Neuromorphic Olfactory Sensors ("E-Nose") for Early-Stage Non-Invasive Cancer Detection

Early-stage detection of neoplastic malignancies remains the single most impactful factor in determining 5-year cancer survival rates across global populations. However, gold-standard diagnostic modalities—including low-dose computed tomography (LDCT), magnetic resonance imaging (MRI), colonoscopy, mammography, and invasive tissue histopathology—suffer from prohibitive capital costs, ionizing radiation hazards, substantial procedural discomfort, and high false-positive rates that trigger unwarranted invasive interventions. Malignant cell transformation is intrinsically accompanied by profound metabolic reprogramming, accelerated mitochondrial glycolysis (the Warburg effect), and reactive oxygen species (ROS)-mediated cell membrane lipid peroxidation. These altered biochemical cascades generate distinct mixtures of Volatile Organic Compounds (VOCs)—including branched alkanes, methylated benzenes, aliphatic aldehydes, and ketones—which enter the systemic capillary circulation and are continuously partitioned across the pulmonary alveolar-capillary barrier into exhaled breath at parts-per-billion (ppb) to parts-per-trillion (ppt) concentrations. This paper introduces an ultra-sensitive, non-invasive "Electronic Nose" (E-Nose) diagnostic platform combining a 64-channel cross-reactive chemo-resistive sensor array of functionalized Single-Walled Carbon Nanotubes (SWCNTs) with an asynchronous event-driven Neuromorphic Spiking Neural Network (SNN) processor. Nanotube surfaces are bio-functionalized with distinct metalloporphyrin complexes and single-stranded synthetic oligonucleotides (ssDNA), creating unique chemical affinity landscapes that translate complex multi-component gas mixtures into orthogonal electrical resistance deltas. Operating via asynchronous delta-modulation, the custom neuromorphic processor converts continuous sensor conductance kinetics into discrete temporal spike trains, mirroring the lateral inhibition and spike-timing-dependent plasticity (STDP) of the mammalian olfactory bulb. Clinical trial simulations spanning 1,500 patient exhalation profiles across early-stage lung adenocarcinoma, breast carcinoma, and colorectal malignancies demonstrate an unprecedented Stage-1 classification accuracy of 96.4%, a sensitivity of 95.8%, and a specificity of 97.1%, establishing a transformative blueprint for ubiquitous, low-cost point-of-care oncological screening.