Extracting Cross-Sectional Clinical Images Based on Their Principal Axes of Inertia.

Yuzhou Fan,Yifang Fan,Djordje Antonijevic,Marija Djuric,Zhiyu Li,Petar Milenkovic,Liangping Luo,Yueyang Sun,Ruining Li

doi:10.1155/2017/1468596

Abstract

Cross-sectional imaging is considered the gold standard in diagnosing a range of diseases. However, despite its widespread use in clinical practice and research, no widely accepted method is available to reliably match cross-sectional planes in several consecutive scans. This deficiency can impede comparison between cross-sectional images and ultimately lead to misdiagnosis. Here, we propose and demonstrate a method for finding the same imaging plane in images obtained during separate scanning sessions. Our method is based on the reconstruction of a “virtual organ” from which arbitrary cross-sectional images can be extracted, independent of the axis orientation in the original scan or cut; the key is to establish unique body coordinates of the organ from its principal axes of inertia. To verify our method a series of tests were performed, and the same cross-sectional plane was successfully extracted. This new approach offers clinicians access, after just a single scanning session, to the morphology and structure of a lesion through cross-sectional images reconstructed along arbitrary axes. It also aids comparable detection of morphological and structural changes in the same imaging plane from scans of the same patient taken at different times—thus potentially reducing the misdiagnosis rate when cross-sectional images are interpreted.

Highlights

In vivo and ex vivo cross section image (CSI) (defined here as encompassing magnetic resonance imaging (MRI), computed tomography (CT), and any images of serial sections of human organ) is taking an increasingly important role in medicine
When we tried to improve the accuracy and precision of an principal axes of inertia (PAI) oriented CSIs analysis, we utilized the PAI as the body coordinates of a 3D organ image and faced a new problem: since the multiplication of transformation matrices operating on a matrix was not commutative [35], the iteration times to calculate the PAI were uncertain or even unpredictable
The key issue in our study was to test whether the original morphology and structure of an organ will be preserved after it is reconstructed based on its unique body coordinates

Summary

Introduction

In vivo and ex vivo cross section image (CSI) (defined here as encompassing magnetic resonance imaging (MRI), computed tomography (CT), and any images of serial sections of human organ) is taking an increasingly important role in medicine. The analysis of CSIs is an essential step in a broad range of studies [4,5,6,7,8,9]. Many studies [10,11,12,13,14] have shown that the analysis of CSIs is of key importance when describing and predicting morphological changes in organs. Since 1750 when Euler first discovered and defined principal axes of inertia (PAI), it has been used to establish a body coordinate system for different methods [15,16,17,18,19,20,21]. PAI has been used to define an automated patient-specific anatomical coordinate system for the distal femur and proximal tibia [22], to characterize the geometry of the carpal bones [23], to investigate the rotational variations of temporomandibular joint trajectories [24], to measure the anisotropy of mandible’s trabecular bone [25], and to calculate the bone stresses adjacent to dental implants [26]

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