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6.
J Clin Neurosci ; 95: 55-62, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34929652

RESUMO

Virtual reality (VR) technology had its earliest developments in the 1970s in the U.S. Air Force and has since evolved into a budding area of scientific research with many practical medical purposes. VR shows a high potential to benefit to learners and trainees and improve surgery through enhanced preoperative planning and efficiency in the operating room. Neurosurgery is a field of medicine in which VR has been accepted early on as a useful and promising tool for neuro-navigation planning. Through recent technological developments, VR further increased its level of immersion, accessibility and intuitive use for surgeons and students and now reveals a therapeutic potential for patients. In this paper, we systematically reviewed the neurosurgery literature regarding the use of VR as an assistance for surgery or a tool centered on patients' care. A literature search conducted according to PRISMA guidelines resulted in the screening of 125 abstracts and final inclusion of 100 original publications reviewed. The review shows that neurosurgeons are now relatively familiar with VR technologies (N = 95 articles) for their training and practice. VR technologies are useful for education, pain management and rehabilitation in neurosurgical patients. Nevertheless, the current patient-oriented use of VR remains limited (N = 5 articles). Successful surgery does not only depend on the surgeon's skills and preparation, but also on patients' education, comfort, empowerment and care. Therefore further clinical research is needed to promote the direct use of VR technologies by patients in neurosurgery.


Assuntos
Neurocirurgia , Realidade Virtual , Humanos , Neurocirurgiões , Procedimentos Neurocirúrgicos
7.
Acta Neurochir Suppl ; 134: 75-78, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34862530

RESUMO

There is an increasing interest in using prediction models to forecast clinical outcomes within the fields of neurosurgery and clinical neuroscience. The present chapter outlines the foundations of Bayesian learning and introduces Bayes theorem and its use in machine learning methodology. The use of Bayesian networks to structure and define associations between outcome predictors and final outcomes is highlighted and Naïve Bayes classifiers are outlined for use in predicting neurosurgical outcomes, where the understanding of underlying causes is less important. The present work aims to orient researchers in Bayesian machine learning methods and when and how to use them. When used correctly, these tools have the potential to improve the understanding of factors influencing neurosurgical outcomes, aid in structuring the relationships between them, and provide reliable machine learning classification models for predicting neurosurgical outcomes.


Assuntos
Algoritmos , Neurocirurgia , Teorema de Bayes , Causalidade , Aprendizado de Máquina
8.
Acta Neurochir Suppl ; 134: 115-118, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34862535

RESUMO

Decision curve analysis is an increasingly popular method to assess the impact of a prediction model on medical decision making. The analysis provides a graphical summary. A basic understanding of a decision curve is needed to interpret these graphics. This short introduction addresses the common features of a decision curve. Furthermore, using a glioblastoma patient set provided by the Machine Intelligence in Clinical Neuroscience Lab from the Department of Neurosurgery and Clinical Neuroscience Center, University Hospital Zurich a decision curve is plotted for two prediction models. The corresponding R code is provided.


Assuntos
Modelos Estatísticos , Neurocirurgia , Tomada de Decisão Clínica , Humanos , Prognóstico , Curva ROC
9.
Acta Neurochir Suppl ; 134: 245-250, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34862547

RESUMO

The history of machine learning in neurosurgery spans three decades and continues to develop at a rapid pace. The earliest applications of machine learning within neurosurgery were first published in the 1990s as researchers began developing artificial neural networks to analyze structured datasets and supervised tasks. By the turn of the millennium, machine learning had evolved beyond proof-of-concept; algorithms had success detecting tumors in unstructured clinical imaging, and unsupervised learning showed promise for tumor segmentation. Throughout the 2000s, the role of machine learning in neurosurgery was further refined. Well-trained models began to consistently best expert clinicians at brain tumor diagnosis. Additionally, the digitization of the healthcare industry provided ample data for analysis, both structured and unstructured. By the 2010s, the use of machine learning within neurosurgery had exploded. The rapid deployment of an exciting new toolset also led to the growing realization that it may offer marginal benefit at best over conventional logistical regression models for analyzing tabular datasets. Additionally, the widespread adoption of machine learning in neurosurgical clinical practice continues to lag until additional validation can ensure generalizability. Many exciting contemporary applications nonetheless continue to demonstrate the unprecedented potential of machine learning to revolutionize neurosurgery when applied to appropriate clinical challenges.


