Morris, Jonathan M.

OBJECTIVE Achieving submillimetric accuracy in stereotactic neurosurgery remains critical for safely targeting deep brain structures. Current workflows rely on intraoperative CT to register stereotactic frames to preoperative imaging, but this introduces additional radiation exposure, cost, and workflow complexity. Three-dimensional surface scanning (3DSS) potentially offers a fast radiation-free alternative capable of capturing detailed craniofacial anatomy and frame geometry. Therefore, the aim of this cadaveric study was to evaluate the feasibility, accuracy, and navigational compatibility of integrating 3DSS into stereotactic workflows as a potential replacement for intraoperative CT. METHODS A human cadaveric head was imaged with both thin-slice CT and structured-light 3DSS after mounting stereotactic frame components. CT, 3DSS, and computer-aided design (CAD) models were registered using a multistep point cloud alignment pipeline involving the fast point feature histogram, the random sample consensus method, and the iterative closest point algorithm. Accuracy was assessed using surface deviation error, root mean square error (RMSE), and fiducial registration error within a commercial neuronavigation platform. RESULTS Fusion of the 3D facial scan with CT provided a mean surface deviation error of approximately 0.4 mm. Registration of the 3DSS-derived N-bar localizer to its CAD reference model produced a frame alignment RMSE of 1.3 mm. Within the navigation system, the 3DSS-based workflow achieved a mean fiducial registration error of 0.14 mm (range 0.02–0.20 mm), outperforming the conventional CT-based method (mean error 0.20 mm, range 0.09–0.40 mm). CONCLUSIONS The 3DSS-based method enabled precise submillimetric stereotactic registration without the need for intraoperative CT, reducing radiation exposure and operative complexity. This workflow is fully compatible with existing navigation systems and could serve as a practical radiation-free alternative in stereotactic neurosurgery. Future work will focus on automating frame detection, incorporating artificial intelligence–driven fusion methods, and validating this approach in live surgical settings.

Summary: Anatomy is a critical component of surgical training; however, traditional resources—such as Netter’s Surgical Anatomy , Gray’s Anatomy , and anatomy applications—often fall short in delivering surgically relevant, 3-dimensional (3D) perspectives of facial anatomy. Although cadaveric dissection remains a valuable teaching tool, its accessibility is limited by cost, ethical concerns, and the lack of structured curricula, making it less feasible for ongoing surgical education. To address these limitations, this article introduced a novel educational approach that integrates 3D photogrammetry and virtual reality technology into the surgical anatomy curriculum for craniofacial and aesthetic surgery. Six fresh cadaveric specimens were meticulously dissected by a plastic surgeon to illustrate the intricate layered anatomy of the face and neck. At each stage of the dissection, a photogrammetry technique was used to capture 360-degree images using 5 digital single-lens reflex cameras alongside a 3D handheld camera. This approach not only ensured high-quality imaging but also facilitated the creation of detailed, lifelike virtual 3D models, enhancing the understanding of facial and neck anatomy within a surgical context. Additionally, we present some technical refinements of the 3D volume renderings to capture precise anatomical details during our dissections. Preliminary results from the use of this technology in anatomy courses and workshops indicated trainee engagement, a clearer grasp of the spatial anatomical relationships, and greater confidence in applying this knowledge to hands-on surgical procedures.

Background/Objectives: Accurate assessment of spinal bone density is essential for evaluating bone health, particularly in preoperative planning. Conventional manual methods for Hounsfield unit (HU) measurements rely on single-slice measurements within the region of interest, limiting their precision and reproducibility in patients with severe vertebral deformities. We hypothesize that a novel deep-reasoning and learning model (DR-AI) can fully automate spinal bone density assessment volumetrically, with high correlations to spinal bone mineral density (BMD) obtained from dual-energy X-ray absorptiometry (DXA), as well as to the T- and Z-scores. Methods: A cross-sectional study was conducted on patients who had BMD assessment of their lumbar spine and lumbar CT scans within 1 year. The fully-automated DR model was utilized to analyze the soft-tissue window of the lumbar vertebrae CT scans. Spearman correlation coefficients were calculated to assess the strength of relationships between the computed volumetric HUs and the BMD, T-, and Z-scores from each vertebra. Results: 84 patients (67 females, mean age 74.1 ± 10.3 years; 17 males, mean age 68.1 ± 12.4 years) meeting inclusion criteria. Correlation analyses for L1 to L4 showed significant positive relationships (p < 0.0001), with the strongest correlation at L2 between HU and BMD (ρ = 0.75). Conclusions: the DR model for automated assessment of volumetric HUs offers a highly reliable, efficient, and precise alternative to DXA measurements.

