Health Technology/clinical-trials

Resting-State fMRI and Machine Learning in Glioblastoma: Prospective Trial Seeks to Predict Survival and Guide Neurosurgical Planning

247 Health News Editorial

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16 July 2026

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5 min read

·clinical-trials

A prospective study at Washington University School of Medicine is enrolling 100 patients with suspected glioblastoma to test whether a support vector machine algorithm applied to preoperative resting-state fMRI can classify patients as short- or long-term survivors before surgery. The findings could transform neurosurgical neuronavigation and personalise treatment planning for one of oncology's most challenging diagnoses.

Originally reported by ClinicalTrials.gov

References

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  4. 4.Leuthardt, E. C., Guzman, G., Bandt, S. K., Hacker, C. D., Vellimana, A. K., Limbrick, D. D., Milchenko, M., Shimony, J. S., & Snyder, A. Z. (2018). Integration of resting state fMRI into clinical practice — a large single institution experience. PLOS ONE, 13(6), e0198349. https://doi.org/10.1371/journal.pone.0198349
  5. 5.Duffau, H., & Mandonnet, E. (2013). The 'onco-functional balance' in surgery for diffuse low-grade glioma: Integrating the extent of resection with quality of life. Acta Neurochirurgica, 155(6), 951–957. https://doi.org/10.1007/s00701-012-1545-2
  6. 6.Aerts, H., Fries, P., & van den Heuvel, M. P. (2016). Neuronal dynamics underlying high- and low-frequency EEG oscillations contribute independently to the human BOLD signal. Neuron, 92(5), 983–999. https://doi.org/10.1016/j.neuron.2016.09.004
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247 Health News Editorial

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