The authors would like to thank Richard Raghoo for providing the PET images shown in Figure 1.

All procedures performed involving human participants were in accordance with the ethical standards of the internal review board (IRB) of the Radboud university medical center and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The ORG algorithm is a vendor specific product and is available on the Siemens Biograph mCT PET/CT scanner family and newer PET/CT models.
1. Patient preparation
<ol>
	<li>Patient anamnesis
	<ol>
		<li>Check the patient&#8217;s name and date of birth. Inclusion criteria are similar to routine non-gated PET scanning. No additional in- or exclusion criteria are required.</li>
		<li>Check the label delivered with the syringe containing the radiotracer (name, date of birth and amount of activity). 
		NOTE: The amount of activity administered to the patient is dependent on the patient&#8217;s body mass and can vary between institutions&#160;(in this protocol an amount of 3.2 MBq/kg is suggested).</li>
		<li>Ensure that the clinical information on the application form is correct by interviewing the patient. Ask the patient whether there were any recent relevant changes in treatment or medication.</li>
		<li>Ask the patient whether he or she has diabetes mellitus (DM). In case the patient has DM, ask whether he or she followed appropriate preparation (i.e., no administration of short working insulin less than 4 hours prior to the PET scan, or use of blood glucose lowering agents (such as metformin).</li>
		<li>Ask the patient whether he or she has any allergies or uses anticoagulants.</li>
		<li>Measure the patient&#8217;s blood glucose by applying a drop of blood obtained by pricking the side of the fingertip of the patient on a dedicated test strip (the serum glucose should not exceed 11.0 mmol/L).</li>
		<li>Explain the patient preparation and imaging procedures to the patient.</li>
	</ol>
	</li>
	<li>Administration of the radiotracer
	<ol>
		<li>Secure venous access to the patient by inserting a peripheral venous cannula in one of the antecubital veins.</li>
		<li>Attach a three way stop cock system with Luer lock to a 20 mL syringe containing saline (this is the secondary syringe).</li>
		<li>Flush the three way stop cock system with saline (for the purpose of deaeration).</li>
		<li>Attach the three way stop cock with syringe to the end of the venous cannula.</li>
		<li>Check whether the venous cannula is patent by carefully flushing 10 mL of saline through the cannula (ask the patient whether he or she has any complaints during flushing).</li>
		<li>Attach the syringe containing the radiotracer (primary syringe) to the three way stop cock. Turn the valves of the three way stop cock so that the flow direction of fluid through the system runs from the syringe containing the radiotracer to the peripheral venous cannula. Administer the radiotracer by slowly pushing the plunger of the syringe (the syringe containing the tracer is placed in a special lead shielded container).</li>
		<li>Turn the valves of the three way stop cock in such a way that the syringe containing saline is connected to the primary syringe (that contained the radiotracer) and flush the syringe to rinse any residual radiotracer from the syringe.</li>
		<li>Turn the valves of the three way stop cock and push the plunger of the primary syringe to administer any residual radiotracer remaining in the syringe to the patient.</li>
		<li>Repeat step 1.2.7. and 1.2.8. three times.</li>
		<li>Turn the three way stop cock (to prevent backflow of blood from the patient&#8217;s vein) and detach the primary syringe. Attach a third syringe containing furosemide, turn the three way stop cock again and administer 0.5 g/Kg of furosemide (with a maximum amount of 10 mg) by pushing the plunger of the syringe. Remove the peripheral&#160; venous cannula and apply pressure to the puncture site using a sterile bandage. Check whether there is no significant bleeding and from the puncture site and fix the bandage using medical tape.</li>
	</ol>
	</li>
	<li>Patient incubation
	<ol>
		<li>Let the patient rest in a comfortable position, preferably in a dimly lit room,&#160;for 50 minutes.</li>
		<li>After 50 minutes, instruct the patient to void their bladder.</li>
		<li>At 55 minutes, escort the patient to the scanner and position the patient supine with the arms up on the scanner bed. Use appropriate arm support to make it as comfortable as possible for the patient. If the patient is not able to elevate his or her arms, scanning can be performed with the arms position alongside the patient.</li>
		<li>Observe the patient&#8217;s breathing pattern and secure the respiratory belt around the patient&#8217;s thorax (usually, the position just beneath the rib cage is optimal). Ensure that the sensor is placed at a location where abdominal wall excursion is identified after visual inspection (usually 5-7 cm from the midline). Secure the belt around the patient by using the Velcro-based closing system.</li>
		<li>Check on the scanner display whether the respiratory signal remains within bounds of the minimum and maximum range (if the respiratory signal is clipping, fasten or tighten the belt appropriately).</li>
		<li>Tip: Make sure the belt is fastened tight enough around the patient&#8217;s chest. Given that patients enter a more relaxed state after some time, the respiratory signal tends to drop (baseline drift of the signal). This prevents the signal from going out of bounds, thus maintaining a high quality of surrogate signal that is being used for respiratory gating.</li>
