Celda, María Peris

Abstract BACKGROUND Adamantinomatous craniopharyngiomas (ACPs) are rare, partially cystic central nervous system tumors driven by the WNT/β-catenin pathway. As they grow, ACPs compress the surrounding pituitary gland, optic chiasm, and third ventricle. ACPs are highly morbid tumors with enormous quality of life impact on patients, often early in life. Thus, better treatments are needed. Current ACP treatment consists of maximally safe surgical resection with radiation for residual disease. Complete surgical resection is challenging, and recurrence is common. Targeted systemic chemotherapy is not routinely used for ACP treatment. Interleukin-6 (IL-6) levels are elevated within ACPs compared to normal brain tissue, making IL-6 an intriguing therapeutic target. Treatment response of ACP to tocilizumab alone or in combination with bevacizumab has been reported in children. MATERIAL AND METHODS We retrospectively reviewed the medical records of three adults with recurrent ACP who received combination treatment with bevacizumab and tocilizumab on a compassionate basis between June 2022 and April 2025 at Mayo Clinic in Rochester, MN. We collected demographic, clinical, treatment, radiologic, and outcome data. RESULTS All three patients were male and median age at initial ACP diagnosis was 38 years (range: 32-42 years). All patients underwent subtotal resection followed by radiation therapy. One patient had repeat surgical resection and two patients required interventions for hydrocephalus. At the time of ACP recurrence, all patients had visual impairment, endocrine dysfunction, and headaches. All patients received bevacizumab (7.5 mg/kg q3 weeks) and tocilizumab (8 mg/kg q3 weeks [n=2] or 4 mg/kg q4 weeks [n=1]). While receiving combination therapy, ACP tumor volume decreased on magnetic resonance imaging for all three patients (64%, 68%, and 29% reduction). None exhibited tumor growth since starting combination therapy. One patient had a small intraparenchymal hemorrhage, suspected secondary to radiation-induced cavernous malformation, so bevacizumab was discontinued, and he remains on tocilizumab alone. The other two patients continue combination therapy (for 344 and 351 days). Two patients experienced improvement in vision, and one had improvement in cognition. Possible adverse effects of treatment included sinus infections, fatigue, neutropenia, and hypertension. CONCLUSION Treatment with combination bevacizumab and tocilizumab was associated with shrinkage of ACP tumors and clinical improvements and obviated the need for further surgery or radiation in all three patients. This combination of medications may reprogram the tumor microenvironment, leading to ACP involution. This well-tolerated regimen provides a noninvasive option for treatment of recurrent ACP, and potentially initial ACP treatment, and may improve quality of life for patients.

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.

Abstract Professor Albert J. Rhoton Jr., MD, is renowned for his groundbreaking dissections, marking a monumental achievement in the field of neuroanatomy. Alongside his anatomical contributions, he also passed on his knowledge and skills to numerous fellows, leaving behind a profound legacy. Despite the widespread recognition of his influence, little quantitative work has been done to characterize the scholarly impact of his alumni. Data were collected on Rhoton fellows, including fellowship years, country of origin, current institutions, and titles, practice settings, and leadership roles. Scholarly productivity was evaluated by assessing publication counts, including publications before and after the fellowship, and publications focused on surgical anatomy. Additionally, H-indices and citation counts were recorded. Other variables analyzed included ownership of a surgical anatomy laboratory, and participation in organizing hands-on courses. We analyzed 118 alumni from diverse countries. There was a significant increase in publication output following the fellowship, with publications rising from an average of 7 to 76 (p < 0.001). Fellows from high-income countries had higher research productivity than those from middle-income countries, with greater average H-index (p = 0.003), publication count (p = 0.01), and citation score (p = 0.003). Overall, 65% of fellows pursued academic practice, with 18% owning a laboratory and 30% involved in hands-on courses. Dr. Rhoton's mentorship has shaped a generation of neurosurgeons who continue his legacy. His fellows have established careers worldwide, leading in academia, professional organizations, and surgical training. Their global impact underscores the lasting value of structured mentorship in neurosurgery.

