Analyzing international medical graduate research productivity for application to US neurosurgery residency and beyond: A survey of applicants, program directors, and institutional experience

BackgroundThe authors investigated perceived discrepancies between the neurosurgical research productivity of international medical graduates (IMGs) and US medical graduates (USMGs) through the perspective of program directors (PDs) and successfully matched IMGs.MethodsResponses to 2 separate surveys on neurosurgical applicant research productivity in 115 neurosurgical programs and their PDs were analyzed. Neurosurgical research participation was analyzed using an IMG survey of residents who matched into neurosurgical residency within the previous 8 years. Productivity of IMGs conducting dedicated research at the study institution was also analyzed.ResultsThirty-two of 115 (28%) PDs responded to the first research productivity survey and 43 (37%) to the second IMG research survey. PDs expected neurosurgery residency applicants to spend a median of 12–24 months on research (Q1-Q3: 0–12 to 12–24; minimum time: 0–24; maximum time: 0–48) and publish a median of 5 articles (Q1-Q3: 2–5 to 5–10; minimum number: 0–10; maximum number: 4–20). Among 43 PDs, 34 (79%) ranked “research institution or associated personnel” as the most important factor when evaluating IMGs' research. Forty-two of 79 (53%) IMGs responding to the IMG-directed survey reported a median of 30 months (Q1-Q3: 18–48; range: 4–72) of neurosurgical research and 12 published articles (Q1-Q3: 6–24; range: 1–80) before beginning neurosurgical residency. Twenty-two PDs (69%) believed IMGs complete more research than USMGs before residency. Of 20 IMGs conducting dedicated neuroscience/neurosurgery research at the study institution, 16 of 18 who applied matched or entered a US neurosurgical training program; 2 applied and entered a US neurosurgical clinical fellowship.ConclusionThe research work of IMGs compared to USMGs who apply to neurosurgery residency exceeds PDs' expectations regarding scientific output and research time. Many PDs perceive IMG research productivity before residency application as superior to USMGs. Although IMGs comprise a small percentage of trainees, they are responsible for a significant amount of US-published neurosurgical literature. Preresidency IMG research periods may be improved with dedicated mentoring and advising beginning before the research period, during the period, and within a neurosurgery research department, providing a formal structure such as a research fellowship or graduate program for IMGs aspiring to train in the US

Comprehensive microsurgical anatomy of the middle cranial fossa: Part II-neurovascular anatomy

In order to master the surgical approaches to the middle cranial fossa, the surgeon needs to understand the relevant bony anatomy. However, she/he also needs to have a clear and sound understanding of the neural and vascular anatomy because, oftentimes, the osseous anatomy (except for the optic apparatus) should be removed to expose and protect the neurovascular anatomy. This is the second of a two-part article discussing the neurovascular anatomy of the middle cranial fossa. A brief discussion of the surgical approaches follows

Comprehensive microsurgical anatomy of the middle cranial fossa: Part I-Osseous and meningeal anatomy

The middle cranial fossa is one of the most complex regions in neurosurgery and otolaryngology-in fact, the practice of skull base surgery originated from the need to treat pathologies in this region. Additionally, great neurosurgeons of our present and past are remembered for their unique methods of treating diseases in the middle fossa. The following article reviews the surgical anatomy of the middle fossa. The review is divided into the anatomy of the bones, dura, vasculature, and nerves-in two parts. Emphasis is paid to their neurosurgical significance and applications in skull base surgery. Part I focuses on the bony and dural anatomy

Virtual neurosurgery anatomy laboratory: A collaborative and remote education experience in the metaverse

BACKGROUND: Advances in computer sciences, including novel 3-dimensional rendering techniques, have enabled the creation of cloud-based virtual reality (VR) interfaces, making real-time peer-to-peer interaction possible even from remote locations. This study addresses the potential use of this technology for microsurgery anatomy education. METHODS: Digital specimens were created using multiple photogrammetry techniques and imported into a virtual simulated neuroanatomy dissection laboratory. A VR educational program using a multiuser virtual anatomy laboratory experience was developed. Internal validation was performed by five multinational neurosurgery visiting scholars testing and assessing the digital VR models. For external validation, 20 neurosurgery residents tested and assessed the same models and virtual space. RESULTS: Each participant responded to 14 statements assessing the virtual models, categorized under realism ( = 3), usefulness ( = 2), practicality ( = 3), enjoyment ( = 3), and recommendation ( = 3). Most responses expressed agreement or strong agreement with the assessment statements (internal validation, 94% [66/70] total responses; external validation, 91.4% [256/280] total responses). Notably, most participants strongly agreed that this system should be part of neurosurgery residency training and that virtual cadaver courses through this platform could be effective for education. CONCLUSION: Cloud-based VR interfaces are a novel resource for neurosurgery education. Interactive and remote collaboration between instructors and trainees is possible in virtual environments using volumetric models created with photogrammetry. We believe that this technology could be part of a hybrid anatomy curriculum for neurosurgery education. More studies are needed to assess the educational value of this type of innovative educational resource

