Virtual reality-based evaluation of neurovascular conflict for the surgical planning of microvascular decompression in trigeminal neuralgia patients

The Visualization of Intraneural Venous Compression in Trigeminal Neuralgia by Using Advanced Three-Dimensional Computer Graphics: An Illustrative Case Report

Trigeminal neuralgia (TN) caused by venous compression presents challenges in surgical management, unlike the arterial type. Preoperative diagnostic certainty regarding venous etiology and anatomical relationships is crucial for surgical success. We discuss a case of TN caused by a vein passing through the nerve that was challenging to visualize on conventional MRI and was treated successfully by leveraging information from modern surgical simulation technology with 3D computer graphics. We recognized a potentially troublesome anatomical feature in advance and mitigated the risk by identifying a collateral drainage route for the causative vein, making it feasible to be sacrificed while ensuring treatment efficacy.

Immersive Virtual Reality for Patient-Specific Preoperative Planning: A Systematic Review

Background. Immersive virtual reality (iVR) facilitates surgical decision-making by enabling surgeons to interact with complex anatomic structures in realistic 3-dimensional environments. With emerging interest in its applications, its effects on patients and providers should be clarified. This systematic review examines the current literature on iVR for patient-specific preoperative planning. Materials and Methods. A literature search was performed on five databases for publications from January 1, 2000 through March 21, 2021. Primary studies on the use of iVR simulators by surgeons at any level of training for patient-specific preoperative planning were eligible. Two reviewers independently screened titles, abstracts, and full texts, extracted data, and assessed quality using the Quality Assessment Tool for Studies with Diverse Designs (QATSDD). Results were qualitatively synthesized, and descriptive statistics were calculated. Results. The systematic search yielded 2,555 studies in total, with 24 full-texts subsequently included for qualitative synthesis, representing 264 medical personnel and 460 patients. Neurosurgery was the most frequently represented discipline (10/24; 42%). Preoperative iVR did not significantly improve patient-specific outcomes of operative time, blood loss, complications, and length of stay, but may decrease fluoroscopy time. In contrast, iVR improved surgeon-specific outcomes of surgical strategy, anatomy visualization, and confidence. Validity, reliability, and feasibility of patient-specific iVR models were assessed. The mean QATSDD score of included studies was 32.9%. Conclusions. Immersive VR improves surgeon experiences of preoperative planning, with minimal evidence for impact on short-term patient outcomes. Future work should focus on high-quality studies investigating long-term patient outcomes, and utility of preoperative iVR for trainees.

Three-dimensional technologies in presurgical planning of bone surgeries: current evidence and future perspectives

BACKGROUND

The recent development of three-dimensional (3D) technologies introduces a novel set of opportunities to the medical field in general, and specifically to surgery. The preoperative phase has proven to be a critical factor in surgical success. Utilization of 3D technologies has the potential to improve preoperative planning and overall surgical outcomes. In this narrative review article, the authors describe existing clinical data pertaining to the current use of 3D printing, virtual reality, and augmented reality in the preoperative phase of bone surgery.

METHODS

The methodology included keyword-based literature search in PubMed and Google Scholar for original articles published between 2014 and 2022. After excluding studies performed in nonbone surgery disciplines, data from 61 studies of five different surgical disciplines were processed to be included in this narrative review.

RESULTS

Among the mentioned technologies, 3D printing is currently the most advanced in terms of clinical use, predominantly creating anatomical models and patient-specific instruments that provide high-quality operative preparation. Virtual reality allows to set a surgical plan and to further simulate the procedure via a 2D screen or head mounted display. Augmented reality is found to be useful for surgical simulation upon 3D printed anatomical models or virtual phantoms.

CONCLUSIONS

Overall, 3D technologies are gradually becoming an integral part of a surgeon's preoperative toolbox, allowing for increased surgical accuracy and reduction of operation time, mainly in complex and unique surgical cases. This may eventually lead to improved surgical outcomes, thereby optimizing the personalized surgical approach.

Effects of three-dimension movie visual fatigue on cognitive performance and brain activity

To further develop three-dimensional (3D) applications, it is important to elucidate the negative effects of 3D applications on the human body and mind. Thus, this study investigated differences in the effects of visual fatigue on cognition and brain activity using visual and auditory tasks induced by watching a 1-h movie in two dimensions (2D) and 3D. Eighteen young men participated in this study. Two conditions were randomly performed for each participant on different days, namely, watching the 1-h movie on television in 2D (control condition) and 3D (3D condition). Before and after watching the 1-h movie on television, critical flicker fusion frequency (CFF: an index of visual fatigue), and response accuracy and reaction time for the cognitive tasks were determined. Brain activity during the cognitive tasks was evaluated using a multi-channel near-infrared spectroscopy system. In contrast to the control condition, the decreased CFF, and the lengthened reaction time and the decreased activity around the right primary somatosensory cortex during Go/NoGo blocks in the visual task at post-viewing in the 3D condition were significant, with significant repeated measures correlations among them. Meanwhile, in the auditory task, the changes in cognitive performance and brain activity during the Go/NoGo blocks were not significant in the 3D condition. These results suggest that the failure or delay in the transmission of visual information to the primary somatosensory cortex due to visual fatigue induced by watching a 3D movie reduced the brain activity around the primary somatosensory cortex, resulting in poor cognitive performance for the visual task. This suggests that performing tasks that require visual information, such as running in the dark or driving a car, immediately after using a 3D application, may create unexpected risks in our lives. Thus, the findings of this study will help outlining precautions for the use of 3D applications.

Automated Segmentation of Trigeminal Nerve and Cerebrovasculature in MR-Angiography Images by Deep Learning

Trigeminal neuralgia caused by paroxysmal and severe pain in the distribution of the trigeminal nerve is a rare chronic pain disorder. It is generally accepted that compression of the trigeminal root entry zone by vascular structures is the major cause of primary trigeminal neuralgia, and vascular decompression is the prior choice in neurosurgical treatment. Therefore, accurate preoperative modeling/segmentation/visualization of trigeminal nerve and its surrounding cerebrovascular is important to surgical planning. In this paper, we propose an automated method to segment trigeminal nerve and its surrounding cerebrovascular in the root entry zone, and to further reconstruct and visual these anatomical structures in three-dimensional (3D) Magnetic Resonance Angiography (MRA). The proposed method contains a two-stage neural network. Firstly, a preliminary confidence map of different anatomical structures is produced by a coarse segmentation stage. Secondly, a refinement segmentation stage is proposed to refine and optimize the coarse segmentation map. To model the spatial and morphological relationship between trigeminal nerve and cerebrovascular structures, the proposed network detects the trigeminal nerve, cerebrovasculature, and brainstem simultaneously. The method has been evaluated on a dataset including 50 MRA volumes, and the experimental results show the state-of-the-art performance of the proposed method with an average Dice similarity coefficient, Hausdorff distance, and average surface distance error of 0.8645, 0.2414, and 0.4296 on multi-tissue segmentation, respectively.