Automated versus manual post-processing of perfusion-CT data in patients with acute cerebral ischemia: influence on interobserver variability

The purpose of this study is to compare the variability of PCT results obtained by automatic selection of the arterial input function (AIF), venous output function (VOF) and symmetry axis versus manual selection. Imaging data from 30 PCT studies obtained as part of standard clinical stroke care at our institution in patients with suspected acute hemispheric ischemic stroke were retrospectively reviewed. Two observers performed the post-processing of 30 CTP datasets. Each observer processed the data twice, the first time employing manual selection of AIF, VOF and symmetry axis, and a second time using automated selection of these same parameters, with the user being allowed to adjust them whenever deemed appropriate. The volumes of infarct core and of total perfusion defect were recorded. The cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT) and blood-brain barrier permeability (BBBP) values in standardized regions of interest were recorded. Interobserver variability was quantified using the Bland and Altman's approach. Automated post-processing yielded lower coefficients of variation for the volume of the infarct core and the volume of the total perfusion defect (15.7% and 5.8%, respectively) compared to manual post-processing (31.0% and 12.2%, respectively). Automated post-processing yielded lower coefficients of variation for PCT values (11.3% for CBV, 9.7% for CBF, and 9.5% for MTT) compared to manual post-processing (23.7% for CBV, 32.8% for CBF, and 16.7% for MTT). Automated post-processing of PCT data improves interobserver agreement in measurements of CBV, CBF and MTT, as well as volume of infarct core and penumbra

Quantitative analysis of CT-perfusion parameters in the evaluation of brain gliomas and metastases

<p>Abstract</p> <p>Background</p> <p>The paper reports a quantitative analysis of the perfusion maps of 22 patients, affected by gliomas or by metastasis, with the aim of characterizing the malignant tissue with respect to the normal tissue. The gold standard was obtained by histological exam or nuclear medicine techniques. The perfusion scan provided 11 parametric maps, including Cerebral Blood Volume (CBV), Cerebral Blood Flow (CBF), Average Perfusion (P_mean) and Permeability-surface area product (PS).</p> <p>Methods</p> <p>The perfusion scans were performed after the injection of 40 ml of non-ionic contrast agent, at an injection rate of 8 ml/s, and a 40 s cine scan with 1 s interval was acquired. An expert radiologist outlined the region of interest (ROI) on the unenhanced CT scan, by using a home-made routine. The mean values with their standard deviations inside the outlined ROIs and the contralateral ROIs were calculated on each map. Statistical analyses were used to investigate significant differences between diseased and normal regions. Receiving Operating Characteristic (ROC) curves were also generated.</p> <p>Results</p> <p>Tumors are characterized by higher values of all the perfusion parameters, but after the statistical analysis, only the <it>PS</it>, <it>Pat</it>_{<it>Rsq </it>}(Patlak Rsquare) and <it>T</it>_{<it>peak </it>}(Time to Peak) resulted significant. ROC curves, confirmed both <it>Pat</it>_{<it>Rsq </it>}and <it>PS </it>as equally reliable metrics for discriminating between malignant and normal tissues, with areas under curves (AUCs) of 0.82 and 0.81, respectively.</p> <p>Conclusion</p> <p>CT perfusion is a useful and non invasive technique for evaluating brain neoplasms. Malignant and normal tissues can be accurately differentiated using perfusion map, with the aim of performing tumor diagnosis and grading, and follow-up analysis.</p

The Role of Perfusion Computed Tomography in the Prediction of Cerebral Hyperperfusion Syndrome

Hyperperfusion syndrome (HPS) following carotid angioplasty with stenting (CAS) is associated with significant morbidity and mortality. At present, there are no reliable parameters to predict HPS. The aim of this study was to clarify whether perfusion computed tomography (CT) is a feasible and reliable tool in predicting HPS after CAS.We performed a retrospective case-control study of 54 patients (11 HPS patients and 43 non-HPS) with unilateral severe stenosis of the carotid artery who underwent CAS. We compared the prevalence of vascular risk factors and perfusion CT parameters including regional cerebral blood volume (rCBV), regional cerebral blood flow (rCBF), and time to peak (TTP) within seven days prior to CAS. Demographic information, risk factors for atherosclerosis, and perfusion CT parameters were evaluated by multivariable logistic regression analysis. The rCBV index was calculated as [(ipsilateral rCBV - contralateral rCBV)/contralateral rCBV], and indices of rCBF and TTP were similarly calculated. We found that eleven patients had HPS, including five with intracranial hemorrhages (ICHs) of whom three died. After a comparison with non-HPS control subjects, independent predictors of HPS included the severity of ipsilateral carotid artery stenosis, 3-hour mean systolic blood pressure (3 h SBP) after CAS, pre-stenting rCBV index >0.15 and TTP index >0.22.The combination of severe ipsilateral carotid stenosis, 3 h SBP after CAS, rCBV index and TTP index provides a potential screening tool for predicting HPS in patients with unilateral carotid stenosis receiving CAS. In addition, adequate management of post-stenting blood pressure is the most important treatable factor in preventing HPS in these high risk patients