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Van Ravestyn A, Frantz T, Vandemeulebroucke J, Jansen B, Duerinck J, Scheerlinck T. Determination of rotation center and diameter of femoral heads using off-the-shelf augmented reality hardware for navigation. Sci Rep 2024; 14:15458. [PMID: 38965266 PMCID: PMC11224340 DOI: 10.1038/s41598-024-64957-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Accepted: 06/14/2024] [Indexed: 07/06/2024] Open
Abstract
In total hip arthroplasty (THA), determining the center of rotation (COR) and diameter of the hip joint (acetabulum and femoral head) is essential to restore patient biomechanics. This study investigates on-the-fly determination of hip COR and size, using off-the-shelf augmented reality (AR) hardware. An AR head-mounted device (HMD) was configured with inside-out infrared tracking enabling the determination of surface coordinates using a handheld stylus. Two investigators examined 10 prosthetic femoral heads and cups, and 10 human femurs. The HMD calculated the diameter and COR through sphere fitting. Results were compared to data obtained from either verified prosthetic geometry or post-hoc CT analysis. Repeated single-observer measurements showed a mean diameter error of 0.63 mm ± 0.48 mm for the prosthetic heads and 0.54 mm ± 0.39 mm for the cups. Inter-observer comparison yielded mean diameter errors of 0.28 mm ± 0.71 mm and 1.82 mm ± 1.42 mm for the heads and cups, respectively. Cadaver testing found a mean COR error of 3.09 mm ± 1.18 mm and a diameter error of 1.10 mm ± 0.90 mm. Intra- and inter-observer reliability averaged below 2 mm. AR-based surface mapping using HMD proved accurate and reliable in determining the diameter of THA components with promise in identifying COR and diameter of osteoarthritic femoral heads.
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Affiliation(s)
- Antoine Van Ravestyn
- Department of Orthopedic Surgery and Traumatology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090, Brussels, Belgium.
- Vrije Universiteit Brussel (VUB), Research Group BEFY-ORTHO, Laarbeeklaan 103, 1090, Brussels, Belgium.
| | - Taylor Frantz
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050, Brussels, Belgium
- IMEC, Kapeldreef 75, 3001, Leuven, Belgium
| | - Jef Vandemeulebroucke
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050, Brussels, Belgium
- IMEC, Kapeldreef 75, 3001, Leuven, Belgium
- Department of Radiology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090, Brussels, Belgium
| | - Bart Jansen
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050, Brussels, Belgium
- IMEC, Kapeldreef 75, 3001, Leuven, Belgium
| | - Johnny Duerinck
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090, Brussels, Belgium
| | - Thierry Scheerlinck
- Department of Orthopedic Surgery and Traumatology, Universitair Ziekenhuis Brussel (UZ Brussel), Laarbeeklaan 101, 1090, Brussels, Belgium
- Vrije Universiteit Brussel (VUB), Research Group BEFY-ORTHO, Laarbeeklaan 103, 1090, Brussels, Belgium
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Begagić E, Bečulić H, Pugonja R, Memić Z, Balogun S, Džidić-Krivić A, Milanović E, Salković N, Nuhović A, Skomorac R, Sefo H, Pojskić M. Augmented Reality Integration in Skull Base Neurosurgery: A Systematic Review. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:335. [PMID: 38399622 PMCID: PMC10889940 DOI: 10.3390/medicina60020335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/05/2024] [Accepted: 02/09/2024] [Indexed: 02/25/2024]
Abstract
Background and Objectives: To investigate the role of augmented reality (AR) in skull base (SB) neurosurgery. Materials and Methods: Utilizing PRISMA methodology, PubMed and Scopus databases were explored to extract data related to AR integration in SB surgery. Results: The majority of 19 included studies (42.1%) were conducted in the United States, with a focus on the last five years (77.8%). Categorization included phantom skull models (31.2%, n = 6), human cadavers (15.8%, n = 3), or human patients (52.6%, n = 10). Microscopic surgery was the predominant modality in 10 studies (52.6%). Of the 19 studies, surgical modality was specified in 18, with microscopic surgery being predominant (52.6%). Most studies used only CT as the data source (n = 9; 47.4%), and optical tracking was the prevalent tracking modality (n = 9; 47.3%). The Target Registration Error (TRE) spanned from 0.55 to 10.62 mm. Conclusion: Despite variations in Target Registration Error (TRE) values, the studies highlighted successful outcomes and minimal complications. Challenges, such as device practicality and data security, were acknowledged, but the application of low-cost AR devices suggests broader feasibility.
