Statistical Shape Modelling of the Nasosinusal Anatomy

Michele Bertolini; Silvia Tonghini; Marco Rossoni; Marina Carulli; Susanne Weise; Christian Jan Baldus; Giorgio Colombo; Monica Bordegoni

arXiv · 2510.09713

Statistical Shape Modelling of the Nasosinusal Anatomy

Michele Bertolini·Silvia Tonghini·Marco Rossoni·Marina Carulli·Susanne Weise·Christian Jan Baldus·Giorgio Colombo·Monica Bordegoni

View original source ↗Read source document ↗Export metadata ↓

Abstract

The human nose exhibits a huge variation in shape among individuals. All these variants alter the airflow through the nasal cavity and can impact how we smell odors. To acquire a better understanding of physiological and pathological functioning, it is important to study the effects of these modifications. SSM, or Statistical Shape Modelling, is a widely used methodology for considering morphological differences within a population. In the literature, only a few studies analyze nasal anatomy in its entirety, including paranasal sinuses, whose segmentation is particularly challenging due to their complexity and variability. This work aims at creating a highly accurate SSM for the nasosinusal complex. A traditional, greyscale thresholding-based segmentation approach was chosen, relying on Mimics software (Leuven, Belgium). 40 computed tomography (CT) datasets were considered. After segmentation, post-processing was performed to obtain watertight meshes using 3-Matic software (Leuven, Belgium), which was also used for the SSM generation. The generated model shows all relevant landmarks that typically characterize a nasosinual complex. 32 different modes are needed to explain 95% of the total variance. As a preliminary output, this study showed the feasibility and consistency of a statistical model of the nasosinusal anatomy. However, additional studies involving a larger sample size and a more robust validation process could be conducted.

Explore related subjects

physics.med-ph physics.class-ph

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Michele Bertolini, Silvia Tonghini, Marco Rossoni, Marina Carulli, Susanne Weise, Christian Jan Baldus, Giorgio Colombo, Monica Bordegoni. 2025-10-10. Statistical Shape Modelling of the Nasosinusal Anatomy. https://arxiv.org/abs/2510.09713

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Prediction of biological radiation effects based on ionization clusters (nanodosimetry)

This article reviews approaches that link the formation of ionization clusters in nanometric volumes to radiobiological effectiveness. The corresponding models were developed as the field of nanodosimetry developed. Some address early biological radiation effects, such as DNA damage, while most aim to predict cell survival or inactivation. The models also differ in the nanodosimetric quantities considered, with many based on the probability distribution of ionization cluster formation in a single target. Some models account for the synergistic effects of pairs of ionization clusters formed in different targets. Several models feature macroscopic aggregation frameworks based on particle fluence, which are proposed for use in radiotherapy treatment planning, particularly in ion-beam radiotherapy. The models are presented here using harmonized terminology and notation for nanodosimetric quantities. An extension of the conceptual framework of nanodosimetry is also discussed. This extension transitions from a target-centered description to a track-centered description. It also introduces nanodosimetry-based analogs of dosimetric concepts, such as dose and linear energy transfer. This paper traces and summarizes the historical development of nanodosimetry-based biological effect models and discusses conceptual aspects of the models to reveal their underlying assumptions and the extent to which they are mechanistic or merely elucidate correlations. Eventually, an attempt is made to identify the key open questions in this field that still need to be addressed.

physics.med-ph↗

arXiv2026

Contextual Cellular Growth (ConCeG) of neural cells for realistic grey matter tissue generation for diffusion MRI simulations

Accurate interpretation of diffusion magnetic resonance imaging (dMRI) signals in grey matter (GM) remains challenging due to the complex, heterogeneous, and densely packed cellular environment. Numerical phantoms provide a controlled framework for investigating the relationship between microstructure and diffusion signals, yet existing approaches often lack the morphological realism and multi-cellular organisation required to faithfully represent GM tissue. In this work, we introduce Contextual Cellular Growth (ConCeG), a generative framework for creating individual cells or constructing dense, three-dimensional, multi-cellular GM substrates informed by real neuronal and glial morphologies. The method combines topological neuron synthesis with a spatially constrained growth network, allowing for the controlled generation of heterogeneous cellular environments with realistic intra- and extracellular compartments. Synthetic cells are generated using morphological and topological characteristics derived from biological reconstructions. We validate the framework through comparisons of structural features with real cellular data, demonstrating strong agreement in branch order, length, angle, and tortuosity distributions. Power spectrum analysis further shows that both intracellular compartments reproduce the spatial correlations observed in biological tissue. Together, these results show ConCeG provides a biologically grounded framework for generating grey matter substrates suitable for large scale diffusion MRI simulation.

physics.med-ph↗

arXiv2026

A wearable, stretchable radio-frequency coil for extremity imaging in low-field MRI systems

Purpose: To develop a wearable, stretchable radio-frequency (RF) coil that conforms to the extremities and improves the filling factor in low-field MRI. Methods: A stretchable solenoid RF coil was fabricated by stitching a sinusoidally arranged Litz-wire conductor onto an elastic textile. The coil was compared with four rigid coils, including two routinely used designs and two prototypes designed to isolate the effects of conductor material and stretchability. Performance was characterized through quality-factor, loading-factor, transmit-efficiency, and image-based signal-to-noise ratio (SNR) measurements. Phantom and in-vivo knee experiments for one volunteer were performed using two portable MRI systems operating at 3.53 and 3.04 MHz. Results: The electrical performance of the selected Litz wire decreased with increasing frequency, becoming a slight disadvantage at 3.53 MHz. Nevertheless, the stretchable coil provided the highest phantom SNR in both systems, exceeding that of the best-performing rigid coil by approximately 8 % at 3.53 MHz and 20 % at 3.04 MHz. In vivo, its global SNR was 5 % lower than that of the best rigid coil at 3.53 MHz and 19 % higher at 3.04 MHz. Compared with the larger rigid coil required when knee positioning is constrained, the corresponding SNR improvements were approximately 18 % and 80 %. Conclusion: Anatomical conformity can compensate for the frequency-dependent electrical limitations of Litz wire in stretchable low-field RF coils. The proposed design provided SNR comparable to or greater than the best rigid designs while facilitating coil placement in subjects for whom smaller rigid coils may be impractical.

physics.med-ph↗