Random expert sampling for deep learning segmentation of acute ischemic stroke on non-contrast CT.

BACKGROUND: Outlining acutely infarcted tissue on non-contrast CT is a challenging task for which human inter-reader agreement is limited. We explored two different methods for training a supervised deep learning algorithm: one that used a segmentation defined by majority vote among experts and another that trained randomly on separate individual expert segmentations. METHODS: The data set consisted of 260 non-contrast CT studies in 233 patients with acute ischemic stroke recruited from the multicenter DEFUSE 3 (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke 3) trial. Additional external validation was performed using 33 patients with matched stroke onset times from the University Hospital Lausanne. A benchmark U-Net was trained on the reference annotations of three experienced neuroradiologists to segment ischemic brain tissue using majority vote and random expert sampling training schemes. The median of volume, overlap, and distance segmentation metrics were determined for agreement in lesion segmentations between (1) three experts, (2) the majority model and each expert, and (3) the random model and each expert. The two sided Wilcoxon signed rank test was used to compare performances (1) to 2) and (1) to (3). We further compared volumes with the 24 hour follow-up diffusion weighted imaging (DWI, final infarct core) and correlations with clinical outcome (modified Rankin Scale (mRS) at 90 days) with the Spearman method. RESULTS: The random model outperformed the inter-expert agreement ((1) to (2)) and the majority model ((1) to (3)) (dice 0.51±0.04 vs 0.36±0.05 (P<0.0001) vs 0.45±0.05 (P<0.0001)). The random model predicted volume correlated with clinical outcome (0.19, P<0.05), whereas the median expert volume and majority model volume did not. There was no significant difference when comparing the volume correlations between random model, median expert volume, and majority model to 24 hour follow-up DWI volume (P>0.05, n=51). CONCLUSION: The random model for ischemic injury delineation on non-contrast CT surpassed the inter-expert agreement ((1) to (2)) and the performance of the majority model ((1) to (3)). We showed that the random model volumetric measures of the model were consistent with 24 hour follow-up DWI.

Measuring Quantitative Cerebral Blood Flow in Healthy Children: A Systematic Review of Neuroimaging Techniques.

Cerebral blood flow (CBF) is an important hemodynamic parameter to evaluate brain health. It can be obtained quantitatively using medical imaging modalities such as magnetic resonance imaging and positron emission tomography (PET). Although CBF in adults has been widely studied and linked with cerebrovascular and neurodegenerative diseases, CBF data in healthy children are sparse due to the challenges in pediatric neuroimaging. An understanding of the factors affecting pediatric CBF and its normal range is crucial to determine the optimal CBF measuring techniques in pediatric neuroradiology. This review focuses on pediatric CBF studies using neuroimaging techniques in 32 articles including 2668 normal subjects ranging from birth to 18 years old. A systematic literature search was conducted in PubMed, Embase, and Scopus and reported following the preferred reporting items for systematic reviews and meta-analyses (PRISMA). We identified factors (such as age, gender, mood, sedation, and fitness) that have significant effects on pediatric CBF quantification. We also investigated factors influencing the CBF measurements in infants. Based on this review, we recommend best practices to improve CBF measurements in pediatric neuroimaging. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Longitudinal Alterations of Cerebral Blood Flow in High-Contact Sports.

OBJECTIVE: Repetitive head trauma is common in high-contact sports. Cerebral blood flow (CBF) can measure changes in brain perfusion that could indicate injury. Longitudinal studies with a control group are necessary to account for interindividual and developmental effects. We investigated whether exposure to head impacts causes longitudinal CBF changes. METHODS: We prospectively studied 63 American football (high-contact cohort) and 34 volleyball (low-contact controls) male collegiate athletes, tracking CBF using 3D pseudocontinuous arterial spin labeling magnetic resonance imaging for up to 4 years. Regional relative CBF (rCBF, normalized to cerebellar CBF) was computed after co-registering to T1-weighted images. A linear mixed effects model assessed the relationship of rCBF to sport, time, and their interaction. Within football players, we modeled rCBF against position-based head impact risk and baseline Standardized Concussion Assessment Tool score. Additionally, we evaluated early (1-5 days) and delayed (3-6 months) post-concussion rCBF changes (in-study concussion). RESULTS: Supratentorial gray matter rCBF declined in football compared with volleyball (sport-time interaction p = 0.012), with a strong effect in the parietal lobe (p = 0.002). Football players with higher position-based impact-risk had lower occipital rCBF over time (interaction p = 0.005), whereas players with lower baseline Standardized Concussion Assessment Tool score (worse performance) had relatively decreased rCBF in the cingulate-insula over time (interaction effect p = 0.007). Both cohorts showed a left-right rCBF asymmetry that decreased over time. Football players with an in-study concussion showed an early increase in occipital lobe rCBF (p = 0.0166). INTERPRETATION: These results suggest head impacts may result in an early increase in rCBF, but cumulatively a long-term decrease in rCBF. ANN NEUROL 2023;94:457-469.

DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy.

OBJECTIVES: Treatment and outcomes of acute stroke have been revolutionised by mechanical thrombectomy. Deep learning has shown great promise in diagnostics but applications in video and interventional radiology lag behind. We aimed to develop a model that takes as input digital subtraction angiography (DSA) videos and classifies the video according to (1) the presence of large vessel occlusion (LVO), (2) the location of the occlusion, and (3) the efficacy of reperfusion. METHODS: All patients who underwent DSA for anterior circulation acute ischaemic stroke between 2012 and 2019 were included. Consecutive normal studies were included to balance classes. An external validation (EV) dataset was collected from another institution. The trained model was also used on DSA videos post mechanical thrombectomy to assess thrombectomy efficacy. RESULTS: In total, 1024 videos comprising 287 patients were included (44 for EV). Occlusion identification was achieved with 100% sensitivity and 91.67% specificity (EV 91.30% and 81.82%). Accuracy of location classification was 71% for ICA, 84% for M1, and 78% for M2 occlusions (EV 73, 25, and 50%). For post-thrombectomy DSA (n = 194), the model identified successful reperfusion with 100%, 88%, and 35% for ICA, M1, and M2 occlusion (EV 89, 88, and 60%). The model could also perform classification of post-intervention videos as mTICI < 3 with an AUC of 0.71. CONCLUSIONS: Our model can successfully identify normal DSA studies from those with LVO and classify thrombectomy outcome and solve a clinical radiology problem with two temporal elements (dynamic video and pre and post intervention). KEY POINTS: • DEEP MOVEMENT represents a novel application of a model applied to acute stroke imaging to handle two types of temporal complexity, dynamic video and pre and post intervention. • The model takes as an input digital subtraction angiograms of the anterior cerebral circulation and classifies according to (1) the presence or absence of large vessel occlusion, (2) the location of the occlusion, and (3) the efficacy of thrombectomy. • Potential clinical utility lies in providing decision support via rapid interpretation (pre thrombectomy) and automated objective gradation of thrombectomy outcomes (post thrombectomy).

Automatic Lung Nodule Segmentation and Intra-Nodular Heterogeneity Image Generation.

Automatic segmentation of lung nodules on computed tomography (CT) images is challenging owing to the variability of morphology, location, and intensity. In addition, few segmentation methods can capture intra-nodular heterogeneity to assist lung nodule diagnosis. In this study, we propose an end-to-end architecture to perform fully automated segmentation of multiple types of lung nodules and generate intra-nodular heterogeneity images for clinical use. To this end, a hybrid loss is considered by introducing a Faster R-CNN model based on generalized intersection over union loss in generative adversarial network. The Lung Image Database Consortium image collection dataset, comprising 2,635 lung nodules, was combined with 3,200 lung nodules from five hospitals for this study. Compared with manual segmentation by radiologists, the proposed model obtained an average dice coefficient (DC) of 82.05% on the test dataset. Compared with U-net, NoduleNet, nnU-net, and other three models, the proposed method achieved comparable performance on lung nodule segmentation and generated more vivid and valid intra-nodular heterogeneity images, which are beneficial in radiological diagnosis. In an external test of 91 patients from another hospital, the proposed model achieved an average DC of 81.61%. The proposed method effectively addresses the challenges of inevitable human interaction and additional pre-processing procedures in the existing solutions for lung nodule segmentation. In addition, the results show that the intra-nodular heterogeneity images generated by the proposed model are suitable to facilitate lung nodule diagnosis in radiology.

