Faut-il injecter ? Tourdias, Thomas; Dousset, Vincent
Journal of neuroradiology,
March 2016, Letnik:
43, Številka:
2
Journal Article
Recenzirano
Le rehaussement d’une lésion de sclérose en plaques (SEP) est un critère important traduisant l’activité de la maladie. La prise de contraste d’une lésion est inclue dans les critères diagnostiques ...révisés en 2010. Il s’agit également d’un élément pronostique et permettant de guider la prise en charge thérapeutique. De même certains aspects de rehaussement peuvent orienter vers le diagnostic de leucoencéphalopathie multifocale (LEMP) chez un patient traité par natalizumab (Tysabri® ). Ainsi, l’injection de gadolinium est une pratique courante et répétée chez les patients atteints de SEP (recommandation de l’OFSEP 1 ). Néanmoins, depuis 2014, de nombreux auteurs ont rapporté l’apparition d’hypersignaux T1, particulièrement au sein des noyaux dentelés et des globus pallidus, chez des patients ayant reçu plusieurs injections 2–6 . Des analyses post-mortem ont montré que ces hypersignaux T1 étaient en rapport avec une accumulation de gadolinium intracérébrale. Les conséquences de cette accumulation progressive de gadolinium dans les noyaux gris centraux suite à des injections répétées restent pour le moment non-connues. Néanmoins ces observations font discuter l’innocuité parfaite des injections répétées. Cela nous invite à reconsidérer les situations face auxquelles l’injection d’un patient suspect ou diagnostiqué avec une SEP est une vraie nécessité ou peut être évitée.
Abstract only Introduction: Initial motor impairment assessed in the acute stroke phase (as measured by the Fugl-Meyer (FM) Assessment) is a strong predictor of lower extremity (LE) motor impairment ...at 3 months (Smith et al., 2017). The predictive value of measures of motor tract integrity, lesion size and location is not known. For our analysis we combined two motor tracts that might be particularly important in the control of proximal leg muscles to create a canonical tract of the corticospinal tract proper (CST) and the corticorubrospinal tract (CRST)(Lindenberg et al., 2010; Rueber et al., 2012). In previous work (Feng et al., 2015) we have shown that weighted CST-Lesion Load (a combined variable of lesion size and location) is a significant predictor of 3 months outcome for the UE. Hypothesis: Weighted CST-CRST Lesion-Load (wCST/CRST-LL) can improve the FM-based predictions of lower limb motor recovery. Methods: Ischemic stroke patients with a upper limb paresis (UE-FM<66) and lower limb paresis (LE-FM<34) were assessed between 48-72h and 3 months poststroke with the FM scale. Lesion maps drawn on diffusion-weighted images were used to calculate lesion loads of a combined CST-CRST probabilistic tract derived from matched elderly healthy control subjects. Then, several variables that have been shown to predict outcome (e.g., FM, lesion load, age, hemisphere) were subjected to individual regression analyses. Significant variables (at p<0.05) were entered into a multiple regression model to assess predictors of lower limb motor recovery (i.e., actual difference in LE-FM between 3 months and initial stroke phase assessment). Results: Both baseline and 3-months follow-up were available for 134 patients. Initial motor impairment (FM-LE) and wCST/CRST-LL were independent strong predictors of lower limb motor recovery (respectively p<0.0001 and p=0.0005). Combining initial motor impairment and wCST/CRST lesion load was a much better model than FM-LE by itself (respectively R2=0.43 and R2=0.46, p=0.003) which was confirmed by the Akaike Information Criterion (AIC). Conclusion: wCST/CRST-LL, a combined measure of lesion size/location, adds significant power to a combined model with FM, but is also a strong predictor of lower limb motor recovery by itself.
BACKGROUND AND PURPOSE—On top of functional outcome, accurate prediction of cognitive outcome for stroke patients is an unmet need with major implications for clinical management. We investigated ...whether stroke location may contribute independent prognostic value to multifactorial predictive models of functional and cognitive outcomes.
METHODS—Four hundred twenty-eight consecutive patients with ischemic stroke were prospectively assessed with magnetic resonance imaging at 24 to 72 hours and at 3 months for functional outcome using the modified Rankin Scale and cognitive outcome using the Montreal Cognitive Assessment (MoCA). Statistical maps of functional and cognitive eloquent regions were derived from the first 215 patients (development sample) using voxel-based lesion-symptom mapping. We used multivariate logistic regression models to study the influence of stroke location (number of eloquent voxels from voxel-based lesion-symptom mapping maps), age, initial National Institutes of Health Stroke Scale and stroke volume on modified Rankin Scale and MoCA. The second part of our cohort was used as an independent replication sample.
