Carefully transfer the animal onto the scanner bed, ensuring the medetomidine line and tail vein catheter remain secure. Position the animal&#39;s head as straight as possible using a nose cone for assistance if necessary. Secure the head with tape once properly positioned.</li>
		<li>Turn on the heating pad and verify the respiratory rate monitoring system is functioning correctly, adjusting pressure sensor positioning if needed.</li>
	</ol>
	</li>
	<li>Ten to five minutes before starting the PET scan, fill an insulin syringe with approximately 20 MBq 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) diluted in 0.1&#8211;0.8 mL of saline. 
	&#8203;CAUTION: Fluorine-18 (18F) is a fluorine radioisotope with a half-life of 109.8 min. Follow local radiation safety protocols when handling radioactive material.</li>
	<li>Open the scanner software and configure the following scan parameters: Select 18F as the isotope (important for decay correction), enter the measured activity of the syringe containing the radiotracer (in MBq measured by the dose calibrator), and the time of measurement (the information will be saved in the metadata, which is needed to convert the data to other units such as standard uptake values). Select the General protocol and tick Automatic sorting after acquisition. Set the scan duration to 1 h, and adjust the region of interest (ROI) so it contains the entire rat brain (typically position 2-5).&#160;</li>
	<li>Once 30 min have passed since the stop of isoflurane administration, initiate the PET scan:
	<ol>
		<li>Again, confirm proper placement in the vein by aspiration followed by injection of a small amount of saline as described in step 1.7.4.</li>
		<li>Replace the saline syringe with the radiotracer syringe. When removing the syringe from the PE tubing, it is possible that blood enters the PE tubing, pushing out saline. Insert the needle of the radiotracer syringe quickly without puncturing the PE tubing.</li>
		<li>Start the scan using the scanner software.</li>
		<li>Once the acquisition begins, inject the tracer as a bolus over approximately 0.5&#8211;2 s. Immediately replace the empty radiotracer syringe with the saline syringe and flush the PE tubing with approximately 0.1 mL of saline. Use a tissue to catch any drops of radiotracer that may escape during the syringe swap. 
		NOTE: The count rate displayed by the scanner software should rapidly increase to 4.5&#8211;6.5 Mcps following tracer injection. The count rate initially being significantly below 4 Mcps and increasing afterwards indicates a (partially) paravenous tracer injection.</li>
		<li>Assess the remaining activity that was not injected into the animal by measuring the activity of the tracer syringe and potentially contaminated tissue(s) and gloves. Enter that activity and the time of measurement into the scanner software to have it saved in the metadata. 
		&#8203;NOTE: A remaining activity of 0.1&#8211;1.5 MBq is typical, depending on how much tracer escaped when switching the tracer for the saline syringe.</li>
	</ol>
	</li>
	<li>Once the scan is completed, eject the bed with the animal from the scanner. 
	NOTE: The animal may react to stimuli or wake up before medetomidine has been antagonized. Handle the animal with care and be prepared for sudden movements during the following steps. Also be aware that the animal is radioactive. Thus, aim to complete the following steps as quickly and carefully as possible.</li>
	<li>Remove the needle and PE tubing from the animal&#39;s tail using a needle holder. Apply a tissue or compress to the puncture site to stop potential bleeding.</li>
	<li>Stop medetomidine administration and remove the needle and PE tubing from the animal&#39;s neck.</li>
	<li>Place the animal in a cage free of other animals, using a tissue to catch (radioactive) urine that may be excreted while moving the animal. Administer 1 mL of saline subcutaneously in its back using a 1 mL insulin syringe to promote rehydration.</li>
	<li>Reverse the sedation with a subcutaneous injection of atipamezole.
	<ol>
		<li>Calculate the appropriate volume v&#160;using the following equation: 
		<img alt="Equation 1" src="/files/ftp_upload/67458/67458eq1v2.jpg" style="opacity: 0.9;" /> 
		Where d = 0.5 mg/kg, i.e. the dose of medetomidine in mg per kg of animal weight, m&#160;is the weight of the animal in kg, and c&#160;is the concentration of atipamezole in mg/mL.</li>
		<li>For light-weight animals resulting in small calculated volumes, dilute the atipamezole with saline to allow for a more accurate dose. Fill an insulin syringe with 4&#160;&#8226;&#160;v&#160;of atipamezole and 12 &#8226;&#160;v&#160;of saline. Inject 1/4&#160;of the resulting solution subcutaneously into the animal&#39;s back near the neck.</li>
	</ol>
	</li>
	<li>Monitor the animal visually until it wakes up, which should take 1&#8211;5 min. Once the animal is able to keep itself upright and move around freely, return it to group housing. Provide the animal with food and water.</li>
</ol>
2. Data reconstruction and quality check
NOTE: Using the hard- and software available in our study, all PET data were corrected for radionuclide decay, and acquired sinograms were reconstructed with the ordered subset expectation maximization 3-dimensional (OSEM-3D) algorithm using a 30% window around the 511 keV photopeak. The OSEM reconstruction software used its default settings of 10 subsets with 20 million events per subset. Images were reconstructed into a 192 x 192 x 384 transverse matrix with cubic image voxels of 0.4 mm. No attenuation correction was performed.
