White matter multi-resolution segmentation using fuzzy set theory

International audienceThe neural architecture of the white matter of the brain, obtained using tractography algorithms, can be divided into different tracts. Their function is, in many cases, still an object of study and might be affected in some syndromes or conditions. Obtaining a reproducible and correct segmentation is therefore crucial both in clinics and in research. However, it is difficult to obtain due to the huge number of fibers and high inter-subject variability. In this paper, we propose to segment and recognize tracts by directly modeling their anatomical definitions, which are usually based on relationships between structures. Since these definitions are mainly qualitative, we propose to model their intrinsic vagueness using fuzzy spatial relations and combine them into a single quantitative score mapped to each fiber. To cope with the high redundancy of tractograms and ease interpretation , we also take advantage of a simplification scheme based on a multi-resolution representation. This allows for an interactive and real-time navigation through different levels of detail. We illustrate our method using the Human Connectome Project dataset and compare it to other well-known white matter segmentation techniques

A Meta-Analysis of Survival Outcomes Following Reoperation in Recurrent Glioblastoma: Time to Consider the Timing of Reoperation

Background: Glioblastoma multiforme (GBM) inevitably recurs, but no standard regimen has been established for recurrent patients. Reoperation at recurrence alleviates mass effects, and the survival benefit has been reported in many studies. However, in most studies, the effect of reoperation timing on survival benefit was ignored. The aim of this meta-analysis was to investigate whether reoperation provided similar survival benefits in recurrent GBM patients when it was analyzed as a fixed or time-dependent covariate.Methods: A systematic literature search of PubMed, EMBASE, and Cochrane databases was performed to identify original articles that evaluated the associations between reoperation and prognosis in recurrent GBM patients.Results: Twenty-one articles involving 8,630 patients were included. When reoperation was considered as a fixed covariate, it was associated with better overall survival (OS) and post-progression survival (PPS) (OS: HR = 0.66, 95% CI 0.61-0.71, p < 0.001, I2 = 0%; PPS: HR = 0.70, 95% CI 0.57–0.88, p < 0.01, I2 = 70.2%). However, such a survival benefit was not observed when reoperation was considered as a time-dependent covariate (OS: HR = 2.19, 95% CI 1.47–3.27, p < 0.001; PPS: HR = 0.95, 95% CI 0.82–1.10, p = 0.51, I2 = 0%). The estimate bias caused by ignoring the time-dependent nature of reoperation was further demonstrated by the re-analysis of survival data in three included studies.Conclusions: The timing of reoperation may have an impact on the survival outcome in recurrent GBM patients, and survival benefits of reoperation in recurrent GBM may be overestimated when analyzed as fixed covariates. Proper analysis methodology should be used in future work to confirm the clinical benefits of reoperation

Imaging of non tumorous and tumorous human brain tissue with full-field optical coherence tomography

A prospective study was performed on neurosurgical samples from 18 patients to evaluate the use of Full-Field Optical Coherence Tomography (FF-OCT) in brain tumor diagnosis. FF-OCT captures en face slices of tissue samples at 1\mum resolution in 3D with a typical 200\mum imaging depth. A 1cm2 specimen is scanned at a single depth and processed in about 5 minutes. This rapid imaging process is non-invasive and 30 requires neither contrast agent injection nor tissue preparation, which makes it particularly well suited to medical imaging applications. Temporal chronic epileptic parenchyma and brain tumors such as meningiomas, low- grade and high-grade gliomas, and choroid plexus papilloma were imaged. A subpopulation of neurons, myelin fibers and CNS vasculature were clearly identified. Cortex could be discriminated from white matter, but individual glial cells as astrocytes (normal or reactive) or oligodendrocytes were not observable. This study reports for the first time on the feasibility of using FF-OCT in a real-time manner as a label-free non-invasive imaging technique in an intra-operative neurosurgical clinical setting to assess tumorous glial and epileptic margins

Domain Mapping and Deep Learning from Multiple MRI Clinical Datasets for Prediction of Molecular Subtypes in Low Grade Gliomas