		<li>Start scanning at 60 minutes after incubation time.</li>
	</ol>
	</li>
</ol>
2. Image acquisition and reconstruction
<ol>
	<li>Protocol selection
	<ol>
		<li>Select the whole-body protocol on the scanner. This can be done by moving the cursor over the appropriate protocol category (indicated by the circles next to the patient icon in the examination card), and click on the appropriate protocol (Figure 3).</li>
		<li>The ORG acquisition protocol will start with a scout scan (topogram) of the patient. To initiate acquisition of the topogram, press the scanner start key (yellow round key with a radiation sign) on the scanner control box (Figure 4). To halt or abort acquisition of the topogram, press the suspend or stop key respectively.</li>
		<li>Start by planning the PET bed positions on the topogram. This can be done by clicking the left mouse button on the topogram and setting the scan range.</li>
		<li>Select the bed positions which to be corrected for respiratory motion (Figure 5). 
		NOTE: These are the &#8216;gated&#8217; bed positions that cover the thorax. The &#8216;gated&#8217; bed positions are recorded in listmode. Depending on the clinical indication, bed positions covering the upper abdomen can also be gated (for example when imaging is indicated for liver or pancreatic lesions). For the non-gated bed positions, it is only necessary to record the sinograms for image reconstruction.</li>
		<li>Set image recording time for the PET bed positions (Figure 5). 
		NOTE: Depending on the amount of injected activity, scan duration of the non-gated&#160;bed positions has to be adapted to yield sufficient image quality. Additionally, the recording time of the non-gated bed positions in combination with the duty cycle being used for image reconstruction of the gated bed positions, the recording time of the gated bed positions is determined. For example, for a duty cycle of 35%, lengthening the scan by factor 3 yields approximately similar statistics for gated and non-gated bed positions. Suggested imaging protocol at the Radboud University Medical Center is a recording time for non-gated bed positions of 2 minutes, whilst for gated bed positions recording time is 6 minutes using a duty cycle of 35%</li>
		<li>After setting up the acquisition parameters, press and hold the start key (yellow round button with a radiation sign) on the scanner control box and wait until the scanner bed has moved back to the starting position. Press the start key again to acquire a low dose CT scan from the patient (head to feet). After acquiring the CT scan, press the start key to initiate the PET scan.</li>
		<li>During image acquisition, regularly check on the patient and the quality of the respiratory signal (adjust the respiratory belt if required). 
		NOTE: Adjustment of the belt should only be performed when no respiratory gated bed positions are acquired. Therefore, adjustments should be done before or after these bed positions are acquired. Adjustment of the belt during acquisition of the gated bed position will affect the quality of the ORG images. Careful observation of the respiratory signal and possible adjustment of the respiratory belt before acquisition of the gated bed positions is required to counteract any significant baseline drifting of the signal during PET scanning.</li>
	</ol>
	</li>
	<li>Image reconstruction
	<ol>
		<li>Review the respiratory signal that has been acquired and select the appropriate duty cycle for the gated bed positions (Figure 6). 
		NOTE: The amplitude range used for respiratory gating is superimposed on the respiratory signal). Check for inconstancies or baseline drifts in the respiratory signal that can influence quality of the respiratory gating.</li>
		<li>Select image reconstruction protocol optimized for viewing (Figure 7). This is usually a high-resolution image reconstruction protocol with smaller voxel sizes for detection of small lesions. It is of importance to realize that the ORG algorithm will calculate the optimal amplitude range by using the entire respiratory signal of the selected bed positions. Though different duty cycles can be used for different bed positions (for example to correct for a varying quality respiratory signal), using different duty cycles for different bed positions is not advised given that this will introduce variations in image quality between different bed positions. 
		NOTE: Here is an example image reconstruction protocol for viewing:
		<ul>
			<li>Algorithm: TrueX + TOF (UltraHD PET)</li>
			<li>Number of iterations:3</li>
			<li>Number of subsets: 21</li>
			<li>Matrix size: 400 &#215; 400</li>
			<li>Post-reconstruction filtering, kernel (3D Gaussian), full width half maximum (FWHM): 3.0 mm</li>
			<li>Duty cycle 35%</li>
		</ul>
		</li>
		<li>Furthermore, reconstruct the PET images with an protocol compliant to the Research4Life (EARL) initiative for quantitative PET imaging. These are usually lower resolution images with specific post-reconstruction filtering applied. 
		NOTE: Here is an example image reconstruction protocol for image quantification:
		<ul>
			<li>Algorithm: TrueX + TOF (UltraHD PET)</li>
			<li>Number of iterations: 3</li>
			<li>Number of subsets: 21</li>
			<li>Matrix size: 256</li>
			<li>Post-reconstruction filtering, kernel (3D Gaussian), full width half maximum (FWHM): 8.0 mm</li>
			<li>Duty cycle 35%</li>
		</ul>
		</li>
		<li>Send the reconstructed images to the PACS archive. The images are now ready to be evaluated by the nuclear medicine physician</li>
	</ol>
	</li>
</ol>

