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Predicting resection volumes within the nasal cavity to improve patients breathing

机译:预测鼻腔内的切除体积,以改善患者呼吸

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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 cross-section 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.
机译:鼻腔的当前调查技术(钻石测量,内窥镜检查,例如,例如,鼻腔并不总能能够诊断成功的手术结果来缓解呼吸。所提出的方法使用医学成像数据集(即锥形光束计算机断层扫描)来模拟通过使用激光多普勒风速(LDA)验证的晶格Boltzmann(LB)仿真的鼻腔的流量。为了发现潜在的手术相关点(SRP),患者的LB模拟压降的测定用于与灵敏度分析发现的临界压降比较(3例鼻中隔偏差,1人没有呼吸问题) 。基于SRPS,开发的优化器形状鼻腔。术后CT数据集中的所有SRP的所有位置都显示出鼻腔的横截面的增加。术后CT在术后CT中预热和优化的鼻腔之间的横截面的差异小于15%。优化结果显示良好,此方法将在未来的临床试验中验证。

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