Computed Tomography - Science method

IV contrast is the medication most commonly used in the Computed Tomography (CT) field of Radiology. Some of the common norma side effects that subside are:

Warm/hot feeling throughout the body, the need to micturate, and a metallic taste in the mouth.

1- What is the reason for the importance of synthetic CT image generating (Due to the low radiation dose in new devices)? 2- What is the pros for using the UNet model compared to other deep learning models (Due to the need to data augmentation to reduce the error)? 3- MR and CT images are complementary. Therefore, it is not possible to expect to produce a flawless image and it is not medically safe.

I want to apply neural network on kidney stones images (whether its CT images or ultrasound) to determine whether the kidney has stones or not.

Hello,

I'm relatively new to qPCR and have been utilizing a manufacturer's analysis software for my experiments, including one-way ANOVA for statistical analysis. However, I've encountered a discrepancy when manually conducting the same statistical analysis using CT values imported from the software (because i'd like to conduct some post-hoc tests too). Specifically, I've noticed that genes with higher CT values appear to be more expressed when considering dCt and ddCt values calculated within the app. Could you tell me why this difference occurs, especially given my beginner level of experience with qPCR?

What are some key radiographic findings indicative of severe TBI on CT imaging?

Hi,

I am looking for an open-source tool to generate maps of cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) from raw CT perfusion data.

I found some tools to process MRI data and an article ( ), which describes an implementation in R, but I cannot find the GitHub repo (SethLirette/CTP) mentioned there.

Do you know any tools?

Thanks a lot.

Please help to decide MS research tooic on advance MRI and CT

CT slice sensitivity profiles

.,.

1. As I navigate through the complexities of miRNA expression analysis using qPCR, my study involves a panel of 20 plates, each containing 96 wells—18 dedicated to patient samples and 2 for controls.

In categorizing my samples into newly diagnosed lymphoma/leukemia, those in remission, and those exhibiting resistance to treatment, I aim to calculate essential parameters such as ΔCT, ΔΔCT, and fold change. Is it appropriate to determine the average CT values for each subgroup to obtain a representative measure of miRNA expression within these distinct clinical states? keep in mind each group contain 3 samples from different individuals. Also is't acceptable to take multiple reference genes and take average of them for normalization?

Additionally, I encounter undetermined CT values; what would be the most judicious approach to handle these values? Should I assign them as 35?

Similarly, CT values exceeding 35 pose a challenge. How can I establish thresholds for further analysis in order to maintain data accuracy? because I cant delete any thing from genes as they are panel of miRNA

Moving into the statistical analysis phase, which methods, like ANOVA or t-tests, would be most effective in discerning significant differences between the categories of my samples?

Finally, in presenting my findings, how can I ensure clarity and transparency, incorporating well-organized tables and figures to visually convey the intricate dynamics of miRNA expression?

Moreover, how should I adeptly discuss the biological implications of my results while addressing potential limitations in my study?"

It's worth noting that the source of my samples is plasma, and they are derived from patients with hematological malignancies at various stages of the disease. Furthermore, each sample has been processed only once without any technical repeats.

Hello!!

Can anyone tell what could be the reason to get completely opposite Cts value in 2 different qPCR with same qPCR components?

I was testing a certain primer on different tissues, first time i TurboDNAse treated on 1ug of extracted RNA then made 10ul of CDNA with 0.5ug treated RNA and run qPCR 10ul of reaction

I got CT values pretty high (28-38) except in one tissue where it was around 22Ct.

Second time i wanted to run with reference gene, so i remade cDNA with 0.5ug but with 20ul of cDNA reaction and ran with a bit different cycling conditions.

And i got pretty low CT around 8-12 except the same tissue which had 22 Ct in previous run had Ct 33. So, it was just opposite results.

Can anyone has any idea why it can be?

Regards

Im doing a qpcr for genotyping ERCC1 rs11615, now Im in a middle of optimization of Probe ERCC1 wild type, with 2 confirmed sample (WT and heterozygous sample).

and the result, Ive got a big CT value (more than 38) in WT sample, and no ct in every heterozygous sample. what does it mean? and is that valid result or I have an error in doing a lab skill?

