[Surgical Simulation Using a Three-Dimensional Printer].

3D printers have been applied in bone-based surgeries, including craniofacial, plastic, oral, and orthopedic surgeries. The improved capabilities of diagnostic imaging equipment and 3D printers have enabled the development of more precise models, and research on surgical simulations and training in the field of neurosurgery is increasing. This review outlines the use of 3D printers in neurosurgery at our institution in terms of modeling methods and surgical simulations. Modeling with the powder-sticking lamination method using plaster as the material allows drilling, which is a surgical procedure. Therefore, it is useful for simulating skull base tumors, such as petrosectomy in a combined transpetrosal approach or anterior clinoidectomy in an orbitozygomatic approach. The color coding of each part of the model facilitates anatomical understanding, and meshed tumor modeling allows deep translucency. As shown above, the 3D printer's modeling ingenuity allows for useful surgical simulations for each case.

[Preoperative Simulation of Neuroendovascular Therapy Using a Three-Dimensional Printer Model of a Tailor-Made Hollow Cerebral Aneurysm].

Several studies have reported the importance of preoperative simulations. This report describes the methods and utility of neuroendovascular treatment using a three-dimensional(3D)-printed hollow cerebral aneurysm model. This model was created using a stereolithography apparatus-type 3D printer with digital imaging and communications in medicine data from 3D digital subtraction angiograms. The 3D model was used to perform preoperative simulations of microcatheter placement in aneurysms, microguidewire manipulation, and stent deployment. We performed each simulated procedure during surgery. The hollow cerebral aneurysm 3D model can also be used as a training model for surgical trainees. Preoperative simulation using a high-precision hollow cerebral aneurysm model created using 3D printers enables the discussion of specific treatment strategies for each case, including new devices and device sizes, and is expected to develop into "tailor-made medicine" in the future, contributing to safe and reliable treatment implementation.

WATTS happening? Evaluation of thermal dose during holmium laser lithotripsy in a high-fidelity anatomic model.

PURPOSE: To evaluate the thermal profiles of the holmium laser at different laser parameters at different locations in an in vitro anatomic pelvicalyceal collecting system (PCS) model. Laser lithotripsy is the cornerstone of treatment for urolithiasis. With the prevalence of high-powered lasers, stone ablation efficiency has become more pronounced. Patient safety remains paramount during surgery. It is well recognized that the heat generated from laser lithotripsy has the potential to cause thermal tissue damage. METHODS: Utilizing high-fidelity, 3D printed hydrogel models of a PCS with a synthetic BegoStone implanted in the renal pelvis, laser lithotripsy was performed with the Moses 2.0 holmium laser. At a standard power (40 W) and irrigation pressure (100 cm H2O), we evaluated operator duty cycle (ODC) variations with different time-on intervals at four different laser settings. Temperature was measured at two separate locations-at the stone and away from the stone. RESULTS: Temperatures were highest closest to the laser tip with a decrease away from the laser. Fluid temperatures increased with longer laser-on times and higher ODCs. Thermal doses were greater with increased ODCs and the threshold for thermal injury was reached for ODCs of 75% and 100%. CONCLUSION: Temperature generation and thermal dose delivered are greatest closer to the tip of the laser fiber and are not dependent on power alone. Significant temperature differences were noted between four laser settings at a standardized power (40 W). Temperatures can be influenced by a variety of factors, such as laser-on time, operator duty cycle, and location in the PCS.

Unveiling new patterns: A surgical deep learning model for intestinal obstruction management.

BACKGROUND: Swift and accurate decision-making is pivotal in managing intestinal obstructions. This study aims to integrate deep learning and surgical expertise to enhance decision-making in intestinal obstruction cases. METHODS: We developed a deep learning model based on the YOLOv8 framework, trained on a dataset of 700 images categorised into operated and non-operated groups, with surgical outcomes as ground truth. The model's performance was evaluated through standard metrics. RESULTS: At a confidence threshold of 0.5, the model demonstrated sensitivity of 83.33%, specificity of 78.26%, precision of 81.7%, recall of 75.1%, and mAP@0.5 of 0.831. CONCLUSIONS: The model exhibited promising outcomes in distinguishing operative and nonoperative management cases. The fusion of deep learning with surgical expertise enriches decision-making in intestinal obstruction management. The proposed model can assist surgeons in intricate scenarios such as intestinal obstruction management and promotes the synergy between technology and clinical acumen for advancing patient care.

