Scott Pohlman

Perfusion-CT Assessment of Infarct Core and Penumbra: Receiver Operating Characteristic Curve Analysis in 130 Patients Suspected of Acute Hemispheric Stroke

Background and Purpose— Different definitions have been proposed to define the ischemic penumbra from perfusion-CT (PCT) data, based on parameters and thresholds tested only in small pilot studies. The purpose of this study was to perform a systematic evaluation of all PCT parameters (cerebral blood flow, volume [CBV], mean transit time [MTT], time-to-peak) in a large series of acute stroke patients, to determine which (combination of) parameters most accurately predicts infarct and penumbra. Methods— One hundred and thirty patients with symptoms suggesting hemispheric stroke ≤12 hours from onset were enrolled in a prospective multicenter trial. They all underwent admission PCT and follow-up diffusion-weighted imaging/fluid-attenuated inversion recovery (DWI/FLAIR); 25 patients also underwent admission DWI/FLAIR. PCT maps were assessed for absolute and relative reduced CBV, reduced cerebral blood flow, increased MTT, and increased time-to-peak. Receiver-operating characteristic curve analysis was performed to determine the most accurate PCT parameter, and the optimal threshold for each parameter, using DWI/FLAIR as the gold standard. Results— The PCT parameter that most accurately describes the tissue at risk of infarction in case of persistent arterial occlusion is the relative MTT (area under the curve=0.962), with an optimal threshold of 145%. The PCT parameter that most accurately describes the infarct core on admission is the absolute CBV (area under the curve=0.927), with an optimal threshold at 2.0 ml×100 g−1. Conclusion— In a large series of 130 patients, the optimal approach to define the infarct and the penumbra is a combined approach using 2 PCT parameters: relative MTT and absolute CBV, with dedicated thresholds.

Dynamic Perfusion CT Assessment of the Blood-Brain Barrier Permeability: First Pass versus Delayed Acquisition

BACKGROUND AND PURPOSE: The Patlak model has been applied to first-pass perfusion CT (PCT) data to extract information on blood-brain barrier permeability (BBBP) to predict hemorrhagic transformation in patients with acute stroke. However, the Patlak model was originally described for the delayed steady-state phase of contrast circulation. The goal of this study was to assess whether the first pass or the delayed phase of a contrast bolus injection better respects the assumptions of the Patlak model for the assessment of BBBP in patients with acute stroke by using PCT. MATERIALS AND METHODS: We retrospectively identified 125 consecutive patients (29 with acute hemispheric stroke and 96 without) who underwent a PCT study by using a prolonged acquisition time up to 3 minutes. The Patlak model was applied to calculate BBBP in ischemic and nonischemic brain tissue. Linear regression of the Patlak plot was performed separately for the first pass and for the delayed phase of the contrast bolus injection. Patlak linear regression models for the first pass and the delayed phase were compared in terms of their respective square root mean squared errors (√MSE) and correlation coefficients (R) by using generalized estimating equations with robust variance estimation. RESULTS: BBBP values calculated from the first pass were significantly higher than those from the delayed phase, both in nonischemic brain tissue (2.81 mL × 100 g−1 × min−1 for the first pass versus 1.05 mL × 100 g−1 × min−1 for the delayed phase, P < .001) and in ischemic tissue (7.63 mL × 100 g−1 × min−1 for the first pass versus 1.31 mL × 100 g−1 × min−1 for the delayed phase, P < .001). Compared with regression models from the first pass, Patlak regression models obtained from the delayed data were of better quality, showing significantly lower √MSE and higher R. CONCLUSION: Only the delayed phase of PCT acquisition respects the assumptions of linearity of the Patlak model in patients with and without stroke.

Accuracy and anatomical coverage of perfusion CT assessment of the blood-brain barrier permeability: one bolus versus two boluses.

Purpose: To assess whether blood-brain barrier permeability (BBBP) values, extracted with the Patlak model from the second perfusion CT (PCT) contrast bolus, are significantly lower than the values extracted from the first bolus in the same patient. Materials and Methods: 125 consecutive patients (29 with acute hemispheric stroke and 96 without stroke) who underwent a PCT study using a prolonged acquisition time up to 3 min were retrospectively identified. The Patlak model was applied to calculate the rate of contrast leakage out of the vascular compartment. Patlak plots were created from the arterial and parenchymal time enhancement curves obtained in multiple regions of interest drawn in ischemic brain tissue and in nonischemic brain tissue. The slope of a regression line fit to the Patlak plot was used as an indicator of BBBP. Square roots of the mean squared errors and correlation coefficients were used to describe the quality of the linear regression model. This was performed separately for the first and the second PCT bolus. Results from the first and the second bolus were compared in terms of BBBP values and the quality of the linear model fitted to the Patlak plot, using generalized estimating equations with robust variance estimation. Results: BBBP values from the second bolus were not lower than BBBP values from the first bolus in either nonischemic brain tissue [estimated mean with 95% confidence interval: 1.42 (1.10–1.82) ml·100 g–1·min–1 for the first bolus versus 1.64 (1.31–2.05) ml·100 g–1·min–1 for the second bolus, p = 1.00] or in ischemic tissue [1.04 (0.97–1.12) ml·100 g–1·min–1 for the first bolus versus 1.19 (1.11–1.28) ml·100 g–1·min–1 for the second bolus, p = 0.79]. Compared to regression models from the first bolus, the Patlak regression models obtained from the second bolus were of similar or slightly better quality. This was true both in nonischemic and ischemic brain tissue. Conclusion: The contrast material from the first bolus of contrast for PCT does not negatively influence measurements of BBBP values from the second bolus. The second bolus can thus be used to increase anatomical coverage of BBBP assessment using PCT.

CT perfusion: comparison of gamma-variate fit and deconvolution

The purpose of this paper is to present results of a study comparing CT brain perfusion image calculated using the maximum slope and deconvolution method on data from 32 patients. The 32 patients were organized into two groups. One group was obtained using a 4cc/sec contrast injection rate and 10 sec injection period; the other group was obtained using a 6cc/sec injection rate and 7 sec injection period. All clinical data were analyzed using both the maximum slope and deconvolution methods. Perfusion maps computed from the two methods were reviewed by radiologists. The contrast enhanced CT data were noisy, especially in the white matter area. Our results showed that, for both methods, perfusion maps from 4cc/sec injection were noisier than those using a 6cc/sec injection. However, both 4cc/sec and 6cc/sec produced useful diagnostic images. Our qualitative side-by-side studies also showed that perfusion images from the maximum slope and deconvolution are both clinically useful and substantially equivalent.

Multislice CT brain image registration for perfusion studies

During the last several years perfusion CT techniques have been developed as an effective technique for clinically evaluating cerebral hemodynamics. Perfusion CT techniques are capable of measurings functional parameters such as tissue perfusion, blood flow, blood volume, and mean transit time and are commonly used to evaluate stroke patients. However, the quality of functional images of the brain frequently suffers from patient head motion. Because the time window for an effective treatment of stroke patient is narrow, a fast motion correction is required. The purpose of the paper is to present a fast and accurate registration technique for motion correction of multi-slice CT and to demonstrate the effects of the registration on perfusion calculation.