Automated assessment of ischemic core on non-contrast computed tomography: a multicenter comparative analysis with CT perfusion.

BACKGROUND: Application of machine learning (ML) algorithms has shown promising results in estimating ischemic core volumes using non-contrast CT (NCCT). OBJECTIVE: To assess the performance of the e-Stroke Suite software (Brainomix) in assessing ischemic core volumes on NCCT compared with CT perfusion (CTP) in patients with acute ischemic stroke. METHODS: In this retrospective multicenter study, patients with anterior circulation large vessel occlusions who underwent pretreatment NCCT and CTP, successful reperfusion (modified Thrombolysis in Cerbral Infarction ≥2b), and post-treatment MRI, were included from three stroke centers. Automated calculation of ischemic core volumes was obtained on NCCT scans using ML algorithm deployed by e-Stroke Suite and from CTP using Olea software (Olea Medical). Comparative analysis was performed between estimated core volumes on NCCT and CTP and against MRI calculated final infarct volume (FIV). RESULTS: A total of 111 patients were included. Estimated ischemic core volumes (mean±SD, mL) were 20.4±19.0 on NCCT and 19.9±18.6 on CTP, not significantly different (P=0.82). There was moderate (r=0.40) and significant (P<0.001) correlation between estimated core on NCCT and CTP. The mean difference between FIV and estimated core volume on NCCT and CTP was 29.9±34.6 mL and 29.6±35.0 mL, respectively (P=0.94). Correlations between FIV and estimated core volume were similar for NCCT (r=0.30, P=0.001) and CTP (r=0.36, P<0.001). CONCLUSIONS: Results show that ML-based estimated ischemic core volumes on NCCT are comparable to those obtained from concurrent CTP in magnitude and in degree of correlation with MR-assessed FIV.

Perfusion Collateral Index versus Hypoperfusion Intensity Ratio in Assessment of Collaterals in Patients with Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Perfusion-based collateral indices such as the perfusion collateral index and the hypoperfusion intensity ratio have shown promise in the assessment of collaterals in patients with acute ischemic stroke. We aimed to compare the diagnostic performance of the perfusion collateral index and the hypoperfusion intensity ratio in collateral assessment compared with angiographic collaterals and outcome measures, including final infarct volume, infarct growth, and functional independence. MATERIALS AND METHODS: Consecutive patients with acute ischemic stroke with anterior circulation proximal arterial occlusion who underwent endovascular thrombectomy and had pre- and posttreatment MRI were included. Using pretreatment MR perfusion, we calculated the perfusion collateral index and the hypoperfusion intensity ratio for each patient. The angiographic collaterals obtained from DSA were dichotomized to sufficient (American Society of Interventional and Therapeutic Neuroradiology [ASITN] scale 3-4) versus insufficient (ASITN scale 0-2). The association of collateral status determined by the perfusion collateral index and the hypoperfusion intensity ratio was assessed against angiographic collaterals and outcome measures. RESULTS: A total of 98 patients met the inclusion criteria. Perfusion collateral index values were significantly higher in patients with sufficient angiographic collaterals (P < .001), while there was no significant (P = .46) difference in hypoperfusion intensity ratio values. Among patients with good (mRS 0-2) versus poor (mRS 3-6) functional outcome, the perfusion collateral index of ≥ 62 was present in 72% versus 31% (P = .003), while the hypoperfusion intensity ratio of ≤0.4 was present in 69% versus 56% (P = .52). The perfusion collateral index and the hypoperfusion intensity ratio were both significantly predictive of final infarct volume, but only the perfusion collateral index was significantly (P = .03) associated with infarct growth. CONCLUSIONS: Results show that the perfusion collateral index outperforms the hypoperfusion intensity ratio in the assessment of collateral status, infarct growth, and determination of functional outcomes.

Grey Matter Reshaping of Language-Related Regions Depends on Tumor Lateralization.