Sensitivity of Phonation Onset Pressure to Vocal Fold Stiffness Distribution.

Phonation onset is characterized by the unstable growth of vocal fold (VF) vibrations that ultimately results in self-sustained oscillation and the production of modal voice. Motivated by histological studies, much research has focused on the role of the layered structure of the vocal folds in influencing phonation onset, wherein the outer "cover" layer is relatively soft and the inner "body" layer is relatively stiff. Recent research, however, suggests that the body-cover (BC) structure over-simplifies actual stiffness distributions by neglecting important spatial variations, such as inferior-superior (IS) and anterior-posterior gradients and smooth transitions in stiffness from one histological layer to another. Herein, we explore sensitivity of phonation onset to stiffness gradients and smoothness. By assuming no a priori stiffness distribution and considering a second-order Taylor series sensitivity analysis of phonation onset pressure with respect to stiffness, we find two general smooth stiffness distributions most strongly influence onset pressure: a smooth stiffness containing aspects of BC differences and IS gradients in the cover, which plays a role in minimizing onset pressure, and uniform increases in stiffness, which raise onset pressure and frequency. While the smooth stiffness change contains aspects qualitatively similar to layered BC distributions used in computational studies, smooth transitions in stiffness result in higher sensitivity of onset pressure than discrete layering. These two general stiffness distributions also provide a simple, low-dimensional, interpretation of how complex variations in VF stiffness affect onset pressure, enabling refined exploration of the effects of stiffness distributions on phonation onset.

Utilization of 3D printing technology in hepatopancreatobiliary surgery. / 3D打印技术在肝胆胰外科中的应用进展.

The technology of three-dimensional (3D) printing emerged in the late 1970s and has since undergone considerable development to find numerous applications in mechanical engineering, industrial design, and biomedicine. In biomedical science, several studies have initially found that 3D printing technology can play an important role in the treatment of diseases in hepatopancreatobiliary surgery. For example, 3D printing technology has been applied to create detailed anatomical models of disease organs for preoperative personalized surgical strategies, surgical simulation, intraoperative navigation, medical training, and patient education. Moreover, cancer models have been created using 3D printing technology for the research and selection of chemotherapy drugs. With the aim to clarify the development and application of 3D printing technology in hepatopancreatobiliary surgery, we introduce seven common types of 3D printing technology and review the status of research and application of 3D printing technology in the field of hepatopancreatobiliary surgery.

3D-printed model for gingival flap surgery simulation: Development and pilot test.

INTRODUCTION: To assess the feasibility of a realistic model for learning oral flaps using 3D printing technology. MATERIALS AND METHODS: A mould was designed to reproduce the mandibular gingival mucosa, and a mandibular model was created using a three-dimensional printer for training undergraduate students to perform gingival flaps. After a short interview about its use, the participants were asked to use the simulator and provide feedback using a 5-point Likert questionnaire. RESULTS: The 3D-printed oral surgery flap training model was practical and inexpensive. The model was very realistic, educational and useful for hands-on training. CONCLUSIONS: 3D printing technology offers new possibilities for training in dental treatments that are currently difficult to replicate. The use of this simulator for oral flap surgery was well-received and considered promising by the participants.

From 2D slices to a 3D model: Training students in digital microanatomy analysis techniques through a 3D printed neuron project.

The reconstruction of two-dimensional (2D) slices to three-dimensional (3D) digital anatomical models requires technical skills and software that are becoming increasingly important to the modern anatomist, but these skills are rarely taught in undergraduate science classrooms. Furthermore, learning opportunities that allow students to simultaneously explore anatomy in both 2D and 3D space are increasingly valuable. This report describes a novel learning activity that trains students to digitally trace a serially imaged neuron from a confocal stack and to model that neuron in 3D space for 3D printing. By engaging students in the production of a 3D digital model, this learning activity is designed to provide students a novel way to enhance their understanding of the content, including didactic knowledge of neuron morphology, technical research skills in image analysis, and career exploration of neuroanatomy research. Moreover, students engage with microanatomy in a way that starts in 2D but results in a 3D object they can see, touch, and keep. This discursive article presents the learning activity, including videos, instructional guides, and learning objectives designed to engage students on all six levels of Bloom's Taxonomy. Furthermore, this work is a proof of principle modeling workflow that is approachable, inexpensive, achievable, and adaptable to cell types in other organ systems. This work is designed to motivate the expansion of 3D printing technology into microanatomy and neuroanatomy education.