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Affiliation(s)
- Emir Begagić
- Department of General Medicine, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina;
| | - Hakija Bečulić
- Department of Neurosurgery, Cantonal Hospital Zenica, Crkvice 67, 72000 Zenica, Bosnia and Herzegovina; (H.B.)
- Department of Anatomy, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina;
| | - Ragib Pugonja
- Department of Anatomy, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina;
| | - Zlatan Memić
- Department of General Medicine, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina;
| | - Simon Balogun
- Division of Neurosurgery, Department of Surgery, Obafemi Awolowo University Teaching Hospitals Complex, Ilesa Road PMB 5538, Ile-Ife 220282, Nigeria
| | - Amina Džidić-Krivić
- Department of Neurology, Cantonal Hospital Zenica, Crkvice 67, 72000 Zenica, Bosnia and Herzegovina
| | - Elma Milanović
- Neurology Clinic, Clinical Center University of Sarajevo, Bolnička 25, 71000 Sarajevo, Bosnia and Herzegovina
| | - Naida Salković
- Department of General Medicine, School of Medicine, University of Tuzla, Univerzitetska 1, 75000 Tuzla, Bosnia and Herzegovina;
| | - Adem Nuhović
- Department of General Medicine, School of Medicine, University of Sarajevo, Univerzitetska 1, 71000 Sarajevo, Bosnia and Herzegovina;
| | - Rasim Skomorac
- Department of Neurosurgery, Cantonal Hospital Zenica, Crkvice 67, 72000 Zenica, Bosnia and Herzegovina; (H.B.)
- Department of Surgery, School of Medicine, University of Zenica, Travnička 1, 72000 Zenica, Bosnia and Herzegovina
| | - Haso Sefo
- Neurosurgery Clinic, Clinical Center University of Sarajevo, Bolnička 25, 71000 Sarajevo, Bosnia and Herzegovina
| | - Mirza Pojskić
- Department of Neurosurgery, University Hospital Marburg, Baldingerstr., 35033 Marburg, Germany
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Kos TM, Colombo E, Bartels LW, Robe PA, van Doormaal TPC. Evaluation Metrics for Augmented Reality in Neurosurgical Preoperative Planning, Surgical Navigation, and Surgical Treatment Guidance: A Systematic Review. Oper Neurosurg (Hagerstown) 2023; 26:01787389-990000000-01007. [PMID: 38146941 PMCID: PMC11008635 DOI: 10.1227/ons.0000000000001009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 10/10/2023] [Indexed: 12/27/2023] Open
Abstract
BACKGROUND AND OBJECTIVE Recent years have shown an advancement in the development of augmented reality (AR) technologies for preoperative visualization, surgical navigation, and intraoperative guidance for neurosurgery. However, proving added value for AR in clinical practice is challenging, partly because of a lack of standardized evaluation metrics. We performed a systematic review to provide an overview of the reported evaluation metrics for AR technologies in neurosurgical practice and to establish a foundation for assessment and comparison of such technologies. METHODS PubMed, Embase, and Cochrane were searched systematically for publications on assessment of AR for cranial neurosurgery on September 22, 2022. The findings were reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS The systematic search yielded 830 publications; 114 were screened full text, and 80 were included for analysis. Among the included studies, 5% dealt with preoperative visualization using AR, with user perception as the most frequently reported metric. The majority (75%) researched AR technology for surgical navigation, with registration accuracy, clinical outcome, and time measurements as the most frequently reported metrics. In addition, 20% studied the use of AR for intraoperative guidance, with registration accuracy, task outcome, and user perception as the most frequently reported metrics. CONCLUSION For quality benchmarking of AR technologies in neurosurgery, evaluation metrics should be specific to the risk profile and clinical objectives of the technology. A key focus should be on using validated questionnaires to assess user perception; ensuring clear and unambiguous reporting of registration accuracy, precision, robustness, and system stability; and accurately measuring task performance in clinical studies. We provided an overview suggesting which evaluation metrics to use per AR application and innovation phase, aiming to improve the assessment of added value of AR for neurosurgical practice and to facilitate the integration in the clinical workflow.
