Effects of white matter hyperintensity burden on functional outcome after mild versus moderate-to-severe ischemic stroke.

It is uncertain whether the prognostic power of white matter hyperintensity (WMH) on post-stroke outcomes is modulated as a function of initial neurological severity, a critical determinant of outcome after stroke. This multi-center MRI study tested if higher WMH quintiles were associated with 3-month poor functional outcome (modified Rankin Scale ≥ 3) for mild versus moderate-to-severe ischemic stroke. Mild and moderate-to-severe stroke were defined as admission National Institute of Health Stroke Scale scores of 1-4 and ≥ 5, respectively. Mean age of the enrolled patients (n = 8918) was 67.2 ± 12.6 years and 60.1% male. The association between WMH quintiles and poor functional outcome was modified by stroke severity (p-for-interaction = 0.008). In mild stroke (n = 4994), WMH quintiles associated with the 3-month outcome in a dose-dependent manner for the 2nd to 5th quintile versus the 1st quintile, with adjusted-odds-ratios (aOR [95% confidence interval]) being 1.29 [0.96-1.73], 1.37 [1.02-1.82], 1.60 [1.19-2.13], and 1.89 [1.41-2.53], respectively. In moderate-to-severe stroke (n = 3924), however, there seemed to be a threshold effect: only the highest versus the lowest WMH quintile was significantly associated with poor functional outcome (aOR 1.69 [1.29-2.21]). WMH burden aggravates 3-month functional outcome after mild stroke, but has a lesser modulatory effect for moderate-to-severe stroke, likely due to saturation effects.

The Impact of MRI-Based Advanced Neuroimaging on Neurooncologists' Clinical Decision-Making in Patients With Posttreatment High-Grade Glioma: A Prospective Survey-Based Study.

Background: Advanced MRI-based neuroimaging techniques, such as perfusion and spectroscopy, have been increasingly incorporated into routine follow-up protocols in patients treated for high-grade glioma (HGG), to help differentiate tumor progression from treatment effect. However, these techniques' influence on clinical management remains poorly understood. Objective: To evaluate the impact of MRI-based advanced neuroimaging on clinical decision-making in patients with HGG in the posttreatment setting. Methods: This prospective study, performed at a comprehensive cancer center from March 1, 2017, to October 31, 2020, included adult patients treated by chemoradiation for WHO grade 4 diffuse glioma who underwent MRIbased advanced neuroimaging (comprising multiple perfusion imaging sequences and spectroscopy) to further evaluate findings on conventional MRI equivocal for tumor progression versus treatment effect. The ordering neuro-oncologists completed surveys before and after each advanced neuroimaging session. The percent of care episodes with a change between the intended and actual management plan on the surveys conducted before and after advanced neuroimaging, respectively, was computed and compared with a previously published percent using the Wald test for independent samples proportions. Results: The study included 63 patients (mean age, 55±13 years; 36 women, 27 men) who underwent 70 advanced neuroimaging sessions. Ordering neuro-oncologists' intended and actual management plans on the surveys completed before and after advanced neuroimaging, respectively, differed in 44% (31/70, [95% CI: 33-56%]) of episodes, which differed from the previously published frequency of 8.5% (5/59) (p<.001). These management plan changes included selection of a different plan for 6/8 episodes with an intended plan to enroll patients in a clinical trial, 12/19 episodes with an intended plan to change chemotherapeutic agents, 4/8 episodes with an intended plan of surgical intervention, and 1/2 episodes with an intended plan of re-irradiation. The ordering neuro-oncologists found advanced neuroimaging to be helpful in 93% (95% CI: 87%-99%) (65/70) of episodes. Conclusion: Neuro-oncologists' management plans changed in a substantial fraction of adult patients with HGG who underwent advanced neuroimaging to further evaluate conventional MRI findings equivocal for tumor progression versus treatment effect. Clinical Impact: The findings support incorporation of advanced neuroimaging into HGG posttreatment monitoring protocols.

Automated segmentation of MRI white matter hyperintensities in 8,421 patients with acute ischemic stroke.

