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

Background/Objectives: Diffuse glioma surgery requires balancing cytoreduction, distributed brain function, and individual priorities. We propose a patient-oriented, resource-adaptive framework and a testable hypothesis concerning postoperative functional recovery. Methods: A targeted narrative synthesis informed seven steps across network characterization, patient priorities, and therapeutic decision-making. A graph formulation separates expected resected tumor volume, direct functional cost, structural perturbation, and residual connectivity. A synthetic example illustrates its internal logic. Results: The framework links lesion topography and baseline function to patient-defined activities, consequences of loss, benefit–risk assessment, operative boundaries, and shared decisions. Connected candidate resections are compared under anatomical protections, declared cost limits, and independently audited connectivity thresholds. We hypothesize that model-estimated perturbation and residual connectivity add prognostic information about functional recovery beyond conventional clinical, anatomical, and molecular variables. Topological compensation is a possible mechanism; IDH status is an exploratory effect modifier. Population atlases provide probabilistic information, whereas individualized methods reduce uncertainty. Resource limitations may require restricted objectives or referral. Conclusions: The proposal makes the oncofunctional balance explicit and auditable. Mathematical consistency and the synthetic illustration establish no clinical efficacy or safety. Prospective validation is required before prescriptive use.