Challenges and Opportunities in Awake Craniotomy for Brain Tumor Surgery in Low- and Lower-Middle-Income Countries: A Narrative Review and Perspective.

BACKGROUND: Low-income countries (LICs) and lower-middle-income countries (LMICs) are presented with unique challenges and opportunities when performing awake craniotomy (AC) for brain tumors. These circumstances arise from factors that are financial, infrastructural, educational, personnel, and sociocultural in nature. METHODS: We performed a systematic narrative review of series on AC for intra-axial brain tumors in LICs/LMICs using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, focusing on the challenges and opportunities in these settings. The PubMed, Scopus, and Web of Science databases were searched. RESULTS: After initially identifying 74 studies, inclusion-exclusion criteria were applied, leaving a total of 14 studies included in the review. These involved 409 patients who underwent AC in LICs/LMICs. These series were from India, Ghana, Nigeria, Iran, Pakistan, Morocco, the Philippines, and Egypt. The most common pathology encountered were gliomas (10-70%). Most studies (11/14, 78.5%) reported on their technique of cortical-subcortical mapping. All reported on motor mapping and 8 of these performed language mapping. The most common outcomes reported were seizure and neurologic deficits, and longest follow-up was at 1 year. Challenges noted were lack of equipment and trained personnel, need for validated tests for the local setting, and sociocultural factors. Opportunities identified were volume for training, technique innovation, and international collaboration. CONCLUSIONS: There are numerous challenges and opportunities that arise when performing AC in LICs/LMICs. A collaborative approach toward harnessing the opportunities, and seeking creative solutions to address the challenges, would provide an ideal mechanism toward advancing neurosurgical care and specialty worldwide.

Meningioma recurrence: Time for an online prediction tool?

Background: Meningioma, the most common brain tumor, traditionally considered benign, has a relatively high risk of recurrence over a patient's lifespan. In addition, with the emergence of several clinical, radiological, and molecular variables, it is becoming evident that existing grading criteria, including Simpson's and World Health Organization classification, may not be sufficient or accurate. As web-based tools for widespread accessibility and usage become commonplace, such as those for gene identification or other cancers, it is timely for meningioma care to take advantage of evolving new markers to help advance patient care. Methods: A scoping review of the meningioma literature was undertaken using the MEDLINE and Embase databases. We reviewed original studies and review articles from September 2022 to December 2023 that provided the most updated information on the demographic, clinical, radiographic, histopathological, molecular genetics, and management of meningiomas in the adult population. Results: Our scoping review reveals a large body of meningioma literature that has evaluated the determinants for recurrence and aggressive tumor biology, including older age, female sex, genetic abnormalities such as telomerase reverse transcriptase promoter mutation, CDKN2A deletion, subtotal resection, and higher grade. Despite a large body of evidence on meningiomas, however, we noted a lack of tools to aid the clinician in decision-making. We identified the need for an online, self-updating, and machine-learning-based dynamic model that can incorporate demographic, clinical, radiographic, histopathological, and genetic variables to predict the recurrence risk of meningiomas. Conclusion: Although a challenging endeavor, a recurrence prediction tool for meningioma would provide critical information for the meningioma patient and the clinician making decisions on long-term surveillance and management of meningiomas.

neuroGPT-X: toward a clinic-ready large language model.

