Takahito Miki

Automated Segmentation and Morphometric Analysis of the Human Airway Tree from Multidetector CT Images

Remarkable advances in computed tomography (CT) technology geared our research toward investigating the integrative function of the lung and the development of a database of the airway tree incorporating anatomical and functional data with computational models. As part of this project, we are developing the algorithm to construct an anatomically realistic geometric model of airways from CT images. The basic concept of the algorithm is to segment as many airway trees as possible from CT images and later correct quantified parameters based on CT values. CT images are acquired with a 64-channel multidetector CT, and the airway is then extracted from them by the region-growing method while maintaining connectivity. Using this method, we extracted 428 airways up to the 14th branching generation. Although the airway diameters up to the 4th generation showed good agreement with those reported in an autopsy study, those in later generations were all greater than the reported values because of the limited resolution of the CT images. We corrected the errors in diameters by assessing the relationship between the diameter and median value of Hounsfield unit (HU) intensity of each airway; consequently, the diameters up to generation 8 agreed well with the reported values. Based on these results, we conclude that the use of HU-based correction algorithm combined with rough segmentation can be another way to improve data accuracy in the morphometric analysis of airways from CTs.

Deposition of micrometer particles in pulmonary airways during inhalation and breath holding

We investigated how breath holding increases the deposition of micrometer particles in pulmonary airways, compared with the deposition during inhalation period. A subject-specific airway model with up to thirteenth generation airways was constructed from multi-slice CT images. Airflow and particle transport were simulated by using GPU computing. Results indicate that breath holding effectively increases the deposition of 5μm particles for third to sixth generation (G3-G6) airways. After 10s of breath holding, the particle deposition fraction increased more than 5 times for 5μm particles. Due to a small terminal velocity, 1μm particles only showed a 50% increase in the most efficient case. On the other hand, 10μm particles showed almost complete deposition due to high inertia and high terminal velocity, leading to an increase of 2 times for G3-G6 airways. An effective breath holding time for 5μm particle deposition in G3-G6 airways was estimated to be 4-6s, for which the deposition amount reached 75% of the final deposition amount after 10s of breath holding.

Patient-specific modelling of pulmonary airflow using GPU cluster for the application in medical practice

In this paper, we propose a novel patient-specific method of modelling pulmonary airflow using graphics processing unit (GPU) computation that can be applied in medical practice. To overcome the barriers imposed by computation speed, installation price and footprint to the application of computational fluid dynamics, we focused on GPU computation and the lattice Boltzmann method (LBM). The GPU computation and LBM are compatible due to the characteristics of the GPU. As the optimisation of data access is essential for the performance of the GPU computation, we developed an adaptive meshing method, in which an airway model is covered by isotropic subdomains consisting of a uniform Cartesian mesh. We found that 43 size subdomains gave the best performance. The code was also tested on a small GPU cluster to confirm its performance and applicability, as the price and footprint are reasonable for medical applications.

Image Based Simulation of Pulmonary Airflow Using Multi-Level Voxel Modeling

Chronic Obstructive Pulmonary Disease (COPD) refers to a group of diseases that are characterized by airflow obstruction. Currently, COPD is the fourth leading cause of death worldwide, but fluid dynamics in airways of COPD patients has not been well understood. Multi-slice Computer Tomography (CT) images provide three-dimensional realistic geometry of patient airways. Computational Fluid Dynamics (CFD) analysis using the patient-specific geometry will greatly help the understanding of the mechanism of COPD. However, few studies have performed such a patient-specific pulmonary airflow simulation. Our aim is to develop a patient-specific CFD method applicable to multi-scale airways, involving trachea, bronchi, bronchioles, and alveoli. We propose a CFD method using multi-level voxel modeling of airway geometry, in which voxel size in a local domain is adaptively refined or coarsened to the local flow scale.Copyright

Automated Segmentation and Morphometric Measurement of a Human Airway Tree From Multi-Detector CT Images Toward the Numerical Analysis of Pulmonary Flow Dynamics

Advancement in imaging technologies has shortened scan time of computed-tomography (CT). Recently introduced to a clinical market, 64-detector CT is capable of acquiring 64 simultaneous 0.5-mm slices with each 400-ms gantry revolution, yielding precise isotropic imaging of even peripheral airways within a single breath hold.Copyright