Variation in CT perfusion protocol has implications on defining irreversibly damaged ischemic brain parenchyma

The collateral map: prediction of lesion growth and penumbra after acute anterior circulation ischemic stroke

OBJECTIVES

This study evaluated the collateral map's ability to predict lesion growth and penumbra after acute anterior circulation ischemic strokes.

METHODS

This was a retrospective analysis of selected data from a prospectively collected database. The lesion growth ratio was the ratio of the follow-up lesion volume to the baseline lesion volume on diffusion-weighted imaging (DWI). The time-to-maximum (Tmax)/DWI ratio was the ratio of the baseline Tmax  > 6 s volume to the baseline lesion volume. The collateral ratio was the ratio of the hypoperfused lesion volume of the phase_FU (phase with the hypoperfused lesions most approximate to the follow-up DWI lesion) to the hypoperfused lesion volume of the phase_baseline of the collateral map. Multiple logistic regression analyses were conducted to identify independent predictors of lesion growth. The concordance correlation coefficients of Tmax/DWI ratio and collateral ratio for lesion growth ratio were analyzed.

RESULTS

Fifty-two patients, including twenty-six males (mean age, 74 years), were included. Intermediate (OR, 1234.5; p < 0.001) and poor collateral perfusion grades (OR, 664.7; p = 0.006) were independently associated with lesion growth. Phase_FUs were immediately preceded phases of the phase_baselines in intermediate or poor collateral perfusion grades. The concordance correlation coefficients of the Tmax/DWI ratio and collateral ratio for the lesion growth ratio were 0.28 (95% CI, 0.17-0.38) and 0.88 (95% CI, 0.82-0.92), respectively.

CONCLUSION

Precise prediction of lesion growth and penumbra can be possible using collateral maps, allowing for personalized application of recanalization treatments. Further studies are needed to generalize the findings of this study.

CLINICAL RELEVANCE STATEMENT

Precise prediction of lesion growth and penumbra can be possible using collateral maps, allowing for personalized application of recanalization treatments.

KEY POINTS

• Cell viability in cerebral ischemia due to proximal arterial steno-occlusion mainly depends on the collateral circulation. • The collateral map shows salvageable brain extent, which can survive by recanalization treatments after acute anterior circulation ischemic stroke. • Precise estimation of salvageable brain makes it possible to make patient-specific treatment decision.

Standardizing the estimation of ischemic regions can harmonize CT perfusion stroke imaging

OBJECTIVES

We aimed to evaluate the real-world variation in CT perfusion (CTP) imaging protocols among stroke centers and to explore the potential for standardizing vendor software to harmonize CTP images.

METHODS

Stroke centers participating in a nationwide multicenter healthcare evaluation were requested to share their CTP scan and processing protocol. The impact of these protocols on CTP imaging was assessed by analyzing data from an anthropomorphic phantom with center-specific vendor software with default settings from one of three vendors (A-C): IntelliSpace Portal, syngoVIA, and Vitrea. Additionally, standardized infarct maps were obtained using a logistic model.

RESULTS

Eighteen scan protocols were studied, all varying in acquisition settings. Of these protocols, seven, eight, and three were analyzed with center-specific vendor software A, B, and C respectively. The perfusion maps were visually dissimilar between the vendor software but were relatively unaffected by the acquisition settings. The median error [interquartile range] of the infarct core volumes (mL) estimated by the vendor software was - 2.5 [6.5] (A)/ - 18.2 [1.2] (B)/ - 8.0 [1.4] (C) when compared to the ground truth of the phantom (where a positive error indicates overestimation). Taken together, the median error [interquartile range] of the infarct core volumes (mL) was - 8.2 [14.6] before standardization and - 3.1 [2.5] after standardization.

CONCLUSIONS

CTP imaging protocols varied substantially across different stroke centers, with the perfusion software being the primary source of differences in CTP images. Standardizing the estimation of ischemic regions harmonized these CTP images to a degree.

CLINICAL RELEVANCE STATEMENT

The center that a stroke patient is admitted to can influence the patient's diagnosis extensively. Standardizing vendor software for CT perfusion imaging can improve the consistency and accuracy of results, enabling a more reliable diagnosis and treatment decision.

KEY POINTS

• CT perfusion imaging is widely used for stroke evaluation, but variation in the acquisition and processing protocols between centers could cause varying patient diagnoses. • Variation in CT perfusion imaging mainly arises from differences in vendor software rather than acquisition settings, but these differences can be reconciled by standardizing the estimation of ischemic regions. • Standardizing the estimation of ischemic regions can improve CT perfusion imaging for stroke evaluation by facilitating reliable evaluations independent of the admission center.

A retrospective study of non-equidistant interstitial brain CT perfusion scanning and prediction of time to peak

Background

Eexploring the limits of CT cranial perfusion scan acquisition intervals and predicting time to peak.