Abstract Cadaveric dissections, which are considered the most realistic model to study neuroanatomy, are expensive and not readily available in all centers. Given the surge of technological advances, incorporation of three‐dimensional (3D) scanning technologies and 3D models has gained popularity, both in the educational and clinical settings. We present our institutional experience in creating high‐fidelity neuroanatomical 3D models using three 3D scanning techniques: structured light 3D scanning, “manual” photogrammetry with a single DSLR camera, and “automatic” photogrammetry using a scanner equipped with five vertically arranged DSLR cameras and an automatic turntable within a square box. A survey study was conducted with 20 neurosurgical residents to assess the quality of the three resulting 3D models. In the study, “manual” photogrammetry was determined to be the most cost‐effective technique, while “automatic” photogrammetry was the most time‐effective and user‐friendly technique. The best visual quality was obtained using “manual” photogrammetry, as determined from survey results of 20 neurosurgical residents. While structured light 3D scanning had the lowest quality of resolution of the texture map, this technique was the most accurate to use for determining measurements, with a fixed accuracy of 0.05 mm. Overall, “manual” photogrammetry can allow for the most detailed 3D models and is the most cost‐effective strategy, while structured light 3D scanning is most suitable for obtaining clinically relevant measurements given the high degree of structural accuracy. Alternatively, “automatic” photogrammetry can serve as a hybrid between obtaining relatively high‐quality models in a time‐effective and user‐friendly manner.

Background: Despite increased adoption of virtual surgical planning (VSP) in various craniofacial indications, the incorporation of VSP/3DP into facial trauma care remains limited. Therefore, Expedited Preoperative Point of Care for Fracture Reduction to Normalized Anatomy and 3DP to Improve Surgical Outcomes (EPPOCRATIS) was introduced in 2021. This study evaluates our experience with EPPORATIS in craniomaxillofacial trauma over 10 years. Methods: A retrospective review of patients who underwent facial trauma repair between September 2014 and September 2024 was conducted. For each VSP/3DP case, a patient with similar facial trauma patterns, who was treated without VSP, was selected. Evaluation metrics included operative time, blood loss, length of stay, complication rates, and fracture reduction accuracy through 3D heatmap analyses. Operative metrics were normalized by implant (i.e., fracture plates and screws) count to account for fracture complexity. A value of p < 0.05 was deemed statistically significant. Results: The VSP group presented with more complex injuries and higher involvement of various surgical specialties (p < 0.5) and demonstrated longer operative times (p < 0.03). Although the difference was not statistically significant (p = 0.4), when adjusted for implant count, the VSP group had shorter operative times (median: 15.4 vs. 19.3 min/implant) and reduced blood loss compared to non-VSP cases (median: 3.4 mL/implant vs. 4.2 mL/implant). Complications, revision rates, and length of stay showed no significant differences. Conclusions: The use of VSP/3DP (EPPOCRATIS) in craniomaxillofacial trauma reconstruction demonstrated operative efficiency and accurate fracture reduction in complex cases. Further studies are needed to examine the feasibility and cost-effectiveness of point-of-care VSP/3DP in trauma centers.

AbstractPurposeThe small and complex space of the intranasal cavity poses a challenge to teaching and learning sinonasal anatomy in undergraduate medical education. Evidence suggests that utilizing 3D‐printed (3DP) models is an effective means to comprehend anatomical structures and their spatial relationships. In this study, we introduce and evaluate the educational value of rigid nasal endoscopy on realistic 3DP and silicone‐cast sinus models as a method to teach medical students intranasal anatomy.MethodsTwelve first‐year medical students participated in an educational rigid‐nasal endoscopy workshop led by Otolaryngology PGY‐2 residents and rhinology consultants. The workshop consisted of (1) an introductory PowerPoint on rigid nasal endoscopy and basic intranasal anatomy, (2) timed trials that tested students' ability to locate intranasal anatomical structures while scoping with a rigid endoscope, and (3) pre‐ and post‐surveys.ResultsParticipants improved in their ability to locate each intranasal anatomical structure during the timed trials. Participants felt that rigid endoscopy of 3DP models was an effective method to learn intranasal anatomy compared to their traditional medical school anatomy course.ConclusionThe results of this study suggest that rigid nasal endoscopy of 3DP sinus models is a potentially high‐value educational method for teaching intranasal anatomy to first‐year medical students. Students enjoyed the opportunity to learn intranasal anatomy while practicing a clinically relevant procedure ‐ rigid nasal endoscopy.

Objective: The pattern, rate, and natural history of bone flap resorption following cranioplasty with frozen, autologous bone flap has not been fully defined. The authors sought to quantify the progression and natural history of bone flap resorption. Methods: Patients who had craniectomy and delayed cranioplasty with stored, frozen bone flap between 2012 and 2022 were included in this study. Results: Ninety patients (63% male) were included, with a median age of 44.8 years (range: 4.2–84.4 y) at the time of autologous bone flap cranioplasty. Delayed, autologous cranioplasty occurred at a median time of 29.5 days (range: 2 d–10 y) from the index craniectomy. The median follow-up was 16.6 months (range: 3.4–85.4 mo). Radiographically quantifiable bone flap resorption occurred in 50 patients (56%). During the follow-up, the average percentage volume loss was 17%, with a nonlinear pattern of resorption. Following delayed, autologous cranioplasty, 11 patients had clinically significant bone flap resorption requiring secondary alloplastic cranioplasty at a median time of 13.8 months (range: 5.9–57.2 mo), with a mean percentage volume loss of 61%. Younger age was a risk factor for bone flap resorption (P < 0.05), whereas active smoking, presence of comorbidities, and number of days of bone flap storage were not risk factors for bone flap resorption. Penalized B-spline regression analysis showed that bone flap resorption followed a nonlinear pattern. Conclusion: Radiographically quantifiable bone flap resorption occurred in about 56% of patients following delayed autologous cranioplasty. Resorption followed a non-linear pattern. Young age is a risk factor for bone flap resorption.