Gadolinium Retention and Nephrotoxicity in a Mouse Model of Acute Ischemic Stroke: Linear Versus Macrocyclic Agents

BACKGROUND

Gadolinium (Gd)-based contrast agents (GBCAs) have been widely used for acute ischemic stroke (AIS) patients. GBCAs or AIS alone may cause the adverse effects on kidney tissue, respectively. However, whether GBCAs and AIS would generate a synergistic negative effect remains undefined.

PURPOSE

To evaluate synergistic negative effects of AIS and GBCAs on renal tissues in a mouse model of AIS, and to compare the differences of these negative effects between linear and macrocyclic GBCAs.

STUDY TYPE

Animal study.

ANIMAL MODEL

Seventy-two healthy mice underwent transient middle cerebral artery occlusion (tMCAO) and sham operation to establish AIS and sham model (N = 36/model). 5.0 mmol/kg GBCAs (gadopentetate or gadobutrol) or 250 μL saline were performed at 4.5 hours and 1 day after model establishing (N = 12/group).

ASSESSMENT

Inductively coupled plasma mass spectrometry (ICP-MS) was performed to detect Gd concentrations. Serum biochemical analyzer was performed to measure the serum creatinine (Scr), uric acid (UA), and blood urea nitrogen (BUN). Pathological staining was performed to observe tubular injury, cell apoptosis, mesangial hyperplasia, and interstitial fibrosis.

STATISTICAL TESTS

Two-way analysis of variances with post hoc Sidak's tests and independent-samples t-tests were performed. A P-value <0.05 was considered statistically significant.

RESULTS

AIS groups showed higher Gd concentration than sham group on day 1 p.i. regardless of gadopentetate or gadobutrol used. Increased total Gd concentration was also found in AIS + gadopentetate group compared with the sham group on day 28 p.i. Significantly higher rates for renal dysfunction, higher tubular injury scores, and higher numbers of apoptotic cells on days 1 or 28 p.i. were found for AIS mice injected with GBCA. AIS + gadopentetate group displayed more severe renal damage than the AIS + gadobutrol group.

DATA CONCLUSION

AIS and GBCAs may cause increased total Gd accumulation and nephrotoxicity in a mouse, especially linear GBCAs were used.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 4.

Long-Term Effect of Mechanical Thrombectomy in Stroke Patients According to Advanced Imaging Characteristics

PURPOSE

Data on long-term effect of mechanical thrombectomy (MT) in patients with large ischemic cores (≥ 70 ml) are scarce. Our study aimed to assess the long-term outcomes in MT-patients according to baseline advanced imaging parameters.

METHODS

We performed a single-centre retrospective cohort study of stroke patients receiving MT between January 1, 2010 and December 31, 2018. We assessed baseline imaging to determine core and mismatch volumes and hypoperfusion intensity ratio (with low ratio reflecting good collateral status) using RAPID automated post-processing software. Main outcomes were cross-sectional long-term mortality, functional outcome and quality of life by May 2020. Analysis were stratified by the final reperfusion status.

RESULTS

In total 519 patients were included of whom 288 (55.5%) have deceased at follow-up (median follow-up time 28 months, interquartile range 1-55). Successful reperfusion was associated with lower long-term mortality in patients with ischemic core volumes ≥ 70 ml (adjusted hazard ratio (aHR) 0.20; 95% confidence interval (95% CI) 0.10-0.44) and ≥ 100 ml (aHR 0.26; 95% CI 0.08-0.87). The effect of successful reperfusion on long-term mortality was significant only in the presence of relevant mismatch (aHR 0.17; 95% CI 0.01-0.44). Increasing reperfusion grade was associated with a higher rate of favorable outcomes (mRS 0-3) also in patients with ischemic core volume ≥ 70 ml (aOR 3.58, 95% CI 1.64-7.83).

CONCLUSION

Our study demonstrated a sustainable benefit of better reperfusion status in patients with large ischemic core volumes. Our results suggest that patient deselection based on large ischemic cores alone is not advisable.