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Affiliation(s)
- Tessa M. Kos
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Elisa Colombo
- Department of Neurosurgery, Clinical Neuroscience Center, Universitätsspital Zürich, Zurich, The Netherlands
| | - L. Wilbert Bartels
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Pierre A. Robe
- Department of Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Tristan P. C. van Doormaal
- Department of Neurosurgery, Clinical Neuroscience Center, Universitätsspital Zürich, Zurich, The Netherlands
- Department of Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands
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Lewandrowski KU, Elfar JC, Li ZM, Burkhardt BW, Lorio MP, Winkler PA, Oertel JM, Telfeian AE, Dowling Á, Vargas RAA, Ramina R, Abraham I, Assefi M, Yang H, Zhang X, Ramírez León JF, Fiorelli RKA, Pereira MG, de Carvalho PST, Defino H, Moyano J, Lim KT, Kim HS, Montemurro N, Yeung A, Novellino P. The Changing Environment in Postgraduate Education in Orthopedic Surgery and Neurosurgery and Its Impact on Technology-Driven Targeted Interventional and Surgical Pain Management: Perspectives from Europe, Latin America, Asia, and The United States. J Pers Med 2023; 13:852. [PMID: 37241022 PMCID: PMC10221956 DOI: 10.3390/jpm13050852] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/15/2023] [Accepted: 05/16/2023] [Indexed: 05/28/2023] Open
Abstract
Personalized care models are dominating modern medicine. These models are rooted in teaching future physicians the skill set to keep up with innovation. In orthopedic surgery and neurosurgery, education is increasingly influenced by augmented reality, simulation, navigation, robotics, and in some cases, artificial intelligence. The postpandemic learning environment has also changed, emphasizing online learning and skill- and competency-based teaching models incorporating clinical and bench-top research. Attempts to improve work-life balance and minimize physician burnout have led to work-hour restrictions in postgraduate training programs. These restrictions have made it particularly challenging for orthopedic and neurosurgery residents to acquire the knowledge and skill set to meet the requirements for certification. The fast-paced flow of information and the rapid implementation of innovation require higher efficiencies in the modern postgraduate training environment. However, what is taught typically lags several years behind. Examples include minimally invasive tissue-sparing techniques through tubular small-bladed retractor systems, robotic and navigation, endoscopic, patient-specific implants made possible by advances in imaging technology and 3D printing, and regenerative strategies. Currently, the traditional roles of mentee and mentor are being redefined. The future orthopedic surgeons and neurosurgeons involved in personalized surgical pain management will need to be versed in several disciplines ranging from bioengineering, basic research, computer, social and health sciences, clinical study, trial design, public health policy development, and economic accountability. Solutions to the fast-paced innovation cycle in orthopedic surgery and neurosurgery include adaptive learning skills to seize opportunities for innovation with execution and implementation by facilitating translational research and clinical program development across traditional boundaries between clinical and nonclinical specialties. Preparing the future generation of surgeons to have the aptitude to keep up with the rapid technological advances is challenging for postgraduate residency programs and accreditation agencies. However, implementing clinical protocol change when the entrepreneur-investigator surgeon substantiates it with high-grade clinical evidence is at the heart of personalized surgical pain management.
