TECHNICAL DESCRIPTION 2019-04-16T15:23:28+00:00


In NASAL, state of the art medical imaging processing technology merges with aerospace technology to analyze and study the physical phenomena that take place within our patients’ nasal cavity, thanks to the information obtained from medical imaging (CT).

NASAL~FLOW® is a pioneer integrated system created to study the physiologic behaviour of respiratory airflow, in order to offer a new tool for the medical decision-making process in the treatment of upper airway dysfunctions, which affect over 20% of the World’s population.

The service we offer is fully online, through which health professionals from around the globe can forward radiological DICOM images from their patients and obtain valuable qualitative and/or quantitative analysis of variables such as pressure, velocity, temperature or resistance of the airflow in any given place of the nasal cavity.


Our service’s ultimate goal is to achieve the creation of computational models that faithfully represent real patients. Our technological methodology allows to navigate from the reality of a breathing patient to a computational model in which to intervene and experiment without any risk to our patient, and with all the benefit this process offers us. That is, the goal is to obtain harmlessly and safely the data which, otherwise would only be obtained through hazardous or expensive experimenting.


The analysis process of NASAL~FLOW® it has three very defined stages.


The starting point for our analysis is obtaining a realistic computational model of the nasal cavity. The base for the process are patients CT Scan images, from which, through complex image processing algorithms, we manage to differentiate and separate each internal structure that cannot be identified in the CT scan, in order to discard everything unrelated to the airway. This process is known as “segmentation” and it is of utmost importance for any study of these characteristics, as it is what will really describe in detail the nasal cavity of a given patient.


Once the structures we are interested in have been identified within the CT Scan, the software will create a 3D geometric reconstruction based on the segmented images. The algorithm’s processing mechanism will result in a 3D model of the nasal cavity with many sharp edges that don’t actually exist in the real cavity. To achieve a more realistic image, smoothing algorithms transform the previous image into a new one which truly resembles the interior of the patients airway. Its noteworthy that this phase is interesting in itself, as it will allow the identification of anatomical anomalies as well as the three-dimensional visualization of the airway.


Once the 3D model has been perfectly defined and with the description of the airflow volume, fluid-mechanic equations will be solved using advanced numerical techniques. This process implies the discretization of the geometric volume (process known as “meshing”) to solve the previously mentioned equations in a finite number of points, obtaining the rest by interpolation. The answer comes in form of a series of classical values in numerical simulation of fluid dynamics, such as pressure, velocity, temperature and other parameters further obtained from these, which will result in highly valuable information on the aerodynamic behaviour of the nasal cavity. Moreover, other classical parameters such as nasal resistance and flow rate are also obtained. The latter could previously only be obtained by less precise techniques such as rhinomanometry.

This way our studies will render you not only traditional indicators, which used to be obtained only experimentally with the logical consequences for the patient, but also a considerable amount of complementary and highly accurate information, both in quantity and quality. With this information Phyiscians will achieve a better understanding of the airway behaviour in the specific nasal cavity of a specific patient, thus contributing to a better diagnosis and/or surgical treatment, therefore improving our life quality.