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S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+a+Free-Breathing+CT+and+an+Expiratory+Breath-Hold+CT+with+Regard+to+Spatial+Alignment+of+Amplitude-Based+Respiratory-Gated+PET+and+CT+Images.">Comparison of a Free-Breathing CT and an Expiratory Breath-Hold CT with Regard to Spatial Alignment of Amplitude-Based Respiratory-Gated PET and CT Images.</a> Journal of Nuclear Medicine Technology. 42 (4), 269-273 (2014).</li><li>van der Vos, C. S., Meeuwis, A. P. W., Grootjans, W., de Geus-Oei, L. F., Visser, E. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improving+the+spatial+alignment+in+PET/CT+using+amplitude-based+respiratory-gated+PET+and+patient-specific+breathing-instructed+CT.">Improving the spatial alignment in PET/CT using amplitude-based respiratory-gated PET and patient-specific breathing-instructed CT.</a> Journal of Nuclear Medicine Technology. 47 (2), 154-159 (2018).</li><li>Houdu, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Why+harmonization+is+needed+when+using+FDG+PET/CT+as+a+prognosticator:+demonstration+with+EARL-compliant+SUV+as+an+independent+prognostic+factor+in+lung+cancer.">Why harmonization is needed when using FDG PET/CT as a prognosticator: demonstration with EARL-compliant SUV as an independent prognostic factor in lung cancer.</a> European Journal of Nuclear Medicine and Molecular Imaging. 46 (2), 421-428 (2019).</li><li>Kaalep, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EANM/EARL+FDG-PET/CT+accreditation+-+summary+results+from+the+first+200+accredited+imaging+systems.">EANM/EARL FDG-PET/CT accreditation - summary results from the first 200 accredited imaging systems.</a> European Journal of Nuclear Medicine and Molecular Imaging. 45 (3), 412-422 (2018).</li></ol>

