Neurosurgical Planning Research Articles

EPID-28. TRENDS IN LOW GRADE GLIOMA PROGNOSIS AND THE EVOLVING IMPACT OF GROSS TOTAL RESECTION ACROSS FIFTY YEARS: A MULTICOHORT ANALYSIS

Abstract OBJECTIVE Significant advancements in neurosurgical planning, approach, and practice over the past five decades have improved the surgical management of diffuse low and high-grade gliomas. We sought to evaluate the extent to which LGG survival outcomes have evolved over the past fifty years using glioma registry datasets with histopathological groups defined by WHO diagnostic criteria and supplemented with next generation genome-sequencing. METHODS Three datasets (SEER, TCGA, and GENIE) were used to evaluate trends in prognosis following LGG diagnosis and resection between 1975 and present (GBM as a comparator cohort). The primary outcomes evaluated were longitudinal disease-specific survival and overall survival, with secondary fixed-timepoint outcomes evaluated at 12-months, 24-months, and 60-months. Subjects from SEER were categorized by histology, while subjects from TCGA and GENIE were included based IDH mutation status with available histopathology. RESULTS A total of 39,958 adult patients were included. Overall survival increased for both LGG and GBM between 1975 and 2010, however only LGG outcomes continued to improve following 2010 (2010-; HR=0.955, 95%CI 0.926 to 0.986). Evaluation of the interaction between resection extent and diagnosis year revealed a progressive increase in the survival benefit of GTR in recent years, particularly for LGG. Independent of other available clinical/molecular features and considering the interaction term between year of diagnosis and resection extent, the gap in independent prognostic benefit associated with GTR between LGG and GBM has significantly widened (2010-2020 vs 1990-2000, p<0.05). CONCLUSION Over the past three decades, consistent improvements in LGG outcomes were observed while prognosis following GBM diagnosis has remained largely unchanged following 2010. Notably, we observed increasing prognostic value of achieving GTR particularly in patients with LGG.

CNSC-24. REAL-TIME HIGH-DENSITY ECOG MAPPING OF SENSORIMOTOR REGIONS AND CONSCIOUSNESS DIFFERENTIATION IN PERI-ROLANDIC GLIOMA SURGERY

Abstract INTRODUCTION Accurately mapping sensorimotor regions is crucial for preserving motor and sensory functions in the treatment of gliomas located in the peri-Rolandic areas of the brain. OBJECTIVE We examined the use of high-density electrocorticography (ECoG) for passive mapping of sensorimotor regions in treating peri-Rolandic gliomas by analyzing the spatial-temporal and spectral features of real-time somatosensory evoked potentials (SSEPs), and their spectral patterns in differentiating states of consciousness. METHODS During surgery, SSEPs were recorded using high-density ECoG on fourteen patients (n=14), both in anesthetized and awake states. Neural data from 0.6Hz median nerve stimulation were captured at 2.4kHz and processed in real-time using MATLAB Simulink. The system displayed SSEPs’ peak activations as a 2D heat map on a screen, particularly around the 20ms time point (N20), and generated the spectral power in the gamma range using the Stockwell transform. Accuracy in delineating the central sulcus (CS) was assessed using the ROC curve, and paired t-tests compared gamma oscillations between states of consciousness. RESULTS Patients consistently showed clear discrimination between anterior and posterior channels at the 20ms time point, with 93.6±14.9% accuracy. Color contrast delineated the CS, correlating with the sulcus in the 3D reconstructed magnetic resonance imaging of each patient. Late gamma (60–250 Hz) modulation occurred 50 ms after stimulation onset, extending up to 250 ms in the primary somatosensory area. It was suppressed in the anesthetized state and significantly increased in the awake state (delineation accuracy: 81±10.3% and 91±13.4%, respectively). CONCLUSIONS These results demonstrate that SSEPs and gamma modulations can delineate sensorimotor areas and assess consciousness, significantly impacting neurosurgical planning.