Ultrafast Brain MRI with Deep Learning Reconstruction for Suspected Acute Ischemic Stroke

Background Deep learning (DL)-accelerated MRI can substantially reduce examination times. However, studies prospectively evaluating the diagnostic performance of DL-accelerated MRI reconstructions in acute suspected stroke are lacking. Purpose To investigate the interchangeability of DL-accelerated MRI with conventional MRI in patients with suspected acute ischemic stroke at 1.5 T. Materials and Methods In this prospective study, 211 participants with suspected acute stroke underwent clinically indicated MRI at 1.5 T between June 2022 and March 2023. For each participant, conventional MRI (including T1-weighted, T2-weighted, T2*-weighted, T2 fluid-attenuated inversion-recovery, and diffusion-weighted imaging; 14 minutes 18 seconds) and DL-accelerated MRI (same sequences; 3 minutes 4 seconds) were performed. The primary end point was the interchangeability between conventional and DL-accelerated MRI for acute ischemic infarction detection. Secondary end points were interchangeability regarding the affected vascular territory and clinically relevant secondary findings (eg, microbleeds, neoplasm). Three readers evaluated the overall occurrence of acute ischemic stroke, affected vascular territory, clinically relevant secondary findings, overall image quality, and diagnostic confidence. For acute ischemic lesions, size and signal intensities were assessed. The margin for interchangeability was chosen as 5%. For interrater agreement analysis and interrater reliability analysis, multirater Fleiss κ and the intraclass correlation coefficient, respectively, was determined. Results The study sample consisted of 211 participants (mean age, 65 years ± 16 [SD]); 123 male and 88 female). Acute ischemic stroke was confirmed in 79 participants. Interchangeability was demonstrated for all primary and secondary end points. No individual equivalence indexes (IEIs) exceeded the interchangeability margin of 5% (IEI, -0.002 [90% CI: -0.007, 0.004]). Almost perfect interrater agreement was observed (P > .91). DL-accelerated MRI provided higher overall image quality (P < .001) and diagnostic confidence (P < .001). The signal properties of acute ischemic infarctions were similar in both techniques and demonstrated good to excellent interrater reliability (intraclass correlation coefficient, ≥0.8). Conclusion Despite being four times faster, DL-accelerated brain MRI was interchangeable with conventional MRI for acute ischemic lesion detection. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Haller in this issue.

Cerebral Microvascular Perfusion Assessed in Elderly Adults by Spin-Echo Dynamic Susceptibility Contrast MRI at 7 Tesla

Perfusion measures of the total vasculature are commonly derived with gradient-echo (GE) dynamic susceptibility contrast (DSC) MR images, which are acquired during the early passes of a contrast agent. Alternatively, spin-echo (SE) DSC can be used to achieve specific sensitivity to the capillary signal. For an improved contrast-to-noise ratio, ultra-high-field MRI makes this technique more appealing to study cerebral microvascular physiology. Therefore, this study assessed the applicability of SE-DSC MRI at 7 T. Forty-one elderly adults underwent 7 T MRI using a multi-slice SE-EPI DSC sequence. The cerebral blood volume (CBV) and cerebral blood flow (CBF) were determined in the cortical grey matter (CGM) and white matter (WM) and compared to values from the literature. The relation of CBV and CBF with age and sex was investigated. Higher CBV and CBF values were found in CGM compared to WM, whereby the CGM-to-WM ratios depended on the amount of largest vessels excluded from the analysis. CBF was negatively associated with age in the CGM, while no significant association was found with CBV. Both CBV and CBF were higher in women compared to men in both CGM and WM. The current study verifies the possibility of quantifying cerebral microvascular perfusion with SE-DSC MRI at 7 T.

Deep Learning-Based Synthetic TOF-MRA Generation Using Time-Resolved MRA in Fast Stroke Imaging

BACKGROUND AND PURPOSE

Time-resolved MRA enables collateral evaluation in acute ischemic stroke with large-vessel occlusion; however, a low SNR and spatial resolution impede the diagnosis of vascular occlusion. We developed a CycleGAN-based deep learning model to generate high-resolution synthetic TOF-MRA images using time-resolved MRA and evaluated its image quality and clinical efficacy.

MATERIALS AND METHODS

This retrospective, single-center study included 397 patients who underwent both TOF- and time-resolved MRA between April 2021 and January 2022. Patients were divided into 2 groups for model development and image-quality validation. Image quality was evaluated qualitatively and quantitatively with 3 sequences. A multireader diagnostic optimality evaluation was performed by 16 radiologists. For clinical validation, we evaluated 123 patients who underwent fast stroke MR imaging to assess acute ischemic stroke. The diagnostic confidence level and decision time for large-vessel occlusion were also evaluated.

RESULTS

Median values of overall image quality, noise, sharpness, venous contamination, and SNR for M1, M2, the basilar artery, and posterior cerebral artery are better with synthetic TOF than with time-resolved MRA. However, with respect to real TOF, synthetic TOF presents worse median values of overall image quality, sharpness, vascular conspicuity, and SNR for M3, the basilar artery, and the posterior cerebral artery. During the multireader evaluation, radiologists could not discriminate synthetic TOF images from TOF images. During clinical validation, both readers demonstrated increases in diagnostic confidence levels and decreases in decision time.

