CT perfusion cerebral blood volume does not always predict infarct core in acute ischemic stroke

Automated advanced imaging in acute ischemic stroke. Certainties and uncertainties

The purpose of this is study was to review pearls and pitfalls of advanced imaging, such as computed tomography perfusion and diffusion-weighed imaging and perfusion-weighted imaging in the selection of acute ischemic stroke (AIS) patients suitable for endovascular treatment (EVT) in the late time window (6-24 h from symptom onset). Advanced imaging can quantify infarct core and ischemic penumbra using specific threshold values and provides optimal selection parameters, collectively called target mismatch. More precisely, target mismatch criteria consist of core volume and/or penumbra volume and mismatch ratio (the ratio between total hypoperfusion and core volumes) with precise cut-off values. The parameters of target mismatch are automatically calculated with dedicated software packages that allow a quick and standardized interpretation of advanced imaging. However, this approach has several limitations leading to a misclassification of core and penumbra volumes. In fact, automatic software platforms are affected by technical artifacts and are not interchangeable due to a remarkable vendor-dependent variability, resulting in different estimate of target mismatch parameters. In addition, advanced imaging is not completely accurate in detecting infarct core, that can be under- or overestimated. Finally, the selection of candidates for EVT remains currently suboptimal due to the high rates of futile reperfusion and overselection caused by the use of very stringent inclusion criteria. For these reasons, some investigators recently proposed to replace advanced with conventional imaging in the selection for EVT, after the demonstration that non-contrast CT ASPECTS and computed tomography angiography collateral evaluation are not inferior to advanced images in predicting outcome in AIS patients treated with EVT. However, other authors confirmed that CTP and PWI/DWI postprocessed images are superior to conventional imaging in establishing the eligibility of patients for EVT. Therefore, the routine application of automatic assessment of advanced imaging remains a matter of debate. Recent findings suggest that the combination of conventional and advanced imaging might improving our selection criteria.

FDA-approved machine learning algorithms in neuroradiology: A systematic review of the current evidence for approval

Over the past decade, machine learning (ML) and artificial intelligence (AI) have become increasingly prevalent in the medical field. In the United States, the Food and Drug Administration (FDA) is responsible for regulating AI algorithms as "medical devices" to ensure patient safety. However, recent work has shown that the FDA approval process may be deficient. In this study, we evaluate the evidence supporting FDA-approved neuroalgorithms, the subset of machine learning algorithms with applications in the central nervous system (CNS), through a systematic review of the primary literature. Articles covering the 53 FDA-approved algorithms with applications in the CNS published in PubMed, EMBASE, Google Scholar and Scopus between database inception and January 25, 2022 were queried. Initial searches identified 1505 studies, of which 92 articles met the criteria for extraction and inclusion. Studies were identified for 26 of the 53 neuroalgorithms, of which 10 algorithms had only a single peer-reviewed publication. Performance metrics were available for 15 algorithms, external validation studies were available for 24 algorithms, and studies exploring the use of algorithms in clinical practice were available for 7 algorithms. Papers studying the clinical utility of these algorithms focused on three domains: workflow efficiency, cost savings, and clinical outcomes. Our analysis suggests that there is a meaningful gap between the FDA approval of machine learning algorithms and their clinical utilization. There appears to be room for process improvement by implementation of the following recommendations: the provision of compelling evidence that algorithms perform as intended, mandating minimum sample sizes, reporting of a predefined set of performance metrics for all algorithms and clinical application of algorithms prior to widespread use. This work will serve as a baseline for future research into the ideal regulatory framework for AI applications worldwide.

