Shortened Mean Transit Time in CT Perfusion With Singular Value Decomposition Analysis in Acute Cerebral Infarction: Quantitative Evaluation and Comparison With Various CT Perfusion Parameters

Abnormal cerebral hemodynamics and blood-brain barrier permeability detected with perfusion MRI in systemic lupus erythematosus patients

OBJECTIVE

Dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) has previously shown alterations in cerebral perfusion in patients with systemic lupus erythematosus (SLE). However, the results have been inconsistent, in particular regarding neuropsychiatric (NP) SLE. Thus, we investigated perfusion-based measures in different brain regions in SLE patients with and without NP involvement, and additionally, in white matter hyperintensities (WMHs), the most common MRI pathology in SLE patients.

MATERIALS AND METHODS

We included 3 T MRI images (conventional and DSC) from 64 female SLE patients and 19 healthy controls (HC). Three different NPSLE attribution models were used: the Systemic Lupus International Collaborating Clinics (SLICC) A model (13 patients), the SLICC B model (19 patients), and the American College of Rheumatology (ACR) case definitions for NPSLE (38 patients). Normalized cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) were calculated in 26 manually drawn regions of interest and compared between SLE patients and HC, and between NPSLE and non-NPSLE patients. Additionally, normalized CBF, CBV and MTT, as well as absolute values of the blood-brain barrier leakage parameter (K2) were investigated in WMHs compared to normal appearing white matter (NAWM) in the SLE patients.

RESULTS

After correction for multiple comparisons, the most prevalent finding was a bilateral significant decrease in MTT in SLE patients compared to HC in the hypothalamus, putamen, right posterior thalamus and right anterior insula. Significant decreases in SLE compared to HC were also found for CBF in the pons, and for CBV in the bilateral putamen and posterior thalamus. Significant increases were found for CBF in the posterior corpus callosum and for CBV in the anterior corpus callosum. Similar patterns were found for both NPSLE and non-NPSLE patients for all attributional models compared to HC. However, no significant perfusion differences were revealed between NPSLE and non-NPSLE patients regardless of attribution model. The WMHs in SLE patients showed a significant increase in all perfusion-based metrics (CBF, CBV, MTT and K2) compared to NAWM.

CONCLUSION

Our study revealed perfusion differences in several brain regions in SLE patients compared to HC, independently of NP involvement. Furthermore, increased K2 in WMHs compared to NAWM may indicate blood-brain barrier dysfunction in SLE patients. We conclude that our results show a robust cerebral perfusion, independent from the different NP attribution models, and provide insight into potential BBB dysfunction and altered vascular properties of WMHs in female SLE patients. Despite SLE being most prevalent in females, a generalization of our conclusions should be avoided, and future studies including all sexes are needed.

A Bayesian estimation method for cerebral blood flow measurement by area-detector CT perfusion imaging

PURPOSE

Bayesian estimation with advanced noise reduction (BEANR) in CT perfusion (CTP) could deliver more reliable cerebral blood flow (CBF) measurements than the commonly used reformulated singular value decomposition (rSVD). We compared the efficacy of CBF measurement by CTP using BEANR and rSVD, evaluating both relative to N-isopropyl-p-[(123) I]- iodoamphetamine (¹²³I-IMP) single-photon emission computed tomography (SPECT) as a reference standard, in patients with cerebrovascular disease.

METHODS

Thirty-one patients with suspected cerebrovascular disease underwent both CTP on a 320 detector-row CT system and SPECT. We applied rSVD and BEANR in the ischemic and contralateral regions to create CBF maps and calculate CBF ratios from the ischemic side to the healthy contralateral side (CBF index). The analysis involved comparing the CBF index between CTP methods and SPECT using Pearson's correlation and limits of agreement determined with Bland-Altman analyses, before comparing the mean difference in the CBF index between each CTP method and SPECT using the Wilcoxon matched pairs signed-rank test.

RESULTS

The CBF indices of BEANR and ¹²³I-IMP SPECT were significantly and positively correlated (r = 0.55, p < 0.0001), but there was no significant correlation between the rSVD method and SPECT (r = 0.15, p > 0.05). BEANR produced smaller limits of agreement for CBF than rSVD. The mean difference in the CBF index between BEANR and SPECT differed significantly from that between rSVD and SPECT (p < 0.001).