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Affiliation(s)
- Kai-Uwe Lewandrowski
- Center For Advanced Spine Care of Southern Arizona, 4787 E Camp Lowell Drive, Tucson, AZ 85719, USA
- Department of Orthopaedics, Fundación Universitaria Sanitas, Bogotá 111321, Colombia
| | - John C. Elfar
- Department of Orthopaedic Surgery, College of Medicine—Tucson Campus, Health Sciences Innovation Building (HSIB), University of Arizona, 1501 N. Campbell Avenue, Tower 4, 8th Floor, Suite 8401, Tucson, AZ 85721, USA;
| | - Zong-Ming Li
- Departments of Orthopaedic Surgery and Biomedical Engineering, College of Medicine—Tucson Campus, Health Sciences Innovation Building (HSIB), University of Arizona, 1501 N. Campbell Avenue, Tower 4, 8th Floor, Suite 8401, Tucson, AZ 85721, USA;
| | - Benedikt W. Burkhardt
- Wirbelsäulenzentrum/Spine Center—WSC, Hirslanden Klinik Zurich, Witellikerstrasse 40, 8032 Zurich, Switzerland;
| | - Morgan P. Lorio
- Advanced Orthopaedics, 499 E. Central Pkwy, Ste. 130, Altamonte Springs, FL 32701, USA;
| | - Peter A. Winkler
- Department of Neurosurgery, Charite Universitaetsmedizin Berlin, 13353 Berlin, Germany;
| | - Joachim M. Oertel
- Klinik für Neurochirurgie, Universitätsdes Saarlandes, Kirrberger Straße 100, 66421 Homburg, Germany;
| | - Albert E. Telfeian
- Department of Neurosurgery, Rhode Island Hospital, The Warren Alpert Medical School of Brown University, Providence, RI 02903, USA;
| | - Álvaro Dowling
- Orthopaedic Surgery, University of São Paulo, Brazilian Spine Society (SBC), Ribeirão Preto 14071-550, Brazil; (Á.D.); (H.D.)
| | - Roth A. A. Vargas
- Department of Neurosurgery, Foundation Hospital Centro Médico Campinas, Campinas 13083-210, Brazil;
| | - Ricardo Ramina
- Neurological Institute of Curitiba, Curitiba 80230-030, Brazil;
| | - Ivo Abraham
- Clinical Translational Sciences, University of Arizona, Roy P. Drachman Hall, Rm. B306H, Tucson, AZ 85721, USA;
| | - Marjan Assefi
- Department of Biology, Nano-Biology, University of North Carolina, Greensboro, NC 27413, USA;
| | - Huilin Yang
- Orthopaedic Department, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou 215031, China;
| | - Xifeng Zhang
- Department of Orthopaedics, First Medical Center, PLA General Hospital, Beijing 100853, China;
| | - Jorge Felipe Ramírez León
- Minimally Invasive Spine Center Bogotá D.C. Colombia, Reina Sofía Clinic Bogotá D.C. Colombia, Department of Orthopaedics Fundación Universitaria Sanitas, Bogotá 0819, Colombia;
| | - Rossano Kepler Alvim Fiorelli
- Department of General and Specialized Surgery, Gaffrée e Guinle University Hospital, Federal University of the State of Rio de Janeiro (UNIRIO), Rio de Janeiro 20270-004, Brazil;
| | - Mauricio G. Pereira
- Faculty of Medecine, University of Brasilia, Federal District, Brasilia 70919-900, Brazil;
| | | | - Helton Defino
- Orthopaedic Surgery, University of São Paulo, Brazilian Spine Society (SBC), Ribeirão Preto 14071-550, Brazil; (Á.D.); (H.D.)
