Computing SUV PET Dicom image

Hi, is there any reference for computing SUV from PET Dicom image?(matlab/c++)

1 commentaire

Wenhui Zhang
Wenhui Zhang le 26 Jan 2021
Hi, do you know the answer now? I am quite new to this area and if you know now, could you please tell me the answer.

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Réponses (2)

Caroline Jordan
Caroline Jordan le 2 Jan 2018

0 votes

OsiriX uses the following formula:
SUV (g/ml) = Pixel value (Bq/ml) * Weight (kg) / Dose(Bq) * 1000 (g/kg)

1 commentaire

antogeo
antogeo le 8 Avr 2018
Hello, Do you maybe know if "Dose" is corrected for time of acquisition or reads the dicom field: [0018, 1074]"Radionuclide Total Dose"?

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Cata_Ray
Cata_Ray le 5 Août 2021
Modifié(e) : Cata_Ray le 16 Août 2021

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Using the formula:
The Dose should be corrected in relation to the injection and acquisition time. That information can be found in the DICOM Header and access via "dicominfo".
In this example I call the DICOM Header structure "header"
PET = %load PET imgage;
% Calculate SUV factor from DICOM header
delta_time = (str2double(header.AcquisitionTime) - str2double(header.RadiopharmaceuticalStartTime)) / 100; % [min]
half_life = header.RadionuclideHalfLife/ 60; % [min]
corrected_dose = header.RadionuclideTotalDose * exp(- delta_time * log(2) / half_life); % [Bq]
SUV_factor = (header.RescaleSlope * str2double(header.patient_weight) * 1000)/ (corrected_dose); % [g/Bq] = [] * [Kg]* 1000[g/kg] / [Bq]
% Create SUV image
PET_SUV = double(PET) * double(SUV_factor) ; %[g/ml] = [Bq/ml] * [g/Bq]

3 commentaires

Sophia Lerebours
Sophia Lerebours le 16 Août 2021
Is there a particular reason that you did not include the dose calibration factor in your calculations?
Cata_Ray
Cata_Ray le 16 Août 2021
It is not needed for this method of SUV calculation. You can see the formula at the begining of the answer.
Is there a praticular reason for you to want to use it?
Sophia Lerebours
Sophia Lerebours le 20 Août 2021
I included the dose calibration factor in my calculations becuase of the paper Shin et al., 2017. https://pubmed.ncbi.nlm.nih.gov/28551298/

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