The effect of nasal shape on the thermal conditioning of inhaled air: Using clinical tomographic data to build a large-scale statistical shape model.

In this paper, we investigate the heating function of the nasal cavity qualitatively, using a high-quality, large-scale statistical shape model. This model consists of a symmetrical and an asymmetrical part and provides a new and unique way of examining changes in nasal heating function resulting from natural variations in nasal shape (as obtained from 100 clinical CT scans). Data collected from patients suffering from different nasal or sinus-related complaints are included. Parameterized models allow us to investigate the effect of continuous deviations in shape from the mean nasal cavity. This approach also enables us to avoid many of the compounded effects on flow and heat exchange, which one would encounter when comparing different patient-specific models. The effects of global size, size-related features, and turbinate size are investigated using the symmetrical shape model. The asymmetrical model is used to investigate different types of septal deviation using Mladina's classification. The qualitative results are discussed and compared with findings from the existing literature.

Matlab® toolbox for semi-automatic segmentation of the human nasal cavity based on active shape modeling.

The nose is a complex and important organ with a multitude of functions. Computational fluid dynamics (CFD) has been shown to be a valuable tool to obtain a better understanding of the functioning of the nose. CFD simulations require a surface geometry, which is constructed from tomographic data. This can be a very time-consuming task when one chooses to exclude the sinuses from the simulation domain, which in general keeps the size of the CFD model more manageable. In this work, an approach for the semi-automatic construction of the human nasal cavity is presented. In the first part, limited manual interaction is needed to create a coarse surface model. In the next part, this result is further refined based on the combination of active shape modeling with elastic surface deformation. The different steps are bundled in a Matlab toolbox with a graphical interface which guides the user. This interface allows easy manipulation of the data during intermediate steps, and also allows manual adjustments of the reconstructed nasal surface at the end. Two results are shown, and the approach and its precision are discussed. These results demonstrated that the followed approach can be used for the semi-automatic segmentation of a human nasal cavity from tomographic data, substantially reducing the amount of operator time.

High quality statistical shape modelling of the human nasal cavity and applications.

The human nose is a complex organ that shows large morphological variations and has many important functions. However, the relation between shape and function is not yet fully understood. In this work, we present a high quality statistical shape model of the human nose based on clinical CT data of 46 patients. A technique based on cylindrical parametrization was used to create a correspondence between the nasal shapes of the population. Applying principal component analysis on these corresponded nasal cavities resulted in an average nasal geometry and geometrical variations, known as principal components, present in the population with a high precision. The analysis led to 46 principal components, which account for 95% of the total geometrical variation captured. These variations are first discussed qualitatively, and the effect on the average nasal shape of the first five principal components is visualized. Hereafter, by using this statistical shape model, two application examples that lead to quantitative data are shown: nasal shape in function of age and gender, and a morphometric analysis of different anatomical regions. Shape models, as the one presented here, can help to get a better understanding of nasal shape and variation, and their relationship with demographic data.

3D morphometric analysis of the human incudomallear complex using clinical cone-beam CT.

Human middle ears show large morphological variations. This could affect our perception of hearing and explain large variation in experimentally obtained transfer functions. Most morphological studies focus on capturing variation by using landmarks on cadaveric temporal bones. We present statistical shape analysis based on clinical cone beam CT (CBCT) scans of 100 patients. This allowed us to include surface information on the incudomallear (IM) complex (joint, ligaments and tendon not included) of 123 healthy ears with a scanning resolution of 150 µm and without a priori assumptions. Statistical shape modeling yields an average geometry for the IM complex and the variations present in the population with a high precision. Mean values, variation and correlations among anatomical features (length of manubrium, combined length of malleus head and neck, lengths of incus long and short process, enclosing angles, ossicular lever ratio, incudomallear angle, and principal moments of inertia) are reported and compared to results from the literature. Most variation is found in overall size and the angle between incus and malleus. The compact representation provided by statistical shape modeling is demonstrated and its benefits for surface modeling are discussed.