An open-source toolkit for the volumetric measurement of CT lung lesions

doi:10.1364/OE.18.015256

An open-source toolkit for the volumetric measurement of CT lung lesions

Karthik Krishnan, Luis Ibanez, Wesley D. Turner, Julien Jomier, and Ricardo S. Avila »View Author Affiliations

Optics Express, Vol. 18, Issue 14, pp. 15256-15266 (2010)
http://dx.doi.org/10.1364/OE.18.015256

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Abstract
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Abstract

An open source lesion sizing toolkit has been developed with a general architecture for implementing lesion segmentation algorithms and a reference algorithm for segmenting solid and part-solid lesions from lung CT scans. The CT lung lesion segmentation algorithm detects four three-dimensional features corresponding to the lung wall, vasculature, lesion boundary edges, and low density background lung parenchyma. These features form boundaries and propagation zones that guide the evolution of a subsequent level set algorithm. User input is used to determine an initial seed point for the level set and users may also define a region of interest around the lesion. The methods are validated against 18 nodules using CT scans of an anthropomorphic thorax phantom simulating lung anatomy. The scans were acquired under differing scanner parameters to characterize algorithm behavior under varying acquisition protocols. We also validated repeatability using six clinical cases in which the patient was rescanned on the same day (zero volume change). The source code, data sets, and a running application are all provided under an unrestrictive license to encourage reproducibility and foster scientific exchange.

OCIS Codes
(100.6890) Image processing : Three-dimensional image processing
(110.2960) Imaging systems : Image analysis

History
Original Manuscript: January 20, 2010
Revised Manuscript: June 28, 2010
Manuscript Accepted: June 30, 2010
Published: July 2, 2010

Virtual Issues
Vol. 5, Iss. 11 Virtual Journal for Biomedical Optics
Imaging in Diagnosis and Treatment of Lung Cancer (2010) Optics Express

Citation
Karthik Krishnan, Luis Ibanez, Wesley D. Turner, Julien Jomier, and Ricardo S. Avila, "An open-source toolkit for the volumetric measurement of CT lung lesions," Opt. Express 18, 15256-15266 (2010)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-18-14-15256

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References

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P. Therasse, S. G. Arbuck, E. A. Eisenhauer, J. Wanders, R. S. Kaplan, L. Rubinstein, J. Verweij, M. Van Glabbeke, A. T. van Oosterom, M. C. Christian, and S. G. Gwyther, “New guidelines to evaluate the response to treatment in solid tumors,” J. Natl. Cancer Inst. 92(3), 205–216 (2000). [CrossRef] [PubMed]
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Lesion sizing toolkit, http://public.kitware.com/LesionSizingKit
K. Krishnan, L. Ibanez, W. D. Turner, and R. S. Avila, “Algorithms, architecture, validation of an open source toolkit for segmenting CT lung lesions,” in Proc. MICCAI Workshop on Pulmonary Image Analysis (Sept. 2009), pp. 365–375.
L. Ibanez, W. Schroeder, L. Ng, J. Cates, and ITK Software Guide, Kitware Inc.
W. Schroeder, K. Martin, and W. Lorensen, Visualization Toolkit, Kitware Inc.
M. Descoteaux, M. Audette, K. Chinzei, and K. Siddiqi, “Bone enhancement filtering: Application to sinus bone segmentation and simulation of pituitary surgery,” in MICCAI (2005), pp. 9–16.
Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998). [CrossRef]
A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever, “Multiscale vessel enhancement filtering,” Lect. Notes Comput. Sci. 1496, 130–137 (1998). [CrossRef]
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J. A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge Press (1999).
R. Malladi, J. A. Sethian, and B. C. Vemuri, “Shape modeling with front propagation: A level set approach,” IEEE Trans. Pattern Anal. Mach. Intell. 17(2), 158–175 (1995). [CrossRef]
V. Caselles, R. Kimmel, and G. Sapiro, “Geodesic active contours,” Int. J. Comput. Vis. 22(1), 61–79 (1997). [CrossRef]
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M. A. Gavrielides, R. Zeng, L. M. Kinnard, K. J. Myers, and N. A. Petrick, “A matched filter approach for the analysis of lung nodules in a volumetric CT phantom study,” in Proc. SPIE Med. Imaging (Feb. 2009).
M. A. Gavrielides, L. Kinnard, S. Park, I. Kyprianou, B. Gallas, A. Badano, N. Petrick, and K. J. Myers, “Quantitative in silico imaging and biomarker assessment using physical and computational phantoms: a review of new tools and methods available from the NIBIB/CDRH joint Laboratory for the Assessment of Medical Imaging Systems,” in Radiology (2008).
The Optical Society of America, The National Library of Medicine, Kitware Inc, Interactive Science Publishing: http://www.opticsinfobase.org/isp.cfm
Kitware Inc, VolView, http://www.kitware.com/VolView

Alyassin, A. M.
Arbuck, S.
Arbuck, S. G.
Atsumi, H.
Bogaerts, J.
Canny, J. F.
Caselles, V.
Christian, M. C.
Cline, H. E.
Dancey, J.
Dodd, L.
Downs, J. H.
Eisenhauer, E. A.
Eisenhauer, E.A.
Ford, R.
Fox, P. T.
Frangi, A. F.
Gerig, G.
Gwyther, S.
Gwyther, S. G.
Hunter, R. D.
Kaplan, R.
Kaplan, R. S.
Kikinis, R.
Kimmel, R.
Koller, T.
Lacombe, D.
Lancaster, J. L.
Lorensen, W. E.
Malladi, R.
Mooney, M.
Nakajima, S.
Niessen, W. J.
Rubinstein, L.
Sapiro, G.
Sargent, D.
Sato, Y.
Schwartz, L.H.
Sethian, J. A.
Shankar, L.
Shiraga, N.
Therasse, P.
Van Glabbeke, M.
van Oosterom, A. T.
Vemuri, B. C.
Verweij, J.
Viergever, M. A.
Vincken, K. L.
Wanders, J.
Yoshida, S.

