PMA-MET: Metabolic Reprogramming as an Intraoperative Adjunct in Minimally Invasive Evacuation of Intracerebral Hemorrhage: A Falsifiable Theoretical and Computational Framework

Intracerebral hemorrhage (ICH) remains a leading cause of stroke-related mortality and disability. In the MISTIE III phase 3 trial, minimally invasive surgery (MIS) with adjunctive thrombolysis did not significantly improve the proportion of patients achieving a good functional outcome (modified Rankin Scale [mRS] 0–3) at 365 days relative to standard medical care (45% versus 41%; adjusted risk difference 4%, 95% CI −4 to 12; p = 0.33), despite substantially reducing residual hematoma volume. This dissociation between mechanical clot evacuation and functional recovery motivates interest in adjunctive strategies that target the metabolic sequelae of hemorrhage rather than its mass effect alone. Secondary brain injury after ICH is associated with peri-hematomal glutamate accumulation and excitotoxicity alongside depletion of branched-chain amino acids (BCAAs, particularly leucine), impairing mTOR-dependent neuroprotective signaling. This manuscript presents PMA-MET (Precision Metabolic-Integrated Adaptive Microsurgical Evacuation Technique), a conceptual surgical paradigm that couples adaptive, AI-gain-modulated mechanical evacuation with real-time microfluidic metabolomic sensing and localized enzymatic glutamate depletion and leucine supplementation, drawing a mechanistic analogy to amino-acid-depletion therapies used in oncology.We formulate a coupled evacuation-metabolism ordinary differential equation (ODE) system, propagate parameter uncertainty via Monte Carlo simulation (n = 10,000 literature-motivated parameter draws), and quantify input sensitivity via Sobol first-order and total-order indices computed by the Saltelli sampling scheme (N = 4000 base samples; 56,000 model evaluations). Across parameter draws, 87.3% reach the pre-specified neuroprotective threshold (leucine/glutamate ratio ≥ 0.8) within a 2-hour intraoperative window, with a median time-to-threshold of 61.5 minutes (IQR 45.6 to 83.4). Initial hematoma volume is the dominant driver of metabolic-normalization variability (first-order Sobol index S1 = 0.49, total-order ST = 0.64), followed by enzymatic depletion efficiency (S1 = 0.13) and evacuation flow rate (S1 = 0.09). Because no empirical dataset links this metabolic-normalization endpoint to functional outcome in ICH, we do not fit or assert a precise clinical effect size; instead we propagate an explicitly labeled, literature-anchored but unfitted effect-size prior through the same Monte Carlo framework, yielding a projected good-functional-outcome probability of 50.1% (5th to 95th percentile across the uncertainty distribution: 44.9 to 55.7%), corresponding to a mean relative improvement of 28.7% over the standard-care baseline (5th to 95th percentile: 15.4 to 43.3%), reported here as a theory-generated, assumption-dependent projection to be tested, not as a clinical claim. The framework is explicitly falsifiable through five pre-specified, quantitatively bounded hypotheses (Section 8), includes a closed-loop stability analysis for the control law with an explicit sufficient condition and direct numerical verification, and outlines a ten-year, milestone-driven translational roadmap beginning with ex-vivo and large-animal validation. Every quantitative result, table entry, and figure in this manuscript is a direct, traceable output of the embedded, self-contained Python 3 code in Section 3; the manuscript states plainly, throughout, where an assumption, rather than a measurement, is doing the work.