RADT-45. INTEGRATION OF FUNCTIONAL MAGNETIC RESONANCE IMAGING INTO STEREOTACTIC RADIOSURGERY PLANNING TO REDUCE SYMPTOMATIC RADIATION NECROSIS

Abstract BACKGROUND Radiation necrosis (RN) is a common complication of stereotactic radiosurgery (SRS). Functional magnetic resonance imaging (fMRI) localizes eloquent cortical areas for neurosurgical planning but is seldom applied to SRS. We explored the relationship between symptomatic RN and functional neuroanatomy on fMRI. We evaluated the potential benefit of reducing radiation dose to functional areas. METHODS From 2011 to 2022, patients with an fMRI within 3 months of SRS for resected or unresected brain metastases (BM) were included. The BM nearest to the primary motor, language, or visual cortices was designated as the index BM. The functional area on fMRI nearest to the index BM was designated as the fOAR. Focally symptomatic RN (FSRN) was defined as radiographic RN alongside new or worsening focal neurologic symptoms consistent with the fOAR. Patients treated with 5-fraction SRS and modern planning techniques after 2013 were included in the dosimetric analysis. Associations between fOAR dose and FSRN were evaluated with logistic regression. SRS replanning was performed to determine if fOAR dose could be reduced without sacrificing target coverage. RESULTS Among 94 patients, 82% received SRS postoperatively, and 71% received 5-fraction SRS. fOARs included the primary motor (77%), language (19%), and visual (2%) cortices. Of 20 patients with radiographic RN, 20% were neurologically asymptomatic, 20% had anatomically unrelated neurologic symptoms, and 60% had FSRN. The dosimetric analysis included 39 patients. The fOAR volume receiving a single-fraction equivalent dose ≥14 Gy (V14Gy) was associated with FSRN at 18 months post-SRS (OR=6.8/mL, p=0.05). Replanning reduced fOAR V14Gy in all cases. The mean reduction was 28%. CONCLUSION Neurologic symptoms of SRS-induced RN reflect nearby functional neuroanatomy on fMRI. Dose reduction to functional areas while maintaining target coverage is consistently achievable and may mitigate symptomatic RN. Integrated fMRI-based SRS planning may protect neurologic function when treating tumors near eloquent areas.

The Evolving Role Of Artificial Intelligence In Neurosurgical Planning And Outcome Prediction: A MetaAnalysis

Artificial Intelligence (AI) is transforming various medical fields, including neurosurgery. This review explores the evolving role of AI in neurosurgical planning and outcome prediction, with a focus on its applications in preoperative imaging, intraoperative navigation, and postoperative outcome forecasting. A meta-analysis of recent studies shows that AI enhances precision, reduces errors, and offers personalized patient care. However, significant challenges such as interpretability and integration into clinical practice remain. This article discussescurrent developments, limitations, and future innovations in the use of AI in neurosurgery.

Current Applications of the Three-Dimensional Printing Technology in Neurosurgery: A Review.

In the recent years, three-dimensional (3D) printing technology has emerged as a transformative tool, particularly in health care, offering unprecedented possibilities in neurosurgery. This review explores the diverse applications of 3D printing in neurosurgery, assessing its impact on precision, customization, surgical planning, and education. A literature review was conducted using PubMed, Web of Science, Embase, and Scopus, identifying 84 relevant articles. These were categorized into spine applications, neurovascular applications, neuro-oncology applications, neuroendoscopy applications, cranioplasty applications, and modulation/stimulation applications. 3D printing applications in spine surgery showcased advancements in guide devices, prosthetics, and neurosurgical planning, with patient-specific models enhancing precision and minimizing complications. Neurovascular applications demonstrated the utility of 3D-printed guide devices in intracranial hemorrhage and enhanced surgical planning for cerebrovascular diseases. Neuro-oncology applications highlighted the role of 3D printing in guide devices for tumor surgery and improved surgical planning through realistic models. Neuroendoscopy applications emphasized the benefits of 3D-printed guide devices, anatomical models, and educational tools. Cranioplasty applications showed promising outcomes in patient-specific implants, addressing biomechanical considerations. The integration of 3D printing into neurosurgery has significantly advanced precision, customization, and surgical planning. Challenges include standardization, material considerations, and ethical issues. Future directions involve integrating artificial intelligence, multimodal imaging fusion, biofabrication, and global collaboration. 3D printing has revolutionized neurosurgery, offering tailored solutions, enhanced surgical planning, and invaluable educational tools. Addressing challenges and exploring future innovations will further solidify the transformative impact of 3D printing in neurosurgical care. This review serves as a comprehensive guide for researchers, clinicians, and policymakers navigating the dynamic landscape of 3D printing in neurosurgery.

