Structural white matter connectometry of word production in aphasia: an observational study.

While current dual-steam neurocognitive models of language function have coalesced around the view that distinct neuroanatomical networks subserve semantic and phonological processing, respectively, the specific white matter components of these networks remain a matter of debate. To inform this debate, we investigated relationships between structural white matter connectivity and word production in a cross-sectional study of 42 participants with aphasia due to unilateral left hemisphere stroke. Specifically, we reconstructed a local connectome matrix for each participant from diffusion spectrum imaging data and regressed these matrices on indices of semantic and phonological ability derived from their responses to a picture-naming test and a computational model of word production. These connectometry analyses indicated that both dorsally located (arcuate fasciculus) and ventrally located (inferior frontal-occipital, uncinate, and middle longitudinal fasciculi) tracts were associated with semantic ability, while associations with phonological ability were more dorsally situated, including the arcuate and middle longitudinal fasciculi. Associations with limbic pathways including the posterior cingulum bundle and the fornix were also found. All analyses controlled for total lesion volume and all results showing positive associations obtained false discovery rates < 0.05. These results challenge dual-stream accounts that deny a role for the arcuate fasciculus in semantic processing, and for ventral-stream pathways in language production. They also illuminate limbic contributions to both semantic and phonological processing for word production.

Biofilms-Impacts on Human Health and Its Relevance to Space Travel.

As the world looks towards the stars, the impacts of endogenous and exogenous microorganisms on human health during long-duration space flight are subjects of increased interest within the space community. The presence and continued growth of bacterial biofilms about spacecraft has been documented for decades; however, the impact on crew health is in its infancy. The impacts of biofilms are well known in the medical, agricultural, commercial, and industrial spaces. It less known that biofilms are undermining many facets of space travel and that their effects need to be understood and addressed for future space missions. Biofilms can damage space crew health and spoil limited food supply. Yet, at the same time, they can benefit plant systems for food growth, nutrient development, and other biological systems that are being explored for use in space travel. Various biofilm removal techniques have been studied to mitigate the hazards posed by biofilm persistence during space travel. Because the presence of biofilms can advance or hinder humanity's space exploration efforts, an understanding of their impacts over the duration of space flights is of paramount importance.

Tractostorm: The what, why, and how of tractography dissection reproducibility.

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC-ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real-life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and "virtual dissection" across various laboratories and hospitals. Intra-rater agreement (Dice score) was approximately 0.77, while inter-rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.

Neurosurgery and Manned Spaceflight.

There has been a renewed interest in manned spaceflight due to endeavors by private and government agencies. Publicized goals include manned trips to or colonization of Mars. These missions will likely be of long duration, exceeding existing records for human exposure to extra-terrestrial conditions. Participants will be exposed to microgravity, temperature extremes, and radiation, all of which may adversely affect their physiology. Moreover, pathological mechanisms may differ from those of a terrestrial nature. Known central nervous system (CNS) changes occurring in space include rises in intracranial pressure and spinal unloading. Intracranial pressure increases are thought to occur due to cephalad re-distribution of body fluids secondary to microgravity exposure. Spinal unloading in microgravity results in potential degenerative changes to the bony vertebrae, intervertebral discs, and supportive musculature. These phenomena are poorly understood. Trauma is of highest concern due to its potential to seriously incapacitate crewmembers and compromise missions. Traumatic pathology may also be exacerbated in the setting of altered CNS physiology. Though there are no documented instances of CNS pathologies arising in space, existing diagnostic and treatment capabilities will be limited relative to those on Earth. In instances where neurosurgical intervention is required in space, it is not known whether open or endoscopic approaches are feasible. It is obvious that prevention of trauma and CNS pathology should be emphasized. Further research into neurosurgical pathology, its diagnosis, and treatment in space are required should exploratory or colonization missions be attempted.

Promises and Perils of Artificial Intelligence in Neurosurgery.

Artificial intelligence (AI)-facilitated clinical automation is expected to become increasingly prevalent in the near future. AI techniques may permit rapid and detailed analysis of the large quantities of clinical data generated in modern healthcare settings, at a level that is otherwise impossible by humans. Subsequently, AI may enhance clinical practice by pushing the limits of diagnostics, clinical decision making, and prognostication. Moreover, if combined with surgical robotics and other surgical adjuncts such as image guidance, AI may find its way into the operating room and permit more accurate interventions, with fewer errors. Despite the considerable hype surrounding the impending medical AI revolution, little has been written about potential downsides to increasing clinical automation. These may include both direct and indirect consequences. Directly, faulty, inadequately trained, or poorly understood algorithms may produce erroneous results, which may have wide-scale impact. Indirectly, increasing use of automation may exacerbate de-skilling of human physicians due to over-reliance, poor understanding, overconfidence, and lack of necessary vigilance of an automated clinical workflow. Many of these negative phenomena have already been witnessed in other industries that have already undergone, or are undergoing "automation revolutions," namely commercial aviation and the automotive industry. This narrative review explores the potential benefits and consequences of the anticipated medical AI revolution from a neurosurgical perspective.