CONCLUSIONS

A CycleGAN-based deep learning model was developed to generate synthetic TOF from time-resolved MRA. Synthetic TOF can potentially assist in the detection of large-vessel occlusion in stroke centers using time-resolved MRA.

Prognostic value of multiphase CT angiography: estimated infarct core volume in the patients with acute ischaemic stroke after mechanical thrombectomy

BACKGROUND AND PURPOSE

Recent studies reported the feasibility of quantifying a reliable infarct core (IC) volume using multiphase computed tomography (mCTA) based on deep learning, however its prognostic value was not fully clarified. Therefore, we aimed to evaluate the prognostic value of mCTA-estimated IC volume in patients with acute ischemic stroke (AIS) after mechanical thrombectomy (MT).

MATERIALS AND METHODS

We retrospectively reviewed patients who underwent mCTA and MT for large vessel occlusion in middle cerebral artery and (or) internal carotid artery within 6 hours after symptom onset between January 2018 and November 2019. Patients were dichotomized into good (modified Rankin Scale [mRS] score, 0-2) and poor (mRS, 3-6) outcome groups. mCTA-estimated IC volume were generated based on a multi-scale three-dimensional convolutional neural network. Univariate, multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were used to identify the independent variables, and evaluate their performances in predicting the clinical outcome.

RESULTS

Of 44 included patients, 27 (61.4%) patients achieved good outcome. National Institutes of Health Stroke Scale scores at admission [NIHSSpre] (odds ratio [OR], 1.191; 95%confidence interval [CI], 1.028-1.379; P=0.020) and mCTA-estimated IC volume (OR, 1.076; 95%CI, 1.016-1.140; P=0.013) were found to be independently associated with functional outcome in patients with AIS after MT. After integrating NIHSSpre and mCTA-estimated IC volume, optimal performance (area under the ROC curve, 0.874; 95%CI, 0.739-0.954) could be obtained in predicting the clinical outcome.

CONCLUSIONS

mCTA-estimated IC volume might be promising for predicting the prognosis, and assisting in making individualized treatment decision in patients with AIS.

Neuroimaging Modalities Used for Ischemic Stroke Diagnosis and Monitoring

Strokes are one of the global leading causes of physical or mental impairment and fatality, classified into hemorrhagic and ischemic strokes. Ischemic strokes happen when a thrombus blocks or plugs an artery and interrupts or reduces blood supply to the brain tissue. Deciding on the imaging modality which will be used for stroke detection depends on the expertise and availability of staff and the infrastructure of hospitals. Magnetic resonance imaging provides valuable information, and its sensitivity for smaller infarcts is greater, while computed tomography is more extensively used, since it can promptly exclude acute cerebral hemorrhages and is more favorable speed-wise. The aim of this article was to give information about the neuroimaging modalities used for the diagnosis and monitoring of ischemic strokes. We reviewed the available literature and presented the use of computed tomography, CT angiography, CT perfusion, magnetic resonance imaging, MR angiography and MR perfusion for the detection of ischemic strokes and their monitoring in different phases of stroke development.

PerfU-Net: Baseline infarct estimation from CT perfusion source data for acute ischemic stroke

CT perfusion imaging is commonly used for infarct core quantification in acute ischemic stroke patients. The outcomes and perfusion maps of CT perfusion software, however, show many discrepancies between vendors. We aim to perform infarct core segmentation directly from CT perfusion source data using machine learning, excluding the need to use the perfusion maps from standard CT perfusion software. To this end, we present a symmetry-aware spatio-temporal segmentation model that encodes the micro-perfusion dynamics in the brain, while decoding a static segmentation map for infarct core assessment. Our proposed spatio-temporal PerfU-Net employs an attention module on the skip-connections to match the dimensions of the encoder and decoder. We train and evaluate the method on 94 and 62 scans, respectively, using the Ischemic Stroke Lesion Segmentation (ISLES) 2018 challenge data. We achieve state-of-the-art results compared to methods that only use CT perfusion source imaging with a Dice score of 0.46. We are almost on par with methods that use perfusion maps from third party software, whilst it is known that there is a large variation in these perfusion maps from various vendors. Moreover, we achieve improved performance compared to simple perfusion map analysis, which is used in clinical practice.