Three-Dimensional Modeling and Extended Reality Simulations of the Cross-Sectional Anatomy of the Cerebrum, Cerebellum, and Brainstem

BACKGROUND: Understanding the anatomy of the human cerebrum, cerebellum, and brainstem and their 3-dimensional (3D) relationships is critical for neurosurgery. Although 3D photogrammetric models of cadaver brains and 2-dimensional images of postmortem brain slices are available, neurosurgeons lack free access to 3D models of cross-sectional anatomy of the cerebrum, cerebellum, and brainstem that can be simulated in both augmented reality (AR) and virtual reality (VR). OBJECTIVE: To create 3D models and AR/VR simulations from 2-dimensional images of cross-sectionally dissected cadaveric specimens of the cerebrum, cerebellum, and brainstem. METHODS: The Klingler method was used to prepare 3 cadaveric specimens for dissection in the axial, sagittal, and coronal planes. A series of 3D models and AR/VR simulations were then created using 360° photogrammetry. RESULTS: High-resolution 3D models of cross-sectional anatomy of the cerebrum, cerebellum, and brainstem were obtained and used in creating AR/VR simulations. Eleven axial, 9 sagittal, and 7 coronal 3D models were created. The sections were planned to show important deep anatomic structures. These models can be freely rotated, projected onto any surface, viewed from all angles, and examined at various magnifications. CONCLUSION: To our knowledge, this detailed study is the first to combine up-to-date technologies (photogrammetry, AR, and VR) for high-resolution 3D visualization of the cross-sectional anatomy of the entire human cerebrum, cerebellum, and brainstem. The resulting 3D images are freely available for use by medical professionals and students for better comprehension of the 3D relationship of the deep and superficial brain anatomy

Development and Validation of a Novel Methodological Pipeline to Integrate Neuroimaging and Photogrammetry for Immersive 3D Cadaveric Neurosurgical Simulation

Background: Visualizing and comprehending 3-dimensional (3D) neuroanatomy is challenging. Cadaver dissection is limited by low availability, high cost, and the need for specialized facilities. New technologies, including 3D rendering of neuroimaging, 3D pictures, and 3D videos, are filling this gap and facilitating learning, but they also have limitations. This proof-of-concept study explored the feasibility of combining the spatial accuracy of 3D reconstructed neuroimaging data with realistic texture and fine anatomical details from 3D photogrammetry to create high-fidelity cadaveric neurosurgical simulations. Methods: Four fixed and injected cadaver heads underwent neuroimaging. To create 3D virtual models, surfaces were rendered using magnetic resonance imaging (MRI) and computed tomography (CT) scans, and segmented anatomical structures were created. A stepwise pterional craniotomy procedure was performed with synchronous neuronavigation and photogrammetry data collection. All points acquired in 3D navigational space were imported and registered in a 3D virtual model space. A novel machine learning-assisted monocular-depth estimation tool was used to create 3D reconstructions of 2-dimensional (2D) photographs. Depth maps were converted into 3D mesh geometry, which was merged with the 3D virtual model\u27s brain surface anatomy to test its accuracy. Quantitative measurements were used to validate the spatial accuracy of 3D reconstructions of different techniques. Results: Successful multilayered 3D virtual models were created using volumetric neuroimaging data. The monocular-depth estimation technique created qualitatively accurate 3D representations of photographs. When 2 models were merged, 63% of surface maps were perfectly matched (mean [SD] deviation 0.7 ± 1.9 mm; range -7 to 7 mm). Maximal distortions were observed at the epicenter and toward the edges of the imaged surfaces. Virtual 3D models provided accurate virtual measurements (margin of error \u3c1.5 mm) as validated by cross-measurements performed in a real-world setting. Conclusion: The novel technique of co-registering neuroimaging and photogrammetry-based 3D models can (1) substantially supplement anatomical knowledge by adding detail and texture to 3D virtual models, (2) meaningfully improve the spatial accuracy of 3D photogrammetry, (3) allow for accurate quantitative measurements without the need for actual dissection, (4) digitalize the complete surface anatomy of a cadaver, and (5) be used in realistic surgical simulations to improve neurosurgical education