RESULTS—In univariate analyses, stroke location, age, initial National Institutes of Health Stroke Scale, and stroke volume were all predictive of poor modified Rankin Scale and MoCA. In multivariable analyses, stroke location remained the strongest independent predictor of MoCA and significantly improved the prediction compared with using only age, initial National Institutes of Health Stroke Scale, and stroke volume (area under the curve increased from 0.697–0.771; difference=0.073; 95% confidence interval, 0.008–0.155). In contrast, stroke location did not persist as independent predictor of modified Rankin Scale that was mainly driven by initial National Institutes of Health Stroke Scale (area under the curve going from 0.840 to 0.835). Similar results were obtained in the replication sample.
CONCLUSIONS—Stroke location is an independent predictor of cognitive outcome (MoCA) at 3 months post stroke.
In this article, we present an innovative MRI‐based method for Alzheimer disease (AD) detection and mild cognitive impairment (MCI) prognostic, using lifespan trajectories of brain structures. After ...a full screening of the most discriminant structures between AD and normal aging based on MRI volumetric analysis of 3,032 subjects, we propose a novel Hippocampal‐Amygdalo‐Ventricular Atrophy score (HAVAs) based on normative lifespan models and AD lifespan models. During a validation on three external datasets on 1,039 subjects, our approach showed very accurate detection (AUC ≥ 94%) of patients with AD compared to control subjects and accurate discrimination (AUC = 78%) between progressive MCI and stable MCI (during a 3‐year follow‐up). Compared to normative modeling, classical machine learning methods and recent state‐of‐the‐art deep learning methods, our method demonstrated better classification performance. Moreover, HAVAs simplicity makes it fully understandable and thus well‐suited for clinical practice or future pharmaceutical trials.
In this article, we present an innovative MRI‐based method for Alzheimer disease (AD) detection and mild cognitive impairment (MCI) prognostic, using lifespan trajectories of brain structures. Compared to normative modeling and recent state‐of‐the‐art deep learning methods, our method demonstrated better classification performance. Moreover, it simplicity makes it fully understandable and thus well‐suited for clinical practice or future pharmaceutical trials.
Gadolinium leakage in ocular structures (GLOS) was recently observed in fluid-attenuated inversion recovery (FLAIR) images obtained the day after an initial gadolinium injection in stroke patients. ...The specificity of GLOS to stroke and its mechanisms remain unclear.
We investigated the factors associated with GLOS in a cohort of patients presenting with acute neurological deficits.
This retrospective study included consecutive patients admitted to our stroke unit for acute neurological deficit between July 2017 and August 2018 who underwent baseline brain magnetic resonance imaging with the injection of a macrocyclic gadolinium agent and another scan without injection within 72 hours. The patients were separated into a stroke group and a stroke mimic group based on diffusion-weighted images. Gadolinium leakage in ocular structures was defined as a bright signal in the vitreous in follow-up FLAIR compared with baseline FLAIR (pregadolinium). Clinical data were collected together with imaging features from the baseline scans, including the volume of the infarct and of hypoperfusion if applicable, white matter hyperintensities, the number of lacunes, and the number of microbleeds, which were combined to yield a small vessel disease (SVD) score. We compared the prevalence of GLOS in both groups using the χ2 test. In the entire cohort, univariate and multivariate regression models were used to test the associations between GLOS and the collected data.
Among the 467 patients included in the study, GLOS was observed in similar proportions in the stroke group (32.2%, 136/422) and the stroke mimic group (28.9%, 13/45; mean difference, 3.3%; 95% confidence interval, -10.9 to 17.6; P = 0.65). In univariate analysis, GLOS was associated with older age, increased prevalence of vascular risk factors, brain imaging features of SVD (white matter hyperintensities, lacunes, microbleeds), as well as with impairment of renal function and increased dose of gadolinium. No associations were found with factors related to stroke, such as its volume, acute treatment, or rate of recanalization. Multivariate analyses showed that aging (P < 0.001), diabetes (P = 0.010), severe renal failure (P = 0.004), and increased dose of gadolinium (P < 0.001) were independent contributors to GLOS.