A brain tumor in the left hemisphere can decrease language laterality as assessed through fMRI. However, it remains unclear whether or not this decreased language laterality is associated with a structural reshaping of the grey matter, particularly within the language network. Here, we examine if the disruption of the language hubs exclusively affects the macrostructural properties of the contralateral homologues or whether it affects both hemispheres. This study uses voxel-based morphometry applied to high-resolution MR T1-weighted MPRAGE images from 31 adult patients' left hemisphere, which is dominant for language. Eighteen patients had brain tumors in the left hemisphere, and thirteen had tumors in the right hemisphere. A cohort of 71 healthy individuals matched with respect to age and sex was used as a baseline. We defined 10 ROIs per hemisphere involved in language function. Two separate repeated-measure ANOVAs were conducted with the volume per region as the dependent variable. For the patients, tumor lateralization (right versus left) served as a between-subject factor. The current study demonstrated that the presence of a brain tumor generates global volumetric changes affecting the left language regions and their contralateral homologues. These changes are mediated by the lateralization of the lesion. Our findings suggest that functional mechanisms are supported by the rearrangement of the grey matter.

Grey matter reshaping of language-related regions depends on tumor lateralization.

A brain tumor in the left hemisphere can decrease language laterality as assessed with fMRI. However, it remains unclear whether or not this decreased language laterality is associated with a structural reshaping of the grey matter, particularly within the language network. Here, we examine if the disruption of language hubs exclusively affects macrostructural properties of contralateral homologues (as suggested by previous research), or whether it affects both hemispheres. This study uses voxel-based morphometry applied to high-resolution MR T1-weighted MPRAGE images from 31 adult patients left-dominant for language. Eighteen patients had brain tumors in the left hemisphere, and 13 had tumors in the right hemisphere. A cohort of 71 healthy individuals matched on age and sex was used as a baseline. We defined 10 ROIs per hemisphere known to subserve language function. Two separate repeated-measures ANOVAs were conducted with the volume per region as the dependent variables. For the patients, tumor lateralization (right versus left) served as a between-subject factor. The current study demonstrated that the presence of a brain tumor generates a global volumetric change affecting left language regions and their contralateral homologues. These changes are mediated by the lateralization of the lesion. Our findings suggest that compensatory functional mechanisms are supported by the rearrangement of the grey matter, although future longitudinal research should determine the temporal course of such changes.

Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning.

BACKGROUND: Accurate estimation of ischemic core on baseline imaging has treatment implications in patients with acute ischemic stroke (AIS). Machine learning (ML) algorithms have shown promising results in estimating ischemic core using routine noncontrast computed tomography (NCCT). OBJECTIVE: We used an ML-trained algorithm to quantify ischemic core volume on NCCT in a comparative analysis to pretreatment magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) in patients with AIS. METHODS: Patients with AIS who had both pretreatment NCCT and MRI were enrolled. An automatic segmentation ML approach was applied using Brainomix software (Oxford, UK) to segment the ischemic voxels and calculate ischemic core volume on NCCT. Ischemic core volume was also calculated on baseline MRI DWI. Comparative analysis was performed using Bland-Altman plots and Pearson correlation. RESULTS: A total of 72 patients were included. The time-to-stroke onset time was 134.2/89.5 minutes (mean/median). The time difference between NCCT and MRI was 64.8/44.5 minutes (mean/median). In patients who presented within 1 hour from stroke onset, the ischemic core volumes were significantly (p = 0.005) underestimated by ML-NCCT. In patients presented beyond 1 hour, the ML-NCCT estimated ischemic core volumes approximated those obtained by MRI-DWI and with significant correlation (r = 0.56, p < 0.001). CONCLUSION: The ischemic core volumes calculated by the described ML approach on NCCT approximate those obtained by MRI in patients with AIS who present beyond 1 hour from stroke onset.

MR Angiography in Assessment of Collaterals in Patients with Acute Ischemic Stroke: A Comparative Analysis with Digital Subtraction Angiography.