<ol>
	<li>To verify that tracer injection was successful, check the count rate detected during the 60 min acquisition (i.e., time-activity curve (TAC)). Confirm that there is a peak within the first minute of acquisition, immediately after the tracer had been injected.</li>
	<li>Static reconstruction: Reconstruct the acquired data using an OSEM algorithm using 30 iterations, an isometric voxel size of 400 &#181;m, and an energy window of 30% centered on the 511 keV photopeak.</li>
	<li>Once the reconstruction is complete, inspect the resulting image for artifacts.</li>
	<li>Dynamic reconstruction: Reconstruct the acquired data into thirty 2 min time frames using the same settings as for the static reconstruction.</li>
</ol>
3. Data analysis
NOTE: The following steps 3.1 and 3.2 are performed in a biomedical software environment dedicated to quantification of PET data, using the Image Registration and Fusion Tool (PFUS) and the General Kinetic Modeling Tool (PKIN).
<ol>
	<li>In PFUS:
	<ol>
		<li>In sub-page Load Input Images:
		<ol>
			<li>Load the DICOM file of the dynamic reconstruction by either using the INP load button or by dragging and dropping the file into the canvas. Use the General image display control in the right top to navigate through slices and time frames and adjust the color bar. If needed, adjust the image orientation to standard orientation by using the Change input image orientation button on the right sidebar.</li>
			<li>Cropping and frame average: Click the arrow in the right bottom to display the hidden controls for summing and cropping and tick Crop. In the canvas, define the boundaries for cropping by adjusting the edges and dragging the center of the cropping box; ensure the whole brain and a bit of padding, containing parts of the eyes and spinal cord, are contained. Once the cropping box is defined properly, click the cropping button to crop the image. Calculate the time-weighted frame average over all time frames by clicking the orange average button and wait for the result to be automatically added to the input images, resulting in two input images in total: the cropped dynamic data with the time frames and the cropped time-weighted average of the same data.</li>
			<li>Select Deform as Matching method or press the button if already selected to move on to template-based normalization.</li>
		</ol>
		</li>
		<li>In sub-page Reference &#38; Matching:
		<ol>
			<li>Select the time-weighted average image as the input image (it is normally selected automatically from the last step).</li>
			<li>Load a reference by clicking on the button to select a normalization template as the reference image. Select Rat FDG (W. Schiffer).</li>
			<li>Match the input to the template by clicking the button for Input matching | Input: Adjust manually in the sidebar on the right. Drag and rotate the input image to roughly match the template. Ensure that Rat is selected as species, the registration method is Deform, then click the Match Current button to reach the next sub-page.</li>
		</ol>
		</li>
		<li>In sub-page Matching Result:
		<ol>
			<li>Check the result and adjust the match manually if needed. Click Apply Current Transformation to All to also match the input image consisting of the time frames.</li>
			<li>Click the green button VOIs to move on to the next processing step.</li>
		</ol>
		</li>
		<li>In sub-page VOI Analysis:
		<ol>
			<li>Select the image containing the time frames as image A in the bottom right menu.</li>
			<li>Go to the Template tab and select Px Rat (W. Schiffer) in the Atlas tab, or load a custom atlas, and select the desired volumes. To apply the VOIs, click the Outline button in the bottom.</li>
			<li>Click the button above the Template tab to calculate TACs and send them to PKIN tools.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>In PKIN:
	<ol>
		<li>In the bottom right, select TACs for Display Type to visualize the TACs in kBq/mL of the VOIs selected beforehand.</li>
		<li>Right-click on the canvas with the TACs and click Value table of visible curves. Copy the table to a spreadsheet for further analysis.</li>
	</ol>
	</li>
	<li>Calculate the Pearson correlation between all pairings of VOIs, using data from the sixth to last time frame (= 10&#8211;60 min post scan start), to obtain a correlation matrix. A Python script called &#8220;correlation_matrix.py&#8221; fulfilling this purpose is included in Supplemental File 1.</li>
	<li>Calculate whether the Pearson correlation is significant by using the t-test statistic:&#160;<img alt="Equation 1" src="/files/ftp_upload/67458/67458eq2v2.jpg" />&#160;with n - 2 degrees of freedom, where r is the Pearson correlation coefficient and n = 25 the number of time frames used for calculating the Pearson correlation. Apply a suitable correction for multiple comparisons and compare the statistic to the critical value of a two-tailed t-distribution (p = 0.05) with n - 2 degrees of freedom. Consider the Pearson correlation between two VOIs significant if the corrected t-test value is smaller than the critical value.</li>
</ol>

