Prediction of the Topography of the Corticospinal Tract on T1-Weighted MR Images Using Deep-Learning-Based Segmentation

INTRODUCTION

Tractography is an invaluable tool in the planning of tumor surgery in the vicinity of functionally eloquent areas of the brain as well as in the research of normal development or of various diseases. The aim of our study was to compare the performance of a deep-learning-based image segmentation for the prediction of the topography of white matter tracts on T1-weighted MR images to the performance of a manual segmentation.

METHODS

T1-weighted MR images of 190 healthy subjects from 6 different datasets were utilized in this study. Using deterministic diffusion tensor imaging, we first reconstructed the corticospinal tract on both sides. After training a segmentation model on 90 subjects of the PIOP2 dataset using the nnU-Net in a cloud-based environment with graphical processing unit (Google Colab), we evaluated its performance using 100 subjects from 6 different datasets.

RESULTS

Our algorithm created a segmentation model that predicted the topography of the corticospinal pathway on T1-weighted images in healthy subjects. The average dice score was 0.5479 (0.3513-0.7184) on the validation dataset.

CONCLUSIONS

Deep-learning-based segmentation could be applicable in the future to predict the location of white matter pathways in T1-weighted scans.

[Tractography in functional neuronavigation]

The review addresses the combined use of tractography and neuronavigation. Fundamentals of diffusion tensor imaging are given, technical aspects of fiber tracking in general and in depicting separate subcortical tracts are described. Main advantages of the method and possible causes of errors are highlighted. Precision assessment of this technology is given by comparing with results of subcortical neurostimulation. Surgical tactics is described depending on distance between the tumor and subcortical pathways.

Cerebral mechanism of Tuina analgesia in management of knee osteoarthritis using multimodal MRI: study protocol for a randomised controlled trial

Background

The chronic pain of patients with knee osteoarthritis (KOA) seriously affects their quality of life and leads to heavy social and economic burden. As a nondrug therapy in Traditional Chinese Medicine (TCM), Tuina is generally recognised as safe and effective for reducing the chronic pain of KOA. However, the underlying central mechanisms of Tuina for improving the pain of KOA are not fully understood.

Methods/design

This study will be a randomised controlled trial with a parallel-group design. A total of 60 eligible participants will be assigned to the Tuina group or healthcare education group (Education group) at 1:1 ratio using stratified randomisation with gender and age as factors. The interventions of both groups will last for 30 min per session and be conducted twice each week for 12 weeks. This study will primarily focus on pain evaluation assessed by detecting the changes in brain grey matter (GM) structure, white matter (WM) structure, and the cerebral functional connectivity (FC) elicited by Tuina treatment, e.g., thalamus, hippocampus, anterior cingulate gyrus, S1, insula, and periaqueductal grey subregions (PAG). The two groups of patients will be evaluated by clinical assessments and multimodal magnetic resonance imaging (MRI) to observe the alterations in the GM, WM, and FC of participants at the baseline and the end of 6 and 12 weeks’ treatment and still be evaluated by clinical assessments but not MRI for 48 weeks of follow-up. The visual analogue scale of current pain is the primary outcome. The Short-Form McGill Pain Questionnaire, Western Ontario and McMaster Universities Osteoarthritis Index, 36-Item Short Form Health Survey, Hamilton Depression Scale, and Hamilton Anxiety Scale will be used to evaluate the pain intensity, pain feeling, pain emotion, clinical symptoms, and quality of life, respectively. MRI assessments, clinical data evaluators, data managers, and statisticians will be blinded to the group allocation in the outcome evaluation procedure and data analysis to reduce the risk of bias. The repeated measures analysis of variance (2 groups × 6 time points ANOVA) will be used to analyse numerical variables of the clinical and neuroimaging data obtained in the study. P<0.05 will be the statistical significance level.

Discussion

The results of this randomised controlled trial with clinical assessments and multimodal MRI will help reveal the influence of Tuina treatment on the potential morphological changes in cortical and subcortical brain structures, the white matter integrity, and the functional activities and connectivity of brain regions of patients with KOA, which may provide scientific evidence for the clinical application of Tuina in the management of KOA.

Trial registration

Chinese Clinical Trial Registry ChiCTR2000037966. Registered on Sep. 8, 2020.

Dissemination

The results will be published in peer-reviewed journals and disseminated through the study’s website, and conferences.

Transcranial magnetic stimulation (TMS) seeded tractography provides superior prediction of eloquence compared to anatomic seeded tractography

Background

For patients with brain tumors, maximizing the extent of resection while minimizing postoperative neurological morbidity requires accurate preoperative identification of eloquent structures. Recent studies have provided evidence that anatomy may not always predict eloquence. In this study, we directly compare transcranial magnetic stimulation (TMS) data combined with tractography to traditional anatomic grading criteria for predicting permanent deficits in patients with motor eloquent gliomas.