CONCLUSIONS

BEANR has a better potential utility for CBF measurement in CTP than rSVD compared to SPECT in patients with cerebrovascular disease.

Correlation between the CT Perfusion Parameter Values and Response to Recanalization in Patients with Acute Ischemic Stroke

Objective

CT perfusion (CTP) provides various hemodynamic parameters. However, it is unclear which CTP parameters are useful in predicting clinical outcome in patients with acute ischemic stroke (AIS).

Methods

Between February 2019 and June 2021, patients with anterior circulation large-vessel occlusion who achieved successful recanalization within 8 hours after stroke onset were included. The relative CTP parameter values analyzed by the reformulated singular value decomposition (SVD) method in the affected middle cerebral artery territories compared to those in the unaffected side were calculated. In addition, the ischemic core volume (ICV) was evaluated using a Bayesian Vitrea. The final infarct volume (FIV) was assessed by 24-hour MRI. The correlation between these CTP-derived values and clinical outcome was assessed.

Results

Forty-two patients were analyzed. Among the CTP-related parameters, the ICV, relative cerebral blood volume (rCBV), and relative mean transit time (rMTT) showed a strong correlation with the FIV (ρ = 0.74, p <0.0001; ρ = -0.67, p <0.0001; and ρ = -0.66, p <0.0001, respectively). In multivariate analysis, rCBV, rMTT, and ICV were significantly associated with good functional outcome, which was defined as a modified Rankin Scale score ≤2 (OR, 6.87 [95% CI, 1.20-39.30], p = 0.0303; OR, 11.27 [95% CI, 0.97-130.94], p = 0.0269; and OR, 36.22 [95% CI, 2.78-471.18], p = 0.0061, respectively).

Conclusion

Among the CTP parameters analyzed by the SVD deconvolution algorithms, rCBV and rMTT could be useful imaging predictors of response to recanalization in patients with AIS, and the performances of these variables were similar to that of the ICV calculated by the Bayesian Vitrea.

Comparison of a Bayesian estimation algorithm and singular value decomposition algorithms for 80-detector row CT perfusion in patients with acute ischemic stroke

PURPOSE

A variety of postprocessing algorithms for CT perfusion are available, with substantial differences in terms of quantitative maps. Although potential advantages of a Bayesian estimation algorithm are suggested, direct comparison with other algorithms in clinical settings remains scarce. We aimed to compare performance of a Bayesian estimation algorithm and singular value decomposition (SVD) algorithms for the assessment of acute ischemic stroke using an 80-detector row CT perfusion.

METHODS

CT perfusion data of 36 patients with acute ischemic stroke were analyzed using the Vitrea implemented a standard SVD algorithm, a reformulated SVD algorithm and a Bayesian estimation algorithm. Correlations and statistical differences between affected and contralateral sides of quantitative parameters (cerebral blood volume [CBV], cerebral blood flow [CBF], mean transit time [MTT], time to peak [TTP] and delay) were analyzed. Agreement of the CT perfusion-estimated and the follow-up diffusion-weighted imaging-derived infarct volume were evaluated by nonparametric Passing-Bablok regression analysis.

RESULTS

CBF and MTT of the Bayesian estimation algorithm were substantially different and showed a better correlation with the standard SVD algorithm (ρ = 0.78 and 0.80, p < 0.001) than with the reformulated SVD algorithm (ρ = 0.59 and 0.39, p < 0.001). There is no significant difference in MTT only when using the reformulated SVD algorithm (p = 0.217). Regarding the regression lines, the slope and intercept were nearly ideal with the Bayesian estimation algorithm (y = 2.42 x-6.51; ρ = 0.60, p < 0.001) in comparison with the SVD algorithms.

CONCLUSIONS

The Bayesian estimation algorithm can lead to a better performance compared with the SVD algorithms in the assessment of acute ischemic stroke because of better delineation of abnormal perfusion areas and accurate estimation of infarct volume.