Methods

A retrospective analysis was conducted on 45 patients with suspected stroke who underwent brain CTP scans. Different sampling intervals were set based on the TDC. The patients were divided into four groups: Group 1 underwent continuous scanning with a uniform interval of 1.5 s; Group 2 had a uniform interval of 3 s; Group 3 had a 1.5-s interval between arterial and venous peak vertices with 1 point retained before and after the peak for 1.5 s and with a remaining acquisition interval of 4.5 s; and Group 4 had a uniform interval of 4.5 s. Statistical analysis was performed on the perfusion parameters of each group. Additionally, in 286 patients who underwent head and neck CTA examinations, the peak time of contrast medium was recorded, and the peak time was predicted based on factors such as age, height, weight, heart rate, systolic blood pressure, diastolic blood pressure, triglycerides, and total cholesterol. The results compared with Group 1 and Group 2, as well as Group 1 and Group 3, the P values of CBF, CBV, MTT, and Tmax in the left and right cerebral hemispheres of healthy subjects and in the infarct and noninfarct areas of patients were all >0.05. A comparison between Group 1 and Group 4 showed that right cerebral hemisphere CBF and CBV, left cerebral hemisphere CBF, CBV, and Tmax, infarct area CBV and Tmax, and noninfarct area CBF, CBV, and MTT had P values > 0.05, while other groups all had P values < 0.05. Bland‒Altman analysis showed that the perfusion parameters in Group 1 were consistent with those in Group 2, and those in Group 1 were consistent with those in Group 3. The radiation doses in the second and third groups were lower, and the dose in the third group was lower than that in the second group.

Conclusion

Continuous acquisition between the peak points of the arterial and venous phases, with 1 point reserved before and after the peak and a 4.5-s interval for the rest, represents the maximum time interval for CTP scanning and can effectively reduce the radiation dose. The formula Tmax (s) = 0.290 × height (cm) - 0.226 × heart rate (times/min) + 0.216 × age (years) - 1.901 × triglycerides (mmol/L) - 0.061 × systolic blood pressure (mmHg) - 7.216 (R2 = 0.449, F = 17.905, P < 0.01) was established for predicting time to peak enhancement.

Initial CT Imaging Predicts Mortality in Severe Traumatic Brain Injuries in Pediatric Population-A Systematic Review and Meta-Analysis

The purpose of this systematic review was to analyze evidence based on existing studies on the ability of initial CT imaging to predict mortality in severe traumatic brain injuries (TBIs) in pediatric patients. An experienced librarian searched for all existing studies based on the inclusion and exclusion criteria. The studies were screened by two blinded reviewers. Of the 3277 studies included in the search, data on prevalence of imaging findings and mortality rate could only be extracted from 22 studies. A few of those studies had patient-specific data relating specific imaging findings to outcome, allowing the data analysis, calculation of the area under the curve (AUC) and receiver operating characteristic (ROC), and generation of a forest plot for each finding. The data were extracted to calculate the sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predicted value (NPV), AUC, and ROC for extradural hematoma (EDH), subdural hematoma (SDH), traumatic subarachnoid hemorrhage (tSAH), skull fractures, and edema. There were a total of 2219 patients, 747 females and 1461 males. Of the total, 564 patients died and 1651 survived; 293 patients had SDH, 76 had EDH, 347 had tSAH, 244 had skull fractures, and 416 had edema. The studies included had high bias and lower grade of evidence. Out of the different CT scan findings, brain edema had the highest SN, PPV, NPV, and AUC. EDH had the highest SP to predict in-hospital mortality.

Probability maps classify ischemic stroke regions more accurately than CT perfusion summary maps

OBJECTIVES

To compare single parameter thresholding with multivariable probabilistic classification of ischemic stroke regions in the analysis of computed tomography perfusion (CTP) parameter maps.

METHODS

Patients were included from two multicenter trials and were divided into two groups based on their modified arterial occlusive lesion grade. CTP parameter maps were generated with three methods-a commercial method (ISP), block-circulant singular value decomposition (bSVD), and non-linear regression (NLR). Follow-up non-contrast CT defined the follow-up infarct region. Conventional thresholds for individual parameter maps were established with a receiver operating characteristic curve analysis. Probabilistic classification was carried out with a logistic regression model combining the available CTP parameters into a single probability.

RESULTS

A total of 225 CTP data sets were included, divided into a group of 166 patients with successful recanalization and 59 with persistent occlusion. The precision and recall of the CTP parameters were lower individually than when combined into a probability. The median difference [interquartile range] in mL between the estimated and follow-up infarct volume was 29/23/23 [52/50/52] (ISP/bSVD/NLR) for conventional thresholding and was 4/6/11 [31/25/30] (ISP/bSVD/NLR) for the probabilistic classification.

CONCLUSIONS

Multivariable probability maps outperform thresholded CTP parameter maps in estimating the infarct lesion as observed on follow-up non-contrast CT. A multivariable probabilistic approach may harmonize the classification of ischemic stroke regions.

KEY POINTS

• Combining CTP parameters with a logistic regression model increases the precision and recall in estimating ischemic stroke regions. • Volumes following from a probabilistic analysis predict follow-up infarct volumes better than volumes following from a threshold-based analysis. • A multivariable probabilistic approach may harmonize the classification of ischemic stroke regions.