Brain tumors, such as low grade gliomas (LGG), are molecularly classified which require the surgical collection of tissue samples. The pre-surgical or non-operative identification of LGG molecular type could improve patient counseling and treatment decisions. However, radiographic approaches to LGG molecular classification are currently lacking, as clinicians are unable to reliably predict LGG molecular type using magnetic resonance imaging (MRI) studies. Machine learning approaches may improve the prediction of LGG molecular classification through MRI, however, the development of these techniques requires large annotated data sets. Merging clinical data from different hospitals to increase case numbers is needed, but the use of different scanners and settings can affect the results and simply combining them into a large dataset often have a significant negative impact on performance. This calls for efficient domain adaption methods. Despite some previous studies on domain adaptations, mapping MR images from different datasets to a common domain without affecting subtitle molecular-biomarker information has not been reported yet. In this paper, we propose an effective domain adaptation method based on Cycle Generative Adversarial Network (CycleGAN). The dataset is further enlarged by augmenting more MRIs using another GAN approach. Further, to tackle the issue of brain tumor segmentation that requires time and anatomical expertise to put exact boundary around the tumor, we have used a tight bounding box as a strategy. Finally, an efficient deep feature learning method, multi-stream convolutional autoencoder (CAE) and feature fusion, is proposed for the prediction of molecular subtypes (1p/19q-codeletion and IDH mutation). The experiments were conducted on a total of 161 patients consisting of FLAIR and T1 weighted with contrast enhanced (T1ce) MRIs from two different institutions in the USA and France. The proposed scheme is shown to achieve the test accuracy of\ua074.81%\ua0on 1p/19q codeletion and\ua081.19%\ua0on IDH mutation, with marked improvement over the results obtained without domain mapping. This approach is also shown to have comparable performance to several state-of-the-art methods

Diagnostic performance of dynamic 3D magnetic resonance angiography in daily practice for the detection of intracranial arteriovenous shunts in patients with non-traumatic intracranial hemorrhage

IntroductionIdentification of treatable causes of intracranial hemorrhage (ICH) such as intracranial arteriovenous shunt is crucial to prevent recurrence. However, diagnostic approaches vary considerably across centers, partly because of limited knowledge of the diagnostic performance of first-line vascular imaging techniques. We assessed the diagnostic performance of dynamic three-dimensional magnetic resonance angiography (dynamic 3D MRA) in daily practice to detect intracranial arteriovenous shunts in ICH patients against subsequent digital subtraction angiography (DSA) as reference standard.MethodsWe reviewed all adult patients who underwent first-line dynamic 3D MRA and subsequent DSA for non-traumatic ICH between January 2016 and September 2021 in a tertiary center. Sensitivity, specificity, accuracy, positive and negative predictive values of dynamic 3D MRA for the detection of intracranial arteriovenous shunt were calculated with DSA as reference standard.ResultsAmong 104 included patients, 29 (27.9%) had a DSA-confirmed arteriovenous shunt [19 pial arteriovenous malformations, 10 dural arteriovenous fistulae; median onset-to-DSA: 17 (IQR: 3–88) days]. The sensitivity and specificity of dynamic 3D MRA [median onset-to-dynamic 3D MRA: 14 (3–101) h] for the detection of intracranial arteriovenous shunt were 66% (95% CI: 48–83) and 91% (95% CI: 84–97), respectively. The corresponding accuracy, positive and negative predictive values were 84% (95% CI: 77–91), 73% (95% CI: 56–90), and 87% (95% CI: 80–95), respectively.ConclusionThis study suggests that although first-line evaluation with dynamic 3D MRA may be helpful for the detection of intracranial arteriovenous shunts in patients with ICH, additional vascular imaging work-up should not be withheld if dynamic 3D MRA is negative. Comparative prospective studies are needed to determine the best imaging strategy to diagnose arteriovenous shunts after non-traumatic ICH

Imaging practice in low-grade gliomas among European specialized centers and proposal for a minimum core of imaging