OBJECTIVE: The objective was to assess the performance of a context-enriched large language model (LLM) compared with international neurosurgical experts on questions related to the management of vestibular schwannoma. Furthermore, another objective was to develop a chat-based platform incorporating in-text citations, references, and memory to enable accurate, relevant, and reliable information in real time. METHODS: The analysis involved 1) creating a data set through web scraping, 2) developing a chat-based platform called neuroGPT-X, 3) enlisting 8 expert neurosurgeons across international centers to independently create questions (n = 1) and to answer (n = 4) and evaluate responses (n = 3) while blinded, and 4) analyzing the evaluation results on the management of vestibular schwannoma. In the blinded phase, all answers were assessed for accuracy, coherence, relevance, thoroughness, speed, and overall rating. All experts were unblinded and provided their thoughts on the utility and limitations of the tool. In the unblinded phase, all neurosurgeons provided answers to a Likert scale survey and long-answer questions regarding the clinical utility, likelihood of use, and limitations of the tool. The tool was then evaluated on the basis of a set of 103 consensus statements on vestibular schwannoma care from the 8th Quadrennial International Conference on Vestibular Schwannoma. RESULTS: Responses from the naive and context-enriched Generative Pretrained Transformer (GPT) models were consistently rated not significantly different in terms of accuracy, coherence, relevance, thoroughness, and overall performance, and they were often rated significantly higher than expert responses. Both the naive and content-enriched GPT models provided faster responses to the standardized question set than expert neurosurgeon respondents (p < 0.01). The context-enriched GPT model agreed with 98 of the 103 (95%) consensus statements. Of interest, all expert surgeons expressed concerns about the reliability of GPT in accurately addressing the nuances and controversies surrounding the management of vestibular schwannoma. Furthermore, the authors developed neuroGPT-X, a chat-based platform designed to provide point-of-care clinical support and mitigate the limitations of human memory. neuroGPT-X incorporates features such as in-text citations and references to enable accurate, relevant, and reliable information in real time. CONCLUSIONS: The present study, with its subspecialist-level performance in generating written responses to complex neurosurgical problems for which evidence-based consensus for management is lacking, suggests that context-enriched LLMs show promise as a point-of-care medical resource. The authors anticipate that this work will be a springboard for expansion into more medical specialties, incorporating evidence-based clinical information and developing expert-level dialogue surrounding LLMs in healthcare.

Corrigendum: Grade 3 Meningioma Survival and Recurrence Outcomes in an International Multicenter Cohort.

[This corrects the article DOI: 10.1055/s-0044-1779888.].

Ruptured pial-pial collateral aneurysm associated with left internal carotid artery occlusion: nuances of surgical management. Illustrative case.

BACKGROUND: Carotid occlusion often leads to the formation of a collateral network. On rare occasions, due to hemodynamic influence, aneurysms can occur. Here, the authors describe a 69-year-old male presenting with intracerebral hemorrhage secondary to a ruptured aneurysm within such a network. OBSERVATIONS: The patient presented to the emergency department with an altered level of consciousness. Imaging showed a left temporal lobe hemorrhage extending into the ventricle, subdural hematoma, and evidence of contrast extravasation. Digital subtraction angiography revealed an occluded left internal carotid artery with the left middle cerebral artery territory reconstituted by flow through an external carotid artery-internal carotid artery anastomosis. The latter was formed by the superficial temporal artery-superior orbital artery, as well as pial-pial collaterals from the posterior temporal artery. Notably, a 4-mm aneurysm arising from the pial-pial collateral network was identified. Surgical intervention involved a left temporal craniectomy and aneurysm excision, with special attention paid to preserving the anastomotic flow through the superficial temporal artery. LESSONS: This case underscores the importance of recognizing and preserving collateral vascular pathways in cases of carotid occlusion with an associated aneurysm. It emphasizes the necessary balance between managing aneurysm risk and maintaining cerebral perfusion, highlighting the need for careful preoperative planning and intraoperative caution.

Grade 3 meningioma survival and recurrence outcomes in an international multicenter cohort.

OBJECTIVE: Grade 3 meningioma represents a rare meningioma subtype, for which limited natural history data are available. The objective of this study was to identify demographics and pathologic characteristics, clinical and functional status outcomes, and prognostic factors in an international cohort of grade 3 meningioma patients. METHODS: Clinical and histopathological data were collected for patients treated at 7 sites across North America and Europe between 1991 and 2022. RESULTS: A total of 103 patients (54% female, median age 65 [IQR 52, 72] years) were included. Sixty-seven (65%) patients had de novo grade 3 lesions, whereas 29 (28%) had malignant transformations of lower-grade meningiomas. All patients underwent initial resection of their tumor. Patients were followed for a median of 46 (IQR 24, 108) months, during which time there were 65 (73%) recurrences and 50 (49%) deaths. The 5-year overall survival (OS) and progression-free survival (PFS) rates were 66% (95% CI 56%-77%) and 37% (95% CI 28%-48%), respectively. Age ≥ 65 years and male sex were independent predictors of worse OS and PFS in multivariate regression analysis, while postoperative radiotherapy was independently associated with improved OS. Karnofsky Performance Status (KPS) remained stable relative to baseline over 5 years postdiagnosis among participants who were alive at the end of the follow-up period. CONCLUSIONS: This large multicenter study provides insight into the longitudinal outcomes of grade 3 meningioma, with respect to recurrence, survival, and functional status. This study affirms the survival benefit conferred by radiotherapy in this population and suggests good functional status outcomes for patients surviving to 5 years postoperatively.