The impact of moulage on learners' experience in simulation-based education and training: systematic review.

BACKGROUND: Moulage is a technique used to simulate injury, disease, aging and other physical characteristics specific to a scenario, often used in health and emergency worker training, predominantly for simulation-based learning activities. Its use in allied health fields is unclear. Previous work has explored moulage as an adjunct for authentic simulations, however there is opportunity for broadening its scope. AIM: To explore the effects of moulage interventions in simulation-based education and training, for learner experience. A secondary aim was to understand which pedagogical frameworks were embedded in moulage interventions. METHOD: Four electronic databases (PubMed, CINAHL, EmBase, Proquest Central) were systematically searched to December 2022 for studies utilising moulage in simulation-based education experiences. Outcomes were focused on learner satisfaction, confidence, immersion, engagement, performance, or knowledge. Study quality was assessed using the Mixed Methods Appraisal Tool. RESULTS: Twenty studies (n = 11,470) were included. Studies were primarily conducted in medicine (n = 9 studies) and nursing (n = 5 studies) and less frequently across other health disciplines. The findings demonstrated greater learner satisfaction, confidence, and immersion when moulage was used against a comparator group. Minimal improvements in knowledge and performance were identified. One study underpinned the intervention with a pedagogical theory. CONCLUSION: Moulage improves learner experience in simulation-based education or training, but not knowledge or clinical performance. Further research utilising moulage across a broader range of professions is needed. Interventions using moulage should be underpinned by pedagogical theories.

A Custom-Tailored Multichannel Pressure Monitoring System Designed for Experimental Surgical Model of Abdominal Compartment Syndrome.

In experimental medicine, a wide variety of sensory measurements are used. One of these is real-time precision pressure measurement. For comparative studies of the complex pathophysiology and surgical management of abdominal compartment syndrome, a multichannel pressure measurement system is essential. An important aspect is that this multichannel pressure measurement system should be able to monitor the pressure conditions in different tissue layers, and compartments, under different settings. We created a 12-channel positive-negative sensor system for simultaneous detection of pressure conditions in the abdominal cavity, the intestines, and the circulatory system. The same pressure sensor was used with different measurement ranges. In this paper, we describe the device and major experiences, advantages, and disadvantages. The sensory systems are capable of real-time, variable frequency sampling and data collection. It is also important to note that the pressure measurement system should be able to measure pressure with high sensitivity, independently of the filling medium (gas, liquid). The multichannel pressure measurement system we developed was well suited for abdominal compartment syndrome experiments and provided data for optimizing the method of negative pressure wound management. The system is also suitable for direct blood pressure measurement, making it appropriate for use in additional experimental surgical models.

Development and validation of a novel home-made bench-top training model for retrograde intrarenal surgery.

PURPOSE: To develop and validate a low-cost homemade bench-top training model to facilitate retrograde intrarenal surgery (RIRS) training. METHODS: The RIRS training model (G-Model) was developed using a surgical glove and a recycled ureter access sheath. Fifteen participants including 10 residents and 5 urologists were enrolled. Designed training curriculum for residents was carried out. Face validity, content validity, construct validity and criterion validity evaluation of the G-Model were carried out. RESULTS: The global score of face and content validity was 4.15 ± 0.53 and 4.65 ± 0.29, respectively. For construct validity, the overall modified global rating scale (mGRS) score was significantly improved [12.5 (5.25) vs. 24.0 (5.25), p = 0.004], and the total task time was significantly shortened (39.5 ± 4.48 min vs. 24.1 ± 3.81 min, p < 0.001) within residents after G-Model training. The baseline mGRS score and total task time of residents were poorer than those of urologists [12.5 (5.25) vs. 32.0 (1.00), p < 0.001; 39.5 ± 4.48 min vs. 16.0 ± 1.58 min, p < 0.001]. Spearman correlation analysis revealed strong correlations between residents' G-Model and real patient performance. CONCLUSION: The current study presented a valid low-cost easily accessible RIRS bench-top training model which could facilitate skill acquisition and translate to real-life scenario.

Three-dimensional Liver Model Application for Liver Transplantation.