| | - Jaime Moyano
- La Sociedad Iberolatinoamericana De Columna (SILACO), and the Spine Committee of the Ecuadorian Society of Orthopaedics and Traumatology (Comité de Columna de la Sociedad Ecuatoriana de Ortopedia y Traumatología), Quito 170521, Ecuador;
| | - Kang Taek Lim
- Good Doctor Teun Teun Spine Hospital, Anyang 14041, Republic of Korea;
| | - Hyeun-Sung Kim
- Department of Neurosurgery, Nanoori Hospital, Seoul 06048, Republic of Korea;
| | - Nicola Montemurro
- Department of Neurosurgery, Azienda Ospedaliero Universitaria Pisana, University of Pisa, 56124 Pisa, Italy;
| | - Anthony Yeung
- Desert Institute for Spine Care, Phoenix, AZ 85020, USA;
| | - Pietro Novellino
- Guinle and State Institute of Diabetes and Endocrinology, Rio de Janeiro 20270-004, Brazil;
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Van Gestel F, Frantz T, Buyck F, Geens W, Neuville Q, Bruneau M, Jansen B, Scheerlinck T, Vandemeulebroucke J, Duerinck J. Neuro-oncological augmented reality planning for intracranial tumor resection. Front Neurol 2023; 14:1104571. [PMID: 36998774 PMCID: PMC10043492 DOI: 10.3389/fneur.2023.1104571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 02/14/2023] [Indexed: 03/18/2023] Open
Abstract
BackgroundBefore starting surgery for the resection of an intracranial tumor, its outlines are typically marked on the skin of the patient. This allows for the planning of the optimal skin incision, craniotomy, and angle of approach. Conventionally, the surgeon determines tumor borders using neuronavigation with a tracked pointer. However, interpretation errors can lead to important deviations, especially for deep-seated tumors, potentially resulting in a suboptimal approach with incomplete exposure. Augmented reality (AR) allows displaying of the tumor and critical structures directly on the patient, which can simplify and improve surgical preparation.MethodsWe developed an AR-based workflow for intracranial tumor resection planning deployed on the Microsoft HoloLens II, which exploits the built-in infrared-camera for tracking the patient. We initially performed a phantom study to assess the accuracy of the registration and tracking. Following this, we evaluated the AR-based planning step in a prospective clinical study for patients undergoing resection of a brain tumor. This planning step was performed by 12 surgeons and trainees with varying degrees of experience. After patient registration, tumor outlines were marked on the patient's skin by different investigators, consecutively using a conventional neuronavigation system and an AR-based system. Their performance in both registration and delineation was measured in terms of accuracy and duration and compared.ResultsDuring phantom testing, registration errors remained below 2.0 mm and 2.0° for both AR-based navigation and conventional neuronavigation, with no significant difference between both systems. In the prospective clinical trial, 20 patients underwent tumor resection planning. Registration accuracy was independent of user experience for both AR-based navigation and the commercial neuronavigation system. AR-guided tumor delineation was deemed superior in 65% of cases, equally good in 30% of cases, and inferior in 5% of cases when compared to the conventional navigation system. The overall planning time (AR = 119 ± 44 s, conventional = 187 ± 56 s) was significantly reduced through the adoption of the AR workflow (p < 0.001), with an average time reduction of 39%.ConclusionBy providing a more intuitive visualization of relevant data to the surgeon, AR navigation provides an accurate method for tumor resection planning that is quicker and more intuitive than conventional neuronavigation. Further research should focus on intraoperative implementations.