Integration of virtual reality in neurosurgical training and planning: current developments.

Integration of virtual reality in neurosurgical training and planning: current developments.

Structural changes in eloquent cortex secondary to glioma in sensorimotor area.

This study aims to investigate the structural reorganization in the sensorimotor area of the brain in patients with gliomas, distinguishing between those with impaired and unimpaired strength. Using voxel-based morphometry (VBM) and region of interest (ROI) analysis, gray matter volumes (GMV) were compared in the contralesional primary motor gyrus, primary sensory gyrus, premotor area, bilateral supplementary motor area, and medial Brodmann area 8 (BA8). The results revealed that in patients with right hemisphere gliomas, the right medial BA8 volume was significantly larger in the impaired group than in the unimpaired group, with both groups exceeding the volume in 16 healthy controls (HCs). In patients with left hemisphere gliomas, the right supplementary motor area (SMA) was more pronounced in the impaired group compared to the unimpaired group, and both groups were greater than HCs. Additionally, the volumes of the right medial BA8 in both the impaired group were greater than HCs. Contralateral expansions in the gray matter of hand- and trunk-related cortices of the premotor area, precentral gyrus, and postcentral gyrus were observed compared to HCs. Furthermore, a negative correlation was found between hand Medical Research Council (MRC) score and volumes of the contralateral SMA and bilateral medial BA8. Notably, our findings reveal consistent results across both analytical approaches in identifying significant structural reorganizations within the sensorimotor cortex. These consistent findings underscore the adaptive neuroplastic responses to glioma presence, highlighting potential areas of interest for further neurosurgical planning and rehabilitation strategies.

Multi-Dynamic-Multi-Echo-based MRI for the Pre-Surgical Determination of Sellar Tumor Consistency: a Quantitative Approach for Predicting Lesion Resectability

PurposePre-surgical information about tumor consistency could facilitate neurosurgical planning. This study used multi-dynamic-multi-echo (MDME)-based relaxometry for the quantitative determination of pituitary tumor consistency, with the aim of predicting lesion resectability.MethodsSeventy-two patients with suspected pituitary adenomas, who underwent preoperative 3 T MRI between January 2020 and January 2022, were included in this prospective study. Lesion-specific T1-/T2-relaxation times (T1R/T2R) and proton density (PD) metrics were determined. During surgery, data about tumor resectability were collected. A Receiver Operating Characteristic (ROC) curve analysis was performed to investigate the diagnostic performance (sensitivity/specificity) for discriminating between easy- and hard-to-remove by aspiration (eRAsp and hRAsp) lesions. A Mann-Whitney-U-test was done for group comparison.ResultsA total of 65 participants (mean age, 54 years ± 15, 33 women) were enrolled in the quantitative analysis. Twenty-four lesions were classified as hRAsp, while 41 lesions were assessed as eRAsp. There were significant differences in T1R (hRAsp: 1221.0 ms ± 211.9; eRAsp: 1500.2 ms ± 496.4; p = 0.003) and T2R (hRAsp: 88.8 ms ± 14.5; eRAsp: 137.2 ms ± 166.6; p = 0.03) between both groups. The ROC analysis revealed an area under the curve of 0.72 (95% CI: 0.60–0.85) at p = 0.003 for T1R (cutoff value: 1248 ms; sensitivity/specificity: 78%/58%) and 0.66 (95% CI: 0.53–0.79) at p = 0.03 for T2R (cutoff value: 110 ms; sensitivity/specificity: 39%/96%).ConclusionMDME-based relaxometry enables a non-invasive, pre-surgical characterization of lesion consistency and, therefore, provides a modality with which to predict tumor resectability.