Objective: Imaging studies in diffuse low-grade gliomas (DLGG) vary across centers. In order to establish a minimal core of imaging necessary for further investigations and clinical trials in the field of DLGG, we aimed to establish the status quo within specialized European centers. Methods: An online survey composed of 46 items was sent out to members of the European Low-Grade Glioma Network, the European Association of Neurosurgical Societies, the German Society of Neurosurgery and the Austrian Society of Neurosurgery. Results: A total of 128 fully completed surveys were received and analyzed. Most centers (n=96, 75%) were academic and half of the centers (n=64, 50%) adhered to a dedicated treatment program for DLGG. There were national differences regarding the sequences enclosed in MRI imaging and use of PET, however most included T1 (without and with contrast, 100%), T2 (100%) and TIRM or FLAIR (20, 98%). DWI is performed by 80% of centers and 61% of centers regularly performed PWI.ConclusionA minimal core of imaging composed of T1 (w/wo contrast), T2, TIRM/FLAIR, PWI and DWI could be identified. All morphologic images should be obtained in a slice thickness of 3mm. No common standard could be obtained regarding advanced MRI protocols and PET. Importance of the study: We believe that our study makes a significant contribution to the literature because we were able to determine similarities in numerous aspects of LGG imaging. Using the proposed minimal core of imaging in clinical routine will facilitate future cooperative studies

Predictive value of S100-B and copeptin for outcomes following seizure: the BISTRO International Cohort Study.

OBJECTIVE: To evaluate the performance of S100-B protein and copeptin, in addition to clinical variables, in predicting outcomes of patients attending the emergency department (ED) following a seizure. METHODS: We prospectively included adult patients presented with an acute seizure, in four EDs in France and the United Kingdom. Participants were followed up for 28 days. The primary endpoint was a composite of seizure recurrence, all-cause mortality, hospitalization or rehospitalisation, or return visit in the ED within seven days. RESULTS: Among the 389 participants included in the analysis, 156 (40%) experienced the primary endpoint within seven days and 195 (54%) at 28 days. Mean levels of both S100-B (0.11 μg/l [95% CI 0.07-0.20] vs 0.09 μg/l [0.07-0.14]) and copeptin (23 pmol/l [9-104] vs 17 pmol/l [8-43]) were higher in participants meeting the primary endpoint. However, both biomarkers were poorly predictive of the primary outcome with a respective area under the receiving operator characteristic curve of 0.57 [0.51-0.64] and 0.59 [0.54-0.64]. Multivariable logistic regression analysis identified higher age (odds ratio [OR] 1.3 per decade [1.1-1.5]), provoked seizure (OR 4.93 [2.5-9.8]), complex partial seizure (OR 4.09 [1.8-9.1]) and first seizure (OR 1.83 [1.1-3.0]) as independent predictors of the primary outcome. A second regression analysis including the biomarkers showed no additional predictive benefit (S100-B OR 3.89 [0.80-18.9] copeptin OR 1 [1.00-1.00]). CONCLUSION: The plasma biomarkers S100-B and copeptin did not improve prediction of poor outcome following seizure. Higher age, a first seizure, a provoked seizure and a partial complex seizure are independently associated with adverse outcomes

Imaging practice in low-grade gliomas among European specialized centers and proposal for a minimum core of imaging.

OBJECTIVE: Imaging studies in diffuse low-grade gliomas (DLGG) vary across centers. In order to establish a minimal core of imaging necessary for further investigations and clinical trials in the field of DLGG, we aimed to establish the status quo within specialized European centers. METHODS: An online survey composed of 46 items was sent out to members of the European Low-Grade Glioma Network, the European Association of Neurosurgical Societies, the German Society of Neurosurgery and the Austrian Society of Neurosurgery. RESULTS: A total of 128 fully completed surveys were received and analyzed. Most centers (n = 96, 75%) were academic and half of the centers (n = 64, 50%) adhered to a dedicated treatment program for DLGG. There were national differences regarding the sequences enclosed in MRI imaging and use of PET, however most included T1 (without and with contrast, 100%), T2 (100%) and TIRM or FLAIR (20, 98%). DWI is performed by 80% of centers and 61% of centers regularly performed PWI. CONCLUSION: A minimal core of imaging composed of T1 (w/wo contrast), T2, TIRM/FLAIR, PWI and DWI could be identified. All morphologic images should be obtained in a slice thickness of ≤ 3 mm. No common standard could be obtained regarding advanced MRI protocols and PET. IMPORTANCE OF THE STUDY: We believe that our study makes a significant contribution to the literature because we were able to determine similarities in numerous aspects of LGG imaging. Using the proposed "minimal core of imaging" in clinical routine will facilitate future cooperative studies