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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 18, Iss. 14 — Jul. 5, 2010
  • pp: 15267–15282

Data sets for the qualification of volumetric CT as a quantitative imaging biomarker in lung cancer

A. J. Buckler, L. H. Schwartz, N. Petrick, M. McNitt-Gray, B. Zhao, C. Fenimore, A. P. Reeves, P. D. Mozley, and R. S. Avila  »View Author Affiliations


Optics Express, Vol. 18, Issue 14, pp. 15267-15282 (2010)
http://dx.doi.org/10.1364/OE.18.015267


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Abstract

The drug development industry is faced with increasing costs and decreasing success rates. New ways to understand biology as well as the increasing interest in personalized treatments for smaller patient segments requires new capabilities for the rapid assessment of treatment responses. Deployment of qualified imaging biomarkers lags apparent technology capabilities. The lack of consensus methods and qualification evidence needed for large-scale multi-center trials, as well as the standardization that allows them, are widely acknowledged to be the limiting factors. The current fragmentation in imaging vendor offerings, coupled with the independent activities of individual biopharmaceutical companies and their contract research organizations (CROs), may stand in the way of the greater opportunity were these efforts to be drawn together. A preliminary report, “Volumetric CT: a potential biomarker of response,” of the Quantitative Imaging Biomarkers Alliance (QIBA) activity was presented at the Medical Imaging Continuum: Path Forward for Advancing the Uses of Medical Imaging in the Development of New Biopharmaceutical Products meeting of the Extended Pharmaceutical Research and Manufacturers of America (PhRMA) Imaging Group sponsored by the Drug Information Agency (DIA) in October 2008. The clinical context in Lung Cancer and a methodology for approaching the qualification of volumetric CT as a biomarker has since been reported [Acad. Radiol. 17, 100–106, 107–115 (2010)]. This report reviews the effort to collect and utilize publicly available data sets to provide a transparent environment in which to pursue the qualification activities in such a way as to allow independent peer review and verification of results. This article focuses specifically on our role as stewards of image sets for developing new tools.

© 2010 OSA

OCIS Codes
(110.2960) Imaging systems : Image analysis
(100.3008) Image processing : Image recognition, algorithms and filters

History
Original Manuscript: March 22, 2010
Revised Manuscript: June 11, 2010
Manuscript Accepted: June 11, 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
A. J. Buckler, L. H. Schwartz, N. Petrick, M. McNitt-Gray, B. Zhao, C. Fenimore, A. P. Reeves, P. D. Mozley, and R. S. Avila, "Data sets for the qualification of volumetric CT as a quantitative imaging biomarker in lung cancer," Opt. Express 18, 15267-15282 (2010)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-18-14-15267


