Is ultrasound perfusion imaging capable of detecting mismatch? A proof-of-concept study in acute stroke patients

Abstract

In this study, we compared contrast-enhanced ultrasound perfusion imaging with magnetic resonance perfusion-weighted imaging or perfusion computed tomography for detecting normo-, hypo-, and nonperfused brain areas in acute middle cerebral artery stroke. We performed high mechanical index contrast-enhanced ultrasound perfusion imaging in 30 patients. Time-to-peak intensity of 10 ischemic regions of interests was compared to four standardized nonischemic regions of interests of the same patient. A time-to-peak >3 s (ultrasound perfusion imaging) or >4 s (perfusion computed tomography and magnetic resonance perfusion) defined hypoperfusion. In 16 patients, 98 of 160 ultrasound perfusion imaging regions of interests of the ischemic hemisphere were classified as normal, and 52 as hypoperfused or nonperfused. Ten regions of interests were excluded due to artifacts. There was a significant correlation of the ultrasound perfusion imaging and magnetic resonance perfusion or perfusion computed tomography (Pearson's chi-squared test 79.119, p < 0.001) (OR 0.1065, 95% CI 0.06-0.18). No perfusion in ultrasound perfusion imaging (18 regions of interests) correlated highly with diffusion restriction on magnetic resonance imaging (Pearson's chi-squared test 42.307, p < 0.001). Analysis of receiver operating characteristics proved a high sensitivity of ultrasound perfusion imaging in the diagnosis of hypoperfused area under the curve, (AUC = 0.917; p < 0.001) and nonperfused (AUC = 0.830; p < 0.001) tissue in comparison with perfusion computed tomography and magnetic resonance perfusion. We present a proof of concept in determining normo-, hypo-, and nonperfused tissue in acute stroke by advanced contrast-enhanced ultrasound perfusion imaging.

Keywords: Acute ischemic stroke; brain imaging; cerebral perfusion; neurosonology; ultrasound perfusion imaging.

Figures

Figure 1.

Overview of the perfusion categories of the regions of interest (ROIs) in the ischemic hemisphere as measured by CTP/MRP and/or UPI. Schematic representation of the different diagnostic levels comparing the UPI insonation level (a) and the MRI scanning level (b) in a patient with left MCA occlusion. Sectional schematic images from HighMI UPI of the contralateral side (a) and axial images from MRI with perfusion imaging (b). Parametric images from UPI (c) and MRP (d) with threshold representation as described in our study (UPI 3 s; MRP 4 s). According to the threshold representation of the normal perfused (green), hypoperfused (yellow) and nonperfused (red) tissue. (Copyright Neurosurgery Department, Inselspital, Bern, Switzerland).

Figure 2.

Schematic representation of the different diagnostic levels showing the MRI scanning level (a) and the UPI insonation level (b) in a patient suffering of left middle cerebral artery occlusion. Representation of the diencephalic insonation level through the third ventricle and visualization of ipsi- and contralateral basal ganglia. Note that the insonation level has a 10–20° inclination in comparison to the MRI scanning level, causing anatomical differences between the two hemispheres. (c, d) ROC curves of UPI in comparison with MRP. Using the patient-adjusted analysis algorithm (b) the specificity of the UPI investigation increased in comparison to the standard analysis algorithm (a). (Copyright Neurosurgery Department, Inselspital, Bern, Switzerland.

Figure 3.

Comparison of TTP maps and ROI analysis between VueBox and dedicated software. Patient 7 with M1 occlusion of RMCA with imaging performed 278 min after symptom onset. (a) and (b). Screenshots of VueBox derived analysis with color-coded TTP map displaying both hemispheres with a marked area of delayed intensity rise in the RMCA territory (dark blue area a), exemplary time–intensity curves (TIC, c) derived from thalamic area of unaffected hemisphere (yellow box, TTP = 11.41 s), and from hypoperfused cortical area of affected hemisphere (green box, TTP = 14.70 s). (b) and (d). Corresponding color-coded TTP map (b) and example TICs (d) derived from thalamic area (yellow box, TTP = 11.31 s) and cortical area (green box, TTP = 14.69 s) by dedicated software.

Figure 4.

Comparison of UPI-based quantification of hypoperfused and nonperfused area with the gold standard-based quantification for hypoperfusion CTP/MRP and nonperfusion DWI. Receiver operating characteristics (ROC) curves of UPI in comparison with MRP and DWI. Detection of the hypoperfused tissue showed high sensitivity and specificity in comparison to CTP/MRP (a). The same was observed for detection of nonperfused tissue, where the nonperfused UPI ROIs were correlated with DWI regions on MRI (b). Scatter plot showing the linear correlation between absolute TTP delay values measured by UPI versus perfusion CT/MRI. R2 Coefficient of determination is 0.519 (c).