Methods

We selected a cohort of 42 glioma patients with perirolandic tumors who underwent preoperative TMS mapping with subsequent resection and intraoperative mapping. We collected clinical outcome data from their chart with the primary outcome being new or worsened motor deficit present at 3 month follow up, termed “permanent deficit”. We overlayed the postoperative resection cavity onto the preoperative MRI containing preoperative imaging features.

Results

Almost half of the patients showed TMS positive points significantly displaced from the precentral gyrus, indicating tumor induced neuroplasticity. In multivariate regression, resection of TMS points was significantly predictive of permanent deficits while the resection of the precentral gyrus was not. TMS tractography showed significantly greater predictive value for permanent deficits compared to anatomic tractography, regardless of the fractional anisotropic (FA) threshold. For the best performing FA threshold of each modality, TMS tractography provided both higher positive and negative predictive value for identifying true nonresectable, eloquent cortical and subcortical structures.

Conclusion

TMS has emerged as a preoperative mapping modality capable of capturing tumor induced plastic reorganization, challenging traditional presurgical imaging modalities.

Connectivity-based parcellation of normal and anatomically distorted human cerebral cortex

For over a century, neuroscientists have been working toward parcellating the human cortex into distinct neurobiological regions. Modern technologies offer many parcellation methods for healthy cortices acquired through magnetic resonance imaging. However, these methods are suboptimal for personalized neurosurgical application given that pathology and resection distort the cerebrum. We sought to overcome this problem by developing a novel connectivity‐based parcellation approach that can be applied at the single‐subject level. Utilizing normative diffusion data, we first developed a machine‐learning (ML) classifier to learn the typical structural connectivity patterns of healthy subjects. Specifically, the Glasser HCP atlas was utilized as a prior to calculate the streamline connectivity between each voxel and each parcel of the atlas. Using the resultant feature vector, we determined the parcel identity of each voxel in neurosurgical patients (n = 40) and thereby iteratively adjusted the prior. This approach enabled us to create patient‐specific maps independent of brain shape and pathological distortion. The supervised ML classifier re‐parcellated an average of 2.65% of cortical voxels across a healthy dataset (n = 178) and an average of 5.5% in neurosurgical patients. Our patient dataset consisted of subjects with supratentorial infiltrating gliomas operated on by the senior author who then assessed the validity and practical utility of the re‐parcellated diffusion data. We demonstrate a rapid and effective ML parcellation approach to parcellation of the human cortex during anatomical distortion. Our approach overcomes limitations of indiscriminately applying atlas‐based registration from healthy subjects by employing a voxel‐wise connectivity approach based on individual data.

Diffusion MRI tractography for neurosurgery: the basics, current state, technical reliability and challenges

Diffusion magnetic resonance imaging (dMRI) tractography is currently the only imaging technique that allows for non-invasive delineation and visualisation of white matter (WM) tractsin vivo,prompting rapid advances in related fields of brain MRI research in recent years. One of its major clinical applications is for pre-surgical planning and intraoperative image guidance in neurosurgery, where knowledge about the location of WM tracts nearby the surgical target can be helpful to guide surgical resection and optimise post-surgical outcomes. Surgical injuries to these WM tracts can lead to permanent neurological and functional deficits, making the accuracy of tractography reconstructions paramount. The quality of dMRI tractography is influenced by many modifiable factors, ranging from MRI data acquisition through to the post-processing of tractography output, with the potential of error propagation based on decisions made at each and subsequent processing steps. Research over the last 25 years has significantly improved the anatomical accuracy of tractography. An updated review about tractography methodology in the context of neurosurgery is now timely given the thriving research activities in dMRI, to ensure more appropriate applications in the clinical neurosurgical realm. This article aims to review the dMRI physics, and tractography methodologies, highlighting recent advances to provide the key concepts of tractography-informed neurosurgery, with a focus on the general considerations, the current state of practice, technical challenges, potential advances, and future demands to this field.

Tractography and the connectome in neurosurgical treatment of gliomas: the premise, the progress, and the potential

The ability of diffusion tensor MRI to detect the preferential diffusion of water in cerebral white matter tracts enables neurosurgeons to noninvasively visualize the relationship of lesions to functional neural pathways. Although viewed as a research tool in its infancy, diffusion tractography has evolved into a neurosurgical tool with applications in glioma surgery that are enhanced by evolutions in crossing fiber visualization, edema correction, and automated tract identification. In this paper the current literature supporting the use of tractography in brain tumor surgery is summarized, highlighting important clinical studies on the application of diffusion tensor imaging (DTI) for preoperative planning of glioma resection, and risk assessment to analyze postoperative outcomes. The key methods of tractography in current practice and crucial white matter fiber bundles are summarized. After a review of the physical basis of DTI and post-DTI tractography, the authors discuss the methodologies with which to adapt DT image processing for surgical planning, as well as the potential of connectomic imaging to facilitate a network approach to oncofunctional optimization in glioma surgery.