Collateral status has prognostic and treatment implications in acute ischemic stroke (AIS) patients. Unlike CTA, grading collaterals on MRA is not well studied. We aimed to evaluate the accuracy of assessing collaterals on pretreatment MRA in AIS patients against DSA. AIS patients with anterior circulation proximal arterial occlusion with baseline MRA and subsequent endovascular treatment were included. MRA collaterals were evaluated by two neuroradiologists independently using the Tan and Maas scoring systems. DSA collaterals were evaluated by using the American Society of Interventional and Therapeutic Neuroradiology grading system and were used as the reference for comparative analysis against MRA. A total of 104 patients met the inclusion criteria (59 female, age (mean ± SD): 70.8 ± 18.1). The inter-rater agreement (k) for collateral scoring was 0.49, 95% CI 0.37-0.61 for the Tan score and 0.44, 95% CI 0.26-0.62 for the Maas score. Total number (%) of sufficient vs. insufficient collaterals based on DSA was 49 (47%) and 55 (53%) respectively. Using the Tan score, 45% of patients with sufficient collaterals and 64% with insufficient collaterals were correctly identified in comparison to DSA, resulting in a poor agreement (0.09, 95% CI 0.1-0.28). Using the Maas score, only 4% of patients with sufficient collaterals and 93% with insufficient collaterals were correctly identified against DSA, resulting in poor agreement (0.03, 95% CI 0.06-0.13). Pretreatment MRA in AIS patients has limited concordance with DSA when grading collaterals using the Tan and Maas scoring systems.

Refining epileptogenic high-frequency oscillations using deep learning: a reverse engineering approach.

Intracranially recorded interictal high-frequency oscillations have been proposed as a promising spatial biomarker of the epileptogenic zone. However, its visual verification is time-consuming and exhibits poor inter-rater reliability. Furthermore, no method is currently available to distinguish high-frequency oscillations generated from the epileptogenic zone (epileptogenic high-frequency oscillations) from those generated from other areas (non-epileptogenic high-frequency oscillations). To address these issues, we constructed a deep learning-based algorithm using chronic intracranial EEG data via subdural grids from 19 children with medication-resistant neocortical epilepsy to: (i) replicate human expert annotation of artefacts and high-frequency oscillations with or without spikes, and (ii) discover epileptogenic high-frequency oscillations by designing a novel weakly supervised model. The 'purification power' of deep learning is then used to automatically relabel the high-frequency oscillations to distill epileptogenic high-frequency oscillations. Using 12 958 annotated high-frequency oscillation events from 19 patients, the model achieved 96.3% accuracy on artefact detection (F1 score = 96.8%) and 86.5% accuracy on classifying high-frequency oscillations with or without spikes (F1 score = 80.8%) using patient-wise cross-validation. Based on the algorithm trained from 84 602 high-frequency oscillation events from nine patients who achieved seizure-freedom after resection, the majority of such discovered epileptogenic high-frequency oscillations were found to be ones with spikes (78.6%, P < 0.001). While the resection ratio of detected high-frequency oscillations (number of resected events/number of detected events) did not correlate significantly with post-operative seizure freedom (the area under the curve = 0.76, P = 0.06), the resection ratio of epileptogenic high-frequency oscillations positively correlated with post-operative seizure freedom (the area under the curve = 0.87, P = 0.01). We discovered that epileptogenic high-frequency oscillations had a higher signal intensity associated with ripple (80-250 Hz) and fast ripple (250-500 Hz) bands at the high-frequency oscillation onset and with a lower frequency band throughout the event time window (the inverted T-shaped), compared to non-epileptogenic high-frequency oscillations. We then designed perturbations on the input of the trained model for non-epileptogenic high-frequency oscillations to determine the model's decision-making logic. The model confidence significantly increased towards epileptogenic high-frequency oscillations by the artificial introduction of the inverted T-shaped signal template (mean probability increase: 0.285, P < 0.001), and by the artificial insertion of spike-like signals into the time domain (mean probability increase: 0.452, P < 0.001). With this deep learning-based framework, we reliably replicated high-frequency oscillation classification tasks by human experts. Using a reverse engineering technique, we distinguished epileptogenic high-frequency oscillations from others and identified its salient features that aligned with current knowledge.

Gadolinium deposition within the paediatric brain: no increased intrinsic T1-weighted signal intensity within the dentate nucleus following the administration of a minimum of four doses of the macrocyclic agent gadobutrol.