Thankyou

Can I get the limit of detection just with CT value in qPCR? I dont have concentration neither pfu

Thanks

How can machine and deep learning models be integrated with medical imaging technologies, such as MRI, CT, and PET scans, to improve brain tumor detection and classification?

As it is known, the potential tube voltage of the CT scanner is equivalent to the maximum energy of the produced photons, but it is not equivalent to the effective energy of the photons beam. Theoretically, effective energy = 1/2 to 1/3 of the maximum energy (or kVp). Furthermore, it varies from one CT modality to another and differs when exposure parameters are changed.

So, how could the effective energy be determined practically and precisely?

Thanks

Hi! Normally we process our PCR results for fold change in Excel by calculating delta CT, delta delta CT and finally 2^-delta delta CT. My question is, can it be done in Graphpad Prism in a simple way. If yes then how can it be done?

So I was running an RT-qPCR, but as you can see from the attachment some of my technical replicate triplets have CT values that vary by 1 (e.g. 26.16, 25.88, 25.14), leading to standard deviation greater than 0.5.

What to do then? Can I still keep the good results and re-run the problem ones on a new plate with the same housekeeping gene? I have made aliquots of the same samples and primers that I can use.

Also, any advice on how to prevent CT value variation in replicates. This is probably a pipetting error, right? As an inexperienced undergrad I spent 3 hours making this plate ;(

I am looking for large data sets of medical imaging, mostly related to neurology. Specifically, a wide array of CT, MRI, diffusion, CTA, PE, and the like. I was wondering if anyone can share some companies they may be aware of that sell such datasets?

I have some difficulties in finding a good number of DICOM files for SSM...

Dear CT experts,

i need to estimate the expected equivalent dose to the eye lens for a CT head scan.

The scanner provides me with the CTDI and DLP values, but I couldn't find so far a comprehensive description with approximated conversion formulas to estimate the eye dose. Any help is appreciated.

Thanks in advance, Christoph

5-min? 10-min? more?

I tried doing a qpcr analysis after the whole process I got no Ct value everything, washing negative on the analysis table.

Hi All,

I have the results of both qPCR CT values and RNA-seq TPM values. Now that I have 2 sets of data, is it proper to compare expression fold change (2^ of delta delta CT) with log2 of TPM values?

Thanks in advance,

Selim Rozyyev

#qPCR, #RNA-sequence analysis, #TPM.

I have been doing some qPCRs on bacterial genomic DNA. I am using 16S as my "housekeeping gene". My sample of interest, however, yield a lower CT value.

I am trying to figure out how to overcome this issue.

Should I redesign 16S primers?

Is there any other "housekeeping gene" for bacteria?

Should I send my samples to genome sequencing?

I am looking for CT datasets for any type of artifacts (Beam hardening, Scatter, Metal, Ring,...) for ( Brain- Head & Neck,...)

I know that in LighterCycler 480 system, we can use Absolute quantification/fixed points methods and then set a reasonable noise band to estimate the CT values.

My workmate told me to use this analysis method in repeating her work, however, the qPCR machine in our lab is Applied Biosystems ViiA ™ 7 Real-Time PCR System. And I really can not find out how to set the noise band or apply this method.

Thank you so much for your attention and advices!

Dear colleague

I evaluate MTF in Matlab through Edge Spread Function and Point Spread Function for computed tomography scanner but there is  a question and I would be grateful if you guided me through this.

How could I convert the x axis from distance (mm) to spatial frequency (1/mm)?

Best Regards

Faeze

The camera trap photos show the ambient temperature in the image, but it looks that the info it's not in the EXIF data

Rectal GIST is relatively rare, and no endoscopy image and CT/MRI shows suspicion for GIST rather than particular characteristic.

We have performed an EUS biopsy, but it doesn't yield a definitive diagnosis. Just spindle cell. And it is not resectable >5cm.

What would your advice be?

