The Audible Human Project: Geometric and Acoustic Modeling in The Airways, Lungs and Torso
thesisposted on 27.07.2018 by Brian Henry
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Mechanical wave motion (acoustics) over multiple temporal and spatial scales pervades existing and emerging diagnostic and therapeutic medical technology for every organ and region in the body. Diagnostic approaches span from auscultation (body sound analysis) to emerging dynamic elastography methods based on magnetic resonance, ultrasound or photonics for quantitatively imaging mechanical properties. Therapeutic examples include acoustic removal of excess airway secretions to accelerated (soft and hard) tissue repair via acoustic stimulation from hertz to millions of hertz. Further advances in diagnostic and therapeutic capability are hampered by our limited fundamental understanding of acoustic wave phenomena – reflection, scattering, absorption – in the complex heterogeneous anisotropic medium that is the human body. Nowhere else is this more evident than in the lungs, the most acoustically complex region where different pathological conditions lead to changes that uniquely alter acoustic behavior over multiple scales, providing a rich but woefully untapped source of noninvasively obtainable disease biomarkers and therapeutic possibilities. Moreover, the lungs are especially challenging for conventional medical imaging approaches based on ultrasound, magnetic resonance or ionizing radiation; consequently, many diseases of the lung have high morbidity and mortality. The purpose of the Audible Human Project (AHP) (NIH EB012142) has been to develop a computer simulation model of sound propagation in the human body to enable advances in therapy and diagnostics, as well as medical education. The AHP also seeks to accelerate the translational R&D process by creating in silico acoustic animal models that could replace the need for some live animal studies. A modified 1D waveguide is applied on a 3D human conducting airway geometry to develop an acoustic model of sound transmission between healthy and pathologic (pulmonary fibrosis, bronchoconstriction and pulmonary infiltrate) virtual patients. The waveguide is then used as a basis for numerical Boundary Element simulations, where sound transmission on the lung surface is estimated using an array of monopoles placed and with strength calculated from airway analytical models. Source localization algorithms are then used to predict acoustic source locations. Quantitative differences in airway acoustic pressure, airway wall radial velocity and lung surface centroid normal velocity between healthy and pathologic virtual patients give rise to possible noninvasive modes of diagnosis for lung and airway pathologies.