P9. Cinemanography – Challenges and potentials of fusing manometric and fluoroscopic imaging. Issue 8 (August 2021) - Bernhard, L.; Gassert, F.; Fingerle, A.; Feußner, H.; Jell, A.
Abstract : Introduction . Dysphagia affects 1 of 6 adults during their lifetime [1]. There are both benign and malignant forms of dysphagia, commonly caused by esophageal, oropharyngeal and neuromuscular diseases. Even in its benign forms, dysphagia can have a significant impact on quality of life. In current practice, a combination of endoscopy, esophageal manometry and fluoroscopic x-ray cinematography has been established for diagnostics. These modalities are applied in sequential order and provide quite different views on the issue. We propose a novel approach for time-synchronizing and visualizing manometric and cinematographic data to provide an intuitive means for diagnosing oropharyngeal dysphagia and to gain an enhanced understanding of the functional processes in the highly dynamic oropharyngoesophageal region. Materials and Methods. We used a state-of-the-art manometric probe with 36 pressure sensors for gathering the manometric data. The cinematography was recorded simultaneously with an x-ray machine. Since both data sets had to be recorded on separate devices (PC and x-ray machine) with individual clocks, we developed a method for determining the time difference between both devices: We placed a stamp mechanism in the radiologic frame that is able to actuate one of the manometry probe"s sensors and thus creates a noticeable stimulus in both manometric and radiologic data. For both data sets, we extracted the timestamps of the exact frame when this stimulus begins and calculated the time difference. This time difference was later used to precisely time-synchronize manometric and radiologic data gathered from the study participant. Within the x-ray frames we detected the sensor positions of the manometric probe and overlayed the manometric data using a well-established color-coded visualization for high-resolution manometry [2]. Results and Discussion. Our sensor detection algorithm yielded robust results for well-exposed radiologic images, though we experienced difficulties in regions where the sensor geometry blends into the background, especially around the mandibular corpus and angelus. By fitting a cubic b-spline through all successfully detected sensors, we were able to effectively bridge gaps in most cases (Fig. 1). We showed the final visualization to experienced examiners as well as novices and received overall positive feedback regarding the intuitiveness of our visualization. According to the participants, this new form of presenting diagnostic data enhances the understanding of disorders and of both anatomy and physiologic motility. It is especially helpful for visualizing pressure changes and probe movement in the highly dynamic oropharyngoesophageal region. Refernces [1] Adkins, Christopher, et al. (2020); DOI: https://doi.org/10.1016/j.cgh.2019.10.029. [2] R. Yadlapati (2017); PMID: 28539845. Fig. 1. Result of sensor detection and spline fitting.