Pituitary society expert Delphi consensus: operative workflow in endoscopic transsphenoidal pituitary adenoma resection

Attention in surgical phase recognition for endoscopic pituitary surgery: Insights from real-world data

BACKGROUND AND OBJECTIVE

Surgical Phase Recognition systems are used to support the automated documentation of a procedure and to provide the surgical team with real-time feedback, potentially improving surgical outcome and reducing adverse events. The objective of this work is to develop a model for endoscopic pituitary surgery, a challenging procedure for phase recognition due to the high variability in the order of surgical phases.

METHODS

A dataset of 69 pituitary endoscopic videos was collected and labelled by two surgeons in seven different phases. The architecture proposed comprises a Convolutional Neural Network to identify spatial features in individual frames, and a Segment Attentive Hierarchical Consistency Network (which combines Temporal Convolutional Networks with attention mechanisms) to learn temporal relationship information between frames and segments at different temporal scales. Finally, predictions are refined with an adaptative mode window.

RESULTS

We have built and made publicly available the largest pituitary endoscopic surgery database to date, named PituPhase. We have built a model with a 73 % accuracy (75 % using a 10 s relaxed boundary). This result is comparable to other state-of-the-art methods in this surgical domain despite the challenges of the dataset (only 10 % of the videos are complete and only 3 % present all phases in the same order, versus 90 % and 50 % respectively in other studies).

CONCLUSIONS

Attention mechanisms in combination with Temporal Convolutional Networks and adaptive mode windows improve the performance of Surgical Phase Recognition systems and are robust to missing video sections and high variability in phase order.

Exploring perspectives on skull base chordoma management: a modified Delphi approach to consensus

OBJECTIVE

Current treatment for skull base chordomas utilizes both surgical resection and adjuvant radiation, but recent studies have demonstrated evidence that has brought the use of adjuvant radiotherapy into question. Chordomas differ greatly in molecular makeup and proliferation. These factors have led to significant variation in management across providers. We used a modified Delphi approach to work towards consensus on standardized operative definitions and evidence-based management of chordomas.

METHODS

Our multidisciplinary panel included participants representing the AANS/CNS Tumor Section and North American Skull Base Society (NASBS) with a track record of publishing on chordoma management. Our approach involved a four-step process: one statement-generation round, two voting rounds to establish consensus and refine statements, and a final external validation round by NASBS members. Anonymous voting was completed via Qualtrics surveys.

RESULTS

The statement-generation process produced 65 statements. Through the Delphi process, 36 statements reached consensus during the first round and an additional 17 were refined for further consensus in the second round. Moderate (67-80%) or strong (> 80%) consensus was achieved for 43 final statements. Forty-one items were externally validated. There was consensus that an endoscopic endonasal approach should be utilized whenever possible. They defined the tumor characteristics (molecular and cytogenic) to consider before offering adjuvant radiotherapy.

CONCLUSIONS

This modified Delphi study generated consensus on 41 statements regarding skull base chordoma management. These statements aim to shed light on the consensus among providers regarding the use of surgery, neoadjuvant radiation, adjuvant radiation, adjuvant systemic therapies, and treatment of recurrence for chordoma.

Augmented reality system for endoscopic pituitary surgery with automatic registration

PURPOSE

Endoscopic pituitary surgery is a minimally invasive technique to remove pituitary tumours through the nose. Currently, image guidance may be used in the form of a tracked pointer to help surgeons navigate the region and avoid damage to critical structures. However, the pointer method is mentally demanding as the pointer location is displayed in a different modality and disrupts the surgical workflow due to the setup time and frequent tool removal.

METHODS

We propose an Augmented Reality (AR) system where information from the pre-operative scan is displayed directly onto the endoscopic video. Our system features an on-board tracking system, allowing for the registration process to be performed automatically.

RESULTS

We evaluated the accuracy of our system and compared it to an AR system that uses an infrared (IR) camera to track an endoscope with reflective markers. Our system gave an accuracy of 1.1 (± 0.4) mm, compared to 2.4 (± 0.9) mm in the IR-tracked endoscope approach.

CONCLUSION

Our Augmented Reality system is a more compact and transportable setup which outperformed the IR-tracked endoscope. The automatic registration method can save time in the operating room as well as increase AR overlay accuracy, improving the translation of these technologies.

New 3D printed simulator for training of endoscopic transsphenoidal surgery used in a dedicated pituitary course: A French cross-sectional study

CONTEXT

The objective was to evaluate the feasibility and usefulness of a new 3D printed simulator for endoscopic pituitary surgery. This simulator was used at the Pituitary Workshop, a French theoretical and practical course designed to teach the basics of pituitary tumour management.

METHODS

We conducted a cross-sectional study. The pituitary workshop had two components: (i) hands-on skills lab on the simulator, and (ii) lecture-based learning. The simulator was assessed by scoring its realism (face validity, score out of 80), its effectiveness in improving participants' surgical technique (content validity, score out of 60), and its ability to differentiate levels of skill competence using performance metrics (construct validity, score out of 12). In a subgroup of 9 participants, the impact of the theoretical component of the course was also assessed (score out of 33), using a knowledge questionnaire before and after the course.

RESULTS

Participants were neurosurgery residents (n = 24) and board-certified neurosurgeons (n = 6), supervised by expert neurosurgeons (n = 3). Face and content validity scores were high, reaching 63.3 ± 8.4 and 55.7 ± 4.6 respectively. Performance scores were higher in the group of experts and board-certified neurosurgeons than in the group of residents (12 ± 0 and 11.3 ± 1.2 vs. 9.2 ± 2.3, P = 0.019). The knowledge score improved significantly after the workshop (25.5 ± 4.8 vs. 10.9 ± 5.8, P = 7.1e-05).

CONCLUSIONS

Based on the face, content and construct validity scores, simulation training using the new model can be considered feasible and useful for neurosurgery residents. The pituitary workshop has a positive practical and theoretical impact on the majority of participants.

Advances of artificial intelligence in clinical application and scientific research of neuro-oncology: Current knowledge and future perspectives

Brain tumors refer to the abnormal growths that occur within the brain's tissue, comprising both primary neoplasms and metastatic lesions. Timely detection, precise staging, suitable treatment, and standardized management are of significant clinical importance for extending the survival rates of brain tumor patients. Artificial intelligence (AI), a discipline within computer science, is leveraging its robust capacity for information identification and combination to revolutionize traditional paradigms of oncology care, offering substantial potential for precision medicine. This article provides an overview of the current applications of AI in brain tumors, encompassing the primary AI technologies, their working mechanisms and working workflow, the contributions of AI to brain tumor diagnosis and treatment, as well as the role of AI in brain tumor scientific research, particularly in drug innovation and revealing tumor microenvironment. Finally, the paper addresses the existing challenges, potential solutions, and the future application prospects. This review aims to enhance our understanding of the application of AI in brain tumors and provide valuable insights for forthcoming clinical applications and scientific inquiries.