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The authors have no conflicts of interest to disclose.

The protocol provided here guides users through the process of acquiring 1 h dynamic PET data using [18F]FDG as a tracer in rats. In the end, a correlation matrix of VOIs is obtained, which can be used to assess metabolic connectivity on a single-subject level. Experienced researchers may adjust the protocol to fit their specific needs at various points, for example, by using a different radiotracer, acquisition time, or time frame widths for image reconstructions, and selecting relevant VOIs in the data analysis part.
Tracer injection is one of the most critical parts of this protocol. Preparation of the tail vein access should be performed by an experienced professional in lab animal research. When the needle is correctly positioned inside the tail vein, there should be little resistance when injecting saline or the tracer through the tubing. If there is doubt about the quality of the tail vein access, it is recommended to remove the needle and tubing and try to get proper access before any tracer has been injected. In case an animal has been injected paravenously, it is recommended to redo the experiment at a later time point, as the uptake dynamics of the tracer are different compared to a successful injection (see Figure 1). Since the half-life of 18F is 109.8 min, an already injected animal has to wait at least 18.5 h before it can be injected again to avoid residual radioactivity in the animal&#39;s system from the first injection. An alternative to the intravenous injection is intraperitoneal injection, which will also result in different uptake dynamics13.
Animal handling leading up to and during the experiment can impact the results and should thus be kept consistent across acquisitions. To maximize the uptake of [18F]FDG as opposed to dietary glucose, it is essential that the animals fast prior to the PET scan14. Furthermore, keeping the animal warm after the tracer injection reduces tracer uptake in brown adipose tissue14.
The choice of time frames used for correlation analysis poses another impactful factor in this protocol. The first frames of the acquisition reflect a mix of both brain perfusion and glucose consumption. Previous studies have demonstrated that the transition from perfusion to glucose uptake as the dominant process occurs within the first ten minutes following intravenous injection in rats13,15. To ensure the correlation matrix represents metabolic activity rather than perfusion, we exclude the first five frames (equivalent to 10 min) from correlation analysis. Additionally, the length of time frames and resulting number of time frames can influence the outcome. We chose to use twenty-five 2 min frames for correlation analysis to maximize the signal-to-noise ratio per frame while obtaining enough data points for a valid calculation of the Pearson&#39;s correlation coefficients. Extending the scan duration to increase the number and/or length of time frames could further enhance data quality.
While protocols of PET imaging in awake animals are emerging16, anesthetizing the animals during tracer injection and scan acquisition remains the most feasible option in most research settings. This poses a relevant deviation from the clinical setting, as the choice of anesthesia influences [18F]FDG uptake and brain response17,18.&#160;For this study, we chose medetomidine, an &#945;2-adrenoreceptor agonist, over isoflurane, which has been shown to affect [18F]FDG uptake differently in different brain regions. Sedation with medetomidine can be well controlled and is reversed quickly by the administration of atipamezole. However, there have been reports of dose-dependent effects of medetomidine on functional connectivity in fMRI studies19.&#160;During the preparation of tail vein access, isoflurane is the preferred option, as the lighter sedation achieved through medetomidine may allow the animal to perceive and react to needle insertion.
Once the metabolic connectivity matrix is obtained, graphs can be constructed from them with VOIs representing nodes and the correlation coefficients representing the edges between them, allowing for graph theory analysis. The resulting graphs can be characterized using network metrics that assess global or local connectivity, offering insights into integration and segregation within the brain network20. This kind of analysis can be especially helpful in studying conditions altering the brain network, such as neurodegenerative diseases or epilepsy, on a single-subject level4,5,21.
VOI-based analysis of the rat brain presents several challenges. Although rat brain atlases are available (such as the Schiffer and Tonoku atlas in PMOD), some brain regions are extremely small, resulting in noisy TACs. Additionally, the limited spatial resolution of preclinical PET (approximately 1 mm) may not always match the size or fine details of certain VOIs represented in these atlases. This issue becomes more significant in smaller animals, like mice, due to their smaller brain size. When translating this methodology to humans, the mismatch between atlas-defined regions and actual brain structure will remain an issue, potentially even more pronounced due to the greater individual variability. However, the larger brain size and the relatively better spatial resolution of clinical PET (3-4 mm) will improve discrimination between brain areas. The gain of temporal resolution through dynamic PET comes with the cost of longer scan times, making this approach less feasible than its static equivalent. Nevertheless, we strongly believe that the development of methods allowing single-subject analysis, such as dynamic PET-based metabolic connectivity presented in this manuscript, is an important research direction in brain research, opening the door to applying metabolic network analysis in clinical practice.

Positron emission tomography (PET) is a molecular imaging technique commonly used in research as well as in clinical settings. Due to the development of various PET tracers, PET can be used to study disease pathophysiology and monitor disease progression and response to treatments1. One of the most widely used radiotracers is 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), which allows for the imaging of glucose metabolism, indicative of cellular activation. It is utilized in oncology for diagnosis, staging, and prognosis; in neurology, commonly in the context of neurodegenerative diseases such as dementia; and in cardiology, to diagnose conditions like sarcoidosis, to name just a few examples1,2,3.
Assessment of metabolic brain connectivity, obtained from [18F]FDG PET data, refers to the functional relationships between tracer uptake in different brain regions. This approach enables the computation of a &#34;connectivity matrix&#34; by selecting a set of brain regions, which can provide insights into how different parts of the brain interact and function together. This type of analysis is particularly useful for studying brain function in health and disease, including conditions such as dementia, epilepsy, and other neurological disorders4,5.
The first study assessing metabolic brain connectivity already dates back to the 1980s6, but researchers mainly explored structural brain connectivity, also known as the &#34;connectome&#34;7, by means of diffusion-weighted magnetic resonance imaging (DW-MRI). Furthermore, functional connectivity using techniques such as functional MRI (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) has been widely investigated for multiple decades8,9.
Recently, there is a regained interest in studying metabolic brain connectivity using [18F]FDG PET, not only on its own, but also in combination with other forms of brain connectivity10. However, due to the inherent &#34;static&#34; nature of PET images (in contrast to, e.g., functional MRI), the vast majority of brain network PET-based results are based on group-level analysis, where correlations between brain regions are calculated at the intersubject level. This limitation makes a within-subject analysis of PET images impossible, which is essential for longitudinal studies that can track changes over time within the same individual4. Therefore, the development of methods that allow single-subject analysis, such as dynamic PET-based molecular connectivity, is an important research direction in brain research investigating network disorders, since it opens the door to the use of molecular network analysis in clinical practice. Hence, dynamic PET data were used in our preclinical study.
Our research groups are currently conducting a study that examines changes in metabolic connectivity following an intracerebral hemorrhage on an intrasubject level across multiple time points using the rat collagenase model11. To investigate intrasubject metabolic brain connectivity, temporal information of the tracer uptake in different brain regions is required, which can be obtained through dynamic PET. In the following sections, we give a detailed description of the data acquisition and analysis protocol.