Patient-specific 3-dimensionally printed models for neurosurgical planning and education.

OBJECTIVE: Advances in 3-dimensional (3D) printing technology permit the rapid creation of detailed anatomical models. Integration of this technology into neurosurgical practice is still in its nascence, however. One potential application is to create models depicting neurosurgical pathology. The goal of this study was to assess the clinical value of patient-specific 3D printed models for neurosurgical planning and education. METHODS: The authors created life-sized, patient-specific models for 4 preoperative cases. Three of the cases involved adults (2 patients with petroclival meningioma and 1 with trigeminal neuralgia) and the remaining case involved a pediatric patient with craniopharyngioma. Models were derived from routine clinical imaging sequences and manufactured using commercially available software and hardware. RESULTS: Life-sized, 3D printed models depicting bony, vascular, and neural pathology relevant to each case were successfully manufactured. A variety of commercially available software and hardware were used to create and print each model from radiological sequences. The models for the adult cases were printed in separate pieces, which had to be painted by hand, and could be disassembled for detailed study, while the model for the pediatric case was printed as a single piece in separate-colored resins and could not be disassembled for study. Two of the models were used for patient education, and all were used for presurgical planning by the surgeon. CONCLUSIONS: Patient-specific 3D printed models are useful to neurosurgical practice. They may be used as a visualization aid for surgeons and patients, or for education of trainees.

Neuroendovascular-specific engineering modifications to the CorPath GRX Robotic System.

OBJECTIVE: The aim of this study was to evaluate new, neuroendovascular-specific engineering and software modifications to the CorPath GRX Robotic System for their ability to support safer and more effective cranial neurovascular interventions in a preclinical model. METHODS: Active device fixation (ADF) control software, permitting automated manipulation of the guidewire relative to the microcatheter, and a modified drive cassette suitable for neuroendovascular instruments were the respective software and hardware modifications to the current CorPath GRX robot, which was cleared by the FDA for percutaneous coronary and peripheral vascular intervention. The authors then trialed the modified system in a live porcine model with simulated neuroendovascular pathology. Femoral access through the aortic arch to the common carotid artery was accomplished manually (without robotic assistance), and the remaining endovascular procedures were performed with robotic assistance. The system was tested for the enhanced ability to navigate and manipulate neurovascular-specific guidewires and microcatheters. The authors specifically evaluated the movement of the wire forward and backward during the advancement of the microcatheter. RESULTS: Navigation of the rete mirabile and an induced aneurysm within the common carotid artery were successful. The active device fixation feature enabled independent advancement and retraction of the guidewire and working device relative to the microcatheter. When ADF was inactive, the mean forward motion of the guidewire was 5 mm and backward motion was 0 mm. When ADF was active, the mean forward motion of the guidewire was 0 mm and backward motion was 1.5 mm. The modifications made to the robotic cassette enabled the system to successfully manipulate the microcatheter and guidewire safely and in a manner more suited to neuroendovascular procedures than before. There were no occurrences of dissection, extravasation, or thrombosis. CONCLUSIONS: The robotic system was originally designed to navigate and manipulate devices for cardiac and peripheral vascular intervention. The current modifications described here improved its utility for the more delicate and tortuous neurovascular environment. This will set the stage for the development of a neurovascular-specific robot.

Machine Learning Versus Logistic Regression Methods for 2-Year Mortality Prognostication in a Small, Heterogeneous Glioma Database.

