Computer-­Assisted  Coronary  CT  Angiography  Analysis : From  Software  Development  to  Clinical  Application

Advances in coronary Computed Tomography Angiography (CTA) have resulted in a boost in the use of this new technique in recent years, creating a challenge for radiologists due to the increasing number of exams and the large amount of data for each patient. The main goal of this study was to develop...

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Main Author: Wang, Chunliang
Format: Doctoral Thesis
Language:English
Published: Linköpings universitet, Medicinsk radiologi 2011
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-68705
http://nbn-resolving.de/urn:isbn:978-91-7393-191-5
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spelling ndltd-UPSALLA1-oai-DiVA.org-liu-687052013-10-22T05:16:19ZComputer-­Assisted  Coronary  CT  Angiography  Analysis : From  Software  Development  to  Clinical  ApplicationengWang, ChunliangLinköpings universitet, Medicinsk radiologiLinköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIVLinköpings universitet, HälsouniversitetetLinköping : Linköping University Electronic Press2011Vessel segmentationcoronary CTAfuzzy connectednesslevel setcoronary artery diseaseImage analysisBildanalysRadiological researchRadiologisk forskningAdvances in coronary Computed Tomography Angiography (CTA) have resulted in a boost in the use of this new technique in recent years, creating a challenge for radiologists due to the increasing number of exams and the large amount of data for each patient. The main goal of this study was to develop a computer tool to facilitate coronary CTA analysis by combining knowledge of medicine and image processing, and to evaluate the performance in clinical settings. Firstly, a competing fuzzy connectedness tree algorithm was developed to segment the coronary arteries and extract centerlines for each branch. The new algorithm, which is an extension of the “virtual contrast injection” (VC) method, preserves the low-density soft tissue around the artery, and thus reduces the possibility of introducing false positive stenoses during segmentation. Visually reasonable results were obtained in clinical cases. Secondly, this algorithm was implemented in open source software in which multiple visualization techniques were integrated into an intuitive user interface to facilitate user interaction and provide good over­views of the processing results. An automatic seeding method was introduced into the interactive segmentation workflow to eliminate the requirement of user initialization during post-processing. In 42 clinical cases, all main arteries and more than 85% of visible branches were identified, and testing the centerline extraction in a reference database gave results in good agreement with the gold standard. Thirdly, the diagnostic accuracy of coronary CTA using the segmented 3D data from the VC method was evaluated on 30 clinical coronary CTA datasets and compared with the conventional reading method and a different 3D reading method, region growing (RG), from a commercial software. As a reference method, catheter angiography was used. The percentage of evaluable arteries, accuracy and negative predictive value (NPV) for detecting stenosis were, respectively, 86%, 74% and 93% for the conventional method, 83%, 71% and 92% for VC, and 64%, 56% and 93% for RG. Accuracy was significantly lower for the RG method than for the other two methods (p<0.01), whereas there was no significant difference in accuracy between the VC method and the conventional method (p = 0.22). Furthermore, we developed a fast, level set-based algorithm for vessel segmentation, which is 10-20 times faster than the conventional methods without losing segmentation accuracy. It enables quantitative stenosis analysis at interactive speed. In conclusion, the presented software provides fast and automatic coron­ary artery segmentation and visualization. The NPV of using only segmented 3D data is as good as using conventional 2D viewing techniques, which suggests a potential of using them as an initial step, with access to 2D reviewing techniques for suspected lesions and cases with heavy calcification. Combining the 3D visualization of segmentation data with the clinical workflow could shorten reading time. Doctoral thesis, comprehensive summaryinfo:eu-repo/semantics/doctoralThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-68705urn:isbn:978-91-7393-191-5Linköping University Medical Dissertations, 0345-0082 ; 1237application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Doctoral Thesis
sources NDLTD
topic Vessel segmentation