<table><tbody><tr><td>Antisedan</td><td>Orion Pharma</td><td></td><td>Atipamezole hydrochloride 5 mg/mL</td></tr><tr><td>BD Micro-Fine+ insulin syringe 1 mL</td><td>BD</td><td>324827</td><td>0.33 mm (29G) x 12.7 mm</td></tr><tr><td>BD Microlance 3 Needles 30 G x 1/2&quot;</td><td>BD</td><td>304000</td><td>30 G x 1/2&quot;; 0,3 x 13 mm</td></tr><tr><td>BD Plastipak syringe 1 mL</td><td>BD</td><td>303172</td><td>for infusion pump</td></tr><tr><td>BTPE-10 Polyethylene tubing</td><td>Instech</td><td></td><td>0.11x.024in (.28x60mm)</td></tr><tr><td>Domitor</td><td>Orion Pharma</td><td>1070499</td><td>Medetomidine hydrochloride 1 mg/mL</td></tr><tr><td>Fusion 100 infusion pump</td><td>Chemyx Inc.</td><td>07100</td><td>Newer model available: Fusion 100X</td></tr><tr><td>Isoflutek 1000 mg/g</td><td>Alivira</td><td></td><td>Isoflurane</td></tr><tr><td>MOLECUBES &amp;beta;-CUBE with CUBEFLOW software</td><td>MOLECUBES NV</td><td></td><td>Preclinical PET scanner</td></tr><tr><td>PMOD Software version 4.4&amp;nbsp;</td><td>Bruker Corporation</td><td></td><td>http://www.pmod.com; quantification of PET data</td></tr><tr><td>Saline</td><td>B. Braun</td><td>394496</td><td>NaCl 0.9%</td></tr><tr><td>Vidisic eye gel</td><td>Vidisic</td><td></td><td>Carbomerum 980 2 mg/g</td></tr></tbody></table>

studying metabolic brain connectivity using 2-deoxy-2-[18f]fluoro-d-glucose dynamic positron emission tomography at the single-subject level

To this day, metabolic brain connectivity is mostly studied on a group level through the acquisition of static positron emission tomography (PET) data of multiple subjects. Our research groups are currently studying changes in metabolic connectivity across multiple time points following an intracerebral hemorrhage on an intrasubject level in rats. To investigate intrasubject metabolic brain connectivity, temporal information of the tracer uptake in different brain regions is required, which can be achieved through dynamic PET. In this publication, we give a detailed description of our data acquisition and analysis protocol.
Dynamic PET data of the rat brain are acquired on a dedicated preclinical PET system using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) as tracer. The tracer is injected intravenously as a bolus at the start of the PET scan. During the 60 min acquisition, animals are sedated with medetomidine.
After acquisition, the PET data are reconstructed into thirty 2 min time frames using an iterative reconstruction algorithm (Maximum-Likelihood Expectation-Maximization). A parcellated atlas consisting of multiple volumes of interest (VOIs) is used to extract time-activity curves of each VOI, which are then used to calculate the Pearson correlation coefficient between each pair of VOIs.
This dynamic PET protocol enables the assessment of metabolic connectivity differences between two single scans, rather than between groups of scans. This approach allows for the study of changes in metabolic connectivity within a single subject across different time points, or for the comparison of an individual&#39;s metabolic connectivity to a normal database. Such comparisons could be useful for tracking disease progression or aiding in the diagnosis of neurological disorders characterized by disrupted communication between brain regions, such as epilepsy or dementia.