Assessment Precision of CT Perfusion Imaging in the Detection of Acute Ischemic Stroke: A Systematic Review and Meta-Analysis

Stroke, a prevalent medical emergency, comprises ischemic and hemorrhagic subtypes, with acute ischemic stroke (AIS) being a predominant type. The application of computed tomography perfusion (CTP) imaging has gained prominence due to its rapidity and accessibility in stroke evaluation. This study systematically reviews and conducts a meta-analysis of existing literature to assess the diagnostic accuracy of CTP in detecting AIS and predicting hemorrhagic transformation (HT). Employing Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, an extensive search was conducted across electronic databases and relevant radiology journals. Studies conducted between 2007 and 2023 that fulfilled predetermined inclusion criteria underwent quality assessment using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS 2) tool. Cochrane diagnostic accuracy tools were used for data extraction. Thirteen studies involving a total of 1014 patients were included in the analysis. The diagnostic performance of CTP in predicting HT demonstrated high sensitivity (86.7%) and moderate specificity (77.8%), resulting in an overall accuracy of 79.1%. The negative predictive value (NPV) was notably high (92.9%), signifying its efficacy in excluding patients at risk of HT. The positive predictive value (PPV) was comparatively lower (60.3%), highlighting the need for clinical context when making thrombolysis decisions. The false positive rate was 16.2%, while the false negative rate was minimal (9.8%). Subgroup analysis underscored consistent sensitivity and specificity across diverse imaging metrics. The findings of this study emphasize the promising diagnostic accuracy of CTP imaging in predicting HT subsequent to AIS. This non-invasive technique can aid treatment decisions and patient management strategies. By effectively assessing perfusion status and offering predictive insights, CTP imaging improves stroke intervention choices, especially in identifying patients with a lower risk of HT.

Quantifying infarct core volume in ischemic stroke: What is the optimal threshold and parameters of computed tomography perfusion?

OBJECTIVE

Although computed tomography perfusion (CTP) is used to select and guide decision-making processes in patients with acute ischemic stroke, there is no clear standardization of the optimal threshold to predict ischemic core volume accurately. The infarct core volume with a relative cerebral blood flow(rCBF) threshold of < 30% is commonly used. We aimed to assess the volumetric agreement of the infarct core volume with different CTP parameters and thresholds using CTP software (RAPID, VITREA) and the infarct volume on diffusion-weighted imaging (DWI), with a short interval time (within 60 min) between CTP and follow-up DWI.

MATERIALS AND METHODS

This retrospective study included 42 acute ischemic stroke patients with occlusion of the large artery in the anterior circulation between April 2017-November 2020. RAPID identified infarct core as tissue rCBF < 20-38%. VITREA defined the infarct core as cerebral blood volume (CBV) < 26-56%. Olea Sphere was used to measure infarct core volume on DWI. The CTP-infarct core volume with different thresholds of perfusion parameters (CBF threshold vs CBV threshold) were compared with DWI-infarct core volumes.

RESULTS

The median time between CTP and DWI was 37.5min. The commonly used threshold of CBV< 41% (4.3 mL) resulted in lower median infarct core volume difference compared to the commonly used thresholds of rCBF < 30% (8.2mL). On the other hand, the optimal thresholds of CBV < 26% (-1.0mL; 95% CI, -53.9 to 58.1 mL; 0.945) resulted in the lowest median infarct core volume difference, narrowest limits of agreement, and largest interclass correlation coefficient compared with the optimal thresholds of rCBF < 38% (4.9 mL; 95% CI, -36.4 to 62.9 mL; 0.939).

CONCLUSION

Our study found that the both optimal and commonly used thresholds of CBV provided a more accurate prediction of the infarct core volume in patients with AIS than rCBF.

Can angiographic Flat Detector Computed Tomography blood volume measurement be used to predict final infarct size in acute ischemic stroke?

INTRODUCTION AND PURPOSE

Flat detector computed tomography (FD-CT) technology is becoming more widely available in the angiography suites of comprehensive stroke centers. In patients with acute ischemic stroke (AIS), who are referred for endovascular therapy (EVT), FD-CT generates cerebral pooled blood volume (PBV) maps, which might help in predicting the final infarct area. We retrospectively analyzed pre- and post-recanalization therapy quantitative PBV measurements in both the infarcted and hypoperfused brain areas of AIS patients referred for EVT.