Time-Based Decision Making for Reperfusion in Acute Ischemic Stroke

Decision making in the extended time windows for acute ischemic stroke can be a complex and time-consuming process. The process of making the clinical decision to treat has been compounded by the availability of different imaging modalities. In the setting of acute ischemic stroke, time is of the essence and chances of a good outcome diminish by each passing minute. Navigating the plethora of advanced imaging modalities means that treatment in some cases can be inefficaciously delayed. Time delays and individually based non-programmed decision making can prove challenging for clinicians. Visual aids can assist such decision making aimed at simplifying the use of advanced imaging. Flow charts are one such visual tool that can expedite treatment in this setting. A systematic review of existing literature around imaging modalities based on site of occlusion and time from onset can be used to aid decision making; a more program-based thought process. The use of an acute reperfusion flow chart helping navigate the myriad of imaging modalities can aid the effective treatment of patients.

Central Nervous System Injury in Patients With Severe Acute Respiratory Syndrome Coronavirus 2: MRI Findings

Due to the presence of a new and rapidly spreading coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the World Health Organization declared the coronavirus disease 2019 (COVID-19) outbreak a pandemic on March 11, 2020. This new disease has a multisystemic effect that predominantly targets the respiratory system; however, neurologic symptoms have been documented in approximately 36% of patients with confirmed COVID-19. During the period of March 2020 to March 2021, 481 brain MRI studies were performed by medical request. Of these, 9.7% (n = 47) were hospitalized with a diagnosis of COVID-19 pneumonia confirmed by SARS-CoV-2 reverse transcriptase-polymerase chain reaction (RT-PCR) test with the following findings: microbleeds, osmotic demyelination, arterial thrombosis, ischemic infarcts, venous thrombosis, metabolic cerebellar syndrome, posterior reversible leukoencephalopathy, abnormal signal intensity in the frontal lobes and olfactory bulbs, microangiopathy, gliosis, and findings consistent with hypoxic-ischemic encephalopathy. In patients with histories of malignant central nervous system (CNS) tumors, the most frequent histological lineage being high-grade glioma, 100% progression was identified with respect to previous imaging studies, without other significant findings. In two patients, a brain MRI was performed due to altered alertness, identifying only involutive changes in the brain parenchyma; MRI was repeated 72 hours later, after a lack of improvement in higher functions, without identifying imaging findings. To date, limited studies have documented CNS abnormalities related to COVID-19 using MRI. Therefore, the purpose of this study is to present abnormal imaging findings in patients with SARS-CoV-2 infection and their clinical correlations.

Automated Collateral Flow Assessment in Patients with Acute Ischemic Stroke Using Computed Tomography with Artificial Intelligence Algorithms

BACKGROUND

Collateral circulation is associated with improved functional outcome in patients with large vessel occlusion acute ischemic stroke (AIS) who undergo reperfusion therapy. Assessment of collateral flow can be time consuming, subjective, and difficult because of complex neurovasculature. This study assessed the ability of multiple artificial intelligence algorithms in determining collateral flow of patients with AIS.

METHODS

Two hundred patients with AIS between March 2019 and January 2020 were included in this retrospective study. Peak arterial computed tomography perfusion volumes were used to assess collateral scores. Neural networks were developed for dichotomized (≥50% or <50%) and multiclass (0% filling, 0%-50% filling, 50%-100% filling, or 100% filling) collateral scoring. Maximum intensity projections from axial and anteroposterior (AP) views were synthesized for each bone subtracted three-dimensional volume and used as network inputs separately and together, along with three-dimensional data. Training:testing:validation splits of 60:30:10 and 20 iterations of Monte Carlo cross-validation were used. Network performance was assessed using 95% confidence intervals of accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

The axial and AP input combination provided the most accurate results for dichotomized classification: accuracy, 0.85 ± 0.01; sensitivity, 0.88 ± 0.02; specificity, 0.82 ± 0.03; PPV, 0.86 ± 0.02; and NPV, 0.83 ± 0.03. Similarly, the axial and AP input combination provided the best results for multiclass classification: accuracy, 0.80 ± 0.01; sensitivity, 0.64 ± 0.01; specificity, 0.85 ± 0.01; PPV, 0.65 ± 0.02; and NPV, 0.85 ± 0.01.

CONCLUSIONS

This study reports one of the first artificial intelligence-based algorithms capable of accurately and efficiently assessing collateral flow of patients with AIS. This automated method for determining collateral filling could streamline clinical workflow, reduce bias, and aid in clinical decision making for determining reperfusion-eligible patients.

Value of Perfusion CT in the Prediction of Intracerebral Hemorrhage after Endovascular Treatment

Background

Intracerebral hemorrhage (ICH) is a serious complication of endovascular treatment (EVT) in stroke patients with large vessel occlusion (LVO) and associated with increased morbidity and mortality.