Force Profile as Surgeon-Specific Signature.

Objective: To investigate the notion that a surgeon's force profile can be the signature of their identity and performance. Summary background data: Surgeon performance in the operating room is an understudied topic. The advent of deep learning methods paired with a sensorized surgical device presents an opportunity to incorporate quantitative insight into surgical performance and processes. Using a device called the SmartForceps System and through automated analytics, we have previously reported surgeon force profile, surgical skill, and task classification. However, an investigation of whether an individual surgeon can be identified by surgical technique has yet to be studied. Methods: In this study, we investigate multiple neural network architectures to identify the surgeon associated with their time-series tool-tissue forces using bipolar forceps data. The surgeon associated with each 10-second window of force data was labeled, and the data were randomly split into 80% for model training and validation (10% validation) and 20% for testing. Data imbalance was mitigated through subsampling from more populated classes with a random size adjustment based on 0.1% of sample counts in the respective class. An exploratory analysis of force segments was performed to investigate underlying patterns differentiating individual surgical techniques. Results: In a dataset of 2819 ten-second time segments from 89 neurosurgical cases, the best-performing model achieved a micro-average area under the curve of 0.97, a testing F1-score of 0.82, a sensitivity of 82%, and a precision of 82%. This model was a time-series ResNet model to extract features from the time-series data followed by a linearized output into the XGBoost algorithm. Furthermore, we found that convolutional neural networks outperformed long short-term memory networks in performance and speed. Using a weighted average approach, an ensemble model was able to identify an expert surgeon with 83.8% accuracy using a validation dataset. Conclusions: Our results demonstrate that each surgeon has a unique force profile amenable to identification using deep learning methods. We anticipate our models will enable a quantitative framework to provide bespoke feedback to surgeons and to track their skill progression longitudinally. Furthermore, the ability to recognize individual surgeons introduces the mechanism of correlating outcome to surgeon performance.

Tissue Acceleration as a Novel Metric for Surgical Performance During Carotid Endarterectomy.

BACKGROUND AND OBJECTIVES: Gentle tissue handling to avoid excessive motion of affected fragile vessels during surgical dissection is essential for both surgeon proficiency and patient safety during carotid endarterectomy (CEA). However, a void remains in the quantification of these aspects during surgery. The video-based measurement of tissue acceleration is presented as a novel metric for the objective assessment of surgical performance. This study aimed to evaluate whether such metrics correlate with both surgeons' skill proficiency and adverse events during CEA. METHODS: In a retrospective study including 117 patients who underwent CEA, acceleration of the carotid artery was measured during exposure through a video-based analysis. Tissue acceleration values and threshold violation error frequencies were analyzed and compared among the surgeon groups with different surgical experience (3 groups: novice , intermediate , and expert ). Multiple patient-related variables, surgeon groups, and video-based surgical performance parameters were compared between the patients with and without adverse events during CEA. RESULTS: Eleven patients (9.4%) experienced adverse events after CEA, and the rate of adverse events significantly correlated with the surgeon group. The mean maximum tissue acceleration and number of errors during surgical tasks significantly decreased from novice, to intermediate, to expert surgeons, and stepwise discriminant analysis showed that the combined use of surgical performance factors could accurately discriminate between surgeon groups. The multivariate logistic regression analysis revealed that the number of errors and vulnerable carotid plaques were associated with adverse events. CONCLUSION: Tissue acceleration profiles can be a novel metric for the objective assessment of surgical performance and the prediction of adverse events during surgery. Thus, this concept can be introduced into futuristic computer-aided surgeries for both surgical education and patient safety.