The authors declare no conflict of interest.

In the nuclear medicine community, the deteriorating effects of respiratory motion artefacts in PET imaging have been well-recognized for a long time. It has been shown in many studies that the blurring effect of respiratory motion artefacts can significantly influence image quantification and lesion detectability. Although several respiratory gating methods have been developed, respiratory gating is currently not widely being used in clinical practice. This is particularly due to a resulting variable image quality, unac...

Positron Emission Tomography (PET) in combination with X-ray computed tomography (CT) is a widely accepted imaging tool in clinical practice for accurate diagnosis and clinical staging of a variety of diseases1. The advantage of PET imaging is the ability to visualize and quantify a myriad of biological processes in vivo with high sensitivity and accuracy2. This is achieved through intravenously administering a radioactively labelled compound, also known as a radiotracer, to the patient. Depending on the radiotracer being used, tissue characteristics such as glucose metabolism, cellular proliferation, degree of hypoxia, amino acid transport, and expression of proteins and receptors, can be visualized and quantified2.
Although several radiotracers have been developed, validated, and used in clinical practice, the radioactive glucose analogue 18F-fluorodeoxyglucose (FDG) is the most widely used radiotracer in clinical practice. Given that FDG predominantly accumulates in cells with an elevated glycolytic rate (i.e., cells with elevated glucose uptake and conversion to pyruvate for energy production), it is possible to discriminate tissues with different metabolic states. Similar to glucose, the first step of FDG uptake is transport from the extra-cellular space over the plasma membrane to the intra-cellular space, which is facilitated by glucose transporters (GLUT)3. Once the FDG is in the intra-cellular space, phosphorylation by hexokinases will result in the generation of FDG-6-phosphate. However, in contrast to glucose-6-phosphate, FDG-6-phosphate cannot enter the Krebs cycle for further aerobic dissimilation due to the absence of a hydroxyl (OH) group at the second (2&#8217;) carbon position. Given that the reverse reaction, the dephosphorylation of FDG-6-phosphate back to FDG, hardly occurs in most tissues, the FDG-6-phosphate is trapped intracellularly3. Therefore, the degree of FDG uptake is dependent on the expression of the GLUT (in particular GLUT1 and GLUT3) on the plasma membrane, and the intracellular enzymatic activity of hexokinases. The concept of this continuous uptake and trapping of FDG is referred to as metabolic trapping. The fact that FDG preferentially accumulates in tissues with an elevated metabolic activity is shown in Figure 1a, demonstrating the physiological distribution of FDG in a patient. This FDG-PET image shows higher uptake in heart, brain, and liver tissues, which are known to be metabolically active organs under normal conditions.
The high sensitivity for detecting differences in the metabolic state of tissues makes FDG an excellent radiotracer for discriminating normal from diseased tissues, given that an altered metabolism is an important hallmark for many diseases. This is readily depicted in Figure 1b, showing an FDG-PET image of a patient with stage IV non-small cell lung cancer (NSCLC). There is increased uptake in the primary tumor as well as in metastatic lesions. In addition to visualization, quantification of radiotracer uptake plays an important role in clinical management of patients. Quantitative indices derived from PET images reflecting the degree of radiotracer uptake, such as the standardized uptake value (SUV), metabolic volumes, and total lesion glycolysis (TLG), can be used to provide important prognostic information and measure treatment response for different patient groups4,5,6. In this regard, FDG-PET imaging is increasingly being used to personalize radiotherapy and systemic treatment in oncology patients7. Furthermore, the use of FDG-PET for monitoring acute treatment induced toxicity, such as radiation induced esophagitis8, pneumonitis9 and systemic inflammatory responses10, has been described and provides important information for making image-guided treatment decisions.
Given the important role of PET for clinical management of patients, image quality and quantitative accuracy is important for appropriately guiding treatment decisions based on PET images. However, there are numerous technical factors that can compromise quantitative accuracy of PET images11. An important factor that can significantly influence image quantification in PET is related to the longer acquisition times of PET compared to other radiological imaging modalities, typically several minutes per bed position. As a consequence, patients are usually instructed to breath freely during PET imaging. The result is that PET images suffer from respiratory induced motion, which can lead to significant blurring of organs located within the thorax and upper abdomen. This respiratory-induced motion blurring can significantly impair adequate visualization and quantitative accuracy of radiotracer uptake, which can affect clinical management of patients when using PET images for diagnosis and staging, target volume definition for radiation treatment planning applications, and monitoring of therapy response12.
Several respiratory gating methods have been developed in an attempt to correct PET images for respiratory motion artefacts13. These methods can be categorized into prospective, retrospective, and data-driven gating strategies. Prospective and retrospective respiratory gating techniques typically rely on the acquisition of a respiratory surrogate signal during PET imaging14. These respiratory surrogate signals are used to track and monitor the patient&#8217;s respiratory cycle. Examples of respiratory tracking devices are detection of chest wall excursion using pressure sensors12 or optical tracking systems (e.g., video cameras)15, thermocouples to measure the temperature of breathed air16, and spirometers to measure airflow and thereby indirectly estimating volume changes in the patient&#8217;s lungs17.
Respiratory gating is then typically accomplished by continuously and simultaneously recording a surrogate signal (designated S(t)), with the PET data during image acquisition. Using the surrogate signal acquired, PET data corresponding to a particular respiratory phase or amplitude range (amplitude-based gating) can be selected12,13,18. Phase-based gating is performed by dividing each respiratory cycle into a fixed number of gates, as depicted in Figure 2a. Respiratory gating is then performed by selecting data acquired at a particular phase during the patient&#8217;s respiratory cycle to be used for image reconstruction. Similarly, amplitude-based gating relies on defining an amplitude range of the respiratory signal, as shown in Figure 2b. When the value of the respiratory signal falls within the set amplitude range, the corresponding PET listmode data will be used for image reconstruction. For retrospective gating approaches, all data is collected and re-binning of the PET data is performed after image acquisition. Although prospective respiratory gating methods use the same concepts as retrospective gating approaches for re-binning of PET data, these methods rely on collecting data prospectively during image acquisition. When a sufficient amount of PET data is collected, image acquisition will be finalized. The difficulty of such prospective and retrospective gating approaches is maintaining acceptable image quality without significantly prolonging image acquisition times when irregular breathing occurs13. In this regard, phase-based respiratory gating methods are particularly sensitive to irregular breathing patterns13,19, where significant amounts of PET data can be discarded due to rejection of inappropriate triggers, resulting in considerable reduction of image quality or unacceptable lengthening of image acquisition time. Additionally, when inappropriate triggers are accepted, the performance of the respiratory gating algorithm and thereby the effectiveness of motion rejection from the PET images can be reduced due to the fact that respiratory gates are defined at different phases of the respiratory cycle, as depicted in Figure 2a. Indeed, it has been reported that amplitude-based respiratory gating is more stable than phase-based approaches in case of irregularities in the respiratory signal13. Though amplitude-based respiratory gating algorithms are more robust in the presence of irregular breathing frequencies, these algorithms are more sensitive to baseline drifting of the respiratory signal. Drifting of the baseline signal can occur due to numerous reasons when the patient&#8217;s muscle tension (i.e., transition of a patient into a more relaxed state during image acquisition) or breathing pattern changes. In order to prevent such baseline drifting of the signal, care should be taken to securely attach tracking sensors to the patient and perform regular monitoring of the respiratory signal.
Although these problems are known, traditional respiratory gating algorithms only allow limited control over image quality and usually require significant lengthening of image acquisition time or increased amounts of radiotracer to be administered to the patient. These factors resulted in limited adoption of such protocols in clinical routine. In order to circumvent these problems related to the variable quality of the respiratory gated images , a specific type of amplitude-based gating algorithm, also known as optimal respiratory gating (ORG), has been proposed18. Respiratory gating with ORG permits the user to specify image quality of the respiratory gated images by providing a duty cycle as input to the algorithm. The duty cycle is defined as a percentage of the acquired PET list-mode data that is used for image reconstruction. In contrast to many other respiratory gating algorithms, this concept permits the user to directly determine image quality of the reconstructed PET images. Based on the duty cycle specified, an optimal amplitude range is calculated, which takes the specific characteristics of the entire respiratory surrogate signal into account18. The optimal amplitude range for a specific duty cycle will be calculated by starting with a selection of different values for the lower amplitude limit, designated (L), of the respiratory signal. For each selected lower limit, the upper amplitude limit, designated (U), is adjusted in such a way that the sum of the selected PET data, defined as data acquired when the respiratory signal falls within the amplitude range (L&#60;S(t)&#60;U), is equal to the specified duty cycle. For example, for a duty cycle of 50% and six minutes of acquired PET listmode data, the amplitude range is adapted to include three minutes (50%) of PET data. The optimal amplitude range (W) is defined as the smallest amplitude range used for respiratory gating that still contains the required amount of PET data (i.e., ArgMax([U-L])), as depicted in Figure 2c12. Thus, by specifying the duty cycle, the user makes a trade-off between the amount of noise and the degree of residual motion residing in the ORG PET images. Lowering the duty cycle will increase the amount of noise, though this will also reduce the amount of residual motion in the PET images (and vice versa). Although the concepts and effects of ORG have been described in previous reports, the purpose of this manuscript is to provide clinicians with details on the specific protocols when using ORG in clinical practice. Therefore, the use of ORG in a clinical imaging protocol is described. Several practical aspects, including patient preparation, image acquisition and reconstruction protocols will be provided. Furthermore, the manuscript will cover the user interface of the ORG software and specific choices that can be made when performing respiratory gating during PET imaging. Lastly, the effect of ORG on lesion detectability and image quantification, as shown in previous studies, are discussed.