I am wondering if the protocol of pelvis examination for obese patient should change. instead of them been x-rayed which radiation dose will sometime be equal or more than radiation dose for CT of same with higher details.

According to my view, even the mere opening of a drawer or a cupboard is already damaging to cultural remains. The shock of opening a drawer, the changing environment between the inside and the outside of a drawer, as well as a sudden light that falls on an artifact that has been in the dark is damaging to any item, especially to parchment, papyrus and paper.

When it comes to 'taking a sample' needed for applying a analytical technique to an artifact, one can only speak of less and more destructive, because destructive it is.

For example in Neutron Activation and Petrography, one needs either an amount of 80 mg of pottery powder or a thin-section before submitting the sample either as powder or as a pellet to a nuclear reactor or to a glass slide to be looked at under a microscope.

I think that the formula "non-destructive sampling technique" was invented by scientists to obtain samples they needed from a curator or conservator. I, therefore, suggest to omit the word "non-destructive" from the Cultural Heritage vocabulary.

I used Trizol method to extract cellular RNA, and A260/A280 was always around 2.1. The RT reagent of TAKARA and the qPCR reagent of TAKARA were used. The experimental steps were all in accordance with the reagent instructions, and the Ct value of the internal reference gene (GAPDH) of the qPCR was always around 30.

Later, it was suspected that RT was the problem, but the CT value of three batches of RT reagent was still around 30. I also verified that my qPCR reagent and primer were no problem with the cDNA obtained after reverse transcription experiment by others, and the CT value was 15.

So it should be my RT and the previous extraction operation may have problems.

So I changed a very clean experimental environment to extract RNA, and the chloroform，isopropyl alcohol and ethanol used in the extraction process of Trizol were also changed into brand new ones. As a result, the Ct value of the internal reference was changed to about 27, which was still too large.

Could you give me some advice? What else could go wrong, so that the Ct value is more than 10 cycles larger than the normal value? I can be sure that I did not add the wrong reagent in each step, because I have repeatedly checked it.

Please please please help me! ! ! I've been stuck in this RT-qPCR experiment for nearly two months.

Hello,

If you are aware of any available codes for material decomposition in Spectral CT, please share them.

Thanks in advance!

U

Hello everyone,

I am currently doing a medical image processing project. I have a dataset with 300 CT images from each person. I want to determine whether the subject is patient or not. So I need to decide based on all CT images from each person. Which deep learning algorithm can be used for this goal? Is conv-lstm a good choice?

Thanks in advanced

Hello,

I have extracted RNA from the Intestinal Enteroid Cell Line and have measured the expression of multiple genes using RT-qPCR. I tested two housekeeping genes GAPDH and ACTBR both showed good CT values: 18 and 19 *mean values. However, I recently measured their expression using the same primers and dilution factors done in the previous experiment. It was conducted on FH74 cells (Premature infant intestinal cells) However, this time CT values for GAPDH were ~30 and ACTBR were ~28. So it appears that there is expression but not as great as the enteroids. Is it possible that the difference in cell lines would generate that much of a difference for housekeeping genes?

P.S. RNA yield and cDNA yield were higher for the FH74 cells

I plan on rerunning the experiment with higher concentration of primers. To try and trouble shoot the issue. I was hoping to hear your thoughts on the discrepancy of CT values for the house keeping genes.

I read some .dcm meta data file and I think there is no field point out Dual-energy CT or Conventional CT.

Not sure how the value data is convert to material ? Is that using HU convert formulas ?

Thanks

Which is the better option for performing radiomics analysis on CT images? Should radiomics features be extracted directly from CT images with HU values, or should the CT images be converted to ED maps first before extracting features?

The reason I am asking this question is: although there are many great pieces of research looked into the repeatability and reproducibility of radiomics features based on CTs, including test-retest, intra-, and inter- CT scans, however, I found that few of them talked about whether they calculated the features based on HU images or ED images. So I am quite curious, for instance, if we want to calculate the radiomics feature reproducibility between different CT scanners, in order to eliminate the potential difference from the scanner's physical setting (such as energy, phantom setup error, etc..), which method is more convincing and fair?