coronary CTA
fuzzy connectedness
level set
coronary artery disease
Image analysis
Bildanalys
Radiological research
Radiologisk forskning
spellingShingle Vessel segmentation
coronary CTA
fuzzy connectedness
level set
coronary artery disease
Image analysis
Bildanalys
Radiological research
Radiologisk forskning
Wang, Chunliang
Computer-­Assisted  Coronary  CT  Angiography  Analysis : From  Software  Development  to  Clinical  Application
description Advances in coronary Computed Tomography Angiography (CTA) have resulted in a boost in the use of this new technique in recent years, creating a challenge for radiologists due to the increasing number of exams and the large amount of data for each patient. The main goal of this study was to develop a computer tool to facilitate coronary CTA analysis by combining knowledge of medicine and image processing, and to evaluate the performance in clinical settings. Firstly, a competing fuzzy connectedness tree algorithm was developed to segment the coronary arteries and extract centerlines for each branch. The new algorithm, which is an extension of the “virtual contrast injection” (VC) method, preserves the low-density soft tissue around the artery, and thus reduces the possibility of introducing false positive stenoses during segmentation. Visually reasonable results were obtained in clinical cases. Secondly, this algorithm was implemented in open source software in which multiple visualization techniques were integrated into an intuitive user interface to facilitate user interaction and provide good over­views of the processing results. An automatic seeding method was introduced into the interactive segmentation workflow to eliminate the requirement of user initialization during post-processing. In 42 clinical cases, all main arteries and more than 85% of visible branches were identified, and testing the centerline extraction in a reference database gave results in good agreement with the gold standard. Thirdly, the diagnostic accuracy of coronary CTA using the segmented 3D data from the VC method was evaluated on 30 clinical coronary CTA datasets and compared with the conventional reading method and a different 3D reading method, region growing (RG), from a commercial software. As a reference method, catheter angiography was used. The percentage of evaluable arteries, accuracy and negative predictive value (NPV) for detecting stenosis were, respectively, 86%, 74% and 93% for the conventional method, 83%, 71% and 92% for VC, and 64%, 56% and 93% for RG. Accuracy was significantly lower for the RG method than for the other two methods (p<0.01), whereas there was no significant difference in accuracy between the VC method and the conventional method (p = 0.22). Furthermore, we developed a fast, level set-based algorithm for vessel segmentation, which is 10-20 times faster than the conventional methods without losing segmentation accuracy. It enables quantitative stenosis analysis at interactive speed. In conclusion, the presented software provides fast and automatic coron­ary artery segmentation and visualization. The NPV of using only segmented 3D data is as good as using conventional 2D viewing techniques, which suggests a potential of using them as an initial step, with access to 2D reviewing techniques for suspected lesions and cases with heavy calcification. Combining the 3D visualization of segmentation data with the clinical workflow could shorten reading time.
author Wang, Chunliang
author_facet Wang, Chunliang
author_sort Wang, Chunliang
title Computer-­Assisted  Coronary  CT  Angiography  Analysis : From  Software  Development  to  Clinical  Application
title_short Computer-­Assisted  Coronary  CT  Angiography  Analysis : From  Software  Development  to  Clinical  Application
title_full Computer-­Assisted  Coronary  CT  Angiography  Analysis : From  Software  Development  to  Clinical  Application
title_fullStr Computer-­Assisted  Coronary  CT  Angiography  Analysis : From  Software  Development  to  Clinical  Application
title_full_unstemmed Computer-­Assisted  Coronary  CT  Angiography  Analysis : From  Software  Development  to  Clinical  Application
title_sort computer-­assisted  coronary  ct  angiography  analysis : from  software  development  to  clinical  application
publisher Linköpings universitet, Medicinsk radiologi
publishDate 2011
url http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-68705
http://nbn-resolving.de/urn:isbn:978-91-7393-191-5
work_keys_str_mv AT wangchunliang computerassistedcoronaryctangiographyanalysisfromsoftwaredevelopmenttoclinicalapplication
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