BACKGROUND AND PURPOSE: To date, only a few small studies have attempted deep learning-based automatic segmentation of white matter hyperintensity (WMH) lesions in patients with cerebral infarction, which is complicated because stroke-related lesions can obscure WMH borders. We developed and validated deep learning algorithms to segment WMH lesions accurately in patients with cerebral infarction, using multisite datasets involving 8,421 patients with acute ischemic stroke. MATERIALS AND METHODS: We included 8,421 stroke patients from 9 centers in Korea. 2D UNet and SE-Unet models were trained using 2,408 FLAIR MRI from 3 hospitals and validated using 6,013 FLAIR MRIs from 6 hospitals. WMH segmentation performance was assessed by calculating DSC, correlation coefficient, and concordance correlation coefficient compared to a human-segmented gold standard. In addition, we obtained an uncertainty index that represents overall ambiguity in the voxel classification for WMH segmentation in each patient based on the Kullback-Leibler divergence. RESULTS: In the training dataset, the mean age was 67.4±13.0 years and 60.4% were men. The mean (95% CI) DSCs for Unet in internal testing and external validation were respectively 0.659 (0.649-0.669) and 0.710 (0.707-0.714), which were slightly lower than the reliability between humans (DSC=0.744; 95% CI=0.738-0.751; P=.031). Compared with the Unet, the SE-Unet demonstrated better performance, achieving a mean DSC of 0.675 (0.666-0.685; P<.001) in the internal testing and 0.722 (0.719-0.726; P<.001) in the external validation; moreover, it achieved high DSC values (ranging from 0.672 to 0.744) across multiple validation datasets. We observed a significant correlation between WMH volumes that were segmented automatically and manually for the Unet (r=0.917, P<.0001) and even stronger for the SE-Unet (r=0.933, P<.0001). The SE-Unet also attained a high concordance correlation coefficient (ranging from 0.841 to 0.956) in external test datasets. In addition, the uncertainty indices in the majority of patients (86%) in the external datasets were below 0.35, with an average DSC of 0.744 in these patients. CONCLUSIONS: We developed and validated deep learning algorithms to segment WMH in patients with acute cerebral infarction using the largest-ever MRI datasets. In addition, we showed that the uncertainty index can be used to identify cases where automatic WMH segmentation is less accurate and requires human review. ABBREVIATIONS: WMH = white matter hyperintensity; CNN = convolutional neural networks; SE = squeeze-and-excitation; KL = Kullback-Leibler; ReLU = rectified linear unit; LKW = last known well; mRS = modified Rankin Scale; NIHSS = National Institute of Health Stroke Scale; LAA = large artery atherosclerosis; SVO = small vessel occlusion; CE = cardioembolism.

Deep Learning-Based Automatic Classification of Ischemic Stroke Subtype Using Diffusion-Weighted Images.

BACKGROUND AND PURPOSE: Accurate classification of ischemic stroke subtype is important for effective secondary prevention of stroke. We used diffusion-weighted image (DWI) and atrial fibrillation (AF) data to train a deep learning algorithm to classify stroke subtype. METHODS: Model development was done in 2,988 patients with ischemic stroke from three centers by using U-net for infarct segmentation and EfficientNetV2 for subtype classification. Experienced neurologists (n=5) determined subtypes for external test datasets, while establishing a consensus for clinical trial datasets. Automatically segmented infarcts were fed into the model (DWI-only algorithm). Subsequently, another model was trained, with AF included as a categorical variable (DWI+AF algorithm). These models were tested: (1) internally against the opinion of the labeling experts, (2) against fresh external DWI data, and (3) against clinical trial dataset. RESULTS: In the training-and-validation datasets, the mean (±standard deviation) age was 68.0±12.5 (61.1% male). In internal testing, compared with the experts, the DWI-only and the DWI+AF algorithms respectively achieved moderate (65.3%) and near-strong (79.1%) agreement. In external testing, both algorithms again showed good agreements (59.3%-60.7% and 73.7%-74.0%, respectively). In the clinical trial dataset, compared with the expert consensus, percentage agreements and Cohen's kappa were respectively 58.1% and 0.34 for the DWI-only vs. 72.9% and 0.57 for the DWI+AF algorithms. The corresponding values between experts were comparable (76.0% and 0.61) to the DWI+AF algorithm. CONCLUSION: Our model trained on a large dataset of DWI (both with or without AF information) was able to classify ischemic stroke subtypes comparable to a consensus of stroke experts.

First-in-Human Hyperpolarized MRI for Tumor Metabolism in HNSCC.

This case report describes the use of hyperpolarized magnetic resonance imaging (MRI) in a patient with head and neck squamous cell carcinoma (HNSCC) to demonstrate its translational viability.

Mutual-information based optimal experimental design for hyperpolarized [Formula: see text]C-pyruvate MRI.