A computed tomography-based retrospective study on the foramen ovale and foramen spinosum in a Nigerian population

Abstract Background: This study investigated the shapes and dimensions of the foramen ovale (FO) and foramen spinosum (FS) in a specific population sample from Delta State, Nigeria, emphasizing their significance in various neurosurgical procedures. Materials and Methods: Following ethical clearance, this retrospective study analyzed 250 brain computed tomography (CT) images from the Radiology Department of a teaching hospital in Delta State, Nigeria. The sample included images from 100 females and 150 males, all aged 18 years or older. The dimensions of the FO and FS were measured on axial sections using a standardized protocol. Statistical analyses were conducted with Statistical Package for Social Sciences (IBM, Chicago, Illinois, United States) software, categorizing data by gender and age groups. Inferential statistics, including Student t test, analysis of variance, and Pearson’s correlation, were performed, with findings considered significant at P < 0.05. Results: The predominant shapes of the FO and FS were oval and round, respectively. Significant side differences were observed in the length of the right FS (P = 0.040). Gender differences were noted in the length of the bilateral FO (P = 0.010) and the width of the left FO (P = 0.001). A significant correlation with age was found for the width of the left FO (P = 0.006) and the distance from the right FO to FS (P = 0.037). The FS was absent in 24 cases (9.6%). Conclusion: This study highlights age-, side-, and gender-related differences in the shapes and dimensions of the FO and FS. It emphasizes the importance of precise preoperative radiological assessments to ensure optimal outcomes for neurosurgical planning.

The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology.

A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications in anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g. thalamic subregions, etc.) derived from high-resolution Mean Apparent Propagator-MRI, T2W, and magnetization transfer ratio images ex vivo. We then confirmed the location and borders of these segmented regions in the MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within Analysis of Functional NeuroImages software. Tracing and validating these important deep brain structures in 3D will improve neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, functional MRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.

Generation and applications of synthetic computed tomography images for neurosurgical planning.

CT and MRI are synergistic in the information provided for neurosurgical planning. While obtaining both types of images lends unique data from each, doing so adds to cost and exposes patients to additional ionizing radiation after MRI has been performed. Cross-modal synthesis of high-resolution CT images from MRI sequences offers an appealing solution. The authors therefore sought to develop a deep learning conditional generative adversarial network (cGAN) which performs this synthesis. Preoperative paired CT and contrast-enhanced MR images were collected for patients with meningioma, pituitary tumor, vestibular schwannoma, and cerebrovascular disease. CT and MR images were denoised, field corrected, and coregistered. MR images were fed to a cGAN that exported a "synthetic" CT scan. The accuracy of synthetic CT images was assessed objectively using the quantitative similarity metrics as well as by clinical features such as sella and internal auditory canal (IAC) dimensions and mastoid/clinoid/sphenoid aeration. A total of 92,981 paired CT/MR images obtained in 80 patients were used for training/testing, and 10,068 paired images from 10 patients were used for external validation. Synthetic CT images reconstructed the bony skull base and convexity with relatively high accuracy. Measurements of the sella and IAC showed a median relative error between synthetic CT scans and ground truth images of 6%, with greater variability in IAC reconstruction compared with the sella. Aerations in the mastoid, clinoid, and sphenoid regions were generally captured, although there was heterogeneity in finer air cell septations. Performance varied based on pathology studied, with the highest limitation observed in evaluating meningiomas with intratumoral calcifications or calvarial invasion. The generation of high-resolution CT scans from MR images through cGAN offers promise for a wide range of applications in cranial and spinal neurosurgery, especially as an adjunct for preoperative evaluation. Optimizing cGAN performance on specific anatomical regions may increase its clinical viability.

A review of algorithms and software for real-time electric field modeling techniques for transcranial magnetic stimulation.

Transcranial magnetic stimulation (TMS) is a device-based neuromodulation technique increasingly used to treat brain diseases. Electric field (E-field) modeling is an important technique in several TMS clinical applications, including the precision stimulation of brain targets with accurate stimulation density for the treatment of mental disorders and the localization of brain function areas for neurosurgical planning. Classical methods for E-field modeling usually take a long computation time. Fast algorithms are usually developed with significantly lower spatial resolutions that reduce the prediction accuracy and limit their usage in real-time or near real-time TMS applications. This review paper discusses several modern algorithms for real-time or near real-time TMS E-field modeling and their advantages and limitations. The reviewed methods include techniques such as basis representation techniques and deep neural-network-based methods. This paper also provides a review of software tools that can integrate E-field modeling with navigated TMS, including a recent software for real-time navigated E-field mapping based on deep neural-network models.

