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Deconvolution assessment of splenic and splanchnic contributions to portal venous blood flow in liver cirrhosis
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10.1118/1.3582691
/content/aapm/journal/medphys/38/5/10.1118/1.3582691
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/38/5/10.1118/1.3582691

Figures

Image of FIG. 1.
FIG. 1.

Schematic representation of relative organ positions and the relationship between portal venous, splenic, and splanchnic circulation.

Image of FIG. 2.
FIG. 2.

Compartmental modeling of portal venous blood flow. (a) Block diagram of splenic and splanchnic contributions to portal blood flow. (b) Structure of the two-compartment (vascular–intersitial model) within each of the splenic and splanchnic blocks. F denotes the blood flow that supplies the vascular compartment. k 1 and k 2 refer to the exchange rates constants for influx and efflux (backflux), respectively.

Image of FIG. 3.
FIG. 3.

Results for Patient 6. (a) Outlines of the various regions-of-interests (ROIs) for sampling of the arterial (circles), portal venous (triangles) and splenic (∗) concentration-time curves. (b) Fitting of the various concentration-time curves using the proposed method. (c) Impulse residue and outflow response functions of the splenic and splanchnic pathways derived from fitting the respective concentration-time curves.

Image of FIG. 4.
FIG. 4.

Results for patient 4.

Image of FIG. 5.
FIG. 5.

Results for patient 7.

Image of FIG. 6.
FIG. 6.

Example of a Monte Carlo simulation run at SNR = 20. The aorta concentration–time curve C A(t) was obtained from patient 4.

Image of FIG. 7.
FIG. 7.

Schematic illustration of two approaches to observe a tracer experiment and the corresponding impulse response functions. Following the unit impulse input δ(t), the transit time distribution h(t) specifies the probability of tracer exit at the venous output. At any point in time, the cumulative output, represented by the content collected in the container, can be given by the integral . The fraction of tracer remaining in the system as a function of time can thus be given by the difference of this integral from unity.

Image of FIG. 8.
FIG. 8.

Results for patient 1.

Image of FIG. 9.
FIG. 9.

Results for patient 2.

Image of FIG. 10.
FIG. 10.

Results for patient 3.

Image of FIG. 11.
FIG. 11.

Results for patient 5.

Image of FIG. 12.
FIG. 12.

Results for patient 8.

Tables

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TABLE I.

Patient demographics and clinical parameters.

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TABLE II.

Splenic and splanchnic hemodynamic parameters derived from parametric deconvolution analysis. Splenic parameters are obtained by fitting of the splenic concentration–time curve while the splanchnic and PV parameters are obtained by fitting of the portal venous concentration–time curve. The empty entries for splanchnic parameters correspond to cases where the fitting of the portal vein concentration–time curves do not depend on the splanchnic parameters and therefore the splanchnic parameters cannot be estimated. These cases with empty entries for the splanchnic parameters were not included in the computation of mean and SD of the splanchnic parameters.

Generic image for table
TABLE III.

Results of Monte Carlo simulation study on the precision of the various hemodynamic parameters estimated using the proposed deconvolution procedure. Each entry represents the mean and percentage coefficient of variation (in brackets) for 1000 simulation runs.

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/content/aapm/journal/medphys/38/5/10.1118/1.3582691
2011-05-09
2014-04-16
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Deconvolution assessment of splenic and splanchnic contributions to portal venous blood flow in liver cirrhosis
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/38/5/10.1118/1.3582691
10.1118/1.3582691
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