If this is the gene NDRG4 of Controls range:

Positive 32-38

Negative undertermined or >=39

NTC undertermined or >=39

The results are inconsistent. Which result will you be confident? as this test rely with a ratio to other gene result. the combination result calculated in the system and interpret as "Positive/Negative"

1st result: 37.26 CT (POSITIVE)

*RE-PCR in the same batch with 3 criteria:

3rd result: we add duplicate template 39.34 (NEGATIVE)

4th result: 4fold dilution 37.34 (POSITIVE)

*FAM (BLUE) is the NDRG4 gene

Please kindly refer to the photo, Thanks.

For me, I'll release the 1st valid result as negative. Please correct me.

Regards,

Mercy

Which software do you recommend for analyzing computed tomography images?

The project is about bird brains so it involves measurements and anatomical reconstructions. I have heard about Avizo, Mimics and SlicerMorph. Which do you suggest and why?

Thank you all in advance.

Hello,

I'm currently looking to segment some CT data with the Dragonfly software. However, the reconstructed data I received is in the .vol file format, which I cannot import/open with all the segmentation programs I use. I am now looking for a program to slice up the .vol files into .TIFF files and start my segmentation from there. Does anyone know a way to convert .vol files like that? Or is anyone aware of freeware to segment .vol files?

I am measuring the gene expression of my target gene DDX43. I took 2.5 ul of cDNA for Q-PCR. I am using SYBR GREEN for my q-PCR. The concentrations of RNA for most samples were 20-60 ng/ul.

The CT value for housekeeping gene hypoxanthine phosphoribosyl transferase 1 (HPRT1) is around 32-36 and CT value for for DDX43 with all samples were"undetermined". When I search in expression atlas for my target gene. I find it below cutoff in the tissue I used for RNA extraction.

Can I add up to 5ul of my samples in running q-PCR? or this result is consistent with below cutoff expression which means it is undetected so undetermined in qPCR?

I am coming from the background of Computer Science and now I am doing Phd. in eduaction. I want to connect my core subject computer science with the subject eduaction. I want to do a survey study on the topic Computational Thinking (CT)and Digital Competence (DC). Here I want to work on the relationship between CT and DC. I eagerly need your help and your valuable suggestion so that I can forward my work.

I am working on rtPCR for different primers and different cDNA samples as a duplicate to confirm the results. However, I am suffering to make the duplicate has the same or close CT value. In general, the difference between the duplicate is more than 3, and sometimes the difference in CT value reaches more than 8. While preparing the primers, diluted cDNA, and master mix the microtubes placed on ice, I couldn't find the reason for the differences between the CTs for wells that have the same primes and the same cDNA sample.

I can find very little in the literature about the use of CT for examining slide mounted specimens. This is obviously very important because of the number of slide mounted type specimens out there. Confocal is often not effective for examining slide mounted type specimens because of autofluorescence and bleaching. Is CT simply no good for slide mounted specimens, or this a neglected field of research. I have little idea as my background is largely conventional microscopy and confocal. And if anyone does know of any literature on this topic, can they please point me to it. Thanks very much in advance.

Hi everyone,

I'm looking for a free cardiovascular image dataset of any imaging modality (MRI, CT, OCT, SPECT, ...), I will use it for classification and detection.

Thank you in advance.

I understand that cycle threshold or CT value is an important determinant for secondary transmission of cases, whereas it is not associated with severity or infection. I need others opinion about it.

I am planning to compare CT values of two population set during Delta and Omicron surge. General overview would should a difference but need to apply statistical tool.

I have to check the radiotherapy plan and dosimetry distribution for a CT image that I have generated and need to compare it with other plan.

Is there any free software to compute the radiotherapy plan using a CT volume?

Please suggest one.

I am a new researcher in the X-fluorescence Computed Tomography field. I am doing the attenuation correction of the XFCT imaging system and I am confused with something.