Diffusion Tensor Imaging Tractography for Fornix Identification in Intraventricular Tumor Surgery: A Case Series

BACKGROUND

The proximity of intraventricular or periventricular tumors to critical white matter structures, such as the fornix, poses an operative challenge. In order to avoid significant neurological morbidity, deliberate selection of surgical approach is necessary when planning resection of tumors in this region. We report our initial experience with fornix modeling as an adjunct to standard navigational techniques across multiple pathologies.

OBJECTIVE

To report the feasibility of using diffusion tensor imaging (DTI) fornix modeling as an adjunct to standard navigational techniques for surgical treatment of intraventricular and periventricular tumors involving the fornix.

METHODS

Between July 2018 and August 2019, DTI tractography was performed on 12 patients with intraventricular or periventricular tumors involving the fornix. DTI fornix modeling was performed and included as part of the intraoperative navigation in all cases.

RESULTS

The patient group was composed of 6 males and 6 females. The fornix model was delineated in all cases using DTI tractography as described. The mean patient age was 45.7 yr. The 2 most-common tumor pathologies represented in our patient cohort included meningioma and cranipharyngioma, both found in 2 patients. A glioneuronal tumor, low-grade glioma, ependymoma, subependymoma, mixed germ-cell tumor, pituitary adenoma, and renal cell carcinoma metastasis were found in 1 patient each. Case examples of fornix modeling that may be incorporated into standard neuronavigation are presented. No patient experienced new or worsening post-operative memory deficits.

CONCLUSION

DTI tractography for fornix identification is a useful adjunct to standard navigational techniques employed in surgical resection of forniceal involving tumors.

Tractography in Neurosurgery: A Systematic Review of Current Applications

The ability to visualize the brain's fiber connections noninvasively in vivo is relatively young compared with other possibilities of functional magnetic resonance imaging. Although many studies showed tractography to be of promising value for neurosurgical care, the implications remain inconclusive. An overview of current applications is presented in this systematic review. A search was conducted for (("tractography" or "fiber tracking" or "fibre tracking") and "neurosurgery") that produced 751 results. We identified 260 relevant articles and added 20 more from other sources. Most publications concerned surgical planning for resection of tumors (n = 193) and vascular lesions (n = 15). Preoperative use of transcranial magnetic stimulation was discussed in 22 of these articles. Tractography in skull base surgery presents a special challenge (n = 29). Fewer publications evaluated traumatic brain injury (TBI) (n = 25) and spontaneous intracranial bleeding (n = 22). Twenty-three articles focused on tractography in pediatric neurosurgery. Most authors found tractography to be a valuable addition in neurosurgical care. The accuracy of the technique has increased over time. There are articles suggesting that tractography improves patient outcome after tumor resection. However, no reliable biomarkers have yet been described. The better rehabilitation potential after TBI and spontaneous intracranial bleeding compared with brain tumors offers an insight into the process of neurorehabilitation. Tractography and diffusion measurements in some studies showed a correlation with patient outcome that might help uncover the neuroanatomical principles of rehabilitation itself. Alternative corticofugal and cortico-cortical networks have been implicated in motor recovery after ischemic stroke, suggesting more complex mechanisms in neurorehabilitation that go beyond current models. Hence tractography may potentially be able to predict clinical deficits and rehabilitation potential, as well as finding possible explanations for neurologic disorders in retrospect. However, large variations of the results indicate a lack of data to establish robust diagnostical concepts at this point. Therefore, in vivo tractography should still be interpreted with caution and by experienced surgeons.

A Connectomic Atlas of the Human Cerebrum-Chapter 18: The Connectional Anatomy of Human Brain Networks

BACKGROUND

It is widely understood that cortical functions are mediated by complex, interdependent brain networks. These networks have been identified and studied using novel technologies such as functional magnetic resonance imaging under both resting-state and task-based conditions. However, no one has attempted to describe these networks in terms of their cortical parcellations.

OBJECTIVE

To describe our approach to network modeling and discuss its significance for the future of neuronavigation in brain surgery using the cortical parcellation scheme detailed within this supplement.

METHODS

Using network models previously elucidated by our group using coordinate-based meta-analytic techniques, we show the anatomic position and underlying white matter tracts of the cortical regions comprising 8 functional networks of the human cerebrum. These network models are displayed using Synaptive's clinically available BrightMatter tractography software (Synaptive Medical, Toronto, Canada).

RESULTS

The relevant cortical parcellations of 8 different cerebral networks have been identified. The fiber tracts between these regions were used to construct anatomically precise models of the networks. Models are described for the dorsal attention, ventral attention, semantic, auditory, supplementary motor, ventral premotor, default mode, and salience networks.