Once the scan is completed, the TAC of the detected rate during the acquisition can be investigated to check for a correct tracer injection and uptake. Figure 1 displays a TAC resulting from the whole FOV of the scanner after a successful tracer injection and acquisition (panel A), and a TAC resulting after a partially paravenous tracer injection (panel B). In the successful case, the count rate rises rapidly after tracer injection and reaches its peak within the first 4 min before steadily decreasing for the rest of the acquisition. In the paravenous case, the count rate reaches a local maximum shortly after tracer injection and decreases for multiple minutes before rising again and reaching its global maximum during the second half of the acquisition.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/67458/67458fig01v2.jpg" /> 
Figure 1: Time-activity curves of 60 min acquisitions of the whole field of view of the scanner. (A) Time-activity curve after a successful tracer injection. (B)Time-activity curve after a partially paravenous tracer injection. <a href="https://www.jove.com/files/ftp_upload/67458/67458fig01largev2.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Figure 2 shows an axial, sagittal, and coronal slice of the time-weighted average of the 25 last 2 min frames (10-60 min post scan start) (panel A) and a single 2 min time frame (38-40 min post scan start) (panel B), both resulting from the same acquisition and matching. The colors represent the standard uptake values, with the color bar ranging from 25 (blue) to 200 (red) for these images. The eyes of the animal display high uptake in both images. Figure 3 shows a selection of adapted VOIs from the Px Rat (W. Schiffer) atlas on top of the time-weighted average after spatial normalization with the Rat FDG (W. Schiffer) template. In the study providing the example data shown here, we investigate changes in metabolic connectivity after an intrastriatal hemorrhage, thus regions connected to or in proximity to the striatum were selected.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/67458/67458fig2.jpg" /> 
Figure 2: PET data (standard uptake values) after cropping around the rat brain. (A) Image after time-averaging 25&#160;2 min time frames. (B) Image of the 20th 2 min frame (38-40 min post scan start). <a href="https://www.jove.com/files/ftp_upload/67458/67458fig2large.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/67458/67458fig3.jpg" /> 
Figure 3: Adapted Px Rat (W. Schiffer) atlas. VOIs of the rat atlas on top of the acquired PET image (screenshot of PMOD). Abbreviation: VOIs = volumes of interest. <a href="https://www.jove.com/files/ftp_upload/67458/67458fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:font-size="6px" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td></td>
			<td>Hippocampus</td>
			<td>Midbrain</td>
			<td>Accumbens</td>
			<td>Amygdala</td>
			<td>Striatum</td>
			<td>Thalamus</td>
			<td>CingulateC</td>
			<td>EntorhinalC</td>
			<td>MotorC</td>
			<td>RetrosplenialC</td>
			<td>SomatosensoryC</td>
		</tr>
		<tr>
			<td>Hippocampus</td>
			<td>1.000</td>
			<td>0.821</td>
			<td>0.667</td>
			<td>0.502</td>
			<td>0.858</td>
			<td>0.746</td>
			<td>0.715</td>
			<td>0.818</td>
			<td>0.868</td>
			<td>0.848</td>
			<td>0.855</td>
		</tr>
		<tr>
			<td>Midbrain</td>
			<td>0.821</td>
			<td>1.000</td>
			<td>0.750</td>
			<td>0.531</td>
			<td>0.865</td>
			<td>0.803</td>
			<td>0.740</td>
			<td>0.854</td>
			<td>0.913</td>
			<td>0.892</td>
			<td>0.876</td>
		</tr>
		<tr>
			<td>Accumbens</td>
			<td>0.667</td>
			<td>0.750</td>
			<td>1.000</td>
			<td>0.608</td>
			<td>0.812</td>
			<td>0.656</td>
			<td>0.756</td>
			<td>0.752</td>
			<td>0.840</td>
			<td>0.811</td>
			<td>0.805</td>
		</tr>
		<tr>
			<td>Amygdala</td>
			<td>0.502</td>
			<td>0.531</td>
			<td>0.608</td>
			<td>1.000</td>
			<td>0.634</td>
			<td>0.678</td>
			<td>0.744</td>
			<td>0.552</td>
			<td>0.598</td>
			<td>0.615</td>
			<td>0.668</td>
		</tr>
		<tr>
			<td>Striatum</td>
			<td>0.858</td>
			<td>0.865</td>
			<td>0.812</td>
			<td>0.634</td>
			<td>1.000</td>
			<td>0.864</td>
			<td>0.865</td>
			<td>0.925</td>
			<td>0.942</td>
			<td>0.912</td>
			<td>0.944</td>
		</tr>
		<tr>
			<td>Thalamus</td>
			<td>0.746</td>
			<td>0.803</td>
			<td>0.656</td>
			<td>0.678</td>
			<td>0.864</td>
			<td>1.000</td>
			<td>0.819</td>
			<td>0.859</td>
			<td>0.831</td>
			<td>0.883</td>
			<td>0.877</td>
		</tr>
		<tr>
			<td>CingulateC</td>
			<td>0.715</td>
			<td>0.740</td>
			<td>0.756</td>
			<td>0.744</td>
			<td>0.865</td>
			<td>0.819</td>
			<td>1.000</td>
			<td>0.857</td>
			<td>0.836</td>
			<td>0.820</td>
			<td>0.832</td>
		</tr>
		<tr>
			<td>EntorhinalC</td>
			<td>0.818</td>
			<td>0.854</td>
			<td>0.752</td>
			<td>0.552</td>
			<td>0.925</td>
			<td>0.859</td>
			<td>0.857</td>
			<td>1.000</td>
			<td>0.888</td>
			<td>0.892</td>
			<td>0.888</td>
		</tr>
		<tr>
			<td>MotorC</td>
			<td>0.868</td>
			<td>0.913</td>
			<td>0.840</td>
			<td>0.598</td>
			<td>0.942</td>
			<td>0.831</td>
			<td>0.836</td>
			<td>0.888</td>
			<td>1.000</td>
			<td>0.978</td>
			<td>0.939</td>
		</tr>
		<tr>
			<td>RetrosplenialC</td>
			<td>0.848</td>
			<td>0.892</td>
			<td>0.811</td>
			<td>0.615</td>
			<td>0.912</td>
			<td>0.883</td>
			<td>0.820</td>
			<td>0.892</td>
			<td>0.978</td>
			<td>1.000</td>
			<td>0.921</td>
		</tr>
		<tr>
			<td>SomatosensoryC</td>
			<td>0.855</td>
			<td>0.876</td>
			<td>0.805</td>
			<td>0.668</td>
			<td>0.944</td>
			<td>0.877</td>
			<td>0.832</td>
			<td>0.888</td>
			<td>0.939</td>
			<td>0.921</td>
			<td>1.000</td>
		</tr>
	</tbody>
</table>
Table 1: Correlation matrix. An example of a correlation matrix containing the Pearson correlation coefficients between 11 VOIs. The matrix was computed from one healthy animal using 25 2 min time frames spanning 10-60 min after scan start and tracer injection. Abbreviation: VOIs = volumes of interest.
Table 1 contains the Pearson correlation coefficients between the TACs of all pairings of 11 VOIs from the adapted Px Rat (W. Schiffer) atlas shown in Figure 3. For generating this example, left and right structures of the same brain region were combined into one VOI before TACs were calculated. While the number and selection of specific VOIs need to be chosen by the researchers depending on their study, the result is always a symmetric matrix whose elements on the main diagonal equal 1.
Supplemental File 1: A Python script &#34;correlation_matrix.py.&#34; <a href="https://www.jove.com/files/ftp_upload/67458/correlation_matrix.py" target="_blank">Please click here to download this file.</a>

The acquisition of dynamic positron emission tomography (PET) data and reconstruction into time frames allows for metabolic brain connectivity analysis at the single-subject level. We describe a method to acquire [18F]FDG dynamic PET data of the rat brain and obtain a connectivity matrix through the extraction of time-activity curves of volumes of interest.

Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level

To this day, metabolic brain connectivity is mostly studied on a group level through the acquisition of static positron emission tomography (PET) data of ...

studying-metabolic-brain-connectivity-using-2-deoxy-2-18ffluoro-d

Universidad San Sebastian

Research

JoVE Journal

Neuroscience

209 Views.  Ghent University. The acquisition of dynamic positron emission tomography (PET) data and reconstruction into time frames allows for metabolic brain connectivity analysis at the single-subject level. We describe a method to acquire [18F]FDG dynamic PET data of the rat brain and obtain a connectivity matrix through the extraction of time-activity curves of volumes of interest.

Video: Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level

Studying the Integration of Adult-born Neurons

Neurogenesis occurs in adult mammalian brains in the sub-ventricular zone (SVZ) of the lateral ventricle and in the sub-granular zone (SGZ) of the hippocampal dentate gyrus throughout life. Previous reports have shown that adult hippocampal neurogenesis is associated with diverse brain disorders, including epilepsy, schizophrenia, depression and anxiety (1). Deciphering the process of normal and aberrant adult-born neuron integration may shed light on the etiology of these diseases and inform the development of new therapies.
SGZ adult neurogenesis mirrors embryonic and post-natal neuronal development, including stages of fate specification, migration, synaptic integration, and maturation. However, full integration occurs over a prolonged, 6-week period. Initial synaptic input to adult-born SGZ dentate granule cells (DGCs) is GABAergic, followed by glutamatergic input at 14 days (2). The specific factors which regulate circuit formation of adult-born neurons in the dentate gyrus are currently unknown.
Our laboratory uses a replication-deficient retroviral vector based on the Moloney murine leukemia virus to deliver fluorescent proteins and hypothesized regulatory genes to these proliferating cells. This viral technique provides high specificity and resolution for analysis of cell birth date, lineage, morphology, and synaptogenesis.
A typical experiment often employs two or three viruses containing unique label, transgene, and promoter elements for single-cell analysis of a desired developmental process in vivo. The following protocol describes a method for analyzing functional newborn neuron integration using a single green (GFP) or red (dTomato) fluorescent protein retrovirus and patch-clamp electrophysiology.

A way to study the integration of newborn dentate granule cells in adult animals is described. This technique uses an engineered retrovirus to label newborn neurons, followed by electrophysiological recordings to determine in vivo functional integration.

Neurogenesis occurs in adult mammalian brains in the sub-ventricular zone (SVZ) of the lateral ventricle and in the sub-granular zone (SGZ) of the ...

Imaging Cleared Intact Biological Systems at a Cellular Level by 3DISCO

Tissue clearing and subsequent imaging of transparent organs is a powerful method to analyze fluorescently labeled cells and molecules in 3D, in intact organs. Unlike traditional histological methods, where the tissue of interest is sectioned for fluorescent imaging, 3D imaging of cleared tissue allows examination of labeled cells and molecules in the entire specimen. To this end, optically opaque tissues should be rendered transparent by matching the refractory indices throughout the tissue. Subsequently, the tissue can be imaged at once using laser-scanning microscopes to obtain a complete high-resolution 3D image of the specimen. A growing list of tissue clearing protocols including 3DISCO, CLARITY, Sca/e, ClearT2, and SeeDB provide new ways for researchers to image their tissue of interest as a whole. Among them, 3DISCO is a highly reproducible and straightforward method, which can clear different types of tissues and can be utilized with various microscopy techniques. This protocol describes this straightforward procedure and presents its various applications. It also discusses the limitations and possible difficulties and how to overcome them.

To obtain high-resolution images of fluorescently labeled cells within large tissues, ideally, the biological samples should be imaged without sectioning. 3DISCO is a straightforward tissue clearing procedure based on sequential incubation with organic solvents. Upon clearing, the organs become transparent allowing an end-to-end laser scan of the specimen.

Tissue clearing and subsequent imaging of transparent organs is a powerful method to analyze fluorescently labeled cells and molecules in 3D, in intact ...

A Simple One-step Dissection Protocol for Whole-mount Preparation of Adult Drosophila Brains

There is an increasing interest in using Drosophila to model human brain degenerative diseases, map neuronal circuitries in adult brains, and study the molecular and cellular basis of higher brain functions. A whole-mount preparation of adult brains with well-preserved morphology is critical for such whole brain-based studies, but can be technically challenging and time-consuming. This protocol describes an easy-to-learn, one-step dissection approach of an adult fly head in less than 10 s, while keeping the intact brain attached to the rest of the body to facilitate subsequent processing steps. The procedure helps remove most of the eye and tracheal tissues normally associated with the brain that can interfere with the later imaging step, and also places less demand on the quality of the dissecting forceps. Additionally, we describe a simple method that allows convenient flipping of the mounted brain samples on a coverslip, which is important for imaging both sides of the brains with similar signal intensity and quality. As an example of the protocol, we present an analysis of dopaminergic (DA) neurons in adult brains of WT (w1118) flies. The high efficacy of the dissection method makes it particularly useful for large-scale adult brain-based studies in Drosophila.

