Patient characteristics influencing the variability of distributed parameter-based models in DCE-CT kinetic analysis.

Area of Science:

• Medical Imaging
• Radiology
• Pharmacokinetics

Background:

• Kinetic parameter variability in dynamic contrast-enhanced computed tomography (DCE-CT) can stem from model selection, implementation, or patient-specific factors.
• Understanding these influences is crucial for accurate quantitative analysis in DCE-CT studies.

Purpose of the Study:

• To assess the impact of kinetic model choice and patient-specific effects on the variability of DCE-CT kinetic parameters.
• To compare inter-model and intra-model variability for key kinetic parameters.

Main Methods:

• Utilized high signal-to-noise ratio, test-retest DCE-CT scans in 11 canine patients with sinonasal tumors.
• Assessed variability of three distributed parameter (DP)-based models using analysis of variance.
• Employed mixed-effects modeling to evaluate patient-specific effects.

Main Results:

• Inter-model variability (CVinter) was comparable to or lower than intra-model variability (CVintra) for blood flow, fractional vascular volume, and permeability-surface area product.
• Kinetic models were significantly impacted by patient characteristics, including patient size, affecting the area under the curve for arteries and tumors (P<0.05).

Conclusions:

• DP-based models showed good agreement, with similar differences observed between models and across scans.
• High variability in kinetic parameters and their sensitivity to patient size may restrict the application of certain quantitative DCE-CT analyses.