A key parameter of interest recovered from hyperpolarized (HP) MRI measurements is the apparent pyruvate-to-lactate exchange rate, [Formula: see text], for measuring tumor metabolism. This manuscript presents an information-theory-based optimal experimental design approach that minimizes the uncertainty in the rate parameter, [Formula: see text], recovered from HP-MRI measurements. Mutual information is employed to measure the information content of the HP measurements with respect to the first-order exchange kinetics of the pyruvate conversion to lactate. Flip angles of the pulse sequence acquisition are optimized with respect to the mutual information. A time-varying flip angle scheme leads to a higher parameter optimization that can further improve the quantitative value of mutual information over a constant flip angle scheme. However, the constant flip angle scheme, 35 and 28 degrees for pyruvate and lactate measurements, leads to an accuracy and precision comparable to the variable flip angle schemes obtained from our method. Combining the comparable performance and practical implementation, optimized pyruvate and lactate flip angles of 35 and 28 degrees, respectively, are recommended.

Biological Mechanism of Sex Difference in Stroke Manifestation and Outcomes.

BACKGROUND AND OBJECTIVES: Female patients tend to have greater disability and worse long-term outcomes after stroke than male patients. To date, the biological basis of sex difference in ischemic stroke remains unclear. We aimed to (1) assess sex differences in clinical manifestation and outcomes of acute ischemic stroke and (2) investigate whether the sex disparity is due to different infarct locations or different impacts of infarct in the same location. METHODS: This MRI-based multicenter study included 6,464 consecutive patients with acute ischemic stroke (<7 days) from 11 centers in South Korea (May 2011-January 2013). Multivariable statistical and brain mapping methods were used to analyze clinical and imaging data collected prospectively: admission NIH Stroke Scale (NIHSS) score, early neurologic deterioration (END) within 3 weeks, modified Rankin Scale (mRS) score at 3 months, and culprit cerebrovascular lesion (symptomatic large artery steno-occlusion and cerebral infarction) locations. RESULTS: The mean (SD) age was 67.5 (12.6) years, and 2,641 (40.9%) were female patients. Percentage infarct volumes on diffusion-weighted MRI did not differ between female patients and male patients (median 0.14% vs 0.14%, p = 0.35). However, female patients showed higher stroke severity (NIHSS score, median 4 vs 3, p < 0.001) and had more frequent END (adjusted difference 3.5%; p = 0.002) than male patients. Female patients had more frequent striatocapsular lesions (43.6% vs 39.8%, p = 0.001) and less frequent cerebrocortical (48.2% vs. 50.7% in patients older than 52 years, p = 0.06) and cerebellar (9.1% vs. 11.1%, p = 0.009) lesions than male patients, which aligned with angiographic findings: female patients had more prevalent symptomatic steno-occlusion of the middle cerebral artery (MCA) (31.1% vs 25.3%; p < 0.001) compared with male patients, who had more frequent symptomatic steno-occlusion of the extracranial internal carotid artery (14.2% vs 9.3%; p < 0.001) and vertebral artery (6.5% vs 4.7%; p = 0.001). Cortical infarcts in female patients, specifically left-sided parieto-occipital regions, were associated with higher NIHSS scores than expected for similar infarct volumes in male patients. Consequently, female patients had a higher likelihood of unfavorable functional outcome (mRS score >2) than male patients (adjusted absolute difference 4.5%; 95% CI 2.0-7.0; p < 0.001). DISCUSSION: Female patients have more frequent MCA disease and striatocapsular motor pathway involvement with acute ischemic stroke, along with left parieto-occipital cortical infarcts showing greater severity for equivalent infarct volumes than in male patients. This leads to more severe initial neurologic symptoms, higher susceptibility to neurologic worsening, and less 3-month functional independence, when compared with male patients.

Towards a biomarker for acute arterial thrombosis using complete blood count and white blood cell differential parameters in mice.

