Dear Sibi, I am assuming that you are using the “Absolute Signal Enhancement” conversion method since for DCE CT the assumption is usually made that the signal change is proportional to the contrast agent concentration.
The proportionality factor k is dependent on many different factors and is usually not known. However, it does not need to be known as long as k is tissue independent (which also is a realistic assumption for DCE CT data) . When fitting a pharmacokinetic model based on the standard tracer-kinetic theory of linear and stationary systems, which is true for the two compartment exchange model, k scales out because it is the same for blood and tissue. Therefore, you can for example just set k = 1.0. Best wishes, Ina Von: Sibi Thirunavukkarasu [mailto:sthir...@ualberta.ca] Gesendet: Mittwoch, 23. August 2023 15:19 An: Kompan, Ina Nora <i.kom...@dkfz-heidelberg.de> Cc: mitk-users@lists.sourceforge.net Betreff: Re: [Extern] - [mitk-users] Help with DCE MR Perfusion Datafit view Thanks, Ina, that worked. I do have a follow-up question. I am trying to do a two-compartment exchange model for Blood-brain barrier permeability calculation using DCE CT. I am not able to find the concentration conversion factor K for DCE CT. Do I have to go with a reference value for this? or this can be calculated from the imaging data as well? Best Sibi On Mon, Aug 21, 2023 at 2:01 AM Kompan, Ina Nora <i.kom...@dkfz-heidelberg.de<mailto:i.kom...@dkfz-heidelberg.de>> wrote: Dear Sibi, it looks like the mask of your region of interest is (at least partially) not within the image region which is processed during the fitting. How have you created the mask? Have you generated it in MITK? If you haven’t done so yet I would recommend trying the following steps: 1) Open your 4D DCE CT image in the Data Manager. 2) Open the segmentation plugin with the DCE CT image as input and select a new segmentation (+ button). 3) In the pop-up window select “Create static segmentation”. 4) Use the segmentation tools at the bottom of the plugin to create the mask in one of the time steps (for a static segmentation the mask will be the same for all time steps). 5) The mask will appear as a sub-node of the DCE CT data in the Data Manager. To avoid confusion, you can rename the mask in the Data Manager, e.g. to “Tumor-label”. 6) If you are using a model that requires an arterial input function, you can repeat the steps for the segmentation of an AIF mask. 7) In the DCE MR Perfusion Datafit View, set the ROI mask (and AIF mask if used) as input. You can also find a detailed documentation on segmentation in MITK when you press F1 when the segmentation plugin is active (the tab of the plugin is highlighted). I hope this helps. Best wishes, Ina Von: Sibi Thirunavukkarasu [mailto:sthir...@ualberta.ca<mailto:sthir...@ualberta.ca>] Gesendet: Samstag, 19. August 2023 04:42 An: mitk-users@lists.sourceforge.net<mailto:mitk-users@lists.sourceforge.net> Betreff: [Extern] - [mitk-users] Help with DCE MR Perfusion Datafit view Dear all, I am trying to calculate blood-brain barrier permeability using DCE CT. When I try to run the DCE MR Perfusion DATA fit view using pixel-based fitting strategy, I encounter the following error. MultiOutputNaryFunctorImageFilter(000001C623DA28F0): Mask of filter is set but does not cover region of thread. Mask region: ImageRegion (000001C6119AB2C0) Dimension: 3 Index: [0, 0, 0] Size: [512, 512, 16] Thread region: ImageRegion (000000C40EDFEB70) Dimension: 3 Index: [0, 0, 0] Size: [512, 516, 1] Fitting finished. I am not sure how to proceed further to rectify this error. Best regards Sibi
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