As we know that while doing the attenuation correction for emission tomography, we need to convert the attenuation coefficient value for the energy of 511 KeV by using some Bi/Trilinear method! That means :

""Transmission CT energy ( attenuation coefficient value) ==> Emission CT energy ( attenuation coefficient value) "".

As it is known XFCT has two parts: Fluorescent Excitation ( Transmission) and Fluorescent Emission. I have Attenuation co-efficient values for 30KeV energy.

What will be the process for converting the attenuation co-efficient values for XFCT? Would I need to convert the attenuation co-efficient value two times ( for transmission and emission) ?

I am a bit confused about this problem!

I would like to ask anesthesiologists or clinicians who have experienced anesthesia mumps. Was there a case in which the swelling of the parotid gland is associated with a retrograde insufflation of air in the Stensen’s duct and the parotid gland (pneumoparotid)? If you know the literature on anesthesia mumps confirmed by CT as pneumoparotid, I would appreciate it if you could let me know.

I am looking for a COVID-19 image (CT or x-ray) dataset that has additional information such as age, gender, and clinical information such as co or previous morbidities of the patients. Any link would be appreciated.

Am working on femur bone biomechanics.I do have assigned the material properties to the geometry model generated from the CT data in mimics. But couldn't able to do the same for external meshed body(Means the same geometry after initiating the fracture, virtual surgery with implants in some other software). I just want assign the materials of femur for surgery models. Please let me know with possible solution.

This happens both in mouse and rats samples. After perfusion with saline we use to perfuse with Microfil. We then store the samples as required and acquire by CT. After reconstruction the vascular tree is usually perfectly represented as a continuum but sometimes we detect some kind of interruptions along the vessel (white vessel profile, then a dark void and then again the white vessel profile). What are these areas of void due to? How could they be overcome considering that perfusion quality is almost the same all the time? Thank you.

Donor-Bridge-Acceptor (DBA) or Donor-Acceptor (DA) architectures are widely employed protocols to achieve Charge Transfer (CT) in organic semiconductors. Lower Exciton Binding energies (EBE) are required to attain higher efficiencies in Solar Cells.

By exploiting the dipole moment changes we design Donor-Electret-Acceptor moieties which enhances hole and electron distance upon excitation favoring higher CT and CT distance, reducing EBE, plausibly enhancing solar cell efficiencies in the following article.

Hello,

we using the same amount of RNA for cDNA synthesis, and we are sure there are no hand mistakes for doing qPCR. using both TaqMan and SYBER green master mix, the qPCR instrumentt name is Quantstudio3.

reaction size is 20 ul, for information, the instrument is brand new and was calibrated one month before

CT values were 10.45,10.67,10.47 in control and 12.45,12.67,12.47 in Treated gp

the CT values of the reference should be close and the difference should be no more than 0.5, but we see the difference is around 2 CT values.

we repeat the experiment more than 4 times we still face this problem if anyone has a suggestion it will be grateful to give advice

Could You please give me a link to a source where I can get (for free) a data set of contrasted CT images of an abdominal aortic aneurism in DICOM (or which?) format manually segmented by a specialist? Even a normal abdominal aorta will fit.

Hello;

I know how to train image classifiers (CNN) for classification of single cross-sectional CT or MRI image. However, I don't know how to send all images from one patient to the model. I need to stack all images from a patients, add the label, and send them to the model to be used for training. It should be a sort of 3D CNN.

Anybody knows how to do it?

Thank you very much.

I have, extinction ratio (ER)=25.6dB ; Crosstalk (CT)= <-18db, Insertion/Excess loss(IL)= 0.51 (0.04)db. How to calculate bandwidth for multiplexer?

When we perform housekeeping genes (such as GADPH) for baseline comparison control in RT-PCR analysis, the degrees of CT values were found to vary a lot between different animals (in our case, 5 control rats) from 17-22. But we have to choose one CT value for baseline comparison of other genes of interest. Do anyone encounter the same condition and what is the solution?

Thanks a lot in advance!

I am looking for a CT dataset of bone fractures in different bones to reconstruct 3D models. I am using these models for developing automated design algorithms. If there is a database of already existing 3D models of bone fractures, that would be useful as well.

