Questions related to PET Imaging
Positron emission tomography generally shows imaging of the physiology of the tumor as well as its anatomy, which is superior. It is unique compared to other cross-sectional imaging such as computed tomography or computed tomography (CT) or computed tomography. CT scans or MRIs often can not detect changes at the cellular level if the PET scan is capable of immediate changes. Identify in patient cells.
In order to image the tumor using PET or other methods, differences in basic features established in physiological and Metabolic of tumors and normal tissues. These differences include tumor surface antigens compared to cell tissues. Generally grow and DNA precursors such as thymidine and the rate of protein synthesis in tumors often increase compared to normal tissues. transport and Mixing of various amino acids, as well as anaerobic and aerobic glucose levels, are observed in tumor cells. In a wide range of Tumor types Glucose intake increases significantly compared to healthy tissues. In a typical PET system they are separated by a lead or tungsten blade detection of random photons in one shot Match with photons detected in other shots. In the diagram below, I plotted the average positron emitted energy from several desired radionuclides. Which of these radionuclides is best for our purposes?
I have 9 positron emission tomography (PET) images of a patient, taken at different times. I want to calculate total disintegration (cumulated activity) but I don't know where to begin.
Has anyone came across this topic before? Is there a practical reference or step-by-step guide to it? What tools do I need?
Thank you for your time and attention.
I know that in List mode data the scintillating events are stored along with the time stamps of the event. I have a doubt regarding image reconstruction from the list mode data.
Is each (x,y coordinate of) photon count binned into an image matrix or are the photon counts integrated in certain time interval and treated with Anger algorithm or MLEM algorithm then binned into a image matrix? If the latter is the case then what is the value of the time interval?
If my question is not clear or wrong can anybody suggest some sources which will help me in understanding this ?
I am going to perform a longitudinal study in mice involving a radiotracer that is eluted in Ethanol in its formulation, [11C] Raclopride. The amount of Ethanol in the final product is no higher than 10%. I am planning to inject this very solution in the animal via i.v. and flush with a saline solution, but I am concerned with the final concentration of Ethanol in the organism being high enough to hinder the animal, or giving me some long-term effect on dopaminergic neurons that are undesirable in a longitudinal study.
Is there anyone that looked into this specific matter, or that can give me some references on it?
Thank you very much.
I guess we need the optical part of GATE. But how do I modify / set the physics to simulate this effect (because geant4 seems to have it already)?
I see at least 8-9 methods for doing the correction, and papers that compare their merits, but none of these papers discusses the specifics of how they did it, only mathematical formulas and algorithms. My lab already uses FSL, Freesurfer and AFNI if anyone knows an approach that would work with minimal new coding. Thanks.
There are different types of diagnostic tests for Alzheimer's disease. as far as I know, one of them is positron emission tomography (PET) scanning. what exactly does cause the sign of the disease on a PET image? what percentage of Alzheimer's disease can be diagnosed by this procedure? do prescription drugs affect these signs after we take the test again?
We have injected a radiolabeled small protein (10 kDa) to an animal model bearing positive and negative tumors. During submission process, reviewers asked for the concentration of accumulated protein in the positive tumor and... I really don't know how to do this.
I've tried with the "binding potential" formula, but we aren't in the good experimental conditions (the concentration of radiolabeled protein is too low and we have only one time point). Help!
What we know :
- Number of receptors of interest per cell : 5 × 10^5 EGFR per cell (5x10^6 cells were injected in each mouse).
- Effective specific activity of the injected proteins (mixture of labeled and unlabeled proteins): 37.0 – 53.6 MBq/nmol
- Total quantity of injected proteins: 10 nmol
- Uptake in the positive tumor 2.5h p.i. : 1.42 ± 0.18 %ID/g
- Uptake in the negative tumor 2.5h p.i. : 0.56 ± 0.10 %ID/g
- In vitro affinity of the protein for the receptor : Kd = 27 nM
I try to quantify the biodistribution via pet/ct images but I have some problems, for example I am not sure that is that ok if I apply any filter such as 3D Gaussian on SPECT or PET images?
I am working with p-mod software.
My question is whether positron emission tomography measures the binding of the radioligand to a receptor that is specifically located at the cytoplasmic membrane or to all receptors regardless where they are located in the cell. I guess it depends on the tracer physiochemical characteristics, whether it penetrates the cellular membrane or not, and on the binding site within the protein. I just need a confirmation from an expert.
I am looking for an appropriate FDG PET SUVmax threshold to use. Can anybody provide me with some ideas?
