Paper
13 March 2019 Predicting resection volumes within the nasal cavity to improve patients breathing
Author Affiliations +
Abstract
Current investigation techniques (Rhinomanometry, Endoscopy, e.g.) of the nasal cavity are not always able to diagnose a successful surgery outcome to relieve breathing. The presented approach uses medical imaging datasets (i.e. cone beam Computer Tomography) to simulate the flow through the nasal cavity with a Laser Doppler Anemometry (LDA) validated lattice Boltzmann (LB) simulation. In order to find potential surgically relevant points (SRP), the determination of the patient’s LB-simulated pressure drop is used for comparison with a critical pressure drop found by a sensitivity analysis (3 patients with nasal septum deviation, 1 person without breathing problems). Based on SRPs a developed optimizer shapes the nasal cavity. All locations of SRPs in postoperative CT datasets show an increase of the crosssection of the nasal cavity. The difference of cross-section between pre- and optimized nasal cavity in the postoperative CT is smaller than 15%. The optimization result shows good and this method will be validated in a future clinical trial.
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Manuel Berger, Martin Pillei, Andreas Mehrle, Wolfgang Recheis, Florian Kral, Michael Kraxner, and Wolfgang Freysinger "Predicting resection volumes within the nasal cavity to improve patients breathing", Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 1095036 (13 March 2019); https://doi.org/10.1117/12.2512358
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KEYWORDS
Optical spheres

Surgery

Binary data

Computed tomography

Computer simulations

Image segmentation

Laser Doppler velocimetry

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