<table>
	<tbody>
		<tr>
			<td>Sensor Port, sensor, black box, wave deck, elastic band, load cell sensor (complete set)</td>
			<td>anzai medical co.</td>
			<td>respiratory gating system AZ-733V</td>
			<td>http://www.anzai-med.co.jp/en/product/item/az733v</td>
		</tr>
	</tbody>
</table>

management of respiratory motion artefacts in 18f-fluorodeoxyglucose positron emission tomography using an amplitude-based optimal respiratory gating algorithm

Positron emission tomography (PET) combined with X-ray computed tomography (CT) is an important molecular imaging platform that is required for accurate diagnosis and clinical staging of a variety of diseases. The advantage of PET imaging is the ability to visualize and quantify a myriad of biological processes in vivo with high sensitivity and accuracy. However, there are multiple factors that determine image quality and quantitative accuracy of PET images. One of the foremost factors influencing image quality in PET imaging of the thorax and upper abdomen is respiratory motion, resulting in respiration-induced motion blurring of anatomical structures. Correction of these artefacts is required for providing optimal image quality and quantitative accuracy of PET images.
Several respiratory gating techniques have been developed, typically relying on acquisition of a respiratory signal simultaneously with PET data. Based on the respiratory signal acquired, PET data is selected for reconstruction of a motion-free image. Although these methods have been shown to effectively remove respiratory motion artefacts from PET images, the performance is dependent on the quality of the respiratory signal being acquired. In this study, the use of an amplitude-based optimal respiratory gating (ORG) algorithm is discussed. In contrast to many other respiratory gating algorithms, ORG permits the user to have control over image quality versus the amount of rejected motion in the reconstructed PET images. This is achieved by calculating an optimal amplitude range based on the acquired surrogate signal and a user-specified duty cycle (the percentage of PET data used for image reconstruction). The optimal amplitude range is defined as the smallest amplitude range still containing the amount of PET data required for image reconstruction. It was shown that ORG results in effective removal of respiration-induced image blurring in PET imaging of the thorax and upper abdomen, resulting in improved image quality and quantitative accuracy.

The use of ORG in PET results in an overall reduction of respiratory-induced blurring of the images. For example, in a clinical evaluation of patients with non-small cell lung cancer (NSCLC), ORG resulted in detection of more pulmonary lesions and hilar/mediastinal lymph nodes20. This is readily demonstrated in Figure 8 and Figure 9, showing non-gated and ORG PET images of patients with NSCLC.
In particular, OR...

Watch this Scientific Journal Video about Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorith

Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm

Amplitude-based optimal respiratory gating (ORG) effectively removes respiratory-induced motion blurring from clinical 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images. Correction of FDG-PET images for these respiratory motion artefacts improves image quality, diagnostic and quantitative accuracy. Removal of respiratory motion artefacts is important for adequate clinical management of patients using PET.

Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm

Positron emission tomography (PET) combined with X-ray computed tomography (CT) is an important molecular imaging platform that is required for accurate ...

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5.4K Views.  Leiden University Medical Centre. Amplitude-based optimal respiratory gating (ORG) effectively removes respiratory-induced motion blurring from clinical 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images. Correction of FDG-PET images for these respiratory motion artefacts improves image quality, diagnostic and quantitative accuracy. Removal of respiratory motion artefacts is important for adequate clinical management of patients using PET.

Video: Management of Respiratory Motion Artefacts in 18F-fluorodeoxyglucose Positron Emission Tomography using an Amplitude-Based Optimal Respiratory Gating Algorithm

Determining the Optimal Inhibitory Frequency for Cancerous Cells Using Tumor Treating Fields (TTFields)

Tumor Treating Fields (TTFields) are an effective treatment modality delivered via the continuous, noninvasive application of low-intensity (1-3 V/cm), alternating electric fields in the frequency range of several hundred kHz. The study of TTFields in tissue culture is carried out using the TTFields in vitro application system, which allows for the application of electric fields of varying frequencies and intensities to ceramic Petri dishes with a high dielectric constant (&#400; &#62; 5,000). Cancerous cell lines plated on coverslips at the bottom of the ceramic Petri dishes are subjected to TTFields delivered in two orthogonal directions at various frequencies to facilitate treatment outcome tests, such as cell counts and clonogenic assays. The results presented in this report demonstrate that the optimal frequency of the TTFields with respect to both cell counts and clonogenic assays is 200 kHz for both ovarian and glioma cells.