Tool-tissue force segmentation and pattern recognition for evaluating neurosurgical performance.

Surgical data quantification and comprehension expose subtle patterns in tasks and performance. Enabling surgical devices with artificial intelligence provides surgeons with personalized and objective performance evaluation: a virtual surgical assist. Here we present machine learning models developed for analyzing surgical finesse using tool-tissue interaction force data in surgical dissection obtained from a sensorized bipolar forceps. Data modeling was performed using 50 neurosurgery procedures that involved elective surgical treatment for various intracranial pathologies. The data collection was conducted by 13 surgeons of varying experience levels using sensorized bipolar forceps, SmartForceps System. The machine learning algorithm constituted design and implementation for three primary purposes, i.e., force profile segmentation for obtaining active periods of tool utilization using T-U-Net, surgical skill classification into Expert and Novice, and surgical task recognition into two primary categories of Coagulation versus non-Coagulation using FTFIT deep learning architectures. The final report to surgeon was a dashboard containing recognized segments of force application categorized into skill and task classes along with performance metrics charts compared to expert level surgeons. Operating room data recording of > 161 h containing approximately 3.6 K periods of tool operation was utilized. The modeling resulted in Weighted F1-score = 0.95 and AUC = 0.99 for force profile segmentation using T-U-Net, Weighted F1-score = 0.71 and AUC = 0.81 for surgical skill classification, and Weighted F1-score = 0.82 and AUC = 0.89 for surgical task recognition using a subset of hand-crafted features augmented to FTFIT neural network. This study delivers a novel machine learning module in a cloud, enabling an end-to-end platform for intraoperative surgical performance monitoring and evaluation. Accessed through a secure application for professional connectivity, a paradigm for data-driven learning is established.

Ultrasound Elastography in Neurosurgery: Current Applications and Future Perspectives.

BACKGROUND: Similar to clinical palpation, Ultrasound elastography (USE) helps distinguish between tissues by providing information on their elasticity. While it has been widely explored and has been applied to many body organs, USE has not been studied as extensively for application in neurosurgery. The current systematic review was performed to identify articles related to the use of interoperative USE in neurosurgery. METHODS: Search included MEDLINE(R) database. Only original peer-reviewed full-text articles were included. No language or publication year restrictions were imposed. Two independent reviewers assessed the search results for relevance. The identified articles were screened by title, abstract, and full-text review. RESULTS: Seventeen articles were included in the qualitative analysis and 13 articles were related to oncology, epilepsy (n = 3), and spine (n = 1). In oncology, USE was found useful in defining tumor stiffness, aiding surgical planning, detecting residual tumors, discriminating between tumor and brain tissue, and differentiating between different tumors. In epilepsy, USE could improve the detection of epileptogenic foci, thereby enhancing the prospect of complete and safe resection. The application in spinal surgery was limited to demonstrating that a compressed spinal cord is stiffer than the decompressed one. CONCLUSIONS: USE was found to be a safe, quick, portable, and economic tool that was a useful intraoperative adjunct to provide information corresponding to a variety of neurosurgical diseases, at different stages of surgery. This review describes the current intraoperative neurosurgical applications of USE, the concept of elasticity, and different USE modalities as well as the technical challenges, limitations, and possible future implications.

Survival After Resection of Newly-Diagnosed Intracranial Grade II Ependymomas: An Initial Multicenter Analysis and the Logistics of Intraoperative Magnetic Resonance Imaging.