Changing the HU values of the DICOM CBCT image

Hello everyone,

I have a DICOM image from CBCT and a DICOM image from CT. The two images describe the same object, but each image has different gray values (HU values).

The goal is to overlay the CBCT image with CT image. I.e. plannings CT image is subtracted with CBCT to see if the two images are completely transferred.

The range of HU values for CBCT image is between 0 and 1000.

The range of HU values for the Plannings CT image is between 0 and 800.

Now I wanted to reduce HU values of CBCT image by 200 HU values so that HU values of CBCT correspond to HU values of Plannings CT.

My question is the following, Is it allowed to change or manpulate the HU values of DICIOM.

As far as I know the HU values describe physical cause.

I've been stuck with this for a week, is there any other way to make the two CTs have the same HU values?

Thank you for any answer

We have many cases with normal D-dimer with the normal CT pulmonary angiography.

I am working on developing a real-time PCR assay but I don't know how to set up and/or define the range for CT values which could help me in lower and upper CT values for determining the positive and negative samples of the experiment.

For my thesis I'm in need of finding information on incorrect fitting patient specific surgical guides due to the partial volume effect in the segmentation of the taken CT data for a osteotomy procedure. Can anyone help me out? All tips are welcome!

Thanks and best regards,

Richard

Hello,

Can someone with experience in CT image analysis help me to understand the elements of the pictures. It is a plate thermoformed from waste like ABS and PMMA polymers and fiberglass. I need to know what black dots represent, white particles, and also if fiberglass is visible.

Thank you!

Hello Dear Colleagues!

We are trying to determine CTDIvol and DLP from CT scans using CT Expo v 2.7.

However, we need to enter the scan length (in cm) into CT Expo. Does anyone know how to calculate the scan length using the information in the DICOM header?

The equipment is old, we only have the following tags:

Single Collimation Width (0018,9306)

SliceLocation (0020,1041)

SliceThickness (0018,0050)

And in addition there is no information in the

SpacingBetweenSlices (0018,0088) tag.

Can anyone help us?

Best regards

Need CT image database for Normal Pneumonia.

I knew tools for dicom format but I want for nifti, is there?

thanks

I don't have enough cDNA, so I need to dilute 1: 3. The problem is that I can't figure out what calculations I should do when obtaining the CT to calculate the DDCt. Anyone who can help me with this? Thank you.

I am looking for CT image dataset for COVID-19 that have annotated the infection areas with severity score.

Please, can you help to find such dataset.?

Thanks in advance

In this regard, I'm looking for a CT/MRI dataset required to train a CNN model for medical image segmentation.

Currently, I'm working on a paper that deals with CT image classification. I am using two open-source datasets among which, I can't find any relevant paper on the Harvard Dataverse CT image dataset (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi%3A10.7910%2FDVN%2FSZDUQX) to compare with the results of our paper.

Can you please suggest a few published papers?

Thanks :)

Question about expanding the linear range for my standard curve dilution in Taqman probe qPCR? I am doing a 4-fold serial dilution using the Taqman probe assay to generate a standard curve dilution, and it was a multiplex qPCR. And I am trying to use the reagent and primers concentration from a paper, and the amount of concentration for the primers and reagents I used is the same as the paper. The sample I used Nanodrop result is shown attached. I am using 4-fold dilution (3ng-0.01ng), 1800 copies of DNA, and 2 copies. The paper uses plasmid 3.8kb length(10pg-1fg) 5-point dilution 10^6 copies DNA to 10^1 copies. And They are using 10-fold dilution. By looking at their standard dilution plot, in the high end (low CT, high input), and compared their plot and my plot, their slope looks steep in the high end, my plot looks flatten. The slope is about -3.7, and the qPCR amplification efficacy En is 88%. How to improve my standard curve in the high end makes the plot steep, improving my qPCR amplification efficacy? How to expand my linear range for my curve? I only can use the lower end (High CT, low initial input DNA amount) for now.