Determining the Optimal Inhibitory Frequency for Cancerous Cells Using Tumor Treating Fields TTFields

Tumor Treating Fields (TTFields) are an effective anti-tumor treatment modality delivered via the continuous, noninvasive application of low-intensity, intermediate-frequency, alternating electric fields. TTFields application to cell lines using a TTFields in vitro application system allows for the determination of the optimal frequency that leads to the highest reduction in cell counts.

Tumor Treating Fields (TTFields) are an effective treatment modality delivered via the continuous, noninvasive application of low-intensity (1-3 V/cm), ...

Multimodal Bioluminescent and Positronic-emission Tomography/Computational Tomography Imaging of Multiple Myeloma Bone Marrow Xenografts in NOG Mice

Multiple myeloma (MM) tumors engraft in the bone marrow (BM) and their survival and progression are dependent upon complex molecular and cellular interactions that exist within this microenvironment. Yet the BM microenvironment cannot be easily replicated in vitro, which potentially limits the physiologic relevance of many in vitro and ex vivo experimental models. These issues can be overcome by utilizing a xenograft model in which luciferase (LUC)-transfected 8226 MM cells will specifically engraft in the mouse skeleton. When these mice are given the appropriate substrate, D-luciferin, the effects of therapy on tumor growth and survival can be analyzed by measuring changes in the bioluminescent images (BLI) produced by the tumors in vivo. This BLI data combined with positronic-emission tomography/computational tomography (PET/CT) analysis using the metabolic marker 2-deoxy-2-(18F)fluoro-D-glucose (18F-FDG) is used to monitor changes in tumor metabolism over time. These imaging platforms allow for multiple noninvasive measurements within the tumor/BM microenvironment.

Here we use bioluminescent, X-ray, and positron-emission tomography/computed tomography imaging to study how inhibiting mTOR activity impacts bone marrow-engrafted myeloma tumors in a xenograft model. This allows for physiologically relevant, non-invasive, and multimodal analyses of the anti-myeloma effect of therapies targeting bone marrow-engrafted myeloma tumors in vivo.

Multiple myeloma (MM) tumors engraft in the bone marrow (BM) and their survival and progression are dependent upon complex molecular and cellular ...

Establishment and Characterization of Three Afatinib-resistant Lung Adenocarcinoma PC-9 Cell Lines Developed with Increasing Doses of Afatinib

Acquired resistance to molecular target inhibitors is a severe problem in cancer therapy. Lung cancer remains the leading cause of cancer-related death in most countries. The discovery of "oncogenic driver mutations," such as epidermal growth factor receptor (EGFR)-activating mutations, and subsequent development of molecular targeted agents of EGFR tyrosine kinase inhibitors (TKIs) (gefitinib, erlotinib, afatinib, dacomitinib, and osimertinib) have dramatically altered lung cancer treatment in recent decades. However, these drugs are still not effective in patients with non-small cell lung cancer (NSCLC) carrying EGFR-activating mutations. Following acquired resistance, the systemic progression of NSCLC remains a significant obstacle in treating patients with EGFR mutation-positive NSCLC. Here, we present a stepwise dose escalation method for establishing three independent acquired afatinib-resistant cell lines from NSCLC PC-9 cells harboring EGFR-activating mutations of 15-base pair deletions in EGFR exon 19. Methods for characterizing the three independent afatinib-resistance cell lines are briefly presented. The acquired resistance mechanisms to EGFR TKIs are heterogeneous. Therefore, multiple cell lines with acquired resistance to EGFR-TKIs must be examined. Ten to twelve months are required to obtain cell lines with acquired resistance using this stepwise dose escalation approach. The discovery of novel acquired resistance mechanisms will contribute to the development of more effective and safe therapeutic strategies.

A method for establishing afatinib-resistance cell lines from lung adenocarcinoma PC-9 cells was developed, and resistant cells were characterized. The resistant cells can be used to investigate epidermal growth factor receptor tyrosine kinase inhibitor-resistance mechanisms, applicable for patients with non-small cell lung cancer.

Acquired resistance to molecular target inhibitors is a severe problem in cancer therapy. Lung cancer remains the leading cause of cancer-related death in ...