OBJECTIVE: To identify factors, including the use of intraoperative magnetic resonance imaging (iMRI), impacting overall survival (OS) and progression-free survival (PFS) after resections of newly diagnosed intracranial grade II ependymomas performed across 4 different institutions. METHODS: Analyses of a multicenter mixed retrospective/prospective database assessed the impact of patient, treatment, and tumor characteristics on OS and PFS. iMRI workflow and logistics were also outlined. RESULTS: Forty-three patients were identified (mean age 25.4 years, mean follow-up 52.8 months). The mean OS was 52.8 ± 44.7 months. Univariate analyses failed to identify prognostic factors associated with OS, likely due to relatively shorter follow-up time for this less aggressive glioma subtype. The mean PFS was 43.7 ± 39.8 months. Multivariate analyses demonstrated that gross-total resection was associated with prolonged PFS compared to both subtotal resection (STR) (P = 0.005) and near-total resection (P = 0.01). Infratentorial location was associated with improved PFS compared to supratentorial location (P = 0.04). Log-rank analyses of Kaplan-Meier survival curves showed that increasing extent of resection (EOR) led to improved OS specifically for supratentorial tumors (P = 0.02) and improved PFS for all tumors (P < 0.001). Thirty cases (69.8%) utilized iMRI, of which 12 (27.9%) involved additional resection after iMRI. Of these, 8/12 (66.7%) resulted in gross-total resection, while 2/12 (16.7%) were near-total resection and 2/12 (16.7%) were subtotal resection. iMRI was not an independent prognosticator of PFS (P = 0.72). CONCLUSIONS: Greater EOR and infratentorial location were associated with increased PFS for grade II ependymomas. Greater EOR was associated with longer OS only for supratentorial tumors. A longer follow-up is needed to establish prognostic factors for this cohort, including use of iMRI.

Tool-Tissue Forces in Hemangioblastoma Surgery.

OBJECTIVE: Surgical resection of intracranial hemangioblastoma poses technical challenges that may be difficult to impart to trainees. Here, we introduce knowledge of tool-tissue forces in Newton (N), observed during hemangioblastoma surgery. METHODS: Seven surgeons (2 groups: trainees and mentor), with mentor (n = 1) and trainees (n = 6, PGY 1-6 including clinical fellowship), participated in 6 intracranial hemangioblastoma surgeries. Using sensorized bipolar forceps, we evaluated tool-tissue force profiles of 5 predetermined surgical tasks: 1) dissection, 2) coagulation, 3) retracting, 4) pulling, and 5) manipulating. Force profile for each trial included force duration, average, maximum, minimum, range, standard deviation (SD), and correlation coefficient. Force errors including unsuccessful trial bleeding or incomplete were compared between surgeons and with successful trials. RESULTS: Force data from 718 trials were collected. The mean (standard deviation) of force used in all surgical tasks and across all surgical levels was 0.20 ± 0.17 N. The forces exerted by trainee surgeons were significantly lower than those of the mentor (0.15 vs. 0.24; P < 0.0001). A total of 18 (4.5%) trials were unsuccessful, 4 of them being unsuccessful trial-bleeding and the rest, unsuccessful trial-incomplete. The force in unsuccessful trial-bleeding was higher than successful trials (0.3 [0.09] vs. 0.17 [0.11]; P = 0.0401). Toward the end of surgery, higher force was observed (0.17 vs. 0.20; P < 0.0001). CONCLUSIONS: The quantification of tool-tissue forces during hemangioblastoma surgery with feedback to the surgeon, could well enhance surgical training and allow avoidance of bleeding associated with high force error.

A data-driven performance dashboard for surgical dissection.

Surgical error and resulting complication have significant patient and economic consequences. Inappropriate exertion of tool-tissue force is a common variable for such error, that can be objectively monitored by sensorized tools. The rich digital output establishes a powerful skill assessment and sharing platform for surgical performance and training. Here we present SmartForceps data app incorporating an Expert Room environment for tracking and analysing the objective performance and surgical finesse through multiple interfaces specific for surgeons and data scientists. The app is enriched by incoming geospatial information, data distribution for engineered features, performance dashboard compared to expert surgeon, and interactive skill prediction and task recognition tools to develop artificial intelligence models. The study launches the concept of democratizing surgical data through a connectivity interface between surgeons with a broad and deep capability of geographic reach through mobile devices with highly interactive infographics and tools for performance monitoring, comparison, and improvement.

Interhemispheric arachnoid cyst.