BACKGROUND: Machine learning (ML) is the application of specialized algorithms to datasets for trend delineation, categorization, or prediction. ML techniques have been traditionally applied to large, highly dimensional databases. Gliomas are a heterogeneous group of primary brain tumors, traditionally graded using histopathologic features. Recently, the World Health Organization proposed a novel grading system for gliomas incorporating molecular characteristics. We aimed to study whether ML could achieve accurate prognostication of 2-year mortality in a small, highly dimensional database of patients with glioma. METHODS: We applied 3 ML techniques (artificial neural networks [ANNs], decision trees [DTs], and support vector machines [SVMs]) and classical logistic regression (LR) to a dataset consisting of 76 patients with glioma of all grades. We compared the effect of applying the algorithms to the raw database versus a database where only statistically significant features were included into the algorithmic inputs (feature selection). RESULTS: Raw input consisted of 21 variables and achieved performance of accuracy/area (C.I.) under the curve of 70.7%/0.70 (49.9-88.5) for ANN, 68%/0.72 (53.4-90.4) for SVM, 66.7%/0.64 (43.6-85.0) for LR, and 65%/0.70 (51.6-89.5) for DT. Feature selected input consisted of 14 variables and achieved performance of 73.4%/0.75 (62.9-87.9) for ANN, 73.3%/0.74 (62.1-87.4) for SVM, 69.3%/0.73 (60.0-85.8) for LR, and 65.2%/0.63 (49.1-76.9) for DT. CONCLUSIONS: We demonstrate that these techniques can also be applied to small, highly dimensional datasets. Our ML techniques achieved reasonable performance compared with similar studies in the literature. Although local databases may be small versus larger cancer repositories, we demonstrate that ML techniques can still be applied to their analysis; however, traditional statistical methods are of similar benefit.

Full tractography for detecting the position of cranial nerves in preoperative planning for skull base surgery: technical note.

OBJECTIVE: Diffusion imaging tractography has allowed the in vivo description of brain white matter. One of its applications is preoperative planning for brain tumor resection. Due to a limited spatial and angular resolution, it is difficult for fiber tracking to delineate fiber crossing areas and small-scale structures, in particular brainstem tracts and cranial nerves. New methods are being developed but these involve extensive multistep tractography pipelines including the patient-specific design of multiple regions of interest (ROIs). The authors propose a new practical full tractography method that could be implemented in routine presurgical planning for skull base surgery. METHODS: A Philips MRI machine provided diffusion-weighted and anatomical sequences for 2 healthy volunteers and 2 skull base tumor patients. Tractography of the full brainstem, the cerebellum, and cranial nerves was performed using the software DSI Studio, generalized-q-sampling reconstruction, orientation distribution function (ODF) of fibers, and a quantitative anisotropy-based generalized deterministic algorithm. No ROI or extensive manual filtering of spurious fibers was used. Tractography rendering was displayed in a tridimensional space with directional color code. This approach was also tested on diffusion data from the Human Connectome Project (HCP) database. RESULTS: The brainstem, the cerebellum, and the cisternal segments of most cranial nerves were depicted in all participants. In cases of skull base tumors, the tridimensional rendering permitted the visualization of the whole anatomical environment and cranial nerve displacement, thus helping the surgical strategy. CONCLUSIONS: As opposed to classical ROI-based methods, this novel full tractography approach could enable routine enhanced surgical planning or brain imaging for skull base tumors.

Automatic Removal of False Connections in Diffusion MRI Tractography Using Topology-Informed Pruning (TIP).

Diffusion MRI fiber tracking provides a non-invasive method for mapping the trajectories of human brain connections, but its false connection problem has been a major challenge. This study introduces topology-informed pruning (TIP), a method that automatically identifies singular tracts and eliminates them to improve the tracking accuracy. The accuracy of the tractography with and without TIP was evaluated by a team of 6 neuroanatomists in a blinded setting to examine whether TIP could improve the accuracy. The results showed that TIP improved the tracking accuracy by 11.93% in the single-shell scheme and by 3.47% in the grid scheme. The improvement is significantly different from a random pruning (p value < 0.001). The diagnostic agreement between TIP and neuroanatomists was comparable to the agreement between neuroanatomists. The proposed TIP algorithm can be used to automatically clean-up noisy fibers in deterministic tractography, with a potential to confirm the existence of a fiber connection in basic neuroanatomical studies or clinical neurosurgical planning.

Tractography for Surgical Neuro-Oncology Planning: Towards a Gold Standard.

Magnetic resonance imaging tractography permits in vivo visualization of white matter structures. Aside from its academic value, tractography has been proven particularly useful to neurosurgeons for preoperative planning. Preoperative tractography permits both qualitative and quantitative analyses of tumor effects upon surrounding white matter, allowing the surgeon to specifically tailor their operative approach. Despite its benefits, there is controversy pertaining to methodology, implementation, and interpretation of results in this context. High-definition fiber tractography (HDFT) is one of several non-tensor tractography approaches permitting visualization of crossing white matter trajectories at high resolutions, dispensing with the well-known shortcomings of diffusion tensor imaging (DTI) tractography. In this article, we provide an overview of the advantages of HDFT in a neurosurgical context, derived from our considerable experience implementing the technique for academic and clinical purposes. We highlight nuances of qualitative and quantitative approaches to using HDFT for brain tumor surgery planning, and integration of tractography with complementary operative adjuncts, and consider areas requiring further research.