Assuntos
Neurocirurgia , Algoritmos , Aprendizado de Máquina , Redes Neurais de Computação , Procedimentos Neurocirúrgicos
10.
Acta Neurochir Suppl ; 134: 271-276, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34862551

RESUMO

The clinical neurosciences have historically been at the forefront of innovation, often incorporating the newest research methods into practice. This chapter will explore the adoption, implementation, and refinement of big data and predictive modeling using machine learning within neurosurgery. Initial development of national databases arose from surgeons aiming to improve outcome predictions for patients with traumatic brain injury in the 1960s. In the following decades, other surgical specialties began building databases that left a lasting impact on the current national neurosurgical databases, particularly in spine surgery. Significant contributions to the literature have been made as a result of the numerous registries today, leading to broad quality improvements for neurosurgical patients. Important limitations of large databases do exist, including lack of standardized reporting and challenges in data extraction from medical records. New vistas will include the use of metadata to track human function, performance, and pain in a real-time manner to augment the reliance on traditional patient-reported outcome measures (PROMs). Overall, big data has demonstrated significant utility within neurosurgical research and machine learning-powered analyses have highlighted several promising areas of interest for future exploration.


Assuntos
Neurociências , Neurocirurgia , Big Data , Humanos , Procedimentos Neurocirúrgicos , Sistema de Registros
11.
Acta Neurochir Suppl ; 134: 291-301, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34862553

RESUMO

Machine learning applications in neurosurgery are increasingly reported for diverse tasks such as faster and more accurate preoperative diagnosis, enhanced lesion characterization, as well as surgical outcome, complications and healthcare cost prediction. Even though the pertinent literature in pituitary surgery is less extensive with respect to other neurosurgical diseases, past research attempted to answer clinically relevant questions to better assist surgeons and clinicians. In the present chapter we review reported ML applications in pituitary surgery including differential diagnosis, preoperative lesion characterization (immunohistochemistry, cavernous sinus invasion, tumor consistency), surgical outcome and complication predictions (gross total resection, tumor recurrence, and endocrinological remission, cerebrospinal fluid leak, postoperative hyponatremia). Moreover, we briefly discuss from a practical standpoint the current barriers to clinical translation of machine learning research. On the topic of pituitary surgery, published reports can be considered mostly preliminary, requiring larger training populations and strong external validation. Thoughtful selection of clinically relevant outcomes of interest and transversal application of model development pipeline-together with accurate methodological planning and multicenter collaborations-have the potential to overcome current limitations and ultimately provide additional tools for more informed patient management.


Assuntos
Neurocirurgia , Neoplasias Hipofisárias , Humanos , Aprendizado de Máquina , Estudos Multicêntricos como Assunto , Recidiva Local de Neoplasia , Procedimentos Neurocirúrgicos , Neoplasias Hipofisárias/cirurgia , Resultado do Tratamento
12.
13.
Acta Neurochir Suppl ; 134: 101-108, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34862533

RESUMO

The use of predictive models within neurosurgery is increasing and many models described in published journal articles are made available to readers in formats such as nomograms and online calculators. The present chapter details a step-by-step methodology with accompanying R code that may be used to implement models both in the form of traditional nomograms and as open-access, online calculators through RStudio's Shinyapps. The chapter assumes a basic understanding of predictive modeling in R and utilizes open-access files created by the Machine Intelligence in Clinical Neuroscience (MICN) Lab (Department of Neurosurgery and the Clinical Neuroscience Center of the University Hospital Zurich). When implemented correctly, tools such as nomograms and predictive calculators have the potential to improve user understanding of the underlying statistical models, facilitate broader adoption, and to streamline the eventual use of such models in clinical settings.