Gadolinium leakage in ocular structures, which occurs more commonly at higher concentrations of gadolinium, is not specific to stroke and may represent increased permeability of the blood-retinal barrier associated with age- and vascular risk factor-related SVD.
Delayed cerebral ischemia associated with cerebral vasospasm (CVS) in aneurysmal subarachnoid hemorrhage significantly affects patient prognosis. Levosimendan has emerged as a potential treatment, ...but clinical data are lacking. The aim of this study is to decipher levosimendan's effect on cerebral hemodynamics by automated quantitative measurements of brain computed tomography perfusion (CTP).
We conducted a retrospective analysis of a database of a neurosurgical intensive care unit. All patients admitted from January 2018 to July 2022 for aneurysmal subarachnoid hemorrhage and treated with levosimendan for CVS who did not respond to other therapies were included. Quantitative measurements of time to maximum (Tmax), relative cerebral blood volume (rCBV), and relative cerebral blood flow (rCBF) were automatically compared with coregistered CTP before and after levosimendan administration in oligemic regions.
Of 21 patients included, CTP analysis could be performed in 16. Levosimendan improved Tmax from 14.4 s (interquartile range IQR 9.1-21) before treatment to 7.1 s (IQR 5.5-8.1) after treatment (p < 0.001). rCBV (94% IQR 79-103 before treatment and 89% IQR 72-103 after treatment, p = 0.63) and rCBF (85% IQR 77-90 before treatment and 87% IQR 73-98 after treatment, p = 0.98) remained stable. The subgroup of six patients who did not develop cerebral infarction attributed to delayed cerebral ischemia showed an approximately 10% increase (rCBV 85% IQR 79-99 before treatment vs. 95% IQR 88-112 after treatment, p = 0.21; rCBF 81% IQR 76-87 before treatment vs. 89% IQR 84-99 after treatment, p = 0.4).
In refractory CVS, levosimendan use was associated with a significant reduction in Tmax in oligemic regions. However, this value remained at an abnormal level, indicating the presence of a persistent CVS. Further analysis raised the hypothesis that levosimendan causes cerebral vasodilation, but other studies are needed because our design does not allow us to quantify the effect of levosimendan from that of the natural evolution of CVS.
L'angiopathie amyloïde cérébrale représente une forme particulière de maladie des petites artères cérébrales. Elle est caractérisée par l'accumulation, dans les parois des petites artères cérébrales, ...de dépôts de protéines amyloïdes. Elle est le plus souvent sporadique chez les sujets âgés et se manifeste par des hémorragies intracérébrales de topographie lobaire. Toutefois, certaines formes, notamment chez le sujet jeune, peuvent être d'origine génétique ou iatrogène. (1,2)
nous présentons le cas d'un patient de 40 ans, suivi pendant plusieurs années, et ayant présenté de multiples hématomes et microsaignements lobaires associés à une extension de foyers d'hémosidérose. Son évolution clinique rapide et son jeune âge constituaient des atypies cliniques conduisant à la recherche de causes secondaires. Son antécédent médico-chirurgical principal était un traumatisme crânien grave opéré dans son enfance. Après avoir éliminé les différentes causes d'angiopathie amyloïde du sujet jeune, nous avons retenu le diagnostic final d'angiopathie amyloïde secondaire à l'exposition à une dure-mère d'origine cadavérique d'un donneur possiblement porteur d'angiopathie amyloïde, suite à la chirurgie du traumatisme crânien dans l'enfance.
après recherche complète de base de données internationales Pubmed, Cochrane, Embase et Google Scholar, nous avons identifié les cas de 20 patients ayant présenté le déclenchement précoce d'une angiopathie amyloïde à distance d'une intervention chirurgicale avec potentielle contamination par le peptide ?-amyloïde. Ils présentaient des caractéristiques cliniques similaires à notre patient avec un début précoce, à distance de l'exposition.
l'angiopathie amyloïde cérébrale d'origine iatrogène représente une cause rare et méconnue d'hématomes lobaires récidivants du sujet jeune. Elle alimente la théorie récente de propagation du peptide bêta-amyloïde sous forme prion suite à la transmission chirurgicale des années auparavant. Elle présente une potentielle conséquence clinique majeure et nécessite une reconnaissance rapide du diagnostic en imagerie (fig 1).
