Network-Based Oncological Neurosurgery in Diffuse Gliomas: A Patient-Oriented and Resource-Adaptive Framework

Background/Objectives: Diffuse glioma surgery requires balancing tumor removal, brain function, and the patient’s priorities. We propose a patient-oriented, resource-adaptive framework and a testable hypothesis about postoperative functional recovery. Methods: A targeted narrative synthesis informed three domains: network characterization, patient priorities, and therapeutic decision. A graph model compares connected resections within clinically selected corridors. It separates modeled tumor-target volume, direct functional cost, structural disruption, and residual connectivity. Results: The framework relates the lesion and baseline function to activities valued by the patient, the consequences of losing them, and acceptable operative boundaries. An exploratory classification combines functional importance with radiological evidence of tract involvement. Indispensable connections remain protected. Trajectory intersections with the proposed resection or access corridor determine connection loss, including fibers of passage and partial bundle interruption. Maximum flow then audits the remaining structural capacity between protected pairs. A fully specified synthetic example shows how spatial injury, patient priorities, and connectivity requirements change the selected plan. We hypothesize that the resulting measures add prognostic information beyond conventional predictors. Topological compensation is a possible mechanism, and IDH status is an exploratory modifier. Conclusions: The framework provides a transparent way to document priorities and compare plans under uncertainty. Its classification, input estimates, and clinical predictions require validation. Services without the necessary individual network data can use the clinical framework to document uncertainty and adapt objectives or referrals.