Reproducibility of cerebrovascular reactivity measurements: A systematic review of neuroimaging techniques.

Cerebrovascular reactivity (CVR), the capacity of the brain to increase cerebral blood flow (CBF) to meet changes in physiological demand, is an important biomarker to evaluate brain health. Typically, this brain "stress test" is performed by using a medical imaging modality to measure the CBF change between two states: at baseline and after vasodilation. However, since there are many imaging modalities and many ways to augment CBF, a wide range of CVR values have been reported. An understanding of CVR reproducibility is critical to determine the most reliable methods to measure CVR as a clinical biomarker. This review focuses on CVR reproducibility studies using neuroimaging techniques in 32 articles comprising 427 total subjects. The literature search was performed in PubMed, Embase, and Scopus. The review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We identified 5 factors of the experimental subjects (such as sex, blood characteristics, and smoking) and 9 factors of the measuring technique (such as the imaging modality, the type of the vasodilator, and the quantification method) that have strong effects on CVR reproducibility. Based on this review, we recommend several best practices to improve the reproducibility of CVR quantification in neuroimaging studies.

Molecular imaging of a fluorescent antibody against epidermal growth factor receptor detects high-grade glioma.

The prognosis for high-grade glioma (HGG) remains dismal and the extent of resection correlates with overall survival and progression free disease. Epidermal growth factor receptor (EGFR) is a biomarker heterogeneously expressed in HGG. We assessed the feasibility of detecting HGG using near-infrared fluorescent antibody targeting EGFR. Mice bearing orthotopic HGG xenografts with modest EGFR expression were imaged in vivo after systemic panitumumab-IRDye800 injection to assess its tumor-specific uptake macroscopically over 14 days, and microscopically ex vivo. EGFR immunohistochemical staining of 59 tumor specimens from 35 HGG patients was scored by pathologists and expression levels were compared to that of mouse xenografts. Intratumoral distribution of panitumumab-IRDye800 correlated with near-infrared fluorescence and EGFR expression. Fluorescence distinguished tumor cells with 90% specificity and 82.5% sensitivity. Target-to-background ratios peaked at 14 h post panitumumab-IRDye800 infusion, reaching 19.5 in vivo and 7.6 ex vivo, respectively. Equivalent or higher EGFR protein expression compared to the mouse xenografts was present in 77.1% HGG patients. Age, combined with IDH-wildtype cerebral tumor, was predictive of greater EGFR protein expression in human tumors. Tumor specific uptake of panitumumab-IRDye800 provided remarkable contrast and a flexible imaging window for fluorescence-guided identification of HGGs despite modest EGFR expression.

Simultaneous time of flight-MRA and T2* imaging for cerebrovascular MRI.

PURPOSE: 3D multi-echo gradient-recalled echo (ME-GRE) can simultaneously generate time-of-flight magnetic resonance angiography (pTOF) in addition to T2*-based susceptibility-weighted images (SWI). We assessed the clinical performance of pTOF generated from a 3D ME-GRE acquisition compared with conventional TOF-MRA (cTOF). METHODS: Eighty consecutive children were retrospectively identified who obtained 3D ME-GRE alongside cTOF. Two blinded readers independently assessed pTOF derived from 3D ME-GRE and compared them with cTOF. A 5-point Likert scale was used to rank lesion conspicuity and to assess for diagnostic confidence. RESULTS: Across 80 pediatric neurovascular pathologies, a similar number of lesions were reported on pTOF and cTOF (43-40%, respectively, p > 0.05). Rating of lesion conspicuity was higher with cTOF (4.5 ± 1.0) as compared with pTOF (4.0 ± 0.7), but this was not significantly different (p = 0.06). Diagnostic confidence was rated higher with cTOF (4.8 ± 0.5) than that of pTOF (3.7 ± 0.6; p < 0.001). Overall, the inter-rater agreement between two readers for lesion count on pTOF was classified as almost perfect (κ = 0.98, 96% CI 0.8-1.0). CONCLUSIONS: In this study, TOF-MRA simultaneously generated in addition to SWI from 3D MR-GRE can serve as a diagnostic adjunct, particularly for proximal vessel disease and when conventional TOF-MRA images are absent.

