PXMOD Implementation

Acquisition and Data Requirements

Image Data

A dynamic PET data set representing the measurements of brain activity after injection of a H₂¹⁵O bolus.

Model Preprocessing

A methodology has been implemented to automatically extract low-flow and high-flow TACs as follows:

The signals are integrated over the acquisition duration in all pixels.
A lower threshold (40% in the example below) is applied to restrict the volume-of-interest to brain.
A histogram within the threshold volume is calculated.
The C1 (ex. 5000) pixels at the lower end of the histogram are assumed to represent low-flow pixels; their average curve TAC1 is calculated. Only this GENERATED approach is supported, no manual TAC specification.
The C2 (ex. 2000) pixels at the upper end of the histogram are assumed to represent high-flow pixels; their average curve TAC2 is calculated. Only this GENERATED approach is supported, no manual TAC specification.
Then an iterative fit of Watabe's eq. (7) is performed to calculate the flows (f₁,f₂) and distribution volumes (DV₁,DV₂) of the two TACs. The resulting f₁ and DV₁ together with an assumed distribution volume DV (which must be specified by the user) are then used for the pixel-wise flow calculations by Watabe's eq. (8).

PXMOD rCBF (Watabe) Model Pre-Processing

f1	Flow in low-flow region estimated during preprocessing and subsequently used in pixel-wise calculations.
DV1	Distribution volume in low-flow region estimated during preprocessing and subsequently used in pixel-wise calculations.
f2	Flow in high-flow region estimated during preprocessing but NOT further used.
DV2	Distribution volume in high-flow region estimated during preprocessing but NOT further used.
DV	Fixed distribution volume which is assumed for each pixel-wise TAC.
Weighting	Different schemes for residual weighting in the iterative preprocessing fit.
C1 points	Number of points used for the generation of TAC1.
C2 points	Number of points used for the generation of TAC2.
Threshold	Discrimination threshold for background masking.

After preprocessing, the Watabe plot is shown on the Results panel for inspection. Note that the the integral curves can be deactivated using the check boxes to see the generated TACs.

PXMOD rCBF (Watabe) Model Pre-Processing

Important Note: Experience has shown that the results of this reference method highly depend on the iterative fit with 4 parameters. As illustrated in this example, the identifiability of the parameters is often poor, and the results may heavily depend on the starting values. In an attempt to make the method more stable, one can fix VD2 to a reasonable value such as 0.9. To this end, just deactivate the box next to VD2 .

Map Parameters

PXMOD rCBF (Watabe) Model Pre-Processing Result

f	Regional perfusion in [ml/min/100ml]. It is calculated for each pixel by a closed-form calculation (Watabe's eq. 8). Reasonable values are about 30 (white matter) and 60 (gray matter) ml/min/100ml [11].