The Evaluation of Dermatological Disease Profiles of Neurosurgery Inpatients: A Tertiary Clinic Experience.

Both the skin and neuronal systems originate from the ectoderm. In patients hospitalized for neurosurgery, their skin may be affected by genetic and environmental factors. This study researched disease relationships by evaluating the profile of hospitalized neurosurgery patients who consulted with dermatologyin a tertiary clinic (Neurosurgery Clinic, Ankara Training and Research Hospital, Ankara). This study included hospitalized neurosurgery patients who consulted with dermatology. Age, gender, type of hospitalization, neurosurgical diseases, and dermatology diseases were selected as study variables. The medical health records of the patients were retrospectively scanned and analyzed. A total of 172 consultations were analyzed. The mean age of patients was 44.7 years oldranging from 1 year to99 years old. The percentage of male patients was 54.7%; 25.5% of the patients were hospitalized for cerebral vascular diseases, 30.2% for spinal diseases, 22.1% for tumors, 12.2% for infections, and 1.2% for other neurosurgical diseases. The most commonly diagnosed dermatological disease in patients was drug eruptions (18.6%), followed by seborrheic dermatitis (16.2%) and contact dermatitis (14.5%). According to this study, the most commonly diagnosed dermatological diseases in neurosurgery inpatients were drug eruption, contact dermatitis, and seborrheic dermatitis. The results of this study may be helpful in terms of neurosurgical training planning and treatment management.

Radiologically derived 3D virtual models for neurosurgical planning

Three dimensional (3D) virtual models for neurosurgery have demonstrated substantial clinical utility, especially for neuro-oncological cases. Computer-aided design (CAD) modelling of radiological images can provide realistic and high-quality 3D models which neurosurgeons may use pre-operatively for surgical planning. 3D virtual models are useful as they are the basis for other models that build off this design. 3D virtual models are quick to segment but can also be easily added to normal neurosurgical and radiological workflow without disruption. Three anatomically complex neuro-oncology cases that were referred from a single institution by three different neurosurgeons were segmented and 3D virtual models were created for pre-operative surgical planning. A face-to-face interview was performed with the surgeons after the models were delivered to gauge the usefulness of the model in pre-surgical planning. All three neurosurgeons found that the 3D virtual model was useful for presurgical planning. Specifically, the virtual model helped in planning operative positioning, understanding spatial relationship between lesion and surrounding critical anatomy and identifying anatomy that will be encountered intra-operatively in a sequential manner. It provided benefit in Multidisciplinary team (MDT) meetings and patient education for shared decision making.3D virtual models are beneficial for pre-surgical planning and patient education for shared decision making for neurosurgical neuro-oncology cases. We believe this could be further expanded to other surgical specialties. The integration of 3D virtual models into normal workflow as the initial step will provide an easier transition into modalities that build off the virtual models such as printed, virtual, augmented and mixed reality models.

A Neural Implant Design Toolbox for Nonhuman Primates.

This paper describes an in-house method of 3D brain and skull modeling from magnetic resonance imaging (MRI) tailored for nonhuman primate (NHP) neurosurgical planning. This automated, computational software-based technique provides an efficient way of extracting brain and skull features from MRI files as opposed to traditional manual extraction techniques using imaging software. Furthermore, the procedure provides a method for visualizing the brain and craniotomized skull together for intuitive, virtual surgical planning. This generates a drastic reduction in time and resources from those required by past work, which relied on iterative 3D printing. The skull modeling process creates a footprint that is exported into modeling software to design custom-fit cranial chambers and headposts for surgical implantation. Custom-fit surgical implants minimize gaps between the implant and the skull that could introduce complications, including infection or decreased stability. By implementing these pre-surgical steps, surgical and experimental complications are reduced. These techniques can be adapted for other surgical processes, facilitating more efficient and effective experimental planning for researchers and, potentially, neurosurgeons.

The Integration of 3D Virtual Reality and 3D Printing Technology as Innovative Approaches to Preoperative Planning in Neuro-Oncology.