Assuntos
Neurocirurgia , Nomogramas , Humanos , Neurocirurgia/tendências
14.
Neurosurg Clin N Am ; 33(1): 1-5, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34801134

RESUMO

The developing field of syndromic neurosurgery has significant challenges and opportunities in quality and safety. Quality care must be safe, effective, patient-centered, timely, efficient, and equitable; the Donabedian model focused on system structures, processes, and outcomes is a helpful framework to guide improvement in these areas. Ultimately, a successful syndromic neurosurgery program will bring together an interested multidisciplinary team of experts who will grow care through open communication and steady improvement efforts.


Assuntos
Neurocirurgia , Comunicação , Humanos , Melhoria de Qualidade
15.
Proc Inst Mech Eng H ; 236(1): 84-93, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34423707

RESUMO

Bone grinding is used to remove the skull bone and access tumors through the nasal passage during cranial base neurosurgery. The generated heat of the spherical diamond tool propagates and could damage the nerves or coagulate the arteries blood. Little is known about the non-Fourier behavior of heat propagation during bone grinding. Therefore, this study develops an analytical model of the hyperbolic Pennes bioheat transfer equation (HPBTE) to calculate the three-dimensional temperature and necrosis in the grinding region. In vitro experimental investigations were carried out, and the contact zone temperature was measured using an infrared thermography system to validate the proposed thermal model. The results demonstrate that the HPBTE provides more reliable temperature evaluation and thermal damage than Fourier or parabolic heat transfer equation (PHTE). Due to the low thermal diffusivity of the bone, the lower grinding feed rate leads to higher temperature amplitude and a smaller radius of the affected zone in the surface and depth of the bone. Also, the intensity of bone necrosis decreases with the increase of the feed rate, and the shape of the damage zone becomes stretched. This analytical model can assess the potential risk of the surgery before clinical trials. Also, it could be used for comparing the different operating conditions to minimize bone necrosis and improve the control process in neurosurgeries.


Assuntos
Neurocirurgia , Temperatura Alta , Modelos Biológicos , Procedimentos Neurocirúrgicos , Base do Crânio/cirurgia , Temperatura
16.
Zh Vopr Neirokhir Im N N Burdenko ; 85(6): 131-134, 2021.
Artigo em Russo | MEDLINE | ID: mdl-34951770

RESUMO

The authors claim four milestones of V.M. Ugriumov's career - time spent twice in Moscow, Saratov, and Leningrad. In Moscow, V.M. Ugriumov evolved as an N.N. Burdenko disciple and later as deputy director of Burdenko Neurosurgical Institute. Ugriumov's life and career in Saratov was the least studied part of his biography, and the authors used archive documents of various origins to investigate and describe them. As a result, the new scope of text and photo files was introduced into the scholarly discourse. It was in Saratov where V.M. Ugriumov designed his original neurosurgery studies, laid the groundwork for the development of Saratov neurosurgery school, and brought his management and teaching talents to light. Later, in Leningrad, Professor V.M. Ugriumov proved to be a remarkable neurosurgeon, physiologist, science, and healthcare manager.


Assuntos
Aniversários e Eventos Especiais , Neurocirurgia , Academias e Institutos , História do Século XX , Humanos , Moscou , Procedimentos Neurocirúrgicos
18.
BMC Res Notes ; 14(1): 434, 2021 Nov 27.
Artigo em Inglês | MEDLINE | ID: mdl-34838152