Semi-automatic PD-L1 Characterization and Enumeration of Circulating Tumor Cells from Non-small Cell Lung Cancer Patients by Immunofluorescence

Circulating tumor cells (CTCs) derived from the primary tumor are shed into the bloodstream or lymphatic system. These rare cells (1&#8722;10 cells per mL of blood) warrant a poor prognosis and are correlated with shorter overall survival in several cancers (e.g., breast, prostate and colorectal). Currently, the anti-EpCAM-coated magnetic bead-based CTC capturing system is the gold standard test approved by the U.S. Food and Drug Administration (FDA) for enumerating CTCs in the bloodstream. This test is based on the use of magnetic beads coated with anti-EpCAM markers, which specifically target epithelial cancer cells. Many studies have illustrated that EpCAM is not the optimal marker for CTC detection. Indeed, CTCs are a heterogeneous subpopulation of cancer cells and are able to undergo an epithelial-to-mesenchymal transition (EMT) associated with metastatic proliferation and invasion. These CTCs are able to reduce the expression of cell surface epithelial marker EpCAM, while increasing mesenchymal markers such as vimentin. To address this technical hurdle, other isolation methods based on physical properties of CTCs have been developed. Microfluidic technologies enable a label-free approach to CTC enrichment from whole blood samples. The spiral microfluidic technology uses the inertial and Dean drag forces with continuous flow in curved channels generated within a spiral microfluidic chip. The cells are separated based on the differences in size and plasticity between normal blood cells and tumoral cells. This protocol details the different steps to characterize the programmed death-ligand 1 (PD-L1) expression of CTCs, combining a spiral microfluidic device with customizable immunofluorescence (IF) marker set.

The characterization of circulating tumor cells (CTCs) is a popular topic in translational research. This protocol describes a semi-automatic immunofluorescence (IF) assay for PD-L1 characterization and enumeration of CTCs in non-small cell lung cancer (NSCLC) patient samples.

Circulating tumor cells (CTCs) derived from the primary tumor are shed into the bloodstream or lymphatic system. These rare cells (1&#8722;10 cells per mL ...

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, depending on the cancer type. To reduce the brain metastatic tumor burden, gaps in basic and translational knowledge need to be addressed. Major challenges include a paucity of reproducible preclinical models and associated tools. Three-dimensional models of brain metastasis can yield the relevant molecular and phenotypic data used to address these needs when combined with dedicated analysis tools. Moreover, compared to murine models, organ-on-a-chip models of patient tumor cells traversing the blood brain barrier into the brain microenvironment generate results rapidly and are more interpretable with quantitative methods, thus amenable to high throughput testing. Here we describe and demonstrate the use of a novel 3D microfluidic blood brain niche (&#181;mBBN) platform where multiple elements of the niche can be cultured for an extended period (several days), fluorescently imaged by confocal microscopy, and the images reconstructed using an innovative confocal tomography technique; all aimed to understand the development of micro-metastasis and changes to the tumor micro-environment (TME) in a repeatable and quantitative manner. We demonstrate how to fabricate, seed, image, and analyze the cancer cells and TME cellular and humoral components, using this platform. Moreover, we show how artificial intelligence (AI) is used to identify the intrinsic phenotypic differences of cancer cells that are capable of transit through a model &#181;mBBN and to assign them an objective index of brain metastatic potential. The data sets generated by this method can be used to answer basic and translational questions about metastasis, the efficacy of therapeutic strategies, and the role of the TME in both.

Here, we present a protocol for preparing and culturing a blood brain barrier metastatic tumor micro-environment and then quantifying its state using confocal imaging and artificial intelligence (machine learning).

Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, ...

Dynamic Imaging of Chimeric Antigen Receptor T Cells with [18F]Tetrafluoroborate Positron Emission Tomography/Computed Tomography

T cells genetically engineered to express chimeric antigen receptors (CAR) have shown unprecedented results in pivotal clinical trials for patients with B cell malignancies or multiple myeloma (MM). However, numerous obstacles limit the efficacy and prohibit the widespread use of CAR T cell therapies due to poor trafficking and infiltration into tumor sites as well as lack of persistence in vivo. Moreover, life-threatening toxicities, such as cytokine release syndrome or neurotoxicity, are major concerns. Efficient and sensitive imaging and tracking of CAR T cells enables the evaluation of T cell trafficking, expansion, and in vivo characterization and allows the development of strategies to overcome the current limitations of CAR T cell therapy. This paper describes the methodology for incorporating the sodium iodide symporter (NIS) in CAR T cells and for CAR T cell imaging using [18F]tetrafluoroborate-positron emission tomography ([18F]TFB-PET) in preclinical models. The methods described in this protocol can be applied to other CAR constructs and target genes in addition to the ones used for this study.

Dynamic Imaging of Chimeric Antigen Receptor T Cells with [18F]Tetrafluoroborate Positron Emission Tomography/Computed Tomography

This protocol describes the methodology for non-invasively tracking T cells genetically engineered to express chimeric antigen receptors in vivo with a clinically available platform.

T cells genetically engineered to express chimeric antigen receptors (CAR) have shown unprecedented results in pivotal clinical trials for patients with B ...

Preparation of Human Tissues Embedded in Optimal Cutting Temperature Compound for Mass Spectrometry Analysis

Sphingolipids are cellular components that have well-established roles in human metabolism and disease. Mass spectrometry can be used to determine whether sphingolipids are altered in a disease and investigate whether sphingolipids can be targeted clinically. However, properly powered prospective studies that acquire tissues directly from the surgical suite can be time consuming, and technically, logistically, and administratively challenging. In contrast, retrospective studies can take advantage of cryopreserved human specimens already available, usually in large numbers, at tissue biorepositories. Other advantages of procuring tissues from biorepositories include access to information associated with the tissue specimens including histology, pathology, and in some instances clinicopathological variables, all of which can be used to examine correlations with lipidomics data. However, technical limitations related to the incompatibility of optimal cutting temperature compound (OCT) used in the cryopreservation and mass spectrometry is a technical barrier for the analysis of lipids. However, we have previously shown that OCT can be easily removed from human biorepository specimens through cycles of washes and centrifugation without altering their sphingolipid content. We have also previously established that sphingolipids in human tissues cryopreserved in OCT are stable for up to 16 years. In this report, we outline the steps and workflow to analyze sphingolipids in human tissue specimens that are embedded in OCT, including washing tissues, weighing tissues for data normalization, the extraction of lipids, preparation of samples for analysis by liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS), mass spectrometry data integration, data normalization, and data analysis.