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References

  1. 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]
  2. N. R. Bogot, E. A. Kazerooni, A. M. Kelly, L. E. Quint, B. Desjardins, and B. Nan, “Interobserver and intraobserver variability in the assessment of pulmonary nodule size on CT using film and computer display methods,” Acad. Radiol. 12(8), 948–956 (2005). [CrossRef] [PubMed]
  3. P. D. Mozley, L. H. Schwartz, C. Bendtsen, B. Zhao, N. Petrick, and A. J. Buckler, “Change in lung tumor volume as a biomarker of treatment response: A critical review of the evidence,” Ann. Oncol. (to be published). [PubMed]
  4. K. Marten, F. Auer, S. Schmidt, G. Kohl, E. J. Rummeny, and C. Engelke, “Inadequacy of manual measurements compared to automated CT volumetry in assessment of treatment response of pulmonary metastases using RECIST criteria,” Eur. Radiol. 16(4), 781–790 (2006). [CrossRef]
  5. J. J. Erasmus, G. W. Gladish, L. Broemeling, B. S. Sabloff, M. T. Truong, R. S. Herbst, and R. F. Munden, “Interobserver and intraobserver variability in measurement of non-small-cell carcinoma lung lesions: implications for assessment of tumor response,” J. Clin. Oncol. 21(13), 2574–2582 (2003). [CrossRef] [PubMed]
  6. J. E. Munzenrider, M. Pilepich, J. B. Rene-Ferrero, I. Tchakarova, and B. L. Carter, “Use of body scanner in radiotherapy treatment planning,” Cancer 40(1), 170–179 (1977). [CrossRef] [PubMed]
  7. J. M. Quivey, J. R. Castro, G. T. Chen, A. Moss, and W. M. Marks, “Computerized tomography in the quantitative assessment of tumour response,” Br. J. Cancer Suppl. 4, 30–34 (1980). [PubMed]
  8. C. G. Moertel and J. A. Hanley, “The effect of measuring error on the results of therapeutic trials in advanced cancer,” Cancer 38(1), 388–394 (1976). [CrossRef] [PubMed]
  9. M.-P. Revel, C. Lefort, A. Bissery, M. Bienvenu, L. Aycard, G. Chatellier, and G. Frija, “Pulmonary nodules: preliminary experience with three-dimensional evaluation,” Radiology 231(2), 459–466 (2004). [CrossRef] [PubMed]
  10. B. Zhao, L. H. Schwartz, C. S. Moskowitz, M. S. Ginsberg, N. A. Rizvi, and M. G. Kris, “Lung cancer: computerized quantification of tumor response--initial results,” Radiology 241(3), 892–898 (2006). [CrossRef] [PubMed]
  11. B. Zhao, G. R. Oxnard, P. Guo, et al., “A pilot study comparing computerized volume measurement with diameter measurement as an early biomarker of the biologic activity of EGFR targeted therapy,” IASLC 13th World Conference on Lung Cancer, July 31–August 4, 2009, San Francisco, California.
  12. L. Schwartz, S. Curran, R. Trocola, J. Randazzo, D. Ilson, D. Kelsen, and M. Shah, “Volumetric 3D CT analysis–an early predictor of response to therapy,” J. Clin. Oncol. 25(18S), 4576 (2007).
  13. N. Altorki, J. Heymach, M. Guarino, P. Lee, E. Felip, T. Bauer, S. Swann, D. Roychowdhury, L. H. Ottesen, and D. Yankelevitz, “Phase II study of pazopanib (GW786034) given preoperatively in stage I–II non-small cell lung cancer (NSCLC): a proof-of-concept study,” Ann. Oncol. 19(Supplement 8), 124 (2008).
  14. L. P. Clarke, R. D. Sriram, and L. B. Schilling, “Imaging as a biomarker: standards for change measurements in therapy workshop summary,” Acad. Radiol. 15(4), 501–530 (2008). [CrossRef] [PubMed]
  15. G. McLennan, L. P. Clarke, and R. J. Hohl, “Imaging as a biomarker for therapy response: cancer as a prototype for the creation of research resources,” Clin. Pharmacol. Ther. 84(4), 433–436 (2008). [CrossRef] [PubMed]
  16. S. G. Armato, C. R. Meyer, M. F. Mcnitt-Gray, G. McLennan, A. P. Reeves, B. Y. Croft, L. P. Clarke, and RIDER Research Group, “The Reference Image Database to Evaluate Response to therapy in lung cancer (RIDER) project: a resource for the development of change-analysis software,” Clin. Pharmacol. Ther. 84(4), 448–456 (2008). [CrossRef] [PubMed]
  17. N. Petrick, D. G. Brown, O. Suleiman, and K. J. Myers, “Imaging as a tumor biomarker in oncology drug trials for lung cancer: the FDA perspective,” Clin. Pharmacol. Ther. 84(4), 523–525 (2008). [CrossRef] [PubMed]