ACM SIGGRAPH Comput. Graph.

W. E. Lorensen and H. E. Cline, “Marching cubes: A high resolution 3D surface construction algorithm,” ACM SIGGRAPH Comput. Graph. 21(4), 163–169 (1987). [CrossRef]

Eur. J. Cancer

E.A. Eisenhauer, P. Therasse, J. Bogaerts, L.H. Schwartz, D. Sargent, R. Ford, J. Dancey, S. Arbuck, S. Gwyther, M. Mooney, L. Rubinstein, L. Shankar, L. Dodd, R. Kaplan, D. Lacombe, and J. Verweij, “New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1),” Eur. J. Cancer 45(2), 228–247 (2009). [CrossRef]

IEEE Trans. Pattern Anal. Mach. Intell.

J. F. Canny, “A computational approach to edge detection,” IEEE Trans. Pattern Anal. Mach. Intell. 8(6), 679–698 (1986). [CrossRef] [PubMed]
R. Malladi, J. A. Sethian, and B. C. Vemuri, “Shape modeling with front propagation: A level set approach,” IEEE Trans. Pattern Anal. Mach. Intell. 17(2), 158–175 (1995). [CrossRef]

Int. J. Comput. Vis.

V. Caselles, R. Kimmel, and G. Sapiro, “Geodesic active contours,” Int. J. Comput. Vis. 22(1), 61–79 (1997). [CrossRef]

Int. J. Radiat. Biol.

R. D. Hunter, “WHO Handbook for Reporting Results of Cancer Treatment,” Int. J. Radiat. Biol. 38(4), 481 (1980), doi:. [CrossRef]

J. Natl. Cancer Inst.

P. Therasse, S. G. Arbuck, E. A. Eisenhauer, J. Wanders, R. S. Kaplan, L. Rubinstein, J. Verweij, M. Van Glabbeke, A. T. van Oosterom, M. C. Christian, and S. G. Gwyther, “New guidelines to evaluate the response to treatment in solid tumors,” J. Natl. Cancer Inst. 92(3), 205–216 (2000). [CrossRef] [PubMed]

Lect. Notes Comput. Sci.

A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever, “Multiscale vessel enhancement filtering,” Lect. Notes Comput. Sci. 1496, 130–137 (1998). [CrossRef]

Med. Image Anal.

Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kikinis, “Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images,” Med. Image Anal. 2(2), 143–168 (1998). [CrossRef]

Med. Phys.

A. M. Alyassin, J. L. Lancaster, J. H. Downs, and P. T. Fox, “Evaluation of new algorithms for the interactive measurement of surface area and volume,” Med. Phys. 21(6), 741–752 (1994). [CrossRef] [PubMed]

Other

M. A. Gavrielides, R. Zeng, L. M. Kinnard, K. J. Myers, and N. A. Petrick, “A matched filter approach for the analysis of lung nodules in a volumetric CT phantom study,” in Proc. SPIE Med. Imaging (Feb. 2009).
M. A. Gavrielides, L. Kinnard, S. Park, I. Kyprianou, B. Gallas, A. Badano, N. Petrick, and K. J. Myers, “Quantitative in silico imaging and biomarker assessment using physical and computational phantoms: a review of new tools and methods available from the NIBIB/CDRH joint Laboratory for the Assessment of Medical Imaging Systems,” in Radiology (2008).
The Optical Society of America, The National Library of Medicine, Kitware Inc, Interactive Science Publishing: http://www.opticsinfobase.org/isp.cfm
Kitware Inc, VolView, http://www.kitware.com/VolView
J. A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge Press (1999).
Lesion sizing toolkit, http://public.kitware.com/LesionSizingKit
K. Krishnan, L. Ibanez, W. D. Turner, and R. S. Avila, “Algorithms, architecture, validation of an open source toolkit for segmenting CT lung lesions,” in Proc. MICCAI Workshop on Pulmonary Image Analysis (Sept. 2009), pp. 365–375.
L. Ibanez, W. Schroeder, L. Ng, J. Cates, and ITK Software Guide, Kitware Inc.
W. Schroeder, K. Martin, and W. Lorensen, Visualization Toolkit, Kitware Inc.
M. Descoteaux, M. Audette, K. Chinzei, and K. Siddiqi, “Bone enhancement filtering: Application to sinus bone segmentation and simulation of pituitary surgery,” in MICCAI (2005), pp. 9–16.

2009, Eisenhauer, Eur. J. Cancer
2000, Therasse, J. Natl. Cancer Inst.
1998, Sato, Med. Image Anal.
1998, Frangi, Lect. Notes Comput. Sci.
1997, Caselles, Int. J. Comput. Vis.
1995, Malladi, IEEE Trans. Pattern Anal. Mach. Intell.
1994, Alyassin, Med. Phys.
1987, Lorensen, ACM SIGGRAPH Comput. Graph.
1986, Canny, IEEE Trans. Pattern Anal. Mach. Intell.
1980, Hunter, Int. J. Radiat. Biol.

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