Precision-Guided Minimally Invasive Neurosurgery: Anatomical Accuracy, Patient Selection, and Contemporary Challenges
DOI:
https://doi.org/10.64784/307Palabras clave:
minimally invasive neurosurgery, image-guided surgery, neuronavigation, intraoperative MRI, intraoperative ultrasound, tractography, tubular retractors, neuroendoscopy, augmented reality, laser interstitial thermal therapy, patient selection, anatomical precision, brain shift, neurological preservationResumen
Image-guided minimally invasive neurosurgery has transformed the management of intracranial lesions by integrating advanced imaging, neuronavigation, stereotactic planning, intraoperative visualization, and reduced surgical corridors. The objective of this study was to analyze the anatomical precision, patient-selection criteria, clinical outcomes, and current limitations associated with minimally invasive image-guided neurosurgical approaches. A structured integrative review based on the scientific method was conducted using evidence from PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar. The analysis included studies addressing neuronavigation, diffusion tensor imaging and tractography, intraoperative magnetic resonance imaging, intraoperative ultrasound, tubular and parafascicular approaches, neuroendoscopy, augmented reality, and laser interstitial thermal therapy. The reviewed evidence showed that intraoperative MRI can significantly increase complete resection rates in selected glioma patients, while intraoperative ultrasound and tubular approaches also demonstrate favorable resection outcomes in appropriately selected populations. Navigation systems showed mean target registration errors of approximately 2.5–2.6 mm, although their accuracy may progressively decrease because of brain shift and intraoperative anatomical deformation. Patient selection was strongly influenced by lesion depth, accessibility, proximity to eloquent structures, lesion size and geometry, previous treatments, neurological status, and expected therapeutic benefit. Current limitations include registration error, imaging artifacts, restricted operative maneuverability, learning curves, procedure-specific complications, cost, technological availability, and heterogeneity of the available evidence. Overall, image-guided minimally invasive neurosurgery can improve anatomical localization and support safer, function-preserving interventions when combined with rigorous patient selection and intraoperative adaptability. Its clinical value should not be defined exclusively by the size of the surgical corridor, but by the capacity to achieve adequate lesion control while minimizing unnecessary disruption of healthy neural structures.
Referencias
• Sulangi, A. J., Husain, A., Lei, H., & Okun, J. (2024). Neuronavigation in glioma resection: Current applications, challenges, and clinical outcomes. Frontiers in Surgery, 11, 1430567. DOI: 10.3389/fsurg.2024.1430567.
• Thomas, N. W. D., & Sinclair, J. (2015). Image-guided neurosurgery: History and current clinical applications. Journal of Medical Imaging and Radiation Sciences, 46(3), 331–342. DOI: 10.1016/j.jmir.2015.06.003.
• Senft, C., Bink, A., Franz, K., Vatter, H., Gasser, T., & Seifert, V. (2011). Intraoperative MRI guidance and extent of resection in glioma surgery: A randomised, controlled trial. The Lancet Oncology, 12(11), 997–1003. DOI: 10.1016/S1470-2045(11)70196-6.
• Mahboob, S., McPhillips, R., Qiu, Z., Jiang, Y., Meggs, C., Schiavone, G., Button, T., Desmulliez, M., Demore, C., Cochran, S., & Eljamel, S. (2016). Intraoperative ultrasound-guided resection of gliomas: A meta-analysis and review of the literature. World Neurosurgery, 92, 255–263. DOI: 10.1016/j.wneu.2016.05.007.
• Dixon, L., Lim, A., Grech-Sollars, M., Nandi, D., & Camp, S. (2022). Intraoperative ultrasound in brain tumor surgery: A review and implementation guide. Neurosurgical Review, 45(4), 2503–2515. DOI: 10.1007/s10143-022-01778-4.
• Shetty, P., Yeole, U., Singh, V., & Moiyadi, A. (2021). Navigated ultrasound-based image guidance during resection of gliomas: Practical utility in intraoperative decision-making and outcomes. Neurosurgical Focus, 50(1), E14. DOI: 10.3171/2020.10.FOCUS20550.
• Manan, A. A., Yahya, N., Idris, Z., & Manan, H. A. (2022). The utilization of diffusion tensor imaging as an image-guided tool in brain tumor resection surgery: A systematic review. Cancers, 14(10), 2466. DOI: 10.3390/cancers14102466.
• Potgieser, A. R. E., Wagemakers, M., van Hulzen, A. L. J., de Jong, B. M., Hoving, E. W., & Groen, R. J. M. (2014). The role of diffusion tensor imaging in brain tumor surgery: A review of the literature. Clinical Neurology and Neurosurgery, 124, 51–58. DOI: 10.1016/j.clineuro.2014.06.009.