MATERIALS AND METHODS

We included AIS patients with large vessel occlusion in the anterior circulation referred for EVT from primary stroke centers to our comprehensive stroke center. The pre- and post-recanalization FD-CT regional relative PBV (rPBV) values were measured between ipsilateral lesional and contralateral non-lesional areas based on final infarct area on post EVT follow-up cross-sectional imaging. Statistical analysis was performed to identify differences in PBV values between infarcted and non-infarcted, recanalized brain areas.

RESULTS

We included 20 AIS patients. Mean age was 63 years (ranging from 36 to 86 years). The mean pre- EVT rPBV value was 0.57 (±0.40) for infarcted areas and 0.75 (±0.43) for hypoperfusion areas. The mean differences (Δ) between pre- and post-EVT rPBV values for infarcted and hypoperfused areas were respectively 0.69 (±0.59) and 0.69 (±0.90). We found no significant differences (p > 0.05) between pre-EVT rPBV and ΔrPBV values of infarct areas and hypoperfusion areas.

CONCLUSION

Angiographic PBV mapping is useful for the detection of cerebral perfusion deficits, especially in combination with the fill run images. However, we were not able to distinguish irreversibly infarcted tissue from potentially salvageable, hypoperfused brain tissue based on quantitative PBV measurement in AIS patients.

Evaluation of collateral status and outcome in patients with middle cerebral artery stenosis in late time window by CT perfusion imaging

Objectives

Collateral status (CS) is a crucial determinant of outcome in patients with ischemic stroke. We aimed to test whether the cerebral blood volume (CBV) and cerebral blood flow (CBF) based on computed tomography perfusion (CTP) measurements can quantitatively evaluate CS and explore the predictive ability of CTP parameters in determining clinical outcomes in patients with MCA severe stenosis or occlusion presenting beyond 24 h.

Materials and methods

In this retrospective study, data obtained from September 2018 to March 2022 in consecutive stroke patients caused by isolated middle cerebral artery severe stenosis or occlusion were reviewed within 24–72 h after onset. Correlation between the collateral score systems assessed with CT angiography (CTA) and CTP parameters was calculated using the Spearman correlation. The optimal threshold of the CBV ratio for predicting a good outcome was determined using receiver operating characteristic curve (ROC) analysis.

Results

A total of 69 patients met inclusion criteria. Both the CBV ratio and the CBF ratio had significant correlation with collateral score systems assessed with CTA [CBV ratio and Tan score: rs = 0.702, P &lt; 0.0001; CBV ratio and regional leptomeningeal collateral (rLMC) score: rs = 0.705, P &lt; 0.0001; CBV ratio and Miteff score: rs = 0.625, P &lt; 0.0001. CBF ratio and Tan score: rs= 0.671, P &lt; 0.0001; CBF ratio and rLMC score: rs = 0.715, P &lt; 0.0001; CBF ratio and Miteff score: rs = 0.535, P &lt; 0.0001]. ROC analysis revealed the CBV ratio performed better than the qualitative collateral assessments and the CBF ratio in the prediction of a favorable 90-day modified Rankin scale score. The CBV ratio was a useful parameter that predicted a good functional outcome [area under the curve (AUC), 0.922; 95% CI, 0.862 ± 0.982].

Conclusions

In late time window stroke patients, the CBV and CBF ratio on CTP may be valuable parameters for quantitatively revealing the collateral status after stroke. In addition, the CBV ratio was the predictor of clinical outcomes in patients with MCA severe stenosis or occlusion.

Flat Detector CT with Cerebral Pooled Blood Volume Perfusion in the Angiography Suite: From Diagnostics to Treatment Monitoring

C-arm flat-panel detector computed tomographic (CT) imaging in the angiography suite increasingly plays an important part during interventional neuroradiological procedures. In addition to conventional angiographic imaging of blood vessels, flat detector CT (FD CT) imaging allows simultaneous 3D visualization of parenchymal and vascular structures of the brain. Next to imaging of anatomical structures, it is also possible to perform FD CT perfusion imaging of the brain by means of cerebral blood volume (CBV) or pooled blood volume (PBV) mapping during steady state contrast administration. This enables more adequate decision making during interventional neuroradiological procedures, based on real-time insights into brain perfusion on the spot, obviating time consuming and often difficult transportation of the (anesthetized) patient to conventional cross-sectional imaging modalities. In this paper we review the literature about the nature of FD CT PBV mapping in patients and demonstrate its current use for diagnosis and treatment monitoring in interventional neuroradiology.

