3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells.

AIMS:The 3D geometry of individual vascular smooth muscle cells (VSMCs), which are essential for understanding the mechanical function of blood vessels, are currently not available. This paper introduces a new 3D segmentation algorithm to determine VSMC morphology and orientation. METHODS AND RESULT...

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Main Authors: Tong Luo, Huan Chen, Ghassan S Kassab
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4755581?pdf=render
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spelling doaj-09305db150554b9a80067a8ecb9e3d582020-11-25T01:16:12ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01112e014727210.1371/journal.pone.01472723D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells.Tong LuoHuan ChenGhassan S KassabAIMS:The 3D geometry of individual vascular smooth muscle cells (VSMCs), which are essential for understanding the mechanical function of blood vessels, are currently not available. This paper introduces a new 3D segmentation algorithm to determine VSMC morphology and orientation. METHODS AND RESULTS:A total of 112 VSMCs from six porcine coronary arteries were used in the analysis. A 3D semi-automatic segmentation method was developed to reconstruct individual VSMCs from cell clumps as well as to extract the 3D geometry of VSMCs. A new edge blocking model was introduced to recognize cell boundary while an edge growing was developed for optimal interpolation and edge verification. The proposed methods were designed based on Region of Interest (ROI) selected by user and interactive responses of limited key edges. Enhanced cell boundary features were used to construct the cell's initial boundary for further edge growing. A unified framework of morphological parameters (dimensions and orientations) was proposed for the 3D volume data. Virtual phantom was designed to validate the tilt angle measurements, while other parameters extracted from 3D segmentations were compared with manual measurements to assess the accuracy of the algorithm. The length, width and thickness of VSMCs were 62.9±14.9 μm, 4.6±0.6 μm and 6.2±1.8 μm (mean±SD). In longitudinal-circumferential plane of blood vessel, VSMCs align off the circumferential direction with two mean angles of -19.4±9.3° and 10.9±4.7°, while an out-of-plane angle (i.e., radial tilt angle) was found to be 8±7.6° with median as 5.7°. CONCLUSIONS:A 3D segmentation algorithm was developed to reconstruct individual VSMCs of blood vessel walls based on optical image stacks. The results were validated by a virtual phantom and manual measurement. The obtained 3D geometries can be utilized in mathematical models and leads a better understanding of vascular mechanical properties and function.http://europepmc.org/articles/PMC4755581?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Tong Luo
Huan Chen
Ghassan S Kassab
spellingShingle Tong Luo
Huan Chen
Ghassan S Kassab
3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells.
PLoS ONE
author_facet Tong Luo
Huan Chen
Ghassan S Kassab
author_sort Tong Luo
title 3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells.
title_short 3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells.
title_full 3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells.
title_fullStr 3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells.
title_full_unstemmed 3D Reconstruction of Coronary Artery Vascular Smooth Muscle Cells.
title_sort 3d reconstruction of coronary artery vascular smooth muscle cells.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description AIMS:The 3D geometry of individual vascular smooth muscle cells (VSMCs), which are essential for understanding the mechanical function of blood vessels, are currently not available. This paper introduces a new 3D segmentation algorithm to determine VSMC morphology and orientation. METHODS AND RESULTS:A total of 112 VSMCs from six porcine coronary arteries were used in the analysis. A 3D semi-automatic segmentation method was developed to reconstruct individual VSMCs from cell clumps as well as to extract the 3D geometry of VSMCs. A new edge blocking model was introduced to recognize cell boundary while an edge growing was developed for optimal interpolation and edge verification. The proposed methods were designed based on Region of Interest (ROI) selected by user and interactive responses of limited key edges. Enhanced cell boundary features were used to construct the cell's initial boundary for further edge growing. A unified framework of morphological parameters (dimensions and orientations) was proposed for the 3D volume data. Virtual phantom was designed to validate the tilt angle measurements, while other parameters extracted from 3D segmentations were compared with manual measurements to assess the accuracy of the algorithm. The length, width and thickness of VSMCs were 62.9±14.9 μm, 4.6±0.6 μm and 6.2±1.8 μm (mean±SD). In longitudinal-circumferential plane of blood vessel, VSMCs align off the circumferential direction with two mean angles of -19.4±9.3° and 10.9±4.7°, while an out-of-plane angle (i.e., radial tilt angle) was found to be 8±7.6° with median as 5.7°. CONCLUSIONS:A 3D segmentation algorithm was developed to reconstruct individual VSMCs of blood vessel walls based on optical image stacks. The results were validated by a virtual phantom and manual measurement. The obtained 3D geometries can be utilized in mathematical models and leads a better understanding of vascular mechanical properties and function.
url http://europepmc.org/articles/PMC4755581?pdf=render
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