CONCLUSION

Our goal is to move towards more precise, anatomically specific models of brain networks that can be constructed for individual patients and utilized in navigational platforms during brain surgery. We believe network modeling and future advances in navigation technology can provide a foundation for improving neurosurgical outcomes by allowing us to preserve complex brain networks.

An Examination of the Role of Supramaximal Resection of Temporal Lobe Glioblastoma Multiforme

BACKGROUND

Resection of the T1 contrast-enhancing portion of glioblastoma multiforme (GBM) has been shown to increase patient survival, although whether GBM resection beyond these boundaries has an additional survival benefit is not clear. In this study, we examined the effect of resecting the enhancement and a margin of brain tissue surrounding the enhancement in patients with GBM of the temporal lobe.

METHODS

We identified 32 consecutive patients with temporal lobe GBM who underwent initial resection between 2012 and 2015. Progression-free survival (PFS) and overall survival (OS) were analyzed based on the following categories: subtotal resection (STR; <99% of contrast enhancement removed), gross total resection (GTR; 100% of T1 contrast enhancement removed), and supramaximal resection (SMR; removal of T1 contrast enhancement plus removal of at least 1 cm of brain tissue surrounding the enhancement).

RESULTS

Patients undergoing SMR demonstrated a substantially improved median PFS (15 months) compared with those undergoing GTR (7 months) or those undergoing STR (6 months) (P < 0.003). A median OS advantage was also present in the SMR group (24 months) compared with the GTR (11 months) and STR (9 months) groups (P < 0.004). SMR significantly improved PFS (hazard ratio [HR], 0.093; 95% confidence interval [CI], 0.01-0.89; P = 0.039) and OS (HR, 0.169; 95% CI, 0.05-0.57; P < 0.004) when controlling for other variables. The complication rates did not differ among the resection groups (P = 0.66).

CONCLUSIONS

Achieving SMR substantially improved survival in patients with temporal lobe GBM compared with GTR of the enhancement alone.

The Changing Face of Technologically Integrated Neurosurgery: Today's High-Tech Operating Room

Over the last decade, surgical technology in planning, mapping, optics, robotics, devices, and minimally invasive techniques has changed the face of modern neurosurgery. We explore the current advances in clinical technology across all neurosurgical subspecialties, examine how clinical practice is being shaped by this technology, and suggest what the operating room of tomorrow may look like.

Common Disconnections in Glioma Surgery: An Anatomic Description

Within the surgical treatment of glioma, extended survival is predicated upon extent of resection which is limited by proximity and/or invasion of eloquent structures. Diffusion tensor imaging (DTI) tractography is a very useful tool for guiding supramaximal surgical resection while preserving eloquence. Although gliomas can vary significantly in size, shape, and invasion of functionally significant brain tissue, typical surgical disconnection patterns emerge. In this study, our typical surgical paradigm is outlined. We describe our surgical philosophy for resecting gliomas supramaximally summarized as define, divide, and destroy with the adjuvant utilization of neuronavigation and DTI. We describe the most common disconnections involved in glioma surgery at our institution; specifically, delineating tumor disconnections involving the medial posterior frontal, lateral posterior frontal, posterior temporal, anterior occipital, medial parietal, and insular regions. Although gliomas are highly variable, common patterns emerge in relation to the necessary disconnections required to preserve eloquent brain while maximizing the extent of resection. 

The Use of the Target Cancellation Task to Identify Eloquent Visuospatial Regions in Awake Craniotomies: Technical Note

The success of awake craniotomies relies on the patient's performance of function-specific tasks that are simple, quick, and reproducible. Intraoperative identification of visuospatial function through cortical and subcortical mapping has utilized a variety of intraoperative tests, each with its own benefits and drawbacks. In light of this, we developed a simple software program that aids in preventing neglect by simulating a target-cancellation task on a portable electronic device. In this report, we describe the interactive target cancellation task and have reviewed seven consecutive patients who underwent awake craniotomy for parietal and/or posterior temporal infiltrating brain tumors of the non-dominant hemisphere. Each of these patients performed target cancellation and line bisection tasks intraoperatively. The outcomes of each patient and testing scenario are described. Positive intraoperative cortical and subcortical sites involved with visuospatial processing were identified in three of the seven patients using the target cancellation and confirmed utilizing the line-bisection task. No identification of visuospatial function was accomplished utilizing the line-bisection task alone. Complete visuospatial function mapping was completed in less than 10 minutes in all patients. No patients had preoperative or postoperative hemineglect. Our findings highlight the feasibility of the target cancellation technique for use during awake craniotomy to aid in avoiding postoperative hemineglect. Target cancellation may offer an alternative method of cortical and subcortical visuospatial mapping in patients unable to perform other commonly used modalities.