Sphingolipids are bioactive metabolites with well-established roles in human disease. Characterizing alterations in tissues with mass-spectrometry can reveal roles in disease etiology or identify therapeutic targets. However, the OCT-compound used for cryopreservation in biorepositories interferes with mass-spectrometry. We outline methods to analyze sphingolipids in human tissues embedded in OCT with LC-ESI-MS/MS.

Sphingolipids are cellular components that have well-established roles in human metabolism and disease. Mass spectrometry can be used to determine whether ...

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

A rat glioblastoma model to mimic chemo-radiation treatment of human glioblastoma in the clinic was previously established. Similar to the clinical treatment, computed tomography (CT) and magnetic resonance imaging (MRI) were combined during the treatment-planning process. Positron emission tomography (PET) imaging was subsequently added to implement sub-volume boosting using a micro-irradiation system. However, combining three imaging modalities (CT, MRI, and PET) using a micro-irradiation system proved to be labor-intensive because multimodal imaging, treatment planning, and dose delivery have to be completed sequentially in the preclinical setting. This also results in a workflow that is more prone to human error. Therefore, a user-friendly algorithm to further optimize preclinical multimodal imaging-based radiation treatment planning was implemented. This software tool was used to evaluate the accuracy and efficiency of dose painting radiation therapy with micro-irradiation by using an in silico study design. The new methodology for dose painting radiation therapy is superior to the previously described method in terms of accuracy, time efficiency, and intra- and inter-user variability. It is also an important step towards the implementation of inverse treatment planning on micro-irradiators, where forward planning is still commonly used, in contrast to clinical systems.

Here we present a protocol to perform preclinical positron emission tomography-based radiotherapy in a rat glioblastoma model using algorithms developed in-house to optimize the accuracy and efficiency.

A rat glioblastoma model to mimic chemo-radiation treatment of human glioblastoma in the clinic was previously established. Similar to the clinical ...

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

Biobanks are key research infrastructures aimed at the collection, storage, processing, and sharing of high-quality human biological samples and associated data for research, diagnosis, and personalized medicine. The Biobank for Translational and Digital Medicine Unit at the European Institute of Oncology (IEO) is a landmark in this field. Biobanks collaborate with clinical divisions, internal and external research groups, and industry, supporting patients' treatment and scientific progress, including innovative diagnostics, biomarker discovery, and clinical trial design. Given the central role of biobanks in modern research, biobanking standard operating procedures (SOPs) should be extremely precise. SOPs and controls by certified specialists ensure the highest quality of samples for the implementation of science-based, diagnostic, prognostic, and therapeutic personalized strategies. However, despite numerous efforts to standardize and harmonize biobanks, these protocols, which follow a strict set of rules, quality controls, and guidelines based on ethical and legal principles, are not easily accessible. This paper presents the biobank standard operating procedures of a large cancer center.

Biobanks are crucial resources for biomedical research and the Biobank for Translational and Digital Medicine Unit at the European Institute of Oncology is a model in this field. Here, we provide a detailed description of biobanks' standard operating procedures for the management of different types of human biological samples.

Biobanks are key research infrastructures aimed at the collection, storage, processing, and sharing of high-quality human biological samples and ...

Mapping the Tumor Immune Landscape: An In-Depth Multiplex IHC Analysis Protocol

Multiplex Immunohistochemical Analysis of the Spatial Immune Cell Landscape of the Tumor Microenvironment

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. Multiplex immunohistochemistry is a valuable tool to visualize and identify different types of immune cells in tumor tissues while retaining its spatial information. Here we provide detailed protocols to analyze lymphocyte, myeloid, and dendritic cell populations in tissue sections. Starting from cutting formalin-fixed paraffin-embedded sections, automatic multiplex staining procedures on an automated platform, scanning of the slides on a multispectral imaging microscope, to the analysis of images using an in-house-developed machine learning algorithm ImmuNet. These protocols can be applied to a variety of tumor specimens by simply switching tumor markers to analyze immune cells in different compartments of the sample (tumor versus invasive margin) and apply nearest-neighbor analysis. This analysis is not limited to tumor samples but can also be applied to other (non-)pathogenic tissues. Improvements to the equipment and workflow over the past few years have significantly shortened throughput times, which facilitates the future application of this procedure in the diagnostic setting.

Author Spotlight: Unlocking Insights into the Immune Cell Landscape of Tumors

This protocol describes in detail how immune cell characterization of the tumor microenvironment using multiplex immunohistochemistry is carried out.

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. ...