A Handheld Robot for Endoscopic Endonasal Skull Base Surgery: Updated Preclinical Validation Study (IDEAL Stage 0)

Background and Objectives  Endoscopic endonasal surgery (EES) has become increasingly popular, yet anatomical constraints posed by the nose and limitations of nonarticulated instruments render EES technically challenging, with a steep associated learning curve. Therefore, we developed a handheld robot to enhance dexterity in endoscopic neurosurgical procedures. A previous trial of the robot demonstrated its potential advantages in endoscopic neurosurgery but also the need for improvements. In this study, we assess the feasibility, acceptability, and comparative performance of the updated robotic prototype (version 0.2) against standard instruments in a preclinical phantom and cadaveric trial. Methods  Ethical approval was received. Participants were stratified according to their neurosurgical experience. In the phantom study, a randomized crossover design compared the robot against standard instruments at a phantom tumor resection task. Statistical analysis was performed using Mann-Whitney U tests and paired t -tests. In the cadaver-based user study, participants evaluated the device's functional domains through a qualitative interview design. Results In the phantom study, the device demonstrated a learning curve: initial resection attempts favored the traditional instrument (84% vs. 59%, p  = 0.055), but parity was achieved by the fifth attempt (80% vs. 83%, p  = 0.76). Acceptability was evident, as most clinicians (7/8) preferred the robot for its superior range, ergonomics, and precision. Also, the robot exhibited a diminished cognitive workload. The cadaveric study underscored the robot's clinical feasibility, through sufficient workspace reach and force delivery. Conclusion : Overall, our robot demonstrates promising acceptability and feasibility for endoscopic neurosurgery, yet further iterative developments are required before proceeding to in-human clinical trials.

Identifying research priorities for pituitary adenoma surgery: an international Delphi consensus statement

PURPOSE

Pituitary surgery is the mainstay treatment for most pituitary adenomas, but many questions remain about perioperative and long-term management and outcomes. This study aimed to identify the most pressing research priorities in pituitary surgery with input from patients, caregivers, and healthcare professionals.

METHODS

An initial survey of patients, caregivers, and healthcare professionals assembled priorities related to preoperative care, surgical techniques, and postoperative management in pituitary surgery. Priorities were thematically grouped into summary priorities, and those answered by existing evidence were omitted following a literature review. An interim survey asked patients, caregivers, and healthcare professionals to select their top 10 priorities from the remaining list. The highest-ranked priorities advanced to a consensus meeting, where the top 10 questions were prioritized.

RESULTS

In the initial survey, 147 participants-60.5% of whom were patients, caregivers, or patient support group representatives-submitted 785 priorities, which were then condensed into 52 summary priorities. After a literature review, 33 unanswered priorities were included in the interim survey, completed by 155 respondents, of whom 54.2% were patients, caregivers, or patient support group representatives. The top-ranked priorities were discussed by 14 participants (7 patients and 7 healthcare professionals) during a consensus meeting. The top 10 priorities covered a variety of themes including enhancing diagnosis and management of pituitary adenomas, advancing surgical techniques and technologies, optimizing the prediction of outcomes and complications, and improving patient support and follow-up.

CONCLUSIONS

The top 10 research priorities in pituitary surgery aim to align researchers and direct funding in order to maximize impact and champion patient representation.

Augmented reality for endoscopic transsphenoidal surgery: evaluating design factors with neurosurgeons

PURPOSE

This study investigates the potential utility of augmented reality (AR) in the endoscopic transsphenoidal approach (TSA). While previous research has addressed technical challenges in AR for TSA, this paper explores how design factors can improve AR for neurosurgeons from a human-centred design perspective.

METHODS

Preliminary qualitative research involved observations of TSA procedures ( n = 2 ) and semi-structured interviews with neurosurgeons ( n = 4 ). These informed the design of an AR mockup, which was evaluated with neurosurgeons ( n = 3 ). An interactive low-fidelity prototype-the "AR-assisted Navigation for the TransSphenoidal Approach (ANTSA)"-was then developed in Unity 3D. A user study ( n = 4 ) evaluated the low-fidelity prototype of ANTSA through contextual interviews, providing feedback on design factors.

RESULTS

AR visualisations may be beneficial in streamlining the sellar phase and reducing intraoperative errors such as excessive or inadequate exposure. Key design recommendations include a lean mesh rendering, an intuitive colour palette, and optional structure highlighting.

CONCLUSION

This research presents user-centred design guidelines to improve sensemaking and surgical workflow in the sellar phase of TSA, with the goal of improving clinical outcomes. The specific improvements that AR could bring to the workflow are discussed along with surgeons' reservations and its possible application towards training less experienced physicians.

Automated surgical skill assessment in endoscopic pituitary surgery using real-time instrument tracking on a high-fidelity bench-top phantom

Improved surgical skill is generally associated with improved patient outcomes, although assessment is subjective, labour intensive, and requires domain-specific expertise. Automated data-driven metrics can alleviate these difficulties, as demonstrated by existing machine learning instrument tracking models. However, these models are tested on limited datasets of laparoscopic surgery, with a focus on isolated tasks and robotic surgery. Here, a new public dataset is introduced: the nasal phase of simulated endoscopic pituitary surgery. Simulated surgery allows for a realistic yet repeatable environment, meaning the insights gained from automated assessment can be used by novice surgeons to hone their skills on the simulator before moving to real surgery. Pituitary Real-time INstrument Tracking Network (PRINTNet) has been created as a baseline model for this automated assessment. Consisting of DeepLabV3 for classification and segmentation, StrongSORT for tracking, and the NVIDIA Holoscan for real-time performance, PRINTNet achieved 71.9% multiple object tracking precision running at 22 frames per second. Using this tracking output, a multilayer perceptron achieved 87% accuracy in predicting surgical skill level (novice or expert), with the 'ratio of total procedure time to instrument visible time' correlated with higher surgical skill. The new publicly available dataset can be found at https://doi.org/10.5522/04/26511049.

PitRSDNet: Predicting intra-operative remaining surgery duration in endoscopic pituitary surgery

Accurate intra-operative Remaining Surgery Duration (RSD) predictions allow for anaesthetists to more accurately decide when to administer anaesthetic agents and drugs, as well as to notify hospital staff to send in the next patient. Therefore, RSD plays an important role in improved patient care and minimising surgical theatre costs via efficient scheduling. In endoscopic pituitary surgery, it is uniquely challenging due to variable workflow sequences with a selection of optional steps contributing to high variability in surgery duration. This article presents PitRSDNet for predicting RSD during pituitary surgery, a spatio-temporal neural network model that learns from historical data focusing on workflow sequences. PitRSDNet integrates workflow knowledge into RSD prediction in two forms: (1) multi-task learning for concurrently predicting step and RSD; and (2) incorporating prior steps as context in temporal learning and inference. PitRSDNet is trained and evaluated on a new endoscopic pituitary surgery dataset with 88 videos to show competitive performance improvements over previous statistical and machine learning methods. The findings also highlight how PitRSDNet improves RSD precision on outlier cases utilising the knowledge of prior steps.

Artificial intelligence assisted operative anatomy recognition in endoscopic pituitary surgery

Pituitary tumours are surrounded by critical neurovascular structures and identification of these intra-operatively can be challenging. We have previously developed an AI model capable of sellar anatomy segmentation. This study aims to apply this model, and explore the impact of AI-assistance on clinician anatomy recognition. Participants were tasked with labelling the sella on six images, initially without assistance, then augmented by AI. Mean DICE scores and the proportion of annotations encompassing the centroid of the sella were calculated. Six medical students, six junior trainees, six intermediate trainees and six experts were recruited. There was an overall improvement in sella recognition from a DICE of score 70.7% without AI assistance to 77.5% with AI assistance (+6.7; p < 0.001). Medical students used and benefitted from AI assistance the most, improving from a DICE score of 66.2% to 78.9% (+12.8; p = 0.02). This technology has the potential to augment surgical education and eventually be used as an intra-operative decision support tool.

