Influence of arterial input function on hypoperfusion volumes measured with perfusion-weighted imaging.

Department of Neurology, UZ Gasthuisberg, Herestraat 49, B-3000 Leuven, Belgium.
Stroke (Impact Factor: 6.02). 02/2004; 35(1):94-8. DOI: 10.1161/01.STR.0000106136.15163.73
Source: PubMed

ABSTRACT The arterial input function (AIF) is critical in determining hemodynamic parameters quantitatively with bolus-tracking MRI. We studied the effect of varying the location of measurement of AIF on the volume of hypoperfusion. We compared the volumes of hypoperfusion obtained with different AIFs with the final ischemic lesion volume.
We included 13 patients with acute cerebral ischemia in the anterior circulation who underwent diffusion- (DWI) and perfusion (PWI)-weighted imaging within 8 hours after symptom onset and exhibited DWI lesion expansion between baseline and follow-up. AIF was measured at 4 locations: near both middle cerebral arteries (MCAs), in MCA branches adjacent to the largest DWI abnormality, and at the same level on the opposite hemisphere. Hypoperfusion lesion volumes were compared with the DWI volume at follow-up.
Large variations in PWI lesion size were found with different AIF locations. The largest PWI lesions were found when AIF was measured at the contralateral MCA. Smaller PWI lesions were found when AIF was measured in the other locations. There was no significant difference between PWI lesion area at baseline and follow-up DWI lesion when AIF was measured at the contralateral MCA. The other PWI lesions significantly underestimated follow-up DWI lesion size.
AIF is an important determinant of the size of hypoperfusion lesions measured with PWI. PWI lesion volumes determined with AIF from the contralateral MCA are associated with follow-up lesion volume.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The purpose of this study was to evaluate changes in fractional anisotropy (FA), as measured by diffusion tensor imaging, of white matter (WM) infarction and hypoperfusion in patients with acute ischemic stroke using a quantitative voxel-based analysis. In this prospective study, diffusion tensor imaging and dynamic susceptibility contrast perfusion sequences were acquired in 21 patients with acute ischemic stroke who presented within 6 hours of symptom onset. The coregistered FA, apparent diffusion coefficient, and dynamic susceptibility contrast time to maximum (Tmax) maps were used for voxel-based quantification using a region of interest approach in the ipsilateral affected side and in the homologous contralateral WM. The regions of WM infarction versus hypoperfusion were segmented using a threshold method. Data were analyzed by regression and ANOVA. There was an overall significant mean difference (P<0.001) for the apparent diffusion coefficient, Tmax, and FA values between the normal, hypoperfused, and infarcted WM. The mean±SD of FA was significantly higher (P<0.001) in hypoperfused WM (0.397±0.019) and lower (P<0.001) in infarcted WM (0.313±0.037) when compared with normal WM (0.360±0.020). Regression tree analysis of hypoperfused WM showed the largest mean FA difference at Tmax above versus below 5.4 s with a mean difference of 0.033 (P=0.0096). Diffusion tensor imaging-FA was decreased in regions of WM infarction and increased in hypoperfused WM in patients with hyperacute acute ischemic stroke. The significantly increased FA values in the hypoperfused WM with Tmax≥5.4 s are suggestive of early ischemic microstructural changes. © 2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wolters Kluwer.
    Stroke 12/2014; DOI:10.1161/STROKEAHA.114.007000 · 6.02 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Assessment of cerebral ischemia often employs dynamic susceptibility contrast enhanced magnetic resonance imaging (DSC-MRI) with evaluation of various peak enhancement time parameters. All of these parameters use a single time threshold to judge the maximum tolerable peak enhancement delay that is supposed to reliably differentiate sufficient from critical perfusion. As the validity of this single threshold approach still remains unclear, in this study, (1) the definition of a threshold on an individual patient-basis, nevertheless (2) preserving the comparability of the data, was investigated. The histogram of time-to-peak (TTP) values derived from DSC-MRI, the so-called TTP-distribution curve (TDC), was modeled using a double-Gaussian model in 61 patients without severe cerebrovascular disease. Particular model-based zf-scores were used to describe the arterial, parenchymal and venous bolus-transit phase as time intervals Ia,p,v. Their durations (delta Ia,p,v), were then considered as maximum TTP-delays of each phase. Mean-R2 for the model-fit was 0.967. Based on the generic zf-scores the proposed bolus transit phases could be differentiated. The Ip-interval reliably depicted the parenchymal bolus-transit phase with durations of 3.4 s-10.1 s (median = 4.3s), where an increase with age was noted (∼30 ms/year). Individual threshold-adjustment seems rational since regular bolus-transit durations in brain parenchyma obtained from the TDC overlap considerably with recommended critical TTP-thresholds of 4 s-8 s. The parenchymal transit time derived from the proposed model may be utilized to individually correct TTP-thresholds, thereby potentially improving the detection of critical perfusion.
    PLoS ONE 12/2014; 9(12):e114999. DOI:10.1371/journal.pone.0114999 · 3.53 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: BACKGROUND Diagnostic accuracies of standard NCCT, CTA, CTA-SI, FLAIR, and DWI to detect the diffusion–perfusion mismatch (DPM) were compared. METHODS Stroke patients considered for endovascular therapy within 8 hours of onset were enrolled. DPM was defined as at least 160% mismatch between DWI and PWI volume. RESULTSDPM was seen in 35 (71%) of 49 patients. ASPECTS on NCCT, CTA-SI, and DWI was 9 (8-9), 8 (6-9), and 7 (5-9) in mismatch group, and 6 (4-9), 6 (2-7), 5 (2-6) in nonmismatch group, respectively (P = .027, .006, and .001). Ischemic volume on CTA-SI and DWI was 4.6 (.2-13.0) cm3 and 21.5 (9.7-44.0) cm3 in mismatch group, and 61.5 (6.6-101.1) cm3 and 94.9 (45.7-139.8) cm3 in nonmismatch group (P = .003 and <.001). Significant collateralization on CTA-SI and FLAIR was seen in 80% and 88% in mismatch group, and 42% and 58% in nonmismatch group (P = .026 and .039). Odds ratios (95% CI) of DWI volume of ≤70 cm3 to predict the mismatch was 30.17 (2.06-442.41) after adjusting for ASPECTSs on NCCT, CTA-SI, and DWI, 44.90 (2.75-732.73) for ischemic volume on CTA-SI, and 42.80 (3.05-601.41) for significant collateralization on CTA-SI and FLAIR (P = .013, .008, and .005). CONCLUSIONSDWI volume was the best predictor of DPM.
    Journal of neuroimaging: official journal of the American Society of Neuroimaging 03/2014; 25(2). DOI:10.1111/jon.12107 · 1.82 Impact Factor

Full-text (2 Sources)

Available from
Jun 2, 2014