Cortical Blood Flow Insufficiency Scores with Computed Tomography Perfusion can Predict Outcomes in Aneurysmal Subarachnoid Hemorrhage Patients: A Cohort Study

BACKGROUND

The World Federation of Neurosurgical Societies (WFNS) scale is widely accepted for predicting outcomes for subarachnoid hemorrhage (SAH) patients. However, it is difficult to definitely predict outcomes for the most poor grade, WFNS grade 5. The present study aimed to investigate the prognostic ability of a novel classification using computed tomography perfusion (CTP) findings, called the cortical blood flow insufficiency (CBFI) scores.

METHODS

CTP was performed on admission for aneurysmal SAH followed by radical treatments within 72 hours of onset. Twenty-four cerebral cortex regions of interest (ROIs) were defined. CBFI was defined as Tmax > 4 s in each ROI, and CBFI scores were calculated based on the total number of ROIs with CBFI. Using the optimal cutoff value based on receiver operating characteristics (ROC) analysis to predict patient functional outcomes, CBFI scores were divided into "high" or "low" CBFI scores. Patient functional outcomes at 90 days were categorized based on modified Rankin Scale scores (0-3, favorable group; 4-6 unfavorable group) (0-4, non-catastrophic group; 5-6, catastrophic group).

RESULTS

Fifty-seven patients were included in this study, of whom 21 (36.8%) and 13 (22.8%) were in the unfavorable and the catastrophic groups, respectively. A factor predicting unfavorable and catastrophic outcomes was CBFI score cutoff value of 7 points (area under the curve, 0.73 and 0.81, respectively). In multivariable logistic regression analysis for unfavorable outcome, high CBFI scores (odds ratio (OR), 8.6; 95% confidence interval (CI), 1.1-65.4; P = 0.04) and WFNS grade 5 (OR, 30.0; 95% CI, 4.5-201.0; P < 0.001) remained as independent predictors, while for catastrophic outcome, high CBFI scores (OR, 25.3; 95% CI, 3.3-194.0; P = 0.002) and age (OR, 1.1; 95% CI, 1.0-1.2; P = 0.02) remained as independent predictors. Conversely, WFNS grade 5 was not an independent predictor of catastrophic outcomes (OR, 3.8; 95% CI, 0.6-24.0; P = 0.15). In high CBFI scores, the OR of the delayed cerebral ischemia (DCI) occurrence was 9.6 (95% CI, 1.5-61.4; P = 0.02) after adjusting for age.

CONCLUSION

High CBFI scores could predict unfavorable and catastrophic outcomes for aneurysmal SAH patients and DCI occurrence.

Preliminary study of time maximum intensity projection computed tomography imaging for the detection of early ischemic change in patient with acute ischemic stroke

Noncontrast computed tomography (NCCT) has been used for the detection of early ischemic change (EIC); however, correct interpretation of NCCT findings requires much clinical experience. This study aimed to assess the accuracy of time maximum intensity projection computed tomography technique (tMIP), which reflects the maximum value for the time phase direction from the dynamic volume data for each projected plane, for detection of EIC, against that of NCCT.Retrospective review of NCCT, cerebral blood volume in CT perfusion (CTP-CBV), and tMIP of 186 lesions from 280 regions evaluated by Alberta Stroke Program Early CT Score (ASPECTS) in 14 patients with acute middle cerebral artery stroke who had undergone whole-brain CTP using 320-row area detector CT was performed. Four radiologists reviewed EIC on NCCT, CTP-CBV, and tMIP in each ASPECTS region at onset using the continuous certainty factor method. Receiver operating characteristic analysis was performed to compare the relative performance for detection of EIC. The correlations were evaluated.tMIP-color showed the best discriminative value for detection of EIC. There were significant differences in the area under the curve for NCCT and tMIP-color, CTP-CBV (P < .05). Scatter plots of ASPECTS showed a positive significant correlation between NCCT, tMIP-gray, tMIP-color, and the follow-up study (NCCT, r = 0.32, P = .0166; tMIP-gray, r = 0.44, P = .0007; tMIP-color, r = 0.34, P = .0104).Because tMIP provides a high contrast parenchymal image with anatomical and vascular information in 1 sequential scan, it showed greater accuracy for detection of EIC and predicted the final infarct extent more accurately than NCCT based on ASPECTS.