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Computer-­Assisted  Coronary  CT  Angiography  Analysis: From  Software  Development  to  Clinical  Application
Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Faculty of Health Sciences. (Örjan Smedby)ORCID iD: 0000-0002-0442-3524
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2011. , 57 p.
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1237
Keyword [en]
Vessel segmentation, coronary CTA, fuzzy connectedness, level set, coronary artery disease
National Category
Computer Vision and Robotics (Autonomous Systems) Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:liu:diva-68705ISBN: 978-91-7393-191-5OAI: oai:DiVA.org:liu-68705DiVA: diva2:419941
Public defence
2011-06-07, Wrannesalen, CMIV, Universitetssjukhuset, Campus US, Linköpings univeristet, Linköping, 09:00 (English)
Opponent
Supervisors
Available from: 2011-06-07 Created: 2011-05-30 Last updated: 2013-10-21Bibliographically approved
List of papers
1. Coronary Artery Segmentation and Skeletonization Based on Competing Fuzzy Connectedness Tree
Open this publication in new window or tab >>Coronary Artery Segmentation and Skeletonization Based on Competing Fuzzy Connectedness Tree
2007 (English)In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007: 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part I / [ed] Nicholas Ayache, Sébastien Ourselin, Anthony Maeder, Springer Berlin/Heidelberg, 2007, Vol. 4791, 311-318 p.Conference paper (Refereed)
Abstract [en]

We propose a new segmentation algorithm based on competing fuzzy connectedness theory, which is then used for visualizing coronary arteries in 3D CT angiography (CTA) images. The major difference compared to other fuzzy connectedness algorithms is that an additional data structure, the connectedness tree, is constructed at the same time as the seeds propagate. In preliminary evaluations, accurate result have been achieved with very limited user interaction. In addition to improving computational speed and segmentation results, the fuzzy connectedness tree algorithm also includes automated extraction of the vessel centerlines, which is a promising approach for creating curved plane reformat (CPR) images along arteries’ long axes.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2007
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 4791
Keyword
segmentation - fuzzy connectedness tree - centerline extraction - skeletonization - coronary artery - CT angiography
National Category
Radiology, Nuclear Medicine and Medical Imaging Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-17816 (URN)10.1007/978-3-540-75757-3_38 (DOI)000250916000038 ()978-3-540-75756-6 (print) (ISBN)
Conference
10th International Conference on Medical Image Computing and Computer-Assisted Intervention, Brisbane, Australia, October 29 - November 2, 2007
Note

The original publication is available at www.springerlink.com: Chunliang Wang and Örjan Smedby, Coronary Artery Segmentation and Skeletonization Based on Competing Fuzzy Connectedness Tree, 2007, Medical Image Computing and Computer-Assisted Intervention, (4791), 311-318. http://dx.doi.org/10.1007/978-3-540-75757-3_38 Copyright: Springer-verlag http://www.springerlink.com/

Available from: 2009-04-21 Created: 2009-04-21 Last updated: 2014-09-24Bibliographically approved
2. An interactive software module for visualizing coronary arteries in CT angiography
Open this publication in new window or tab >>An interactive software module for visualizing coronary arteries in CT angiography
2008 (English)In: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, Vol. 3, no 1-2, 11-18 p.Article in journal (Refereed) Published
Abstract [en]

A new software module for coronary artery segmentation and visualization in CT angiography (CTA) datasets is presented, which aims to interactively segment coronary arteries and visualize them in 3D with maximum intensity projection (MIP) and volume rendering (VRT).

Materials and Methods:  The software was built as a plug-in for the open-source PACS workstation OsiriX. The main segmentation function is based an optimized “virtual contrast injection” algorithm, which uses fuzzy connectedness of the vessel lumen to separate the contrast-filled structures from each other. The software was evaluated in 42 clinical coronary CTA datasets acquired with 64-slice CT using isotropic voxels of 0.3–0.5 mm.

