Alsaker Melody, Cárdenas Diego Armando Cardona, Furuie Sérgio Shiguemi, Mueller Jennifer L
Department of Mathematics; Gonzaga University, Spokane, WA 99258 USA.
Escola Politécnica de Universidade de São Paulo, Brazil.
J Comput Appl Math. 2021 Oct 15;395. doi: 10.1016/j.cam.2021.113591. Epub 2021 Apr 20.
For medical professionals caring for patients undergoing mechanical ventilation due to respiratory failure, the ability to quickly and safely obtain images of pulmonary function at the patient's bedside would be highly desirable. Such images could be used to provide early warnings of developing pulmonary pathologies in real time, thereby reducing the incidence of complications and improving patient outcomes. Electrical impedance tomography (EIT) and low-frequency ultrasound computed tomography (USCT) are two imaging techniques with the potential to provide real-time non-ionizing pulmonary monitoring in the ICU setting, and each method has its own unique advantages as well as drawbacks. In this work, we describe a new algorithm for a system in which the strengths of the two modalities are combined in a complementary fashion. Specifically, preliminary reconstructions from each modality are used as priors to stabilize subsequent reconstructions, providing improved spatial resolution, sharper organ boundaries, and enhanced appearance of pathologies and other features. Results are validated using three numerically simulated thoracic phantoms representing pulmonary pathologies.
对于护理因呼吸衰竭而接受机械通气患者的医学专业人员来说,能够在患者床边快速、安全地获取肺功能图像将是非常理想的。这样的图像可用于实时提供肺部病变发展的早期预警,从而降低并发症的发生率并改善患者预后。电阻抗断层成像(EIT)和低频超声计算机断层扫描(USCT)是两种有潜力在重症监护病房(ICU)环境中提供实时非电离肺部监测的成像技术,且每种方法都有其独特的优点和缺点。在这项工作中,我们描述了一种新算法,用于一个将两种模式的优势以互补方式结合的系统。具体而言,将来自每种模式的初步重建用作先验信息,以稳定后续重建,从而提供更高的空间分辨率、更清晰的器官边界以及病变和其他特征的更清晰显示。使用三个代表肺部病变的数值模拟胸部模型对结果进行了验证。