There is no blood biomarker diagnostic of arterial thrombosis. We investigated if arterial thrombosis per se was associated with alterations in complete blood count (CBC) and white blood cell (WBC) differential count in mice. Twelve-week-old C57Bl/6 mice were used for FeCl3-mediated carotid thrombosis (n = 72), sham-operation (n = 79), or non-operation (n = 26). Monocyte count (/µL) at 30-min after thrombosis (median 160 [interquartile range 140-280]) was ~ 1.3-fold higher than at 30-min after sham-operation (120 [77.5-170]), and twofold higher than in non-operated mice (80 [47.5-92.5]). At day-1 and -4 post-thrombosis, compared with 30-min, monocyte count decreased by about 6% and 28% to 150 [100-200] and 115 [100-127.5], which however were about 2.1-fold and 1.9-fold higher than in sham-operated mice (70 [50-100] and 60 [30-75], respectively). Lymphocyte counts (/µL) at 1- and 4-days after thrombosis (mean ± SD; 3513 ± 912 and 2590 ± 860) were ~ 38% and ~ 54% lower than those in the sham-operated mice (5630 ± 1602 and 5596 ± 1437, respectively), and ~ 39% and ~ 55% lower than those in non-operated mice (5791 ± 1344). Post-thrombosis monocyte-lymphocyte-ratio (MLR) was substantially higher at all three time-points (0.050 ± 0.02, 0.046 ± 0.025, and 0.050 ± 0.02) vs. sham (0.003 ± 0.021, 0.013 ± 0.004, and 0.010 ± 0.004). MLR was 0.013 ± 0.005 in non-operated mice. This is the first report on acute arterial thrombosis-related alterations in CBC and WBC differential parameters.

PocketNet: A Smaller Neural Network for Medical Image Analysis.

Medical imaging deep learning models are often large and complex, requiring specialized hardware to train and evaluate these models. To address such issues, we propose the PocketNet paradigm to reduce the size of deep learning models by throttling the growth of the number of channels in convolutional neural networks. We demonstrate that, for a range of segmentation and classification tasks, PocketNet architectures produce results comparable to that of conventional neural networks while reducing the number of parameters by multiple orders of magnitude, using up to 90% less GPU memory, and speeding up training times by up to 40%, thereby allowing such models to be trained and deployed in resource-constrained settings.

Strengthening deep-learning models for intracranial hemorrhage detection: strongly annotated computed tomography images and model ensembles.

Background and purpose: Multiple attempts at intracranial hemorrhage (ICH) detection using deep-learning techniques have been plagued by clinical failures. We aimed to compare the performance of a deep-learning algorithm for ICH detection trained on strongly and weakly annotated datasets, and to assess whether a weighted ensemble model that integrates separate models trained using datasets with different ICH improves performance. Methods: We used brain CT scans from the Radiological Society of North America (27,861 CT scans, 3,528 ICHs) and AI-Hub (53,045 CT scans, 7,013 ICHs) for training. DenseNet121, InceptionResNetV2, MobileNetV2, and VGG19 were trained on strongly and weakly annotated datasets and compared using independent external test datasets. We then developed a weighted ensemble model combining separate models trained on all ICH, subdural hemorrhage (SDH), subarachnoid hemorrhage (SAH), and small-lesion ICH cases. The final weighted ensemble model was compared to four well-known deep-learning models. After external testing, six neurologists reviewed 91 ICH cases difficult for AI and humans. Results: InceptionResNetV2, MobileNetV2, and VGG19 models outperformed when trained on strongly annotated datasets. A weighted ensemble model combining models trained on SDH, SAH, and small-lesion ICH had a higher AUC, compared with a model trained on all ICH cases only. This model outperformed four deep-learning models (AUC [95% C.I.]: Ensemble model, 0.953[0.938-0.965]; InceptionResNetV2, 0.852[0.828-0.873]; DenseNet121, 0.875[0.852-0.895]; VGG19, 0.796[0.770-0.821]; MobileNetV2, 0.650[0.620-0.680]; p < 0.0001). In addition, the case review showed that a better understanding and management of difficult cases may facilitate clinical use of ICH detection algorithms. Conclusion: We propose a weighted ensemble model for ICH detection, trained on large-scale, strongly annotated CT scans, as no model can capture all aspects of complex tasks.

Distinguishing Intrathyroid Parathyroid Adenoma from Colloid Nodules and Papillary Thyroid Carcinomas Using Multiphasic Multidetector Computed Tomography.

