A Fast Nonlinear Regression Method for Estimating Permeability in CT Perfusion Imaging

Abstract

Blood-brain barrier damage, which can be quantified by measuring vascular permeability, is a potential predictor for hemorrhagic transformation in acute ischemic stroke. Permeability is commonly estimated by applying Patlak analysis to computed tomography (CT) perfusion data, but this method lacks precision. Applying more elaborate kinetic models by means of nonlinear regression (NLR) may improve precision, but is more time consuming and therefore less appropriate in an acute stroke setting. We propose a simplified NLR method that may be faster and still precise enough for clinical use. The aim of this study is to evaluate the reliability of in total 12 variations of Patlak analysis and NLR methods, including the simplified NLR method. Confidence intervals for the permeability estimates were evaluated using simulated CT attenuation-time curves with realistic noise, and clinical data from 20 patients. Although fixating the blood volume improved Patlak analysis, the NLR methods yielded significantly more reliable estimates, but took up to 12 Â longer to calculate. The simplified NLR method was B4 Â faster than other NLR methods, while maintaining the same confidence intervals (CIs). In conclusion, the simplified NLR method is a new, reliable way to estimate permeability in stroke, fast enough for clinical application in an acute stroke setting.

Imaging Findings Associated with Space-Occupying Edema in Patients with Large Middle Cerebral Artery Infarcts

“…The permeability surface area was calculated relative to the nonaffected hemisphere. 10 CTA. Admission CTA provided data on intracranial thrombus location, clot burden score, and collateral score.…”

“…9 A measure of the BBB permeability is the permeability surface-area product, which can be obtained from an extended CTP acquisition. 10 Other known risk factors for the development of prominent space-occupying edema include proximal occlusion site, greater infarct size, involvement of Ͼ1 vascular territory, basal ganglia involvement, increased ratio of CBV lesion volume/CSF volume, female sex, and higher NIHSS score on admission.…”

Computed Tomography Perfusion Derived Blood-Brain Barrier Permeability Does Not Yet Improve Prediction of Hemorrhagic Transformation

“…The Patlak model is the most frequently used model to described BBBP but only considers leakage and does not take tissue perfusion into account [22]. Other methods to estimate BBBP, like non-linear regression (NLR) with a perfusion model have demonstrated to be more reliable and robust [23]. Prediction of HT may therefore also improve by using this method, as previously has been shown in a small group of patients [24].…”

Fast nonlinear regression method for CT brain perfusion analysis

“…These models can even be extended to also include other perfusion parameters, such as vascular permeability for predicting hemorrhagic transformation. 8,16 These advantages of model-based methods may lead to smaller variability in results due to differences in implementations, or differences in data properties such as temporal resolution or noise level.…”

“…Horizontally in the tiles the MTT was varied (24,12,8 Prior to analysis, the slices in the phantom were filtered with a two-dimensional (2-D) Gaussian kernel with a standard deviation of 2.5 pixels. No additional filtering was applied.…”