Brain Iron Assessment after Ferumoxytol-enhanced MRI in Children and Young Adults with Arteriovenous Malformations: A Case-Control Study.

Background Iron oxide nanoparticles are an alternative contrast agent for MRI. Gadolinium deposition has raised safety concerns, but it is unknown whether ferumoxytol administration also deposits in the brain. Purpose To investigate whether there are signal intensity changes in the brain at multiecho gradient imaging following ferumoxytol exposure in children and young adults. Materials and Methods This retrospective case-control study included children and young adults, matched for age and sex, with brain arteriovenous malformations who received at least one dose of ferumoxytol from January 2014 to January 2018. In participants who underwent at least two brain MRI examinations (subgroup), the first and last available examinations were analyzed. Regions of interests were placed around deep gray structures on quantitative susceptibility mapping and R2* images. Mean susceptibility and R2* values of regions of interests were recorded. Measurements were assessed by linear regression analyses: a between-group comparison of ferumoxytol-exposed and unexposed participants and a within-group (subgroup) comparison before and after exposure. Results Seventeen participants (mean age ± standard deviation, 13 years ± 5; nine male) were in the ferumoxytol-exposed (case) group, 21 (mean age, 14 years ± 5; 11 male) were in the control group, and nine (mean age, 12 years ± 6; four male) were in the subgroup. The mean number of ferumoxytol administrations was 2 ± 1 (range, one to four). Mean susceptibility (in parts per million [ppm]) and R2* (in inverse seconds [sec-1]) values of the dentate (case participants: 0.06 ppm ± 0.04 and 23.87 sec-1 ± 4.13; control participants: 0.02 ppm ± 0.03 and 21.7 sec-1 ± 5.26), substantia nigrae (case participants: 0.08 ppm ± 0.06 and 27.46 sec-1 ± 5.58; control participants: 0.04 ppm ± 0.05 and 24.96 sec-1 ± 5.3), globus pallidi (case participants: 0.14 ppm ± 0.05 and 30.75 sec-1 ± 5.14; control participants: 0.08 ppm ± 0.07 and 28.82 sec-1 ± 6.62), putamina (case participants: 0.03 ppm ± 0.02 and 20.63 sec-1 ± 2.44; control participants: 0.02 ppm ± 0.02 and 19.65 sec-1 ± 3.6), caudate (case participants: -0.1 ppm ± 0.04 and 18.21 sec-1 ± 3.1; control participants: -0.06 ppm ± 0.05 and 18.83 sec-1 ± 3.32), and thalami (case participants: 0 ppm ± 0.03 and 16.49 sec-1 ± 3.6; control participants: 0.02 ppm ± 0.02 and 18.38 sec-1 ± 2.09) did not differ between groups (susceptibility, P = .21; R2*, P = .24). For the subgroup, the mean interval between the first and last ferumoxytol administration was 14 months ± 8 (range, 1-25 months). Mean susceptibility and R2* values of the dentate (first MRI: 0.06 ppm ± 0.05 and 25.78 sec-1 ± 5.9; last MRI: 0.06 ppm ± 0.02 and 25.55 sec-1 ± 4.71), substantia nigrae (first MRI: 0.06 ppm ± 0.06 and 28.26 sec-1 ± 9.56; last MRI: 0.07 ppm ± 0.06 and 25.65 sec-1 ± 6.37), globus pallidi (first MRI: 0.13 ppm ± 0.07 and 27.53 sec-1 ± 8.88; last MRI: 0.14 ppm ± 0.06 and 29.78 sec-1 ± 6.54), putamina (first MRI: 0.03 ppm ± 0.03 and 19.78 sec-1 ± 3.51; last MRI: 0.03 ppm ± 0.02 and 19.73 sec-1 ± 3.01), caudate (first MRI: -0.09 ppm ± 0.05 and 21.38 sec-1 ± 4.72; last MRI: -0.1 ppm ± 0.05 and 18.75 sec-1 ± 2.68), and thalami (first MRI: 0.01 ppm ± 0.02 and 17.65 sec-1 ± 5.16; last MRI: 0 ppm ± 0.02 and 15.32 sec-1 ± 2.49) did not differ between the first and last MRI examinations (susceptibility, P = .95; R2*, P = .54). Conclusion No overall significant differences were found in susceptibility and R2* values of deep gray structures to suggest retained iron in the brain between ferumoxytol-exposed and unexposed children and young adults with arteriovenous malformations and in those exposed to ferumoxytol over time. © RSNA, 2020.