OBJECTIVES: To determine whether repeated administration of the macrocyclic gadolinium-based contrast agent (GBCA) gadobutrol in children is associated with T1-weighted hyperintensity within the dentate nucleus, an imaging surrogate for gadolinium deposition. METHODS: With institutional review board approval, we identified a cohort of eight patients aged 18 years or younger who underwent at least four gadobutrol-enhanced magnetic resonance imaging (MRI) examinations of the brain from 2013 to 2017. For comparison, we identified a cohort of 19 patients who underwent at least four gadopentetate dimeglumine-enhanced MRI examinations. For each examination, both dentate nuclei were contoured on unenhanced images; the mean dentate-to-pons signal intensity (DN-P SI) ratio was calculated. DN-P SI ratios from the first and last MRI exams were compared using Wilcoxon signed ranks tests and linear regression analyses. RESULTS: In the gadobutrol cohort, there was no significant change in the mean DN-P SI ratio from the first to the last scan (1.02 vs 1.02, p = 1.00). In the gadopentetate dimeglumine cohort, there was a significant increase in the mean DN-P SI ratio from the first to the last scan (1.05 vs 1.13, p = 0.003). After controlling for potentially confounding variables, the change in DN-P SI ratio from the first to the last scan was significantly lower for patients in the gadobutrol group than in the gadopentetate dimeglumine group (ß = -0.08, p = 0.04). CONCLUSIONS: Repeated administration of the macrocyclic GBCA gadobutrol in children was not associated with T1-weighted dentate hyperintensity, while the repeated administration of the linear GBCA gadopentetate dimeglumine was associated with T1-weighted dentate hyperintensity, presumably due to gadolinium deposition. KEY POINTS: • Gadolinium-based contrast agents are routinely used in magnetic resonance imaging. • Repeated administration of the macrocyclic agent gadobutrol in children was not associated with T1-weighted dentate hyperintensity.

Regulation of estrogen receptor signaling in breast carcinogenesis and breast cancer therapy.

Estrogen and estrogen receptors (ERs) are critical regulators of breast epithelial cell proliferation, differentiation, and apoptosis. Compromised signaling vis-à-vis the estrogen receptor is believed to be a major contributing factor in the malignancy of breast cells. Targeting the ER signaling pathway has been a focal point in the development of breast cancer therapy. Although approximately 75 % of breast cancer patients are classified as luminal type (ER(+)), which predicts for response to endocrine-based therapy; however, innate or acquired resistance to endocrine-based drugs remains a serious challenge. The complexity of regulation for estrogen signaling coupled with the crosstalk of other oncogenic signaling pathways is a reason for endocrine therapy resistance. Alternative strategies that target novel molecular mechanisms are necessary to overcome this current and urgent gap in therapy. A thorough analysis of estrogen-signaling regulation is critical. In this review article, we will summarize current insights into the regulation of estrogen signaling as related to breast carcinogenesis and breast cancer therapy.

Regional and voxel-wise comparisons of blood flow measurements between dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) and arterial spin labeling (ASL) in brain tumors.

The objective of the current study was to evaluate the regional and voxel-wise correlation between dynamic susceptibility contrast (DSC) and arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) measurement of cerebral blood flow (CBF) in patients with brain tumors. Thirty patients with histologically verified brain tumors were evaluated in the current study. DSC-MRI was performed by first using a preload dose of gadolinium contrast, then collecting a dynamic image acquisition during a bolus of contrast, followed by posthoc contrast agent leakage correction. Pseudocontinuous ASL was collected using 30 pairs of tag and control acquisition using a 3-dimensional gradient-echo spin-echo (GRASE) acquisition. All images were registered to a high-resolution anatomical atlas. Average CBF measurements within regions of contrast-enhancement and T2 hyperintensity were evaluated between the two modalities. Additionally, voxel-wise correlation between CBF measurements obtained with DSC and ASL were assessed. Results demonstrated a positive linear correlation between DSC and ASL measurements of CBF when regional average values were compared; however, a statistically significant voxel-wise correlation was only observed in around 30-40% of patients. These results suggest DSC and ASL may provide regionally similar, but spatially different measurements of CBF.