The hippocampus contains distinct populations of neurons organized into separate anatomical subfields and layers with differential vulnerability to pathological mechanisms. The ability of in vivo ...neuroimaging to pinpoint regional vulnerability is especially important for better understanding of hippocampal pathology at the early stage of neurodegenerative disorders and for monitoring future therapeutic strategies. This is the case for instance in multiple sclerosis whose neurodegenerative component can affect the hippocampus from the early stage. We challenged the capacity of two models, i.e. the classical diffusion tensor imaging (DTI) model and the neurite orientation dispersion and density imaging (NODDI) model, to compute quantitative diffusion MRI that could capture microstructural alterations in the individual hippocampal layers of experimental-autoimmune encephalomyelitis (EAE) mice, the animal model of multiple sclerosis. To achieve this, the hippocampal anatomy of a healthy mouse brain was first explored ex vivo with high resolution DTI and NODDI. Then, 18 EAE mice and 18 control mice were explored 20 days after immunization with in vivo diffusion MRI prior to sacrifice for the histological quantification of neurites and glial markers in each hippocampal layer. Fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) maps were computed from the DTI model while the orientation dispersion index (ODI), the neurite density index (NDI) and the volume fraction of isotropic diffusivity (isoVF) maps were computed from the NODDI model. We first showed in control mice that color-coded FA and ODI maps can delineate three main hippocampal layers. The quantification of FA, AD, RD, MD, ODI, NDI and isoVF presented differences within these 3 layers, especially within the molecular layer of the dentate gyrus which displayed a specific signature based on a combination of AD (or MD), ODI and NDI. Then, the comparison between EAE and control mice showed a decrease of AD (p = 0.036) and of MD (p = 0.033) selectively within the molecular layer of EAE mice while NODDI indices did not present any difference between EAE and control mice in any layer. Histological analyses confirmed the differential vulnerability of the molecular layer of EAE mice that exhibited decreased dendritic length and decreased dendritic complexity together with activated microglia. Dendritic length and intersections within the molecular layer were independent contributors to the observed decrease of AD (R2 = 0.37 and R2 = 0.40, p < 0.0001) and MD (R2 = 0.41 and R2 = 0.42, p < 0.0001). We therefore identified that NODDI maps can help to highlight the internal microanatomy of the hippocampus but NODDI still presents limitations in grey matter as it failed to capture selective dendritic alterations occurring at early stages of a neurodegenerative disease such as multiple sclerosis, whereas DTI maps were significantly altered.
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•NODDI can delineate the internal anatomy of the mouse hippocampus in vivo.•Quantitative NODDI and DTI data can be collected in vivo in a single hippocampal layer.•AD and MD correlate with dendritic damage in the molecular layer of EAE mice.•NODDI data fail to capture dendritic damages in the molecular layer of EAE mice.•DTI may be more sensitive than NODDI in detecting early changes in the hippocampal layers.
Accurate quantification of WM lesion load is essential for the care of patients with multiple sclerosis. We tested whether the combination of accelerated 3D-FLAIR and denoising using deep ...learning-based reconstruction could provide a relevant strategy while shortening the imaging examination.
Twenty-eight patients with multiple sclerosis were prospectively examined using 4 implementations of 3D-FLAIR with decreasing scan times (4 minutes 54 seconds, 2 minutes 35 seconds, 1 minute 40 seconds, and 1 minute 15 seconds). Each FLAIR sequence was reconstructed without and with denoising using deep learning-based reconstruction, resulting in 8 FLAIR sequences per patient. Image quality was assessed with the Likert scale, apparent SNR, and contrast-to-noise ratio. Manual and automatic lesion segmentations, performed randomly and blindly, were quantitatively evaluated against ground truth using the absolute volume difference, true-positive rate, positive predictive value, Dice similarity coefficient, Hausdorff distance, and F1 score based on the lesion count. The Wilcoxon signed-rank test and 2-way ANOVA were performed.
Both image-quality evaluation and the various metrics showed deterioration when the FLAIR scan time was accelerated. However, denoising using deep learning-based reconstruction significantly improved subjective image quality and quantitative performance metrics, particularly for manual segmentation. Overall, denoising using deep learning-based reconstruction helped to recover contours closer to those from the criterion standard and to capture individual lesions otherwise overlooked. The Dice similarity coefficient was equivalent between the 2-minutes-35-seconds-long FLAIR with denoising using deep learning-based reconstruction and the 4-minutes-54-seconds-long reference FLAIR sequence.
Denoising using deep learning-based reconstruction helps to recognize multiple sclerosis lesions buried in the noise of accelerated FLAIR acquisitions, a possibly useful strategy to efficiently shorten the scan time in clinical practice.
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