Jan Willem Dankbaar

Effect of different components of triple-H therapy on cerebral perfusion in patients with aneurysmal subarachnoid haemorrhage: a systematic review.

IntroductionTriple-H therapy and its separate components (hypervolemia, hemodilution, and hypertension) aim to increase cerebral perfusion in subarachnoid haemorrhage (SAH) patients with delayed cerebral ischemia. We systematically reviewed the literature on the effect of triple-H components on cerebral perfusion in SAH patients.MethodsWe searched medical databases to identify all articles until October 2009 (except case reports) on treatment with triple-H components in SAH patients with evaluation of the treatment using cerebral blood flow (CBF in ml/100 g/min) measurement. We summarized study design, patient and intervention characteristics, and calculated differences in mean CBF before and after intervention.ResultsEleven studies (4 to 51 patients per study) were included (one randomized trial). Hemodilution did not change CBF. One of seven studies on hypervolemia showed statistically significant CBF increase compared to baseline; there was no comparable control group. Two of four studies applying hypertension and one of two applying triple-H showed significant CBF increase, none used a control group. The large heterogeneity in interventions and study populations prohibited meta-analyses.ConclusionsThere is no good evidence from controlled studies for a positive effect of triple-H or its separate components on CBF in SAH patients. In uncontrolled studies, hypertension seems to be more effective in increasing CBF than hemodilution or hypervolemia.

Diagnosing Delayed Cerebral Ischemia With Different CT Modalities in Patients With Subarachnoid Hemorrhage With Clinical Deterioration

Background and Purpose— Delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage worsens the prognosis and is difficult to diagnose. We investigated the diagnostic value of noncontrast CT (NCT), CT perfusion (CTP), and CT angiography (CTA) for DCI after clinical deterioration in patients with subarachnoid hemorrhage. Methods— We prospectively enrolled 42 patients with subarachnoid hemorrhage with clinical deterioration suspect for DCI (new focal deficit or Glasgow Coma Scale decrease ≥2 points) within 21 days after hemorrhage. All patients underwent NCT, CTP, and CTA scans on admission and directly after clinical deterioration. The gold standard was the clinical diagnosis DCI made retrospectively by 2 neurologists who interpreted all clinical data, except CTP and CTA, to rule out other causes for the deterioration. Radiologists interpreted NCT and CTP images for signs of ischemia (NCT) or hypoperfusion (CTP) not localized in the neurosurgical trajectory or around intracerebral hematomas, and CTA images for presence of vasospasm. Diagnostic values for DCI of NCT, CTP, and CTA were assessed by calculating sensitivities, specificities, positive predictive values, and negative predictive values with 95% CIs. Results— In 3 patients with clinical deterioration, imaging failed due to motion artifacts. Of the remaining 39 patients, 25 had DCI and 14 did not. NCT had a sensitivity of 0.56 (95% CI, 0.37 to 0.73), specificity=0.71 (0.57 to 0.77), positive predictive value=0.78 (0.55 to 0.91), negative predictive value=0.48 (0.28 to 0.68); CTP: sensitivity=0.84 (0.65 to 0.94), specificity=0.79 (0.52 to 0.92), positive predictive value=0.88 (0.69 to 0.96), negative predictive value=0.73 (0.48 to 0.89); CTA: sensitivity=0.64 (0.45 to 0.80), specificity=0.50 (0.27 to 0.73), positive predictive value=0.70 (0.49 to 0.84), negative predictive value=0.44 (0.23 to 0.67). Conclusion— As a diagnostic tool for DCI, qualitative assessment of CTP is overall superior to NCT and CTA and could be useful for fast decision-making and guiding treatment.

Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: A Systematic Review of Clinical, Laboratory, and Radiological Predictors

Background and Purpose— Established predictors of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage are large amounts of extravasated blood and poor clinical condition on admission. The predictive value of other factors is uncertain. Methods— We searched MEDLINE (1960–2012) for clinical, laboratory, and radiological predictors routinely available within 72 hours after subarachnoid hemorrhage. The studies were categorized according to methodological quality. Crude data and effect estimates (odds ratio [OR], hazard ratios, and risk ratio) with 95% CI were extracted, (re-)calculated and pooled if possible. For every potential predictor we assessed all effect estimates on consistency (point estimates in equal direction) and clinical relevance (size and 95% CI). Results— Fifty-two studies on 33 potential predictors were included. There was strong evidence (≥3 high-quality studies) for a higher risk of delayed cerebral ischemia in smokers (pooled OR, 1.2; 95% CI, 1.1–1.4), and moderate evidence (2 high-quality studies) for an increased risk in patients with hyperglycemia (OR, 3.2; 1.8–5.8 and hazard ratios, 1.7; 1.1–2.5), hydrocephalus (OR, 1.3; 1.1–1.5 and OR, 2.6; 1.2–5.5), history of diabetes mellitus (pooled OR, 6.7; 1.7–26), and early systemic inflammatory response syndrome (pooled OR, 2.1; 1.4–3.3). Evidence was limited for increased risk in women (pooled OR, 1.3; 1.1–1.6) and in patients with history of hypertension (pooled OR, 1.5; 1.3–1.7). The evidence on initial loss of consciousness, history of migraine, previous use of selective serotonin reuptake inhibitors, hypomagnesemia, low hemoglobin, or high blood flow on early transcranial Doppler was also limited. Conclusions— There is strong evidence that smoking is a predictor of delayed cerebral ischemia. For several other potential predictions the evidence is moderate, limited, or inconsistent.

Diagnostic Threshold Values of Cerebral Perfusion Measured With Computed Tomography for Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage

Background and Purpose— Early diagnosis of delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage is critical but difficult. We analyzed diagnostic threshold values of CT perfusion for use in detection of DCI in patients with subarachnoid hemorrhage. Methods— We prospectively enrolled patients with subarachnoid hemorrhage with CT perfusion on admission and at time of clinical deterioration or after 1 week if no deterioration occurred. The gold standard was the clinical diagnosis of DCI based on all clinical, laboratory, and imaging data except CT perfusion. Patients with failed imaging (n=6) and other causes of deterioration (n=45) were excluded for the current study. We measured CT perfusion values, including cerebral blood volume, blood flow, mean transit time (MTT), and time to peak in predefined regions of interest and then compared absolute perfusion and perfusion asymmetry for patients with and without DCI. Diagnostic threshold values for DCI were evaluated and sensitivity and specificity calculated for optimal thresholds. Results— Of 85 eligible patients with subarachnoid hemorrhage, 50 had DCI; 35 patients with no clinical deterioration comprised the reference group. Cerebral blood flow was significantly lower, MTT higher, and perfusion asymmetry larger in patients with DCI. We found that largest absolute MTT and the MTT difference between hemispheres were good diagnostic tests. Diagnostic threshold values with optimal sensitivity and specificity were an MTT of 5.9 seconds and an MTT difference of 1.1 second. Conclusion— Thresholds for absolute MTT values and between-hemisphere MTT differences on CT perfusion can distinguish between patients with delayed cerebral ischemia and clinically stable patients.

Timing-Invariant Imaging of Collateral Vessels in Acute Ischemic Stroke

Background and Purpose— Although collateral vessels have been shown to be an important prognostic factor in acute ischemic stroke, patients with lack of collaterals on standard imaging techniques may still have good clinical outcome. We postulate that in these cases collateral vessels are present though not visible on standard imaging techniques that are based on a single time frame. Methods— This study included 40 consecutive patients with acute ischemic stroke with a large-vessel occlusion. Standard computed tomography angiography (CTA, single time frame) and CT perfusion (multiple time frames) were obtained at admission and timing-invariant (TI)-CTA was created from the CT perfusion data. Clinical outcome data (modified Rankin Scale) were assessed at 3-month follow-up. Four experienced observers independently assessed collateral status twice on both standard CTA and TI-CTA in an independent, blinded, randomized manner. Collateral status was rated as good if ≥50% and poor if <50% of collaterals were present compared with the contralateral hemisphere. Results— Collateral status was rated higher on TI-CTA (good in 84%) compared with standard CTA (good in 49%; P<0.001). Thirty-one percent of patients with poor collateral status on standard CTA still had good clinical outcome. All of those patients, however, showed good collaterals on TI-CTA. All cases with poor collateral status rated on TI-CTA had poor clinical outcome. Conclusions— Collateral vessels may not always be visible on standard single time-frame CTA because of delayed contrast arrival. Future prognostic studies in acute stroke should consider delay-insensitive techniques, such as TI-CTA, instead of standard single time-frame imaging, such as standard CTA.