Multi-delay multi-parametric arterial spin-labeled perfusion MRI in acute ischemic stroke - Comparison with dynamic susceptibility contrast enhanced perfusion imaging.

The purpose of the present study was to present a multi-delay multi-parametric pseudo-continuous arterial spin labeling (pCASL) protocol with background suppressed 3D GRASE (gradient and spin echo) readout for perfusion imaging in acute ischemic stroke. PCASL data at 4 post-labeling delay times (PLD = 1.5, 2, 2.5, 3 s) were acquired within 4.5 min in 24 patients (mean age 79.7 ± 11.4 years; 11 men) with acute middle cerebral artery (MCA) stroke who also underwent dynamic susceptibility contrast (DSC) enhanced perfusion imaging. Arterial transit times (ATT) were estimated through the calculation of weighted delays across the 4 PLDs, which were included in the calculation of cerebral blood flow (CBF) and arterial cerebral blood volume (CBV). Mean perfusion parameters derived using pCASL and DSC were measured within MCA territories and infarct regions identified on diffusion weighted MRI. The results showed highly significant correlations between pCASL and DSC CBF measurements (r > = 0.70, p < = 0.0001) and moderately significant correlations between pCASL and DSC CBV measurements (r > = 0.45, p < = 0.027) in both MCA territories and infarct regions. ASL ATT showed correlations with DSC time to the maximum of tissue residual function (Tmax)(r = 0.66, p = 0.0005) and mean transit time (MTT)(r = 0.59, p = 0.0023) in leptomeningeal MCA territories. The present study demonstrated the feasibility for noninvasive multi-parametric perfusion imaging using ASL for acute stroke imaging.

The value of arterial spin-labeled perfusion imaging in acute ischemic stroke: comparison with dynamic susceptibility contrast-enhanced MRI.

BACKGROUND AND PURPOSE: The purpose of this study was to evaluate the potential clinical value of arterial spin-labeled (ASL) perfusion MRI in acute ischemic stroke (AIS) through comparison with dynamic susceptibility contrast (DSC) enhanced perfusion MRI. METHODS: Pseudocontinuous ASL with 3-dimensional background-suppressed gradient and spin echo readout was applied with DSC perfusion MRI on 26 patients with AIS. ASL cerebral blood flow and multiparametric DSC perfusion maps were rated for image quality and lesion severity/conspicuity. Mean ASL cerebral blood flow and DSC perfusion values were obtained in main vascular territories. Kendall coefficient of concordance was calculated to evaluate the reliability of ratings. Spearman correlation coefficients were calculated to compare ratings and quantitative perfusion values between ASL and DSC perfusion maps. RESULTS: ASL cerebral blood flow and DSC perfusion maps provided largely consistent results in delineating hypoperfused brain regions in AIS. Hyperemic lesions, which also appeared frequently in the AIS cases studied, were more conspicuous on ASL cerebral blood flow than on DSC cerebral blood flow, mean transit time and time to the maximum of the tissue residual function maps. CONCLUSIONS: As a rapid, noninvasive, and quantitative technique, ASL has clinical use in detecting blood flow abnormalities in patients with AIS.

The murine cardiac 26S proteasome: an organelle awaiting exploration.

Multiprotein complexes have been increasingly recognized as essential functional units for a variety of cellular processes, including the protein degradation system. Selective degradation of proteins in eukaryotes is primarily conducted by the ubiquitin proteasome system. The current knowledge base, pertaining to the proteasome complexes in mammalian cells, relies largely upon information gained in the yeast system, where the 26S proteasome is hypothesized to contain a 20S multiprotein core complex and one or two 19S regulatory complexes. To date, the molecular structure of the proteasome system, the proteomic composition of the entire 26S multiprotein complexes, and the specific designated function of individual components within this essential protein degradation system in the heart remain virtually unknown. A functional proteomic approach, employing multidimensional chromatography purification combined with liquid chromatography tandem mass spectrometry and protein chemistry, was utilized to explore the murine cardiac 26S proteasome system. This article presents an overview on the subject of protein degradation in mammalian cells. In addition, this review shares the limited information that has been garnered thus far pertaining to the molecular composition, function, and regulation of this important organelle in the cardiac cells.