Multimodal CT pc-ASPECTS in infratentorial stroke: diagnostic and prognostic value

BACKGROUND AND PURPOSE

Diagnosis of posterior circulation stroke may be challenged. National Institutes of Health Stroke Scale (NIHSS) and brain imaging (non-contrast brain computed tomography-CT) are used for diagnosis; evaluation on posterior circulation stroke remains a limit of NIHSS, and the value of non-contrast CT (NCCT) is limited due to artifacts caused by the bones of the base of the skull. We tested the validity and prognostic value of posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) in patients with posterior circulation stroke.

METHODS

Pc-ASPECTS allots the posterior circulation 10 points. We studied 50 patients with posterior circulation stroke. We applied pc-ASPECTS to NCCT, CT angiography, and CT Perfusion. We evaluated the correlation of pc-ASPECT with outcome parameters for stroke.

RESULTS

Out of 50 patients, CTP showed abnormalities in 34 cases. The pc-ASPECT score calculated on brain CT and on the brain CT + angio CT had a sensibility of 24%, calculated on brain CT, angio CT and CTPerfusion gain a sensibility of 72%. Pc-ASPECT MTT resulted to be the more reliable parameter: outcome given by NIHSS score at discharge, mRS at discharge, and at 3 months was more severe in patients with Pc-ASPECT MTT alteration. Outcome given by NIHSS score at discharge and mRS at discharge and 1 at 3 months was more severe in patients with higher NIHSS score at admission.

CONCLUSION

We evaluated the usefulness of pc-ASPECTS on CTP in predicting functional outcome in acute posterior circulation stroke that appears to be a powerful marker for predicting functional outcome.

Qualitative versus automatic evaluation of CT perfusion parameters in acute posterior circulation ischaemic stroke

Purpose

To compare the diagnostic accuracy (ACC) in the detection of acute posterior circulation strokes between qualitative evaluation of software-generated colour maps and automatic assessment of CT perfusion (CTP) parameters.

Methods

Were retrospectively collected 50 patients suspected of acute posterior circulation stroke who underwent to CTP (GE “Lightspeed”, 64 slices) within 24 h after symptom onset between January 2016 and December 2018. The Posterior circulation-Acute Stroke Prognosis Early CT Score (pc-ASPECTS) was used for quantifying the extent of ischaemic areas on non-contrast (NC)CT and colour-coded maps generated by CTP4 (GE) and RAPID (iSchemia View) software. Final pc-ASPECTS was calculated on follow-up NCCT and/or MRI (Philips Intera 3.0 T or Philips Achieva Ingenia 1.5 T). RAPID software also elaborated automatic quantitative mismatch maps.

Results

By qualitative evaluation of colour-coded maps, MTT-CTP4D and Tmax-RAPID showed the highest sensitivity (SE) (88.6% and 90.9%, respectively) and ACC (84% and 88%, respectively) compared with the other perfusion parameters (CBV, CBF). Baseline NCCT and CBF provided by RAPID quantitative perfusion mismatch maps had the lowest SE (29.6% and 6.8%, respectively) and ACC (38% and 18%, respectively). CBF and Tmax assessment provided by quantitative RAPID perfusion mismatch maps showed significant lower SE and ACC than qualitative evaluation. No significant differences were found between the pc-ASPECTSs assessed on colour-coded MTT and Tmax maps neither between the scores assessed on colour-coded CBV-CTP4D and CBF-RAPID maps.

Conclusion

Qualitative analysis of colour-coded maps resulted more sensitive and accurate in the detection of ischaemic changes than automatic quantitative analysis.

Diagnostic accuracy of computed tomography perfusion in the prediction of haemorrhagic transformation and patient outcome in acute ischaemic stroke: A systematic review and meta-analysis

Purpose

The aim of this systematic review and meta-analysis is to determine the diagnostic accuracy of computed tomography brain perfusion in the prediction of haemorrhagic transformation and patient outcome in acute ischaemic stroke.