Results:  The median processing time was 6.4 min, and 100% of main branches (right coronary artery, left circumflex artery and left anterior descending artery) and 86.9% (219/252) of visible minor branches were intact. Visually correct centerlines were obtained automatically in 94.7% (321/339) of the intact branches.

Conclusion:  The new software is a promising tool for coronary CTA post-processing providing good overviews of the coronary artery with limited user interaction on low-end hardware, and the coronary CTA diagnosis procedure could potentially be more time-efficient than using thin-slab technique.

Place, publisher, year, edition, pages
Heidelberg/Berlin: Springer, 2008
Keyword
Coronary vessels - Tomography, spiral computed - Algorithms - Radiographic image interpretation, computer-assisted
National Category
Radiology, Nuclear Medicine and Medical Imaging Cardiac and Cardiovascular Systems Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-17817 (URN)10.1007/s11548-008-0160-6 (DOI)
Note

The original publication is available at www.springerlink.com: Chunliang Wang, Hans Frimmel, Anders Persson and Örjan Smedby, An interactive software module for visualizing coronary arteries in CT angiography, 2008, International Journal of Computer Assisted Radiology and Surgery, (3), 1-2, 11-18. http://dx.doi.org/10.1007/s11548-008-0160-6 Copyright: Springer Science Business Media http://www.springerlink.com/

Available from: 2009-04-21 Created: 2009-04-21 Last updated: 2014-08-21Bibliographically approved
3. Integrating automatic and interactive method for coronary artery segmentation: let PACS workstation think ahead
Open this publication in new window or tab >>Integrating automatic and interactive method for coronary artery segmentation: let PACS workstation think ahead
2010 (English)In: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, E-ISSN 1861-6429, Vol. 5, no 3, 275-285 p.Article in journal (Refereed) Published
Abstract [en]

Purpose: To provide an efficient method to extract useful information from the increasing amount of coronary CTA.

Methods: A quantitative coronary CTA analysis tool was built on OsiriX, which integrates both fully automatic and interactive methods for coronary artery extraction. The computational power of an ordinary PC is exploited by running the non-supervised coronary artery segmentation and centerline tracking in the background as soon as the images are received. When the user opens the data, the software provides a real-time interactive analysis environment.

Results: The average overlap between the centerline created in our software and the reference standard was 96.0%. The average distance between them was 0.38 mm. The automatic procedure runs for 3-5 min as a single-thread application in background. Interactive processing takes 3 min in average.

Conclusion: In preliminary experiments, the software achieved higher efficiency than the former interactive method, and reasonable accuracy compared to manual vessel extraction.

Keyword
Coronary CT angiography, automatic vessel extraction, vessel segmentation, centerline tracking
National Category
Radiology, Nuclear Medicine and Medical Imaging Cardiac and Cardiovascular Systems Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-17818 (URN)10.1007/s11548-009-0393-z (DOI)000289288800008 ()
Note

The original publication is available at www.springerlink.com: Chunliang Wang and Örjan Smedby, Integrating automatic and interactive method for coronary artery segmentation: let PACS workstation think ahead, 2011, International Journal of Computer Assisted Radiology and Surgery, (5), 3, 275-285. http://dx.doi.org/10.1007/s11548-009-0393-z Copyright: Springer Science Business Media http://www.springerlink.com/

Available from: 2009-04-21 Created: 2009-04-21 Last updated: 2014-09-24Bibliographically approved
4. Can segmented 3D images be used for stenosis evaluation in coronary CT angiography?
Open this publication in new window or tab >>Can segmented 3D images be used for stenosis evaluation in coronary CT angiography?
Show others...
2012 (English)In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, Vol. 53, no 8, 845-851 p.Article in journal (Refereed) Published
Abstract [en]

Purpose: To retrospectively evaluate the diagnostic accuracy of coronary CT angiography (CCTA) using segmented 3D data for the detection of significant stenoses with catheter angiography (CA) as the reference standard.