Our study explores the integration of three-dimensional (3D) virtual reality (VR) and 3D printing in neurosurgical preoperative planning. Traditionally, surgeons relied on two-dimensional (2D) imaging for complex neuroanatomy analyses, requiring significant mental visualization. Fortunately, nowadays advanced technology enables the creation of detailed 3D models from patient scans, utilizing different software. Afterwards, these models can be experienced through VR systems, offering comprehensive preoperative rehearsal opportunities. Additionally, 3D models can be 3D printed for hands-on training, therefore enhancing surgical preparedness. This technological integration transforms the paradigm of neurosurgical planning, ensuring safer procedures.

Fibre orientation atlas guided rapid segmentation of white matter tracts.

Fibre tract delineation from diffusion magnetic resonance imaging (MRI) is a valuable clinical tool for neurosurgical planning and navigation, as well as in research neuroimaging pipelines. Several popular methods are used for this task, each with different strengths and weaknesses making them more or less suited to different contexts. For neurosurgical imaging, priorities include ease of use, computational efficiency, robustness to pathology and ability to generalise to new tracts of interest. Many existing methods use streamline tractography, which may require expert neuroimaging operators for setting parameters and delineating anatomical regions of interest, or suffer from as a lack of generalisability to clinical scans involving deforming tumours and other pathologies. More recently, data-driven approaches including deep-learning segmentation models and streamline clustering methods have improved reproducibility and automation, although they can require large amounts of training data and/or computationally intensive image processing at the point of application. We describe an atlas-based direct tract mapping technique called 'tractfinder', utilising tract-specific location and orientation priors. Our aim was to develop a clinically practical method avoiding streamline tractography at the point of application while utilising prior anatomical knowledge derived from only 10-20 training samples. Requiring few training samples allows emphasis to be placed on producing high quality, neuro-anatomically accurate training data, and enables rapid adaptation to new tracts of interest. Avoiding streamline tractography at the point of application reduces computational time, false positives and vulnerabilities to pathology such as tumour deformations or oedema. Carefully filtered training streamlines and track orientation distribution mapping are used to construct tract specific orientation and spatial probability atlases in standard space. Atlases are then transformed to target subject space using affine registration and compared with the subject's voxel-wise fibre orientation distribution data using a mathematical measure of distribution overlap, resulting in a map of the tract's likely spatial distribution. This work includes extensive performance evaluation and comparison with benchmark techniques, including streamline tractography and the deep-learning method TractSeg, in two publicly available healthy diffusion MRI datasets (from TractoInferno and the Human Connectome Project) in addition to a clinical dataset comprising paediatric and adult brain tumour scans. Tract segmentation results display high agreement with established techniques while requiring less than 3 min on average when applied to a new subject. Results also display higher robustness than compared methods when faced with clinical scans featuring brain tumours and resections. As well as describing and evaluating a novel proposed tract delineation technique, this work continues the discussion on the challenges surrounding the white matter segmentation task, including issues of anatomical definitions and the use of quantitative segmentation comparison metrics.

An individualized tractography pipeline for the nucleus basalis of Meynert lateral tract

Abstract Background: At the center of the cortical cholinergic network, the nucleus basalis of Meynert (NBM) is crucial for the cognitive domains most vulnerable in Parkinson’s disease (PD). Preclinical evidence has demonstrated the positive impact of NBM deep brain stimulation (DBS) on cognition but early human trials have had mixed results. It is possible that DBS of the lateral NBM efferent white matter fiber bundle may be more effective at improving cognitive-motor function. However, precise tractography modelling is required to identify the optimal target for neurosurgical planning. Individualized tractography approaches have been shown to be highly effective for accurately identifying DBS targets but have yet to be developed for the NBM. Methods: Using structural and diffusion-weighted imaging, we developed a tractography pipeline using manually segmented regions of interest for precise individualized identification of the lateral NBM target tract. Using dice similarity coefficients, the reliability of the tractography outputs was assessed across three cohorts to investigate: 1) whether this manual segmentation pipeline is more reliable than an existing automatic segmentation pipeline currently used in the literature; 2) the inter- and intra-rater reliability of our pipeline in research scans of patients with PD; and 3) the reliability and practicality of this pipeline in clinical scans of DBS patients. Results: The individualized manual pipeline was found to be significantly more reliable than the existing automated pipeline for both the segmentation of the NBM region itself (p < 0.001) and the reconstruction of the target lateral tract (p = 0.002). There was also no significant difference between the reliability of two different raters in the PD cohort (p = 0.25), which showed high inter- (mean Dice coefficient >0.6) and intra-rater (mean Dice coefficient >0.7) reliability across runs. Finally, the pipeline was shown to be highly reliable within the clinical scans (mean Dice coefficient = 0.77). However, accurate reconstruction was only evident in 7/10 tracts. Conclusion: We have developed a reliable tractography pipeline for the identification and analysis of the NBM lateral tract in research and clinical-grade imaging of healthy young adult and PD patient scans.