Identifying cardiovascular risk factors that impact cerebrovascular reactivity: An ASL MRI study.

BACKGROUND: To maintain cerebral blood flow (CBF), cerebral blood vessels dilate and contract in response to blood supply through cerebrovascular reactivity (CR). PURPOSE: Cardiovascular (CV) disease is associated with increased stroke risk, but which risk factors specifically impact CR is unknown. STUDY TYPE: Prospective longitudinal. SUBJECTS: Fifty-three subjects undergoing carotid endarterectomy or stenting. FIELD STRENGTH/SEQUENCE: 3T, 3D pseudo-continuous arterial spin labeling (PCASL) ASL, and T1 3D fast spoiled gradient echo (FSPGR). ASSESSMENT: We evaluated group differences in CBF changes for multiple cardiovascular risk factors in patients undergoing carotid revascularization surgery. STATISTICAL TESTS: PRE (baseline), POST (48-hour postop), and 6MO (6 months postop) whole-brain CBF measurements, as 129 CBF maps from 53 subjects were modeled as within-subject analysis of variance (ANOVA). To identify CV risk factors associated with CBF change, the CBF change from PRE to POST, POST to 6MO, and PRE to 6MO were modeled as multiple linear regression with each CV risk factor as an independent variable. Statistical models were performed controlling for age on a voxel-by-voxel basis using SPM8. Significant clusters were reported if familywise error (FWE)-corrected cluster-level was P < 0.05, while the voxel-level significance threshold was set for P < 0.001. RESULTS: The entire group showed significant (cluster-level P < 0.001) CBF increase from PRE to POST, decrease from POST to 6MO, and no significant difference (all voxels with P > 0.001) from PRE to 6MO. Of multiple CV risk factors evaluated, only elevated systolic blood pressure (SBP, P = 0.001), chronic renal insufficiency (CRI, P = 0.026), and history of prior stroke (CVA, P < 0.001) predicted lower increases in CBF PRE to POST. Over POST to 6MO, obesity predicted lower (P > 0.001) and cholesterol greater CBF decrease (P > 0.001). DATA CONCLUSION: The CV risk factors of higher SBP, CRI, CVA, BMI, and cholesterol may indicate altered CR, and may warrant different stroke risk mitigation and special consideration for CBF change evaluation. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2020;51:734-747.

Erroneous Resting-State fMRI Connectivity Maps Due to Prolonged Arterial Arrival Time and How to Fix Them.

In resting-state functional MRI (rs-fMRI), functional networks are assessed utilizing the temporal correlation between spontaneous blood oxygen level-dependent signal fluctuations of spatially remote brain regions. Recently, several groups have shown that temporal shifts are present in rs-fMRI maps in patients with cerebrovascular disease due to spatial differences in arterial arrival times, and that this can be exploited to map arrival times in the brain. This suggests that rs-fMRI connectivity mapping may be similarly sensitive to such temporal shifts, and that standard rs-fMRI analysis methods may fail to identify functional connectivity networks. To investigate this, we studied the default mode network (DMN) in Moyamoya disease patients and compared it with normal healthy volunteers. Our results show that using standard independent component analysis (ICA) and seed-based approaches, arterial arrival delays lead to inaccurate incomplete characterization of functional connectivity within the DMN in Moyamoya disease patients. Furthermore, we propose two techniques to correct these errors, for seed-based and ICA methods, respectively. Using these methods, we demonstrate that it is possible to mitigate the deleterious effects of arterial arrival time on the assessment of functional connectivity of the DMN. As these corrections have not been applied to the vast majority of >200 prior rs-fMRI studies in patients with cerebrovascular disease, we suggest that they be interpreted with great caution. Correction methods should be applied in any rs-fMRI connectivity study of subjects expected to have abnormally delayed arterial arrival times.

Revealing sub-voxel motions of brain tissue using phase-based amplified MRI (aMRI).

