The Nomenclature of Human White Matter Association Pathways: Proposal for a Systematic Taxonomic Anatomical Classification

The heterogeneity and complexity of white matter (WM) pathways of the human brain were discretely described by pioneers such as Willis, Stenon, Malpighi, Vieussens and Vicq d’Azyr up to the beginning of the 19th century. Subsequently, novel approaches to the gross dissection of brain internal structures have led to a new understanding of WM organization, notably due to the works of Reil, Gall and Burdach highlighting the fascicular organization of WM. Meynert then proposed a definitive tripartite organization in association, commissural and projection WM pathways. The enduring anatomical work of Dejerine at the turn of the 20th century describing WM pathways in detail has been the paramount authority on this topic (including its terminology) for over a century, enriched sporadically by studies based on blunt Klingler dissection. Currently, diffusion-weighted magnetic resonance imaging (DWI) is used to reveal the WM fiber tracts of the human brain in vivo by measuring the diffusion of water molecules, especially along axons. It is then possible by tractography to reconstitute the WM pathways of the human brain step by step at an unprecedented level of precision in large cohorts. However, tractography algorithms, although powerful, still face the complexity of the organization of WM pathways, and there is a crucial need to benefit from the exact definitions of the trajectories and endings of all WM fascicles. Beyond such definitions, the emergence of DWI-based tractography has mostly revealed strong heterogeneity in naming the different bundles, especially the long-range association pathways. This review addresses the various terminologies known for the WM association bundles, aiming to describe the rules of arrangements followed by these bundles and to propose a new nomenclature based on the structural wiring diagram of the human brain

A systematic review of the use of subcortical intraoperative electrical stimulation mapping for monitoring of executive deficits and neglect:What is the evidence so far?

BACKGROUND: Over the past decade, the functional importance of white matter pathways has been increasingly acknowledged in neurosurgical planning. A method to directly study anatomo-functional correlations is direct electrical stimulation (DES). DES has been widely accepted by neurosurgeons as a reliable tool to minimize the occurrence of permanent postoperative motor, vision, and language deficits. In recent years, DES has also been used for stimulation mapping of other cognitive functions, such as executive functions and visuospatial awareness. METHODS: The aim of this review is to summarize the evidence so far from DES studies on subcortical pathways that are involved in visuospatial awareness and in the following three executive functions: (1) inhibitory control, (2) working memory, and (3) cognitive flexibility. RESULTS: Eleven articles reported on intraoperative electrical stimulation of white matter pathways to map the cognitive functions and explicitly clarified which subcortical tract was stimulated. The results indicate that the right SLF-II is involved in visuospatial awareness, the left SLF-III and possibly the right SLF-I are involved in working memory, and the cingulum is involved in cognitive flexibility. CONCLUSIONS: We were unable to draw any more specific conclusions, nor unequivocally establish the critical involvement of pathways in executive functions or visuospatial awareness due to the heterogeneity of the study types and methods, and the limited number of studies that assessed these relationships. Possible approaches for future research to obtain converging and more definite evidence for the involvement of pathways in specific cognitive functions are discussed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00701-021-05012-w

Language processing from the perspective of electrical stimulation mapping

Electrical Stimulation (ES) is a neurostimulation technique that is used to localize language functions in the brain of people with intractable epilepsy and/or brain tumors. We reviewed 25 ES articles published between 1984 and 2018 and interpreted them from a cognitive neuropsychological perspective. Our aim was to highlight ES as a tool to further our understanding of cognitive models of language. We focused on associations and dissociations between cognitive functions within the framework of two non-neuroanatomically specified models of language. Also, we discussed parallels between the ES and the stroke literatures and showed how ES data can help us to generate hypotheses regarding how language is processed. A good understanding of cognitive models of language is essential to motivate task selection and to tailor surgical procedures, for example, by avoiding testing the same cognitive functions and understanding which functions may be more or less relevant to be tested during surgery

Augmented reality for the virtual dissection of white matter pathways

Background: The human white matter pathway network is complex and of critical importance for functionality. Thus, learning and understanding white matter tract anatomy is important for the training of neuroscientists and neurosurgeons. The study aims to test and evaluate a new method for fiber dissection using augmented reality (AR) in a group which is experienced in cadaver white matter dissection courses and in vivo tractography. Methods: Fifteen neurosurgeons, neurolinguists, and neuroscientists participated in this questionnaire-based study. We presented five cases of patients with left-sided perisylvian gliomas who underwent awake craniotomy. Diffusion tensor imaging fiber tracking (DTI FT) was performed and the language-related networks were visualized separated in different tracts by color. Participants were able to virtually dissect the prepared DTI FTs using a spatial computer and AR goggles. The application was evaluated through a questionnaire with answers from 0 (minimum) to 10 (maximum). Results: Participants rated the overall experience of AR fiber dissection with a median of 8 points (mean ± standard deviation 8.5 ± 1.4). Usefulness for fiber dissection courses and education in general was rated with 8 (8.3 ± 1.4) and 8 (8.1 ± 1.5) points, respectively. Educational value was expected to be high for several target audiences (student: median 9, 8.6 ± 1.4; resident: 9, 8.5 ± 1.8; surgeon: 9, 8.2 ± 2.4; scientist: 8.5, 8.0 ± 2.4). Even clinical application of AR fiber dissection was expected to be of value with a median of 7 points (7.0 ± 2.5). Conclusion: The present evaluation of this first application of AR for fiber dissection shows a throughout positive evaluation for educational purposes