Navigating the calvaria with mobile mixed reality-based neurosurgical planning: how feasible are smartphone applications as a craniotomy guide?

Virtual simulation and imaging systems have evolved as advanced products of computing technology over the years. With advancements in mobile technology, smartphones, and tablets, the quality of display and processing speed have gradually improved, thanks to faster central processing units with higher capacity. Integrating these two technologies into the fields of healthcare and medical education has had a positive impact on surgical training. However, contemporary neurosurgical planning units are expensive and integrated neuronavigation systems in operating rooms require additional accessories. The aim of this study was to investigate the compatibility of smartphone applications in augmented reality (AR)-based craniotomy planning, which can be available even in disadvantaged workplaces with insufficient facilities. Thirty patients diagnosed with supratentorial glial tumor and who underwent operations between January 2022 and March 2023 were included in the study. The entire stages of the surgical procedures and the surgical plans were executed with neuronavigation systems. The patient CT scans were reconstructed using software and exported as a 3D figure to an AR-enhanced smartphone application. The evaluation of the application's success was based on the spatial relationship of the AR-based artificial craniotomy to the neuronavigation-based craniotomy, with each AR-based craniotomy scaled from 0 to 3. In the comparison between neuronavigation-based and AR fusion-based craniotomies, 8 of 30 (26.6%) patients scored 0 and were considered failed, 6 (20%) scored 1 and were considered ineffective, 7 (23.3%) scored 2 and were considered acceptable, and 9 (30%) scored 3 and were considered favorable. AR technology has great potential to be a revolutionary milestone of neurosurgical planning, training, and education in the near future. In the authors' opinion, with the necessary legal permissions, there is no obstacle to the integration of surgical technological systems with mobile technology devices such as smartphones and tablets that benefit from their low-budget requirements, wide-range availability, and built-in operating systems.

A patient-specific, interactive, multiuser, online mixed-reality neurosurgical training and planning system.

Mixed-reality simulation is an emerging tool for creating anatomical models for preoperative planning. Its use in neurosurgical training (NT) has been limited because of the difficulty in real-time interactive teaching. This study describes the development of a patient-specific, interactive mixed-reality NT system. The authors took cases of intracranial tumor resection or neurovascular compression (NVC) as examples to verify the technical feasibility and efficacy of the mixed-reality NT system for residents' training and preoperative planning. This study prospectively enrolled 40 patients who suffered from trigeminal neuralgia, hemifacial spasms, or intracranial tumors. The authors used a series of software programs to process the multimodal imaging data, followed by uploading the holographic models online. They used a HoloLens or a standard iOS device to download and display the holographic models for training. Ten neurosurgical residents with different levels of surgical experience were trained with this mixed-reality NT system. Change in surgical strategy was recorded, and a questionnaire survey was conducted to evaluate the efficacy of the mixed-reality NT system. The system allows the trainer and trainee to view the mixed-reality model with either a HoloLens or an iPad/iPhone simultaneously online at different locations. Interactive manipulation and instant updates were able to be achieved during training. A clinical efficacy validation test was conducted. The surgeons changed their exploration strategy in 48.3% of the NVC cases. For residents with limited experience in surgery, the exploration strategy for 75.0% of all patients with NVC was changed after the residents were trained with the mixed-reality NT system. Of the 60 responses for intracranial tumors, the trainee changed the surgical posture in 19 (31.7%) cases. The change of the location (p = 0.0338) and size (p = 0.0056) of craniotomy are significantly related to the experience of the neurosurgeons. The mixed-reality NT system is available for local or real-time remote neurosurgical resident training. It may effectively help neurosurgeons in patient-specific training and planning of surgery for cases of NVC and intracranial tumor. The authors expect the system to have a broader application in neurosurgery in the near future.