Aims

Identification of radiological predictors is highly relevant. We investigated the predictive power of computed tomography perfusion (CTP) parameters concerning ICH in patients receiving EVT.

Methods

392 patients with anterior circulation LVO with multimodal CT imaging who underwent EVT were analyzed. CTP parameters were visually evaluated for modified ASPECTS regions and compared between patients without ICH, those with hemorrhagic infarction (HI), and those with parenchymal hematoma (PH) according to the ECASS criteria at follow-up imaging and broken down by ASPECTS regions.

Results

168 received intravenous thrombolysis (IV-rtPA), and 115 developed subsequent ICH (29.3%), of which 74 were classified as HI and 41 as PH. Patients with HI and PH had lower ASPECTS than patients without ICH and worse functional outcome after 90 days (p < 0.05). In 102 of the 115 patients with ICH, the deep middle cerebral artery (MCA) territory was affected with differences between patients without ICH, those with HI, and those with PH regarding cerebral blood volume (CBV) and blood-brain barrier permeability measured as flow extraction product (FED) relative to the contralateral hemisphere (p < 0.05). Patients with PH showed larger perfusion CT infarct core than patients without ICH (p < 0.01).

Conclusion

None of the examined CTP parameters was found to be a strong predictor of subsequent ICH. ASPECTS and initial CTP core volume were more reliable and may be useful and even so more practicable to assess the risk of subsequent ICH after EVT.

Controversies in Imaging of Patients with Acute Ischemic Stroke: AJR Expert Panel Narrative Review

The development of reperfusion therapies has profoundly impacted stroke care, initially with the advent of IV thrombolytic (IVT) treatment and, more recently, with the development and refinement of endovascular treatment (EVT). Progress in neuroimaging has supported the paradigm shift of stroke care, and advanced neuroimaging now has a fundamental role in triaging patients for both IVT and EVT. As the standard of care for acute ischemic stroke (AIS) evolves, controversies remain in certain clinical scenarios. This article explores the use of multimodality imaging for treatment selection of AIS in the context of recent guidelines, highlighting controversial topics and providing guidance for clinical practice. Results of major randomized trials supporting EVT are reviewed. Advantages and disadvantages of CT, CTA, MRI, and MRA in stroke diagnosis are summarized, with attention to level 1 evidence supporting the role of vascular imaging and perfusion imaging. Patient selection is compared between approaches based on time thresholds and physiologic approaches based on infarct core measurement using imaging. Moreover, various imaging approaches to core measurement are described. As ongoing studies push treatment boundaries, advanced imaging is expected to help identify a widening range of patients who may benefit from therapy.

Reliability and accuracy of 3-mm and 2-mm maximum intensity projection CT angiography to detect intracranial large vessel occlusion in patients with acute anterior cerebral circulation stroke

PURPOSE

To evaluate the reliability and accuracy of thick maximum intensity projection (MIP) CTA images to detect large-vessel occlusion (LVO) in the anterior circulation in patients with acute stroke.

METHODS

A total of 140 acute stroke patients (41 with and 99 without LVO) were evaluated by two neuroradiologists for LVO using axial 3-mm and 2-mm MIPs.

RESULTS

Interobserver agreement was substantial using 3-mm MIPs (ĸ = 0.67) and almost perfect using 2-mm MIPs (ĸ = 0.82). Using 3-mm MIPs, sensitivities were 80.5% and 68.3%, with specificities of 98.0% and 96.0%. Using 2-mm MIPs, sensitivities were 82.9% and 73.2%, with specificities of 98.0% and 99.0%. Sensitivity and specificity of 3 mm and 2 mm MIPs were not statistically significantly different (P ≥ 0.375). The majority of LVOs in the distal intracranial carotid artery, and/or M1-segment were correctly identified: 96.0% (observer 1, 3-mm MIPs), 88.0% (observer 2, 3-mm MIPs), 96.0% (observer 1, 2-mm MIPs), and 96.0% (observer 2, 2 mm MIPs). Using 3-mm MIP images, observers 1 and 2 missed 7/15 (46.7%) and 9/15 (60.0%) of isolated M2-segment occlusions, respectively. Using 2-mm MIP images, observers 1 and 2 missed 5/15 (33.3%) and 6/15 (40.0%) of isolated M2-segment occlusions, respectively.

CONCLUSION

Thick (2-3 mm) axial MIPs are not useful to detect proximal LVO in the anterior circulation.