Improving low-dose blood-brain barrier permeability quantification using sparse high-dose induced prior for Patlak model. Academic Article uri icon

Overview

abstract

  • Blood-brain barrier permeability (BBBP) measurements extracted from the perfusion computed tomography (PCT) using the Patlak model can be a valuable indicator to predict hemorrhagic transformation in patients with acute stroke. Unfortunately, the standard Patlak model based PCT requires excessive radiation exposure, which raised attention on radiation safety. Minimizing radiation dose is of high value in clinical practice but can degrade the image quality due to the introduced severe noise. The purpose of this work is to construct high quality BBBP maps from low-dose PCT data by using the brain structural similarity between different individuals and the relations between the high- and low-dose maps. The proposed sparse high-dose induced (shd-Patlak) model performs by building a high-dose induced prior for the Patlak model with a set of location adaptive dictionaries, followed by an optimized estimation of BBBP map with the prior regularized Patlak model. Evaluation with the simulated low-dose clinical brain PCT datasets clearly demonstrate that the shd-Patlak model can achieve more significant gains than the standard Patlak model with improved visual quality, higher fidelity to the gold standard and more accurate details for clinical analysis.

publication date

  • October 17, 2013

Research

keywords

  • Blood-Brain Barrier
  • Radiographic Image Interpretation, Computer-Assisted
  • Stroke
  • Tomography, X-Ray Computed

Identity

PubMed Central ID

  • PMC4188431

Scopus Document Identifier

  • 84901690103

Digital Object Identifier (DOI)

  • 10.1016/j.media.2013.09.008

PubMed ID

  • 24200529

Additional Document Info

volume

  • 18

issue

  • 6