Method

Electronic databases and grey literature published over the last 10 years related to healthcare and radiology were searched using the key terms: 'computed tomography perfusion', 'haemorrhagic transformation', 'acute ischaemic stroke', 'functional outcome' and their synonyms using both UK and American spellings. Inclusion criteria were: sample size at least 30 patients, original research, evaluate ability of computed tomography perfusion to predict haemorrhagic transformation, reports diagnostic accuracy or provide relevant data for a 2 × 2 contingency table, use follow-up non-contrast computed tomography (NCCT) or magnetic resonance imaging as reference standard.

Findings

Twelve studies were included in the review; studies cover a total of 808 patients. Haemorrhagic transformation occurred in 30.2% of patients. Pooled sensitivity and specificity were 85.9% (95% CI; 65-97%), 73.9% (95% CI; 45-92%) and accuracy of 79.1% (95% CI; 57-98%). Pooled NPV was 92.9% with a high false positive rate (19.8%), which could be explained in terms of outcome classification, acquisition artefact and computed tomography perfusion processing algorithms.

Discussion

This review evaluated the importance of using pre-defined threshold measurement for optimal prediction of HT, the relevance of patient pre-treatment clinical parameters to HT occurrence, the CTP parameters and the measurements that are independent predictors of HT, the significance of rtPA rather as an exacerbator of HT and the impact of both minor and major HT/PH on patient 2⁰ functional outcome.

Conclusion

Computed tomography perfusion has a high sensitivity and moderately high specificity for prediction of haemorrhagic transformation in acute ischaemic stroke. Pre-treatment clinical decision making requires consideration of clinical factors in addition to imaging findings. This systematic review and meta-analysis highlights that pre-treatment computed tomography perfusion adds to clinical confidence by predicting potential for haemorrhage, both in thrombolysed and un-thrombolysed patients, and also influences decisions about alternative treatments for acute ischaemic stroke patients.

Effect of intravenous alteplase on ischaemic lesion water homeostasis

BACKGROUND AND PURPOSE

Intravenous (IV) lysis with alteplase is known to increase biomarkers of blood-brain barrier breakdown and has therefore been associated with secondary injuries such as hemorrhagic transformation. The impact of alteplase on brain edema formation, however, has not been investigated yet. The purpose was to examine the effects of IV alteplase on ischaemic lesion water homeostasis differentiated from final tissue infarct in patients with and without successful endovascular therapy (sET).

METHODS

In all, 232 middle cerebral artery stroke patients were analyzed. 147 patients received IV alteplase, of whom 106 patients received subsequent sET. Out of 85 patients without IV alteplase, 50 received sET. Ischaemic brain edema was quantified at admission and follow-up computed tomography using quantitative lesion net water uptake (NWU) and its difference was calculated (ΔNWU). The relationship of alteplase on ΔNWU and edema-corrected final infarct volume was analyzed using univariate and multivariate linear regression models.

RESULTS

The mean ΔNWU was 11.8% (SD 7.9) in patients with alteplase and 11.5% (SD 8.3) in patients without alteplase (P = 0.8). Alteplase was not associated with lowered ΔNWU whilst being associated with reduced edema-corrected tissue infarct volume [-27.4 ml, 95% confidence interval (CI) -49.4 to -5.4 ml; P = 0.02], adjusted for the Alberta Stroke Program Early Computed Tomography Score and recanalization status. In patients with sET, ΔNWU was 10.5% (95% CI 6.3%-10.5%) for patients with IV alteplase and 8.4% (95% CI 9.1%-12.0%) for patients without IV alteplase.

CONCLUSION

The application of IV alteplase did not significantly alter ischaemic lesion water homeostasis but was associated with reduced edema-corrected tissue infarct volume, which might be directly linked to improved functional outcome.