Video-Based Performance Analysis in Pituitary Surgery - Part 2: Artificial Intelligence Assisted Surgical Coaching

BACKGROUND

Superior surgical skill improves surgical outcomes in endoscopic pituitary adenoma surgery. Video-based coaching programs, pioneered in professional sports, have shown promise in surgical training. In this study, we developed and assessed a video-based coaching program using artificial intelligence (AI) assistance.

METHODS

An AI-assisted video-based surgical coaching was implemented over 6 months with the pituitary surgery team. The program consisted of 1) monthly random video analysis and review; and 2) quarterly 2-hour educational meetings discussing these videos and learning points. Each video was annotated for surgical phases and steps using AI, which improved video interactivity and allowed the calculation of quantitative metrics. Primary outcomes were program feasibility, acceptability, and appropriateness. Surgical performance (via modified Objective Structured Assessment of Technical Skills) and early surgical outcomes were recorded for every case during the 6-month coaching period, and a preceding 6-month control period. Beta and logistic regression were used to assess the change in modified Objective Structured Assessment of Technical Skills scores and surgical outcomes after the coaching program implementation.

RESULTS

All participants highly rated the program's feasibility, acceptability, and appropriateness. During the coaching program, 63 endoscopic pituitary adenoma cases were included, with 41 in the control group. Surgical performance across all operative phases improved during the coaching period (P < 0.001), with a reduction in new postoperative anterior pituitary hormone deficit (P = 0.01).

CONCLUSIONS

We have developed a novel AI-assisted video surgical coaching program for endoscopic pituitary adenoma surgery - demonstrating its viability and impact on surgical performance. Early results also suggest improvement in patient outcomes. Future studies should be multicenter and longer term.

Video-Based Performance Analysis in Pituitary Surgery-Part 1: Surgical Outcomes

BACKGROUND

Endoscopic pituitary adenoma surgery has a steep learning curve, with varying surgical techniques and outcomes across centers. In other surgeries, superior performance is linked with superior surgical outcomes. This study aimed to explore the prediction of patient-specific outcomes using surgical video analysis in pituitary surgery.

METHODS

Endoscopic pituitary adenoma surgery videos from a single center were annotated by experts for operative workflow (3 surgical phases and 15 surgical steps) and operative skill (using modified Objective Structured Assessment of Technical Skills [mOSATS]). Quantitative workflow metrics were calculated, including phase duration and step transitions. Poisson or logistic regression was used to assess the association of workflow metrics and mOSATS with common inpatient surgical outcomes.

RESULTS

100 videos from 100 patients were included. Nasal phase mean duration was 24 minutes and mean mOSATS was 21.2/30. Mean duration was 34 minutes and mean mOSATS was 20.9/30 for the sellar phase, and 11 minutes and 21.7/30, respectively, for the closure phase. The most common adverse outcomes were new anterior pituitary hormone deficiency (n = 26), dysnatremia (n = 24), and cerebrospinal fluid leak (n = 5). Higher mOSATS for all 3 phases and shorter operation duration were associated with decreased length of stay (P = 0.003 &P < 0.001). Superior closure phase mOSATS were associated with reduced postoperative cerebrospinal fluid leak (P < 0.001), and superior sellar phase mOSATS were associated with reduced postoperative visual deterioration (P = 0.041).

CONCLUSIONS

Superior surgical skill and shorter surgical time were associated with superior surgical outcomes, at a generic and phase-specific level. Such video-based analysis has promise for integration into data-driven training and service improvement initiatives.

Diaphragm reconstruction using a TachoSil patch as alternative to intrasellar packing for small focal diaphragm defects in pituitary surgery: a cohort study

BACKGROUND

During pituitary surgery, CSF leaks are often treated by intrasellar packing, using muscle or fat grafts. However, this strategy may interfere with the interpretation of postoperative MRI and may impact the quality of resection in cases of second surgery, due to the existence of additional fibrous tissue. We present an alternative technique, using a diaphragm reconstruction with a heterologous sponge combining fibrinogen and thrombin (TachoSil), applied in selected patients with low-flow CSF leaks. This study investigates the surgical outcome of patients treated with this strategy.

METHODS

From a cohort of 2231 patients treated from June 2011 to June 2023 by endoscopic endonasal approach for pituitary surgery, the surgical technique of diaphragm repair with TachoSil patch performed in 55 patients (2.6%) was detailed, and the rate of closure failure was analyzed at 6 months postoperatively. No intrasellar packing was used and sellar floor reconstruction was performed whenever possible. The rate of postoperative CSF leak was compared with that reported in three previous publications that also used the TachoSil patch technique.

RESULTS

Patients were mostly women (F/M ratio: 1.2) with a median age of 53.6 years. Surgery was indicated for non-functioning adenomas, Cushing's disease, acromegaly, and Rathke's cleft cysts in 38/55 (69.1%), 6/55 (10.9%), 5/55 (9.1%) and 6/55 (10.9%) patients respectively. The rate of postoperative CSF leak was 1.8% (n = 1/55), which was not significantly different from that reported in the three cohorts from the literature (2.8%, p > 0.05). No postoperative meningitis was recorded.

CONCLUSIONS

In highly selected patients with low-flow CSF leaks related to small focal diaphragm defects, diaphragm reconstruction using a TachoSil patch can be a safe and valuable alternative to intrasellar packing.

PitSurgRT: real-time localization of critical anatomical structures in endoscopic pituitary surgery

PURPOSE

Endoscopic pituitary surgery entails navigating through the nasal cavity and sphenoid sinus to access the sella using an endoscope. This procedure is intricate due to the proximity of crucial anatomical structures (e.g. carotid arteries and optic nerves) to pituitary tumours, and any unintended damage can lead to severe complications including blindness and death. Intraoperative guidance during this surgery could support improved localization of the critical structures leading to reducing the risk of complications.

METHODS

A deep learning network PitSurgRT is proposed for real-time localization of critical structures in endoscopic pituitary surgery. The network uses high-resolution net (HRNet) as a backbone with a multi-head for jointly localizing critical anatomical structures while segmenting larger structures simultaneously. Moreover, the trained model is optimized and accelerated by using TensorRT. Finally, the model predictions are shown to neurosurgeons, to test their guidance capabilities.

RESULTS

Compared with the state-of-the-art method, our model significantly reduces the mean error in landmark detection of the critical structures from 138.76 to 54.40 pixels in a 1280 × 720-pixel image. Furthermore, the semantic segmentation of the most critical structure, sella, is improved by 4.39% IoU. The inference speed of the accelerated model achieves 298 frames per second with floating-point-16 precision. In the study of 15 neurosurgeons, 88.67% of predictions are considered accurate enough for real-time guidance.

CONCLUSION

The results from the quantitative evaluation, real-time acceleration, and neurosurgeon study demonstrate the proposed method is highly promising in providing real-time intraoperative guidance of the critical anatomical structures in endoscopic pituitary surgery.

Blood Harmonisation of Endoscopic Transsphenoidal Surgical Video Frames on Phantom Models

Physical phantom models have been integral to surgical training, yet they lack realism and are unable to replicate the presence of blood resulting from surgical actions. Existing domain transfer methods aim to enhance realism, but none facilitate blood simulation. This study investigates the overlay of blood on images acquired during endoscopic transsphenoidal pituitary surgery on phantom models. The process involves employing manual techniques using the GIMP image manipulation application and automated methods using pythons Blend Modes module. We then approach this as an image harmonisation task to assess its practicality and feasibility. Our evaluation uses Structural Similarity Index Measure and Laplacian metrics. The results we obtained emphasize the significance of image harmonisation, offering substantial insights within the surgical field. Our work is a step towards investigating data-driven models that can simulate blood for increased realism during surgical training on phantom models.