OBJECTIVE: The aim of the study is to determine whether multiphase multidetector computed tomography (4D-MDCT) can differentiate between intrathyroid parathyroid adenomas (ITPAs), colloid nodules, and papillary thyroid carcinoma (PTC). METHODS: We studied 22 ITPAs, 22 colloid nodules, and 11 PTCs in 55 patients. Hounsfield unit (HU) values of the nodules were measured on 4D-MDCT in the precontrast, arterial, venous, and delayed phases. Raw HU values, phase with peak enhancement, and washout percentages between the phases were evaluated. RESULTS: Regardless of size, all ITPAs (22/22) showed peak enhancement in the arterial phase, which was significantly greater than both colloid nodules (15/22) and PTC (6/11, P = 0.002); thus, nodules with peak enhancement in the venous or delayed phase were not ITPAs (specificity = 1). For nodules with peak enhancement in the arterial phase, the percentage washout in the arterial-to-venous phases separated ITPAs from PTC and colloid nodules (P < 0.001) with greater than or equal to 23.95% loss of HU value implying IPTA (area under curve, 0.79). This left a subset of colloid nodules or PTC that either peaked in the venous or delayed phase or had an arterial-to-venous phase washout of less than 23.95%. From this subset, PTC measuring 1 cm or greater could be separated from colloid based on HU values in the arterial phase with a cutoff HU value less than 81.4 for PTC (area under curve, 0.72) and an HU value greater than 164.5 suggested colloid. CONCLUSIONS: Intrathyroid parathyroid adenomas can be distinguished from colloid nodules and PTC by peak enhancement in the arterial phase and rapid washout. A subset of colloid and PTC measuring 1 cm or greater can be separated using arterial phase HU values.

An efficient magnetic resonance image data quality screening dashboard.

PURPOSE: Complex data processing and curation for artificial intelligence applications rely on high-quality data sets for training and analysis. Manually reviewing images and their associated annotations is a very laborious task and existing quality control tools for data review are generally limited to raw images only. The purpose of this work was to develop an imaging informatics dashboard for the easy and fast review of processed magnetic resonance (MR) imaging data sets; we demonstrated its ability in a large-scale data review. METHODS: We developed a custom R Shiny dashboard that displays key static snapshots of each imaging study and its annotations. A graphical interface allows the structured entry of review data and download of tabulated review results. We evaluated the dashboard using two large data sets: 1380 processed MR imaging studies from our institution and 285 studies from the 2018 MICCAI Brain Tumor Segmentation Challenge (BraTS). RESULTS: Studies were reviewed at an average rate of 100/h using the dashboard, 10 times faster than using existing data viewers. For data from our institution, 1181 of the 1380 (86%) studies were of acceptable quality. The most commonly identified failure modes were tumor segmentation (9.6% of cases) and image registration (4.6% of cases). Tumor segmentation without visible errors on the dashboard had much better agreement with reference tumor volume measurements (root-mean-square error 12.2 cm3 ) than did segmentations with minor errors (20.5 cm3 ) or failed segmentations (27.4 cm3 ). In the BraTS data, 242 of 285 (85%) studies were acceptable quality after processing. Among the 43 cases that failed review, 14 had unacceptable raw image quality. CONCLUSION: Our dashboard provides a fast, effective tool for reviewing complex processed MR imaging data sets. It is freely available for download at https://github.com/EGates1/MRDQED.

Relation of Pre-Stroke Aspirin Use With Cerebral Infarct Volume and Functional Outcomes.

OBJECTIVE: We investigated (1) the associations of pre-stroke aspirin use with thrombus burden, infarct volume, hemorrhagic transformation, early neurological deterioration (END), and functional outcome, and (2) whether stroke subtypes modify these associations in first-ever ischemic stroke. METHODS: This multicenter magnetic resonance imaging (MRI)-based study included 5,700 consecutive patients with acute first-ever ischemic stroke, who did not undergo intravenous thrombolysis or endovascular thrombectomy, from May 2011 through February 2014. Propensity score-based augmented inverse probability weighting was performed to estimate adjusted effects of pre-stroke aspirin use. RESULTS: The mean age was 67 years (41% women), and 15.9% (n = 907) were taking aspirin before stroke. Pre-stroke aspirin use (vs nonuse) was significantly related to a reduced infarct volume (by 30%), particularly in large artery atherosclerosis stroke (by 45%). In cardioembolic stroke, pre-stroke aspirin use was associated with a ~50% lower incidence of END (adjusted difference = -5.4%, 95% confidence interval [CI] = -8.9 to -1.9). Thus, pre-stroke aspirin use was associated with ~30% higher likelihood of favorable outcome (3-month modified Rankin Scale score < 3), particularly in large artery atherosclerosis stroke and cardioembolic stroke (adjusted difference = 7.2%, 95% CI = 1.8 to 12.5 and adjusted difference = 6.4%, 95% CI = 1.7 to 11.1, respectively). Pre-stroke aspirin use (vs nonuse) was associated with 85% less frequent cerebral thrombus-related susceptibility vessel sign (SVS) in large artery atherosclerosis stroke (adjusted difference = -1.4%, 95% CI = -2.1 to -0.8, p < 0.001) and was associated with ~40% lower SVS volumes, particularly in cardioembolic stroke (adjusted difference = -0.16 cm3 , 95% CI = -0.29 to -0.02, p = 0.03). Moreover, pre-stroke aspirin use was not significantly associated with hemorrhagic transformation (adjusted difference = -1.1%, p = 0.09). INTERPRETATION: Pre-stroke aspirin use associates with improved functional independence in patients with first-ever ischemic large arterial stroke by reducing infarct volume and/or END, likely by decreasing thrombus burden, without increased risk of hemorrhagic transformation. ANN NEUROL 2021;90:763-776.