BACKGROUND: Interhemispheric arachnoid cysts are uncommon and typically associated with other midline neurodevelopmental disorders, such as complete or partial agenesis of the corpus callosum. CASE DESCRIPTION: We report a case of a 27-year-old woman with worsening headache, memory deficit, and radiological progression of an interhemispheric arachnoid cyst. The treatment consisted of craniotomy for interhemispheric cyst fenestration into both the interhemispheric cistern and lateral ventricle. The postoperative course was unremarkable, with considerable clinical improvement and significant reduction in cyst size. CONCLUSION: We successfully treat a patient with an enlarging arachnoid cyst and associated progressive symptoms with microsurgical fenestration.

Findings Predictive of Poor Outcome in Grade 5 Subarachnoid Hemorrhage: A Cohort Study.

BACKGROUND: Most patients with World Federation of Neurological Surgeons (WFNS) grade 5 subarachnoid hemorrhage (SAH) have poor outcomes. Accurate assessment of prognosis is important for treatment decisions and conversations with families regarding goals of care. Unjustified pessimism may lead to "self-fulfilling prophecy," where withdrawal of life-sustaining measures (WLSM) is invariably followed by death. METHODS: We performed a cohort study involving consecutive patients with WFNS grade 5 SAH to identify variables with >= 90% and >= 95% positive predictive value (PPV) for poor outcome (1-year modified Rankin Score >= 4), as well as findings predictive of WLSM. RESULTS: Of 140 patients, 38 (27%) had favorable outcomes. Predictors with >= 95% PPV for poor outcome included unconfounded 72-hour Glasgow Coma Scale motor score <= 4, absence of >= 1 pupillary light reflex (PLR) at 24 hours, and intraventricular hemorrhage (IVH) score of >= 20 (volume >= 54.6 ml). Intracerebral hemorrhage (ICH) volume >= 53 ml had PPV of 92%. Variables associated with WLSM decisions included a poor motor score (p < 0.0001) and radiographic evidence of infarction (p = 0.02). CONCLUSIONS: We identified several early predictors with high PPV for poor outcome. Of these, lack of improvement in motor score during the initial 72 hours had the greatest potential for confounding from "self-fulfilling prophecy." Absence of PLR at 24 hours, IVH score >= 20, and ICH volume >= 53 ml predicted poor outcome without a statistically significant effect on WLSM decisions. More research is needed to validate prognostic variables in grade 5 SAH, especially among patients who do not undergo WLSM.

Intraoperative MRI for newly diagnosed supratentorial glioblastoma: a multicenter-registry comparative study to conventional surgery.

OBJECTIVE: Intraoperative MRI (iMRI) is used in the surgical treatment of glioblastoma, with uncertain effects on outcomes. The authors evaluated the impact of iMRI on extent of resection (EOR) and overall survival (OS) while controlling for other known and suspected predictors. METHODS: A multicenter retrospective cohort of 640 adult patients with newly diagnosed supratentorial glioblastoma who underwent resection was evaluated. iMRI was performed in 332/640 cases (51.9%). Reviews of MRI features and tumor volumetric analysis were performed on a subsample of cases (n = 286; 110 non-iMRI, 176 iMRI) from a single institution. RESULTS: The median age was 60.0 years (mean 58.5 years, range 20.5-86.3 years). The median OS was 17.0 months (95% CI 15.6-18.4 months). Gross-total resection (GTR) was achieved in 403/640 cases (63.0%). Kaplan-Meier analysis of 286 cases with volumetric analysis for EOR (grouped into 100%, 95%-99%, 80%-94%, and 50%-79%) showed longer OS for 100% EOR compared to all other groups (p < 0.01). Additional resection after iMRI was performed in 104/122 cases (85.2%) with initial subtotal resection (STR), leading to a 6.3% mean increase in EOR and a 2.2-cm3 mean decrease in tumor volume. For iMRI cases with volumetric analysis, the GTR rate increased from 54/176 (30.7%) on iMRI to 126/176 (71.5%) postoperatively. The EOR was significantly higher in the iMRI group for intended GTR and STR groups (p = 0.02 and p < 0.01, respectively). Predictors of GTR on multivariate logistic regression included iMRI use and intended GTR. Predictors of shorter OS on multivariate Cox regression included older age, STR, isocitrate dehydrogenase 1 (IDH1) wild type, no O6-methylguanine DNA methyltransferase (MGMT) methylation, and no Stupp therapy. iMRI was a significant predictor of OS on univariate (HR 0.82, 95% CI 0.69-0.98; p = 0.03) but not multivariate analyses. Use of iMRI was not associated with an increased rate of new permanent neurological deficits. CONCLUSIONS: GTR increased OS for patients with newly diagnosed glioblastoma after adjusting for other prognostic factors. iMRI increased EOR and GTR rate and was a significant predictor of GTR on multivariate analysis; however, iMRI was not an independent predictor of OS. Additional supporting evidence is needed to determine the clinical benefit of iMRI in the management of glioblastoma.