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Affiliation(s)
- Frederick Van Gestel
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Research Group Center for Neurosciences (C4N-NEUR), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- *Correspondence: Frederick Van Gestel
| | - Taylor Frantz
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- IMEC, Leuven, Belgium
| | - Felix Buyck
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Wietse Geens
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Quentin Neuville
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Research Group Center for Neurosciences (C4N-NEUR), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Michaël Bruneau
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Bart Jansen
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- IMEC, Leuven, Belgium
| | - Thierry Scheerlinck
- Department of Orthopedic Surgery and Traumatology, Universitair Ziekenhuis Brussel (UZ Brussel), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Research Group Beeldvorming en Fysische Wetenschappen (BEFY-ORTHO), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Jef Vandemeulebroucke
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- IMEC, Leuven, Belgium
- Department of Radiology, Universitair Ziekenhuis Brussel (UZ Brussel), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Johnny Duerinck
- Department of Neurosurgery, Universitair Ziekenhuis Brussel (UZ Brussel), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- Research Group Center for Neurosciences (C4N-NEUR), Vrije Universiteit Brussel (VUB), Brussels, Belgium
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Duerinck J, Van Der Veken J, Schuind S, Van Calenbergh F, van Loon J, Du Four S, Debacker S, Costa E, Raftopoulos C, De Witte O, Cools W, Buyl R, Van Velthoven V, D'Haens J, Bruneau M. Randomized Trial Comparing Burr Hole Craniostomy, Minicraniotomy, and Twist Drill Craniostomy for Treatment of Chronic Subdural Hematoma. Neurosurgery 2022; 91:304-311. [PMID: 35593710 DOI: 10.1227/neu.0000000000001997] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 02/10/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The mainstay of treatment for symptomatic or large chronic subdural hematoma (CSDH) is surgery, but controversy still exists regarding the best surgical technique. Three different techniques are commonly used: burr hole craniostomy (BHC), minicraniotomy (MC), and twist drill craniostomy (TDC). OBJECTIVE To determine which surgical technique for drainage of CSDH offers best results. METHODS We set up a multicenter prospective randomized trial (Comparison of Chronic Subdural Hematoma Treatment [COMPACT] trial) comparing BHC, MC, and TDC for the surgical treatment of CSDH. The primary end point was reoperation rate, and secondary end points included complication rates and clinical outcome. Patients were considered to have good outcome when they did not undergo reoperation, suffered no surgical or medical complication, and had no related mortality. Clinical outcome was also evaluated by evolution of the Markwalder score and the modified Rankin score. RESULTS Two-hundred forty-five patients were included in the final analysis: 79 BHC, 84 MC, and 82 TDC. Mean duration of surgery was shorter for TDC than for BHC and MC (P < .001). Reoperation rate was 7.6% for BHC, 13.1% for MC, and 19.5% for TDC (P = .07). This trend toward better results for BHC was not statistically significant in logistic regression analysis. The proportion of patients with good outcome was 78.5% for BHC group, 76.2% for MC, and 69.5% for TDC (P = .4). Evolution of the Markwalder score and modified Rankin score were not significantly different between treatment groups. CONCLUSION All 3 techniques are effective at treating patients with CSDH with eventual 6-month outcome being similar. Although not reaching statistical significance in our study, BHC offers the lowest recurrence rate combined with manageable complication rate.
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Affiliation(s)
| | - Jorn Van Der Veken
- Department of Neurosurgery, UZ Brussel, Brussels, Belgium.,Current affiliation: Department of Neurosurgery, Flinders Medical Centre, Adelaide, Australia
| | - Sophie Schuind
- Department of Neurosurgery, ULB Erasme, Brussels, Belgium
| | | | | | | | - Servaes Debacker
- Faculty of Medicine, Vrije Universiteit Brussel, Brussels, Belgium
| | - Emmanuel Costa
- Department of Neurosurgery, UCL Saint-Luc, Brussels, Belgium
| | | | | | - Wilfried Cools
- Interfaculty Center Data Processing and Statistics, UZ Brussel/Vrije Universiteit Brussel, Brussels, Belgium
| | - Ronald Buyl
- Biostatistics and Medical Informatics Research Group, Vrije Universiteit Brussel, Brussels, Belgium
| | | | - Jean D'Haens
- Department of Neurosurgery, UZ Brussel, Brussels, Belgium
| | - Michaël Bruneau
- Department of Neurosurgery, ULB Erasme, Brussels, Belgium.,Current affiliation: Department of Neurosurgery, UZ Brussel, Brussels, Belgium