Pituitary surgery outcome in patients 75 years and older: a retrospective study

BACKGROUND

As the population ages, the number of elderly patients with an indication for pituitary surgery is rising. Information on the outcome of patients aged over 75 is limited. This study reports a large series assessing the feasibility of surgical resection in this specific age range, focusing on surgical complications and postoperative results.

METHODS

A retrospective cohort study of patients with pituitary adenomas and Rathke's cleft cysts was conducted. All patients were aged 75 years or over and treated by a single expert neurosurgical team. A control population included 2379 younger adult patients operated by the same surgeons during the same period.

RESULTS

Between 2008 and 2022, 155 patients underwent surgery. Indication was based on vision impairment in most patients (79%). Median follow-up was 13 months (range: 3-96). The first surgery was performed with an endoscopic transsellar approach, an extended endonasal transtuberculum approach and a microscopic transcranial approach in 96%, 3%, and 1% of patients, respectively. Single surgery was sufficient to obtain volume control in 97% of patients. From Kaplan-Meier estimates, 2-year and 5-year disease control with a single surgery were 97.3% and 86.2%, respectively. Resection higher than 80% was achieved in 77% of patients. No vision worsening occurred. In acromegaly and Cushing's disease, endocrine remission was obtained in 90% of non-invasive adenomas. Surgical complications were noted in 5% of patients, with 30-day mortality, hematoma, cerebrospinal fluid leak, meningitis, and epistaxis occurring in 0.6%, 0.6%, 1.9%, 0.6%, and 1.3% respectively. New endocrine anterior deficits occurred in only 5%, while no persistent diabetes insipidus was noted. Compared with younger patients, the complication rate was not statistically different.

CONCLUSIONS

Surgery beyond the age of 75, mainly relying on an endoscopic endonasal transsellar approach, is effective and safe, provided that patients are managed in tertiary centers.

Quantification of Surgical Workflow during Robotic Proctectomy

Aim

Assessments of surgical workflow offer insight regarding procedure variability, case complexity and surgeon proficiency. We utilize an objective method to evaluate step-by-step workflow and step transitions during robotic proctectomy (RP).

Methods

We annotated 31 RPs using a procedure-specific annotation card. Using Spearman's correlation, we measured strength of association of step time and step visit frequency with console time (CT) and total operative time (TOT).

Results

Across 31 RPs, a mean (± standard deviation) of 49.0 (± 20.3) steps occurred per procedure. Mean CT and TOT were 213 (± 90) and 283 (± 108) minutes. Posterior mesorectal dissection required most visits (8.7 ± 5.0), while anastomosis required most time (18.0 [± 8.5] minutes). Inferior mesenteric vein (IMV) ligation required least visits (1.0 ± 0.0) and lowest duration (0.9 [± 0.5] minutes). Strong correlations were seen with CT and step times for IMV dissection and ligation (ρ = 0.60 for both), lateral-to-medial splenic flexure mobilization (SFM) (ρ = 0.63), left rectal dissection (ρ = 0.64) and mesorectal division (ρ = 0.71). CT correlated strongly with medial-to-lateral and supracolic SFM visit frequency (ρ = 0.75 and ρ = 0.65). There were strong correlations with TOT and initial exposure time (ρ = 0.60), as well as visit frequency for medial-to-lateral (ρ = 0.67) and supracolic SFM (ρ = 0.65). Descending colon mobilization was nodal, rectal mobilization convergent and rectal transection divergent.

Conclusion

This study correlates individual surgical steps with CT and TOT through standardized annotation. It provides an objective approach to quantify workflow.

Generating Operative Workflows for Vestibular Schwannoma Resection: A Two-Stage Delphi's Consensus in Collaboration with the British Skull Base Society. Part 2: The Translabyrinthine Approach

Objective  An operative workflow systematically compartmentalizes operations into hierarchal components of phases, steps, instrument, technique errors, and event errors. Operative workflow provides a foundation for education, training, and understanding of surgical variation. In this Part 2, we present a codified operative workflow for the translabyrinthine approach to vestibular schwannoma resection. Methods  A mixed-method consensus process of literature review, small-group Delphi's consensus, followed by a national Delphi's consensus was performed in collaboration with British Skull Base Society (BSBS). Each Delphi's round was repeated until data saturation and over 90% consensus was reached. Results  Seventeen consultant skull base surgeons (nine neurosurgeons and eight ENT [ear, nose, and throat]) with median of 13.9 years of experience (interquartile range: 18.1 years) of independent practice participated. There was a 100% response rate across both the Delphi rounds. The translabyrinthine approach had the following five phases and 57 unique steps: Phase 1, approach and exposure; Phase 2, mastoidectomy; Phase 3, internal auditory canal and dural opening; Phase 4, tumor debulking and excision; and Phase 5, closure. Conclusion  We present Part 2 of a national, multicenter, consensus-derived, codified operative workflow for the translabyrinthine approach to vestibular schwannomas. The five phases contain the operative, steps, instruments, technique errors, and event errors. The codified translabyrinthine approach presented in this manuscript can serve as foundational research for future work, such as the application of artificial intelligence to vestibular schwannoma resection and comparative surgical research.

Assessing national patterns and outcomes of pituitary surgery: is hospital administrative data good enough?

PURPOSE

Patterns of surgical care, outcomes, and quality of care can be assessed using hospital administrative databases but this requires accurate and complete data. The aim of this study was to explore whether the quality of hospital administrative data was sufficient to assess pituitary surgery practice in England.

METHODS

The study analysed Hospital Episode Statistics (HES) data from April 2013 to March 2018 on all adult patients undergoing pituitary surgery in England. A series of data quality indicators examined the attribution of cases to consultants, the coding of sellar and parasellar lesions, associated endocrine and visual disorders, and surgical procedures. Differences in data quality over time and between neurosurgical units were examined.

RESULTS

A total of 5613 records describing pituitary procedures were identified. Overall, 97.3% had a diagnostic code for the tumour or lesion treated, with 29.7% (n = 1669) and 17.8% (n = 1000) describing endocrine and visual disorders, respectively. There was a significant reduction from the first to the fifth year in records that only contained a pituitary tumour code (63.7%-47.0%, p < .001). The use of procedure codes that attracted the highest tariff increased over time (66.4%-82.4%, p < .001). Patterns of coding varied widely between the 24 neurosurgical units.

CONCLUSION

The quality of HES data on pituitary surgery has improved over time but there is wide variation in the quality of data between neurosurgical units. Research studies and quality improvement programmes using these data need to check it is of sufficient quality to not invalidate their results.