Using Histopathology to Assess the Reliability of Intraoperative Magnetic Resonance Imaging in Guiding Additional Brain Tumor Resection: A Multicenter Study.

BACKGROUND: Intraoperative magnetic resonance imaging (iMRI) is a powerful tool for guiding brain tumor resections, provided that it accurately discerns residual tumor. OBJECTIVE: To use histopathology to assess how reliably iMRI may discern additional tumor for a variety of tumor types, independent of the indications for iMRI. METHODS: A multicenter database was used to calculate the odds of additional resection during the same surgical session for grade I to IV gliomas and pituitary adenomas. The reliability of iMRI for identifying residual tumor was assessed using histopathology of tissue resected after iMRI. RESULTS: Gliomas (904/1517 cases, 59.6%) were more likely than pituitary adenomas (176/515, 34.2%) to receive additional resection after iMRI (P < .001), but these tumors were equally likely to have additional tissue sent for histopathology (398/904, 44.4% vs 66/176, 37.5%; P = .11). Tissue samples were available for resections after iMRI for 464 cases, with 415 (89.4%) positive for tumor. Additional resections after iMRI for gliomas (361/398, 90.7%) were more likely to yield additional tumor compared to pituitary adenomas (54/66, 81.8%) (P = .03). There were no significant differences in resection after iMRI yielding histopathologically positive tumor between grade I (58/65 cases, 89.2%; referent), grade II (82/92, 89.1%) (P = .98), grade III (72/81, 88.9%) (P = .95), or grade IV gliomas (149/160, 93.1%) (P = .33). Additional resection for previously resected tumors (122/135 cases, 90.4%) was equally likely to yield histopathologically confirmed tumor compared to newly-diagnosed tumors (293/329, 89.0%) (P = .83). CONCLUSION: Histopathological analysis of tissue resected after use of iMRI for grade I to IV gliomas and pituitary adenomas demonstrates that iMRI is highly reliable for identifying residual tumor.

Data analytics interrogates robotic surgical performance using a microsurgery-specific haptic device.

OBJECTIVES: With the increase in robot-assisted cases, recording the quantifiable dexterity of surgeons is essential for proficiency evaluations. The present study employs sensor-based kinematics and recorded surgeon experience for evaluating a new haptic device. METHODS: Thirty surgeons performed a task simulating micromanipulation with neuroArmPLUSHD and two commercially available hand-controllers. The surgical performance was evaluated based on subjective measures obtained from survey and objective features derived from the sensors. Statistical analyses were performed to assess the hand-controllers and regression analysis was used to identify the key features and develop a machine learning model for surgical skill assessment. FINDINGS: MANCOVA tests on objective features demonstrated significance (α = 0.05) for time (p = 0.02), errors (p = 0.01), distance (p = 0.03), clutch incidents (p = 0.03), and forces (p = 0.00). The majority of metrics were in favor of neuroArmPLUSHD. The surgeons found it smoother, more comfortable, less tiring, and easier to maneuver with more realistic force feedback. The ensemble machine learning model trained with 5-fold cross-validation showed an accuracy (SD) of 0.78 (0.15) in surgeon skill classification. CONCLUSIONS: This study validates the importance of incorporating a superior haptic device in telerobotic surgery for standardization of surgical education and patient care.