Method: CCTA data sets from 30 patients were acquired with a 64-slice dual source CT scanner and segmented by an independent observer using the region growing (RG) method and the “virtual contrast injection” (VC) method. For every examination, each of the three types of images was  then reviewed by one of three reviewers in a blinded fashion for the presence of stenoses with diameter reduction of 50% or more. For the original series, the reviewer was allowed to use all the 2D or 3D visualization tools available (mixed method). For the segmented results (from RG and VC), the reviewer only used the 3D maximum intensity projection. Evaluation results were compared with CA for each artery.

Results: Overall, 34 arteries with significant stenosis were identified by CA. The percentage of evaluable arteries, accuracy and negative predictive value (NPV) for detecting stenosis were, respectively, 86%, 74% and 93% for the mixed 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 mixed method (p = 0.22). Excluding vessels with heavy calcification, all three methods had similar accuracy.

Conclusion: Diagnostic accuracy when using segmented 3D data was lower than with access to 2D images. However, the high NPV of the 3D methods suggests a potential of using them as an initial step, with access to 2D reviewing techniques for suspected lesions and cases with heavy calcification. The VC method, which generates more evaluable arteries and has higher accuracy, seems more promising for this purpose than the RG method.

Place, publisher, year, edition, pages
Informa Healthcare, 2012
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:liu:diva-68794 (URN)10.1258/ar.2012.120053 (DOI)000310820000004 ()
Available from: 2011-06-07 Created: 2011-06-07 Last updated: 2013-10-21Bibliographically approved
5. Level-set based vessel segmentation accelerated with periodic monotonic speed function
Open this publication in new window or tab >>Level-set based vessel segmentation accelerated with periodic monotonic speed function
2011 (English)In: Medical Imaging 2011: Image Processing / [ed] Benoit M. Dawant, David R. Haynor, SPIE - International Society for Optical Engineering, 2011, Vol. 7962, 79621M-1-79621M-7 p.Conference paper (Refereed)
Abstract [en]

To accelerate level-set based abdominal aorta segmentation on CTA data, we propose a periodic monotonic speed function, which allows segments of the contour to expand within one period and to shrink in the next period, i.e., coherent propagation. This strategy avoids the contour’s local wiggling behavior which often occurs during the propagating when certain points move faster than the neighbors, as the curvature force will move them backwards even though the whole neighborhood will eventually move forwards. Using coherent propagation, these faster points will, instead, stay in their places waiting for their neighbors to catch up. A period ends when all the expanding/shrinking segments can no longer expand/shrink, which means that they have reached the border of the vessel or stopped by the curvature force. Coherent propagation also allows us to implement a modified narrow band level set algorithm that prevents the endless computation in points that have reached the vessel border. As these points’ expanding/shrinking trend changes just after several iterations, the computation in the remaining iterations of one period can focus on the actually growing parts. Finally, a new convergence detection method is used to permanently stop updating the local level set function when the 0-level set is stationary in a voxel for several periods. The segmentation stops naturally when all points on the contour are stationary. In our preliminary experiments, significant speedup (about 10 times) was achieved on 3D data with almost no loss of segmentation accuracy.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2011
Series
, Progress in Biomedical Optics and Imaging, ISSN 1605-7422 ; Vol. 7962
Keyword
Level-set; image segmentation; monotonic speed function; coherent propagation; narrow band; sparse field
National Category
Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-68006 (URN)10.1117/12.876704 (DOI)000294154900056 ()9780819485045 (ISBN)
Conference
Medical imaging 2011 - Image Processing, Lake Buena Vista, Florida, USA, 14–16 February 2011
Note

Original Publication: Chunliang Wang, Hans Frimmel and Örjan Smedby, Level-set based vessel segmentation accelerated with periodic monotonic speed function, 2011, SPIE medical imaging 2011 Lake Buena Vista, Florida, USA. http://dx.doi.org/10.1117/12.876704 Copyright 2011 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

Available from: 2011-05-05 Created: 2011-05-05 Last updated: 2015-08-20Bibliographically approved

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