A Simple One-step Dissection Protocol for Whole-mount Preparation of Adult Drosophila Brains

The adult Drosophila brain is a valuable system for studying neuronal circuitry, higher brain functions, and complex disorders. An efficient method to dissect whole brain tissue from the small fly head will facilitate brain-based studies. Here we describe a simple, one-step dissection protocol of adult brains with well-preserved morphology.

There is an increasing interest in using Drosophila to model human brain degenerative diseases, map neuronal circuitries in adult brains, and study the ...

In Vivo Single-Molecule Tracking at the Drosophila Presynaptic Motor Nerve Terminal

An increasing number of super-resolution microscopy techniques are helping to uncover the mechanisms that govern the nanoscale cellular world. Single-molecule imaging is gaining momentum as it provides exceptional access to the visualization of individual molecules in living cells. Here, we describe a technique that we developed to perform single-particle tracking photo-activated localization microscopy (sptPALM) in Drosophila larvae. Synaptic communication relies on key presynaptic proteins that act by docking, priming, and promoting the fusion of neurotransmitter-containing vesicles with the plasma membrane. A range of protein-protein and protein-lipid interactions tightly regulates these processes and the presynaptic proteins therefore exhibit changes in mobility associated with each of these key events. Investigating how mobility of these proteins correlates with their physiological function in an intact live animal is essential to understanding their precise mechanism of action. Extracting protein mobility with high resolution in vivo requires overcoming limitations such as optical transparency, accessibility, and penetration depth. We describe how photoconvertible fluorescent proteins tagged to the presynaptic protein Syntaxin-1A can be visualized via slight oblique illumination and tracked at the motor nerve terminal or along the motor neuron axon of the third instar Drosophila larva.

In Vivo Single-Molecule Tracking at the Drosophila Presynaptic Motor Nerve Terminal

Here we illustrate how single molecule photo-activated localization microscopy can be carried out on the motor nerve terminal of a live Drosophila melanogaster third instar larva.

An increasing number of super-resolution microscopy techniques are helping to uncover the mechanisms that govern the nanoscale cellular world. ...

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software

Measuring neural activity and connectivity associated with cognitive functions at high spatial and temporal resolutions is an important goal in cognitive neuroscience. Intracranial electroencephalography (EEG) can directly record electrical neural activity and has the unique potential to accomplish this goal. Traditionally, averaging analysis has been applied to analyze intracranial EEG data; however, several new techniques are available for depicting neural activity and intra- and inter-regional connectivity. Here, we introduce two analytical protocols we recently applied to analyze intracranial EEG data using the Statistical Parametric Mapping (SPM) software: time-frequency SPM analysis for neural activity and dynamic causal modeling of induced responses for intra- and inter-regional connectivity. We report our analysis of intracranial EEG data during the observation of faces as representative results. The results revealed that the inferior occipital gyrus (IOG) showed gamma-band activity at very early stages (110 ms) in response to faces, and both the IOG and amygdala showed rapid intra- and inter-regional connectivity using various types of oscillations. These analytical protocols have the potential to identify the neural mechanisms underlying cognitive functions with high spatial and temporal profiles.

We present two analytical protocols that can be used to analyze intracranial electroencephalography data using the Statistical Parametric Mapping (SPM) software: time-frequency statistical parametric mapping analysis for neural activity, and dynamic causal modeling of induced responses for intra- and inter-regional connectivity.

Measuring neural activity and connectivity associated with cognitive functions at high spatial and temporal resolutions is an important goal in cognitive ...

Studying Brain Function in Children Using Magnetoencephalography

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique which directly measures magnetic fields produced by the electrical activity of the human brain. MEG is quiet and less likely to induce claustrophobia compared with magnetic resonance imaging (MRI). It is therefore a promising tool for investigating brain function in young children. However, analysis of MEG data from pediatric populations is often complicated by head movement artefacts which arise as a consequence of the requirement for a spatially-fixed sensor array that is not affixed to the child's head. Minimizing head movements during MEG sessions can be particularly challenging as young children are often unable to remain still during experimental tasks. The protocol presented here aims to reduce head movement artefacts during pediatric MEG scanning. Prior to visiting the MEG laboratory, families are provided with resources that explain the MEG system and the experimental procedures in simple, accessible language. An MEG familiarization session is conducted during which children are acquainted with both the researchers and the MEG procedures. They are then trained to keep their head still whilst lying inside an MEG simulator. To help children feel at ease in the novel MEG environment, all of the procedures are explained through the narrative of a space mission. To minimize head movement due to restlessness, children are trained and assessed using fun and engaging experimental paradigms. In addition, children's residual head movement artefacts are compensated for during the data acquisition session using a real-time head movement tracking system. Implementing these child-friendly procedures is important for improving data quality, minimizing participant attrition rates in longitudinal studies, and ensuring that families have a positive research experience.

This article introduces a child-friendly research protocol designed to improve data quality by reducing head movement during pediatric magnetoencephalography (MEG). We familiarize families with the MEG environment, train children to remain still using an MEG simulator, and correct for residual head movement artefacts using a real-time head movement detection system.

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique which directly measures magnetic fields produced by the electrical activity of the ...

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Task-based functional magnetic resonance imaging bears great potential to understand how our brain reacts to various types of stimulation; however, this is often achieved without considering the dynamic facet of functional processing, and analytical outputs typically account for merged influences of task-driven effects and underlying spontaneous fluctuations of brain activity. Here, we introduce a novel methodological pipeline that can go beyond these limitations: the use of a sliding-window analytical scheme permits tracking of functional changes over time, and through cross-subject correlational measurements, the approach can isolate purely stimulus-related effects. Thanks to a rigorous thresholding process, significant changes in inter-subject functional correlation can be extracted and analyzed.
On a set of healthy subjects who underwent naturalistic audio-visual stimulation, we demonstrate the usefulness of the approach by tying the unraveled functional reconfigurations to particular cues of the movie. We show how, through our method, one can capture either a temporal profile of brain activity (the evolution of a given connection), or focus on a spatial snapshot at a key time point. We provide a publicly available version of the whole pipeline, and describe its use and the influence of its key parameters step by step.