Structure, asymmetry, and connectivity of the human temporo-parietal aslant and vertical occipital fasciculi.

We previously proposed a bipartite 'dorsal-ventral' model of human arcuate fasciculus (AF) morphology. This model does not, however, account for the 'vertical,' temporo-parietal subdivision of the AF described in earlier dissection and tractographic studies. In an effort to address the absence of the vertical AF (VAF) within 'dorsal-ventral' nomenclature, we conducted a dedicated tractographic and white-matter dissection study of this tract and another short, vertical, posterior-hemispheric fascicle: the vertical occipital fasciculus (VOF). We conducted atlas-based, non-tensor, deterministic tractography in 30 single subjects from the Human Connectome Project database and verified our results using an average diffusion atlas compiled from 842 separate normal subjects. We also performed white-matter dissection in four post-mortem specimens. Our  tractography results demonstrate that the VAF is, in fact, a bipartite system connecting the ventral parietal and temporal regions, with variable connective, and no volumetric lateralization. The VOF is a non-lateralized, non-segmented system connecting lateral occipital areas with basal-temporal regions. Importantly, the VOF was spatially dissociated from the VAF. As the VAF demonstrates no overall connective or volumetric lateralization, we postulate its distinction from the AF system and propose its re-naming to the 'temporo-parietal aslant tract,' (TPAT), with unique dorsal and ventral subdivisions. Our tractography results were supported by diffusion atlas and white-matter dissection findings.

A Quantitative Tractography Study Into the Connectivity, Segmentation and Laterality of the Human Inferior Longitudinal Fasciculus.

The human inferior longitudinal fasciculus (ILF) is a ventral, temporo-occipital association tract. Though described in early neuroanatomical works, its existence was later questioned. Application of in vivo tractography to the neuroanatomical study of the ILF has generally confirmed its existence, however, consensus is lacking regarding its subdivision, laterality and connectivity. Further, there is a paucity of detailed neuroanatomic data pertaining to the exact anatomy of the ILF. Generalized Q-Sampling imaging (GQI) is a non-tensor tractographic modality permitting high resolution imaging of white-matter structures. As it is a non-tensor modality, it permits visualization of crossing fibers and accurate delineation of close-proximity fiber-systems. We applied deterministic GQI tractography to data from 30 healthy subjects and a large-volume, averaged diffusion atlas, to delineate ILF anatomy. Post-mortem white matter dissection was also carried out in three cadaveric specimens for further validation. The ILF was found in all 60 hemispheres. At its occipital extremity, ILF fascicles demonstrated a bifurcated, ventral-dorsal morphological termination pattern, which we used to further subdivide the bundle for detailed analysis. These divisions were consistent across the subject set and within the atlas. We applied quantitative techniques to study connectivity strength of the ILF at its anterior and posterior extremities. Overall, both morphological divisions, and the un-separated ILF, demonstrated strong leftward-lateralized connectivity patterns. Leftward-lateralization was also found for ILF volumes across the subject set. Due to connective and volumetric leftward-dominance and ventral location, we postulate the ILFs role in the semantic system. Further, our results are in agreement with functional and lesion-based postulations pertaining to the ILFs role in facial recognition.

Population-averaged atlas of the macroscale human structural connectome and its network topology.

A comprehensive map of the structural connectome in the human brain has been a coveted resource for understanding macroscopic brain networks. Here we report an expert-vetted, population-averaged atlas of the structural connectome derived from diffusion MRI data (N = 842). This was achieved by creating a high-resolution template of diffusion patterns averaged across individual subjects and using tractography to generate 550,000 trajectories of representative white matter fascicles annotated by 80 anatomical labels. The trajectories were subsequently clustered and labeled by a team of experienced neuroanatomists in order to conform to prior neuroanatomical knowledge. A multi-level network topology was then described using whole-brain connectograms, with subdivisions of the association pathways showing small-worldness in intra-hemisphere connections, projection pathways showing hub structures at thalamus, putamen, and brainstem, and commissural pathways showing bridges connecting cerebral hemispheres to provide global efficiency. This atlas of the structural connectome provides representative organization of human brain white matter, complementary to traditional histologically-derived and voxel-based white matter atlases, allowing for better modeling and simulation of brain connectivity for future connectome studies.