RESUMO

OBJECTIVE: Colloid solutions are commonly used to maintain perioperative fluid homeostasis. In regard to perioperative infant-centered care, data about the impact of colloids are rare. New data suggest a possible positive effect of hydroxyethyl starch (HES) concerning blood brain barrier. Therefore we conduct a retrospective single center study of children scheduled for neurosurgery, age < five with a blood loss > 10% of body blood volume, receiving either 6% HES 130/0.4 or 5% human albumin (HA). RESULTS: Out of 913 patients, 86 were included (HES = 30; HA = 56). Compared to HES [16.4 ± 9.2 ml/kg body weight (mean ± SD)] HA group received more colloid volume (25.7 ± 11.3), which had more blood loss [HA 54.8 ± 45.0; HES 30.5 ± 30.0 (%) estimated blood volume] and higher fluid balances. Fibrinogen was decreased and activated partial thromboplastin time was elevated in HA group. Urinary output, creatinine and urea levels did not differ between the two groups. Serum calcium, total protein levels were lower in HES group. HA treated infants tended to have shorter ICU and hospital stays. We conclude that none of the investigated colloid solutions were without leverage to infants. Consequently randomized controlled trials about perioperative goal-directed fluid replacement of children undergoing (neuro)-surgery with major blood loss are needed.


Assuntos
Neurocirurgia , Albumina Sérica Humana , Criança , Hidratação , Humanos , Derivados de Hidroxietil Amido , Lactente , Substitutos do Plasma/uso terapêutico , Estudos Retrospectivos
19.
Scand J Trauma Resusc Emerg Med ; 29(1): 158, 2021 Nov 02.
Artigo em Inglês | MEDLINE | ID: mdl-34727955

RESUMO

BACKGROUND: We leveraged the data of the international CREACTIVE consortium to investigate whether the outcome of traumatic brain injury (TBI) patients admitted to intensive care units (ICU) in hospitals without on-site neurosurgical capabilities (no-NSH) would differ had the same patients been admitted to ICUs in hospitals with neurosurgical capabilities (NSH). METHODS: The CREACTIVE observational study enrolled more than 8000 patients from 83 ICUs. Adult TBI patients admitted to no-NSH ICUs within 48 h of trauma were propensity-score matched 1:3 with patients admitted to NSH ICUs. The primary outcome was the 6-month extended Glasgow Outcome Scale (GOS-E), while secondary outcomes were ICU and hospital mortality. RESULTS: A total of 232 patients, less than 5% of the eligible cohort, were admitted to no-NSH ICUs. Each of them was matched to 3 NSH patients, leading to a study sample of 928 TBI patients where the no-NSH and NSH groups were well-balanced with respect to all of the variables included into the propensity score. Patients admitted to no-NSH ICUs experienced significantly higher ICU and in-hospital mortality. Compared to the matched NSH ICU admissions, their 6-month GOS-E scores showed a significantly higher prevalence of upper good recovery for cases with mild TBI and low expected mortality risk at admission, along with a progressively higher incidence of poor outcomes with increased TBI severity and mortality risk. CONCLUSIONS: In our study, centralization of TBI patients significantly impacted short- and long-term outcomes. For TBI patients admitted to no-NSH centers, our results suggest that the least critically ill can effectively be managed in centers without neurosurgical capabilities. Conversely, the most complex patients would benefit from being treated in high-volume, neuro-oriented ICUs.


Assuntos
Lesões Encefálicas Traumáticas , Neurocirurgia , Adulto , Escala de Coma de Glasgow , Escala de Resultado de Glasgow , Hospitais , Humanos , Unidades de Terapia Intensiva
20.
Stud Health Technol Inform ; 287: 40-44, 2021 Nov 18.
Artigo em Inglês | MEDLINE | ID: mdl-34795076

RESUMO

Implementing the best research principles initiates an important shift in clinical research culture, improving efficiency and the level of evidence obtained. In this article, we share our own view on the best research practice and our experience introducing it into the scientific activities of the N.N. Burdenko National Medical Research Center of Neurosurgery (Moscow, Russian Federation). While being adherent to the principles described in the article, the percentage of publications in the international scientific journals in our Center has increased from 7% to 27%, with an overall gain in the number of articles by 2 times since 2014. We believe it is important that medical informatics professionals equally to medical experts involved in clinical research are familiar with the best research principles.


Assuntos
Pesquisa Biomédica , Neurocirurgia , Hospitais , Procedimentos Neurocirúrgicos , Federação Russa
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