Generating Operative Workflows for Vestibular Schwannoma Resection: A Two-Stage Delphi's Consensus in Collaboration with the British Skull Base Society. Part 1: The Retrosigmoid Approach

Objective  An operative workflow systematically compartmentalizes operations into hierarchal components of phases, steps, instrument, technique errors, and event errors. Operative workflow provides a foundation for education, training, and understanding of surgical variation. In this Part 1, we present a codified operative workflow for the retrosigmoid approach to vestibular schwannoma resection. Methods  A mixed-method consensus process of literature review, small-group Delphi's consensus, followed by a national Delphi's consensus, was performed in collaboration with British Skull Base Society (BSBS). Each Delphi's round was repeated until data saturation and over 90% consensus was reached. Results  Eighteen consultant skull base surgeons (10 neurosurgeons and 8 ENT [ear, nose, and throat]) with median 17.9 years of experience (interquartile range: 17.5 years) of independent practice participated. There was a 100% response rate across both Delphi's rounds. The operative workflow for the retrosigmoid approach contained three phases and 40 unique steps as follows: phase 1, approach and exposure; phase 2, tumor debulking and excision; phase 3, closure. For the retrosigmoid approach, technique, and event error for each operative step was also described. Conclusion  We present Part 1 of a national, multicenter, consensus-derived, codified operative workflow for the retrosigmoid approach to vestibular schwannomas that encompasses phases, steps, instruments, technique errors, and event errors. The codified retrosigmoid approach presented in this manuscript can serve as foundational research for future work, such as operative workflow analysis or neurosurgical simulation and education.

Current and Future Advances in Surgical Therapy for Pituitary Adenoma

The vital physiological role of the pituitary gland, alongside its proximity to critical neurovascular structures, means that pituitary adenomas can cause significant morbidity or mortality. While enormous advancements have been made in the surgical care of pituitary adenomas, numerous challenges remain, such as treatment failure and recurrence. To meet these clinical challenges, there has been an enormous expansion of novel medical technologies (eg, endoscopy, advanced imaging, artificial intelligence). These innovations have the potential to benefit each step of the patient's journey, and ultimately, drive improved outcomes. Earlier and more accurate diagnosis addresses this in part. Analysis of novel patient data sets, such as automated facial analysis or natural language processing of medical records holds potential in achieving an earlier diagnosis. After diagnosis, treatment decision-making and planning will benefit from radiomics and multimodal machine learning models. Surgical safety and effectiveness will be transformed by smart simulation methods for trainees. Next-generation imaging techniques and augmented reality will enhance surgical planning and intraoperative navigation. Similarly, surgical abilities will be augmented by the future operative armamentarium, including advanced optical devices, smart instruments, and surgical robotics. Intraoperative support to surgical team members will benefit from a data science approach, utilizing machine learning analysis of operative videos to improve patient safety and orientate team members to a common workflow. Postoperatively, neural networks leveraging multimodal datasets will allow early detection of individuals at risk of complications and assist in the prediction of treatment failure, thus supporting patient-specific discharge and monitoring protocols. While these advancements in pituitary surgery hold promise to enhance the quality of care, clinicians must be the gatekeepers of the translation of such technologies, ensuring systematic assessment of risk and benefit prior to clinical implementation. In doing so, the synergy between these innovations can be leveraged to drive improved outcomes for patients of the future.

A methodology for the annotation of surgical videos for supervised machine learning applications

PURPOSE

Surgical data science is an emerging field focused on quantitative analysis of pre-, intra-, and postoperative patient data (Maier-Hein et al. in Med Image Anal 76: 102306, 2022). Data science approaches can decompose complex procedures, train surgical novices, assess outcomes of actions, and create predictive models of surgical outcomes (Marcus et al. in Pituitary 24: 839-853, 2021; Røadsch et al. in Nat Mach Intell, 2022). Surgical videos contain powerful signals of events that may impact patient outcomes. A necessary step before the deployment of supervised machine learning methods is the development of labels for objects and anatomy. We describe a complete method for annotating videos of transsphenoidal surgery.

METHODS

Endoscopic video recordings of transsphenoidal pituitary tumor removal surgeries were collected from a multicenter research collaborative. These videos were anonymized and stored in a cloud-based platform. Videos were uploaded to an online annotation platform. Annotation framework was developed based on a literature review and surgical observations to ensure proper understanding of the tools, anatomy, and steps present. A user guide was developed to trained annotators to ensure standardization.

RESULTS

A fully annotated video of a transsphenoidal pituitary tumor removal surgery was produced. This annotated video included over 129,826 frames. To prevent any missing annotations, all frames were later reviewed by highly experienced annotators and a surgeon reviewer. Iterations to annotated videos allowed for the creation of an annotated video complete with labeled surgical tools, anatomy, and phases. In addition, a user guide was developed for the training of novice annotators, which provides information about the annotation software to ensure the production of standardized annotations.

CONCLUSIONS

A standardized and reproducible workflow for managing surgical video data is a necessary prerequisite to surgical data science applications. We developed a standard methodology for annotating surgical videos that may facilitate the quantitative analysis of videos using machine learning applications. Future work will demonstrate the clinical relevance and impact of this workflow by developing process modeling and outcome predictors.

A systematic review of annotation for surgical process model analysis in minimally invasive surgery based on video

BACKGROUND

Annotated data are foundational to applications of supervised machine learning. However, there seems to be a lack of common language used in the field of surgical data science. The aim of this study is to review the process of annotation and semantics used in the creation of SPM for minimally invasive surgery videos.

METHODS

For this systematic review, we reviewed articles indexed in the MEDLINE database from January 2000 until March 2022. We selected articles using surgical video annotations to describe a surgical process model in the field of minimally invasive surgery. We excluded studies focusing on instrument detection or recognition of anatomical areas only. The risk of bias was evaluated with the Newcastle Ottawa Quality assessment tool. Data from the studies were visually presented in table using the SPIDER tool.

RESULTS

Of the 2806 articles identified, 34 were selected for review. Twenty-two were in the field of digestive surgery, six in ophthalmologic surgery only, one in neurosurgery, three in gynecologic surgery, and two in mixed fields. Thirty-one studies (88.2%) were dedicated to phase, step, or action recognition and mainly relied on a very simple formalization (29, 85.2%). Clinical information in the datasets was lacking for studies using available public datasets. The process of annotation for surgical process model was lacking and poorly described, and description of the surgical procedures was highly variable between studies.

CONCLUSION

Surgical video annotation lacks a rigorous and reproducible framework. This leads to difficulties in sharing videos between institutions and hospitals because of the different languages used. There is a need to develop and use common ontology to improve libraries of annotated surgical videos.

Navigating the learning curve with large and giant tumors: Initial experience with endoscopic endonasal transphenoidal resection of PitNETs

BACKGROUND

The endoscopic endonasal approach (EEA) has progressively become the preferred choice of surgical intervention for PitNETs. However, the adoption in Sub-Saharan Africa has been low. We report our initial experience with the utility of the EEA in PitNETs particularly in large and giant tumors despite limited resources.

METHODS

The study was over a 73-month period at the University College Hospital, Ibadan, Nigeria. Pre and post-operative clinical, imaging and neuro-ophthalmological findings were documented. Perioperative and postoperative outcomes were recorded. We compared the outcomes between the early 23 and later 22 patients. Data were analyzed using descriptive statistics, student's t test, Mann-Whitney U test and Chi square test at α = 0.05.

RESULTS

There were 45 patients; 25(55.6%) were males. Mean age was 49.9 ± 13.4 years. Visual symptoms predominated with 12(26%) blind in at least one eye. Median tumor volume was 20.9 cm³ and mean tumor diameter was 4.09 ± 0.89 cm. 31(68.9%) had gross or near total excision. Vision improved in 31(68.9%). There were 2 procedure related mortality from CSF leak/meningitis. The mean of the tumor diameter of the earlier patients was less than that of the latter (3.84 vs 4.40 cm, p = 0.04,). The latter group also had more gross or near total resections (26.8% versus 41.5%) but this was not statistically significant. There was no difference in postoperative complications.