Is there an MRI package that allows you to swap out different templates for brain segmentation (using template from 17 vs 22 year old person)? brain extraction software
As you may know we can use FDG-PET scans for evaluating tumor metabolism. There is a parameter named SUV for PET images that can be used as a measure for metabolic energy evaluations. I wonder if we can use SPECT scans instead? If yes, is there any measure like SUV for SPECT as well?
A couple of radiotracers we developed (C-11 and F-18 labeled) undergo extensive metabolism (less than 10 % intact tracer after 30 min pi). However, the radiometabolites didn't cross the BBB (hence no effect on the image acquired). In biodistributions study, we were also able to block 70 % to 90 % of the binding of the radiotracers in the target organ at 30 min pi with a structurally unrelated/different and validated compound. Hence, this rules out the contribution (significant) radiometabolites on the observed retention of radioactivity in the target organs.
Here is the problem. Can this be considered a significant drawback of the radiotracers as a potential PET tracers? Could anyone give me a feedback on this (including citation will be a plus).
Any help is greatly appreciated.
hello. We want to measure the radiation dose with Nipam gel. As an imaging modality CT scan offered good results. Now there is some problems with image quality and linearity with absorbed dose when we take the image with C-arm device. dose anyone have the same experience about feasibility of using C-arm? please inform me. Thank you .
I found an equation that reads: SUV(t) = Activity concentration (t) / (Injected activity / Body weight ), which implies that the activity concentration is not decay corrected, is this true?
I do not have experience working with PET scanners for patients so I don't know if the software automatically corrects for the branching ratio of the nuclide. Most of the conventional nuclides have positron branching ratios close to 100% (18F, 11C, 68Ga) so the branching ratio does not affect the computation significantly. However, since the positron branching ratio of 64Cu is 17.6%, 5.5 mCi of 64Cu emit the same amount of 511 keV gammas as 1 mCi of 18F and in this case the computation could be off by a factor of 17.6/96.7 = 0.18. For instance if a subject is injected with 5.5 mCi of 64Cu and a lesion captures 100 %ID, the software could potentially assume that the lesion captured only 1 mCi (assuming it is 18F) and since the injected activity is 5.5 mCi 64Cu the software could assume that the %ID was 18% instead of 100%. I ask this because it seems to me that the SUV values for 64Cu and 89Zr reported in the literature are low, as if the positron branching ratio is not being considered.
I have a FDG18 brain PET data set. In order to better visualize and quantify the FDG uptake in different regions, I want to perform a statistical parametric mapping. But it seems that the SPM package requires control group to formulate the template. After searching online, it seems that neurostat/3d-ssp does not require the user defined template. But somehow, it cannot be downloaded now. So I want to know which packages you guys use to perform statistical parametric mapping without control group.
Thanks very much.
I have these set of images:
- MRI images and MRI-ac attenuation maps
- CT images and CT-ac attenuation maps
- PET reconstructed with attenuation correction maps from CT (PET-CTac)
- PET reconstructed without attenuation correction maps from CT or uncorrected PET
The images were acquired with:
PET/CT GEMINI TF TOF 16, Philips
MRI TrioTrim 3T, Siemens
The MRI-ac and CT-ac sets are co-registered to the PET images.
I want to reconstruct the PET images using the attenuation correction maps formed from the MRI images (MRI-ac). The attenuation maps from the MRI were obtained by segmenting the MRI images and assigning to the different classes/tissues their known attenuation coefficients values.
The goal is to compare both reconstructed PET images: PET-CTac and PET-MRac.
I naively changed the pixel data of the CT-ac images with those from the MRI-ac (the header files were kept identical, dicom images) and I tried to make the reconstruction using the proprietary software of the PET/CT scanner. The idea was to use the same parameters that were used to perform the reconstruction of the PET-CTac images and to have a valid point of comparison, but it did not work. The scanner does not accept these new images (MRI-ac).
So, I was wondering if someone could tell me how to perform the reconstruction of the PET images using the MRI-ac attenuation maps and the proprietary software of the PET/CT scanner or with another method/software/libraries?
Or perhaps, is there a simple method to perform attenuation correction on the uncorrected PET images using only the MRI-ac maps without making the whole process of reconstruction again?
Any insight will be helpful,
Are you a family physician or pediatrician? if yes, what would be your main reasons to request an advanced imaging test in pediatric patients?
(Please consider orthopedic cases only)
Is PET scan of any good in this?