On the cutting edge of glioblastoma surgery:where neurosurgeons agree and disagree on surgical decisions

OBJECTIVE: The aim of glioblastoma surgery is to maximize the extent of resection while preserving functional integrity. Standards are lacking for surgical decision-making, and previous studies indicate treatment variations. These shortcomings reflect the need to evaluate larger populations from different care teams. In this study, the authors used probability maps to quantify and compare surgical decision-making throughout the brain by 12 neurosurgical teams for patients with glioblastoma. METHODS: The study included all adult patients who underwent first-time glioblastoma surgery in 2012-2013 and were treated by 1 of the 12 participating neurosurgical teams. Voxel-wise probability maps of tumor location, biopsy, and resection were constructed for each team to identify and compare patient treatment variations. Brain regions with different biopsy and resection results between teams were identified and analyzed for patient functional outcome and survival. RESULTS: The study cohort consisted of 1087 patients, of whom 363 underwent a biopsy and 724 a resection. Biopsy and resection decisions were generally comparable between teams, providing benchmarks for probability maps of resections and biopsies for glioblastoma. Differences in biopsy rates were identified for the right superior frontal gyrus and indicated variation in biopsy decisions. Differences in resection rates were identified for the left superior parietal lobule, indicating variations in resection decisions. CONCLUSIONS: Probability maps of glioblastoma surgery enabled capture of clinical practice decisions and indicated that teams generally agreed on which region to biopsy or to resect. However, treatment variations reflecting clinical dilemmas were observed and pinpointed by using the probability maps, which could therefore be useful for quality-of-care discussions between surgical teams for patients with glioblastoma

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

The Superoanterior Fasciculus (SAF): A Novel White Matter Pathway in the Human Brain?

Fiber tractography (FT) using diffusion magnetic resonance imaging (dMRI) is widely used for investigating microstructural properties of white matter (WM) fiber-bundles and for mapping structural connections of the human brain. While studying the architectural configuration of the brain’s circuitry with FT is not without controversy, recent progress in acquisition, processing, modeling, analysis, and visualization of dMRI data pushes forward the reliability in reconstructing WM pathways. Despite being aware of the well-known pitfalls in analyzing dMRI data and several other limitations of FT discussed in recent literature, we present the superoanterior fasciculus (SAF), a novel bilateral fiber tract in the frontal region of the human brain that—to the best of our knowledge—has not been documented. The SAF has a similar shape to the anterior part of the cingulum bundle, but it is located more frontally. To minimize the possibility that these FT findings are based on acquisition or processing artifacts, different dMRI data sets and processing pipelines have been used to describe the SAF. Furthermore, we evaluated the configuration of the SAF with complementary methods, such as polarized light imaging (PLI) and human brain dissections. The FT results of the SAF demonstrate a long pathway, consistent across individuals, while the human dissections indicate fiber pathways connecting the postero-dorsal with the antero-dorsal cortices of the frontal lobe

Preoperative Brain Tumor Imaging:Models and Software for Segmentation and Standardized Reporting

For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the lack of standardized and automatic methods for tumor detection and generation of clinical reports, incorporating a wide range of tumor characteristics, represents a major hurdle. In this study, we investigate the most occurring brain tumor types: glioblastomas, lower grade gliomas, meningiomas, and metastases, through four cohorts of up to 4,000 patients. Tumor segmentation models were trained using the AGU-Net architecture with different preprocessing steps and protocols. Segmentation performances were assessed in-depth using a wide-range of voxel and patient-wise metrics covering volume, distance, and probabilistic aspects. Finally, two software solutions have been developed, enabling an easy use of the trained models and standardized generation of clinical reports: Raidionics and Raidionics-Slicer. Segmentation performances were quite homogeneous across the four different brain tumor types, with an average true positive Dice ranging between 80 and 90%, patient-wise recall between 88 and 98%, and patient-wise precision around 95%. In conjunction to Dice, the identified most relevant other metrics were the relative absolute volume difference, the variation of information, and the Hausdorff, Mahalanobis, and object average symmetric surface distances. With our Raidionics software, running on a desktop computer with CPU support, tumor segmentation can be performed in 16-54 s depending on the dimensions of the MRI volume. For the generation of a standardized clinical report, including the tumor segmentation and features computation, 5-15 min are necessary. All trained models have been made open-access together with the source code for both software solutions and validation metrics computation. In the future, a method to convert results from a set of metrics into a final single score would be highly desirable for easier ranking across trained models. In addition, an automatic classification of the brain tumor type would be necessary to replace manual user input. Finally, the inclusion of post-operative segmentation in both software solutions will be key for generating complete post-operative standardized clinical reports