Timing-Invariant Reconstruction for Deriving High-Quality CT Angiographic Data from Cerebral CT Perfusion Data

PURPOSE To suggest a simple and robust technique used to reconstruct high-quality computed tomographic (CT) angiographic images from CT perfusion data and to compare it with currently used CT angiography techniques. MATERIALS AND METHODS Institutional review board approval was waived for this retrospective study, which included 25 consecutive patients who had had a stroke. Temporal maximum intensity projection (tMIP) CT angiographic images were created by using prior temporal filtering as a timing-insensitive technique to produce CT angiographic images from CT perfusion data. The temporal filter strength was optimized to gain maximal contrast-to-noise ratios (CNRs) in the circle of Willis. The resulting timing-invariant (TI) CT angiography was compared with standard helical CT angiography, the arterial phase of dynamic CT angiography, and nonfiltered tMIP CT angiography. Vascular contrast, image noise, and CNR were measured. Four experienced observers scored all images for vascular noise, vascular contour, detail of small and medium arteries, venous superimposition, and overall image quality in a blinded side-by-side comparison. Measurements were compared with a paired t test; P ≤ .05 indicated a significant difference. RESULTS On average, optimized temporal filtering in TI CT angiography increased CNR by 18% and decreased image noise by 18% at the expense of a decrease in vascular contrast of 3% when compared with nonfiltered tMIP CT angiography. CNR, image noise, vascular noise, vascular contour, detail visibility of small and medium arteries, and overall image quality of TI CT angiograms were superior to those of standard CT angiography, tMIP CT angiography, and the arterial phase of dynamic CT angiography at a vascular contrast that was similar to that of standard CT angiography. Venous superimposition was similar for all techniques. Image quality of the arterial phase of dynamic CT angiography was rated inferior to that of standard CT angiography. CONCLUSION TI CT angiographic images constructed by using temporally filtered tMIP CT angiographic data have excellent image quality that is superior to that achieved with currently used techniques, but they suffer from modest venous superimposition.

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

IntroductionThe 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.MethodsImaging 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 Altmans approach.ResultsAutomated 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).ConclusionAutomated post-processing of PCT data improves interobserver agreement in measurements of CBV, CBF and MTT, as well as volume of infarct core and penumbra.

Prediction of outcome in patients with suspected acute ischaemic stroke with CT perfusion and CT angiography: the Dutch acute stroke trial (DUST) study protocol

BackgroundPrediction of clinical outcome in the acute stage of ischaemic stroke can be difficult when based on patient characteristics, clinical findings and on non-contrast CT. CT perfusion and CT angiography may provide additional prognostic information and guide treatment in the early stage. We present the study protocol of the Dutch acute Stroke Trial (DUST). The DUST aims to assess the prognostic value of CT perfusion and CT angiography in predicting stroke outcome, in addition to patient characteristics and non-contrast CT. For this purpose, individualised prediction models for clinical outcome after stroke based on the best predictors from patient characteristics and CT imaging will be developed and validated.Methods/designThe DUST is a prospective multi-centre cohort study in 1500 patients with suspected acute ischaemic stroke. All patients undergo non-contrast CT, CT perfusion and CT angiography within 9 hours after onset of the neurological deficits, and, if possible, follow-up imaging after 3 days. The primary outcome is a dichotomised score on the modified Rankin Scale, assessed at 90 days. A score of 0–2 represents good outcome, and a score of 3–6 represents poor outcome. Three logistic regression models will be developed, including patient characteristics and non-contrast CT (model A), with addition of CT angiography (model B), and CT perfusion parameters (model C). Model derivation will be performed in 60% of the study population, and model validation in the remaining 40% of the patients. Additional prognostic value of the models will be determined with the area under the curve (AUC) from the receiver operating characteristic (ROC) curve, calibration plots, assessment of goodness-of-fit, and likelihood ratio tests.DiscussionThis study will provide insight in the added prognostic value of CTP and CTA parameters in outcome prediction of acute stroke patients. The prediction models that will be developed in this study may help guide future treatment decisions in the acute stage of ischaemic stroke.