BACKGROUND: Children are removed from the liver transplant waitlist because of death or progressive illness. Size mismatch accounts for 30% of organ refusal. This study aimed to demonstrate that 3-dimensional (3D) technology is a feasible and accurate adjunct to organ allocation and living donor selection process. METHODS: This prospective multicenter study included pediatric liver transplant candidates and living donors from January 2020 to February 2023. Patient-specific, 3D-printed liver models were used for anatomic planning, real-time evaluation during organ procurement, and surgical navigation. The primary outcome was to determine model accuracy. The secondary outcome was to determine the impact of outcomes in living donor hepatectomy. Study groups were analyzed using propensity score matching with a retrospective cohort. RESULTS: Twenty-eight recipients were included. The median percentage error was -0.6% for 3D models and had the highest correlation to the actual liver explant (Pearson's R = 0.96, P < 0.001) compared with other volume calculation methods. Patient and graft survival were comparable. From 41 living donors, the median percentage error of the allograft was 12.4%. The donor-matched study group had lower central line utilization (21.4% versus 75%, P = 0.045), shorter length of stay (4 versus 7 d, P = 0.003), and lower mean comprehensive complication index (3 versus 21, P = 0.014). CONCLUSIONS: Three-dimensional volume is highly correlated with actual liver explant volume and may vary across different allografts for living donation. The addition of 3D-printed liver models during the transplant evaluation and organ procurement process is a feasible and safe adjunct to the perioperative decision-making process.

Are 3D-printed anatomical models of the ear effective for teaching anatomy? A comparative pilot study versus cadaveric models.

PURPOSE: Despite the combination of chalkboard lectures and cadaveric models, the ear remains a complex anatomical structure that is difficult for medical students to grasp. The aim of this study was to evaluate the contribution of a 3D-printed ear model for educating undergraduate medical students by comparing it with a conventional cadaveric model. METHODS: Models of the ear comprising the outer ear, tympanic membrane, ossicles and inner ear were modeled and then 3D-printed at 6:1 and 10:1 scales based on cadaveric dissection and CT, cone-beam CT and micro/nano CT scans. Cadaveric models included two partially dissected dry temporal bones and ossicles. Twenty-four 3rd year medical students were given separate access to cadaveric models (n = 12) or 3D-printed models (n = 12). A pre-test and two post-tests were carried out to assess knowledge (n = 24). A satisfaction questionnaire focusing solely on the 3D-printed model, comprising 17 items assessed on a 5-point Likert scale, was completed by all study participants. A 5-point Likert scale questionnaire comprising four items (realism, color, quality and satisfaction with the 3D-printed ear model) was given to three expert anatomy Professors. RESULTS: The test scores on the first post-test were higher for the students who had used the 3D-printed models (p < 0.05). Overall satisfaction among the students and the experts was very high, averaging 4.7 on a 5-point Likert-type satisfaction scale. CONCLUSION: This study highlights the overall pedagogical value of a 3D-printed model for learning ear anatomy.

Simulated outcomes for durotomy repair in minimally invasive spine surgery.

Minimally invasive spine surgery (MISS) is increasingly performed using endoscopic and microscopic visualization, and the captured video can be used for surgical education and development of predictive artificial intelligence (AI) models. Video datasets depicting adverse event management are also valuable, as predictive models not exposed to adverse events may exhibit poor performance when these occur. Given that no dedicated spine surgery video datasets for AI model development are publicly available, we introduce Simulated Outcomes for Durotomy Repair in Minimally Invasive Spine Surgery (SOSpine). A validated MISS cadaveric dural repair simulator was used to educate neurosurgery residents, and surgical microscope video recordings were paired with outcome data. Objects including durotomy, needle, grasper, needle driver, and nerve hook were then annotated. Altogether, SOSpine contains 15,698 frames with 53,238 annotations and associated durotomy repair outcomes. For validation, an AI model was fine-tuned on SOSpine video and detected surgical instruments with a mean average precision of 0.77. In summary, SOSpine depicts spine surgeons managing a common complication, providing opportunities to develop surgical AI models.

In-House 3D Printing and Model Processing Technique for Creating High-Fidelity Transparent Craniofacial Models.