Rate of incidental central nervous system meningioma detected in patients undergoing 18F-fluciclovine PET/CT imaging for evaluation of prostate cancer.

OBJECTIVE: To evaluate the rate of incidental detection of central nervous system (CNS) meningioma in patients undergoing 18F-fluciclovine PET/computed tomography (CT) imaging for the evaluation of prostate cancer. METHODS: The reports of 850 18F-fluciclovine PET/CT scans in 566 patients with pathologically proven prostate cancer performed from April 2017 to July 2019, were retrospectively reviewed for the presence of CNS meningioma. RESULTS: A total of 14 patients (2.8%) (age range: 54-82 years old) had abnormal focal intracranial 18F-fluciclovine uptake, all extra-axial in location (SUVmax range: 3.2-19.3). Two cases out of 14 (0.35%) were diagnosed as metastatic lesions. Twelve out of the 14 patients, had 18F-fluciclovine PET/CT imaging findings suspicious for CNS meningioma, 2 of them received another diagnosis on further imaging, and only 10 cases (2%) had the diagnosis of meningioma according to follow-up MRI and 18F-fluciclovine PET/CT. CONCLUSION: Focal 18F-fluciclovine avid intracranial lesions incidentally detected in patients undergoing PET/CT imaging for prostate cancer are most often CNS meningiomas.

The Calcium Versus Hemorrhage Trial: Developing Diagnostic Criteria for Chronic Intracranial Susceptibility Lesions Using Single-Energy Computed Tomography, Dual-Energy Computed Tomography, and Quantitative Susceptibility Mapping.

PURPOSE: Chronic susceptibility lesions in the brain can be either hemorrhagic (potentially dangerous) or calcific (usually not dangerous) but are difficult to discriminate on routine imaging. We proposed to develop quantitative diagnostic criteria for single-energy computed tomography (SECT), dual-energy computed tomography (DECT), and quantitative susceptibility mapping (QSM) to distinguish hemorrhage from calcium. MATERIALS AND METHODS: Patients with positive susceptibility lesions on routine T2*-weighted magnetic resonance of the brain were recruited into this prospective imaging clinical trial, under institutional review board approval and with informed consent. The SECT, DECT, and QSM images were obtained, the lesions were identified, and the regions of interest were defined, with the mean values recorded. Criteria for quantitative interpretation were developed on the first 50 patients, and then applied to the next 45 patients. Contingency tables, scatter plots, and McNemar test were applied to compare classifiers. RESULTS: There were 95 evaluable patients, divided into a training set of 50 patients (328 lesions) and a validation set of 45 patients (281 lesions). We found the following classifiers to best differentiate hemorrhagic from calcific lesions: less than 68 Hounsfield units for SECT, calcium level of less than 15 mg/mL (material decomposition value) for DECT, and greater than 38 ppb for QSM. There was general mutual agreement among the proposed criteria. The proposed criteria outperformed the current published criteria. CONCLUSIONS: We provide the updated criteria for the classification of chronic positive susceptibility brain lesions as hemorrhagic versus calcific for each major clinically available imaging modality. These proposed criteria have greater internal consistency than the current criteria and should likely replace it as gold standard.

Short-Term Cessation of Dabigatran Causes a Paradoxical Prothrombotic State.