Technical considerations of multi-parametric tissue outcome prediction methods in acute ischemic stroke patients

Decisions regarding acute stroke treatment rely heavily on imaging, but interpretation can be difficult for physicians. Machine learning methods can assist clinicians by providing tissue outcome predictions for different treatment approaches based on acute multi-parametric imaging. To produce such clinically viable machine learning models, factors such as classifier choice, data normalization, and data balancing must be considered. This study gives comprehensive consideration to these factors by comparing the agreement of voxel-based tissue outcome predictions using acute imaging and clinical parameters with manual lesion segmentations derived from follow-up imaging. This study considers random decision forest, generalized linear model, and k-nearest-neighbor machine learning classifiers in conjunction with three data normalization approaches (non-normalized, relative to contralateral hemisphere, and relative to contralateral VOI), and two data balancing strategies (full dataset and stratified subsampling). These classifier settings were evaluated based on 90 MRI datasets from acute ischemic stroke patients. Distinction was made between patients recanalized using intraarterial and intravenous methods, as well as those without successful recanalization. For primary quantitative comparison, the Dice metric was computed for each voxel-based tissue outcome prediction and its corresponding follow-up lesion segmentation. It was found that the random forest classifier outperformed the generalized linear model and the k-nearest-neighbor classifier, that normalization did not improve the Dice score of the lesion outcome predictions, and that the models generated lesion outcome predictions with higher Dice scores when trained with balanced datasets. No significant difference was found between the treatment groups (intraarterial vs intravenous) regarding the Dice score of the tissue outcome predictions.

Evolving Treatments for Acute Ischemic Stroke

The purpose of this article is to review advances in stroke treatment in the hyperacute period. With recent evolutions of technology in the fields of imaging, thrombectomy devices, and emergency room workflow management, as well as improvement in statistical methods and study design, there have been ground breaking changes in the treatment of acute ischemic stroke. We describe how stroke presents as a clinical syndrome and how imaging as the most important biomarker will help differentiate between stroke subtypes and treatment eligibility. The evolution of hyperacute treatment has led to the current standard of care: intravenous thrombolysis with tissue-type plasminogen activator and endovascular treatment for proximal vessel occlusion in the anterior cerebral circulation. All patients with acute ischemic stroke are in need of hyperacute secondary prevention because the risk of recurrence is highest closest to the index event. The dominant themes of modern stroke care are the use of neurovascular imaging and speed of diagnosis and treatment.

Cerebral Blood Volume ASPECTS Is the Best Predictor of Clinical Outcome in Acute Ischemic Stroke: A Retrospective, Combined Semi-Quantitative and Quantitative Assessment

Introduction

The capability of CT perfusion (CTP) Alberta Stroke Program Early CT Score (ASPECTS) to predict outcome and identify ischemia severity in acute ischemic stroke (AIS) patients is still questioned.

Methods

62 patients with AIS were imaged within 8 hours of symptom onset by non-contrast CT, CT angiography and CTP scans at admission and 24 hours. CTP ASPECTS was calculated on the affected hemisphere using cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) maps by subtracting 1 point for any abnormalities visually detected or measured within multiple cortical circular regions of interest according to previously established thresholds. MTT-CBV ASPECTS was considered as CTP ASPECTS mismatch. Hemorrhagic transformation (HT), recanalization status and reperfusion grade at 24 hours, final infarct volume at 7 days and modified Rankin scale (mRS) at 3 months after onset were recorded.

Results

Semi-quantitative and quantitative CTP ASPECTS were highly correlated (p<0.00001). CBF, CBV and MTT ASPECTS were higher in patients with no HT and mRS≤2 and inversely associated with final infarct volume and mRS (p values: from p<0.05 to p<0.00001). CTP ASPECTS mismatch was slightly associated with radiological and clinical outcomes (p values: from p<0.05 to p<0.02) only if evaluated quantitatively. A CBV ASPECTS of 9 was the optimal semi-quantitative value for predicting outcome.

Conclusions

Our findings suggest that visual inspection of CTP ASPECTS recognizes infarct and ischemic absolute values. Semi-quantitative CBV ASPECTS, but not CTP ASPECTS mismatch, represents a strong prognostic indicator, implying that core extent is the main determinant of outcome, irrespective of penumbra size.