PURPOSE: Amplified magnetic resonance imaging (aMRI) was recently introduced as a new brain motion detection and visualization method. The original aMRI approach used a video-processing algorithm, Eulerian video magnification (EVM), to amplify cardio-ballistic motion in retrospectively cardiac-gated MRI data. Here, we strive to improve aMRI by incorporating a phase-based motion amplification algorithm. METHODS: Phase-based aMRI was developed and tested for correct implementation and ability to amplify sub-voxel motions using digital phantom simulations. The image quality of phase-based aMRI was compared with EVM-based aMRI in healthy volunteers at 3T, and its amplified motion characteristics were compared with phase-contrast MRI. Data were also acquired on a patient with Chiari I malformation, and qualitative displacement maps were produced using free form deformation (FFD) of the aMRI output. RESULTS: Phantom simulations showed that phase-based aMRI has a linear dependence of amplified displacement on true displacement. Amplification was independent of temporal frequency, varying phantom intensity, Rician noise, and partial volume effect. Phase-based aMRI supported larger amplification factors than EVM-based aMRI and was less sensitive to noise and artifacts. Abnormal biomechanics were seen on FFD maps of the Chiari I malformation patient. CONCLUSION: Phase-based aMRI might be used in the future for quantitative analysis of minute changes in brain motion and may reveal subtle physiological variations of the brain as a result of pathology using processing of the fundamental harmonic or by selectively varying temporal harmonics. Preliminary data shows the potential of phase-based aMRI to qualitatively assess abnormal biomechanics in Chiari I malformation.

Imaging of cerebrovascular reserve and oxygenation in Moyamoya disease.

This study aimed to determine whether measurements of cerebrovascular reserve and oxygenation, assessed with spin relaxation rate R2', yield similar information about pathology in pre-operative Moyamoya disease patients, and to assess whether R2' is a better measure of oxygenation than other proposed markers, such as R2* and R2. Twenty-five pre-operative Moyamoya disease patients were scanned at 3.0T with acetazolamide challenge. Cerebral blood flow mapping with multi-delay arterial spin labeling, and R2*, R2, and R2' mapping with Gradient-Echo Sampling of Free Induction Decay and Echo were performed. No baseline cerebral blood flow difference was found between angiographically abnormal and normal regions (49 ± 12 vs. 48 ± 11 mL/100 g/min, p = 0.44). However, baseline R2' differed between these regions (3.2 ± 0.7 vs. 2.9 ± 0.6 s-1, p < 0.001), indicating reduced oxygenation in abnormal regions. Cerebrovascular reserve was lower in angiographically abnormal regions (21 ± 38 vs. 41 ± 26%, p = 0.001). All regions showed trend toward significantly improved oxygenation post-acetazolamide. Regions with poorer cerebrovascular reserve had lower baseline oxygenation (Kendall's τ = -0.24, p = 0.003). A number of angiographically abnormal regions demonstrated preserved cerebrovascular reserve, likely due to the presence of collaterals. Finally, of the concurrently measured relaxation rates, R2' was superior for oxygenation assessment.

Measuring vascular reactivity with resting-state blood oxygenation level-dependent (BOLD) signal fluctuations: A potential alternative to the breath-holding challenge?

Measurement of the ability of blood vessels to dilate and constrict, known as vascular reactivity, is often performed with breath-holding tasks that transiently raise arterial blood carbon dioxide (PaCO2) levels. However, following the proper commands for a breath-holding experiment may be difficult or impossible for many patients. In this study, we evaluated two approaches for obtaining vascular reactivity information using blood oxygenation level-dependent signal fluctuations obtained from resting-state functional magnetic resonance imaging data: physiological fluctuation regression and coefficient of variation of the resting-state functional magnetic resonance imaging signal. We studied a cohort of 28 older adults (69 ± 7 years) and found that six of them (21%) could not perform the breath-holding protocol, based on an objective comparison with an idealized respiratory waveform. In the subjects that could comply, we found a strong linear correlation between data extracted from spontaneous resting-state functional magnetic resonance imaging signal fluctuations and the blood oxygenation level-dependent percentage signal change during breath-holding challenge ( R2 = 0.57 and 0.61 for resting-state physiological fluctuation regression and resting-state coefficient of variation methods, respectively). This technique may eliminate the need for subject cooperation, thus allowing the evaluation of vascular reactivity in a wider range of clinical and research conditions in which it may otherwise be impractical.

