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 < or =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 x 100 g(-1). CONCLUSIONS: 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.

Accuracy of dynamic perfusion CT with deconvolution in detecting acute hemispheric stroke.

BACKGROUND AND PURPOSE: Dynamic perfusion CT (PCT) with deconvolution produces maps of time-to-peak (TTP), mean transit time (MTT), regional cerebral blood flow (rCBF), and regional cerebral blood volume (rCBV), with a computerized automated map of the infarct and penumbra. We determined the accuracy of these maps in patients with suspected acute hemispheric stroke. METHODS: Forty-six patients underwent nonenhanced CT and dynamic PCT, with follow-up CT or MR imaging. Two observers reviewed the nonenhanced studies for signs of stroke and read the PCT maps for TTP, MTT, rCBF, and rCBV abnormalities. Sensitivity, specificity, accuracy, and interobserver agreement were compared (Wilcoxon tests). Nonenhanced CT and PCT data were reviewed for stroke extent according to previously reported methods. Sensitivity, specificity, and accuracy of the computerized maps in detecting ischemia and its extent were determined. RESULTS: Compared with nonenhanced CT, PCT maps were significantly more accurate in detecting stroke (75.7-86.0% vs. 66.2%; P <.01), MTT maps were significantly more sensitive (77.6% vs. 69.2%; P <.01), and rCBF and rCBV maps were significantly more specific (90.9% and 92.7%, respectively, vs. 65.0%; P <.01). Regarding stroke extent, PCT maps were significantly more sensitive than nonenhanced CT (up to 94.4% vs. 42.9%; P <.01) and had higher interobserver agreement (up to 0.763). For the computerized map, sensitivity, specificity, and accuracy, respectively, were 68.2%, 92.3%, and 88.1% in detecting ischemia and 72.2%, 91.8%, and 87.9% in showing the extent. CONCLUSION: Dynamic PCT maps are more accurate than nonenhanced CT in detecting hemispheric strokes. Despite limited spatial coverage, PCT is highly reliable to assess the stroke extent.

Dynamic perfusion CT: optimizing the temporal resolution and contrast volume for calculation of perfusion CT parameters in stroke patients.

BACKGROUND AND PURPOSE: Numerous parameters are involved in dynamic perfusion CT (PCT). We assessed the influence of the temporal sampling rate and the volume of contrast material. METHODS: Sixty patients with ischemic hemispheric stroke lasting > or = 12 hours underwent PCT. Groups of 15 patients each received 30, 40, 50, or 60 mL of contrast agent. Regional cerebral blood volume (rCBV), regional cerebral blood flow (rCBF), mean transit time (MTT), and time-to-peak (TTP) maps were calculated for temporal sampling intervals of 0.5, 1, 2, 3, 4, 5, and 6 seconds. Results were statistically compared. Signal-to-noise ratios (SNRs), duration of arterial entrance to venous exit, and radiation dose were also assessed. RESULTS: Increasing temporal sampling intervals lead to significant overestimation of rCBV, rCBF, and TTP and significant underestimation of MTT compared with values for an interval of 1 second. Maximal allowable intervals to avoid these effects were 2, 3, 3, and 4 seconds for 30, 40, 50, and 60-mL boluses, respectively. Venous exit of contrast material occurred in 97.5% of patients after 36, 42, 42, and 48 seconds, respectively, for the four volumes. SNRs did not differ with volume. The effective radiation dose varied between 0.852 and 1.867 mSv, depending on the protocol. The cine mode with two 40-mL boluses and the toggling-table technique with one 60-mL bolus had the lowest doses. CONCLUSION: Temporal sampling intervals greater than 1 second can be used without altering the quantitative accuracy of PCT. Increased sampling intervals reduce the radiation dose and may allow for increased spatial coverage.

Magnetic resonance image registration in multiple sclerosis: comparison with repositioning error and observer-based variability.

PURPOSE: To study the use of image registration in the analysis of multiple sclerosis (MS) lesion volume and compare this with repositioning error and observer-based variability. MATERIALS AND METHODS: The normalized mutual information (NMI) algorithm is evaluated in an accuracy study using a phantom, followed by a validation study on magnetic resonance (MR) data of MS patients. Further, using scan-rescan MR data, the effect of registration on MS lesion volume compared with repositioning error and observer-based variability is assessed. RESULTS: The registration accuracy was near perfect in the phantom study, while the in vivo validation study demonstrated an accuracy on the order of 0.2-0.3 mm. In the scan-rescan study, quantification accounted for 15.6% of the relative variance, repositioning for 44.4%, and registration for 40.0%. CONCLUSION: NMI resulted in robust and accurate alignment of MR brain images of MS patients. Its use in the detection of changes in MS using large serial MR imaging (MRI) data warrants future evaluation.