SUMMARY: The use of high-fidelity stereolithographic models that accurately reflect patient-specific pathology has become commonplace in craniofacial surgery. Multiple studies have reported the use of commercially available three-dimensional (3D) printers that allow medical centers with limited resources to reconstruct 3D models comparable to industry-made counterparts. However, most models are printed using only a single filament, which portrays the surface craniofacial anatomy, but fails to highlight relevant intraosseous structures. This presents a significant limitation when used for preoperative planning and intraoperative guidance in surgical procedures requiring osteotomies, where knowledge of the precise location of critical structures is paramount to avoid injury. The authors report a novel technique for creating transparent 3D models of relevant intraosseous craniofacial anatomy at a cost that mitigates the financial burden of industrial 3D model or industrial 3D printer acquisition. Cases are presented to demonstrate the diverse applications of this technique, with accurate display of the tooth roots, the inferior alveolar nerve, and the optic nerve, to aid in preoperative planning of osteotomies. This technique enables production of low-cost, high-fidelity transparent 3D models with applications in preoperative planning for craniofacial surgery.

Creation of Three-dimensional Anatomic Models in Pediatric Surgical Patients Using Cross-sectional Imaging: A Demonstration of Low-cost Methods and Applications.

BACKGROUND: Pediatric surgery patients often present with complex congenital anomalies or other conditions requiring deep understanding of their intricate anatomy. Commercial applications and services exist for the conversion of cross-sectional imaging data into three-dimensional (3D) models for education and preoperative planning. However, the associated costs and lack of familiarity may discourage their use in centers with limited resources. The purpose of this report is to present a low-cost, reproducible method for generating 3D images to visualize patient anatomy. METHODS: De-identified DICOM files were obtained from the hospital PACS system in preparation for assorted pediatric surgical procedures. Using open-source visualization software, variations in anatomic structures were examined using volume rendering and segmentation techniques. Images were further refined using available editing tools or artificial intelligence-assisted software extensions. RESULTS: Using the described techniques we were able to obtain excellent visualization of desired structures and associated anatomic variations. Once structures were selected and modeled in 3D (segmentation), they could be exported as one of several 3D object file formats. These could then be retained for 3D printing, visualization in virtual reality, or as an anatomic reference during the perioperative period. Models may also be imported into commercial gaming engines for rendering under optimal lighting conditions and with enhanced detail. CONCLUSION: Pediatric surgeons are frequently tasked with the treatment of patients with complex and rare anomalies. Visualization and preoperative planning can be assisted by advanced imaging software at minimal to no cost, thereby facilitating enhanced understanding of these conditions in resource-limited environments. LEVEL OF EVIDENCE: V, Case Series, Description of Technique.

Topographical Systematization of Human Placenta Model for Training in Microneurosurgery.

BACKGROUND: Neurosurgical training continuously seeks innovative methods to enhance the acquisition of essential technical skills for neurosurgeons worldwide. While various training models have been employed, few truly replicate real-life conditions optimally. Human placenta is a good model for neurosurgical microsurgery training due to its anatomic similarities to neurovascular structures. Placental vessels exhibit a branching pattern and caliber comparable with intracranial vessels, making them suitable for practicing microsurgical techniques. The study aims to delineate the anatomic zones of the placenta and propose a segmented training model, resulting in a reproducible, cost-effective, and realistic neurosurgical microsurgery training environment. METHODS: Twenty human placentas were meticulously prepared, injected with dyes, and categorized into zones on the basis of anatomic features. Measurements of placental vessels were recorded and compared with cerebral vessels. The placenta was divided into 4 quadrants to facilitate specific training techniques. RESULTS: Our results revealed varying vessel diameters across placental zones, closely resembling cerebral vessels. Different microsurgical techniques were applied to specific placental zones, thereby optimizing training scenarios. The applicability section described exercises such as membrane dissection, vessel skeletonization, aneurysm creation, vascular bypass, and tumor dissection within the placental model, providing detailed guidance on the zones suitable for each exercise. CONCLUSIONS: Human placenta serves as an effective microsurgical training model for neurosurgery, enhancing neurosurgeons' skills through anatomic segmentation. Integrating this model into training programs can significantly contribute to skill acquisition and improved surgical outcomes. Further research is warranted to refine and expand its utilization, complemented by clinical experiences and other simulation tools.

The Educational Impact of Radiology in Anatomy Teaching: A Field Study Using Cross-Sectional Imaging and 3D Printing for the Study of the Spine.