Validation of CT brain perfusion methods using a realistic dynamic head phantom

PURPOSE Development and evaluation of a realistic hybrid head phantom for the validation of quantitative CT brain perfusion methods. METHODS A combination, or hybrid, of CT images of an anthropomorphic head phantom together with clinically acquired MRI brain images was used to construct a dynamic hybrid head phantom. Essential CT imaging parameters such as spatially dependent noise, effects of resolution, tube settings, and reconstruction parameters were intrinsically included by scanning a skull phantom using CT perfusion (CTP) protocols with varying mAs. These data were combined with processed high resolution 7T clinical MRI images to include healthy and diseased brain parenchyma, as well as the cerebral vascular system. Time attenuation curves emulating contrast bolus passage based on perfusion as observed in clinical studies were added. Using the phantom, CTP images were generated using three brain perfusion calculation methods: bcSVD, sSVD, and fit-based deconvolution, and the linearity and accuracy of the three calculation methods was assessed. Dependency of perfusion outcome on calculation method was compared to clinical data. Furthermore, the potential of the phantom to optimize brain perfusion packages was investigated. RESULTS All perfusion calculation methods showed overestimation of low perfusion values and underestimation of high perfusion values. Good correlation in behavior between phantom and clinical data was found (R2 = 0.84). CONCLUSIONS A dynamic hybrid head phantom constructed from CT and MRI data was demonstrated to realistically represent clinical CTP studies, which is useful for assessing CT brain perfusion acquisition, reconstruction, and analysis.

The Prognostic Value of CT Angiography and CT Perfusion in Acute Ischemic Stroke.

Background: CT angiography (CTA) and CT perfusion (CTP) are important diagnostic tools in acute ischemic stroke. We investigated the prognostic value of CTA and CTP for clinical outcome and determined whether they have additional prognostic value over patient characteristics and non-contrast CT (NCCT). Methods: We included 1,374 patients with suspected acute ischemic stroke in the prospective multicenter Dutch acute stroke study. Sixty percent of the cohort was used for deriving the predictors and the remaining 40% for validating them. We calculated the predictive values of CTA and CTP predictors for poor clinical outcome (modified Rankin Scale score 3-6). Associations between CTA and CTP predictors and poor clinical outcome were assessed with odds ratios (OR). Multivariable logistic regression models were developed based on patient characteristics and NCCT predictors, and subsequently CTA and CTP predictors were added. The increase in area under the curve (AUC) value was determined to assess the additional prognostic value of CTA and CTP. Model validation was performed by assessing discrimination and calibration. Results: Poor outcome occurred in 501 patients (36.5%). Each of the evaluated CTA measures strongly predicted outcome in univariable analyses: the positive predictive value (PPV) was 59% for Alberta Stroke Program Early CT Score (ASPECTS) ≤7 on CTA source images (OR 3.3; 95% CI 2.3-4.8), 63% for presence of a proximal intracranial occlusion (OR 5.1; 95% CI 3.7-7.1), 66% for poor leptomeningeal collaterals (OR 4.3; 95% CI 2.8-6.6), and 58% for a >70% carotid or vertebrobasilar stenosis/occlusion (OR 3.2; 95% CI 2.2-4.6). The same applied to the CTP measures, as the PPVs were 65% for ASPECTS ≤7 on cerebral blood volume maps (OR 5.1; 95% CI 3.7-7.2) and 53% for ASPECTS ≤7 on mean transit time maps (OR 3.9; 95% CI 2.9-5.3). The prognostic model based on patient characteristics and NCCT measures was highly predictive for poor clinical outcome (AUC 0.84; 95% CI 0.81-0.86). Adding CTA and CTP predictors to this model did not improve the predictive value (AUC 0.85; 95% CI 0.83-0.88). In the validation cohort, the AUC values were 0.78 (95% CI 0.73-0.82) and 0.79 (95% CI 0.75-0.83), respectively. Calibration of the models was satisfactory. Conclusions: In patients with suspected acute ischemic stroke, admission CTA and CTP parameters are strong predictors of poor outcome and can be used to predict long-term clinical outcome. In multivariable prediction models, however, their additional prognostic value over patient characteristics and NCCT is limited in an unselected stroke population.