CONCLUSIONS

EEA remains a veritable option for PitNETs, including for large and huge tumors, even within resource challenged environments, with acceptable limits of complications.

Reported outcomes in transsphenoidal surgery for pituitary adenomas: a systematic review

PURPOSE

Transsphenoidal surgery is an established treatment for pituitary adenomas. We examined outcomes and time points following transsphenoidal surgery for pituitary adenoma to identify reporting heterogeneity within the literature.

METHODS

A systematic review of studies that reported outcomes for transsphenoidal surgery for pituitary adenoma 1990-2021 were examined. The protocol was registered a priori and adhered to the PRISMA statement. Studies in English with > 10 patients (prospective) or > 500 patients (retrospective) were included.

RESULTS

178 studies comprising 427,659 patients were included. 91 studies reported 2 or more adenoma pathologies within the same study; 53 studies reported a single pathology. The most common adenomas reported were growth hormone-secreting (n = 106), non-functioning (n = 101), and ACTH-secreting (n = 95); 27 studies did not state a pathology. Surgical complications were the most reported outcome (n = 116, 65%). Other domains included endocrine (n = 104, 58%), extent of resection (n = 81, 46%), ophthalmic (n = 66, 37%), recurrence (n = 49, 28%), quality of life (n = 25, 19%); and nasal (n = 18, 10%). Defined follow up time points were most reported for endocrine (n = 56, 31%), extent of resection (n = 39, 22%), and recurrence (n = 28, 17%). There was heterogeneity in the follow up reported for all outcomes at different time points: discharge (n = 9), < 30 days (n = 23), < 6 months (n = 64), < 1 year (n = 23), and > 1 year (n = 69).

CONCLUSION

Outcomes and follow up reported for transsphenoidal surgical resection of pituitary adenoma are heterogenous over the last 30 years. This study highlights the necessity to develop a robust, consensus-based, minimum, core outcome set. The next step is to develop a Delphi survey of essential outcomes, followed by a consensus meeting of interdisciplinary experts. Patient representatives should also be included. An agreed core outcome set will enable homogeneous reporting and meaningful research synthesis, ultimately improving patient care.

CRANIAL Consortium. Machine learning driven prediction of cerebrospinal fluid rhinorrhoea following endonasal skull base surgery: A multicentre prospective observational study

Background

Cerebrospinal fluid rhinorrhoea (CSFR) is a common complication following endonasal skull base surgery, a technique that is fundamental to the treatment of pituitary adenomas and many other skull base tumours. The CRANIAL study explored CSFR incidence and related risk factors, particularly skull base repair techniques, via a multicentre prospective observational study. We sought to use machine learning to leverage this complex multicentre dataset for CSFR prediction and risk factor analysis.

Methods

A dataset of 865 cases - 725 transsphenoidal approach (TSA) and 140 expanded endonasal approach (EEA) - with cerebrospinal fluid rhinorrhoea as the primary outcome, was used. Relevant variables were extracted from the data, and prediction variables were divided into two categories, preoperative risk factors; and repair techniques, with 6 and 11 variables respectively. Three types of machine learning models were developed in order to predict CSFR: logistic regression (LR); decision tree (DT); and neural network (NN). Models were validated using 5-fold cross-validation, compared via their area under the curve (AUC) evaluation metric, and key prediction variables were identified using their Shapley additive explanations (SHAP) score.

Results

CSFR rates were 3.9% (28/725) for the transsphenoidal approach and 7.1% (10/140) for the expanded endonasal approach. NNs outperformed LR and DT for CSFR prediction, with a mean AUC of 0.80 (0.70-0.90) for TSA and 0.78 (0.60-0.96) for EEA, when all risk factor and intraoperative repair data were integrated into the model. The presence of intraoperative CSF leak was the most prominent risk factor for CSFR. Elevated BMI and revision surgery were also associated with CSFR for the transsphenoidal approach. CSF diversion and gasket sealing appear to be strong predictors of the absence of CSFR for both approaches.

Conclusion

Neural networks are effective at predicting CSFR and uncovering key CSFR predictors in patients following endonasal skull base surgery, outperforming traditional statistical methods. These models will be improved further with larger and more granular datasets, improved NN architecture, and external validation. In the future, such predictive models could be used to assist surgical decision-making and support more individualised patient counselling.

A Sensorised Surgical Glove to Analyze Forces During Neurosurgery

BACKGROUND

Measuring intraoperative forces in real time can provide feedback mechanisms to improve patient safety and surgical training. Previous force monitoring has been achieved through the development of specialized and adapted instruments or use designs that are incompatible with neurosurgical workflow.

OBJECTIVE

To design a universal sensorised surgical glove to detect intraoperative forces, applicable to any surgical procedure, and any surgical instrument in either hand.

METHODS

We created a sensorised surgical glove that was calibrated across 0 to 10 N. A laboratory experiment demonstrated that the sensorised glove was able to determine instrument-tissue forces. Six expert and 6 novice neurosurgeons completed a validated grape dissection task 20 times consecutively wearing the sensorised glove. The primary outcome was median and maximum force (N).

RESULTS

The sensorised glove was able to determine instrument-tissue forces reliably. The average force applied by experts (2.14 N) was significantly lower than the average force exerted by novices (7.15 N) ( P = .002). The maximum force applied by experts (6.32 N) was also significantly lower than the maximum force exerted by novices (9.80 N) ( P = .004). The sensorised surgical glove's introduction to operative workflow was feasible and did not impede on task performance.

CONCLUSION

We demonstrate a novel and scalable technique to detect forces during neurosurgery. Force analysis can provide real-time data to optimize intraoperative tissue forces, reduce the risk of tissue injury, and provide objective metrics for training and assessment.

CSF rhinorrhoea after endonasal intervention to the skull base (CRANIAL): A multicentre prospective observational study

Objective

Despite progress in endonasal skull-base neurosurgery, cerebrospinal fluid (CSF) rhinorrhoea remains common and significant. The CRANIAL study sought to determine 1) the scope of skull-base repair methods used, and 2) corresponding rates of postoperative CSF rhinorrhoea in the endonasal transsphenoidal approach (TSA) and the expanded endonasal approach (EEA) for skull-base tumors.

Methods

A prospective observational cohort study of 30 centres performing endonasal skull-base neurosurgery in the UK and Ireland (representing 91% of adult units). Patients were identified for 6 months and followed up for 6 months. Data collection and analysis was guided by our published protocol and pilot studies. Descriptive statistics, univariate and multivariable logistic regression models were used for analysis.

Results

A total of 866 patients were included - 726 TSA (84%) and 140 EEA (16%). There was significant heterogeneity in repair protocols across centres. In TSA cases, nasal packing (519/726, 72%), tissue glues (474/726, 65%) and hemostatic agents (439/726, 61%) were the most common skull base repair techniques. Comparatively, pedicled flaps (90/140, 64%), CSF diversion (38/140, 27%), buttresses (17/140, 12%) and gasket sealing (11/140, 9%) were more commonly used in EEA cases. CSF rhinorrhoea (biochemically confirmed or requiring re-operation) occurred in 3.9% of TSA (28/726) and 7.1% of EEA (10/140) cases. A significant number of patients with CSF rhinorrhoea (15/38, 39%) occurred when no intraoperative CSF leak was reported. On multivariate analysis, there may be marginal benefits with using tissue glues in TSA (OR: 0.2, CI: 0.1-0.7, p<0.01), but no other technique reached significance. There was evidence that certain characteristics make CSF rhinorrhoea more likely - such as previous endonasal surgery and the presence of intraoperative CSF leak.