OBJECTIVE: It is unclear if stopping treatment with dabigatran, a new oral anticoagulant (NOAC), induces a paradoxical rebound prothrombotic state. We investigated if short-term (1-3 days) dabigatran cessation is associated with a higher thrombus volume than expected from a simple reversal of the anticoagulant effect. METHODS: Ten-week-old C57Bl/6 mice (n = 338) received one of the following oral treatments: phosphate-buffered saline (PBS), dabigatran for 7 days with or without 1 to 4 day cessation, and aspirin in either a single dose or daily for 7 days. Some of the animals that ceased dabigatran for 1 to 3 days received single-dose aspirin. Thereafter, we induced FeCl3 -mediated carotid thrombosis in 130 mice, after which we performed micro computed tomography thrombus imaging. The other 208 mice underwent coagulation assays or platelet function tests. As an explorative pilot study, we reviewed the medical records of 18 consecutive patients with NOAC cessation-related cerebral infarction in a large acute stroke cohort. RESULTS: We observed a ~ 40% higher volume of carotid thrombus after dabigatran cessation at 1 to 3 days than after vehicle treatment and showed that this effect could be prevented by single-dose aspirin pretreatment. Dabigatran cessation unduly increased platelet aggregability for 2 days after drug cessation, an effect mediated through thrombin or arachidonic acid, which effect was significantly attenuated by single-dose aspirin pretreatment. In patients, short-term (≤ 3 days) cessation of NOAC therapy, compared with longer-term (≥ 5 days) cessation, tended to be associated with relatively high stroke severity. INTERPRETATION: We provide the first preclinical evidence that a rebound prothrombotic state follows short-term cessation of dabigatran therapy. ANN NEUROL 2021;89:444-458.

Axonal Transport as an In Vivo Biomarker for Retinal Neuropathy.

We illuminate a possible explanatory pathophysiologic mechanism for retinal cellular neuropathy by means of a novel diagnostic method using ophthalmoscopic imaging and a molecular imaging agent targeted to fast axonal transport. The retinal neuropathies are a group of diseases with damage to retinal neural elements. Retinopathies lead to blindness but are typically diagnosed late, when substantial neuronal loss and vision loss have already occurred. We devised a fluorescent imaging agent based on the non-toxic C fragment of tetanus toxin (TTc), which is taken up and transported in neurons using the highly conserved fast axonal transport mechanism. TTc serves as an imaging biomarker for normal axonal transport and demonstrates impairment of axonal transport early in the course of an N-methyl-D-aspartic acid (NMDA)-induced excitotoxic retinopathy model in rats. Transport-related imaging findings were dramatically different between normal and retinopathic eyes prior to presumed neuronal cell death. This proof-of-concept study provides justification for future clinical translation.

Effects of exercise training and detraining on atheromatous matrix metalloproteinase activity in mice.

BACKGROUND AND AIMS: Exercise training (ET) helps treat atherosclerosis. However, many patients stop regular ET for various reasons. The effect of detraining on atherosclerosis is not well studied. We examined the effects of ET vs. short-term detraining on atheromatous matrix-metalloproteinase (MMP) activity in preexisting plaque and circulating cytokines/lipids. METHODS AND RESULTS: Eighteen-week-old apolipoprotein-E-/- mice (n = 56) on a Western diet underwent: 1) ET for 6-weeks (ET5+1), 2) ET for 5-weeks and detraining for 1-week (ET5+0), 3) ET for the last 1-week (ET0+1), or 4) no treadmill ET at all for 6-weeks (ET0+0). Atheromatous MMP-activity was visualized using molecular imaging with an MMP-2/9-activatable near-infrared-fluorescent probe. Compared with no ET (ET0+0), regular ET (ET5+1) decreased carotid atheromatous MMP activity, but this protective effect was significantly blunted by short-term detraining (ET5+0). Short-term detraining after longer-term ET showed a reduction in MMP-activity similar to short-term ET (ET0+1). Blood levels of lipids and cytokines paralleled the molecular imaging results: exercise caused higher levels of high-density lipoprotein, adiponectin, and interleukin-10 and lower levels of vascular cell adhesion molecule, monocyte chemoattractant protein-1, interleukin-1ß, and low-density lipoprotein. However, this beneficial effect was short-lived, with the ET5+0 group being similar to the ET0+0 group, and the ET0+1 group being similar to the ET5+1 group. The effect of exercise can be modeled with an exponential-decay of the protective factor of about 15%/day. CONCLUSIONS: Even short-term detraining reduces atheroprotective effects, and tips the balance towards atherosclerosis. This suggests that ET, to be effective, needs to be prolonged and regular, and that detraining should be avoided.

Disease Characteristics, Radiologic Patterns, Comorbid Diseases, and Ethnic Differences in 32 Patients With Rosai-Dorfman Disease.