Brain structural connectivity distinguishes patients at risk for cognitive decline after carotid interventions.

While brain connectivity analyses have been demonstrated to identify ill patients for a number of diseases, their ability to predict cognitive impairment after brain injury is not well established. Traditional post brain injury models, such as stroke, are limited for this evaluation because pre-injury brain connectivity patterns are infrequently available. Patients with severe carotid stenosis, in contrast, often undergo non-emergent revascularization surgery, allowing the collection of pre and post-operative imaging, may experience brain insult due to perioperative thrombotic/embolic infarcts or hypoperfusion, and can suffer post-operative cognitive decline. We hypothesized that a distributed function such as memory would be more resilient in patients with brains demonstrating higher degrees of modularity. To test this hypothesis, we analyzed preoperative structural connectivity graphs (using T1 and DWI MRI) for 34 patients that underwent carotid intervention, and evaluated differences in graph metrics using the Brain Connectivity Toolbox. We found that patients with lower binary component number, binary community number and weighted community number prior to surgery were at greater risk for developing cognitive decline. These findings highlight the promise of brain connectivity analyses to predict cognitive decline following brain injury and serve as a clinical decision support tool. Hum Brain Mapp 37:2185-2194, 2016. © 2016 Wiley Periodicals, Inc.

Amplified magnetic resonance imaging (aMRI).

PURPOSE: This work describes a new method called amplified MRI (aMRI), which uses Eulerian video magnification to amplify the subtle spatial variations in cardiac-gated brain MRI scans and enables better visualization of brain motion. METHODS: The aMRI method takes retrospective cardiac-gated cine MRI data as input, applies a spatial decomposition, followed by temporal filtering and frequency-selective amplification of the MRI cardiac-gated frames before synthesizing a motion-amplified cine data set. RESULTS: This approach reveals deformations of the brain parenchyma and displacements of arteries due to cardiac pulsatility, especially in the brainstem, cerebellum, and spinal cord. CONCLUSION: aMRI has the potential for widespread neuro- and non-neuro clinical use because it can amplify and characterize small, often barely perceptible motion and can visualize the biomechanical response of tissues using the heartbeat as an endogenous mechanical driver. Magn Reson Med 75:2245-2254, 2016. © 2016 Wiley Periodicals, Inc.

Intensity-Corrected Dual-Echo Echo-Planar Imaging (DE-EPI) for Improved Pediatric Brain Diffusion Imaging.

Here we investigate the utility of a dual-echo Echo-Planar Imaging (DE-EPI) Diffusion Weighted Imaging (DWI) approach to improve lesion conspicuity in pediatric imaging. This method delivers two 'echo images' for one diffusion-preparation period. We also demonstrate how the echoes can be utilized to remove transmit/receive coil-induced and static magnetic field intensity modulations on both echo images, which often mimic pathology and thereby pose diagnostic challenges. DE-EPI DWI data were acquired in 18 pediatric patients with abnormal diffusion lesions, and 46 pediatric patient controls at 3T. Echo1 [TE = 45ms] and Echo2 [TE = 86ms] were corrected for signal intensity variation across the images by exploiting the images equivalent coil-sensitivity and susceptibility-induced modulations. Two neuroradiologists independently reviewed Echo1 and Echo2 and their intensity-corrected variants (cEcho1 and cEcho2) on a 7-point Likert scale, with grading on lesion conspicuity diagnostic confidence. The apparent diffusion coefficient (ADC) map from Echo1 was used to validate presence of true pathology. Echo2 was unanimously favored over Echo1 for its sensitivity for detecting acute brain injury, with a mean respective lesion conspicuity of 5.7/4.4 (p < 0.005) and diagnostic confidence of 5.1/4.3 (p = 0.025). cEcho2 was rated higher than cEcho1, with a mean respective lesion conspicuity of 5.5/4.3 (p < 0.005) and diagnostic confidence of 5.4/4.4 (p < 0.005). cEcho2 was favored over all echoes for its diagnostic reliability, particularly in regions close to the head coil. This work concludes that DE-EPI DWI is a useful alternative to conventional single-echo EPI DWI, whereby Echo2 and cEcho2 allows for improved lesion detection and overall higher diagnostic confidence.