  18. M. M. Goodsitt, H.-P. Chan, T. W. Way, S. C. Larson, E. G. Christodoulou, and J. Kim, “Accuracy of the CT numbers of simulated lung nodules imaged with multi-detector CT scanners,” Med. Phys. 33(8), 3006–3017 (2006). [CrossRef] [PubMed]
  19. M. A. Gavrielides, L. M. Kinnard, K. J. Myers, J. Peregoy, W. F. Pritchard, R. Zeng, J. Esparza, J. Karanian, and N. Petrick, “A resource for the development of methodologies for lung nodule size estimation: database of thoracic CT scans of an anthropomorphic phantom,” Opt. Express 18(14), 15244–15255 (2010). [CrossRef] [PubMed]
  20. E. Nioutsikou, N. Richard, J. Symonds-Tayler, J. L. Bedford, and S. Webb, “Quantifying the effect of respiratory motion on lung tumour dosimetry with the aid of a breathing phantom with deforming lungs,” Phys. Med. Biol. 51, 3359–3374 (2006). [CrossRef] [PubMed]
  21. T. W. Way, H.-P. Chan, M. M. Goodsitt, B. Sahiner, L. M. Hadjiiski, C. Zhou, and A. Chughtai, “Effect of CT scanning parameters on volumetric measurements of pulmonary nodules by 3D active contour segmentation: a phantom study,” Phys. Med. Biol. 53(5), 1295–1312 (2008). [CrossRef] [PubMed]
  22. M. A. Gavrielides, L. M. Kinnard, K. J. Myers, and N. Petrick, “Noncalcified lung nodules: volumetric assessment with thoracic CT,” Radiology 251(1), 26–37 (2009). [CrossRef] [PubMed]
  23. M. A. Gavrielides, R. Zeng, L. M. Kinnard, K. J. Myers, and N. Petrick, “A template-based approach for the analysis of lung nodules in a volumetric CT phantom study,” Proc. SPIE 7260, 726009–726011 (2009). [CrossRef]
  24. M. F. McNitt-Gray, L. M. Bidaut, S. G. Armato, C. R. Meyer, M. A. Gavrielides, C. Fenimore, G. McLennan, N. Petrick, B. Zhao, A. P. Reeves, R. Beichel, H. J. Kim, and L. Kinnard, “Computed tomography assessment of response to therapy: tumor volume change measurement, truth data, and error,” Transl. Oncol. 2(4), 216–222 (2009). [PubMed]
  25. C. R. Meyer, S. G. Armato, C. P. Fenimore, G. McLennan, L. M. Bidaut, D. P. Barboriak, M. A. Gavrielides, E. F. Jackson, M. F. McNitt-Gray, P. E. Kinahan, N. Petrick, and B. Zhao, “Quantitative imaging to assess tumor response to therapy: common themes of measurement, truth data, and error sources,” Transl. Oncol. 2(4), 198–210 (2009). [PubMed]
  26. B. Zhao, L. P. James, C. S. Moskowitz, P. Guo, M. S. Ginsberg, R. A. Lefkowitz, Y. Qin, G. J. Riely, M. G. Kris, and L. H. Schwartz, “Evaluating variability in tumor measurements from same-day repeat CT scans of patients with non-small cell lung cancer,” Radiology 252(1), 263–272 (2009). [CrossRef] [PubMed]
  27. A. P. Reeves, A. M. Biancardi, D. Yankelevitz, S. Fotin, B. M. Keller, A. Jirapatnakul, and J. Lee, “A public image database to support research in computer aided diagnosis,” in 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Sept. 2009, pp. 3715–3718.
  28. http://www.via.cornell.edu/databases/crpf.html.
  29. http://www.grand-challenge.org/index.php/MICCAI_2010_Workshop.
  30. https://wiki.nci.nih.gov/display/Imaging/Algorithm+Validation+Toolkit+(AVT).
  31. http://www.itl.nist.gov/iad/894.05/biochange2008/Biochange2008-webpage.htm.
  32. A. P. Reeves, A. C. Jirapatnakul, A. M. Biancardi, et al., “The VOLCANO'09 challenge: preliminary results,” in Second International Workshop of Pulmonary Image Analysis, Sept. 2009, pp. 353–364.
  33. http://preventcancer.org/.
  34. A. P. Reeves, A. M. Biancardi, T. V. Apanasovich, C. R. Meyer, H. MacMahon, E. J. van Beek, E. A. Kazerooni, D. Yankelevitz, M. F. McNitt-Gray, G. McLennan, S. G. Armato, C. I. Henschke, D. R. Aberle, B. Y. Croft, and L. P. Clarke, “The Lung Image Database Consortium (LIDC): a comparison of different size metrics for pulmonary nodule measurements,” Acad. Radiol. 14(12), 1475–1485 (2007). [CrossRef] [PubMed]
  35. http://www.via.cornell.edu/volcaman/ Draft version of the VOLCAMAN study.
  36. http://qibawiki.rsna.org/index.php?title=Volumetric_CT.

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