Conclusions

There is a wide range of skull base repair techniques used across centres. Overall, CSF rhinorrhoea rates across the UK and Ireland are lower than generally reported in the literature. A large proportion of postoperative leaks occurred in the context of occult intraoperative CSF leaks, and decisions for universal sellar repairs should consider the risks and cost-effectiveness of repair strategies. Future work could include longer-term, higher-volume studies, such as a registry; and high-quality interventional studies.

Automatic generation of operation notes in endoscopic pituitary surgery videos using workflow recognition

Operation notes are a crucial component of patient care. However, writing them manually is prone to human error, particularly in high pressured clinical environments. Automatic generation of operation notes from video recordings can alleviate some of the administrative burdens, improve accuracy, and provide additional information. To achieve this for endoscopic pituitary surgery, 27-steps were identified via expert consensus. Then, for the 97-videos recorded for this study, a timestamp of each step was annotated by an expert surgeon. To automatically determine whether a step is present in a video, a three-stage architecture was created. Firstly, for each step, a convolution neural network was used for binary image classification on each frame of a video. Secondly, for each step, the binary frame classifications were passed to a discriminator for binary video classification. Thirdly, for each video, the binary video classifications were passed to an accumulator for multi-label step classification. The architecture was trained on 77-videos, and tested on 20-videos, where a 0.80 weighted-F1 score was achieved. The classifications were inputted into a clinically based predefined template, and further enriched with additional video analytics. This work therefore demonstrates automatic generation of operative notes from surgical videos is feasible, and can assist surgeons during documentation.

High fidelity simulation of the endoscopic transsphenoidal approach: Validation of the UpSurgeOn TNS Box

Objective

Endoscopic endonasal transsphenoidal surgery is an established technique for the resection of sellar and suprasellar lesions. The approach is technically challenging and has a steep learning curve. Simulation is a growing training tool, allowing the acquisition of technical skills pre-clinically and potentially resulting in a shorter clinical learning curve. We sought validation of the UpSurgeOn Transsphenoidal (TNS) Box for the endoscopic endonasal transsphenoidal approach to the pituitary fossa.

Methods

Novice, intermediate and expert neurosurgeons were recruited from multiple centres. Participants were asked to perform a sphenoidotomy using the TNS model. Face and content validity were evaluated using a post-task questionnaire. Construct validity was assessed through post-hoc blinded scoring of operative videos using a Modified Objective Structured Assessment of Technical Skills (mOSAT) and a Task-Specific Technical Skill scoring system.

Results

Fifteen participants were recruited of which n = 10 (66.6%) were novices and n = 5 (33.3%) were intermediate and expert neurosurgeons. Three intermediate and experts (60%) agreed that the model was realistic. All intermediate and experts (n = 5) strongly agreed or agreed that the TNS model was useful for teaching the endonasal transsphenoidal approach to the pituitary fossa. The consensus-derived mOSAT score was 16/30 (IQR 14-16.75) for novices and 29/30 (IQR 27-29) for intermediate and experts (p < 0.001, Mann-Whitney U). The median Task-Specific Technical Skill score was 10/20 (IQR 8.25-13) for novices and 18/20 (IQR 17.75-19) for intermediate and experts (p < 0.001, Mann-Whitney U). Interrater reliability was 0.949 (CI 0.983-0.853) for OSATS and 0.945 (CI 0.981-0.842) for Task-Specific Technical Skills. Suggested improvements for the model included the addition of neuro-vascular anatomy and arachnoid mater to simulate bleeding vessels and CSF leak, respectively, as well as improvement in materials to reproduce the consistency closer to that of human tissue and bone.

Conclusion

The TNS Box simulation model has demonstrated face, content, and construct validity as a simulator for the endoscopic endonasal transsphenoidal approach. With the steep learning curve associated with endoscopic approaches, this simulation model has the potential as a valuable training tool in neurosurgery with further improvements including advancing simulation materials, dynamic models (e.g., with blood flow) and synergy with complementary technologies (e.g., artificial intelligence and augmented reality).

Evolution in endoscopic endonasal approach for the management of hypothalamic–pituitary region metastasis: A single-institution experience

Introduction

Endonasal endoscopic surgery has changed the treatment perspectives for different lesions of the hypothalamic–pituitary region. The metastases of the hypothalamic–pituitary region represent 0.4% of all intracranial metastatic tumors and account for only 1.8% of surgically managed pituitary lesions. The aim of tshis study is to describe a single-center institutional experience with 13 cases of hypothalamic–pituitary metastasis focused on presurgical workup, the evolution of the surgical technique, and postsurgical management according to our protocols, showing effects on progression-free and overall survival rates for this relatively uncommon location.

Material and Methods

We retrospectively reviewed the whole series of patients that received the endoscopic endonasal approach at the Division of Neurosurgery at the University of Naples “Federico II” undergoing surgery from January 1997 to December 2021. We identified 13 cases whose pathology reports revealed a metastatic lesion. Statistical analysis was performed to determine the Kaplan–Meier survival function and assess for log-rank differences in survival based on gender, surgical treatment, and postoperative therapy (p-value &lt; 0.02*).

Results

The pathology report disclosed lung adenocarcinoma (six cases, 46%), breast adenocarcinoma (two cases, 15.4%), clear cell renal carcinoma (one case, 7%), melanoma (one case, 7%), colorectal adenocarcinoma (one case, 7%), uterine cervix carcinoma (one case, 7%), and follicular thyroid carcinoma (one case, 7%). A standard endoscopic endonasal approach was performed in 10 patients (76.9%), while an extended endonasal procedure was performed in only three cases (23%). Biopsy was the surgical choice in five patients with infiltrative and invasive lesions and a poor performance status (38%), while in the cases where neurovascular decompression was necessary, a subtotal resection was achieved in five patients (38%) and partial resection in three patients (23%). Recovery of visual field defect was observed in six of seven patients with visual loss (85.7%), improvement of oculomotor nerve palsy occurred in four of seven patients with this defect (57.1%), while the impairment of oculomotor palsy was observed in three patients (42.9%). Visual function was stable in the other patients. The median progression-free survival and overall survival were 14 and 18 months, respectively. There were statistically significant differences in PFS and OS in patients who underwent adjuvant radiotherapy (p=0.019 is referred to OS and p=0.017 to PFS, respectively; p-value = 0.02).

Conclusions

The endoscopic endonasal approach is a viable approach for the management of hypothalamic–pituitary metastases as this surgery provides an adequate opportunity to obtain tissue sample and neurovascular decompression, both being crucial for continuing the integrated adjuvant therapy protocols.

Radiological evolution of autograft fat used for skull base reconstruction after transsphenoidal surgery for pituitary adenomas

PURPOSE

Cerebro-spinal fluid leak after transsphenoidal surgery for pituitary adenomas may be prevented by skull base reconstruction with fat autograft. However, graft changes may interfere with the interpretation of postoperative images. Our aim is to describe the radiological evolution of the fat autograft.

METHODS

A retrospective analysis was performed, including patients undergoing a transsphenoidal surgery for pituitary adenomas with a fat autograft for skull base reconstruction. Clinical and radiological data were collected, with assessment of fat autograft and extent of resection. Statistical analysis was performed using Kruskal-Wallis and Wilcoxon signed-rank test while Spearman's Rho was used to analyze the relationship between variables.