The goal of the described approach is to determine at what moments of the paradigm (temporal perspective), and between which regions (spatial perspective), significant reconfigurations in functional connectivity occur on functional magnetic resonance imaging recordings during which a time-locked stimulus is played.

Task-based functional magnetic resonance imaging bears great potential to understand how our brain reacts to various types of stimulation; however, this ...

A Benchtop Approach to the Location Specific Blood Brain Barrier Opening using Focused Ultrasound in a Rat Model

Stereotaxic surgery is the gold standard for localized drug and gene delivery to the rodent brain. This technique has many advantages over systemic delivery including precise localization to a target brain region and reduction of off target side effects. However, stereotaxic surgery is highly invasive which limits its translational efficacy, requires long recovery times, and provides challenges when targeting multiple brain regions. Focused ultrasound (FUS) can be used in combination with circulating microbubbles to transiently open the blood brain barrier (BBB) in millimeter sized regions. This allows intracranial localization of systemically delivered agents that cannot normally cross the BBB. This technique provides a noninvasive alternative to stereotaxic surgery. However, to date this technique has yet to be widely adopted in neuroscience laboratories due to the limited access to equipment and standardized methods. The overall goal of this protocol is to provide a benchtop approach to FUS BBB opening (BBBO) that is affordable and reproducible and can therefore be easily adopted by any laboratory.

Focused ultrasound with microbubble agents can open the blood brain barrier focally and transiently. This technique has been used to deliver a wide range of agents across the blood brain barrier. This article provides a detailed protocol for the localized delivery to the rodent brain with or without MRI guidance.

Stereotaxic surgery is the gold standard for localized drug and gene delivery to the rodent brain. This technique has many advantages over systemic ...

Extraction and Dissection of the Domesticated Pig Brain

Use of the pig as a preclinical and translatable animal model has been well-documented and accepted by research fields investigating cardiovascular systems, gastrointestinal systems, and nutrition, and the pig is increasingly being used as a large animal model in neuroscience. Furthermore, the pig is an accepted model to study neurodevelopment as it displays brain growth and development patterns similar to what occurs in humans. As a less common animal model in neuroscience, surgical and dissection procedures on pigs may not be as familiar or well-practiced among researchers. Therefore, a standardized visual protocol detailing consistent extraction and dissection methods may prove valuable for researchers working with the pig. The following video showcases a technique to remove the pig brain while keeping the cortex and brainstem intact and reviews methods to dissect several commonly investigated brain regions including the brainstem, cerebellum, midbrain, hippocampus, striatum, thalamus, and medial prefrontal cortex. The purpose of this video is to provide researchers with the tools and knowledge necessary to consistently perform a brain extraction and dissection on the four-week-old pig.

This protocol details the technique for removal of the pig brain in its entirety and dissection of several brain regions commonly studied in neuroscience.

Use of the pig as a preclinical and translatable animal model has been well-documented and accepted by research fields investigating cardiovascular ...

Positron Emission Tomography Imaging for In Vivo Measuring of Myelin Content in the Lysolecithin Rat Model of Multiple Sclerosis

Multiple sclerosis (MS) is a neuroinflammatory disease with expanding axonal and neuronal degeneration and demyelination in the central nervous system, leading to motor dysfunctions, psychical disability, and cognitive impairment during MS progression. Positron emission tomography (PET) is an imaging technique able to quantify in vivo cellular and molecular alterations.
Radiotracers with affinity to intact myelin can be used for in vivo imaging of myelin content changes over time. It is possible to detect either an increase or decrease in myelin content, what means this imaging technique can detect demyelination and remyelination processes of the central nervous system. In this protocol we demonstrate how to use PET imaging to detect myelin changes in the lysolecithin rat model, which is a model of focal demyelination lesion (induced by stereotactic injection) (i.e., a model of multiple sclerosis disease). 11C-PIB PET imaging was performed at baseline, and 1 week and 4 weeks after stereotaxic injection of lysolecithin 1% in the right striatum (4 &#181;L) and corpus callosum (3 &#181;L) of the rat brain, allowing quantification of focal demyelination (injection site after 1 week) and the remyelination process (injection site at 4 weeks).
Myelin PET imaging is an interesting tool for monitoring in vivo changes in myelin content which could be useful for monitoring demyelinating disease progression and therapeutic response.

Positron Emission Tomography Imaging for In Vivo Measuring of Myelin Content in the Lysolecithin Rat Model of Multiple Sclerosis

This protocol has the aim of monitoring in vivo myelin changes (demyelination and remyelination) by positron emission tomography (PET) imaging in an animal model of multiple sclerosis.

Multiple sclerosis (MS) is a neuroinflammatory disease with expanding axonal and neuronal degeneration and demyelination in the central nervous system, ...

Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[¹⁸F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level

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Studying Brain Function in Children Using Magnetoencephalography

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

A Benchtop Approach to the Location Specific Blood Brain Barrier Opening using Focused Ultrasound in a Rat Model

Extraction and Dissection of the Domesticated Pig Brain

Positron Emission Tomography Imaging for In Vivo Measuring of Myelin Content in the Lysolecithin Rat Model of Multiple Sclerosis