• Meola, A., Cutolo, F., Carbone, M., Cagnazzo, F., Ferrari, M., & Ferrari, V. (2017). Augmented reality in neurosurgery: A systematic review. Neurosurgical Review, 40(4), 537–548. DOI: 10.1007/s10143-016-0732-9.
• Fick, T., van Doormaal, J. A. M., Hoving, E. W., Willems, P. W. A., & van Doormaal, T. P. C. (2021). Current accuracy of augmented reality neuronavigation systems: Systematic review and meta-analysis. World Neurosurgery, 146, 179–188. DOI: 10.1016/j.wneu.2020.11.029.
• Chidambaram, S., Stifano, V., Demetres, M., Teyssandier, M., Palumbo, M. C., Redaelli, A., Olivi, A., Apuzzo, M. L. J., & Pannullo, S. C. (2021). Applications of augmented reality in the neurosurgical operating room: A systematic review of the literature. Journal of Clinical Neuroscience, 91, 43–61. DOI: 10.1016/j.jocn.2021.06.032.
• Jarmula, J., de Andrade, E. J., Kshettry, V. R., & Recinos, P. F. (2022). The current state of visualization techniques in endoscopic skull base surgery. Brain Sciences, 12(10), 1337. DOI: 10.3390/brainsci12101337.
• Marenco-Hillembrand, L., Prevatt, C., Suarez-Meade, P., Ruiz-Garcia, H., Quinones-Hinojosa, A., & Chaichana, K. L. (2020). Minimally invasive surgical outcomes for deep-seated brain lesions treated with different tubular retraction systems: A systematic review and meta-analysis. World Neurosurgery, 143, 537–545.e3. DOI: 10.1016/j.wneu.2020.07.115.
• Abdala-Vargas, N. J., Umana, G. E., Patiño-Gomez, J. G., Ordoñez-Rubiano, E., Cifuentes-Lobelo, H. A., Palmisciano, P., Ferini, G., Viola, A., Zagardo, V., Casanova-Martínez, D., Tomasi, O. S., Campero, A., & Baldoncini, M. (2023). Standardization of strategies to perform a parafascicular tubular approach for the resection of brain tumors in eloquent areas. Brain Sciences, 13(3), 498. DOI: 10.3390/brainsci13030498.
• Eliyas, J. K., Glynn, R., Kulwin, C. G., Rovin, R., Young, R., Alzate, J., Pradilla, G., Shah, M. V., Kassam, A., Ciric, I., & Bailes, J. (2016). Minimally invasive transsulcal resection of intraventricular and periventricular lesions through a tubular retractor system: Multicentric experience and results. World Neurosurgery, 90, 556–564. DOI: 10.1016/j.wneu.2015.12.100.
• Rahmathulla, G., Recinos, P. F., Kamian, K., Mohammadi, A. M., Ahluwalia, M. S., & Barnett, G. H. (2014). MRI-guided laser interstitial thermal therapy in neuro-oncology: A review of its current clinical applications. Oncology, 87(2), 67–82. DOI: 10.1159/000362817.
• Chen, C., Lee, I., Tatsui, C., Elder, T., & Sloan, A. E. (2021). Laser interstitial thermotherapy (LITT) for the treatment of tumors of the brain and spine: A brief review. Journal of Neuro-Oncology, 151(3), 429–442. DOI: 10.1007/s11060-020-03652-z.
• Mirza, F. A., Mitha, R., & Shamim, M. S. (2020). Current role of laser interstitial thermal therapy in the treatment of intracranial tumors. Asian Journal of Neurosurgery, 15(4), 800–808. DOI: 10.4103/ajns.AJNS_185_20.
• Rafati Fard, A., Hibberd, O., Akinduro, I., Bhatti, Z., Smith, K. J., Patel, R., Karmarkar, S., Mowforth, O. D., & Hill, C. S. (2025). Tubular retractors in neuro-oncological surgery: A systematic review and meta-analysis. Neurosurgical Review, 48(1), 530. DOI: 10.1007/s10143-025-03677-w.
• Sharma, N., Mallela, A. N., Khan, T., Canton, S. P., Kass, N. M., Steuer, F., Jardini, J., Biehl, J., & Andrews, E. G. (2024). Evolution of the meta-neurosurgeon: A systematic review of the current technical capabilities, limitations, and applications of augmented reality in neurosurgery. Surgical Neurology International, 15, 146. DOI: 10.25259/SNI_167_2024.