INTRODUCTION: Cross-sectional imaging and 3D printing represent state-of-the-art approaches to improve anatomy teaching compared to traditional learning, but their use in medical schools remains limited. This study explores the utility of these educational tools for teaching normal and pathological spinal anatomy, aiming to improve undergraduate medical education. MATERIALS AND METHODS: A field study was conducted on a cohort of undergraduate medical students who were exposed to anatomy lessons of the spine considering three learning paradigms: traditional learning, cross-sectional imaging examinations, and 3D printed models. 20 students (intervention group) received the three approaches, and other 20 students (control group) received the conventional (traditional) approach. The students were examined through a multiple-choice test and their results were compared to those of a control group exposed to traditional learning matched by age, sex and anatomy grades. In addition, students in the experimental group were assessed for their satisfaction with each learning method by means of an ad hoc questionnaire. RESULTS: Students exposed to cross-sectional imaging and 3D printing demonstrated better knowledge outcomes compared to the control group. They showed high satisfaction rates and reported that these technologies enhanced spatial understanding and facilitated visualization of specific pathologies. However, limitations such as the representativeness of non-bone conditions in 3D printed models and the need for further knowledge on imaging fundamentals were highlighted. CONCLUSION: Cross-sectional imaging and 3D printing offer valuable tools for enhancing the teaching of spinal anatomy in undergraduate medical education. Radiologists are well positioned to lead the integration of these technologies, and further research should explore their potential in teaching anatomy across different anatomical regions.

Evaluation of polyethylene terephthalate glycol (PETG), Simubone™, and photopolymer resin as 3D printed temporal bone models for surgical simulation.

OBJECTIVES: Among types of 3D printing, fused deposition modeling (FDM) and digital light processing (DLP) are the most accessible, making them attractive, low-cost options for simulating surgical procedures. This study characterized and compared inexpensive, synthetic temporal bone models printed using Resin, PETG, and Simubone™. MATERIALS AND METHODS: This study compared models made of polyethylene terephthalate glycol (PETG), Simubone™ produced from a FDM printer, and photopolymer resin from a DLP printer. These temporal bone models were processed by: (1) DICOM files from a patient's CT scan were segmented to define critical parts expected in a temporal bone surgery. (2) The model was appended with a base that articulates with a 3D-printed temporal bone holder. (3) The refined, patient-specific model was manufactured using FDM and DLP printing technologies. (4) The models were sent to evaluators, who assessed the models based on anatomic accuracy, dissection experience, and its applicability as a surgical simulation tool for temporal bone dissection. RESULTS: The photopolymer resin outperformed PETG and Simubone™ in terms of anatomical accuracy and dissection experience. Additionally, resin and PETG were evaluated to be appropriate for simple mastoidectomy and canal wall down mastoidectomy while Simubone™ was only suitable for simple mastoidectomy. All models were unsuitable for posterior tympanotomy and labyrinthectomy. CONCLUSIONS: Photopolymer resin and PETG have shown to be suitable materials for dissection models with 3D-printed resin models showing more accuracy in replicating anatomical structures and dissection experience. Hence, the use of 3D-printed temporal bones may be a suitable low-cost alternative to cadaveric dissection.

Modularity and community detection in human brain morphology.

Humans possess morphologically complex brains, which are spatially constrained by their many intrinsic and extrinsic physical interactions. Anatomical network analysis can be used to study these constraints and their implications. Modularity is a key issue in this framework, namely, the presence of groups of elements that undergo morphological evolution in a concerted way. An array of community detection algorithms was tested on a previously designed anatomical network model of the human brain in order to provide a detailed assessment of modularity in this context. The algorithms that provide the highest quality partitions also reveal general phenotypic patterns underlying the topology of human brain morphology. Taken together, the community detection algorithms highlight the simultaneous presence of a longitudinal and a vertical modular partition of the brain's topology, the combination of which matches the organization of the enveloping braincase. Specifically, the longitudinal organization is in line with the different morphogenetic environments of the three endocranial fossae, while the vertical arrangement corresponds to the distinct developmental processes associated with the cranial base and vault, respectively. The results are robust and have the potential to be compared with equivalent network models of other species. Furthermore, they suggest a degree of concerted topological reciprocity in the spatial organization of brain and skull elements, and posit questions about the extent to which geometrical constraints of the cranial base and the modular partition of the corresponding brain regions may channel both evolutionary and developmental trajectories.