As this is not an animal trial, I would be happy to know whether any non-invasive sensitive tool is available?
I used a general protocol using multiple regression (treshold masking 0.8, no global calculation,..). Moreover, I get the same (whole brain) cluster when I perform correlations with other behavioral tests. Has any of you experienced the same problem and found a solution to the problem?
I want to correct a FDG-PET image by using the corresponding MRI information. I tried this software SFSRR developed by Miho Shidahara et al. But it failed in the last step. The output image contained only NaN values. Anyone has an idea about this problem? Do you know any other convenient software that can do this job? Thank you in advance!
I am wondering if anyone could suggest standard databases for PET images with ground truth showing inside and outside the lesions (e.g contour or coordinate).
Are there any CT and PET dataset together with ground truth?
Does anyone happen to have (or know of) data on both features and exemplars for a particular concept combination and also for its two constituents? (e.g. feature and exemplar data on PET, feature and exemplar data on FISH, and feature and exemplar data on PET FISH?) There is lots of partial data but we are looking for a complete data set of this kind.
Many thanks in advance.
Any experience in T2* sequence of thalassaemia for detection of iron overload on the heart on toshiba MRI machine ??
Some molecules are secreted from the gastro-intestinal mucosa to the gastro-intestinal lumen, and eventually ends up in the feces. Some positron emission tomography (PET) tracers may be secreted into the GI-lumen in this fashion, and therefore potentially confound the use of these tracers for imaging cancers and other pathology in the GI-tract. I would appreciate some good references for papers or book chapters, which describe the principles and mechanisms of this type of secretion. Thanks.
Our centre using GE Discovery ST scanner with an 8-slice CT unit for PET/CT - 3D acquisition; and Philips Brightview XCT for SPECT/CT. Our images was grainy and full of scattered photon.
I'm working my way through the evidence base on decision making theory in clinical reasoning. There's obviously a myriad of models. Is anyone familiar with where current thinking lies? I'm particularly interested in making decisions using medical imaging.
Any thoughts or recommend articles would be appreciated.
It is very much operator dependent and has an impact on quantitative measurement.
I would like to know if spleen, liver, salivary glands, adrenals etc take up the tracer - i.e. if the human tracer has cross-species affinity
I am trying to do a multimodal registration. For that I am in need of CT and PET images of brain tumors. Can someone send me a list of websites where I can get them from?
Thanks in advance..
As far as I know, within several min after injection activity absorption would be in the highest value possible. What is "the" value in (Mbq/ml or mCi/ml) ?
In some papers they say dynamic SPECT provides a better contrast between normal and decreased ﬂow regions than can be obtained from static imaging. what are the other advantages,if any?
In PET imaging, anatomical expertise is essential because images are so fuzzy. I'm involved in a project where we want to automatically detect cancer lesion (for instance, lymphoma nodes) using PET/CT imaging. Lesions typically don't show up in the CT but the CT could be used for registering an anatomical model, for instance using the skeleton information, which would then be used to weed out false positives based on the location. For instance, the heart and liver show up prominently in the PET result, but there isn't any lymph nodes in either. Is there any work where an anatomical model is used in such a context? Thanks for any pointers.
K1 and k2 are cardiac kinetic parameters which define wash-in and wash-out rate in a compartmental model of the cardiac muscle. j1 and j2 are two coefficients which are related to K1 and k2. using equation Count=-C1.exp(-j1.t)+C2.exp(-j2.t) time-acitivity curve for myocardium can be plotted which shows washin and washout rate of myocardium, but as far as I know K1 and k2 are somehow different from j1 and j2.
We are comparing MR, 99mTc-tetrofosmin, and FDG in assessing viability in a day protocol.
If different isotopes (11-C, 89-Zr, 64Cu) are used to label different antibodies, can they all be used at the same time during PET imaging? Or because all of them undergo Beta+ decay and produce Gamma rays, is it not possible to distinguish between signals coming from the different probes?
When searching for a method to compare two medical images, e.g. to determine how similar they are or how much and where they differ, I came across several proposals. A simple subtraction image + width of histogram or entropy, crosscorrelation or joint histograms to name some of them. Nevertheless, I wonder if there is something like a standard method? And if not, it might be worth to discuss what could be a sensible approach.
A 46 yr old presented with a 3x2 cm lump in the upper outer quadrant, with just palpable axillary lymph nodes. PET scan done suggests a hot lesion in the breast with non FDG avid nodes in axilla, but the mediastinum has two hot nodes (1cm ) with a SUV of 5. Is this stage IV?