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Updated: Aug 14, 2026

3D Cine Magnetic Resonance Imaging of Respiratory Motion in Mechanically Ventilated Mice and Rats
Published on: September 19, 2025
Respiratory pyramid interface (RPI): a conceptual three-dimensional pyramid model for visualization of lung mechanics
1Department of Internal Medicine, Division of Intensive Care, Bursa Uludağ University Faculty of Medicine, Bursa, Türkiye.
Abstract:
Mechanical ventilation is a life-saving intervention in critically ill patients; however, the real-time integration of its key physiological determinants elastic load, resistive load, and obstructive components remains cognitively demanding at the bedside. Current monitoring approaches present these parameters in fragmented formats, which may limit rapid interpretation. The Respiratory Pyramid Interface (RPI) is a conceptual, hypothesis-generating framework that integrates the fundamental variables of respiratory mechanics flow (F), pressure (P), and volume (V) into a unified three-dimensional geometric model. Within this structure, resistive, elastic, and obstructive components are represented along the pyramid edges, while derived indices including mechanical power (MP), driving pressure (DP), static compliance (Cstat), the Pyramid Asymmetry Index (PAI), and a pressure-based surrogate of the expiratory time constant (τ_est) are dynamically mapped. The framework was demonstrated across eleven simulated pathophysiological scenarios, each producing distinct geometric patterns corresponding to specific mechanical phenotypes. Importantly, RPI does not introduce new physiological variables but offers a structured visual integration of routinely available ventilator data, intended to support hypothesis generation, education, and pattern recognition rather than to provide direct treatment guidance. Limitations of the underlying single-compartment model including regional lung heterogeneity, pendelluft, spontaneous respiratory effort, and elevated neural respiratory drive are acknowledged. Prospective validation is required before the proposed indices can be considered for clinical decision support.
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