Noncontrast mapping of arterial delay and functional connectivity using resting-state functional MRI: a study in Moyamoya patients.

PURPOSE: To investigate if delays in resting-state spontaneous fluctuations of the BOLD (sfBOLD) signal can be used to create maps similar to time-to-maximum of the residue function (Tmax) in Moyamoya patients and to determine whether sfBOLD delays affect the results of brain connectivity mapping. MATERIALS AND METHODS: Ten patients were scanned at 3 Tesla using a gradient-echo echo planar imaging sequence for sfBOLD imaging. Cross correlation analysis was performed between each brain voxel signal and a reference signal comprised of either the superior sagittal sinus (SSS) or whole brain (WB) average time course. sfBOLD delay maps were created based on the time shift necessary to maximize the correlation coefficient, and compared with dynamic susceptibility contrast Tmax maps. Standard and time-shifted resting-state BOLD connectivity analyses of the default mode network were compared. RESULTS: Good linear correlations were found between sfBOLD delays and Tmax using the SSS as reference (r(2) = 0.8, slope = 1.4, intercept = -4.6) or WB (r(2) = 0.7, slope = 0.8, intercept = -3.2). New nodes of connectivity were found in delayed regions when accounting for delays in the analysis. CONCLUSION: Resting-state sfBOLD imaging can create delay maps similar to Tmax maps without the use of contrast agents in Moyamoya patients. Accounting for these delays may affect the results of functional connectivity maps.

Fast susceptibility-weighted imaging with three-dimensional short-axis propeller (SAP)-echo-planar imaging.

BACKGROUND: Susceptibility-weighted imaging (SWI) in neuroimaging can be challenging due to long scan times of three-dimensional (3D) gradient recalled echo (GRE), while faster techniques such as 3D interleaved echo-planar imaging (iEPI) are prone to motion artifacts. Here we outline and implement a 3D short-axis propeller echo-planar imaging (SAP-EPI) trajectory as a faster, motion-correctable approach for SWI. METHODS: Experiments were conducted on a 3T MRI system. The 3D SAP-EPI, 3D iEPI, and 3D GRE SWI scans were acquired on two volunteers. Controlled motion experiments were conducted to test the motion-correction capability of 3D SAP-EPI. The 3D SAP-EPI SWI data were acquired on two pediatric patients as a potential alternative to 2D GRE used clinically. RESULTS: The 3D GRE images had a better target resolution (0.47 × 0.94 × 2 mm, scan time = 5 min), iEPI and SAP-EPI images (resolution = 0.94 × 0.94 × 2 mm) were acquired in a faster scan time (1:52 min) with twice the brain coverage. SAP-EPI showed motion-correction capability and some immunity to undersampling from rejected data. CONCLUSION: While 3D SAP-EPI suffers from some geometric distortion, its short scan time and motion-correction capability suggest that SAP-EPI may be a useful alternative to GRE and iEPI for use in SWI, particularly in uncooperative patients.

Spontaneous BOLD signal fluctuations in young healthy subjects and elderly patients with chronic kidney disease.

Spontaneous fluctuations in blood oxygenation level-dependent (BOLD) images are the basis of resting-state fMRI and frequently used for functional connectivity studies. However, there may be intrinsic information in the amplitudes of these fluctuations. We investigated the possibility of using the amplitude of spontaneous BOLD signal fluctuations as a biomarker for cerebral vasomotor reactivity. We compared the coefficient of variation (CV) of the time series (defined as the temporal standard deviation of the time series divided by the mean signal intensity) in two populations: 1) Ten young healthy adults and 2) Ten hypertensive elderly subjects with chronic kidney disease (CKD). We found a statistically significant increase (P<0.01) in the CV values for the CKD patients compared with the young healthy adults in both gray matter (GM) and white matter (WM). The difference was independent of the exact segmentation method, became more significant after correcting for physiological signals using RETROICOR, and mainly arose from very low frequency components of the BOLD signal fluctuation (f<0.025 Hz). Furthermore, there was a strong relationship between WM and GM signal fluctuation CV's (R(2)= 0.87) in individuals, with a ratio of about 1:3. These results suggest that amplitude of the spontaneous BOLD signal fluctuations may be used to assess the cerebrovascular reactivity mechanisms and provide valuable information about variations with age and different disease states.