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Zoli M, Daniele B, Giovanni R, Teresa S, Cesare Z, Giuseppe Maria DP. Young Neurosurgeons and Technology: Survey of Young Neurosurgeons Section of Italian Society of Neurosurgery (SINch). World Neurosurg 2022; 162:e436-e456. [DOI: 10.1016/j.wneu.2022.03.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 03/05/2022] [Accepted: 03/07/2022] [Indexed: 11/25/2022]
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8
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Van Gestel F, Frantz T, Vannerom C, Verhellen A, Gallagher AG, Elprama SA, Jacobs A, Buyl R, Bruneau M, Jansen B, Vandemeulebroucke J, Scheerlinck T, Duerinck J. The effect of augmented reality on the accuracy and learning curve of external ventricular drain placement. Neurosurg Focus 2021; 51:E8. [PMID: 34333479 DOI: 10.3171/2021.5.focus21215] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 05/13/2021] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The traditional freehand technique for external ventricular drain (EVD) placement is most frequently used, but remains the primary risk factor for inaccurate drain placement. As this procedure could benefit from image guidance, the authors set forth to demonstrate the impact of augmented-reality (AR) assistance on the accuracy and learning curve of EVD placement compared with the freehand technique. METHODS Sixteen medical students performed a total of 128 EVD placements on a custom-made phantom head, both before and after receiving a standardized training session. They were guided by either the freehand technique or by AR, which provided an anatomical overlay and tailored guidance for EVD placement through inside-out infrared tracking. The outcome was quantified by the metric accuracy of EVD placement as well as by its clinical quality. RESULTS The mean target error was significantly impacted by either AR (p = 0.003) or training (p = 0.02) in a direct comparison with the untrained freehand performance. Both untrained (11.9 ± 4.5 mm) and trained (12.2 ± 4.7 mm) AR performances were significantly better than the untrained freehand performance (19.9 ± 4.2 mm), which improved after training (13.5 ± 4.7 mm). The quality of EVD placement as assessed by the modified Kakarla scale (mKS) was significantly impacted by AR guidance (p = 0.005) but not by training (p = 0.07). Both untrained and trained AR performances (59.4% mKS grade 1 for both) were significantly better than the untrained freehand performance (25.0% mKS grade 1). Spatial aptitude testing revealed a correlation between perceptual ability and untrained AR-guided performance (r = 0.63). CONCLUSIONS Compared with the freehand technique, AR guidance for EVD placement yielded a higher outcome accuracy and quality for procedure novices. With AR, untrained individuals performed as well as trained individuals, which indicates that AR guidance not only improved performance but also positively impacted the learning curve. Future efforts will focus on the translation and evaluation of AR for EVD placement in the clinical setting.
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Affiliation(s)
- Frederick Van Gestel
- 1Department of Neurosurgery, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels.,2Research Group Center For Neurosciences (C4N-NEUR), Vrije Universiteit Brussel, Brussels
| | - Taylor Frantz
- 3Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Brussels.,4imec, Leuven
| | - Cédric Vannerom
- 1Department of Neurosurgery, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels.,2Research Group Center For Neurosciences (C4N-NEUR), Vrije Universiteit Brussel, Brussels
| | - Anouk Verhellen
- 5Department of Studies on Media, Innovation & Technology (SMIT), Vrije Universiteit Brussel, Brussels
| | | | - Shirley A Elprama
- 5Department of Studies on Media, Innovation & Technology (SMIT), Vrije Universiteit Brussel, Brussels
| | - An Jacobs
- 5Department of Studies on Media, Innovation & Technology (SMIT), Vrije Universiteit Brussel, Brussels
| | - Ronald Buyl
- 7Department of Public Health, Research Group Biostatistics and Medical Informatics (BISI), Vrije Universiteit Brussel, Brussels
| | - Michaël Bruneau
- 1Department of Neurosurgery, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels
| | - Bart Jansen
- 3Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Brussels.,4imec, Leuven
| | - Jef Vandemeulebroucke
- 3Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Brussels.,4imec, Leuven
| | - Thierry Scheerlinck
- 8Department of Orthopedic Surgery and Traumatology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels; and.,9Research Group Beeldvorming en Fysische wetenschappen (BEFY-ORTHO), Vrije Universiteit Brussel, Brussels, Belgium
| | - Johnny Duerinck
- 1Department of Neurosurgery, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel, Brussels.,2Research Group Center For Neurosciences (C4N-NEUR), Vrije Universiteit Brussel, Brussels
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