RESULTS

Seventy-two patients were included. Macroadenomas were diagnosed in 62 cases (86.1%) and in 21 cases an invasion of the cavernous sinus was described (29%). Gross total resection was achieved in 84.7% of cases. The volume of the fat graft significantly decreased between 3 months and 1 year after surgery (p = 0.01) and between 1 year and the last follow-up (mean 4.63 years, p < 0.01). Fat signal ratio significantly diminished between 3 months and 1 year in unenhanced and enhanced T1-weighted sequences (p = 0.04 and p = 0.02 respectively). Volume reduction was related to the decrease in signal ratio in unenhanced T1 sequences (p = 0.008).

CONCLUSION

Fat resorbs with time: almost 50% of the fat volume is lost during the first year after surgery and 60% is resorbed at 4.6 years. T1-signal, before and after gadolinium injection, also decreases during the first year, probably because of the progressive fibrosis of the graft. This information will contribute to the interpretation of postoperative images.

Pediatric pituitary adenomas are more aggressive, more likely to be hormone producing and are more difficult to cure than adult pituitary adenomas: case series and systematic literature review

PURPOSE

Pediatric pituitary adenomas (pPAs) are uncommon. Thus, their presentation and outcomes after treatment are less well-understood than those of pituitary adenomas in adulthood (aPAs).

METHODS

A retrospective chart review was conducted for all patients who underwent endoscopic endonasal transsphenoidal surgery (EETS) for pPA at NewYork-Presbyterian Hospital/Weill Cornell Medicine (NYP/WCM) from 2005-2020. Eleven patients were identified, and information pertaining to age, sex, adenoma characteristics, procedural details, and outcomes was reviewed. A systematic review of the literature was also performed to compare outcomes of EETS versus microscopic endonasal transsphenoidal surgery (METS) for pPA.

RESULTS

From 2005-2020, 11 patients underwent EETS for pPA at NYP/WCM. Mean age at operation was 14.9 ± 2.7 years, and 5 patients (45.5%) were male. 10 adenomas (90.9%) were hormone-producing. Of the functional adenomas, 8 (80.0%) were PRL-secreting and 2 (20.0%) were GH-secreting. Maximum adenoma diameter (MAD) ranged from 1.2-5.1 cm, with a median of 1.55 cm. Cavernous sinus invasion (CSI) occurred in 2 patients with macroprolactinoma. Gross total resection (GTR) was achieved in 10 (90.9%). Biochemical remission occurred in 5/10 (50.0%). Post-operative complications were documented in 8 cases (72.7%) and included diabetes insipidus, hypopituitarism, sinusitis, weight gain, cerebrospinal fluid leak, meningitis, and hydrocephalus. Systematic literature review of 105 microscopic and 175 endoscopic cases revealed high frequency of hormone-producing tumors (83.6%) and similar rates of GTR (82.4% vs 85.1%) and biochemical cure (75.8% vs 64.3%).

CONCLUSIONS

pPAs are more likely to be hormone producing and may be more aggressive and difficult to cure than aPAs. EETS is an effective treatment, although complication rates may be higher than in adult populations.

Reducing Prediction volatility in the surgical workflow recognition of endoscopic pituitary surgery

Purpose:

Workflow recognition can aid surgeons before an operation when used as a training tool, during an operation by increasing operating room efficiency, and after an operation in the completion of operation notes. Although several methods have been applied to this task, they have been tested on few surgical datasets. Therefore, their generalisability is not well tested, particularly for surgical approaches utilising smaller working spaces which are susceptible to occlusion and necessitate frequent withdrawal of the endoscope. This leads to rapidly changing predictions, which reduces the clinical confidence of the methods, and hence limits their suitability for clinical translation.

Methods:

Firstly, the optimal neural network is found using established methods, using endoscopic pituitary surgery as an exemplar. Then, prediction volatility is formally defined as a new evaluation metric as a proxy for uncertainty, and two temporal smoothing functions are created. The first (modal, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$M_n$$\end{document}Mn) mode-averages over the previous n predictions, and the second (threshold, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T_n$$\end{document}Tn) ensures a class is only changed after being continuously predicted for n predictions. Both functions are independently applied to the predictions of the optimal network.

Results:

The methods are evaluated on a 50-video dataset using fivefold cross-validation, and the optimised evaluation metric is weighted-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_1$$\end{document}F1 score. The optimal model is ResNet-50+LSTM achieving 0.84 in 3-phase classification and 0.74 in 7-step classification. Applying threshold smoothing further improves these results, achieving 0.86 in 3-phase classification, and 0.75 in 7-step classification, while also drastically reducing the prediction volatility.

Conclusion:

The results confirm the established methods generalise to endoscopic pituitary surgery, and show simple temporal smoothing not only reduces prediction volatility, but actively improves performance.

DOLPHIN-UK CollaboratorsAquilinaKristianMallucciConorChariAswinaswin.chari.18@ucl.ac.ukhttp://orcid.org/0000-0002-5187-140XMedirattaSaniyasaniya.mediratta@gmail.comSivakumarGnanamurthyJamesGregJallohIbrahimKitchenJohnKirkmanMatthew A.de LacyPatriciaLeachPaulMagdumShailendra AshokDawesWilliamLoWilliam B., Chari A, DOLPHIN-UK CollaboratorsAquilinaKristianMallucciConorSivakumarGnanamurthyJamesGregJallohIbrahimKitchenJohnKirkmanMatthew A.de LacyPatriciaLeachPaulMagdumShailendra AshokDawesWilliamLoWilliam B.. A standardised protocol for neuro-endoscopic lavage for post-haemorrhagic ventricular dilatation: A Delphi consensus approach

Neuro-endoscopic lavage (NEL) has shown promise as an emerging procedure for intraventricular haemorrhage (IVH) and post-haemorrhagic ventricular dilatation (PHVD). However, there is considerable variation with regard to the indications, objectives, and surgical technique in NEL. There is currently no randomised trial evidence that supports the use of NEL in the context of PHVD. This study aims to form a consensus on technical variations in the indications and procedural steps of NEL. A mixed-methods modified Delphi consensus process was conducted between consultant paediatric neurosurgeons across the UK. Stages involved literature review, survey, focused online consultation, and iterative revisions until > 80% consensus was achieved. Twelve consultant paediatric neurosurgeons from 10 centres participated. A standardised protocol including indications, a 3-phase operative workflow (pre-ventricular, intraventricular, post-ventricular), and post-operative care was agreed upon by 100% of participants. Case- and surgeon-specific variation was considered and included through delineation of mandatory, optional, and not recommended steps. Expert consensus on a standardised protocol for NEL was achieved, delineating the surgical workflow into three phases such as pre-ventricular, intraventricular, and post-ventricular, each consisting of mandatory, optional, and not recommended steps. The work provides a platform for future trials, training, and implementation of NEL.

Artificial Intelligence in Brain Tumour Surgery-An Emerging Paradigm

Artificial intelligence (AI) platforms have the potential to cause a paradigm shift in brain tumour surgery. Brain tumour surgery augmented with AI can result in safer and more effective treatment. In this review article, we explore the current and future role of AI in patients undergoing brain tumour surgery, including aiding diagnosis, optimising the surgical plan, providing support during the operation, and better predicting the prognosis. Finally, we discuss barriers to the successful clinical implementation, the ethical concerns, and we provide our perspective on how the field could be advanced.