OBJECTIVE Calcium phosphate cement (CPC) use has been previously described as a strategy to reduce the rates of pseudomeningocele and CSF leakage following skull base surgery. The authors aimed to present their institutional experience with CPC in retrosigmoid craniotomy and perform a systematic review of the literature to determine the effectiveness of CPC in reducing postoperative complications, including pseudomeningocele and craniotomy-site CSF leakage. METHODS A retrospective single-institution cohort study of patients who underwent retrosigmoid craniotomy with and without CPC cranioplasty from January 2017 to April 2024 was performed. A systematic literature review and meta-analysis of CPC use in retrosigmoid craniotomy was also performed. RESULTS Of 336 patients who underwent retrosigmoid craniotomy, 193 (57%) were female and the median age at surgery was 55 years (range 18–81 years). The median follow-up duration was 23 months (range 3–80 months). CPC was used to seal the edge of the craniotomy in 66 patients (20%). Among all patients, 50 (15%) experienced a postoperative complication, and 28 (8%) were wound-specific complications. Patients in the non-CPC group experienced significantly more postoperative wound-specific complications than those in the CPC group (10% vs 0%, p = 0.002). Specifically, pseudomeningocele occurred in 0 patients (0%) in the CPC group compared with 24 patients (9%) in the non-CPC group (p = 0.006), which progressed to CSF leaks at the craniotomy site in 6 patients (p = 0.60). Additionally, no patients (0%) in the CPC group experienced wound infection, dehiscence, or breakdown compared with 10 patients (4%) in the non-CPC group (p = 0.22). Five patients (8%) in the CPC group reported prolonged mild incisional pain at the craniotomy site, and there were no instances of major complications related to the CPC. In the meta-analysis, 10 studies met the inclusion criteria, yielding a total of 2166 patients (including the current study), 1101 of whom received CPC. In the pooled analysis, CPC was significantly associated with lower risk of CSF leakage at the craniotomy site (OR 0.23, 95% CI 0.13–0.42; p < 0.01) and lower risk of infection (OR 0.17, 95% CI 0.08–0.38; p < 0.01). CONCLUSIONS CPC use in retrosigmoid craniotomies could be a safe and effective strategy to reduce the incidence of pseudomeningocele and craniotomy-site CSF leakage, leading to lower rates of wound-related complications and infection.

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.

ABSTRACT Objective There is limited consensus on endoscopic skull base surgery (ESBS) reconstruction principles. This study aims to generate comprehensive themes regarding ESBS reconstruction by pooling the experiences of ESBS experts, with comparison to a literature review of current published evidence. Methods Structured qualitative interviews of ESBS experts regarding postoperative management and reconstruction of various defect locations were conducted. Results A total of 68 experts comprising 40 academic teams across 13 countries with an average of 18 years of ESBS experience were included. We propose 10 stepwise algorithms for common skull base reconstruction scenarios based on these expert interviews. When available, the nasoseptal flap is used for all high_flow cerebrospinal leak defects. Multilayered reconstruction is favored at all anatomical subsites with increasing number of layers for increasing defect size and complexity. Heterogeneity exists in terms of inlay technique and materials, free grafting versus various pedicled flap options for low‐flow defects or in the absence of a nasal septum, nasal packing, tissue sealant, lumbar drain use, and postoperative management. Commonalities and discrepancies between experts were summarized. Conclusion Skull base reconstruction and post‐ESBS management is highly complex with a wide variety of practice patterns and expert strategies. Further research of higher quality evidence is warranted to identify optimal management patterns, though the current work aims to inform surgeons on these controversial areas by drawing from numerous experiences.

OBJECTIVE In this study, the authors aimed to establish a supervised machine learning (ML) model based on multiple tree-based algorithms to predict long-term biochemical outcomes and intervention-free survival (IFS) after endonasal transsphenoidal surgery (ETS) in patients with Cushing’s disease (CD). METHODS The medical records of patients who underwent ETS for CD between 2013 and 2023 were reviewed. Data were collected on the patient’s baseline characteristics, intervention details, histopathology, surgical outcomes, and postoperative endocrine functions. The study’s primary outcome was IFS, and the therapeutic outcomes were labeled as "under control" or "treatment failure," depending on whether additional therapeutic interventions after primary ETS were required. The decision tree and random forest classifiers were trained and tested to predict long-term IFS based on unseen data, using an 80/20 cohort split. RESULTS Data from 150 patients, with a median follow-up period of 56 months, were extracted. In the cohort, 42 (28%) patients required additional intervention for persistent or recurrent CD. Consequently, the IFS rates following ETS alone were 83% at 3 years and 78% at 5 years. Multivariable Cox proportional hazards analysis demonstrated that a smaller tumor diameter that could be detected by MRI (hazard ratio 0.95, 95% CI 0.90–0.99; p = 0.047) was significantly associated with greater IFS. However, the lack of tumor detection on MRI was a poor predictor. The ML-based model using a decision tree model displayed 91% accuracy (95% CI 0.70–0.94, sensitivity 87.0%, specificity 89.0%) in predicting IFS in the unseen test dataset. Random forest analysis revealed that tumor size (mean minimal depth 1.67), Knosp grade (1.75), patient age (1.80), and BMI (1.99) were the four most significant predictors of long-term IFS. CONCLUSIONS The ML algorithm could predict long-term postoperative endocrinological remission in CD with high accuracy, indicating that prognosis may vary not only with previously reported factors such as tumor size, Knosp grade, gross-total resection, and patient age but also with BMI. The decision tree flowchart could potentially stratify patients with CD before ETS, allowing for the selection of personalized treatment options and thereby assisting in determining treatment plans for these patients. This ML model may lead to a deeper understanding of the complex mechanisms of CD by uncovering patterns embedded within the data.