OBJECTIVE: Rosai-Dorfman disease (RDD) is a rare and idiopathic nonneoplastic disease of histiocytes that is characterized by lymphadenopathy and extranodal disease. In this study, we documented anatomical preferences, imaging findings, comorbid diseases, and ethnic differences in 32 RDD patients. METHODS: We conducted a retrospective review of pathologically confirmed cases seen at our institution from 1998 to 2016. These cases were analyzed for (a) anatomical locations, (b) radiologic appearance, (c) comorbid diseases, and (d) differences between ethnic groups. RESULTS: We found 32 patients with RDD, 18 were women and 14 were men. There were 51 lesions in all patients, 23.5% of which were nodal, involving 11 lymph node regions, and 76.5% were extranodal. Cervical lymph nodes and maxillofacial area were the most common affected nodal and extranodal locations, respectively. Only 4 (12.5%) of 32 patients had pure nodal involvement, whereas 20 (62.5%) of 32 had pure extranodal disease and 8 (25%) of 32 had mixed nodal and extranodal disease.Anatomically, RDD affected multiple organs in our cohort, including the lymphatic system, maxillofacial area (glandular and nonglandular tissues), superficial soft tissue, central nervous system, breast, peritoneum, gastrointestinal tract, and lungs.Radiologically, RDD presentation was variable from an organ to another. However, most lesions were hypermetabolic on 18F-fluorodeoxyglucose positron-emission tomography/computed tomography and isointense on T1-weighted magnetic resonance imaging. Computed tomographic findings were extremely variable between organs.Comorbid diseases were found in 11 patients. Those patients had 17 comorbid diseases; the most common were autoimmune diseases, viral diseases, and cancer.The organ distribution of RDD was slightly different between ethnic groups. The most frequent disease location for African Americans was lymph nodes; for whites, central nervous system and nonglandular maxillofacial (27.3% each); for Asians, lymph nodes, subcutaneous tissue, and nonglandular maxillofacial (25% each); and for Hispanics, lymph nodes and glandular maxillofacial (33.3% each). CONCLUSIONS: Rosai-Dorfman disease represents a wide-spectrum disease not limited to lymph nodes. Radiologically, RDD has diverse imaging findings. However, most lesions were hypermetabolic on 18F-fluorodeoxyglucose positron-emission tomography/computed tomography and isointense on T1-weighted imaging. Patients with RDD have a high rate of comorbid diseases including autoimmune disease, viral infections, and cancer.

Hyperpolarized Pyruvate MR Spectroscopy Depicts Glycolytic Inhibition in a Mouse Model of Glioma.

BackgroundA generation of therapies targeting tumor metabolism is becoming available for treating glioma. Hyperpolarized MRI is uniquely suited to directly measure the metabolic effects of these emerging treatments.PurposeTo explore the feasibility of the use of hyperpolarized [1-carbon 13 {13C}]-pyruvate for real-time measurement of metabolism and response to treatment with a glycolytic inhibitor in an orthotopic mouse model of glioma.Materials and MethodsIn this animal study, anatomic MRI and dynamic 13C MR spectroscopy were performed at 7 T during intravenous injection of hyperpolarized [1-13C]-pyruvate on mice with orthotopic U87MG glioma and healthy control mice. Anatomic MRI and dynamic 13C MR spectroscopy were repeated after administration of the glycolytic inhibitor WP1122, a prodrug of 2-deoxy-d-glucose. All experiments were conducted in athymic nude mice between October 2016 and March 2017. Hyperpolarized lactate production was quantified as an apparent reaction rate, or kPL, and normalized lactate ratio (nLac). The Wilcoxon signed-rank test was used to assess changes in paired measures of lactate production before and after treatment.ResultsThirteen 12-16-week-old female mice and five healthy female mice underwent anatomic MRI and hyperpolarized [1-13C]-pyruvate spectroscopy. Large contrast agent-enhanced tumors were shown in mice with glioma at T2-weighted and T1-weighted postcontrast MRI by postimplantation day 40. After treatment with WP1122, a decrease in lactate was observed in mice with glioma (baseline and treatment mean kPL, 0.027 and 0.018 sec-1, respectively, P = .01; baseline and posttreatment mean nLac, 0.28 and 0.22, respectively, P = .01) whereas no significant decrease was observed in healthy control mice (baseline and posttreatment mean kPL, 0.011 and 0.017 sec-1, respectively, P = .91; baseline and posttreatment mean nLac, 0.16 and 0.21, respectively, P = .84).ConclusionHyperpolarized carbon 13 measurements of pyruvate metabolism can provide rapid feedback for monitoring treatment response in glioma.© RSNA, 2019.